text:
Cold-hearted pet owner who left lizards in street is sought
This Dec. 21, 2019, photo released by the Stoughton Police Department shows one of six lizards the department rescued that had been abandoned on a street in Stoughton, Mass. Police said the lizards have been professionally cared for and are searching for the owner, in hopes someone would claim the reptiles. (Stoughton Police Department via AP)
STOUGHTON, Mass. (AP) — Police are searching for the owner of several lizards that were found in cages on a street in Massachusetts.
The Stoughton Police Department posted photos Saturday of six lizards it rescued in the hopes someone would claim the reptiles.
Police asked that the owner call the department to explain the abandonment of such "remarkably creepy yet shockingly majestic creatures."
The department said that it had an "overwhelming response" to the initial lizard post but that the owner had not been located as of Sunday afternoon.
The lizards are being professionally cared for, police said.
More Weird Stories
NJ high court overturns conviction over 'Shining' reference
TRENTON, N.J. (AP) — The New Jersey Supreme court has overturned a man's bank robbery conviction because of a prosecutor's reference to a classic horror movie.
During closing arguments in the case against Damon Williams, the prosecutor showed jurors a photo from the movie "The Shining" depicting a character played by Jack Nicholson telling his terrified wife and son, "Here's Johnny!" moments after breaking through a door with an axe.


The name's Alex. I'm currently majoring in Graphic Design at Cal Poly Pomona. When I'm not busy with schoolwork I like to practice hockey, watch some movies, modify my Nerf blasters, play with my Yamaha DTXpress drum set, or just chill with my friends.
Solar Lamp Hack to run off wall power!


This scary scene was photographed in Changchun in north-east China's Jilin Province.
It shows pedestrians using a highway lane divider in the middle of fast-moving traffic.
The strip is only about 3 feet wide and 0.6 miles long, according to Tencent News.
Their story was originally published saying that the so-called walkway was purposely installed their by local authorities, which wouldn't be surprising considering some of the strange things that happen in China.
However, bloggers were quick to point out that this isn't the case, and it's actually just fearless people choosing to use the strip as a footpath.


