Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: For the GCN with mutual information as input, firstly, the corpus is used as the data set to calculate the mutual information value between words, the word is used as the node, the mutual information value between nodes is used as the representation of the edge. The element aij in its adjacency matrix AɛRN∗Nrepresents the mutual information value between the ith node and the jth node in the graph. For the GCN with dependency syntactic relation as input, firstly, the dependency syntax of sentences is analyzed, with words as nodes and the dependency between words as the representation of edges. The element aij in its adjacency matrix AɛRN∗Nrepresents the dependency between the ith node and the jth node in the graph. If there is a dependency between the two nodes, the aij is 1, otherwise it is 0. For example, in the example of dependency syntactic parsing “evaluations play an invaluable role in X. ”, the adjacency matrix A constructed based on dependency syntactic parsing is shown in Fig. 6. Figure 6: Adjacency matrix constructed based on dependency syntactic parsing. Download full-size image DOI: 10. 7717/peerjcs. 984/fig-6 In order to directly conduct deep learning modeling on graph data, the specific method adopts a variant model of convolution neural network-proposed by Kipf & Welling (2016), and the structure is shown in Fig. 7. The channels input by GCN is C, that is, the feature vector dimension of each node Xi is C, the channels output by GCN is F, that is, the feature vector dimension of each node Zi is F, and finally the label Yi of the node is predicted by the feature of the node. Figure 7: The structure diagram of GCN. Download full-size image DOI: 10. 7717/peerjcs. 984/fig-7 Specifically, given a graph G = (V, E), V is a vertex set containing N nodes, E is an edge set including self-loop edges (that is, each vertex is connected to itself). The feature information of graph G = (V, E)can be represented by Laplace matrix, as shown in Eq. (11). (11) L = D − A.

Output: pass


Input: Claim: Research is ongoing to use nanotechnology in regenerative medicine. [SEP] Text: Moodley and colleagues performed a xenograft implantation in which they injected human amnion epithelial cells parenterally into bleomycin-treated severe combined immunodeficiency (SCID) mice as pulmonary fibrosis model and demonstrated reduced inflammation and fibrosis [8]. The injected cells also developed an alveolar epithelial phenotype with lamellar body formation and expression of surfactants A and D. More interesting, Kajstura and coworkers recently identified stem cells from adult human lung tissue using the stem cell antigen marker c-kit [9]. After being administrated into an injured mouse lung, the cells demonstrated pluripotent capability of generating human bronchioles, alveoli, and pulmonary vessels within the damaged organ. Although some disputes exist on tissue-specific adult human lung stem cells in Kajstura study [10, 11], these evidences collectively suggest that isolated adult lung stem cells are potentially of great clinical importance for cell-based therapies in pulmonary diseases. This review will briefly highlight the recent progresses on mouse lung stem cell research and its applications in some clinical trials for specific lung diseases such as IPF and COPD. We will mainly discuss the endogenous lung stem cells named as epithelial stem/progenitor cells (EpiSPCs) in different anatomic locations, mesenchymal stem cells (MSCs), and endothelial progenitor cells (EPCs). In addition, we will briefly discuss novel bioengineering approaches to generate implantable lung tissues or organs ex vivo and in vivo. Stem cells from different origins may be repopulated into the decellularized or bioengineered scaffold to create new functional organs. Lung stem cells: classification, origin, biomarkers, and functionRecent studies mainly in mice have identified several adult stem cell lines in distinct anatomic locations of lung [12–14]. There might be some equivocal terms to define each cell line. In general, these diverse cell lines can be called lung endogenous stem/progenitor cells. According to the ability to differentiate, all stem cells can be categorized into 5 groups: totipotent, pluripotent, multipotent, oligopotent and unipotent [15]. Most lung endogenous stem/progenitor cells belong to multipotent or oligopotent cells. Alveolar epithelial cells (AECs) type II are unipotent since they only differentiate into type I cells [16].

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Jul 2020;108:106332. [CrossRef]. Taking a break from social media improves wellbeing through sleep quality. Soc Netw. Jun 2021;24(6):421-425. [CrossRef] [Medline]. No more FOMO: limiting social media decreases loneliness and depression. J Psychol. Dec 2018;37(10):751-768. [CrossRef]. Too much of a good thing: who we follow, what we do, and how much time we spend on social media affects well-being. J Psychol. Feb 2021;40(1):46-68. [FREE Full text] [CrossRef]. The effects of reducing social media use on body esteem among transitional-aged youth. J Psychol. Dec 2021;40(6):481-507. [CrossRef]. A short scale for measuring loneliness in large surveys: results from two population-based studies. Res Aging. 2004;26(6):655-672. [FREE Full text] [CrossRef] [Medline]. Therapy. StatIsland. (FL). StatPearls Publishing; 2022. URL: [accessed 2022-08-13]. Concerns about Facebook among users and abstainers: relationships with individual differences and Facebook use. Psychol Sci. 2016;2(3):261-274. [FREE Full text] [CrossRef]Rideout V, Fox S. Digital health practices, social media use, and mental well-being among teens and young adults in the U. S. HopeLab. 2018. URL: [accessed 2022-08-13]. Social media and mental health challenges. J. Jul 2019;28(2):155-159. [FREE Full text] [CrossRef] [Medline]Escobar- For better or for worse? A systematic review of the evidence on social media use and depression among lesbian, gay, and bisexual minorities. . Jul 23, 2018;5(3):e10496. [FREE Full text] [CrossRef] [Medline]Du J, Kerkhof P, van Koningsbruggen GM. The reciprocal relationships between social media self-control failure, mindfulness and wellbeing: a longitudinal study. PLoS One. Aug 04, 2021;16(8):e0255648. [FREE Full text] [CrossRef] [Medline].

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: Or use the symmetric normalized Laplasse matrix, as shown in Eq. (12): (12) L s y s = I N − D − 1 2 A D − 1 2. where A is the adjacency matrix of the graph, IN is the n-order identity matrix; D = diag(d) is the degree matrix of the vertex, as shown in Eq. (13). (13) D i i = ∑ j A i j. Based on the Fourier transform of graph, the graph convolution formula can be expressed as Eq. (14): (14) g ∗ x = U U T g ⋅ U T x. In the formula, x is the basic feature vector of the node; g is convolution kernel; U is the eigenvector matrix of Laplace matrix L. In order to reduce the amount of calculation, scholars used Chebyshev polynomials to simplify the graph convolution formula in 2017. Finally, the layered propagation formula of graph convolution can be expressed as Eq. (15): (15) X l + 1 = σ D ̃ − 1 2 A ̃ D ̃ − 1 2 X l W l. In the formula, A ̃ = A + I N D ̃ = ∑ A ̃ σ is the activation function; W is the weight matrix to be trained. Label representation module Field (CRF) is a statistical-based learning model first proposed by Lafferty, McCallum & Pereira (2001). Through the calculation and statistics of known features, the conditional probability of unknown features can be inferred. Based on the maximum entropy model and hidden Markov model, this model is mainly used for sequence tagging. It has achieved good recognition results in named entity recognition, syntactic analysis and part-of-speech tagging in the field of natural language processing. In the model of this 8. Among them, the input observation sequence is represented by X, and X is used as a precondition. P(y|x) is defined as a joint probability distribution, and the maximum value among them is selected as the corresponding sequence label (Ren, Zhang & Zhang, 2019). Figure 8: The structure diagram of linear-chain CRF. Download full-size image DOI: 10. 7717/peerjcs.

Output: pass


Input: Claim: Research is ongoing to use nanotechnology in regenerative medicine. [SEP] Text: These tissue injury signaling systems would have injury location and potency specificity; helping the repair mechanism recognize the site of the injured organ. They would also share a common pathway for mobilizing the common repair mechanism such as the mobilization of bone marrow cells. The communication between the site of injury and the mobilized repairing materials requires an ensured transportation, vascular and/or lymph system. A damage to any of these signaling, communication, and transportation systems would result in suppression of the self-repair of the injured organ. Rejuvenation of the self-repair mechanism in the elder or under the chronic injury condition would provide an alternative approach to regenerative medicine. This approach, in contrast to the exogenously prepared repair materials, focuses on mobilization of the self-directed and active rather than passive repair of the injured organ. In this context, the rejuvenation would involve identification and renewal of the tissue injury signaling molecules or pathways. The signaling molecules require a well-connected network, which is different from the intracellular signaling transduction system and demands well-maintained vascular and/or lymph transportation systems. The recruitment of the repair mechanism such as bone marrow cells, and the regeneration of the failed organ are fundamental processes responsible for the effective self-repair. The repair of the structural injury only becomes meaningful if the recovery of the physiological function occurs. Therefore, rehabilitation of the renewed organ is required for the eventual regeneration. In this commentary, we will consolidate evidence that shows the possibility of rejuvenation of the self-repair mechanism in the elder or under the chronic injury condition, and discuss the elements that are required for the rejuvenation. If rejuvenation of the self-repair or self-renewal mechanism can be developed, an alternative, if not a better, achievement of the regenerative medicine would be expected. Renewal of the tissue injury signalingThe tissue injury signaling system should exist in the mammalian system, which would be an active and rescue-requiring signaling system generated from the site of the injured organ and transduced to communicate with the remote repair mechanism. This signaling system is different from that operates in the cell, which is a passive response to the trigger outside of the cell and is generated from the cell membrane, transducing to the inside of the cell. The tissue injury signaling system would ensure the rescue to take place when an injury occurs in any organ in the body. A good example of this system would be the immune response to an injury to an organ.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: The influence of personality, parental behaviors, and self-esteem on Internet addiction: a study of Chinese college students. Soc Netw. Feb 2014;17(2):104-110. [FREE Full text] [CrossRef] [Medline]. Social media and mental health: benefits, risks, and opportunities for research and practice. J Sci. Sep 2020;5(3):245-257. [FREE Full text] [CrossRef] [Medline]. Digital resilience mediates healthy use of technology. J. Dec 2022;90(4):195-199. [CrossRef] [Medline]Orben A, Przybylski AK. The association between adolescent well-being and digital technology use. Behav. Feb 2019;3(2):173-182. [CrossRef] [Medline]Çimke S, Cerit E. Social media addiction, cyberbullying and cyber victimization of university students. Nurs. Oct 2021;35(5):499-503. [CrossRef] [Medline]. Reasons or excuses for avoiding meta-analysis in forest plots. BMJ. Jun 21, 2008;336(7658):1413-1415. [FREE Full text] [CrossRef] [Medline]Escobar- Passive and active social media use and depressive symptoms among adults. Soc Netw. Jul 2018;21(7):437-443. [CrossRef] [Medline]. Adolescent social media user types and their mental health and well-being: results from a longitudinal survey of 13-14-year-olds in the United Kingdom. JCPP Adv. Mar 10, 2022;2(2):e12071. [CrossRef] [Medline]Verduyn P, Ybarra O, Résibois M, Jonides J, Kross E. Do social network sites enhance or undermine subjective well-being? A critical review. Policy Rev. Jan 13, 2017;11(1):274-302. [FREE Full text] [CrossRef]Valkenburg PM, van Driel II, Beyens I. The associations of active and passive social media use with well-being: A critical scoping review. Soc. Dec 31, 2021;24(2):530-549.

