bluuebunny/crossref_metadata_2025_split huggingface dataset:
Myeloid deficiency of the intrinsic clock protein BMAL1 accelerates cognitive aging by disrupting microglial synaptic pruning
Authors: Iweka Chinyere Agbaegbu , Seigneur Erica , Hernandez Amira Latif , Paredes Sur Herrera , Cabrera Mica , Blacher Eran , Pasternak Connie Tsai , Longo Frank M. , de Lecea Luis , Andreasson Katrin I. 
Published: November 2022

Abstract
Aging is associated with loss of circadian immune responses and circadian gene transcription in peripheral macrophages. Microglia, the resident macrophages of the brain, also show diurnal rhythmicity in regulating local immune responses and synaptic remodeling. To investigate the interaction between aging and microglial circadian rhythmicity, we examined mice deficient in the core clock transcription factor, BMAL1. Aging Cd11bcre;Bmallox/lox mice demonstrated accelerated cognitive decline in association with suppressed hippocampal long-term potentiation and increases in immature dendritic spines. C1q deposition at synapses and synaptic engulfment were significantly decreased in aging Bmal1-deficient microglia, suggesting that BMAL1 plays a role in regulating synaptic pruning in aging. In addition to accelerated age-associated hippocampal deficits, Cd11bcre;Bmallox/lox mice also showed deficits in the sleep-wake cycle with increased wakefulness across light and dark phases. These results highlight an essential role of microglial BMAL1 in maintenance of synapse homeostasis in the aging brain.
Exercise-induced irisin improves follicular dysfunction by inhibiting IRE1α-TXNIP/ROS-NLRP3 pathway in PCOS
Authors: Weng Yajing , Zhang Yaling , Wang Daojuan , Wang Rong , Zou Xiang , Shen Shanmei , Wang Hongwei , Wu Xiaoke , Wen Yanting , Wang Yong 
Published: November 2022

Abstract
Background
Excessive production of androgen drives oxidative stress (OS) and inflammasome activation in ovarian granulosa cells (GCs). Therefore, the induced follicular developmental disorder is the major cause of infertility in women with polycystic ovary syndrome (PCOS). Exercise-induced upregulation of irisin is capable of regulating metabolism by reducing OS and inflammation. Exercise has been shown to alleviate a range of PCOS symptoms, including maintaining a normal menstrual cycle, in several clinical trials.
Methods
Female Sprague-Dawley (SD) rats and primary ovarian cells were treated with two different androgens, dehydroepiandrosterone (DHEA) and dihydrotestosterone (DHT), to simulate a hyperandrogenic environment, followed by eight weeks of exercise training and irisin intervention. The levels of reactive oxygen species (ROS), tissue inflammation and fibrosis were examined using hematoxylin and eosin (H&E) staining, western blot, quantitative real-time PCR (qRT-PCR), dichlorofluorescein diacetate (DCF-DA) probe detection, immunofluorescence staining, immunohistochemistry, and Sirius red staining.
Results
Exercise for eight weeks improved polycystic ovarian morphology and decreased the levels of inflammation, OS, and fibrosis in PCOS rats. Hyperandrogen increased ROS production in ovarian cells by inducing endoplasmic reticulum stress (ERS) and activating the inositol-requiring enzyme 1α (IRE1α)-thioredoxin-interacting protein (TXNIP)/ROS-NOD-like receptor family pyrin domain containing 3 (NLRP3) signaling pathway, further enhancing the levels of inflammation. Irisin suppressed the expression of IRE1α and its downstream targets, thus improving the ovarian dysfunction of PCOS rats induced by hyperandrogen.
Conclusion
Exercise can alleviate various phenotypes of PCOS rats induced by DHEA, and its therapeutic effect may be mediated by secreting beneficial myokines. IRE1α may be an important target of irisin for reducing OS and inflammation, thereby improving ovarian fibrosis.
K[(CuII,MnII,MnIII)2(TeO3)3]∙2H2O, the first zemannite-type structure based on a Jahn-Teller-distorted framework
Authors: Eder Felix , Weil Matthias , Miletich Ronald 
Published: November 2022