text:
The addition of Lactobacillus spp. negatively affects Mycoplasma bovis viability in bovine cervical mucus
A. García-Galán1,
C. De la Fe1,
J. Gomis2,
E. Bataller2,
A. Sánchez1,
J. J. Quereda2,
E. García-Roselló2 &
A. Gómez-Martín1,2
Mycoplasma bovis is an important pathogen for the cattle industry worldwide causing significant economic losses. Several transmission routes, including those related to reproduction, have been described. Indeed, the pathogen can colonize the female reproductive tract after artificial insemination (AI) with contaminated semen. Lactobacillus spp.-based probiotics have been used for vaginal dysbiosis treatment in women and cows although their role in controlling cervico-vaginal infections due to M. bovis is unknown. The objective of the present work is to assess the viability of M. bovis (PG45, NCTC 10131) in experimentally contaminated cervical mucus after the addition of Lactobacillus spp. at different concentrations as a competing agent and pH acidifier.
The addition of probiotic at a concentration higher than 108 colony forming units (CFU/mL had a detrimental effect (P < 0.05) on mycoplasma viability in cervical mucus. This coincided with a significant LAB growth and an important decrease in pH from 8.4 to 5.6 (P < 0.05). However, after the addition of less concentrated probiotic, M. bovis survival was not affected and there was no significant LAB growth despite the drop of pH from 8.4 to 6.73 (P < 0.05).
The addition of concentrations higher than 108 CFU/mL of Lactobacillus spp. negatively affects M. bovis viability in bovine cervical mucus under in vitro conditions. Although the effect observed on the pathogen viability seems to be related to the pH decrease after LAB proliferation in cervical mucus, further studies are necessary to elucidate if other factors are implicated. Nevertheless, the administration of Lactobacillus spp.-based probiotics might be used in the future to control M. bovis proliferation in the cervico-vaginal tract of cows.
Mycoplasma bovis is a major etiological agent of bovine mycoplasmosis, widely distributed and responsible for important economic losses hardly quantifiable [1]. The complex epidemiology of the infection frequently complicates the establishment of effective control measures. In this sense, the transmission capacity of M. bovis by natural breeding and artificial insemination (AI) has been described, even when using semen extenders supplemented with antimicrobials. The pathogen may cause reproductive disorders such as endometritis, salpingitis, oophoritis, infertility, and abortion [2, 3]. Moreover, semen was the source of M. bovis mastitis outbreaks in two closed dairy herds in Finland [4].
In the case of some animals, M. bovis has been recovered up to 8 months after insemination in cervico-vaginal mucus [2]. Cervical mucus is a hydrogel secreted in the cervical endothelium and it is composed of water in more than 90% as well as soluble and non-soluble particles [5,6,7]. Additionally, antimicrobial peptides have been isolated in cervical mucus and they could play a fundamental role in preventing infections [8]. However, the viability of M. bovis does not seem to be affected by cervical mucus [2].
As M. bovis can survive the entire fertilization process and generate infected embryos [9], many strategies based on the use of antimicrobials have been used to control its presence in semen [10, 11]. However, the in vitro antimicrobial susceptibility of the majority of M. bovis circulating strains has declined dramatically in recent years [12, 13]. On the other hand, Lactobacillus spp.-based probiotics have been used for vaginal dysbiosis treatment in women as they have shown germicidal action against pathogenic bacteria by competing for resources, stimulating the host immune system, and producing organic acids which decrease pH [14,15,16]. Lactic acid bacteria (LAB) of the genus Lactobacillus are part of the vaginal saprophytic flora of cows although at low abundances [17, 18]. The intravaginal administration of LAB in periparturient cows can modulate the incidence of purulent vaginal discharges, expedite the uterine involution and lower the incidence of uterine infections [19,20,21]. Nevertheless, the role of LAB in controlling cervico-vaginal infections due to M. bovis presence still has to be studied.
Mycoplasmas lack a cell wall and therefore they are very sensitive to external changes such as pH variations [22]. In this sense, several authors have observed the effectiveness of the medium acidification to control the growth of mycoplasmas [23,24,25]. In cows, the in vivo pH of the cervical mucus is generally about 6.8 and rises to about 7.6 to 8.1 during estrus [5, 26, 27]. These pH values could promote the survival of mycoplasmas whose optimal pH for growing ranges from 7.3 to 7.8 [28]. Therefore, we wonder whether the addition of LAB as competing agents and pH acidifiers to cervical mucus may affect the viability of M. bovis.
This work was conducted to assess the viability of M. bovis in cervical mucus after the addition of Lactobacillus spp.-based probiotic at different concentrations under in vitro conditions.
Seven in vitro conditions were prepared in cervical mucus and/or modified SP4 to evaluate the viability of M. bovis after the addition of different concentrations of Lactobacillus spp. (Table 1). The statistical analysis revealed that the analytical condition, the time, and their interaction significantly contributed to the variation in pH, the log colony forming units (CFU)/mL of M. bovis and the log CFU/mL of LAB.
Table 1 Experimental conditions evaluated
The impact of each analytical condition on M. bovis survival, disregarding the time, is shown in Table 2. No differences were found between conditions 1 and 4 (P > 0.05). Significant differences were found between the equivalent conditions 1 and 4, and the conditions 5, 6 and 7, which were also statistically different from each other (P < 0.05). A detrimental effect (P < 0.05) on the mycoplasma viability was observed when adding L2 in cervical mucus (condition 5). However, this effect was not observed after adding L1 (condition 4) being M. bovis viability equal than in contaminated cervical mucus without probiotic (condition 1). The addition of probiotic in SP4 (conditions 6 and 7) did not affect the survival of the mycoplasma, whose concentration was higher (P < 0.05) than in cervical mucus conditions (1, 4 and 5).
Table 2 Least squares means of log CFU/mL of M. bovis
The impact of the time on the pH, log CFU/mL of M. bovis and log CFU/mL of LAB under each condition is shown in Table 3. In cervical mucus without probiotic addition (condition 1), neither significant variation of pH nor M. bovis concentration was observed. Under this condition, LAB were quantified, even though neither L1 nor L2 had been added. The inoculums L1 and L2 were viable in cervical mucus and LAB concentration increased over time while pH decreased (P < 0.05; Conditions 2 and 3). In any case, the pH decrease was higher when adding L2 (8.40 to 5.60) that when adding L1 (8.4 to 6.64). No significant increase of LAB concentration was observed in contaminated cervical mucus after adding L1 (condition 4) and M. bovis grew significantly despite the drop of pH from 8.4 to 6.73 (P < 0.05). On the other hand, the LAB grew significantly in contaminated cervical mucus after adding L2 and M. bovis viability was negatively affected since no viable colony was counted (P < 0.05; Condition 5). That concurred with an important reduction in pH from 8.4 to 5.6 (P < 0.05). Finally, neither significant LAB growth nor pH variation was observed in SP4 inoculated with L1 or L2 while M. bovis grew significantly (conditions 6 and 7).
Table 3 Least squares means of pH and log CFU/mL of M. bovis and LAB by time
Under in vitro conditions, the survival of M. bovis in cervical mucus was affected by the addition of Lactobacillus spp.-based probiotic at a concentration of 3.24 × 108 CFU/mL. On the contrary, the addition of 3.24 × 106 CFU/mL of Lactobacillus spp. did not have a detrimental effect on mycoplasma survival.
Our results suggest that the negative impact on the pathogen viability may depend on the dose of probiotic added to cervical mucus. Other authors previously observed that bovine vaginal lactobacilli at a dose of 108–109 CFU/mL were able to modulate the incidence of purulent vaginal discharges, expedite the uterine involution and lower the incidence of uterine infections, in periparturient dairy cows [19,20,21]. On the other hand, L1 was previously inoculated vaginally in an ovine experimental model without producing alterations in the ewes health status and without negatively affecting their fertility, either [29]. It must be stated that the evidence of positive effects from that preliminary study (increases in fertility percentage and decrease in the percentage of vaginal neutrophils) were not significant. Overall, the negative effect on M. bovis viability caused by the addition of L2 but not L1, together with the observations of previous studies, suggests that further in vivo studies should consider the inoculation with L2.
It is known that vaginal Lactobacillus spp. can inhibit the growth of genitourinary pathogenic microorganisms through different mechanisms such as the production of organic acids that reduce pH [15, 16]. As mycoplasmas do not synthesize the cell wall, they are sensitive to external changes such as pH and osmotic variations [22]. We hypothesized that by adding Lactobacillus spp.-based probiotics in cervical mucus the survival of M. bovis could be affected due to the acidification of the medium after LAB proliferation. In effect, M. bovis was negatively affected by the addition of L2 in cervical mucus after 15 h in incubation. That concurred with a significant reduction in pH from 8.4 to 5.6. Previous studies have reported the effectiveness of the medium acidification to control the growth of mycoplasmas. For instance, the acidification to pH 4 during 1 h was enough to eliminate viable M. bovis organisms in milk [23]. We also found out that the viability of M. bovis was negatively affected by the addition of L2 in diluted bull semen which coincided with a significant decrease of pH after 15 h in incubation [25]. Other authors observed a harmful effect on Mycoplasma agalactiae and Mycoplasma mycoides subsp. capri when diluting contaminated goat ejaculate in an acidic semen extender (pH ≤ 6) [24]. On the contrary, the abnormally elevated vaginal pH (> 4.5) in women with bacterial vaginosis may promote the survival of Mycoplasma genitalium [30]. On the other hand, the addition of L1 in cervical mucus did not have a negative impact on M. bovis survival. Although no significant LAB growth was observed, it must be noted that these bacteria remained viable in cervical mucus. Indeed, the significant decrease of pH from 8.40 to 6.73 in cervical mucus with M. bovis and L1 (condition 4) could be a consequence of the living bacteria metabolism.
The survival of M. bovis was not compromised in untreated cervical mucus whose concentration remained constant after 15 h in incubation. We believe that the cervical mucus composition could benefit the pathogen growth. As mycoplasmas have a small genome size, their metabolic activities are limited and they are largely dependent on external sources. Indeed, the cervical mucus soluble part contains basic elements for mycoplasmas growth and survival, including lipids such as cholesterol, proteins, amino acids, and carbohydrates [5, 31]. Besides, LAB were quantified in cervical mucus contaminated with M. bovis but without neither L1 nor L2. This was an expected result since previous authors have isolated LAB from the bovine vagina [17]. Other authors found that Lactobacillus spp. were prevalent among cows microbiota, although at low abundances, and they associated the near-neutral pH observed in the cow's vagina with the low abundances of this bacterial genus [18].
