Search Results: 1 - 10 of 104872 matches for " Haiyan Zhang "
Spectra of 2 × 2 Upper-Triangular Operator Matrices [PDF]
Haiyan Zhang
Applied Mathematics (AM) , 2013, DOI: 10.4236/am.2013.411A1004
In [Perturbation of Spectrums of 2 × 2 Operator Matrices, Proceedings of the American Mathematical Society, Vol. 121, 1994], the authors asked whether there was an operator such that for a given pair (A,B) of operators, where the operator was defined by . In this note, a partial answer for the question is given.
Calculation of compact amplitude-integrated EEG tracing and upper and lower margins using raw EEG data [PDF]
Dandan Zhang, Haiyan Ding
Health (Health) , 2013, DOI: 10.4236/health.2013.55116
Amplitude-integrated EEG (aEEG) is a popular method for monitoring cerebral function. Although various commercial aEEG recorders have been produced, a detailed aEEG algorithm currently is not available. The upper and lower margins in the aEEG tracing are the discriminating features for data inspection and tracing classification. However, most aEEG devices require that these margins be measured semi-subjectively. This paper proposes a step-by-step signal-processing method to calculate a compact aEEG tracing and the upper/lower margin using raw EEG data. The high accuracy of the algorithm was verified by comparison with a recognized commercial aEEG device based on a representative testing dataset composed of 72 aEEG data. The introduced digital algorithm achieved compact aEEG tracing with a small data size. Moreover, the algorithm precisely represented the upper and lower margins in the tracing for objective data interpretation. The described method should facilitate aEEG signal processing and further establish the clinical and experimental application of aEEG methods.
Fixed Points Associated to Power of Normal Completely Positive Maps* [PDF]
Haiyan Zhang, Hongying Si
Journal of Applied Mathematics and Physics (JAMP) , 2016, DOI: 10.4236/jamp.2016.45101
Abstract: Let be a normal completely positive map with Kraus operators . An operator X is said to be a fixed point of , if . Let be the fixed points set of . In this paper, fixed points of are considered for , where means j-power of . We obtain that and for integral when A is self-adjoint and commutable. Moreover, holds under certain condition.
Mixed-Type Reverse Order Laws for Generalized Inverses over Hilbert Space [PDF]
Haiyan Zhang, Fengling Lu
Applied Mathematics (AM) , 2017, DOI: 10.4236/am.2017.85050
Abstract: In this paper, by using a block-operator matrix technique, we study mixed-type reverse order laws for {1,3}-, {1,2,3}- and {1,3,4}-generalized inverses over Hilbert spaces. It is shown that and when the ranges of are closed. Moreover, a new equivalent condition of is given.
Exploration and Practice of the Practical Teaching Curriculum System for Cultivating Applied and Innovative Undergraduate Talents [PDF]
Chunhua He, Haiyan Zhang, Aixiang Wei
Creative Education (CE) , 2012, DOI: 10.4236/ce.2012.37B047
Abstract: Aiming at shortcomings in the current system of practice teaching in high schools especially in regional high schools, a system of practice teaching that fit current cultivation of practical and innovative talents is explored in education. In accordance with the progressive regularity of ability cultivation, the system of practice teaching is divided into four levels: basic practice, basic experiment, advanced practice and comprehensive innovation. And this characteristic system of practice teaching is built up to cultivate practical and innovative talents in grassroots who can meet the requirements of current socio-economic development.
Numerical Simulations of the Equations of Particle Motion in the Gas Flow [PDF]
Kelong Zheng, Liuxiang Zhang, Haiyan Chen
Open Journal of Applied Sciences (OJAppS) , 2013, DOI: 10.4236/ojapps.2013.31B1005
Under the assumption of considering the gravity and without gravity, two different acceleration models to describe particle' motion in the gas flow are formulated, respectively. The corresponding numerical simulations of these models do not only show the trend of the velocity of the particle in different density and particle diameter sizes, but also the relationship between the maximum particle velocity and its diameter size.
GnRH Antagonist Protocol: Is It Optimal for All Patients of Different Ages Undergoing In Vitro Fertilization and Embryo Transfer? [PDF]
Weijie Xing, Haiyan Lin, Qingxue Zhang
Advances in Sexual Medicine (ASM) , 2017, DOI: 10.4236/asm.2017.74012
Abstract: Background: To assess the effect of these two protocols in patients of different ages. Methods: 1923 in vitro fertilization and embryo transfer (IVF-ET) cycles were divided into two groups: a GnRH-ant protocol group and GnRH-a long protocol group, and then every group were subdivided into four age ranges. The general materials and IVF outcomes were compared. Results: The incidence of OHSS fluctuated from 0% to 2.37% with GnRH-ant protocol, which was significantly lower than another (P < 0.05). Of all age ranges, the implantation and clinical pregnancy rates with GnRH-ant protocol were all lower than those with GnRH-a protocol. When the age was less than 35 years old, the CPRs in GnRH-ant protocol group were significantly lower than in another group (45.56% vs. 62.29%, 46.07% vs. 55.59%, respectively; P < 0.05). Conclusion: The antagonist protocol should be considered in patients with a high ovarian response (e.g., PCOS patients) to avoid OHSS. Older patients (>35 years) could be treated with the antagonist protocol.