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: 984/fig-8 order to recognize formulaic language in the text more accurately, this 64. During model training, Adam optimizer is selected as the optimization algorithm, the learning rate is set to 0. 001, and the decay ratio is set to 0. 9. Ablation experiment In order to better verify the effect of formulaic language identification model based on GCN fusing associated information, seven comparative experiments were conducted to determine which feature is more important for formulaic language identification by setting ablation experiments. The specific methods are as follows: Before_Bi-LSTM: The part-of-speech features generated by PyTorch word embedding and the semantic features generated by GloVe word embedding are fused by early fusion. The fused feature vector is input into Bi-LSTM to extract the context semantic relationship. Finally, the features generated by Bi-LSTM are input into CRF to complete the recognition of formulaic language. Before_CNN: The part-of-speech features generated by PyTorch word embedding and the semantic features generated by GloVe word embedding are fused by early fusion. The fused feature vector is input into CNN. The size of convolution kernel is 3 * 3, and a total of two layers of CNN are set. Finally, the features generated by CNN are input into CRF to complete the recognition of formulaic language. After_Bi-LSTM: The part-of-speech features generated by PyTorch word embedding and the semantic features generated by GloVe word embedding are fused by late fusion. That is, the two feature vectors are input into Bi-LSTM respectively, and then the processed vectors are fused. Finally, the fused features are input into CRF to complete the recognition of formulaic language. After_Bi-LSTM_CNN: Based on After_Bi-LSTM, this method adds a layer of CNN between Bi-LSTM and CRF. The size of convolution kernel is 3 * 3, and a total of two layers of CNN are set. Bi-LSTM_DS_GCN: The part-of-speech features generated by PyTorch word embedding and the semantic features generated by GloVe word embedding are fused by late fusion.

Output: pass


Input: Claim: Research is ongoing to use nanotechnology in regenerative medicine. [SEP] Text: Some efforts have focused on bone marrow stem cells in an attempt to treat multiple organ failures and to promote regeneration. On average, bone marrow constitutes 4% of the total body mass of humans; the hematopoietic compartment of bone marrow produces approximately 500 billion blood cells per day, which use the bone marrow vasculature as a conduit to the body's systemic circulation [55]. Bone marrow is also a key component of the lymphatic system, producing lymphocytes that support the body's immune system [56]. Besides these routine activities of bone marrow, the recruitment of bone marrow stem cells in response to tissue injury was one of the major topics of current undertaking of regenerative medicine [49, 50]. Progenitor cells have been considered as a major source of tissue repair or regeneration in response to tissue injury [57, 58]. A progenitor cell, like a stem cell, has a tendency to differentiate into a specific type of cell, but is already more specific than a stem cell and is pushed to differentiate into its "target" cell. The most important difference between stem cells and progenitor cells is that stem cells can replicate indefinitely, whereas progenitor cells can divide only a limited number of times. Most progenitor cells are described as oligopotent [59, 60]. Therefore, they may be compared to adult stem cells. But progenitor cells are said to be in a further stage of cell differentiation. They are in the “center” between stem cells and fully differentiated cells. The kind of potency they have depends on the type of their "parent" stem cells and also on their niche. Some progenitor cells were found to move through the body and migrate towards the tissue where they are needed. In this context, many properties of adult stem cells are shared by progenitor cells [61]. However, the adult stem cells are quite different from embryonic stem cells that are true stem cells; they are pluripotent and show unlimited capacity for self-renewal. In contrast, it has not been comprehensively demonstrated for the adult stem cells of their capacities for unlimited self-renewal and plasticity [62]. Progenitor cells are found in adult organisms and they act as a repair system for the body. They replenish specialized cells, but also maintain the blood, skin and intestinal tissues [63–66].

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Introduction: “Good for People, Good for Society”In the wake of the scandal that broke in early 2018 (Cadwalladr & Graham-Harrison, 2018), whereby the data of millions of Facebook users were sold to a private political consultancy firm without explicit informed consent, faced questions during two sessions in front the US Senate and Congress concerning its business practices and social values. During his Senate hearing, Zuckerberg was asked to comment on recent reports linking Facebook usage with mental health issues such as addiction and depression. Such issues are common themes of contemporary Western mass media coverage of Facebook (Busby, 2018; Carey, 2019; O’Neil, 2019), and are explored in psychological studies that associate increased Facebook usage with decreased subjective well-being (Kross et al. , 2013), higher levels of depression (Feinstein et al. , 2013), and increased envy in users (Appel et al. , 2016). Moreover, (2011) argues that individuals who spend extensive periods online can become isolated within their immediate communities, while (2017) links the rising levels of anxiety in teenagers to increased social media usage and reliance on the smartphone. Adding to this, Facebook’s former vice-president of user growth had recently criticized the “dopamine-driven feedback loops” of Facebook’s liking system in a speech at School (Wong, 2017), and early investor Roger McNamee (2017), in an online 2018. Moreover, choosing to adopt either of these two modes of activity is implicitly presented as better or worse user decision, respectively, with this binary being presented in terms of health. However, as the philosopher of well-being (2001) argues:to determine what is goodness and defect of character, disposition, and choice, we must consider what human good is and how human beings live: in other words, what kind of living thing a human being is. (p. 51)Thus, the claims of “healthy” modes of usership expressed by Facebook’s representatives are normative in the sense that they establish behaviors that can be said to benefit the human subject on Facebook, while determining other forms of activity as deleterious. will show below, Facebook constructs this model of health in direct relation to findings from their research into social psychology and HCI.

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: The fused feature vector is used as the basic feature and the matrix generated by dependency syntactic relation is used as the associated feature, which are input into GCN for feature representation. Finally, the features generated by GCN are input into CRF to complete the recognition of formulaic language. Bi-LSTM_MI_GCN: The difference from Bi-LSTM_DS_GCN is that the matrix generated by dependency syntactic relation is replaced with the matrix generated by the mutual information between words as the associated feature. Bi-LSTM_MI_DS_GCN: This is the model proposed in this 9. 2, train_time represents the time required to train 100 pieces of data, and test_time represents the time required to test 100 pieces of data. Analysis of experimental results: (1) The difference between Experiment 1 and Experiment 2 lies in the comparison between Bi-LSTM and CNN. The experimental results show that Bi-LSTM is much better than CNN in feature extraction. Because the identification of formulaic language is a typical sequence labeling problem, Bi-LSTM can capture the long-distance and long-term dependence of sentence context information and can capture the two-way information of sentences. However, CNN cannot capture the long-distance dependence information well, so it is better to use Bi-LSTM in formulaic language recognition. It is worth noting that the Recall in the result of using CNN to extract features is relatively high, indicating that it can recognize more formulaic languages. However, it can also recognize many non-formulaic languages, so the Precision is not very high. Table 2: Comparison of experimental results of ablation experiment. F1-score Train_time Test_time 1 Before_Bi-LSTM 62. 12 81. 46 70. 49 9. 40775 3. 83115 2 Before_CNN 34. 23 50. 33 40. 75 11. 24228 5. 06429 3 After_Bi-LSTM 77. 08 73. 51 75. 25 11. 96498 5. 16604 4 After_Bi-LSTM_CNN 72. 46 66. 23 69. 20 22. 86475 8. 34037 5 Bi-LSTM_DS_GCN 65. 22 69. 54 67. 31 12. 20419 4. 36681 6 Bi-LSTM_MI_GCN 74.

Output: pass


Input: Claim: Research is ongoing to use nanotechnology in regenerative medicine. [SEP] Text: This process involves both local responses and the recruitment of remote repair mechanisms. This repair process leads to different results between human adults and early stage of life. In human adults, a non-functioning mass of fibrotic tissue known as a scar is often observed at the completion of the repair process. By contrast, early in gestation, injured fetal tissues can be completely recreated without fibrosis, which is the process of regeneration. Regeneration means the regrowth of a damaged or missing organ part from the remaining tissue. Some organs retain high ability to regenerate throughout adult life, such as the liver. If part of the liver is lost by disease or injury, the liver grows back to its original size, though not necessarily to its original shape. However, many other organs are much less capable of regenerating in the adult life. A goal of regenerative medicine is to find and reactivate the missing elements or the suppressed process of regeneration in adult tissues, which exist early in gestation or remain in some organs in the adult life. Regenerative strategies include the rearrangement of pre-existing tissue, the use of progenitor cells and adult stem cells, and the dedifferentiation and/or transdifferentiation of cells. Dedifferentiation of cells means that they lose their tissue-specific characteristics as tissue remodels during the regeneration process. Transdifferentiation of cells is when they lose their tissue-specific characteristics during the regeneration process, and then re-differentiate to a different kind of cells. Multiple regulatory mechanisms operate in the regeneration process and distinguishingly function in one tissue type or the other. All these strategies result in the re-establishment of appropriate tissue polarity, structure, and form [13, 14, 41, 42, 73]. In a study understanding the process of kidney damage and regeneration, a molecular regenerative pathway was identified [74]. This pathway involves macrophages that respond to tissue injury by producing Wnt7b. The Wnt7b is important to the formation of kidney tissues during embryonic organ development. In the regeneration of injured kidneys, macrophages, by migrating to the injured kidney and producing Wnt7b, re-establish an early molecular program operating in the organ development that becomes beneficial to tissue regeneration. Wnt7b belongs to Wnt family of proteins, which regulate cell growth, proliferation and differentiation [75, 76].

