bluuebunny/crossref_metadata_2025 huggingface dataset:
The WRF Simulation Influence of Assimilating GNSS Water Vapor and Parameterization Schemes on Typhoon Rumbia
Authors: Li Li , Ma Yixiang , Li Kai , Pan Jianping , Zhang Mingsong
Published: February 2024

The Weather Research and Forecasting (WRF) model was used to simulate Typhoon Rumbia in this paper. The sensitivity experiments were conducted with 16 different parameterization combination schemes, including four microphysics (WSM6, WSM5, Lin, and Thompson), two boundary layers (YSU and MYJ), and two cumulus convection (Kain–Fritsch and Grell–Freitas) schemes. The impacts of 16 parameterization combination schemes and the data assimilation (DA) of Global Navigation Satellite System (GNSS) water vapor were evaluated by the simulation accuracy of typhoon track and intensity. The results show that the typhoon track and intensity are significantly influenced by parameterization schemes of cumulus and boundary layers rather than microphysics. The averaged track error of Lin_KF_Y is 104.73 km in the entire 72-h simulation period. The track errors of all the other combination schemes are higher than Lin_KF_Y. During the entire 72-h, the averaged intensity error of Thompson_GF_M is 1.36 hPa. It is the lowest among all the combination schemes. As for data assimilation, the simulation accuracy of typhoon tracks can be significantly improved by adding the GNSS water vapor. Thompson_GF_M-DA combination scheme has the lowest average track error of 45.05 km in the initial 24 h. The Lin_KF_Y-DA combination scheme exhibits an average track error of 32.17 km on the second day, 28.03 km on the third day, and 35.33 km during 72-h. The study shows that the combination of parameterization schemes and the GNSS water vapor data assimilation significantly improve the initial conditions and the accuracy of typhoon predictions. The study results contribute to the selection of appropriate combinations of physical parameterization schemes for the WRF-ARW model in the mid-latitude region of the western Pacific coast.
Compact Data Learning for Machine Learning Classifications
Authors: Kim Song-Kyoo (Amang)
Published: February 2024

This paper targets the area of optimizing machine learning (ML) training data by constructing compact data. The methods of optimizing ML training have improved and become a part of artificial intelligence (AI) system development. Compact data learning (CDL) is an alternative practical framework to optimize a classification system by reducing the size of the training dataset. CDL originated from compact data design, which provides the best assets without handling complex big data. CDL is a dedicated framework for improving the speed of the machine learning training phase without affecting the accuracy of the system. The performance of an ML-based arrhythmia detection system and its variants with CDL maintained the same statistical accuracy. ML training with CDL could be maximized by applying an 85% reduced input dataset, which indicated that a trained ML system could have the same statistical accuracy by only using 15% of the original training dataset.
Effects of Complete and Partial Loss of the 24S-Hydroxycholesterol-Generating Enzyme Cyp46a1 on Behavior and Hippocampal Transcription in Mouse
Authors: Shu Hong-Jin , Ziolkowski Luke H. , Salvatore Sofia V. , Benz Ann M. , Wozniak David F. , Yuede Carla M. , Paul Steven M. , Zorumski Charles F. , Mennerick Steven
Published: February 2024

Brain cholesterol metabolic products include neurosteroids and oxysterols, which play important roles in cellular physiology. In neurons, the cholesterol oxidation product, 24S-hydroxycholesterol (24S-HC), is a regulator of signaling and transcription. Here, we examined the behavioral effects of 24S-HC loss, using global and cell-selective genetic deletion of the synthetic enzyme CYP46A1. Mice that are globally deficient in CYP46A1 exhibited hypoactivity at young ages and unexpected increases in conditioned fear memory. Despite strong reductions in hippocampal 24S-HC in mice with selective loss of CYP46A1 in VGLUT1-positive cells, behavioral effects were not recapitulated in these conditional knockout mice. Global knockout produced strong, developmentally dependent transcriptional effects on select cholesterol metabolism genes. These included paradoxical changes in Liver X Receptor targets. Again, conditional knockout was insufficient to recapitulate most changes. Overall, our results highlight the complex effects of 24S-HC in an in vivo setting that are not fully predicted by known mechanisms. The results also demonstrate that the complete inhibition of enzymatic activity may be needed for a detectable, therapeutically relevant impact on gene expression and behavior.
Comprehensive Data-Driven Assessment of Non-Kinase Targets of Inhibitors of the Human Kinome
Authors: Mobasher Mona , Vogt Martin , Xerxa Elena , Bajorath Jürgen
Published: February 2024