GnRH Antagonist Protocol: Is It Effective for Expected Poor Ovarian Responders with Tubal Factor Undergoing IVF? [PDF]
Advances in Reproductive Sciences (ARSci) , 2017, DOI: 10.4236/arsci.2017.54007
Abstract: Background: This study aimed to determine if the gonadotropin releasing hormone (GnRH) antagonist protocol is optimal for expected poor ovarian responders with tubal factor undergoing in vitro fertilization-embryo transfer (IVF-ET). Methods: A total of 341 IVF-ET cycles were retrospectively identified. The following inclusion criteria were applied: age ≥ 40 years and patients with tubal factors. The cycles were divided into two groups: a GnRH antagonist group (157 cycles) and a GnRH agonist group (184 cycles). Results: The duration of stimulation and the total doses of gonadotropin in the GnRH agonist group were significantly more than those in the GnRH antagonist group (P < 0.05). There were significant differences in LH and P values on the hCG measurement days between the two groups (0.91 ± 1.17 vs. 4.82 ± 4.69 U/L and 0.69 ± 0.42 vs. 1.03 ± 0.50 ng/mL, P < 0.05). The implantation rate of the GnRH antagonist group was 12.24%, which was slightly higher than that of the GnRH agonist group (10.10%, P = 0.437). The clinical pregnancy rate of the two groups showed no statistical differences (23.36% vs. 23.03%, P = 1.000). Conclusion: For expected poor ovarian responders, the GnRH antagonist protocol was, to some extent, superior to the GnRH agonist protocol in terms of the implantation and clinical pregnancy rates.
What can false memory tell us about memory impairments in Alzheimer's disease?
Fan Zhang,HaiYan Geng
Chinese Science Bulletin , 2010, DOI: 10.1007/s11434-010-4164-6
Abstract: The range of memory impairments associated with Alzheimer's disease (AD) has been a focus for psychological and clinical researchers for many years. In addition to investigations of AD patients' veridical memory using traditional recognition memory tasks, a number of recent studies have focused on false memories to reveal the underlying causes of memory impairment in AD. Studies comparing illusory memories between AD patients and healthy older people have revealed various differences in memory deficits between the development of AD and the typical aging processes. Here, we review 3 types of memory illusions tested in AD patients: associative memory illusions, fluency-based false memories and source memory errors. By comparing AD patients with healthy older adults, we sought to analyze the mechanisms underlying AD-related memory impairments at different stages of memory processing, including encoding, retrieval and monitoring. This comparison revealed that AD patients exhibit an impaired ability to establish and utilize gist representations at the encoding stage and impairments in processing on the basis of familiarity and recollection at the retrieval stage. Consequently, patients with AD have access to less information when making memory judgments. As a result, they become more susceptible to the effects of item fluency, which can be manipulated during the retrieval stage. Furthermore, with impaired source memory monitoring abilities, the capacity of AD patients to suppress memory illusions is compromised. Based on these findings, we propose that the study of false memories constitute a critical tool for elucidating the memory impairments involved in AD. Further explorations of these memory impairments will have practical significance for the diagnosis and treatment of AD in the future.
On the Erd?s-Ginzburg-Ziv invariant and zero-sum Ramsey number for intersecting families
Haiyan Zhang,Guoqing Wang
Mathematics , 2013,
Abstract: Let $G$ be a finite abelian group, and let $m>0$ with $\exp(G)\mid m$. Let $s_{m}(G)$ be the generalized Erd\H{o}s-Ginzburg-Ziv invariant which denotes the smallest positive integer $d$ such that any sequence of elements in $G$ of length $d$ contains a subsequence of length $m$ with sum zero in $G$. For any integer $r>0$, let $\mathcal{I}_m^{(r)}$ be the collection of all $r$-uniform intersecting families of size $m$. Let $R(\mathcal{I}_m^{(r)},G)$ be the smallest positive integer $d$ such that any $G$-coloring of the edges of the complete $r$-uniform hypergraph $K_{d}^{(r)}$ yields a zero-sum copy of some intersecting family in $\mathcal{I}_m^{(r)}$. Among other results, we mainly prove that $\Omega(s_{m}(G))-1\leq R (\mathcal{I}_{m}^{(r)}, \ G)\leq \Omega(s_{m}(G)),$ where $\Omega(s_{m}(G))$ denotes the least positive integer $n$ such that ${n-1 \choose r-1}\geq s_{m}(G)$, and we show that if $r\mid \Omega(s_{m}(G))-1$ then $R (\mathcal{I}_{m}^{(r)}, \ G)= \Omega(s_{m}(G))$.