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: It is upon these quasi-psychological foundations (Rose, 1998) that Facebook feels authorized to construct, and recommend, a particular version of human sociality within which its services can be understood as valuable, and indeed, necessary for its users’ well-being. For the philosopher of biological science (1991), writing in the early 20th century, however, the definition of healthy human states in Western discourses of medicine constitute “an attachment to some value,” as opposed to a “disposition which can be revealed and explained as a fact” (p. 57). Canguilhem (1991) suggests that “the concept of health is not one of an existence, but of a norm whose function and value is to be brought into contact with existence in order to stimulate modification” (p. 87). In this way, health is not a stable concept existing in abstraction from the historical milieu of its enunciation, but can actually be viewed as a point around which human individuals can adjust their behavior in relation to certain categories of ideal normality. to be able to establish online activity that is “better” and “healthy” for humans, thus, a pre-existing model of normal human nature is necessary, and particular types of human existence need to be identified as valuable to the individual upon this basis. This process of determining valuable human activity is characteristic of eudaimonic accounts of well-being—the attempt to establish what it means to live well as a human in time (Aristotle, 2004; Raibley, 2013). There are two main threads of the psychological and philosophical study of well-being; hedonistic and eudaimonic accounts (Haybron, 2008; Kahneman et al. , 1999). Whereas hedonistic theories focus on human well-being in terms of pleasure attainment and pain avoidance (Parfit, 1984), the eudaimonic approach links well-being with a notion of human flourishing (Kraut, 2007). Eudaimonic well-being can be understood in terms of procedural self-fulfillment, meaningful existence, and well-functioning, with the psychologists Ryan and Deci (2008) describing eudaimonic psychology as concentrating on “the content of one’s life, and the processes involved in living well” (p. 140).

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: 19 76. 16 75. 16 11. 19024 3. 63964 7 Bi-LSTM_MI_DS_GCN 81. 71 85. 37 83. 50 13. 55199 5. 35704 DOI: 10. 7717/peerjcs. 984/table-2 Figure 9: Comparison of experimental results of ablation experiment. Download full-size image DOI: 10. 7717/peerjcs. 984/fig-9 (2) The difference between Experiment 1 and Experiment 3 is that the way of feature fusion is different. Experiment 1 adopts early fusion and Experiment 3 adopts late fusion. The experimental results show that the late fusion method has higher Precision and the early fusion method has higher Recall. The main reason is that the early fusion method can recognize more results when recognizing formulaic languages, but it can also recognize many non-formulaic languages, so its Precision is low. The features of the late fusion method are more accurate, and the recognition results are not as much as those of the early fusion, but the formulaic languages can be recognized more accurately. According to the F1-scores of the two methods, the effect of late fusion is better than that of early fusion. (3) Experiment 4 adds CNN layer based on Experiment 3, but the results after adding CNN are not as good as the previous results. The main reason is that CNN captures local correlations and each layer of CNN has a fixed span. Naturally, this layer can only model limited distance information. 4, Bi-LSTM has obtained the long-distance dependency of the context, and then CNN is added after Bi-LSTM to deeply abstract the features, some correct formulaic languages are filtered out, resulting in a significant decline in Precision and Recall. (4) Experiment 5 adds feature extraction based on GCN fusing dependency syntactic parsing on the basis of Experiment 3. The experimental results showed that after adding dependency syntactic features, the Recall and Precision are reduced. Because dependency syntactic relation mainly focuses on the dependency between two words in a sentence, it is easy to cause that the extracted word string does not belong to formulaic language, so the recognition effect is not good. Experiment 6 adds feature extraction based on GCN fusing mutual information on the basis of Experiment 3.

Output: pass


Input: Claim: Research is ongoing to use nanotechnology in regenerative medicine. [SEP] Text: of : 2325-9620 Toggle navigation & & 1. doi:/10. 4172/2325-9620. 1000101 Nanotechnology to Epigenomics and The objective of regenerative medicine is to repair tissues and organs that are damaged by trauma, disease or aging. The stem cell based technologies have promised to advance therapeutic applications including organ transplants and tissue repair. Although more studies are now being conducted to reveal mechanisms regulating stem cell fate, epigenetic events that contribute to cell differentiation are still relatively poorly defined. Next generation sequencing combined with chromatin immunoprecipitation (ChIPseq) or bisulfite sequencing (BS-seq) is the most common tool to study histone modifications and DNA methylation. However, it requires an abundance of research material and has limited ability to detect different epigenetic signatures in the same cell type. The recent development of the single chromatin analysis at the nanoscale (SCAN) using the nanofluidic single-molecule sorter allows the simultaneous detection of multiple epigenetic marks in a small number of cells. Keywords: Nanotechnology; Nanofluidics; Epigenome; Chromatin; Chip-seq; Regenerative medicine; Next generation sequencing Keywords Nanotechnology; Nanofluidics; Epigenome; Chromatin; Chip-seq; Regenerative medicine; Next generation sequencing is a highly regulated process throughout the life cycle of an organism for maintaining or restoring the normal function of cells and tissues. Regenerative medicine deals with the processes of replacing or regenerating human tissues or organs to restore normal function [1]. One of the main obstacles in regenerative medicine is to develop technologies that allow optimal recovery of damaged tissues. In this respect bioengineering of artificial organs might solve some of the problems associated with poor tissue regeneration. Stem cell research has emerged as one of the most promising areas in cell transplantation including rapid advancement of personalized tissue regeneration therapy to reprogram adult cells into induced pluripotent stem cells (iPSCs) [2]. These cells carry many properties of embryonic stem cells (ESCs) and capable of differentiating into any type of body cell. Thus, there is little doubt that progress in stem cell therapy will enable an organism to regenerate damaged tissues or organs with new cells derived from a patientâ�? �? s own cells.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: For the philosopher Lorraine Besser-Jones (2016), moreover, living-well is “flourishing qua human being” (p. 187). Eudaimonic well-being is therefore oriented toward the recognition and fulfillment of innate and distinctly human capacities. To identify the distinct traits, needs, and qualities of the human subjects/users that act as the idealized target for Facebook’s eudaimonic construct of well-being, I will now turn to the stated research upon which Facebook erects the division between active (healthy) and passive (unhealthy) usership. Access to this research can be gained via a blog post found upon Facebook’s blog series. Hard Questions, as its very first post in June 2017 states, was intended to make Facebook “more open and accountable” (Schrage, 2017) by offering an insight into how Facebook publicly conceptualizes and presents its action on various socio-political issues involving its services, addressing topics such as terrorist activity on Facebook, false news, data privacy, democracy, and user well-being (Schrage, 2017). Accredited to David Ginsberg, then director of research at Facebook, and Moira Burke, a social psychologist at Facebook, the blog post concerning user well-being is titled “Is spending time on social media bad for us? ” (Ginsberg & Burke, 2017). Here, Ginsberg and Burke present Facebook’s well-being research, which suggests it is how people choose to use social media that determines the extent to which it is a positive or negative force for their health. Social UserOn this blog, foreshadowing the quotes from Facebook’s leaders offered above, Ginsberg and Burke (2017) write,According to the research, it really comes down to how you use the technology. For example, on social media, you can passively scroll through posts, much like watching TV, or actively interact with friends—messaging and commenting on each other’s posts. Just like in person, interacting with people you care about can be beneficial, while simply watching others from the sidelines may make you feel worse. The blog post contains hyperlinks to particular psychological studies to bolster these claims. These include, for instance, papers by et al.