Protein kinases (PKs) are involved in many intracellular signal transduction pathways through phosphorylation cascades and have become intensely investigated pharmaceutical targets over the past two decades. Inhibition of PKs using small-molecular inhibitors is a premier strategy for the treatment of diseases in different therapeutic areas that are caused by uncontrolled PK-mediated phosphorylation and aberrant signaling. Most PK inhibitors (PKIs) are directed against the ATP cofactor binding site that is largely conserved across the human kinome comprising 518 wild-type PKs (and many mutant forms). Hence, these PKIs often have varying degrees of multi-PK activity (promiscuity) that is also influenced by factors such as single-site mutations in the cofactor binding region, compound binding kinetics, and residence times. The promiscuity of PKIs is often—but not always—critically important for therapeutic efficacy through polypharmacology. Various in vitro and in vivo studies have also indicated that PKIs have the potential of interacting with additional targets other than PKs, and different secondary cellular targets of individual PKIs have been identified on a case-by-case basis. Given the strong interest in PKs as drug targets, a wealth of PKIs from medicinal chemistry and their activity data from many assays and biological screens have become publicly available over the years. On the basis of these data, for the first time, we conducted a systematic search for non-PK targets of PKIs across the human kinome. Starting from a pool of more than 155,000 curated human PKIs, our large-scale analysis confirmed secondary targets from diverse protein classes for 447 PKIs on the basis of high-confidence activity data. These PKIs were active against 390 human PKs, covering all kinase groups of the kinome and 210 non-PK targets, which included other popular pharmaceutical targets as well as currently unclassified proteins. The target distribution and promiscuity of the 447 PKIs were determined, and different interaction profiles with PK and non-PK targets were identified. As a part of our study, the collection of PKIs with activity against non-PK targets and the associated information are made freely available.
Special Issue “Alzheimer’s Disease—115 Years after Its Discovery”
Authors: Cardoso Susana , Carvalho Cristina , Correia Sónia C.
Published: February 2024

Alzheimer’s disease (AD) is a progressive and multifactorial disease that significantly compromises the lives of millions of people worldwide [...]
Identification of CYFIP2 Arg87Cys Ligands via In Silico and In Vitro Approaches
Authors: Venturi Biembengut Ísis , de Castro Andreassa Emanuella , de Souza Tatiana A. C. B.
Published: February 2024

The advancement of next-generation sequencing has enabled the identification of specific mutations associated with early infantile epileptic encephalopathies (EIEEs). In EIEE, epileptic spasms and seizures that occur since early childhood lead to impaired neurological development. The CYFIP2 p.Arg87Cys variant was recently related to EIEE. CYFIP2 participates in the Wave Regulatory Complex (WRC), which is related to the regulation of actin dynamics. The variant residue is at the interface between the CYFIP2 protein and WAVE1 protein inside the WRC. Thus, the weakening of this interaction induced by the residue modification, which also causes the flexibilization of the loop 80–110 within the CYFIP2 structure, allows the constant activation of the WCR. This study aimed to identify ligands for CYFIP2 p.Arg87Cys and potential therapy targets using in silico in vitro approaches. Models of different CYFIP2 versions were constructed, and molecular docking analyses were conducted. A total of 3946 ligands from the PDE3 and Drugbank databases were screened, leading to the identification of 11 compounds that selectively bind to the variant protein. The impact of binding in CYFIP2 was also evaluated using a thermal stability assay. These findings contribute to a better understanding of CYFIP2’s functional role in pathology and can guide more in vitro experiments, facilitating the development of targeted therapies for CYFIP2-related conditions.
One-Year Outcomes for Depression and Anxiety in SLE Patients
Authors: Duca Liliana , Roman Nadinne Alexandra , Ifteni Petru , Teodorescu Andreea
Published: February 2024

Neuropsychiatric Systemic Lupus Erythematosus (NPSLE) is a severe form of SLE involving the nervous system, resulting in neurological and psychiatric symptoms. Although research has shown that SLE patients often suffer from cognitive impairments, depression, and anxiety, there are no specialized guidelines for psychiatric assessment and treatment. This study aimed to investigate the progression of neuropsychiatric symptoms in SLE patients, explicitly focusing on anxiety and depression, over a year. It also aimed to identify potential biomarkers linked to NPSLE and explore the connection between NPSLE and the overall progression of SLE. Our research involved a longitudinal study with 65 adults diagnosed with SLE. Participants underwent various physical, biochemical, and serological tests and were assessed using disease activity indexes like BILAG-2004 and SLEDAI-2K. Participants also underwent psychological assessments using the Hamilton Anxiety and Depression Rating Scales. The study did not find any significant impact of antidepressant therapy on the evolution of anxiety and depression among participants. However, medications like Methotrexate and Plaquenil showed a substantial reduction in these symptoms. Moreover, anxiolytic therapy seems to influence depression in SLE patients. The study also noted that anxiety levels tend to increase over time but are not directly associated with SLE activity. This study concludes that although specific SLE medications can affect the level of anxiety and depression, the overall effectiveness of neuropsychiatric therapy in managing these symptoms is limited. The findings suggest that further research into the tailored management of NPSLE symptoms and a deeper understanding of the disease’s psychiatric aspects are needed.
The Application of Emodin Treatment on Nasopharyngeal Carcinoma Therapy
Authors: Wu Chung-Chun , Chen Mei-Shu , Chen Jen-Yang
Published: February 2024

Nasopharyngeal carcinoma (NPC) is a malignancy prevailing in Taiwan, Hong Kong, Southern China, Southeast Asia, and North Africa. Although early-stage NPC responds well to the primary treatment of radio-chemotherapy, the mortality rate of advanced NPC remains high. Therefore, developing new therapies for nasopharyngeal carcinoma is an urgent task. Emodin is an anthraquinone derivative mainly found in Rheum palmatum. Emodin has been found to possess many anti-cancer functions against various types of cancers, but they are less discussed in the treatment of NPC. This review organized the different studies about the anti-NPC activity of emodin and discussed the potential and challenges of emodin treatment in NPC therapy.
Real-Time On-Site Monitoring of Viruses in Wastewater Using Nanotrap® Particles and RICCA Technologies
Authors: Sharma Vishnu , Takamura Hitomi , Biyani Manish , Honda Ryo
Published: February 2024

