bluuebunny/crossref_metadata_2025_split huggingface dataset:
Electrical Programmable Low-loss high cyclable Nonvolatile Photonic Random-Access Memory
Authors: Meng Jiawei , Peserico Nicola , Ma Xiaoxuan , Zhang Yifei , Popescu Cosmin-Constantin , Kang Myungkoo , Miscuglio Mario , Richardson Kathleen , Hu Juejun , Sorger Volker 
Published: April 2022

Abstract
The retention-of-state functionality provided by memories is fundamental to any Turing machine and neural network, hence is critical for any information system today. While emerging optical machine learning accelerators and photonic neuromorphic computing paradigms provide promising signal processing and computing performance, the lack of a photon-photon force in the universe makes storing optical information challenging. Fortunately, phase change materials provide such a missing memristive nonvolatile function via their reconfigurable crystalline structure and allow for rapid optical READ paradigms. However, demonstrations of photonic memory are limited by high optical loss, low state-cyclability, and rely on cumbersome non-CMOS like optical programmability. To overcome all three shortcomings and unlock the full potential of optical information storage and access, here we introduce a photonic random-access memory featuring vanishing low optical loss, demonstrate more than half a million switching cycles, a 100x improvement over state-of-art, and realize electrical programmability on-chip. The exceedingly low optical absorption (0.0015 dB/μm) is achieved via a novel broadband transparent phase change material, Ge2Sb2Se5 integrated atop a nanophotonic waveguide of a silicon chip. We show a highly efficient signal modulation (0.2 dB/μm) achieved by realizing a newly designed paired micro-heaters along both sides of waveguide, which allows for electronic-standard programmability of these photonic memories. When interrogated by an optical beam, they offer picosecond-short memory READ latency. Furthermore, we demonstrate a partial amorphization scheme realizing multi-state memory levels on a single heater enhancing footprint efficiency. Lastly, we verify the energy and switching speed and show how each trades-off with heater-to-waveguide proximity and signal strength, respectively. Such as CMOS-near electronically programmed and optical read photonic random-access memory with low-optical loss yet efficient programmability can become a crucial building block for network edge AI system of the looming industry 4.0 era.
In-memory Search with Memristors for Highly Efficient Similarity-Measurement-Based Data Mining
Authors: Li Yi , Yang Ling , Huang Xiao-Di , Zhou Houji , Yu Yingjie , Bao Han , Li Jiangcong , Ren Shengguang , Wang Feng , Ye Lei , He Yuhui , Chen Jia , Pu Guiyou , Li Xiang , Miao Xiang Shui 
Published: April 2022

Abstract
Similarity search, that is, finding similar items in massive data, is a fundamental computing problem in many fields such as data mining, and information retrieval. However, for large-scale and high-dimension data, it suffers from high computational complexity, requiring tremendous computation resources. Here, based on the one-selector-one-resistor memristors, for the first time, we propose an in-memory search (IMS) system with two innovative designs. First, by exploiting the natural distribution law of the devices resistance, a hardware local sensitive hash encoder has been designed to transform the real-valued vectors into more efficient binary codes. Second, a compact memristive ternary content addressable memory is developed to calculate the Hamming distances between the binary codes in parallel. Our IMS system demonstrated a 168× energy efficiency improvement over all-transistors counterparts in clustering and classification tasks, while achieving a software-comparable accuracy, thus providing a low-complexity and low-power solution for in-memory data mining applications.
Evaluation of a Fast Proxy of Vs30 (Vs30m)
Authors: Saqlain Muhammad , ZADA UMAR , Hussain Wakeel 
Published: April 2022