Abstract
Synthetic single crystals of K[(CuII,MnII,MnIII)2(TeO3)3]∙2H2O were obtained from an overconcentrated alkaline aqueous solution in the system K2O-MnO-CuO-TeO2 under hydrothermal conditions at T ≤ 220 °C. Subeuhedral single crystals have been investigated crystallographically by means of single-crystal X-ray diffraction. The crystal structure of this new zemannite-type representative follows a monoclinic twofold superstructure. The doubling of the unit-cell volume is accompanied by a hexagonal-to-monoclinic symmetry reduction, resulting in threefold twinning with individual crystal domains following the space group symmetry P21. Refinements of site-occupation factors and the evaluation of bond valences suggest a distribution of di- and trivalent cations on the octahedral M sites with a ratio (CuII+MnII) : MnIII approximating 1 : 1. From arguments about the cation sizes and the individual bond valence sums, a distribution of CuII1–xMnIIIx and MnIIx MnIII1–x at each two of the four M positions can be assumed with a presumed x between ~0.14 and ~0.50. The K+ cations and crystal water molecules inside the channels are located off the central channel axis. In contrast to most other known zemannite-type phases, the extra-framework atoms show full site occupations and are not disordered. The distribution of the channel contents supports the anisotropic deformation of the surrounding framework, which follows the local symmetry reduction as required for the Jahn-Teller distortion of the octahedrally coordinated M sites within the framework. The arrangement of the deformed channels can be understood as the origin of the existing superstructure.
Clinical and demographic factors associated with the effectiveness of temporomandibular joint arthroscopy
Authors: Gaete Carlos , Droguett Christian , Sáez Felipe , Astorga Paula 
Published: November 2022

Abstract
Purpose
High success rates and minimal complications have consolidated arthroscopy as the therapeutic alternative of choice for minimally invasive treatment of internal disorders (ID) of the temporomandibular joint (TMJ). However, there is no certainty regarding the demographic and clinical factors associated with the technique's success or failure. This study was performed to analyze the effectiveness of arthroscopy regarding pain and the mandibular dynamics and also to determine whether variables such as age, sex, preoperative Wilkes stage and the level of arthroscopy performed influence the results.
Methods
A retrospective study was conducted involving 92 patients with ID of the TMJ between September 2017 and February 2020. In all cases a first stage of intra-articular lysis and lavage was executed. As needed, a phase of operative arthroscopy or arthroscopic discopexy were implemented.
Results
A total of 152 arthroscopies were performed. Both the variation in pain and mouth opening in patients with ID of the TMJ treated were statistically significant for the follow-up periods studied. Better results were observed for patients with lower Wilkes stages and for higher levels of arthroscopy performed. No association with age was found.
Conclusion
Based on the results, we recommend early intervention as soon as an ID in the TMJ is detected.
SDNTruth: Innovative DDoS Detection Scheme for Software-Defined Networks (SDN)
Authors: Linhares Tiago , Patel Ahmed , Barros Ana Luiza , Fernandez Marcial 
Published: November 2022

Abstract
Software-Defined Networks (SDN) are becoming a trending technology in the modern Internet by splitting control and data planes and using a central controller. A SDN controller provides flexible flows management at wire-speed packet forwarding. The centralized control gives an opportunity to implement detection and mitigation security attacks inside the SDN controller. Typically, Distributed Denial of Service (DDoS) attacks poses an immense threat to the Internet security. However, the prediction and prevention of DDoS attacks in SDN environments are a huge challenge. In this paper, we introduce a mechanism to mitigate DDoS attacks in SDN using statistical analysis and traffic entropy. To validate the proposal, a prototype was built in Mininet tool. The accuracy and training time were compared against different Machine Learning algorithms. Finally, we expound about the effectiveness and limitation of the proposed solution as well indicate further research opportunities.
A lexicographic optimisation approach to promote more recent features on longitudinal decision-tree-based classifiers: Applications to the English Longitudinal Study of Ageing
Authors: Ribeiro Caio , Freitas Alex A. 
Published: November 2022