Wastewater-based epidemiology (WBE) is an effective and efficient tool for the early detection of infectious disease outbreaks in a community. However, currently available methods are laborious, costly, and time-consuming due to the low concentration of viruses and the presence of matrix chemicals in wastewater that may interfere with molecular analyses. In the present study, we designed a highly sensitive “Quick Poop (wastewater with fecal waste) Sensor” (termed, QPsor) using a joint approach of Nanotrap microbiome particles and RICCA (RNA Isothermal Co-Assisted and Coupled Amplification). Using QPsor, the WBE study showed a strong correlation with standard PEG concentrations and the qPCR technique. Using a closed format for a paper-based lateral flow assay, we were able to demonstrate the potential of our assay as a real-time, point-of-care test by detecting the heat-inactivated SARS-CoV-2 virus in wastewater at concentrations of 100 copies/mL and within one hour. As a proof-of-concept demonstration, we analyzed the presence of viral RNA of the SARS-CoV-2 virus and PMMoV in raw wastewater samples from wastewater treatment plants on-site and within 60 min. The results show that the QPsor method can be an effective tool for disease outbreak detection by combining an AI-enabled case detection model with real-time on-site viral RNA extraction and amplification, especially in the absence of intensive clinical laboratory facilities. The lab-free, lab-quality test capabilities of QPsor for viral prevalence and transmission in the community can contribute to the efficient management of pandemic situations.
The Role of Sounds and Music in Emotion and Cognition
Authors: Piccardi Laura , Palmiero Massimiliano , Nori Raffaella
Published: February 2024

It is widely agreed upon that both natural and man-made sounds, including music, profoundly impact our emotions and cognitive abilities, such as our attention, memory, problem-solving, decision-making, and creativity [...]
Adaptive LDA Classifier Enhances Real-Time Control of an EEG Brain–Computer Interface for Decoding Imagined Syllables
Authors: Wu Shizhe , Bhadra Kinkini , Giraud Anne-Lise , Marchesotti Silvia
Published: February 2024

Brain-Computer Interfaces (BCIs) aim to establish a pathway between the brain and an external device without the involvement of the motor system, relying exclusively on neural signals. Such systems have the potential to provide a means of communication for patients who have lost the ability to speak due to a neurological disorder. Traditional methodologies for decoding imagined speech directly from brain signals often deploy static classifiers, that is, decoders that are computed once at the beginning of the experiment and remain unchanged throughout the BCI use. However, this approach might be inadequate to effectively handle the non-stationary nature of electroencephalography (EEG) signals and the learning that accompanies BCI use, as parameters are expected to change, and all the more in a real-time setting. To address this limitation, we developed an adaptive classifier that updates its parameters based on the incoming data in real time. We first identified optimal parameters (the update coefficient, UC) to be used in an adaptive Linear Discriminant Analysis (LDA) classifier, using a previously recorded EEG dataset, acquired while healthy participants controlled a binary BCI based on imagined syllable decoding. We subsequently tested the effectiveness of this optimization in a real-time BCI control setting. Twenty healthy participants performed two BCI control sessions based on the imagery of two syllables, using a static LDA and an adaptive LDA classifier, in randomized order. As hypothesized, the adaptive classifier led to better performances than the static one in this real-time BCI control task. Furthermore, the optimal parameters for the adaptive classifier were closely aligned in both datasets, acquired using the same syllable imagery task. These findings highlight the effectiveness and reliability of adaptive LDA classifiers for real-time imagined speech decoding. Such an improvement can shorten the training time and favor the development of multi-class BCIs, representing a clear interest for non-invasive systems notably characterized by low decoding accuracies.
The Relationship between Perceived Organizational Support, Work Engagement, Organizational Citizenship Behavior, and Customer Orientation in the Public Sports Organizations Context
Authors: Park Jongchul , Kim Jooyoung
Published: February 2024

As sports activities have recently become socio-culturally important in South Korea, the roles and functions of public sports organizations are attracting attention. In this situation, perceived organizational support is considered one of the significant variables to explain the attitudes and behaviors of employees within the organizations. Hence, the purpose of this study is to investigate the relationship between perceived organizational support of public sports organizations, work engagement, organizational citizenship behavior, and customer orientation and examine the mediating effect of work engagement. This study collected data from 248 employees working for public sports organizations, and data were analyzed with SPSS 26.0 and AMOS 26.0. The results showed the following. (1) Perceived organizational support has a significant positive effect on work engagement but does not affect organizational citizenship behavior and customer orientation. (2) Work engagement significantly positively affects organizational citizenship behavior and customer orientation. (3) Work engagement has been shown to fully mediate the relationship between perceived organizational support, organizational citizenship behavior, and customer orientation. This study suggests that public sports organizations need an efficient support strategy that can maximize employees’ work engagement. For example, organizations should increase their sense of unity with employees and understand the importance of their work to strengthen perceived organizational support. Lastly, organizations need to create an environment where employees can devote themselves to and focus on their work.
Understanding Mobile OTT Service Users’ Resistance to Participation in Wireless D2D Caching Networks
Authors: Jang Yumi , Kim Seongcheol
Published: February 2024