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: The experimental results show that after adding the mutual information features, the Recall increases, indicating that the number of correctly recognized formulaic language is more. However, due to the reduction of Precision, F1-socre is not improved. At the same time, compared with experiment 5, it shows that mutual information features can better represent the characteristics of formulaic language than dependency syntactic features. (5) Experiment 7 (the model proposed in this 3. 7% higher than that of experiment 3 (the experiment with the highest F1-score among other experiments). This shows that the model in this 10. As can be seen from the figure, the effect of using 3-layer graph convolution is the best for dependency syntactic parsing. Figure 10: Influence of different network layers on GCN based on dependency parsing. Download full-size image DOI: 10. 7717/peerjcs. 984/fig-10 (2) Experiment 6 is a GCN structure based on mutual information. Experiments are carried out by setting 1, 2, 3, 4 and 5-layer graph convolution respectively. The experimental results are shown in Fig. 11. As can be seen from the figure, the effect of using 2-layer graph convolution is the best for mutual information. Figure 11: Influence of different network layers on GCN based on mutual information. Download full-size image DOI: 10. 7717/peerjcs. 984/fig-11 Analysis of experimental results: It is generally believed that increasing the number of network layers can reduce the error and improve the accuracy, but it will also complicate the network, thus increasing the training time of the network and the tendency of over fitting. Therefore, the number of network layers required by different features is different. In this 12. Figure 12: Comparison of experimental results of three models. Download full-size image DOI: 10. 7717/peerjcs. 984/fig-12 Analysis of experimental results: (1) As the CNN_Bi-LSTM_CRF model is the primary method in named entity recognition, the experimental results show that this model does not perform well in the task of formulaic language recognition. It can be seen that in different tasks, although the two tasks are very similar, we should also start from the essence of the object in the task, mine the characteristics that can represent the research object, and design a unique model.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: The misunderstanding responsibilities, issues in confidentiality, lack of standards, interoperability issues and malicious insiders in the cloud computing caused the several issues to preserve the data from the attacks. Security issues have been categorized into data breaches, malicious attack, data loss, and inadequate diligence, sensitive data access, data segregation, etc. [2]. The confidentiality, integrity and availability must be ensured to achieve data security. The data security has become a complex challenge in cloud computing due to the following reasons: ・ The necessity to guard the confidential and sensitive data related to government and business organizations. ・ The sharing of cloud infrastructure among various clients. ・ Legal and regulatory compliances during data mobility. ・ Issues in auditing and reporting. ・ Lack of backup and storage standards. ・ Key management issues and unauthorized access In order to overcome these security challenges, there are several solutions available in secure cloud storage server. The confidentiality can be attained by applying the access controls, authentication mechanisms, cryptography schemes etc. The access to control and authentication mechanisms allows the authorized user access, whereas the cryptography techniques allows only the specific user, who possess the keys to access the data. Hence, the cryptography schemes are the best way to provide data security, in which the user cannot access the data without the knowledge of key. Generally, most of the cryptography techniques include three major steps as follows: ・ Key generation; ・ Encryption; ・ Decryption. Figure 1 shows the data flow and message flow in cloud storage server for secure data transmission. Key generation is the process of producing the keys that are used for encryption and decryption. The encryption is the process of converting the original data into an unreadable form known as cipher text by the keys. The decryption is the process of retrieving back the original message from the cipher text using the appropriate keys. The cryptography schemes are classified into two types such as symmetric or conventional cryptography and asymmetric or public key cryptography. The symmetric cryptography uses same key for both encryption and decryption, whereas the public key cryptography uses different keys. The symmetric cryptography schemes are fast but there is no guarantee for secure key distribution. As they use the same key for encryption and decryption, the third party, who is snooping while key transmission may decrypt the data. In order to overcome this issue, public key cryptography is introduced with a pair of keys, namely, public key and private key.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: (2015, 2017) that survey the links between different types of Facebook activity and user well-being, and Toma and Hancock’s (2013) research into Facebook and self-affirmation. Such research examines the psychological impact of Facebook through the binary of active and passive usage. These studies are referenced by Burke and Kraut as they seem to show that measures of well-being can increase if Facebook users engage in certain active habits—private messaging, liking friends’ photos and commenting for instance, as opposed to passive habits such as scrolling down the without interacting with posts, or failing to message friends and family. The first reference to Facebook’s own research on well-being on the blog is a paper co-authored by herself and Robert E. Kraut (2016). In this paper, Burke and Kraut suggest that Facebook exists as a tool that could benefit users’ well-being if used correctly to actively interact with others on the platform. Their argument, Burke and Kraut (2016) write, works “upon the assumption that people benefit from social interaction with others” (p. 266). This “assumption” is partly justified with a reference to Baumeister and Leary’s (1995) evolutionary concept of human belonging. Baumeister and Leary posit that humans have evolved to be reciprocally caring and social creatures to maintain evolutionary advantages in potentially threatening environments. The positive emotional ties that bind humans with others in familial groups, friendship circles, and romantic relationships are said to be distinct human characteristics that grant access to reproductive mates, mutual protection and resources such as shelter and food. Conversely, Baumeister and Leary (1995) claim that the “lack of [social] attachments is linked to a variety of ill effects on health, adjustment, and well-being” (p. 497), suggesting that human empathy and communication developed as evolutionary and physiological necessities of human survival. In referencing the evolutionary psychology of Baumeister and Leary, Burke and Kraut stake out a particular presentation of the Facebook user as an inherently “social” animal—a being whose healthy internal psyche and physical vitality are linked to communicating and socializing with other like creatures. Solidifying this notion, Burke and Kraut (2016) write thathumans are a social species, with many survival advantages accruing from our connections to others. (p.

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: At the same time, through the CNN_Bi-LSTM_CRF model and Experiments 2 and 4 in the previous section, it can be found that the effect will not get better after adding CNN to the model. Hence, CNN is not suitable for formulaic language identification task. (2) Bi-LSTM_CRF model is used to identify multi-word expressions. Compared with Experiment 1 in the previous section, the difference lies in the different input features. The input features of Experiment 1 are part-of-speech features and GloVe word embedding features, while Bi-LSTM_CRF model inputs part-of-speech features, fastText word embedding features and dependency syntactic relation. The experimental results show that the F1 -score of Bi-LSTM_CRF model is higher. However, the Recall of Experiment 1 is higher, indicating that dependency syntactic relation is conducive to recognizing formulaic language. At the same time, in comparison with the model in this 3. Table 3: Examples of formulaic language recognition errors. language is a nontrivial task since we do not have the ground truth labels to decide the adjustment. It is a nontrivial task since It is a nontrivial task In section 7 we compare these two variants against the regular hash function as well as to other leading hashing schemes found in the literature. As well as As well as to We therefore resort to an approximation of the process which has a negligible impact on the overall precision but greatly reduces run time. Has a negligible impact on Resort to; has a negligible impact on DOI: 10. 7717/peerjcs. 984/table-3 It can be seen from the table that the reason for the recognition error in the first example is that the word ‘since’ is not recognized. The reason for the recognition error in the second example is that the word ‘to’ is recognized. The reason for the recognition error in the third example is that ‘restore to’ is also regarded as a formulaic language. For the first two examples, in fact, the model’s positioning in the sentence is very accurate. However, due to the uncertainty of manual labeling, fixed evaluation indicators and other factors, it can only be considered that this word string recognition is wrong.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: The key advantage of public key cryptography is that the private keys used for decryption is never shared or Figure 1. Data transmission in a secure cloud storage server. transmitted [3]. The public key will be broadcasted, using which the data can be encrypted. The authorized user who possess the private key can only have the right to decrypt the data. The remaining sections of this paper are organized as follows: Section II presents the security challenges in cloud computing. Section III provides the list of cloud security attacks. Section IV describes various public key cryptography techniques to overcome the security issues. shows the results and discussion of the cryptography schemes. The survey is concluded in Section VI. 2. in is an important concern for several organizations that adopts cloud for data storage and maintenance. A minor mistake in any of the client application will pave a way to the hackers to access the entire data in the cloud storage server. If there is vulnerability in the cloud, the unauthorized user may access, corrupt, modify or delete the records in the cloud. The security challenges arise in the deployment models, service models and in the network [4]. It is the responsibility of the security manager to define the security framework of an organization based on asset, threat and vulnerability risk assessment matrices. Confidentiality, integrity, and availability are the three main are of data security [5]. Data confidentiality is significant in a place, where a critical data is stored in a remote server with multi user access. Figure 2 shows various security challenges in cloud computing. In a multitenant cloud infrastructure, the access privileges must be provided to the users to achieve security. Hence, the data of an organization cannot be accessed by the users of any other organization. Integrity is an important factor to maintain the reputation of the service provider. The trust and security can be enhanced by allowing only the authorized person to update the data of an organization. Data loss and data leakage can be prevented by employing integrity. Thus, authentication and identity management is used to provide authorized Figure 2. Security challenges in cloud computing. access. The service level agreement is signed between the vendor and the provider to eliminate the downtime of the server and to make the data always visible [6]. The major security challenges include data segregation and data leakages. The security challenges in cloud computing are listed below. 2. 1. The disclosure of sensitive data to the unauthorized user is termed as data breach.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: 267)As acting upon distinct human qualities to flourish as a human constitutes a core component of eudaimonic procedural accounts of well-being, if humans are social beings “by nature,” striving to act upon this innate sociality by adopting good Facebook habits of active, frequent, communication, can be presented by Facebook and its representatives as a contribution to living well as an ideal user on the platform. In this way, the forms of evolutionary sociality that have supposedly set the possibility of human vitality prior to the development of social media are said to be still operative in the current age of digital connectivity. Upon this basis, Facebook is presented as a tool to be utilized by human agents for their own social evolutionary purposes—a neutral technology that facilitates pre-existing human tendencies to communicate, socialize, and connect with those around them. As the fulfillment of social connection is said to lead to the development of beneficial emotional bonds, required for the evolutionary development of humanity as a species, and the lack of sociality results in damaging health effects, the “need to belong” (Burke & Kraut, 2016, p. 266) is positioned as a natural human trait. As such, Burke and Kraut (2016) predict that “social interaction [on Facebook] should improve well-being by fulfilling these needs” (p. 266). Reciprocating social ties on Facebook is said to sustain the access to the emotional support necessary for humans to fulfill their “species” social being. This is understood by Burke and Kraut (2016) in terms of “relationship maintenance” and “relational investment” (p. 266). The link to evolutionary theory is once again reiterated by Burke and Kraut with a reference to evolutionary psychologists Roberts and Dunbar (2010), whose work claims that regular and repeated interpersonal communications are necessary to maintain both primate and human social networks. Burke and Kraut (2016) refer to this relationship maintenance as an “investment” (p. 266) in time and energy. Relationships on Facebook are said to benefit users in accordance with the costs of time and energy invested into them. This argument is made through a reference to Ellison et al.