Abstract
Supervised machine learning algorithms rarely cope directly with the temporal information inherent to longitudinal datasets, which have multiple measurements of the same feature across several time points and are often generated by large health studies. In this paper we report on experiments which adapt the feature-selection function of decision tree-based classifiers to consider the temporal information in longitudinal datasets, using a lexicographic optimisation approach. This approach gives higher priority to the usual objective of maximising the information gain ratio, and it favours the selection of features more recently measured as a lower priority objective. Hence, when selecting between features with equivalent information gain ratio, priority is given to more recent measurements of biomedical features in our datasets.
We performed experiments with 20 longitudinal datasets created from a human ageing study, and concluded from our results that this lexicographic optimisation approach is worthwhile and computationally inexpensive. In addition to a slight improve in predictive accuracy, the changed feature-selection function promotes models based on information that is more directly related to the subject's current biomedical situation and, thus, more actionable.
Lopinavir and Ritonavir have a high affinity to SARS-CoV-2 S-protein Receptor-Binding Domain sequenced in Brazil
Authors: Marinho Aline Diogo , Braz Helyson Lucas , Silveira João Alison Moraes , Rocha Danilo Galvão , Jorge Roberta Jeane Bezerra , Andrade Geanne Matos 
Published: November 2022

Abstract

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected at China in December 2019 and rapid worldwide spread, causing the coronavirus disease 2019 (COVID-19). In this pandemic situation, the importance of structural-functional relationships between virus and host cell should be considered. In this work, we investigated the molecular interactions of seven drugs used in clinical therapy by in silico analysis with specific protein target of SARS-CoV-2 – RBD domain of the Brazilian S protein genome sequence – in docking models. Initially, a three-dimensional structure of SARS-CoV-2 spike glycoprotein receptor-binding domain (RBD) model was obtained by homology. Then, a prediction analysis of cavities in the RBD structure was performed to detect a possible active site in the S protein fragment. Our molecular docking study demonstrated that only 2 ligands showed considerably acceptable values in relation to the seven drugs (Umifenovir, Darunavir, Lopinavir, Ritonavir, Remdesivir, Pirfenidone, Oseltamivir) used to screen. The interaction between Lopinavir and RBD revealed binding affinity of -9.8 kcal/mol and interactions with residues PHE168, GLY167, SER176, GLN175, GLU166, LEU134, LEU137, TYR171, PHE138, LEU174, PHE172. Ritonavir demonstrated binding affinity of -8.9 kcal/mol and interactions with residues ARG148, ASN130, VAL23, SER81, ASN33, PHE29, TYR33, SER31, ASN132, ALA26, ALA30, ALA34, TYR133. Molecular dynamics simulations were performed to evaluate the stability of the complexes formed. The present study shows that protease inhibitors Lopinavir and Ritonavir have best binding at the active site (the RBD of S protein) through molecular docking.
Enhancement of Plasmonic Photovoltaics with Pyramidal Nanoparticles
Authors: Yassin Heba , El-Batawy Yasser , Soliman Ezzeldin 
Published: November 2022

Abstract
Light trapping as a result of embedding plasmonic Nano-Particles (NPs) into Photovoltaics (PVs) has been recently used to achieve better optical performance compared to conventional PVs. This light trapping technique enhances the efficiency of PVs by confining the incident light into hot-spot field regions around the NPs, which possess higher absorption, thus more enhancing of photocurrent. This research aims to study the impact of embedding metallic pyramidal-shaped NPs inside the PV’s active region for enhancing the efficiency of plasmonic silicon PVs. The optical properties of the pyramidal-shaped NPs in the visible and near-infrared spectrum have been investigated.The light absorption into silicon PV is significantly enhanced by embedding periodic arrays of pyramidal NPs in the cell comparedto the case of bare silicon PV. Furthermore, the effects of varying the pyramidal-shaped NPs dimensions on the absorption enhancement are studied. In addition, a sensitivity analysis has been performed, which helps in identifying the allowed fabrication tolerance for each geometrical dimension. The performance ofthe proposed pyramidal NP is compared with other frequently used shapes, such as cylinder, cone and hemisphere. Poisson’s and Carrier’s continuity equations are formulated and solved for the current density-voltage characteristics associated with embedded pyramidal NPs with different dimensions. The optimized array of pyramidal NPs provides an enhancement of 41% in the generated current density if compared to the bare silicon cell.
Dual-trigger improves oocyte maturation in patients with low oocyte maturation rate: a self-control study
Authors: Li Xiaolan , Li Qian , Cai Jiawei , Chang Yajie , Wang Yanfang , Liang Xiaoyan , Huang Rui 
Published: November 2022