With the explosive pace of mobile over-the-top (OTT) video content streaming services, mobile network traffic has seen unprecedented growth in recent years. However, the limitation of antenna performance, the burden of investment cost, and restricted resources hinder improving the current mobile networks’ functionality. Accordingly, wireless device-to-device (D2D) caching networks came to the fore as one of the competitive alternatives for alleviating the overloads of mobile network traffic. Wireless D2D caching networks can be a desirable alternative for OTT service providers and telecommunication operators, but the problem is user resistance. User participation is imperative to deliver wireless D2D caching network functionality successfully. Thus, to gain a deeper understanding of user resistance toward wireless D2D caching networks and their underlying sources, this study introduces two perceived cost factors contributing to this resistance and one perceived benefit that mitigates such resistance. Based on an online survey, this study found new theoretical links among perceived costs and benefits, resistance, and participation intention. The findings reveal that user resistance is predicted by perceived costs, encompassing resource sacrifices and privacy concerns, whereas perceived benefits—specifically, perceived usefulness—did not significantly influence resistance. This implies that telecommunication operators should prioritize market requirements over technological advantages, emphasizing the potential for successful commercialization of wireless D2D caching networks.
Effect of Footing Shape on the Rocking Behavior of Shallow Foundations
Authors: Khezri Ali , Moradi Mohamadali , Mir Mohammad Hosseini Seyed Majdeddin , Park Hongbae , Lee Daeyong
Published: February 2024

Sources such as wind or severe seismic activity often exert extreme lateral loading onto the shallow foundations supporting high-rise structures such as bridge piers, buildings, shear walls, and wind turbine towers. Such loading conditions may cause the foundation to exhibit nonlinear responses such as uplift and bearing capacity mobilization of the supporting soil (i.e., rocking behavior). Previous numerical and experimental studies suggest that while such inelastic behaviors may engender residual deformations in the soil–foundation system, they offer potential benefits to the overall integrity of structures through dissipating energy and reducing inertia forces transmitted to the superstructure, thereby limiting seismic demand on structural elements. This study investigates the effect of footing shape on the rocking performance of shallow foundations in different subgrade densities and initial vertical factor of safety (FSv). To this end, a series of reduced-scale slow cyclic tests under 1 g condition were conducted using a single degree of freedom (SDOF) structure model. The performance of different footing shapes was studied in terms of moment capacity, recentering ratio, rocking stiffness, damping ratio, and settlement. For three foundations with different length-to-width ratios, the results indicate that increasing the safety factor and length-to-width ratio leads to thinner, S-shaped moment–rotation curves, mainly owing to the enhanced recentering capability and the P-δ effect. Moreover, across all foundation types, the repetition of a limited loading cycles with consistent rotation amplitude does not cause stiffness degradation or moment capacity reduction.
Performance Study on Laterite Road Base Stabilised with Emulsions Incorporating Biochar
Authors: Chilufya Andrew , Gangell David , Shahin Mohamed A. , Abdullah Hayder H.
Published: February 2024

This study explores the utilisation of biochar as an innovative and sustainable additive to emulsions for stabilising laterite road base material in pavements, with the environmental benefit of sequestering atmospheric carbon and stable form storing. A diverse range of design mixtures for the treated road base material with the proposed biochar–emulsion binder was developed for experimental validation and subsequent steps encompassed an array of laboratory tests to scrutinise the engineering attributes of the mixtures. The tests were selected to assess various properties such as unconfined compressive strength, tensile strength, resilient modulus, flexural modulus, fatigue life, and deformation characteristics. To gain practical insights from real-world conditions, two field trials were also conducted to evaluate the performance of the stabilised road base. The findings revealed that a design mix incorporating 5% biochar and 6% emulsion delivered an average unconfined compressive strength (UCS) of 1.5 MPa, which adheres to the standard UCS range for cemented lightly bound base course material. The optimal ratio of biochar to emulsion was identified as 1:1.6, which delivered a higher resilient modulus value than did the minimum stipulated by the literature for average daily traffic in the first year of design. As the temperature rose, the stabilised laterite base exhibited a reduction in its flexural modulus; however, it demonstrated minimal susceptibility to fluctuations in frequency. The deformation observed in the wheel-tracking tests for mixtures of the optimum biochar-to-emulsion ratio was less than 1 mm, which is remarkably lower than the maximum requirement outlined in the literature (i.e., 15 mm). Furthermore, visual inspection post-testing detected minimal cracking. These findings indicate that the integration of biochar and emulsion in the construction of road pavements is a promising technique that could contribute to carbon sequestration and climate change mitigation without sacrificing pavement performance. The successful field trials provided further evidence of the feasibility of this novel technique.
Safety of Boron Neutron Capture Therapy with Borofalan(10B) and Its Efficacy on Recurrent Head and Neck Cancer: Real-World Outcomes from Nationwide Post-Marketing Surveillance
Authors: Sato Mariko , Hirose Katsumi , Takeno Satoshi , Aihara Teruhito , Nihei Keiji , Takai Yoshihiro , Hayashi Toshimitsu , Bando Kosuke , Kimura Hitomi , Tsurumi Keisuke , Ono Koji
Published: February 2024