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: If the recognition effect is viewed from the perspective of word coverage, it must be higher than the existing evaluation indicators. In the third example, although ‘restore to’ is a non-formulaic language, it contains many characteristics of formulaic language, resulting in the model mistakenly considering it as formulaic language. This kind of word string usually contains many characteristics of formulaic language, such as Verb + preposition and other structures. However, it may not have a specific function and meaning in the fields of scientific and technological literature writing, so they are not formulaic languages. This situation is a problem we should think about and solve in the future. this 10. 7717/peerj-cs. 984/supp-1 Information and authors declare there are no competing interests. performed the computation work, authored or reviewed drafts of the 2020. An assistive environment for EAL academic writing using formulaic sequences classification. Environments 28:1-15. 2019. Comparing different word embeddings for multiword expression identification. In: International conference on applications of natural language to information systems. Cham. Springer. 295-302 Berk G, Erden B, Güngör T. 2018. Deep-bgt at parseme shared task 2018: bidirectional lstm-crf model for verbal multiword expression identification. In: Proceedings of the joint workshop on linguistic annotation, multiword expressions and constructions (LAW-MWE-CxG-2018). Santa Fe. 248-253 Chen YH, Baker P. 2010. Lexical bundles in L1 and L2 academic writing. & Technology 14(2):30-49 Durrant P, Mathews-Aydnl J. 2011. A function-first approach to identifying formulaic language in academic writing. English for 30(1):58-72. 2020. using CNN-BilSTM-CRF model. In: 2020 Congress (CAC). Shanghai. 6159-6164. 2017. Deep learning models for multiword expression identification. In: Proceedings of the 6th on Lexical and (* SEM 2017). Vancouver. 54-64 Hochreiter S, Schmidhuber J. 1997. Long short-term memory. 9(8):1735-1780. 2019. Phrase recognition method combining multiple strategies. 37(6):49-54 Hyland K. 2008.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: Attack Side-channel attack urges the application of cryptographic techniques to prevent the cloud systems from security threat. Therefore, it is necessary to evaluate the resilience of the cryptographic system against the side-channel attacks. 3. 2. Authentication is a weak point in hosted and virtual services and is frequently targeted. There are many different ways to authenticate users. The mechanisms used to secure the authentication process and the methods used are a frequent target of attackers. Currently, regarding the architecture of SaaS, IaaS, and PaaS, there is only IaaS offering this kind of information protection and data encryption. 3. 3. Man-In-The-This attack is carried out when an attacker places himself between two users. Anytime attackers can place themselves in the communication’s path, there is the possibility that they can interfere and modify communications. 4. Cryptography plays a significant role in securing the data by converting it into an unreadable form during storage and transmission. The asymmetric encryption, which is also known as public key cryptography, applies public and private keys for encryption and decryption respectively. This adds key strength and hence, key exchange is not a problem in this scheme. Figure 3 shows the various public key cryptography techniques. 4. 1. Rivest, Shamir, Adleman (RSA) RSA algorithm is one of the public key cryptography schemes that is used for secure data transmission. The algorithm is named after its inventors Ron Rivest, Adi Shamir, and [11]. In RSA, a public-private key pair is generated, where the public key is published to all for encryption and the private key is kept safe for decryption. The three major steps are: ・ Key generation; ・ Encryption; ・ Decryption. Figure 3. Public key cryptography techniques. In the key generation phase, each user generates a public key and a private key pair by selecting two large prime in a random order. It uses Euler’s theorem, square and multiply algorithm for exponentiation. A repeated squaring is performed on the base number and the exponents are multiplied to compute the result. Figure 4 shows the workflow of key generation process in RSA. In the encryption step, the sender publishes the public key (m, encr) and keeps the private key. The padding scheme is used to convert the original data D to cipher text C i p h e r = D m o d m.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: ’s (2014) research on social capital and social media, which suggests that high effort in relationship maintenance and communication with friends online correlates with high levels of social capital (the access to emotional and material resources that relationships in social networks can provide (Bourdieu & Wacquant, 1992) and user well-being. As such, the value of relationships in Burke and Kraut’s, and by extension Facebook’s, construction of social well-being is established through the prism of self-interest. Elsewhere in its research, moreover, Facebook repeatedly characterizes relationships as investments in social capital. For instance, in Facebook’s earliest research into user well-being (Burke et al. , 2010, 2011), investing time and energy into relationships is said to constitute healthy Facebook practice by ensuring that social ties remain intact over time. These social investments thereby increase the likelihood that social resources will be available to users if needed in the future. In this model, the rational motivation for ideal usership on Facebook is the expected return individuals would gain on their emotional investment in others. In Facebook’s early studies on social capital and well-being, thus, the former is positively correlated with the latter: higher levels of social capital in users predict higher levels of well-being. While the personal choice to invest in relationships and cultivate social capital amounts to living well on Facebook, once viewed in combination with Facebook’s evolutionary discourse of the social human subject, this choice is simultaneously presented as the fulfillment of a natural inclination to connect with others in a shared social environment. Upon this basis, direct communications, sharing statuses, liking photos, commenting on posts—and all the other hallmarks of good, active usage, rather than being viewed as the result of a designed user-experience intended to gather data for the sake of capitalist profit (Beer, 2016; Hearn, 2010; Skeggs & Yuill, 2016; & Poell, 2013), can instead be presented as the result of rational user choices fulfilling innate human social needs. However, the next section will show how Facebook’s modeling of ideal usership originates from a very particular time and place, specifically working to encourage users to “believe that we can integrate all our values, unify our compartmentalized worlds, and measure our longings” (Espeland & Mitchell, 1998, p. 323) through the rubric of neoliberal self-interest.

Output: contrast


Input: Claim: Syntactic parsing in the brain is influenced by both grammatical rules and context. [SEP] Text: Academic clusters: text patterning in published and postgraduate writing. of 18:41-62. 2020. Extraction and evaluation of formulaic expressions used in scholarly papers. 67:885-992. 2013. Multisensor data fusion: a review of the state-of-the-art. 14(1):28-44 Kipf TN, Welling M. 2016. Semi-supervised classification with graph convolutional networks. preprint. 2016. ICL-HD at SemEval-2016 Task 10: improving the detection of minimal semantic units and their meanings with an ontology and word embeddings. In: Proceedings of the 10th on (SemEval-2016). San Diego. 937-945. 2017. Neural networks for multi-word expression detection. In: Proceedings of the 13th workshop on multiword expressions (MWE 2017). Valencia. 60-65. 2001. Conditional random fields: probabilistic models for segmenting and labeling sequence data. Lei L, Liu D. 2018. The academic English collocation list: a corpus-driven study. of 23(2):216-243 Li GC. 2012. An overview of foreign research on formulaic language identification. Journal of University 18(5):221-225. 2021. Semi-supervised software defect prediction model based on tri-training. KSII Transactions on Internet and 15(11):4028-4042. 2022. Creating knowledge graph of electric power equipment faults based on BERT–BiLSTM–CRF model. Journal of & Technology 17:1-10 Metin SK. 2018. Feature selection in multiword expression recognition. with Applications 92:106-123. 2018. Crf-seq and crf-deptree at parseme shared task 2018: Detecting verbal mwes using sequential and dependency-based approaches. In: Joint workshop on linguistic annotation, multiword expressions and constructions (LAW-MWE-CxG-2018) at the 27th on (2018). Santa Fe. 241-247 Pecina P. 2009. Lexical association measures: collocation extraction. In: of studies in computational and theoretical linguistics. Praha, Czechia: UFAL. . 2014. Glove: global vectors for word representation.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: In the decryption step, the original data D is obtained as follows: D = C i p h e r m o d m. Attacks in RSA Figure 4. Workflow of RSA. The RSA algorithm is attacked by brute force key search, mathematical attacks, and timing attacks. The attacks can be resolved by using a constant exponentiation time and by adding random delays. Some of the three approaches that attack the RSA algorithm are: (attack)―it means testing out all the possible private keys. Arithmetical attacks―the approaches of all equivalent in effect to factoring the product of 2 primes. Timing incursion (attacks)―these depend on the running time of the decryption algorithm. Advantages 1. Integrity, authentication, non-repudiation, and secrecy and privacy are the features of RSA algorithm. 2. Private keys are never exposed. 3. Non-repudiation can be achieved using the digital signatures provided by RSA. 4. Key strength is high, as the key size is large. Disadvantages 1. RSA requires exponential amount of time because of large key sizes. 2. Key generation is complex. 3. No tradeoff between time and security. Applications 1. Layer (SSL) protocol. 2. (SSH) remote connection. 3. Privacy (PGP) to guarantee security and privacy. 4. 2. key exchange algorithm is used to share a public and private key pair for encryption and decryption in a secure way. This algorithm is name after its inventors [12]. Diffie-Hellman is not an encryption algorithm but it is a secure key exchange algorithm, which accomplishes secure exchange by creating a shared secret key. The symmetric key is encrypted using the shared secret key for secure transmission. The public key is certified by the certificate authority to prevent man-in-the-middle attack. Any number of participants can take part in secure exchanges by performing iterations on the agreement protocol and exchanging intermediate data. Here, two users, who are unknown to each other share secret key via an insecure channel. Initially, both of them share a public key for authentication. The third party may access the keys, while transmission, which is commonly known as man in the middle attack [13]. It may alter the key shared between both the sender and the receiver. The workflow of key exchange process is illustrated in Figure 5. Advantages 1. Improves security for the shared secret key.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Neoliberal ChoiceFacebook’s entwining of healthy usership and social capital positions the ideal Facebook user as a rational agent of self-interest, yet its specific political character can be further explicated by tracing the origins of its theoretical construction. In Facebook’s earliest studies of well-being, James S. Coleman (1988) is the first reference used by Facebook’s researchers to conceptualize their version of social capital (Burke et al. , 2010). As a result, and as I will demonstrate below, Facebook’s vision of the ideal user can be said to assume a neoliberal form. Developing the notion of human capital espoused by (1964) and (1961) in the 1960s, which takes the unique capacities of the human actor as differentials of value in the labor market, Coleman’s theory of social capital from the late 1980s attempts to extend the remit of economic rationality to the totality of social relations. Coleman suggests that social capital is an economically functional concept, attributing value to the potentially productive relations that exist between persons. In this way, Coleman (1988) considers social capital in tandem with the concepts of financial, physical, and human capital, and the situation of value in money, factors of production, and personal skills, respectively (p. 118). This results in an economization of social relations. With his version of social capital, Coleman (1988) seeks toimport the economists’ principle of rational action for use in the analysis of social systems proper, including but not limited to economic systems, and to do so without discarding social organization in the process. The concept of social capital is a tool to aid in this. (p. 97)For Coleman, and within Facebook’s research explicated so far, social capital is conceptualized as a resource available to each social actor in any given social environment to further their own self-interested goals, and can be identified as the primary relation that connects individuals together within social networks. Competitive self-interest, thus, forms the theoretical basis upon which social organizations, like Facebook’s social network, can be studied.