The inoculums L1 and L2 were viable in cervical mucus without M. bovis, and a significant LAB growth was observed after 15 h in incubation. This concurred with a significant reduction in pH from 8.4 to 6.64 in condition with L1 and from 8.40 to 5.60 in condition with L2. Synergies occurring with the saprophytic cervical mucus flora or the presence of nutrients in this medium might promote the survival of L1 and L2 [5, 17, 18, 31]. Undoubtedly, this is an important finding from a preventive point of view because the administration of LAB 15 h before AI could reduce the vaginal pH and complicate the proliferation of semen contaminating bacteria. Nevertheless, at this point, we can only make assumptions that should be further investigated in living animals.
Overall, our results suggest that the vaginal administration of probiotics might be useful to control M. bovis proliferation in the cervico-vaginal tract of cows. This could be an interesting tool to minimize the risk of colonization that might occur after AI with contaminated bovine semen. On the other hand, the preventive administration of probiotics before insemination might create an inhospitable acid environment for the semen contaminating bacteria which could prevent their proliferation.
Notwithstanding such interesting results, the present assay has certain limitations: (i) Only PG45 was used for the experiments and therefore, additional M. bovis field isolates should be tested in the future. (ii) This is an in vitro study and our results may change in living animals. Developing an experimental model of vaginal contamination in those animals could be interesting to explore the impact of probiotics on M. bovis viability under in vivo conditions.
Under the present in vitro conditions, we can confirm the susceptibility of the reference strain PG45 to the addition of Lactobacillus spp. at a concentration higher than 108 CFU/mL in bovine cervical mucus. Our results suggest that the administration of probiotics via vaginal might be useful to control M. bovis proliferation in the cervico-vaginal tract of cows.
Animals and cervical mucus samples
Samples from ten different Holstein Friesian dairy cows between one and five deliveries, from a commercial farm in Murcia (Spain), were obtained for this assay on three different days from July to November of 2018. The first sampling was carried out in July and the second and the third samplings in November (with a time interval of 20 days). Five, three and two samples were respectively collected on day 1, 2 and 3 from healthy cows and free of abnormal genital discharges or anatomical abnormalities of the reproductive tract. The animals were immediately released after collecting the samples. The animals were randomly selected from a herd of approximately 800 cows officially free of tuberculosis, brucellosis and enzootic bovine leukosis, and without any other notifiable disease in Spain [32]. The herd had no history of clinical outbreaks associated with M. bovis in the past 10 years. No mycoplasmas were detected in the bulk tank milk during the year of the study.
An Ovsynch protocol [33] was used for heat and ovulation synchronization and the samples were obtained during estrus and before AI. For sample collection, two technicians were necessary. We first emptied the fecal contents of the rectum. Once free of feces, the vulva and the perineal region were washed with soap and water, rinsed with water, dried with sterile gauze swabs and disinfected with a chlorhexidine solution. The samples were obtained by transrectal massaging of the cranial cervix and placed in 100 ml sterile plastic bottles. The samples were immediately placed on ice in an isothermal box and transported to the laboratory within 1 h [34].
Each day, samples contaminated with feces were discarded and a pool of cervical mucus was obtained by mixing clean samples. Thereby, three samples on day 1, and two samples on days 2 and 3 were finally selected for the study.
Only cows free of cervical M. bovis were used in the present study. The absence of mycoplasmas in cervical mucus samples was confirmed by culture in mycoplasmas specific media and the presence of M. bovis was further discarded by polymerase chain reaction (PCR) [35].
Preparation of modified SP4 medium
The medium SP4 was prepared following previous recommendations [36] but with some modifications. The modified medium is composed of three parts (A, B and C). Part A is composed of 4.2 g of Difco PPLO broth (BD), 6.4 g of Bacto Peptone (BD), 12 g of Bacto Tryptone (BD) and 724 mL of deionized water. The solid medium includes 7 g of European Bacteriological Agar (Conda-Pronadisa). The pH is adjusted to 7.8 and then part A is autoclaved at 121 °C for 20 min. Part B is composed of 60 mL of RPMI-1640 (Sigma-Aldrich), 21 mL of fresh yeast extract 50% w/v, 2.4 g of yeast extract (Conda-Pronadisa), 4.8 mL of phenol red 0.5%, (Sigma-Aldrich) and 0.642 g of ampicillin sodium salt (Fisher bioreagents). The pH is adjusted to 7.2 and then part B is filter sterilized through a 0.22 μL pore size filter. Part C is composed of 251 mL of heat-inactivated horse serum (Hyclone) for 30 min at 56 °C. Note that, in this study, the SP4 broth medium did not include ampicillin in part B.
Preparation of the M. bovis and Lactobacillus spp. inoculums
An inoculum of M. bovis (1 × 109 CFU/mL) and two inoculums of Lactobacillus spp., L1 (3.24 × 106 CFU/mL) and L2 (3.24 × 108 CFU/mL) were prepared in a modified broth SP4 as previously described [25]. The reference strain PG45, and the lyophilized commercial probiotic, NS Femibiotic®, based on a mix of Lactobacillus crispatus, Lactobacillus gasseri and Lactobacillus brevis, were employed for preparing the inoculums of M. bovis and L1 and L2 respectively.
Seven in vitro conditions were experimentally prepared in cervical mucus and/or modified SP4 following an experimental protocol previously described [25].
Table 1 shows the volumes of cervical mucus, SP4, and M. bovis and Lactobacillus spp. inoculums that were used to elaborate each condition. Conditions 1, 2 and 3 were controls prepared to assess the viability of M. bovis and Lactobacillus spp. (L1 and L2) in cervical mucus. No controls were included in SP4 because the viability of these bacteria in this medium had been confirmed before the experiment. Conditions 6 and 7 were only included to verify if the viability of M. bovis would be affected by the addition of probiotic in a medium for mycoplasmas growing such as SP4.
The experimental conditions were carried out in eppendorf tubes: Firstly, cervical mucus or SP4 were added to the corresponding tubes followed by the inoculation with M. bovis and/or the inoculation with L1 or L2. The tubes were then incubated at 37 °C for 15 h (h15) and hour 0 (h0) was set after 15 min of incubation. Counts of M. bovis and LAB were made at 0 and 15 h. At h0, the counts were made to estimate the real concentration of bacteria present in each experimental condition at the beginning of the experiment. The next determination was performed at h15 to give the probiotic enough time for growing and acidifying the cervical mucus, and so any effect on M. bovis viability could be seen. Furthermore, pH measurements were made at both times.
Three replicates of the assay were conducted on different days (one replicate for each day of sample collection).
Determination of M. bovis and LAB viability
Counts (CFU/mL) of M. bovis and LAB were conducted on SP4 and MRS agar following a protocol previously described [25]. The counts of M. bovis were only conducted in conditions contaminated with the mycoplasma (Table 1, n = 5) while the counts of LAB were determined in the seven conditions.
Bacterial counts were converted to log (1 + C), being C the count of CFU/mL measured for each organism and analytical condition. Statistical analyses were conducted with a general linear procedure implemented in the program Statistical Analysis System (SAS) [37] according to the model: Yijk = μ + Si + Cj + Tk + CTjk + eijk where Yijk = pH and log CFU/ml of M. bovis and log CFU/mL of LAB (dependent variables); μ = mean; Si = sample effect; Cj = effect of experimental conditions; Tk = effect of time; CTjk = effect of the interaction experimental condition-time; eijk = residual effect.
The datasets used and analyzed during the current study are available from the corresponding author on reasonable request.
AI:
Colony-forming units
CM:
LAB:
Lactic acid bacteria
L1:
Lactobacillus spp. at a concentration of 3.24 × 106 CFU/ mL
Lactobacillus spp. at a concentration of 3.24 × 108CFU/ mL
MB:
Mycoplasma bovis
SAS:
Statistical analysis system
SEM:
Standard error of the mean
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The authors are grateful to the farmers for allowing the collection of samples.
This work has been supported by the Spanish Ministry of Economy and Competitiveness (Spanish Government) co-financed by FEDER funds (project AGL2016–76568-R) by Universidad CEU Cardenal Herrera (project PRCEU-UCH 04/11), and by program FUSP-Santander (To Ángel Gómez-Martín). The funders had no role in the design of the study, collection, analysis and interpretation of data, and in writing the manuscript. Ana García-Galán Pérez is a beneficiary of a research fellowship (State Subprogram Training of the State Program for the Promotion of Talent and its Employability, BES-2017-080186). Juan J. Quereda is supported by a "Ramón y Cajal" contract of the Spanish Ministry of Science, Innovation and Universities (RYC-2018-024985-I).
Ruminant Health Research Group, Department of Animal Health, Faculty of Veterinary Sciences, Regional Campus of International Excellence "Campus Mare Nostrum", University of Murcia, 30100, Murcia, Spain
A. García-Galán, C. De la Fe, A. Sánchez & A. Gómez-Martín
Microbiological Agents Associated with Reproduction (ProVaginBio) Research Group, Universidad Cardenal Herrera-CEU, CEU Universities, 46113, Valencia, Spain
J. Gomis, E. Bataller, J. J. Quereda, E. García-Roselló & A. Gómez-Martín
A. García-Galán
C. De la Fe
J. Gomis
E. Bataller
A. Sánchez
J. J. Quereda
E. García-Roselló
A. Gómez-Martín
AGG intervened in the entire experimental process and statistical analysis and drafted and edited the manuscript. CDF designed and directed the study and drafted, edited and reviewed the manuscript, project administration and funding acquisition JG, EB, and EGR collaborated in the experimental process and reviewed the manuscript. AS contributed to the analytical part of the study and reviewed the manuscript. JJQ designed, collaborated in the experimental process and reviewed the manuscript. AGM designed and directed the study and reviewed and edited the manuscript, project administration and funding acquisition All authors read and approved the final manuscript.
Correspondence to C. De la Fe.
All animal procedures were performed following the EU Directive 2010/63/EU for animal experimentation. Verbal informed consent was obtained from the owner of the animals and this procedure was approved by the committee of the General Directorate of Agriculture, Livestock and, Fisheries of Valencian Community (2017/VSC/PEA/00245) and the University of Murcia committee (REGA ES300305440012).
García-Galán, A., De la Fe, C., Gomis, J. et al. The addition of Lactobacillus spp. negatively affects Mycoplasma bovis viability in bovine cervical mucus. BMC Vet Res 16, 251 (2020). https://doi.org/10.1186/s12917-020-02454-9
Lactobacillus spp.