Background: This study was conducted to evaluate the real-world safety and efficacy of boron neutron capture therapy (BNCT) with borofalan(10B) in Japanese patients with locally advanced or locally recurrent head and neck cancer (LA/LR-HNC). Methods: This prospective, multicenter observational study was initiated in Japan in May 2020 and enrolled all patients who re-ceived borofalan(10B) as directed by regulatory authorities. Patient enrollment continued until at least 150 patients were enrolled, and adverse events attributable to drugs, treatment devices, and BNCT were evaluated. The patients with LA/LR-HNC were systematically evaluated to determine efficacy. Results: The 162 patients enrolled included 144 patients with squamous cell carcinoma of the head and neck (SCCHN), 17 patients with non-SCCHN (NSCCHN), and 1 patient with glioblastoma. Treatmentrelated adverse events (TRAEs) were hyperamylasemia (84.0%), stomatitis (51.2%), sialoadenitis (50.6%), and alopecia (49.4%) as acute TRAEs and dysphagia (4.5%), thirst (2.6%), and skin disorder (1.9%) as more common late TRAEs. One- and two-year OS rates in patients with recurrent SCCHN were 78.8% and 60.7%, respectively. Conclusions: This post-marketing surveillance confirmed the safety and efficacy of BNCT with borofalan(10B) in patients with LA/LR-HNC in a real-world setting.
Harvesting Thermal Energy through Pyroelectric and Thermoelectric Nanomaterials for Catalytic Applications
Authors: Li Shun , Liu Xinbo , Zhang Xinyue , Wang Youling , Chen Shanliang , Liu Yong , Zhang Yuqiao
Published: February 2024

The current scenario sees over 60% of primary energy being dissipated as waste heat directly into the environment, contributing significantly to energy loss and global warming. Therefore, low-grade waste heat harvesting has been long considered a critical issue. Pyroelectric (PE) materials utilize temperature oscillation to generate electricity, while thermoelectric (TE) materials convert temperature differences into electrical energy. Nanostructured PE and TE materials have recently gained prominence as promising catalysts for converting thermal energy directly into chemical energy in a green manner. This short review provides a summary and comparison of catalytic processes initiated by PE and TE effects driven by waste thermal energy. The discussion covers fundamental principles and reaction mechanisms, followed by the introduction of representative examples of PE and TE nanomaterials in various catalytic fields, including water splitting, organic synthesis, air purification, and biomedical applications. Finally, the review addresses challenges and outlines future prospects in this emerging field.
Untangling the Processes of Bitcoin: An Organizational Learning Perspective
Authors: Matthews Rupert L.
Published: February 2024

Bitcoin is a complex phenomenon, whether in terms of the macro factors affecting its price or its role in the global energy infrastructure. However, extant literature pays too little attention to exploring the internal mechanisms of the protocol to be able to link them to how they affect the visible characteristics of Bitcoin. This paper uses secondary data from highly reputable Bitcoin-focused sources to systematically map the processes that enable Bitcoin to function as a peer-to-peer cash system. Novelty is achieved by applying the established and versatile “4I” organisational learning framework to provide a new lens through which to understand how the processes within Bitcoin enable and facilitate different types of changes to the protocol. Further insights are provided to organisational learning from Bitcoin, in relation to managing mission-critical changes to organisational systems. In addition, it presents an option for dealing with irreconcilable internal differences to “hard-fork” part of the organisation. While the scope of this paper is limited to secondary data, opportunities for further research, including primary data collection, are outlined to explore how Bitcoin knowledge disseminates within communities or companies.
Molecular Characterization and Phylogenetic Analysis of Centipedegrass [Eremochloa ophiuroides (Munro) Hack.] Based on the Complete Chloroplast Genome Sequence
Authors: Wang Haoran , Zhang Yuan , Zhang Ling , Wang Jingjing , Guo Hailin , Zong Junqin , Chen Jingbo , Li Dandan , Li Ling , Liu Jianxiu , Li Jianjian
Published: February 2024

Centipedegrass (Eremochloa ophiuroides) is an important warm-season grass plant used as a turfgrass as well as pasture grass in tropical and subtropical regions, with wide application in land surface greening and soil conservation in South China and southern United States. In this study, the complete cp genome of E. ophiuroides was assembled using high-throughput Illumina sequencing technology. The circle pseudomolecule for E. ophiuroides cp genome is 139,107 bp in length, with a quadripartite structure consisting of a large single copyregion of 82,081 bp and a small single copy region of 12,566 bp separated by a pair of inverted repeat regions of 22,230 bp each. The overall A + T content of the whole genome is 61.60%, showing an asymmetric nucleotide composition. The genome encodes a total of 131 gene species, composed of 20 duplicated genes within the IR regions and 111 unique genes comprising 77 protein-coding genes, 30 transfer RNA genes, and 4 ribosome RNA genes. The complete cp genome sequence contains 51 long repeats and 197 simple sequence repeats, and a high degree of collinearity among E. ophiuroide and other Gramineae plants was disclosed. Phylogenetic analysis showed E. ophiuroides, together with the other two Eremochloa species, is closely related to Mnesithea helferi within the subtribe Rottboelliinae. These findings will be beneficial for the classification and identification of the Eremochloa taxa, phylogenetic resolution, novel gene discovery, and functional genomic studies for the genus Eremochloa.
Can the Brain’s Thermostatic Mechanism Generate Sleep-Wake and NREM-REM Sleep Cycles? A Nested Doll Model of Sleep-Regulating Processes
Authors: Putilov Arcady A.
Published: February 2024