Output: contrast


Input: Claim: Rhizobacteria enhance plant growth by fixing atmospheric nitrogen in the soil. [SEP] Text: Optical density was measured carefully to maintain the uniform population of bacteria in the broth at the time of inoculation. 2. 5. Characterization of isolates Root colonization was done by the method of Davis and Whitbread, (1989). For this, inoculated seeds were sown in glass jars containing sterilized sand, and the jars were kept in a growth chamber (18 °C, 70 % relative humidity, 16 hours daylight). After 7 days of germination, the roots were cut off, dipped in phosphate buffer, and were shaken vigorously to remove the bacteria. After 2 days of incubation at 28 °C the number of colonies (CFU/cm) was calculated. For the determination of phosphorus solubilizing activity Research Institute’s Phosphate growth medium (NBRIP) was used. Rhizobacterial strains were cultured and a loop full of each culture was placed on the plates (five per plate) and incubated at 28 °C for a week. A clearing zone around the colonies after a week was calculated as a positive for phosphate solubilization The formula of Premono et al. , (1996) was used for the determination of phosphate solubilizing index (PSI) of these rhizobacterial isolates. PSI = Colony diameter + Halozone diameter Colony diameter The ACC-deaminase activity was determined by the modified method of Honma and Shimomura, (1978) which measures the amount of α-ketobutyrate when the enzyme ACC-deaminase cleaves ACC. The auxin produced by rhizobacteria as indole acetic acid (IAA) in the presence and absence of L-tryptophan (L-TRP) was essayed by the method of Sarwar et al. , (1992). Some pertinent characteristics of the rhizobacterial isolates are shown in Table 1. Table 1. Characterization of rhizobacterial strains -ve = Absent, +ve = Present 2. 6. Determination of plant physical parameters The fresh and dry weight of the shoots and roots were determined with the help of an analytical balance. For dry weight plants were oven dried at 70 °C. 2. 7.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: 2. As the key size is small, the computation is fast. Disadvantages 1. Messages cannot be encrypted using algorithm. Figure 5. Workflow of key exchange. 2. Prone to denial of service and man in the middle attacks [14]. 3. No authentication between the sender and the receiver [14]. 4. Lack of forward secrecy [15]. Applications 1. Layer (SSL) protocol [16]. 2. Security (IPSec). 3. Infrastructure (PKI). 4. (SSH) remote connection [16]. 4. 3. Cryptography (ECC) Elliptical curve cryptography (ECC) is one of the public key encryption technique that generates best cryptographic keys according to the elliptic curve theory. It creates smaller keys within a short period. Rather than using large prime numbers for key generation, ECC uses the properties of elliptic curves to generate keys. Elliptic curve is a nonsingular cubic curve with two variables in a certain field and an infinite rational point [17]. Each user generates a public-private key pair, where the public key is applied for encryption and signature verification and the private key is applied for decryption and signature generation. The high level of security can be achieved in ECC using a 164 bit key, where the traditional techniques need 1024 bit key. ECC is widely used because of its low computing complexity and better utilization of batter power. Security is attractive feature of elliptic curve cryptography. Figure 6 shows the key processes in ECC. Figure 6. Workflow of ECC. ECC includes the following major steps [17] : ・ Key generation; ・ Signature generation; ・ Encryption; ・ Decryption; ・ Signature verification. Advantages 1. Strong security with small keys. 2. Faster performance. 3. Low computational complexity. 4. Increased level of authentication and confidentiality. Disadvantages 1. Size of the encrypted message is increased. 2. Implementation is difficult. Applications 1. Layer. 2. Debit/Credit cards. 3. E-mails. 5. The digital signature standard is used to detect unauthorized modifications and to verify the document’s identity. The digital signature is represented as binary digits and computed using a set of rules and parameters. The signature is generated by the use of a private key, which is known only to the user [18].

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: The sociologists Ferragina and Arrigoni (2017) would argue that the incorporation of Coleman’s theories of social capital into Facebook’s social psychology would represent anexample of how the analytical categories of neoliberalism and the language of the stock market have decisively permeated social and political discourse over the last few decades. The reduction of social relations to something similar to financial capital implicitly means to assume that community involvement and social participation are forms of economic activity. (p. 358)Facebook’s specific utilization of social capital to explicate the value of user relationships, therefore, could be viewed as a reductionist extension of economic rationality to formerly non-economic social domains and institutions. Foucault’s (2010) analysis of neoliberalism presented in his 1978–1979 lectures at the Collège de France is a pertinent reference point to understand this notion further. In these lectures, Foucault (2010) describes the rationality of neoliberalism as a generalized attempt to “use the market economy and the typical analyses of the market economy to decipher non-market relationships and phenomena which are not strictly and specifically economic” (p. 240). Elsewhere, Foucault (1983) describes neoliberalism as the “government of individualization” (p. 212); a form government that tasks itself with the production of subjects capable of being governed by such economic regulatory principles of competition and enterprise. Burchell (1996), therefore, as opposed to a governmental regime of governing less, neoliberalism is best understood as the construction of the “institutional and cultural conditions that will enable an artificial competitive game of entrepreneurial conduct to be played to best effect” (p. 27). Thus, when Foucault (2010) describes neoliberalism as the “the generalization of the economic form of the market [. . . ] throughout the social body” (p. 243), he is referring to those processes that extend the precepts of economic rationality to investigate forms of human organization, conduct, and relationships not previously understood as economic domains. In appropriating scales of neoliberal social capital as measures of well-being, Facebook relays a historicized conceptualization of the human subject entangled with economic discourses of self-interest and competitive choice.

Output: contrast


Input: Claim: Rhizobacteria enhance plant growth by fixing atmospheric nitrogen in the soil. [SEP] Text: Determination of chlorophyll and carotenoids The method of Arnon, (1949) was used for the determination of chlorophyll and carotenoid contents in the acetone extract (80% v/v) at 663, 645 and 480 nm for chlorophyll a, b and carotenoid, respectively. 2. 8. Macro and micronutrients in plant The H2SO4 titration method was used for the plant nitrogen (N) determination (Van-Schouwengerg and Walinge, 1973). For the measurement of the plant phosphorous (P) the method of Buresh et al. , (1982) was followed. The plant potassium (K) was determined by using the dry ashing method (Chapman and Pratt, 1961). The micronutrients i. e. Ca+2, Mg+2, Mn+2, Zn+2, Cu+2 and Fe+3 were determined by atomic absorption spectroscopy after dry ashing (Chapman and Pratt, 1961). 2. 9. Plant enzymes activity For enzymes activity analyses plant samples were prepared by homogenizing 0. 5 g of frozen leaf material in 3 ml of cold solution containing 50 ×10-3 M Na phosphate buffer (pH 7. 8), 1×10-3 M Ethylenediaminetetraacetic acid and 2% (w/v) Polyvinylpolypyrrolidone. The homogenate was centrifuged at 0 °C for 40 minutes at 13000 g. The glutathione S-transferase (GST) was essayed by the method of Habig et al. , (1974). The method of Nakano and Azada, (1987) was used for the spectrophotometric determination of peroxidase (POX) activity. Whereas, the spectrophotometric determination of catalase (Cata) activity was done by the method of Cakmak and Horst, (1991). 2. 10.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: The signature is verified using a public key that is corresponding to the private key. The signature is generated by the user with the help of the private key, which is never shared. A (SSH) function is used in the signature generation pro- cess to obtain a condensed version of the data called a message digest. A digital certificate contains the digital signature of the certificate issuing authority so that anyone can verify the originality of the certificate [19]. The digital certificates will expire after specific duration, which results in insecurity. Advantages 1. Legal compliance. 2. Less processing time. 3. Reduced overhead. 4. Improved security. Disadvantages 1. Short life span. 2. Complicates sharing in case of incompatibility. Applications 1. E-mails. 2. Fund transfers. 3. Data interchange. 4. Software distribution. 6. Results and general public key encryption, or asymmetric encryption, is about 10,000 times slower than private key encryption. This is because of the use of two different keys for encryption and decryption. Even though, they are smaller they provide high degree of security. 6. 1. RSA vs. Diffie-Hellman Diffie-Hellman allows two users A and B, who have never met anywhere, they decide to work together and establish a secret key in order to communicate secretly manner, even in the presence of some intruder. In RSA only the Receiver needs to perform calculations to establish what is called a secret key and a public key. doesn’t have to necessarily know the Sender of the messages. 6. 2. RSA vs. is commonly used cryptography scheme to provide data confidentiality in cloud storage. As the key size increases, the security also increases and storage capacity required to store key in key management server will be large. Security is attractive feature of elliptic curve cryptography. Elliptic curve cryptosystems also are more computationally efficient RSA and Diffie-Hellman. The computation time of ECC is less when compared to RSA and Diffie Hellman, but it is more complex to implement [20]. RSA and Diffie-Hellman algorithms dominate public-key cryptography and have proved its efficiency in real-world applications. ECC promises particularly in smart cards or other restricted environments. The ECC and RSA are compared in terms of key generation time, signature generation and verification time.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: In Facebook’s discourse of the ideal user, consequently, the individual is enjoined to view their relationships as resources to be weighed up to further their self-interested goals and are tasked with choosing habits of active usership to cultivate their social capital for the sake of their own well-being. (2005) suggests such configurations of wellness in neoliberal discourses construct, and treat, individuals as:rational, calculating creatures whose moral authority is measured by their capacity for “self-care”- the ability to provide for their own needs and service their own ambitions. (p. 42)The emphasis on self-sufficiency and the autonomy of personal decision-making means, for W. Brown (2005), that the individual in neoliberal societies “bears full responsibility for the consequences of his or her action no matter how severe the constraints on this action [are]” (p. 42). Thus, regardless of the various social contingencies that structure the possibilities of personal well-being in various spheres of life—in the workplace, at home, or in education, for instance, including, but not exclusive to, configurations of class, ethnicity, gender, or physical capacity (B. J. Brown & Baker, 2013), the ideal users of Facebook, instead, exist in a vacuum whereby their choice of activity on the platform, and their choice of activity alone, determines their social capital and well-being online. However, the atomized agents inherent within neoliberal social capital theories such as Facebook’s greatly contrast with other conceptualizations of social capital as espoused, for instance, by Bourdieu (1986). Bourdieu (1986) suggests that the access to resources enjoyed by individuals within social networks are directly correlated with class and socio-economic standing, indicating that there are variegated structural forces in play that delimit any benefits individuals can glean from their social circles. In Facebook’s discourse of social well-being, however, autonomous users utilizing Facebook’s tools in the right way are solely responsible for their health on the platform. Consequently, such responsibilized processes of personal choice avoid any discussions regarding the structural inequalities that may impact an individual’s well-being as they navigate contemporary neoliberal forms of life (Cole & Ferrarese, 2018; Dardot & Laval, 2013).