Abstract
Background
For patients with low maturation rate, the efficacy of dual-trigger is still uncertain with few related data available. This large retrospective study focused on the effect of dual-trigger in oocyte maturation in patients with a history of low oocyte maturation rate.
Methods
A large retrospective self-controlled study was performed, which included 199 patients with a high proportion of immature oocyte (> 50%) in a previous hCG-only trigger cycle receiving a subsequent dual-trigger between January 2014 and June 2022. The primary outcome was the oocyte maturation rate, and the secondary outcomes were the number of oocytes retrieved, the normal fertilization rate, the high-quality embryos rate and the blastocyst formation rate. Linear regression analysis was applied to control the potential confounders.
Results
The results showed that no significant difference was observed in the number of follicles of > 14 mm and the E2 level on trigger day between the hCG-only and the dual-trigger cycle. Although the number of oocyte retrieval was comparable, higher rates of the oocyte maturation (64.96% vs. 39.40%), P < 0.001) and the normal fertilization (70.47% vs. 62.89%, P = 0.006) were associated with the dual-trigger group. In addition, a slightly higher rate of high-quality embryos (51.21% vs. 50.53%) and blastocyst formation (46.18% vs. 30%) were also observed in the dual-trigger group, although difference didn’t reach statistical significance. Furthermore, linear mixed model confirmed that the dual-trigger was positively associated with the oocyte maturation rate (β = 0.294, P < 0.001) after adjusting potential confounders, such as ovarian stimulation protocols.
Conclusions
Co-administration of GnRH-a and hCG for final oocyte maturation was suggested as an effective tool to improve oocyte maturation in patients with low maturation rate.
Discrete non standard formulation of PDE inverse problems
Authors: Moussata Cyr S. Ngamouyih , Haggar Mahamat Saleh Daoussa , Yindoula Deryl Nathan Bonazébi , Mampassi Benjamin 
Published: November 2022

Abstract

In this paper, we are interested in the computation of the unknown initial state for the simulation and prediction of PDE systems where the solution measures are partially known over a time interval. Such a problem is usually solved by an ill-posed optimal control problem. Based on an appropriate collocation approximation, we obtain a discrete inverse problem. To solve this problem, a non-standard discrete approach is used. This allows to obtain a transformation of the original problem into a well-posed ones based on the zero controllability of a discrete system. The desired control is then calculated as well as the discrete approximation of the initial state values.
Mathematics Subject Classification. 35K55; 35J60; 80A22.
The Product Structure and Algebraic Ricci Solitons of Three-dimensional Lorentzian Lie Groups
Authors: Wang Yanli 
Published: November 2022

Abstract
In this paper, we define a product structure on three-dimensional Lorentzian Lie groups. We compute canonical connections and Kobayashi-Nomizu connections and their curvature with this product structure. We classify algebraic Ricci solitons associ- ated to canonical connections and Kobayashi-Nomizu connections on three-dimensional Lorentzian Lie groups with this product structure.
Assembly line balancing and sensitivity analysis of a single-model stochastic sewing line using arena simulation modelling.
Authors: Hossain Arif , Muneer Khalid Ibn 
Published: November 2022

Abstract

Assembly line balancing is always a critical responsibility for manufacturers as it controls the efficiency and productivity of the assembly line. There are many techniques to solve line balancing problems, some of which are revealed in the literature review section, but computer-aided simulation modelling is prevalent among them. This study aims to analyze an assembly line balancing problem of stochastic nature using a discrete event simulation software (Arena) for the optimal solution and sensitivity analysis of the solution. The empirical study was carried out at Arunima Sportswear Limited garment factory, and a garment style (kid’s pants) with 21 operations was taken into account. First, the computer model was verified by line supervisors and validated by a statistical hypothesis test (t-test). Then, using the Arena OptQuest tool, an optimal solution to the model is achieved. Finally, a sensitivity analysis is performed by varying the values of some key factors (i.e. entities per arrival, process failure time, and operators’ absenteeism) to determine the level of uncertainty of the model.
SGNNRec: A Scalable Double-layer Attention-based Graph Neural Network Recommendation Model
Authors: He Jing , Tang Le , Tang Dan , Wang Ping , Cai Li 
Published: November 2022