Evidence is gradually accumulating in support of the hypothesis that a process of thermostatic brain cooling and warming underlies sleep cycles, i.e., the alternations between non-rapid-eye-movement and rapid-eye-movement sleep throughout the sleep phase of the sleep-wake cycle. A mathematical thermostat model predicts an exponential shape of fluctuations in temperature above and below the desired temperature setpoint. If the thermostatic process underlies sleep cycles, can this model explain the mechanisms governing the sleep cyclicities in humans? The proposed nested doll model incorporates Process s generating sleep cycles into Process S generating sleep-wake cycles of the two-process model of sleep-wake regulation. Process s produces ultradian fluctuations around the setpoint, while Process S turns this setpoint up and down in accord with the durations of the preceding wake phase and the following sleep phase of the sleep-wake cycle, respectively. Predictions of the model were obtained in an in silico study and confirmed by simulations of oscillations of spectral electroencephalographic indexes of sleep regulation obtained from night sleep and multiple napping attempts. Only simple—inverse exponential and exponential—functions from the thermostatic model were used for predictions and simulations of rather complex and varying shapes of sleep cycles during an all-night sleep episode. To further test the proposed model, experiments on mammal species with monophasic sleep are required. If supported, this model can provide a valuable framework for understanding the involvement of sleep-wake regulatory processes in the mechanism of thermostatic brain cooling/warming.
Microstructure Features and Mechanical Properties of Casted CoFeB Alloy Target
Authors: Zhu Ziyi , He Jinjiang , Li Yongjun , Luo Junfeng , Xu Guojin , Yang Wenkui , Liu Dan , Gao Jiali
Published: February 2024

CoFeB alloy, as a promising magneto-resistive material, has attracted extensive attention concerning the magnetic properties of its thin film in the field of magneto-resistive random memory (MRAM). Although there are many studies on the magnetic properties of CoFeB thin films, there is relatively little research on the microstructure and mechanical properties of casted CoFeB alloy. In this work, Co20Fe60B20 (at%) alloy was fabricated through the vacuum induction melting method, and its microstructure features and mechanical performance were studied. Scanning electron microscopy (SEM), electron back scatter diffraction (EBSD), and transmission electron microscopy (TEM) were utilized to characterize the microstructure, which consists of the coarse, needle-like Fe2B phase that crystallizes first, the primary lamellar binary eutectic structure (Fe2B + bcc-Fe), and the ternary eutectic structure (Fe3B + Fe2B + bcc-Fe phase). It is found that Fe3B precipitates on the Fe2B with a core–shell structure. The orientation of bcc-Fe is randomly distributed, while there are two main kinds of textures in Fe2B: {100} <001> and Gaussian texture {110} <001>. In terms of mechanical properties, Co20Fe60B20 alloy’s tensile strength is 140MPa, and the yield strength is 87MPa. Because the cracks are easy to generate and expand along the needle-shaped pre-crystallized Fe2B, the plasticity of Co20Fe60B20 alloy is very poor, only 1%.
Silicon Dioxide Thin Films Deposited Using Oxide Targets: Results of Atomistic Simulation
Authors: Grigoriev F. V. , Sulimov V. B. , Tikhonravov A. V.
Published: February 2024

An atomistic simulation of silicon dioxide thin films deposited using oxide targets is performed. The influence of the oxide target on the deposition process is taken into account by introducing O=Si=O molecules into the flow of particles moving from the target to the substrate. The fraction of these molecules varied from 0 to 50%. It was found that the presence of O=Si=O molecules leads to film densification during a normal deposition. With a low-energy deposition, the increase in density was twice as high as with a high-energy deposition. The absolute value of the compressive stress increased with an increasing fraction of O=Si=O molecules in the flow of deposited particles at a normal, high-energy deposition. The influence of O=Si=O molecules on the structure of the glancing angle deposited films depends on the deposition angle.
Extraction of Rare Earth Elements from Chloride Solutions Using Mixtures of P507 and Cyanex 272
Authors: Afonin Mikhail A. , Nechaev Andrey V. , Yakimenko Ilya A. , Belova Vera V.
Published: February 2024

In this study, the extraction of rare earth elements (REEs) from chloride solutions after leaching REE carbonate concentrate with solutions of the mixtures of P507 (2-ethylhexylphosphonic acid mono-2-ethylhexyl ester) and Cyanex 272 (bis(2,4,4-trimethylpentyl)phosphinic acid) (1:1) at various concentrations was experimentally studied. It was shown that the distribution ratios of all REEs decrease with the increasing concentration of these metals in the initial solution, which is associated with the loading of the organic phase. The most significant improvement in the extraction is observed for the heavy group of rare earth elements. The extractability of REEs increases with the increasing atomic number of the element, as is typical for the extraction of these metals with acidic organophosphorus extractants. The data obtained show that the separation factors of adjacent rare earth elements decrease slightly with the increasing concentration of metals in the initial aqueous solution. Increasing the concentration of the extractant mixture does not have a significant effect on the values of the adjacent REE separation factors. The data obtained on the distribution ratios and separation factors made it possible to propose a flow sheet for the separation of rare earth elements with the production of Y, Ho, Tb and Dy.
Milestones and New Challenges in Compounds
Authors: Mejuto Juan C.
Published: February 2024