Output: contrast


Input: Claim: Rhizobacteria enhance plant growth by fixing atmospheric nitrogen in the soil. [SEP] Text: Comparison of method for measuring the colonization of root system by fluorescent pseudomonads. Plant Soil. 116, 239-246. Dworken, M. , Foster, J. 1958. Experiment with some microorganisms which utilize ethane and hydrogen. J. Bacteriol. 75, 92-601. Etesami, H. , Hosseini, M. , Alikhani, HA. 2014. In planta selection of plant growth promoting endophytic bacteria for rice (Oryza sative L. ). J. Soil Sci. Plant Nut. 14, 491-503. database of World Agriculture. 2006. Food and of the Statistics Division. database of World Agriculture. 2009. Food and of the Statistics Division. Glick, B. R. 2012. Plant Growth-Promoting Bacteria: Mechanisms and Applications. Corporation, Scientifica. 1974. Glutathion S-Transferases, the first enzymatic step in mercapturic acid formation. The J. Biol. Chem. 249, 7130-7139. Hassan, W. , Chen, W. , Huang, Q. , Mohamed, I. 2013a. Microcalorimetric evaluation of soil microbiological properties under plant residues and dogmatic water gradients in Red soil. Soil Sci. Plant Nut. 59, 858-870. Hassan, W. , Akmal, M. , Muhammad, I. , Younas, M. , Zahaid, K. R. , Ali, F. 2013b. Response of soil microbial biomass and enzymes activity to cadmium (Cd) toxicity under different soil textures and incubation times. Aust. J. Crop Sci. 7, 674-680. Hassan, W. , Chen, W. , Cai, P. , Huang, Q. 2013c. Oxidative enzymes, the ultimate regulator: implications for factors affecting their efficiency. J. Environ. Qual. 42, 1779-1790. Hassan, W. 2013d. C and N mineralization and dissolved organic matter potentials of two contrasting plant residues: effects of residue type, moisture and temperature. Acta Agr. Scand. B-S P. 63, 642-652. Hassan, W. , David, J. 2014.

Output: pass


Input: Claim: Cryptography is essential for securing data and communications online. [SEP] Text: Table 4 presents the comparison of signature verification time of RSA and ECC schemes [20]. By varying the key length from 1024 to 15,360 bits, the time required for signature verification increases linearly. In RSA, the minimum time required for signature verification is 0. 01 secs for 1024 bits and the maximum time is 0. 01 secs for 15360 bits. Similarly, the time required for signature generation in ECC is 0. 23 and 4. 53 secs with respect to the key length variations. The signature is verified at the decryption stage and it also depends on the key length. As the number of bits in the key size increases, the time required for signature verification also increases. Table 4. Signature verification time analysis 7. paper addressed the limitations in the security assurance and the data privacy limitations with increase in size of the data on cloud. The evolution of cryptographic approaches addressed these limitations and provided the solution to the preserving process. Due to the multi-tenancy property of the cloud, server and the geographical factors limited the security of the cloud data access and storage. This paper surveyed about the various cryptographic techniques with their key sizes, time required for key/signature generation and verification constraints. The survey discussed the architecture for secure data transmissions among the devices, challenges raised during the transmission and attacks. This paper presents the brief review of major cryptographic techniques such as RSA, and the ECC associated key sizes. This paper investigated the general impact of digital signature generation techniques on cloud security with the advantages and disadvantages. The results and discussion section existing in this paper investigated the time consumption for key/signature generation and verification with the key size variations effectively. Finally, the results of these approaches were compared in terms of key size, key generation time, signature generation time and signature verification time. The initialization of random prime numbers and the key computation based on the points on the elliptic curve assured the high-security compared to the existing schemes with the minimum time consumption and sizes in cloud-based applications. Conflicts of authors declare no conflicts of interest. 2307. [2] Asma, A. , Chaurasia, M. A. and Mokhtar, H. (2012) Security Issues. of Application or Innovation in Engineering & Management, 1, 141-147. [3] Agrawal, M. and Mishra, P. (2012) A on Encryption Techniques. on and Engineering, 4, 877.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: The work of social policy scholar (2005) would indicate that the responsibilization of users on Facebook in terms of well-being is resonant with neoliberal public health policies of individualization. Clark (2005) writes that:responsible citizens [it is claimed] make reasonable choices—and therefore “bad choices” result from the wilfulness of irresponsible people, rather than the structural distribution of resources, capacities and opportunities. (p. 451)This focus on personal choice has also been identified as key element of the discourse surrounding technology and well-being by Schüll (2016). In her exploration of the biopolitics of wearable tracking technologies, such as Fitbit and Jawbone, Schüll (2016) argues that the selves produced by networked technologies are idealized as “choosing subjects” (p. 8) capable of utilizing the array of complex technologies available on the market to improve their physical and mental health. “More precisely,” Schüll (2016) writes, these idealized subjects are “are construed as consumers whose well-being depends on and derives from the market choices they make” (p. 8). In presenting well-being online as an outcome of user choice, Facebook’s account of well-being side-steps the discussion surrounding its potentially addictive, anxiety-inducing, “persuasive” (Fogg, 2003) design. Instead, Facebook’s PR strategy surrounding these issues operates on the level of individual habit, suggesting that well-being arises from correct personal social networking choices alone. While the responsibilized subject of well-being has been studied in relation to funding cuts to public services in the (B. J. Brown & Baker, 2013; Goode et al. , 2004), as a mode of neoliberal biopolitics (Wright, 2013), or as a modality of consumerist and marketized discourses of health care (Anderson et al. , 2016), Facebook’s own individualized concept of well-being limits the discussion of what it means to live well in the present age to the narrow parameters of a particular form of online self-interested connection. The well-being of users in Facebook’s discourse of active and passive usage, therefore, is firmly presented as the responsibility of users themselves.

Output: contrast


Input: Claim: Rhizobacteria enhance plant growth by fixing atmospheric nitrogen in the soil. [SEP] Text: Plant growth-promoting bacteria confer resistance in tomato plants to salt stress. Plant Physiol. Biochem. 42, 565-572. Mia, M. A. B. , Shamsuddin, Z. H. , Wahab, Z. , Marziah, M. 2010. Effect of plant growth promoting rhizobacterial (PGPR) inoculation on growth and nitrogen incorporation of tissue-cultured Musa plantlets under nitrogen-free hydroponics condition. Aus. J. Crop Sci. 4, 85-90. . , Arshad, M. , Shahzad, S. M. 2006. Variation in growth and ion uptake of maize due to inoculation with plant growth promoting rhizobacteria under salt stress. Soil Environ. 25, 78-84. Nakano, Y. , Azada, K. 1987. Purification of ascorbate peroxidase in spinach chloroplasts: its inactivation in ascorbate depleted medium and reactivation by monodehydroascorbate radical. Physiol. 28, 131-140. Premono, H. . 1996. Effect of phosphate-solubilizing Pseudomonas putida on the growth of maize and its survival in the rhizosphere. Indonesian J. Crop Sci. 11, 13-23. Sarwar, M. , Arshad, M. , Martins, D. A. , Frankenberger, Jr. 1992. Tryptophan-dependent biosynthesis of auxins in soil. Plant Soil. 147, 207-215. Schalchli, H. , Pardo, F. , Hormazábal, E. , Palma, R. , Guerrero, J. , Bensch, E. 2012. Antifungal activity of wheat root exudate extracts on Gaeumannomyces graminis var. Tritici growth. J. Soil Sci. Plant Nut. 12, 329-337. Shaharoona, B. , Arshad, M. , Zahir, Z. A. , Mahmood, M. H. 2003. 1-aminocyclopropane-1-carboxylate (ACC) enrichment: An effective approach to screen plant growth promoting rhizobacteria for maize. Pak. J. Agri.