redpajama_set_name: RedPajamaCommonCrawl


text:
Indifly Announces the Indifly Corps — A New Monthly Giving Program with Benefits
SAINT PAUL, Minn. (October 29, 2019) — Indifly is pleased to announce the Indifly Corps — a monthly giving program that allows donors to support Indifly's efforts while making a stronger connection to their work. As a group of monthly givers on a mission to improve indigenous communities, Indifly Corps donors will become important investors in supporting Indifly's community partners.
Indifly, a nonprofit organization, uses fly fishing as a tool for transforming the lives of indigenous peoples and protecting valued environments. In an effort to increase their initiatives at the Rewa Eco-Lodge in Guyana, the Wind River Indian Reservation in Wyoming, Anaa Atoll in French Polynesia, and future projects currently in development, Indifly is inviting donors to become sustaining members.
By joining Indifly Corps, donors commit to making a $20 recurring gift each month, which will help Indifly continue to make an impact on the communities they serve. The Indifly Corps gives donors access to special benefits, including exclusive content, entry into a monthly giveaway (with items such as exclusive Indifly apparel, Costa Sunglasses, drinkware from YETI, and gear from other partners), and an annual giveaway of a hosted trip to an Indifly destination.
"Indifly creates sustainable, local economies that empower communities to conserve natural resources," explains Indifly Executive Director Matt Shilling. "We are excited to launch the Indifly Corps as a vehicle to engage people in our cause. These are not meant to be passive donations — we want Indifly Corps members to feel connected and invested in our mission. For less than 66 cents a day, individuals can have a big impact on the communities we serve."
The first 100 people who join will get a limited edition Indifly YETI Rambler. Learn more at indifly.org/indiflycorps.
About Indifly:
Indifly is a nonprofit organization that uses fly fishing as a tool for transforming the lives of indigenous peoples and protecting valued environments. Indifly works to create sustainable local economies that empower communities to conserve natural resources. Current Indifly projects include Rewa, Guyana, Anaa Atoll, French Polynesia, and the Wind River Indian Reservation in Wyoming.
For more information about Indifly, please visit indifly.org and follow them on Facebook, Instagram, and Twitter.
Posted in environment, misc.Tagged Indifly
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August 15, 2014 – Beginning August 18, Fort Valley State University will implement a new system-wide policy that prohibits the use of tobacco products on campus.
FVSU will officially become a tobacco and smoke-free campus to be in line with with the new University System Board of Regents Policy 9.1.7 that was approved in March 2014. The policy states that the use of all forms of tobacco products on campus is prohibited.
To officially launch the new campaign, the University System of Georgia held a kickoff meeting with all 31 member institutions at Middle Georgia State College's Macon campus in July. Members of the university's Tobacco and Smoke-Free Council were in attendance, including Hobbs, Human Resources Director Tricia Addison, provost and vice president for Academic Affairs Dr. Jessica Bailey, associate vice president of Business and Finance Dr. Dwayne Crew, and Dean of Students Wallace Keese.
FVSU formed a Tobacco and Smoke-Free Council, which submitted a smoke free policy draft to the university's Administrative Council. It was unanimously approved.
The new policy expressly prohibits the use of all forms on tobacco products on property owned, leased, rented or possessed by FVSU. "Tobacco products" are defined as cigarettes, cigars, pipes, all forms of smokeless tobacco, clove cigarettes, and any other smoking devices that use tobacco, such as hookahs, or simulate the use of tobacco, such as electronic cigarettes.
The policy also bans any tobacco-related advertising, the sale of free tobacco-related samples and products on all university properties, unless it is being used for research purposes.
Additionally, the use of tobacco products is prohibited in all vehicles – private or public – on FVSU properties, and applies to all persons entering the campus area including faculty, staff, contractors, subcontractors, spectators and visitors. The regulations also require that all events held by outside entities on campus will be required to be tobacco free.
The Georgia Tobacco Quit Line is available for individuals wanting to quit tobacco use. The Georgia Tobacco Quit Line is a public health service funded by the Georgia Department of Public Health (DPH) through the Georgia Tobacco Use Prevention Program (GTUPP). GTUPP partners with a national tobacco cessation vendor to provide telephone and web-based counseling services in accordance with the United States Public Health Service Treating Tobacco Use and Dependence Clinical Practice Guidelines.
It's a free, confidential and effective service available to assist Georgians with quitting smoking and all forms of tobacco.


text:
Der Neue St.-Nikolai-Friedhof in Hannover, auch Strangrieder Friedhof genannt, wurde 1863 bis 1866 zwischen der Strangriede und der Militärstraße (heutige Appelstraße) angelegt. Das von Universitätsgebäuden, Krankenhaus, Wohnhäusern und Villen umgebene Friedhofsgelände ist parkförmig gestaltet. Im Zentrum steht die 1890 nach Plänen von Friedrich Hölscher (1859–?) erbaute neugotische Backstein-Kapelle.

Standort des in seiner Gesamtanlage auch als Gartendenkmal geschützten Geländes ist die Straße An der Strangriede 41 in der Nordstadt von Hannover.

Geschichte
Der Neue St.-Nikolai-Friedhof ersetzte den innenstadtnahen Alten St.-Nikolai-Friedhof. Die Einweihung fand am 1. Juni 1866 statt. Das Eingangsgebäude, entworfen von Stadtbaumeister Ludwig Droste (1814–1875), wurde im Zweiten Weltkrieg bei den Luftangriffen auf Hannover beschädigt und trotz der Möglichkeit des Wiederaufbaus (Rekonstruktionsplanung von Rudolf Steinmeier, 1946) 1960 abgerissen und durch einen funktionalen Backsteinbau (Architekt Alfred Müller-Hoppe) ersetzt. Auf dem ca. 5 ha großen Friedhofsgelände befinden sich die Grabstätten vieler stadtbekannter Persönlichkeiten.