Since 2021, we have been immersed in the challenge of publishing a journal that constitutes a form of communication of scientific achievements in the field of the synthesis and characterization of chemical compounds from a theoretical and experimental point of view [...]
Quantifying the Effects of Material Input Levels on Jointed Plain Concrete Pavement (JPCP) Performance and Slab Thickness
Authors: McIntosh Megan D. , Sabih Gauhar , Summers Clarke , Cavalline Tara L. , Tempest Brett Q.
Published: February 2024

The mechanistic-empirical pavement design guide (MEPDG) is a commonly accepted design principles guide that aids in jointed plain concrete pavement (JPCP) design and performance analysis. The MEPDG uses three different design parameter input levels, referred to as level one, level two, and level three, providing increasing confidence in the analysis at the lower numbered levels, which use more locally relevant (level two) or project-specific (level one) data. The state-of-the-art pavement ME software (version 2.6.2) uses MEPDG design principles to predict pavement performance. The three performance indicators for JPCP systems (international roughness index (IRI), joint faulting, and transverse cracking) experience significant changes when simulating under a different input level. The IRI and faulting indicator changed by 78 percent when using inputs varying from level one to level three, with the cracking indicator change being more severe at 87 percent. To accommodate the change in performance indicator values between input level one and input level three, increasing the concrete slab thickness is necessary to achieve comparable pavement performance. An increase in the Portland cement concrete (PCC) layer from one inch to two inches is required when input level three simulations are performed, demonstrating the economic and sustainability benefits of using project-specific level one inputs. Understanding the impact of simulation input levels will help to meet design and sustainability goals and improve the lifecycle performance of JPCP systems.
Equitable Vaccine Access in Light of COVID-19 Vaccine Procurement Strategies in Africa
Authors: O’Hara George L. , Halabi Sam , Egbokhare Olohikhuae
Published: February 2024

(1) Background: This study addresses two weaknesses in current international efforts to prevent and prepare for the next pandemic: the lack of robust evidence supporting global policy measures and the corresponding extent to which those measures advance equity. (2) Methods: Using UNICEF’s publicly available but underused COVID-19 Market Dashboard database, we conducted a cross-sectional analysis of vaccine deliveries as of mid-2022 and vaccine procurement strategies used by African low- and lower middle-income countries (LMICs) over the course of the COVID-19 pandemic. (3) Results: Pooled procurement of the kind typified by COVAX (a clearinghouse for high-income-country contributions of vaccines and financing toward the end of equitable LMIC procurement) crowded out alternative strategies that must be supported in future: regional procurement, donation, and bilateral procurement (binding agreement between two parties: one seller (i.e., a national government or a vaccine manufacturer) and one recipient (i.e., national government)), which showed a significant relationship with technology transfer and advancing local production capacity. (4) Conclusions: Expanding the scope of vaccine procurement alternatives to COVAX such as regional pooled procurement and bilateral procurement can stratify risk of supply agreements not materializing in actual supply. Sharing the technology necessary to produce vaccines with LMICs can mitigate obstacles to bilateral procurement. A pooled purchase alliance to procure vaccine doses on behalf of participating countries within a given region can benefit LMICs by accounting for infrastructure limitations that these countries share. Finally, donations bolster global redistributed supply essential to LMICs.
Modeling COVID-19 Disease with Deterministic and Data-Driven Models Using Daily Empirical Data in the United Kingdom
Authors: Agbaje Janet O. , Babasola Oluwatosin , Adeyemo Kabiru Michael , Zhiri Abraham Baba , Adigun Aanuoluwapo Joshua , Lawal Samuel Adefisoye , Nuga Oluwole Adegoke , Abah Roseline Toyin , Adam Umar Muhammad , Oshinubi Kayode
Published: February 2024