Output: pass


Input: Claim: Quantum cryptography is an emerging field with potential for high security. [SEP] Text: encrypts she sends the encrypted information to Bob, who must now recover the original information. Exactly how Alice encrypts the message depends upon the private key, so that to recover the original message Bob needs to know the private key, in order to undo the transformation Alice applied. Unfortunately, private key cryptosystems have some severe problems in many contexts. The most basic problem is how to distribute the keys? In many ways, the key distribution problem is just as difficult as the original problem of communicating in private – a malevolent third party may be eavesdropping on the key distribution, and then use the intercepted key to decrypt some of the message transmission. One of the earliest discoveries in quantum computation and quantum information was that quantum mechanics can be used to do key distribution in such a way that Alice and Bob’s security cannot be compromised. This procedure is known as quantum cryptography or quantum key distribution (abbreviated QKD). The basic idea is to exploit the quantum mechanical principle that observation in general disturbs the system being observed. Thus, if there is an eavesdropper listening in as Alice and Bob attempt to transmit their key, the presence of the eavesdropper will be visible as a disturbance of the communications channel Alice and Bob are using to establish the key. Alice and Bob can then throw out the key bits established while the eavesdropper was listening in, and start over. The first quantum cryptographic ideas were proposed by wrote “Conjugate Coding”[1], which unfortunately took more than ten years to see the light of print. In the mean time, Charles H. Bennett (who knew of Wiesner’s idea) and picked up the subject and brought it to fruition in a series of papers that culminated with the demonstration of an experimental prototype that established the technological feasibility of the concept [2]. Quantum cryptographic systems take advantage of Heisenberg’s uncertainty principle, according to which measuring a quantum system in general disturbs it and yields incomplete information about its state before the measurement. Eavesdropping on a quantum communication channel therefore causes an unavoidable disturbance, alerting the legitimate users. This yields a cryptographic system for the distribution of a secret random cryptographic key between two parties initially sharing no secret information that is secure against an eavesdropper having at her disposal unlimited computing power.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: So far, I have shown how Facebook’s recommendations of “healthy” usership are made through the blending of evolutionary and neoliberal discourses, arguing that Facebook’s model of ideal usership seeks to present the engineered sociality observable on the platform as the outcome of the rational user choosing to act in alignment with their “natural” eudaimonic needs. I have argued that Facebook’s ideal user relays conceptualizations of the neoliberal social subject, and, as such always exists in a necessary process of construction. Thus, I have presented Facebook’s concurrent appeal to evolutionary human need as a strategic attempt to naturalize what is an inherently artificial vision of human sociality. The following section will explore how the discourse of the healthy user manifests in the designed nudges (Thaler & Sunstein, 2008) of Facebook’s user interface. In doing so, the supposed autonomy of Facebook’s ideal user to choose to live well on the platform will be thrown into question. NudgesSimilarly to B. J. Fogg’s (2003) belief that “persuasive” technological design can “create interactive experiences that motivate and persuade people” (p. 5) toward certain ends, Thaler and Sunstein’s (2008) vision of the psychological nudge suggests that subtle environmental design decisions can adjust human behavior in particular directions. For instance, social psychological research has purportedly shown the ways that setting a default option in an administration form increases the likelihood of an individual choosing that option as their final decision (Pichert & Katsikopoulos, 2008); others have demonstrated that drawing attention to specific products on supermarket shelves can influence consumer purchasing patterns (Kroese et al. , 2016); while Thaler and Sunstein (2008) themselves suggest that minute visual cues can unconsciously direct behavior in different settings—as demonstrated by the famous example of the engraving of a housefly on urinals in Schiphol airport that successfully reduced user “spillage” by 80% (p. 4). Beyond constructing consumer choices and toilet hygiene, the UK government has a dedicated “Nudge unit,” officially called the Team, that is tasked with researching and proposing governmental policies that promote healthy behaviors (Halpern, 2015), while Sunstein himself was an advisor to the Obama administration and design consultant to the Act in the in 2010 (Schüll, 2016).

Output: contrast


Input: Claim: Rhizobacteria enhance plant growth by fixing atmospheric nitrogen in the soil. [SEP] Text: IAA production was determined according to the modified method of Glickmann and Dessaux [19]. PGPR cultures were grown in tryptic soy broth (TSB) which contained 2 mg mL−1 of L-tryptophan and incubated on a rotary shaker at 200 rpm under room temperature, 28±2°C for 24 h. The cultures were centrifuged at 7000 rpm for 7 min and the supernatants were quantified spectrophotometrically at 535 nm with 2 mL of Salkowski’s reagent (2% of 0. 5 M FeCl3 in 35% perchloric acid) after 25 min. The IAA concentrations were estimated from a standard IAA curve. 16S rDNA gene analysis of selected bacterial strains Total genomic DNA was extracted using (Co. Ltd. ) according to the supplier’s instructions and used as DNA template in polymerase chain reaction (PCR) for amplification of the 16S rDNA gene. The DNA purity was quantified at 260 nm and 280 nm using Nano(ND1000, Scientific Inc. ), 1. 6 to 2. 2, to detect protein contamination in the DNA [20]. PCR amplification was performed in a reaction mixture containing 50 ng genomic DNA template, 1X reaction buffer, 200 μM dNTPs mixture, 1. 5 mM MgCl2, 2. 5 U Taq DNA polymerase (Scientific), 0. 16 μM of each primer 27F (5’--3’) and 1492R (5’--3’) [21], and ultra-pure sterilised water to a final volume of 50 μL. These primers allowed an approximate 1500 bp of DNA fragments to be amplified. The DNA amplification was performed in a thermal cycler (-1148, Bio-Rad) by an initial denaturation at 94°C for 5 min, followed by 30 amplification cycles of denaturation at 94°C for 30 s, annealing at 55°C for 30 s, extension at 72°C for 1 min and a final extension step at 72°C for 5 min.

Output: pass


Input: Claim: Quantum cryptography is an emerging field with potential for high security. [SEP] Text: Once this secret key is established, it can be used together with classical cryptographic techniques such as the one-time-pad (OTP) to allow the parties to communicate meaningful information in absolute secrecy. The second major type of cryptosystem is the public key cryptosystem. Public key cryptosystem don’t rely on Alice and Bob sharing a secret key in advance. Instead, Bob simply publishes a ‘public key’, which is made available to the general public. Alice can make use of this public key to encrypt a message which she sends to Bob. The third party cannot use Bob’s public key to decrypt the message. Public key cryptography did not achieve widespread use until the mid-1970s, when it was proposed independently by Rivest, Adi Shamir, and developed the RSA cryptosystem, which at the time of writing is the most widely deployed public key cryptosystem, believed to offer a fine balance of security and practical usability. The key to the security of public key cryptosystems is that it should be difficult to invert the encryption stage if only the public key is available. For example, it turns out that inverting the encryption stage of RSA is a problem closely related to factoring. Much of the presumed security of RSA comes from the belief that factoring is a problem hard to solve on a classical computer. However, Shor’s fast algorithm for factoring on cryptosystems which can be broken if a fast algorithm for solving the discrete logarithm problem – like Shor’s quantum algorithm for discrete logarithm – were known. This practical application of quantum computers to the breaking of cryptographic codes has excited much of the interest in quantum computation and quantum information. In addition to key distribution, quantum techniques may also assist in the achievement of subtler cryptographic goals, important in the post-cold war world, such as protecting private information while it is being used to reach public decisions. Such techniques, pioneered by [3] [4], allow two people to compute an agreed-upon function f(x; y) on private inputs x and y when one person knows x, the other knows y, and neither is willing to disclose anything about their private input to the other, except for what follows logically from one’s private input and the function's output.

Output: corroborate


Input: Claim: Social media algorithms always have a positive impact on user mental well-being. [SEP] Text: Nudge, then, refers to the conscious arrangement of environments so as to affect certain behavioral outcomes within them. These types of environments have been termed “choice architectures” by Thaler and Sunstein (2008). Thaler and Sunstein (2008) describe the process of nudging as “libertarian paternalism”—the attempt to design social environments that “move people in directions that will make their lives better” (p. 6) while still maintaining an impression of free choice. By drawing explicitly upon the work of Milton Friedman, who can be viewed as one of the intellectual pillars of neoliberal economic doctrine (Harvey, 2007; Stedman Jones, 2012), Thaler and Sunstein (2008) argue that the libertarian aspect of nudge theory is found in the core notion that people “should be free to do what they like” (p. 6). In their work, Thaler and Sunstein directly quote Friedman’s refrain that individual freedom is constituted in being “free to choose” (Friedman & Friedman, 1980) the direction, character and quality of one’s life. The paternalistic aspect of nudge theory, on the other hand, establishes the idea that it is “legitimate” totry and inﬂuence people’s behaviour in order to make their lives longer, healthier, and better. In other words, we argue for self-conscious efforts, by institutions in the private sector and also by government, to steer people’s choices in directions that will improve their lives. (Thaler & Sunstein, 2008, p. 5)As such, nudging is ethically grounded upon the notion that the direction of human choice is valid if such an effort is consciously intended for the good of the individuals involved. and Sunstein’s nudge theory as a lens to understand the as a “choice architecture,” this section will identify a strongly libertarian paternalistic aspect behind the News Feed’s technical features that prompt increased user interactions over user passivity. Specifically, I will show how the nudging of Facebook users along pathways of active usership on the is always legitimated upon the basis that it will improve their health and well-being, namely by allowing them to fulfill their “natural” social essence and accrue social capital through their online relationships.

Output: contrast


Input: Claim: Rhizobacteria enhance plant growth by fixing atmospheric nitrogen in the soil. [SEP] Text: The suitability of DNA amplification was visualised by electrophoresis of PCR products with 6X loading dye (Thermo Scientific™) at 5:1 (PCR product: dye) ratio and a marker (1kb DNA ladder, Fermentas GeneRuler™) in 1% (w/v) agarose gel in 1X Tris-acetate EDTA (TAE) buffer for 1 h at 80 V. The agarose gel was stained with GelRed™ (Biotium Inc. ) for 40 min and examined under UV light in a UV transilluminator (Bio-Imager® Gel Doc™ XR+ System). Gel image was captured with software (Version 4. 1, Bio-Rad Laboratories) (S3 Fig). DNA fragments were extracted from the gel by slicing the target bands under UV light and purified using QIAquick gel extraction kit (Qiagen®). The purified DNA products were sent for sequencing by. Bhd. (www. base-asia. com) using BigDye® Terminator 3. 1 cycle sequencing kit (Applied BioSystems). The quality of 16S rDNA sequences was checked manually by using Software (version 2. 0). The sequences were analysed using the to identify the most closely related members in the database (www. ncbi. nlm. nih. gov/geo). The partial 16S rDNA sequences of the PGPR strains were submitted to the NCBI database under their respective accession number as follows: Bacillus subtilis UPMB10 (KP641618), Klebsiella sp. Br1 (KP257586), Klebsiella pneumoniae Fr1 (KP641617), Bacillus pumilus S1r1 (KP295962) and Acinetobacter sp. S3r2 (KP295963). Phylogenetic analysis The partial 16S rDNA sequences of UPMB10, Br1, Fr1, S1r1 and S3r2 were aligned with the most closely related bacteria sequences obtained from the NCBI database using [22]. The tree was constructed with Mega version 5 software package [23] by using the maximum likelihood method from distance calculated by the method of Kimura two-parameter model with a discrete Gamma distribution [24].

Output: pass