Abstract
The most frequent parameter used to quantify seismic site response in ground motion models is time-averaged shear wave velocity in the top 30 m of a site (Vs30), used by many engineering design codes and most recently by published empirical-scaling equations to estimate the amplitudes of strong ground motion. The current study explores the potential comparison of the results from the predictive equations and formula recommends by the international building code. In order to avoid forward modeling and inverse modeling, 53 synthetic and real data models with distinct types of Vs profile were used, to determine the theoretical dispersion curves. In the prediction equation, VR36 and VR40 were employed to estimate Vs30. Furthermore, the use of VR40, based on the 53 different models, shows a good agreement with Vs30. The correlation is significantly influenced by the thickness of the first layer. The findings calculated by the correlation are not in the acceptable zone for layer thicknesses of 10 < H < 20 m and thin layers at shallow depths with lower shear wave velocity.
Identification of Resistance to Geminivirus and Whitefly in Pepper
Authors: Sandra Yuke Mareta Ariesta , Maharijaya Awang , Sobir Sobir 
Published: April 2022

Abstract
Pepper yellow leaf curl disease caused by geminivirus (Geminiviridae) is a major problem in chili pepper production. The availability of resistant varieties to geminivirus and whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) as its vector has the potential to overcome this problem. The use of resistant varieties has various advantages, namely reducing pest control costs, producing no harmful chemical residues, and being acceptable and usable by farmers in the long term. This study aims to identify genotypes that are resistant to geminivirus and its vector. Nineteen chili pepper genotypes obtained from the Center for Tropical Horticulture Studies of IPB University were examined in this study by conducting field and laboratory tests. Based on the results, several chili pepper genotypes were found to be resistant to whiteflies and geminivirus. However, none of those genotypes had sufficient vector and virus resistance. This study also found that there was a significant correlation between the numbers of surviving imago and pupae with disease incidence, as well as between disease incidence and disease severity. Thus, the resistance to whitefly as a geminivirus vector can potentially reduce disease severity in chili pepper plants.
Quantum cloud theory: Collapse expectations of matter proportions
Authors: Qu Wenjing 
Published: April 2022

Abstract
Most of metabolic processes are extremely complicated but occur spontaneously and steadily, the essential reason of which may be either a thermodynamic problem or related to some quantum properties. Here, collapse selection is interpreted with an analytical model of energy transfer, from which the concept of quantum cloud is defined as that during undetectable changes of a group of particles between its effective changes, particles are in the superposition of various energy states and the group is named as a cloud. It is deduced from the interpretation of collapse selection and the notion of matter proportions that cloud collapses have different expectations: active cloud collapses have least-time expectation while passive collapses have matter-proportion expectation.
The impact of mask-wearing influenced by restricted interest and repetitive behavior on the mental distress of individuals with autism spectrum disorder during the COVID-19 pandemic: a multisite survey
Authors: Tamon Hiroki , Itahashi Takashi , Yamaguchi Sosei , Tachibana Yoshiyuki , Fujino Junya , Igarashi Miki , Kawashima Makiko , Takahashi Riina , Shinohara Nozomi , Noda Yoshihiro , Nakajima Shinichiro , Hirota Tomoya , Aoki Yuta 
Published: April 2022

Abstract
Background
The coronavirus disease of 2019 pandemic has caused considerable changes in daily life. For children with autism spectrum disorder, adapting to the “new normal,” including mask-wearing, may be difficult because of their restricted interest and repetitive behaviors symptoms. We aimed to examine the relationships between restricted interest and repetitive behaviors symptoms and the impact of mask-wearing on their social communications during the pandemic.
Methods
We recruited 102 children with autism spectrum disorder and collected data on sleep and exercise and the restricted interest and repetitive behaviors symptom frequency before and during the pandemic using an international questionnaire. Then, we conducted factor analyses to compute the restricted interest and repetitive behaviors severity composite scores, which are divided into lower-, such as sensory seeking, and higher-order, such as restricted interest. We also asked about the mask-wearing culture using a bespoke questionnaire. Using Spearman’s rank correlation analyses, we examined the relationships between the before pandemic restricted interest and repetitive behaviors symptoms and the impact of mask-wearing on their social communications during the pandemic.
Results
The current participants spent significantly less time outdoors during the pandemic than before (rho = 0.75, p = 0.005). We also revealed children who exhibited lower-order restricted interest and repetitive behaviors before the pandemic had more challenges with mask-wearing. Mask-wearing was associated with an uncomfortable sensation (rho=-0.34, p = 0.0004) and difficulty in referring to others’ emotions while wearing masks (rho=-0.30, p = 0.0002). We also found an association between higher-order restricted interest and repetitive behaviors and an uncomfortable sensation (rho=-0.42, p = 0.00001).
Conclusions
These symptoms could be an important predictor for children with autism to adapt to the new normal.
Assessing Innovative Approaches for Global Health Capacity Building in Fragile Settings in the MENA region: Development of the Evaluation of Capacity Building (eCAP) Program
Authors: Saleh Shadi , Mansour Rania , Daou Tracy , Brome Dayana , Naal Hady 
Published: April 2022