Abstract
Due to the information from the multi-relationship graphs is difficult to aggregate, the graph neural network recommendation model focuses on single-relational graphs (e.g., the user-item rating bipartite graph and user-user social relationship graphs). However, existing graph neural network recommendation models have insufficient flexibility. The recommendation accuracy instead decreases when low-quality auxiliary information is aggregated in the recommendation model. This paper proposes a scalable graph neural network recommendation model named SGNNRec. SGNNRec fuse a variety of auxiliary information (e.g., user social information, item tag information and user-item interaction information) beside user-item rating as supplements to solve the problem of data sparsity. A tag cluster-based item-semantic graph method and an apriori algorithm-based user-item interaction graph method are proposed to realize the construction of graph relations. Furthermore, a double-layer attention network is designed to learn the influence of latent factors. Thus, the latent factors are to be optimized to obtain the best recommendation results. Empirical results on real-world datasets verify the effectiveness of our model. SGNNRec can reduce the influence of poor auxiliary information; moreover, with increasing the number of auxiliary information, the model accuracy improves.
Pestilence report of Helicoverpa armigera (Hübner) in apple fruit orchards in Northern Himalayan regions of India
Authors: Sharma Vani , Daroch Rakesh Kumar , Kasi Indra Kumar , Sharma PL , Kumar Pramod 
Published: November 2022

Abstract
Helicoverpa armigera Hübner (Lepidoptera: Noctuidae) an extremely destructive pest, causes large economic losses in numerous crops under favourable conditions. In the past few years, it has been seen by researchers and orchardists, feeding on apple fruits grown under high density plantation system under Himachal Pradesh Horticulture Development Project in North Himalayan regions ranging in 320.22’-330.12’N and 750.47’-790.04E with an extent of damage upto 10–15 per cent at various sites. Therefore, in order to determine its biotic potential on apple as a potential host, we studied the demographics of H. armigera on three apple varieties viz., Jeromine, Gale Gala and Red Velox at three fruit growth stages i.e. pea, walnut and mature stage with chickpea and chickpea based diet as control. The test insect completed its life cycle on apple and the duration of different developmental stages was almost equivalent to control, signifying it as potential pest in coming time. H. armigera was unable to survive beyond fifth instar in mature fruits stages, thereby indicating its preference for immature fruits. The population growth parameters were nearly identical; however, the highest values of finite rate of increase (λ) and intrinsic rate of increase (r) with minimum generation time (T) was recorded on insects reared on Gale Gala fruits at walnut stage (1.17, 0.15 and 36.59 days, respectively) which was found to be the most suitable host, while Red Velox was found to be the least preferable host at both pea and walnut stage. Overall, investigations on the biology of H. armigera revealed that apple is a preferred prospective host. If favourable environmental conditions exist, the insect may cause significant harm to high density apple fruit crops, necessitating its management in the future.
Spatially coherent statistical simulation of widespread flooding events under climate change
Authors: Griffin Adam , Kay Alison , Stewart Elizabeth , Sayers Paul 
Published: November 2022

Abstract
Simulating rare widespread hydrological events can be difficult even with the use of modelled data such as the UKCP18 12 km regional climate projections. To generate larger event sets for application in catastrophe modelling, two statistical approaches are highlighted and applied to widespread GB-generated flooding events using a grid-based hydrological model and UKCP18 regional projections. An Empirical Copula method was applied on a national scale, generating over 600,000 events across two time-slices (1980–2010 and 2050–2080). This was compared to model-generated events and showed good matching across time-slices and ensemble members, although lacked some ability to describe the least-rare events. The Empirical Copula was also compared to an implementation of a conditional exceedance model. This model was much more computationally intensive so was restricted to Northwest England but offered the ability to be tuned more finely through choices of marginal distributions. Analysing over 11,000 events, it also matched well with the Empirical Copula and model-generated events but under-represented the smallest events. Both approaches require a broad dataset to draw from but showed reasonable efficacy. For simple statistics, the Empirical Copula shows the potential to be a powerful tool in exploring spatial structure over large regions or at a fine spatial resolution.