Grabdenkmäler (Auswahl)

 Grabstätte(n) der Familie Bahlsen, darunter Hermann Bahlsen (1859–1919), Keksfabrikant, und Hermann Bahlsen (1927–2014)
 Grabstätte der Familie Harro Boit
 Grabstätte der Familie Benecke
 Grabstätte der Familie Buchholz, darunter Hermann Buchholz (1853–1911), Direktor der Schmirgelfabrik – heute VSM; Hans Buchholz (1893–1990), Werbeberater, Mitbegründer der Werbefachschule Hannover, Träger des Bundesverdienstkreuzes 1. Klasse; Rosemarie Buchholz geb. Le Tanneux von Saint Paul (1916–2004) (Adelsgeschlecht Le Tanneux von Saint Paul).
 Theodor Colshorn (1821–1896), Schriftsteller
 Hans Albert Dietrich (1886–1963), Gynäkologe
 Familie Hahn
 ehemaliger Standort des Grabsteins von Jobst Anton von Hinüber (der zuvor auf dem Alten St. Nikolai Friedhof stand)
 Fritz Kahle (1871–1944)
 Friedrich Kochheim (1891–1955), Ingenieur und Unternehmer, KZ-Häftling
 Hans Kopfermann (1895–1963), Experimentalphysiker
 Grabmal der Familie Kraul
 Walther Lampe (1894–1985), Jurist und Kirchenbeamter
 Grabstätte der Familie von Linsingen, darunter Alexander von Linsingen (1850–1935), Generaloberst
 Wilhelm Maxen (1867–1946), Priester, Politiker, Mitglied der Zentrumspartei, Mitglied der Preußischen Landesversammlung und Mitglied des Deutschen Reichstags
 Karl Mohrmann (1857–1927), Architekt
 Grabmal von Max Müller (1850–1912), ebenso Grabstätten-Bezifferung 11b
 Constantin Nordmann (1805–1889), Architekt
 Peter von Oertzen (1924–2008), deutscher Politiker
 Heinrich Rätz (1884–1943) und Frau; der Kriminalkommissar leitete die Ermittlungen gegen den Serienmörder Fritz Haarmann
 Grabmal von Hans Rüpcke (1850–1954) und Maria Rüpcke (1897–1977)
 Gustav Sasse (1904–1969), Organist und Dirigent
 Grabmal der Familien Schmorl und Fiedler
 Karl Siebrecht (1875–1952), Architekt
 Carl Sievers (1867–1925), Obermeister des deutschen Schneiderhandwerks und Abgeordneter beim Deutschen Reichstag
 Bernhard Sprengel (1899–1985), Schokoladenfabrikant und Kunstsammler
 Hubert Stier (1838–1907), Architekt
 Hans Stille (1876–1966), Geologe
 Hermann Wendland (1825–1903), Botaniker und Oberhofgärtner der Herrenhäuser Gärten (Familiengrab)
 Hans-Oskar Wilde (1907–1981), Anglist
 Marie Alice Wittmann († 3. Mai 1959), Witwe des jüdischen Emigranten Konrad Wittmann

Siehe auch
 Friedhöfe in Hannover

Literatur
 Claus Conrad: Neuer St. Nikolai Friedhof. Geschichte, Biografische Skizzen und Wegweiser (aufklappbare Übersichtskarte), hrsg. vom St. Nikolai Stift zu Hannover, Hannover: Selbstverlag, 2016
 Herbert Mundhenke: Hospital und Stift St. Nikolai zu Hannover. In: Hannoversche Geschichtsblätter, Neue Folge 11 (1958), hier: S. 230–234
 Peter Schulze: Nikolaifriedhof (II) Neuer St. Nikolai Friedhof. In: Klaus Mlynek, Waldemar R. Röhrbein (Hrsg.) u. a.: Stadtlexikon Hannover. Von den Anfängen bis in die Gegenwart. Schlütersche, Hannover 2009, ISBN 978-3-89993-662-9, S. 476f.

Weblinks

 Seite des Neuen St. Nikolai Friedhof

Einzelnachweise

Christlicher Friedhof in Hannover
Baudenkmal in Hannover
Nordstadt (Hannover)
Erbaut in den 1860er Jahren
Hannover Nikolai
Hannover

redpajama_set_name: RedPajamaWikipedia


Vessel Vanguard has a challenge making a very complicated service offering understandable and then indispensable. All while increasing awareness for a new category of product that people don't even know they need: an online/mobile boat maintenance management solution. The Vessel Vanguard Puzzle Ad, one example from the dichotomy campaign, makes it clear that Vessel Vanguard answers questions, increases clarity and ensures your boat is in good shape and ready to go whenever you are. The first part of the dichotomy, "Puzzling," presents a problem that a customer might not know they have. This is contrasted with a benefit, "picture perfect," that they can expect to enjoy. Other dichotomies in the campaign include "From in your head…to in your hand" promoting it is a mobile solution, and "From buyer…to lifelong customer" promoting it to boat dealers as consumer benefit they can offer their customers.