The COVID-19 pandemic has had a significant impact on countries worldwide, including the United Kingdom (UK). The UK has faced numerous challenges, but its response, including the rapid vaccination campaign, has been noteworthy. While progress has been made, the study of the pandemic is important to enable us to properly prepare for future epidemics. Collaboration, vigilance, and continued adherence to public health measures will be crucial in navigating the path to recovery and building resilience for the future. In this article, we propose an overview of the COVID-19 situation in the UK using both mathematical (a nonlinear differential equation model) and statistical (time series modeling on a moving window) models on the transmission dynamics of the COVID-19 virus from the beginning of the pandemic up until July 2022. This is achieved by integrating a hybrid model and daily empirical case and death data from the UK. We partition this dataset into before and after vaccination started in the UK to understand the influence of vaccination on disease dynamics. We used the mathematical model to present some mathematical analyses and the calculation of the basic reproduction number (R0). Following the sensitivity analysis index, we deduce that an increase in the rate of vaccination will decrease R0. Also, the model was fitted to the data from the UK to validate the mathematical model with real data, and we used the data to calculate time-varying R0. The homotopy perturbation method (HPM) was used for the numerical simulation to demonstrate the dynamics of the disease with varying parameters and the importance of vaccination. Furthermore, we used statistical modeling to validate our model by performing principal component analysis (PCA) to predict the evolution of the spread of the COVID-19 outbreak in the UK on some statistical predictor indicators from time series modeling on a 14-day moving window for detecting which of these indicators capture the dynamics of the disease spread across the epidemic curve. The results of the PCA, the index of dispersion, the fitted mathematical model, and the mathematical model simulation are all in agreement with the dynamics of the disease in the UK before and after vaccination started. Conclusively, our approach has been able to capture the dynamics of the pandemic at different phases of the disease outbreak, and the result presented will be useful to understand the evolution of the disease in the UK and future and emerging epidemics.
Selective Synthesis of α-Nickel Hydroxide through a Polyol Process
Authors: Kawabata Koki , Okamoto Shusuke , Hondoh Hironori , Nagai Daisuke
Published: February 2024

The polyol process is a straightforward method to produce metallic compounds through transformation from metal salt. An optimized procedure based on the polyol process in this research was developed for the selective synthesis of α-nickel hydroxide from metal salt. From various experimental results, the preparation of the sodium salt of ethylene glycol was crucial for the efficient production of α-nickel hydroxide. The structure of α-nickel hydroxide was studied by powder X-ray diffraction, IR spectroscopy, thermogravimetric analysis, transmission electron microscopy, and scanning electron microscope. The estimated Gibbs free energies for each step of the polyol process, employing density functional theory (DFT) calculations, confirmed the formation of nickel reaction intermediates, which mitigated the production of metallic nickel. The innovative point of this research is the finding that the intentional generation of nickel reaction intermediates leads to selective synthesis of α-nickel hydroxide.
Heat-Affected Zone Microstructural Study via Coupled Numerical/Physical Simulation in Welded Superduplex Stainless Steels
Authors: da Silva Leonardo Oliveira Passos , Lima Tiago Nunes , Júnior Francisco Magalhães dos Santos , Callegari Bruna , Folle Luís Fernando , Coelho Rodrigo Santiago
Published: February 2024

Superduplex stainless steels (SDSS) are known for their combination of good mechanical properties and excellent corrosion resistance, enabled by the microstructural balance between austenite and ferrite and an amount of alloying elements. Their application in welded components is, however, limited by the possibility of the precipitation of intermetallic phases and microstructural misbalance, which might hinder their properties, especially in the heat-affected zone (HAZ). This work introduces a methodology that relies simultaneously on physical and numerical simulations to study the HAZ in a UNS S32750 SDSS. Dimensions of the fusion zone and thermal cycles were calibrated for a numerical model using preliminary welding trials. Numerically simulated cycles for each heat input (HI) were physically reproduced in a Gleeble® simulator, and the heat-treated samples were characterized and compared with real specimens welded using the same parameters. Thermal curves resulting from the numerical simulations were successfully replicated by the Gleeble®, indicating adequate application of the desired HI. The hardness and microstructural results from simulated and welded specimens were also found to be quite similar. Therefore, the proposed methodology showed itself adequate not only for the study of duplex stainless steels, but also of materials with similar thermal and mechanical properties, including the extrapolation of welding parameters.
Randomized Double-Blind Placebo-Controlled Study of Salivary Substitute with Enzymatic System for Xerostomia in Patients Irradiated in Head and Neck Region
Authors: Porangaba Letícia Pacheco , de Melo Garcia Flávio , Rabelo Ana Paula Alvarenga Antonio , Andrade Amanda Puche , de Abreu Alves Fabio , Pellizzon Antonio Cássio Assis , Jaguar Graziella Chagas
Published: February 2024

This study aims to compare whether the use of a salivary substitute including an enzymatic system clinically reduces the intensity of xerostomia, as well as exploring the impact that this has on the quality of life, in patients who had received radiotherapy in the head and neck (HNC) region. Forty patients who had completed radiotherapy treatment within 6 months to 1 year previously were allocated into an Enzymatic Spray group (n = 21) or a Placebo arm (n = 19). It should be noted that two patients in the Placebo arm declined to participate during phase 2 of the study. All patients were randomized and used both products three times a day for 30 days. For analysis, xerostomia grade, unstimulated (UWS) and stimulated (SWS) salivary flow rate, and quality of life through the University of Washington Quality of Life Questionnaire validated in Portuguese (UW-QoL) were assessed in two phases: Phase 1 (before the use of the products) and Phase 2 (after 30 days of using the products). All clinical data were collected from medical records. Analyzing the salivary substitute with the enzymatic system, an improvement in xerostomia complaints was observed 30 days after using the product; however, this difference was not statistically significant (p > 0.05). Regarding quality of life, no significant differences were observed in relation to the UW-QoL and saliva domain between the groups in the two phases of the study (p > 0.05). The salivary substitute with the enzymatic system may be effective in reducing radio-induced xerostomia symptoms; however, further research is necessary to evaluate the efficacy of this salivary substitute on oral health.