Abstract
Background: Given the magnitude and frequency of conflicts in the MENA region along with their devastating impact on health responses and outcomes, there exists a strong need to invest in contextualized, innovative, and accessible capacity building approaches to enhance leadership and skills in global health. The MENA region suffers from limited (1) continued educational and career progression opportunities, (2) gender balance, and (3) skill-mix among its health workforce, which require significant attention. Main Text: The Global Health Institute at the American University of Beirut incepted the Academy division to develop and implement various Global Health Capacity Building (GHCB) initiatives to address those challenges in fragile settings across low-and middle-income countries in the MENA region. These initiatives play a strategic role in this context, especially given their focus on being accessible through employing innovative learning modalities. However, there exists a dearth of evidence-based knowledge on best practices and recommendations to optimize the design, implementation, and evaluation of GHCB in fragile settings in the MENA region. The present paper describes the development of the Evaluation of Capacity Building program (eCAP), implemented under the Academy division, to assess the effectiveness of its initiatives. eCAP is composed of 3 phases: (1) a situational assessment, followed by (2) production of multiple case studies, and finally (3) a meta-assessment leading to model development. The goal of eCAP is not only to inform the Academy’s operations, but also to synthesize produced knowledge into the formation of an evidence-based, scalable, and replicable model for GHCB in fragile settings. Conclusion: eCAP is an important initiative for researchers, educators, and practitioners interested in GHCB in fragile settings. Several lessons can be learned from the outcomes it has yielded so far in its first two phases of implementation, ranging from the situational assessment to the production of evaluation case studies, which are expanded on in the manuscript along with pertinent challenges.
Neuroprotective Effects of Oxymatrine via Triggering Autophagy and Inhibiting Apoptosis Following Spinal Cord Injury in Rats
Authors: Li Jian , Cao Yang , Li Lin-Na , Chu Xin , Wang Yan-Song , Cai Jia-Jun , Zhao Jin , Ma Song , Li Gang , Fan Zhongkai 
Published: April 2022

Abstract
The identification of drugs that promote autophagy and inhibits apoptosis in neurons is critical for improving patient outcomes following spinal cord injury (SCI). Here, we aimed to investigate the neuroprotective effects of oxymatrine (OMT) and the potential mechanism after SCI in rats. Female Sprague-Dawley rats were randomly assigned to either a sham group, SCI group, OMT-treated group (40 mg/kg), and a group treated with both OMT and SIRT1 inhibitor EX527 (10 µg/kg). A modified compressive device (weight 35 g, time 5 min) was applied to induce moderate SCI in all groups except the sham group. After treatment with drugs or vehicle (saline), the neurological functions were evaluated using the Basso, Beattie, and Bresnahan (BBB) locomotor rating scale and footprint analysis. Morphological changes in the spinal cord were assessed using hematoxylin-eosin staining and the number of surviving and apoptotic neurons was determined using Nissl and TUNEL staining, respectively. Neuronal ultrastructures were observed using transmission electron microscope (TEM). Moreover, we investigated the gene and protein expression levels of relevant molecules involved in apoptosis and autophagy, such as SIRT1, AMPK, p62, Beclin-1, LC3B, Bcl-2, Bcl-xL, Bax, Bak and C-caspase-3 using qRT-PCR analysis, Western blotting, or immunofluorescence staining. Our results indicated that OMT treatment significantly reduced the lesion size, promoted survival of motor neurons, and subsequently attenuated motor dysfunction following SCI in rats. OMT significantly enhanced autophagy activity, inhibited apoptosis in neurons, and increased SIRT1 and p-AMPK expression levels. These effects of OMT on SCI were partially prevented by co-treatment with SIRT1 inhibitor EX527. Taken together, these data revealed that OMT exerts a neuroprotective role in functional recovery against SCI in rats, and these effects are potentially associated with OMT-induced activation of autophagy via the SIRT1/AMPK signaling pathway.
A suggested Scientific Research Environment Measure SREM in Medical Faculties
Authors: Yousef Mohammad Ali , Dashash Mayssoon 
Published: April 2022