text:
elodie-meheust » Rock » Stormtroopers Of Death - 20 Years Of Dysfunction
Stormtroopers Of Death - 20 Years Of Dysfunction album download
Stormtroopers Of Death Thrash 2005
Performer: Stormtroopers Of Death
Title: 20 Years Of Dysfunction
Style: Thrash
Format: MP3 FLAC MIDI DTS AU ADX MP2 AHX DXD
Band Name Stormtroopers Of Death. Album Name 20 Years of Dysfunction. DVD and cds marking the Band's 20 Anniversary. DVD. -Live in European Festivals.
20 Years of Dysfunction. Stormtroopers of Death. East 17-Douche Crew 18-Vitality (Milk Part II) 19-Pre-Menstrual Princess Blues 20-Diamonds And Rust 21-Chromatic Death 22-Ballad Of Jimi Hendrix 23-Ballad Of Jimi Hendrix 24-Ballad Of Jimi Hendrix 25-Freddy Kreuger 26-Not. Stormtroopers of Death Discography.
Stormtroopers of Death (abbreviated to . were an American crossover thrash band formed in New York City in 1985. The band is also known for reuniting Anthrax members Scott Ian (guitars) and Charlie Benante (drums) with their former bassist Dan Lilker. The song "Chromatic Death" from their 1985 debut album, Speak English or Die, was the Headbanger's Ball intro anthem for many years. The band were the source of some controversy due. 20 Years of Dysfunction. Nuclear Blast Records.
Hard to believe Megaforce is still a label, but here you have it, their latest, a DVD from legendary NYC hardcore/metal crossover kings Stormtroopers of Death. This DVD contains tons of live footage, all of which is of the hand-held, bootleg variety. They're great live, but unfortunately there's no classic footage here. And the band's second album is quite ignored, which is okay but weird. As a cool bonus, this package also includes a bonus CD with the 1985 Pussywhipped bootleg, with the band finally reclaiming a piece of history as they "bootleg the bootleggers
Live at Budokan is a live album released by American crossover thrash band Stormtroopers of Death. The album is a recording of a one-off re-union gig put on by the band, and includes the majority of the longer tracks from their first album and some previously unheard tracks, as well as covers of the bands . Ministry, Nirvana, and Fear.
Speak English Or Die. 2:20. Theres a similar version . Stormtroopers Of Death - Speak English Or Die with slightly different labels and runouts. Misprint on B-side label, track 3 is titled "Pre-Mentrual Princess Blues" and track B9 is titled "Hey Gordy 1/2". Matrix, Runout (Side A, stamped): 08 25036 20 1A1 9725 1. Matrix, Runout (Side B, stamped): 08 25036 20 1B1 9725. Matrix, Runout (Label side A): 08-025036-20-1. Matrix, Runout (Label side B): 08-025036-20-2. Rights Society: STEMRA. Other Versions (5 of 57) View All. Cat.
Stormtroopers of Death скачать в mp3 на телефон или слушайте песню Piano Tribute Players - Sexy Love, Piano Tribute Players - Sexy Love, Stormtroopers of Death - United Forces, Stormtroopers of Death - Kill Yourself, Stormtroopers of Death - Speak English Or Die и другие популярные треки и рингтоны. STORMTROOPERS OF DEATH – 20 - Ballad Of Jimi Hendrix ( Speak Englis. :28. Stormtroopers of Death – March Of The .
Classics like "Milk," "Chromatic Death," and "Kill Yourself" are here in all their offensive glory. The enthusiastic crowd helps the mood of the album, and certain songs are changed enough to give them an interesting spin. A good example is "Speak English or Die!," which places the opening riff to Slayer's classic "Raining Blood" in the middle of the song. The covers are good, although .
STORMTROOPERS OF DEATH скачать mp3 в хорошем качестве, либо слушайте песню Piano Tribute Players - Sexy Love, Piano Tribute Players - Sexy Love, Stormtroopers of Death - United Forces, Stormtroopers of Death - Kill Yourself, Stormtroopers of Death - Speak English Or Die, а также рингтоны на звонок и все новые треки. STORMTROOPERS OF DEATH – 18 - Douche Crew ( Speak English Or Die . :32. D Stormtroopers Of Death – Milano Mosh. Stormtroopers of Death (. – What s That Noise. D Stormtroopers Of Death – Speak English Or Die. 1:00. Stormtroopers Of Death – What s That Noise. Stormtroopers of Death – Sargent D And The . Stormtroopers of Death – Fist Banging Mania. Stormtroopers of Death – Ram It Up (Live in Tokyo 1999).
Pussy Whipped CD Bootleg Recorded Live City Gardens, New Jersey 10/6/1985 (3rd Show Ever)
CD1 Diamonds And Rust
CD2 What's That Noise
CD3 March Of The S.O.D.
CD4 Fistbanging Mania
CD5 Milano Mosh
CD7 Milk
CD8 Pi Alpha Nu
CD9 Ram It Up
CD10 United Forces
CD11 No Turning Back
CD12 Kill Yourself
CD13 Momo
CD14 Speak English Or Die
CD15 Anti Procrastination Song
CD16 Fuck The Middle East
CD17 Douche Crew
CD18 Vitality
CD19 Premenstrual Princess Blues
CD20 Diamonds And Rust
CD21 Cromatic Death
CD22 Ballad Of Jimi Hendrix
CD25 Freddy Krueger
CD26 Not
DVD Track List
DVD1 Intro
DVD2 Sgt. D & The S.O.D.
DVD3 Shenanigans 1
DVD4 Kill Yourself
DVD5 About Milano Mosh
DVD6 Milano Mosh
DVD8 Speak English Or Die
DVD10 Chromatic Death
DVD11 Fist Banging Mania
DVD12 About Scott Ian
DVD13 Pi Alpha Nu
DVD14 Shenanigans 4
DVD15 Ballads
DVD16 No Turning Back
DVD18 Fuck The Middle East
DVD19 Douche Crew
DVD20 About Danny Lilker
DVD21 Milk
DVD23 Freddy Krueger
DVD24 About Charlie Benante
DVD25 Pussywhipped
DVD27 United Forces
DVD28 End Credits
DVD29 Best Of S.O.D. Live : European Festivals
DVD30 Best Of S.O.D. Live : U.S.A.
DVD31 Best Of S.O.D. Live : Germany
DVD32 Best Of S.O.D. Live : Holland
DVD33 Best Of S.O.D. Live : Japan
DVD35 March Of The S.O.D. / Sgt. D & The S.O.D.
DVD36 Bonus Material
20th Anniversary DVD Release Comprised Of Fan Filmed Footage And Interviews.
The Bonus CD is the Pussywhipped Bootleg Recorded Live City Gardens, Trenton, New Jersey October 6, 1985. This Is The Band's Idea Of "Bootlegging The Bootlegger" As They Took What Used To Be An Unofficial Recording and Added It To This Official Release.
Related to Stormtroopers Of Death - 20 Years Of Dysfunction
Jimi Hendrix - Attention! Jimi Hendrix album mp3
Jimi Hendrix - The Essential Jimi Hendrix album mp3
The Jimi Hendrix Experience - The Guitar Wizzard album mp3
Jimi Hendrix - Hendrix Bootleg & Singerbowl album mp3
Jimi Hendrix - The Cry of Love album mp3
Jimi Hendrix - The Jimi Hendrix Concerts album mp3
Buddy Holly - Rock 'N' Roll Master Works album mp3
The Jimi Hendrix Experience - Freedom: Atlanta Pop Festival album mp3
S.O.D.: Stormtroopers Of Death - Speak English Or Die album mp3
Jimi Hendrix Experience - Hey Joe album mp3


In an interview with Christian Broadcasting Network's David Brody, Sen. Ted Cruz accused the sitting president of having a "Messiah complex," and in a pretty overt stab at the current Republican frontrunner, accused Donald Trump of the same malady.
This election is not about any one person, any one individual who believes he or she will make America great. You know what, for seven years we've had a president in the White House who has had a Messiah complex.
Curiously, in the same interview, Cruz also ripped into Trump for his willingness to reach across the aisle and negotiate with Democrats. "If you think the problem with Republican leadership is that they haven't been willing enough to cut deals, then maybe you ought to vote for Donald," Cruz said.
So is Trump a single-minded self-proclaimed Messiah who wants to accomplish everything by fiat, or is he a consensus builder all too willing to water down his principles to secure a good deal? Depending on the question, according to Sen. Cruz, he's both.
Videos above courtesy of CBN News/The Brody File.


text:
Q: Computations to build a logic in R I am trying to cover a logic in excel, however failing since i am not a pro in excel.
Below is how my data looks like:
  C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15
1 12  3  3  4  5  6  7  7  7   7   7   7   7   7   7
2  1  4  5  5  5  5  5  5  6   7   8   8   8   8   8
3  3  4  4  4  4 45 32 57 23  23  23  23  23  23  23

As you can see, in the first row, from the last column there are multiple 7's. Similary, for the second row starting from the last column
there are multiple 8's and for row3, there are multiple 23's.
I want to replace the multiple columns of 7's,8's and 23's into #N/A, and keep only the first 7 in my result.
I tried it with a simple logic, where IF(C15<>C14, C15,"N/A"), however this logic fails as it also converts the previous repeated values at row level too
Below is how i am looking for the final result.
  C1 C2 C3 C4 C5 C6 C7   C8   C9  C10  C11  C12  C13  C14  C15
1 12  3  3  4  5  6  7 #N/A #N/A #N/A #N/A #N/A #N/A #N/A #N/A
2  1  4  5  5  5  5  5    5    6    7    8 #N/A #N/A #N/A #N/A
3  3  4  4  4  4 45 32   57   23 #N/A #N/A #N/A #N/A #N/A #N/A

Can i do it in excel, or i need to find some code in R?
Any leads would be appreciated.
THanks,
Jay
Data:
df <- structure(list(C1 = c(12, 1, 3), C2 = c(3, 4, 4), C3 = c(3, 5, 4),
               C4 = c(4, 5, 4), C5 = c(5, 5, 4), C6 = c(6, 5, 45),
               C7 = c(7, 5, 32), C8 = c(7, 5, 57), C9 = c(7, 6, 23),
               C10 = c(7, 7, 23), C11 = c(7, 8, 23), C12 = c(7, 8, 23),
               C13 = c(7, 8, 23), C14 = c(7, 8, 23), C15 = c(7, 8, 23)),
          .Names = c("C1", "C2", "C3", "C4", "C5",
                     "C6", "C7", "C8", "C9", "C10",
                     "C11", "C12", "C13", "C14", "C15"),
          row.names = c(NA, -3L), class = "data.frame")

A: Here is an R solution using rleid from data.table:
library(data.table)
df[t(apply(df, 1, function(x) shift(rleid(x) == max(rleid(x)))))] <- NA

Result:
  C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15
1 12  3  3  4  5  6  7 NA NA  NA  NA  NA  NA  NA  NA
2  1  4  5  5  5  5  5  5  6   7   8  NA  NA  NA  NA
3  3  4  4  4  4 45 32 57 23  NA  NA  NA  NA  NA  NA

Note that this works even if the repeating integer appears anywhere in each row not connected to the repeating sequence at the end.
Data:
df = structure(list(C1 = c(12L, 1L, 3L), C2 = c(3L, 4L, 4L), C3 = c(3L,
5L, 4L), C4 = c(4L, 5L, 4L), C5 = c(5L, 5L, 4L), C6 = c(6L, 5L,
45L), C7 = c(7L, 5L, 32L), C8 = c(7L, 5L, 57L), C9 = c(7L, 6L,
23L), C10 = c(7L, 7L, 23L), C11 = c(7L, 8L, 23L), C12 = c(7L,
8L, 23L), C13 = c(7L, 8L, 23L), C14 = c(7L, 8L, 23L), C15 = c(7L,
8L, 23L)), .Names = c("C1", "C2", "C3", "C4", "C5", "C6", "C7",
"C8", "C9", "C10", "C11", "C12", "C13", "C14", "C15"), class = "data.frame", row.names = c(NA,
-3L))

A: With base R you can do it like the following.
This is the third version of the function, thanks to @useR for pointing out the wrong results of the others in some use cases.
fun <- function(x, n){
  r <- rle(x)
  n <- length(x)
  x[(n - r$lengths[length(r$lengths)] + 2):n] <- NA
  x
}

x <- c(12,3,3,4,5,6,7,7,7,7,7,7,7,7,7)
fun(x)
#[1] 12  3  3  4  5  6  7 NA NA NA NA NA NA NA NA

y <- c(12,7,7,4,5,6,7,7,7,7,7,7,7,7,7)
fun(y)
#[1] 12  7  7  4  5  6  7 NA NA NA NA NA NA NA NA

Now with a data.frame.
dat[] <- t(apply(dat, 1, fun))
#  C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 C15
#1 12  3  3  4  5  6  7 NA NA  NA  NA  NA  NA  NA  NA
#2  1  4  5  5  5  5  5  5  6   7   8  NA  NA  NA  NA
#3  3  4  4  4  4 45 32 57 23  NA  NA  NA  NA  NA  NA

Data.
dat <- read.csv(text = "
C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15
12,3,3,4,5,6,7,7,7,7,7,7,7,7,7
1,4,5,5,5,5,5,5,6,7,8,8,8,8,8
3,4,4,4,4,45,32,57,23,23,23,23,23,23,23
")

A: Data:
df1 <- read.table(text='C1,C2,C3,C4,C5,C6,C7,C8,C9,C10,C11,C12,C13,C14,C15
12,3,3,4,5,6,7,7,7,7,7,7,7,7,7
                  1,4,5,5,5,5,5,5,6,7,8,8,8,8,8
                  3,4,4,4,4,45,32,57,23,23,23,23,23,23,23', sep = ",", header = TRUE, stringsAsFactors = FALSE)

Code:
 apply(df1, 1, function(x) {
  x <- rle(x)
  len_x <- length(x$lengths)

  if( (x$lengths)[len_x] > 1 ){ # check for end sequence
    x <- list(lengths = c(x$lengths[-len_x], 1, x$lengths[len_x]- 1 ),
              values = c(x$values, NA))
  }
  inverse.rle(x)
})

Output:
#       [,1] [,2] [,3]
# [1,]   12    1    3
# [2,]    3    4    4
# [3,]    3    5    4
# [4,]    4    5    4
# [5,]    5    5    4
# [6,]    6    5   45
# [7,]    7    5   32
# [8,]   NA    5   57
# [9,]   NA    6   23
# [10,]   NA    7   NA
# [11,]   NA    8   NA
# [12,]   NA   NA   NA
# [13,]   NA   NA   NA
# [14,]   NA   NA   NA
# [15,]   NA   NA   NA

A: Before:

the code:
Sub marine()
    For i = 2 To 4
        For j = 15 To 2 Step -1
            If Cells(i, j).Value = Cells(i, j - 1).Value Then
                Cells(i, j).Value = "#N/A"
            Else
                Exit For
            End If
        Next j
    Next i
End Sub

and after:

A: this only uses one loop:
Sub nadup()

With Worksheets("Sheet5") 'change to your sheet
    Dim i As Long
    For i = 2 To 4
        Dim t As Long
        t = Application.Match(.Cells(i, 15), Range(i & ":" & i), 0)
        If t < 14 Then
            .Range(.Cells(i, t + 1), .Cells(i, 15)).Value = "N/A"
        ElseIf t = 14 Then
            .Cells(i, 15) = "N/A"
        End If
    Next i
End With

End Sub

A: With arrays
Option Explicit

Public Sub ReplaceItems()
    Dim arr(), arr2(), i As Long, j As Long
    With ActiveSheet
        arr() = .Range("A1:O3").Value
        For i = LBound(arr, 1) To UBound(arr, 1)
            ReDim arr2(1 To UBound(arr, 2))
            For j = LBound(arr, 2) To UBound(arr, 2)
                If IsError(Application.Match(arr(i, j), arr2, 0)) Then
                    arr2(j) = arr(i, j)
                Else
                    Select Case arr(i, j)
                    Case 7, 8, 23
                    arr2(j) = "#N/A"
                    Case Else
                    arr2(j) = arr(i, j)
                    End Select
                End If
            Next
            .Range("A" & i).Resize(1, UBound(arr2)).Value = arr2
        Next i
    End With
End Su