Abstract

Background: Creating a supportive environment for scientific research is vital to improve the quality of research and its impact on development of the society. This study outlines the development of a new scale that can measure the scientific research environment of postgraduate medical students.Methods: Based on literature, an initial list with 58 items was formulated. After discussing with postgraduate students and academic staff members from Damascus University and the Syrian Virtual University, A 38-item scale remained from the initial list of 58 items. To test the scale, postgraduate medical students (n= 30) were asked to fill the scale and answer 38 questions-with a 5-point Likert scale-twice in two separate occasions. The Pearson's correlation coefficient was performed to study the internal correlation. The internal consistency test was performed with Cronbach's Alpha, and the Test-Retest Reliability was conducted to study the reliability of the scale.Results: Thirty postgraduate medical students at Damascus University completed the 38-item scale. Scale scores in the sample displayed good reliability in relation to published results. Findings, showed an internal correlation among its sub-scales. The results showed an acceptable reliability values such as internal consistency (α = 0.863) and test–retest reliability (ICC = 0.093).Conclusions: The Scientific Research Environment Measure (SREM), can be suggested as an effective evaluation instrument which can be applied easily to assess the scientific research environment of postgraduate medical students. This would help the decision makers to support teaching, learning, and research environment through implementing new strategies that inspire postgraduate medical students and increase their engagement.
The Abundance of Bifidobacterium in relation to visceral obesity and Serum uric acid
Authors: Gong Hualan , Ren Qingye , Gao Hainv , He Jia 
Published: April 2022

Abstract
Many studies have found that people with obesity have significant gut microbiota dysbiosis. Most of these studies on obesity were based on the BMI classification criteria, which doesn't distinguish Visceral adipose tissue (VAT) from subcutaneous adipose tissue (SAT). However, research showed that VAT has a higher risk of inducing metabolic diseases than SAT. This study focused on the visceral obesity defined by increased visceral fat area. It assessed the association of visceral obesity with gut predominant microbiota and metabolic status. This study included 388 individuals from medical examination center in our hospital. Quantitative polymerase chain reaction (q-PCR) technique was used to detect ten kinds of gut predominant bacteria in fresh feces. visceral fat area (VFA)was measured by bioelectrical impedance analysis. According to the VFA results, the individuals were divided into two groups: Visceral obesity group (VFA ≥ 100cm2) and lean control group (VFA < 100cm2). The results showed that the abundance of Bifidobacterium significantly decreased in the Visceral obesity group and combined with metabolic indicators such as Serum uric acid, triglycerides, low-density lipoprotein (LDL-C), high-density lipoprotein (HDL-C) and fasting blood sugar (FBS), serum uric acid was an independent influencing factor for bifidobacterial. serum uric acid was negatively correlated with Bifidobacterium. serum uric acid was positively correlated with visceral fat area. The results suggested that serum uric acid was probably a mediator to the link between decreased Bifidobacterium and increased visceral adipose tissue.
Genetic and epigenetic mechanisms regulating catalase expression in chronic lymphocytic leukemia
Authors: Galasso Marilisa , Pozza Elisa Dalla , Chignola Roberto , Gambino Simona , Cavallini Chiara , Quaglia Francesca Maria , Lovato Ornella , Dando Ilaria , Malpeli Giorgio , Krampera Mauro , Donadelli Massimo , Romanelli Maria Grazia , Scupoli Maria Teresa 
Published: April 2022

Abstract
Chronic lymphocytic leukemia (CLL) is an incurable disease characterized by an extremely variable clinical course. We have recently shown that high catalase (CAT) expression identifies patients with an aggressive clinical course. Elucidating mechanisms regulating CAT expression in CLL is preeminent to understand disease mechanisms and develop strategies for improving its clinical management. In this study, we investigated the role of the CAT promoter rs1001179 single nucleotide polymorphism (SNP) and of the CpG Island II methylation encompassing this SNP in the regulation of CAT expression in CLL. Leukemic cells harboring the rs1001179 SNP T allele exhibited a significantly higher CAT expression compared with cells bearing the CC genotype. CAT promoter harboring the T -but not C- allele was accessible to ETS-1 and GR-β transcription factors. Moreover, CLL cells exhibited lower methylation levels than normal B cells, in line with the higher CAT mRNA and protein expressed by CLL in comparison with normal B cells. Methylation levels at specific CpG sites negatively correlated with CAT levels in CLL cells. Inhibition of methyltransferase activity induced a significant increase of CAT levels, thus functionally validating the role of CpG methylation in regulating CAT expression in CLL. Finally, the CT/TT genotypes were associated with lower methylation and higher CAT levels, suggesting that the rs1001179 T allele and CpG methylation may interact in regulating CAT expression in CLL. This study identifies genetic and epigenetic mechanisms underlying differential expression of CAT, which could be of crucial relevance for the development of therapies targeting redox regulatory pathways in CLL.
Astrocytic lactoferrin deficiency augments MPTP-induced dopaminergic neuron loss by disturbing ER-mitochondria signaling
Authors: Xu Shuang-Feng , Pang Zhong-Qiu , Bai Chen-Yang , Jia Meng-Yu , Cui Jun-He , Wang Zhuo-Jue , Liang Xiu-Ting , Guo Chuang 
Published: April 2022

Abstract
Increased levels of lactoferrin (Lf) are present in the aged brain and in the lesions of various neurodegenerative diseases, including Parkinson’s disease (PD), may contribute to the cascade of events involved in neurodevelopment and neuroprotection. However, whether Lf originates from astrocytes and functions within either the normal or pathological brain are unknown. Here, we employed mice with specific knockout of the astrocyte Lf gene (named Lf-cKO) to explore its specific roles in the pathological process of PD. We observed a decrease in tyrosine hydroxylase (TH)-positive cells, mitochondrial dysfunction of residual dopaminergic neurons, and motor deficits in Lf-cKO mice, which were significantly aggravated after 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) treatment. To further explore how astrocytic Lf deficiency exacerbated PD-like manifestation in MPTP-treated mice, the critical molecules involved in endoplasmic reticulum (ER)-mitochondria contacts and signaling pathways were investigated. In in vitro and in vivo models, we found an aberrant level of effects implicated in reactive oxygen species (ROS) production, apoptosis, mitochondrial morphology and functions, mitochondrial dynamics, mitochondria-associated ER membranes (MAMs), lipid metabolism, and calcium homeostasis, accompanied by signs of ER stress, which increase the fragility of dopaminergic neurons. These findings confirm the existence of astrocytic Lf and its influence on the fate of dopaminergic neurons by regulating ER-mitochondria signaling. Our findings may be a promising target for the treatment of PD.
Shrinkage estimators of large covariance matrices with Toeplitz structure in array signal processing
Authors: Zhang Bin , Yuan Shoucheng 
Published: April 2022

Abstract
Estimating a covariance matrix plays an essential role in modern statistics and practical applications. One key challenge is seeking an outperformed covariance matrix estimator in large dimension and small sample size scenarios. In this paper, we develop new covariance matrix estimators based on shrinkage regularization acclaimed in high-dimensional statistics. Individually, we consider two kinds of Toeplitz-structured target matrices in the shrinkage estimation. Firstly, we obtain the optimal tuning parameter under the mean squared error criterion in closed form by discovering the mathematical properties of the two target matrices. Secondly, we get some vital moment properties of the complex Wishart distribution, and then we simplify the optimal tuning parameter as the data come from the complex Gaussian distribution. Thirdly, we unbiasedly estimate the unknown scalars involved in the optimal tuning parameter. Then we immediately propose available shrinkage estimators. To verify the performance of the proposed covariance matrix estimators, we provide some numerical simulations and applications to array signal processing compared to some existing estimators.