redpajama_set_name: RedPajamaStackExchange


text:
Matias Salibian-Barrera
Statistics, Master of Science
Statistics, Doctor of Philosophy
Methods for preferential sampling in geostatistics (2018)
Preferential sampling in geostatistics occurs when the locations at which observations are made may depend on the spatial process that underlines the correlation structure of the measurements. If ignored, this may affect the parameter estimates of the model and the resulting spatial predictions. In this thesis, we first show that previously proposed Monte Carlo estimates for the likelihood function may not be approximating the desired function. Furthermore, we argue that for preferential sampling of moderate complexity, alternative and widely available numerical methods to approximate the likelihood function produce better results than Monte Carlo methods. We illustrate our findings on various data sets, include the biomonitoring Galicia dataset analysed previously in the literature. Research on preferential sampling has so far been restricted to stationary sampling locations such as monitoring sites. In this thesis, we also expand the methodology for applicability in cases where the sensors are moving through the domain of interest. More specifically, we propose a flexible framework for inference on preferentially sampled fields, where the process that generates the sampling locations is stochastic and moving through a 2-dimensional space. The main application of these methods is the sampling of ocean temperature fields by marine mammal mounted sensors. This is an area of research which has grown drastically over the past 25 years and is providing scientists with a wealth of new oceanographic information in areas of our oceans previously not well understood. We show that standard geostatistical models may not be reliable for this type of data, due to the possibility that the regions visited by the animals may depend on the ocean temperatures, hence resulting in a type of preferential sampling. Our simulation studies confirm that predictions obtained from the preferential sampling model are more reliable when this phenomenon is present, and they compare very well to the standard ones when there is no preferential sampling. We apply our methods to sea surface temperature data collected by Southern elephant seals in the Southern Indian ocean and show how predictions of sea surface temperature fields using this data may vary when accounting for the preferential movement.
Extending linear grouping analysis and robust estimators for very large data sets (2009)
Cluster analysis is the study of how to partition data into homogeneous subsets so that the partitioned data share some common characteristic. In one to three dimensions, the human eye can distinguish well between clusters of data if clearly separated. However, when there are more than three dimensions and/or the data is not clearly separated, an algorithm is required which needs a metric of similarity that quantitatively measures the characteristic of interest. Linear Grouping Analysis (LGA, Van Aelst et al. 2006) is an algorithm for clustering data around hyperplanes, and is most appropriate when: 1) the variables are related/correlated, which results in clusters with an approximately linear structure; and2) it is not natural to assume that one variable is a "response", and the remainder the "explanatories". LGA measures the compactness within each cluster via the sum of squared orthogonal distances to hyperplanes formed from the data. In this dissertation, we extend the scope of problems to which LGA can be applied. The first extension relates to the linearity requirement inherent within LGA, and proposes a new method of non-linearly transforming the data into a Feature Space, using the Kernel Trick, such that in this space the data might then form linear clusters. A possible side effect of this transformation is that the dimension of the transformed space is significantly larger than the number of observations in a given cluster, which causes problems with orthogonal regression. Therefore, we also introduce a new method for calculating the distance of an observation to a cluster when its covariance matrix is rank deficient.The second extension concerns the combinatorial problem for optimizing a LGA objective function, and adapts an existing algorithm, called BIRCH, for use in providing fast, approximate solutions, particularly for the case when data does not fit in memory. We also provide solutions based on BIRCH for two other challenging optimization problems in the field of robust statistics, and demonstrate, via simulation study as well as application on actual data sets, that the BIRCH solution compares favourably to the existing state-of-the-art alternatives, and in many cases finds a more optimal solution.
Dimension reduction using Independent Component Analysis with an application in business psychology (2017)
Independent component analysis (ICA) is used for separating a set of mixed signals into statistically independent additive subcomponents. The methodology extracts as many independent components as there are dimensions or features in the original dataset. Since not all of these components may be of importance, a few solutions have been proposed to reduce the dimension of the data using ICA. However, most of these solutions rely on prior knowledge or estimation of the number of independent components that are to be used in the model. This work proposes a methodology that addresses the problem of selecting fewer components than the original dimension of the data that best approximate the original dataset without prior knowledge or estimation of their number. The trade off between the number of independent components retained in the model and the loss of information is explored. This work presents mathematical foundations of the proposed methodology as well as the results of its application to a business psychology dataset.
A Markov random fields approach to modelling habitat (2015)
Habitat modelling presents a challenge due to the variety of data available and their corresponding accuracy. One option is to use Markov random fields as a way to incorporate these distinct types of data for habitat modelling. In this work, I provide a brief overview of the intuition, mathematical theory, and application considerations behind modelling habitat under this framework. In particular, an auto-logistic model is built and applied to modelling sea lion habitat using synthetic data. First, we explore modelling one sample of data. Afterwards, the framework is extended to the multi-sample scenario. Finally, the theory for the methodology is presented, the results of the applied implementation are presented.
A robust fit for generalized partial linear partial additive models (2013)
In regression studies, semi-parametric models provide both flexibility and interpretability.In this thesis, we focus on a robust model fitting algorithm for a family of semi-parametric models – the Generalized Partial Linear Partial Addi- tive Models (GAPLMs), which is a hybrid of the widely-used Generalized Linear Models (GLMs) and Generalized Additive Models (GAMs). The traditional model fitting algorithms are mainly based on likelihood proce- dures. However, the resulting fits can be severely distorted by the presence of a small portion of atypical observations (also known as "outliers"), which deviate from the assumed model. Furthermore, the traditional model diag- nostic methods might also fail to detect outliers. In order to systematically solve these problems, we develop a robust model fitting algorithm which is resistant to the effect of outliers. Our method combines the backfitting algorithm and the generalized Speckman estimator to fit the "partial linear partial additive" styled models. Instead of using the likelihood-based weights and adjusted response from the generalized local scoring algorithm (GLSA), we apply the robust weights and adjusted response derived form the robust quasi-likelihood proposed by Cantoni and Ronchetti (2001). We also extend previous methods by proposing a model prediction algorithm for GAPLMs.To compare our robust method with the non-robust one given by the R function gam
Robustification of the sparse K-means clustering algorithm (2011)
Searching a dataset for the ''natural grouping / clustering'' is an important explanatory technique for understanding complex multivariate datasets. One might expect that the true underlying clusters present in a dataset differ only with respect to a small fraction of the features. Furthermore, one might afraid that the dataset might contain potential outliers. Through simulation studies, we find that an existing sparse clustering method can be severely affected by a single outlier. In this thesis, we develop a robust clustering method that is also able to perform variable selection: we robustified sparse K-means (Witten and Tibshirani [28]), based on the idea of trimmed K-means introduced by Gordaliza [7] and Gordaliza [8]. Since high dimensional datasets often contain quite a few missing observations, we made our proposed method capable of handling datasets with missing values. The performance of the proposed robust sparse K-means is assessed in various simulation studies and two data analyses. The simulation studies show that robust sparse K-means performs better than other competing algorithms in terms of both the selection of features and the selection of a partition when datasets are contaminated. The analysis of a microarray dataset shows that robust sparse K-means best reflects the oestrogen receptor status of the patients among all other competing algorithms. We also adapt Clest (Duboit and Fridlyand [5]) to our robust sparse K-means to provide an automatic robust procedure of selecting the number of clusters. Our proposed methods are implemented in the R package RSKC.
Matias Salibian-Barrera's Profile


text:
Jerusalem Post World News
FBI offers reward for details of those behind Washington pipe bombs
Law enforcement agencies had received reports of two suspected devices, one each at the headquarters of the Republican National Committee and the Democratic National Committee.
An FBI investigator
The FBI is offering a reward of up to $50,000 for information on who placed pipe bombs in the committee headquarters of US political parties in Washington.
Law enforcement agencies had received reports of two suspected devices, one each at the headquarters of the Republican National Committee and the Democratic National Committee on Wednesday, the FBI said in a statement.
The statement was accompanied by an image of a masked suspect wearing gloves and a hoodie, carrying an object.
"The FBI is offering a reward of up to $50,000 for information leading to the location, arrest and conviction," it said.
ABC News reported that bomb technicians used water cannon to blast the devices to break them apart and render them harmless on Wednesday just as supporters of US President Donald Trump stormed into the Capitol building, where lawmakers were certifying the victory of President-elect Joe Biden.
Trump initially praised his supporters but later condemned the violence.
Senators and Congressmen were forced to evacuate after the Trump supporters smashed windows and engaged in looting. The violence, which killed five people, followed a rally at which Trump exhorted supporters to fight to overturn the result of the Nov. 3 election.
Tags United States FBI bombing Capitol
Coronavirus: 67-year-old jabbed with five doses instead of one
13 Israelis suffer facial paralysis after coronavirus vaccine - report