bluuebunny/crossref_metadata_2025_split huggingface dataset:
High voltage electrolytes for lithium-ion batteries with micro-sized silicon anodes
Authors: Li Ai-Min , Wang Zeyi , Pollard Travis P. , Zhang Weiran , Tan Sha , Li Tianyu , Jayawardana Chamithri , Liou Sz-Chian , Rao Jiancun , Lucht Brett L. , Hu Enyuan , Yang Xiao-Qing , Borodin Oleg , Wang Chunsheng 
Published: February 2024

AbstractMicro-sized silicon anodes can significantly increase the energy density of lithium-ion batteries with low cost. However, the large silicon volume changes during cycling cause cracks for both organic-inorganic interphases and silicon particles. The liquid electrolytes further penetrate the cracked silicon particles and reform the interphases, resulting in huge electrode swelling and quick capacity decay. Here we resolve these challenges by designing a high-voltage electrolyte that forms silicon-phobic interphases with weak bonding to lithium-silicon alloys. The designed electrolyte enables micro-sized silicon anodes (5 µm, 4.1 mAh cm−2) to achieve a Coulombic efficiency of 99.8% and capacity of 2175 mAh g−1 for >250 cycles and enable 100 mAh LiNi0.8Co0.15Al0.05O2 pouch full cells to deliver a high capacity of 172 mAh g−1 for 120 cycles with Coulombic efficiency of >99.9%. The high-voltage electrolytes that are capable of forming silicon-phobic interphases pave new ways for the commercialization of lithium-ion batteries using micro-sized silicon anodes.
High-performance cryo-temperature ionic thermoelectric liquid cell developed through a eutectic solvent strategy
Authors: Wang Shuaihua , Li Yuchen , Yu Mao , Li Qikai , Li Huan , Wang Yupeng , Zhang Jiajia , Zhu Kang , Liu Weishu 
Published: February 2024

AbstractIonic thermoelectric (i-TE) liquid cells offer an environmentally friendly, cost effective, and easy-operation route to low-grade heat recovery. However, the lowest temperature is limited by the freezing temperature of the aqueous electrolyte. Applying a eutectic solvent strategy, we fabricate a high-performance cryo-temperature i-TE liquid cell. Formamide is used as a chaotic organic solvent that destroys the hydrogen bond network between water molecules, forming a deep eutectic solvent that enables the cell to operate near cryo temperatures (down to –35 °C). After synergistic optimization of the electrode and cell structure, the as-fabricated liquid i-TE cell with cold (–35 °C) and hot (70 °C) ends achieve a high power density (17.5 W m−2) and a large two-hour energy density (27 kJ m−2). In a prototype 25-cell module, the open-circuit voltage and short-circuit current are 6.9 V and 68 mA, respectively, and the maximum power is 131 mW. The anti-freezing ability and high output performance of the as-fabricated i-TE liquid cell system are requisites for applications in frigid regions.
Neural network enabled nanoplasmonic hydrogen sensors with 100 ppm limit of detection in humid air
Authors: Tomeček David , Moberg Henrik Klein , Nilsson Sara , Theodoridis Athanasios , Darmadi Iwan , Midtvedt Daniel , Volpe Giovanni , Andersson Olof , Langhammer Christoph 
Published: February 2024

AbstractEnvironmental humidity variations are ubiquitous and high humidity characterizes fuel cell and electrolyzer operation conditions. Since hydrogen-air mixtures are highly flammable, humidity tolerant H2 sensors are important from safety and process monitoring perspectives. Here, we report an optical nanoplasmonic hydrogen sensor operated at elevated temperature that combined with Deep Dense Neural Network or Transformer data treatment involving the entire spectral response of the sensor enables a 100 ppm H2 limit of detection in synthetic air at 80% relative humidity. This significantly exceeds the <1000 ppm US Department of Energy performance target. Furthermore, the sensors pass the ISO 26142:2010 stability requirement in 80% relative humidity in air down to 0.06% H2 and show no signs of performance loss after 140 h continuous operation. Our results thus demonstrate the potential of plasmonic hydrogen sensors for use in high humidity and how neural-network-based data treatment can significantly boost their performance.
Large-scale proteomics analysis of five brain regions from Parkinson’s disease patients with a GBA1 mutation
Authors: Blumenreich Shani , Nehushtan Tamar , Kupervaser Meital , Shalit Tali , Gabashvili Alexandra , Joseph Tammar , Milenkovic Ivan , Hardy John , Futerman Anthony H. 
Published: February 2024

AbstractDespite being the second most common neurodegenerative disorder, little is known about Parkinson’s disease (PD) pathogenesis. A number of genetic factors predispose towards PD, among them mutations inGBA1, which encodes the lysosomal enzyme acid-β-glucosidase. We now perform non-targeted, mass spectrometry based quantitative proteomics on five brain regions from PD patients with aGBA1mutation (PD-GBA) and compare to age- and sex-matched idiopathic PD patients (IPD) and controls. Two proteins were differentially-expressed in all five brain regions whereas significant differences were detected between the brain regions, with changes consistent with loss of dopaminergic signaling in the substantia nigra, and activation of a number of pathways in the cingulate gyrus, including ceramide synthesis. Mitochondrial oxidative phosphorylation was inactivated in PD samples in most brain regions and to a larger extent in PD-GBA. This study provides a comprehensive large-scale proteomics dataset for the study of PD-GBA.
Dynamic computational phenotyping of human cognition
Authors: Schurr Roey , Reznik Daniel , Hillman Hanna , Bhui Rahul , Gershman Samuel J. 
Published: February 2024

AbstractComputational phenotyping has emerged as a powerful tool for characterizing individual variability across a variety of cognitive domains. An individual’s computational phenotype is defined as a set of mechanistically interpretable parameters obtained from fitting computational models to behavioural data. However, the interpretation of these parameters hinges critically on their psychometric properties, which are rarely studied. To identify the sources governing the temporal variability of the computational phenotype, we carried out a 12-week longitudinal study using a battery of seven tasks that measure aspects of human learning, memory, perception and decision making. To examine the influence of state effects, each week, participants provided reports tracking their mood, habits and daily activities. We developed a dynamic computational phenotyping framework, which allowed us to tease apart the time-varying effects of practice and internal states such as affective valence and arousal. Our results show that many phenotype dimensions covary with practice and affective factors, indicating that what appears to be unreliability may reflect previously unmeasured structure. These results support a fundamentally dynamic understanding of cognitive variability within an individual.
Structural mechanisms of autoinhibition and substrate recognition by the ubiquitin ligase HACE1
Authors: Düring Jonas , Wolter Madita , Toplak Julia J. , Torres Camilo , Dybkov Olexandr , Fokkens Thornton J. , Bohnsack Katherine E. , Urlaub Henning , Steinchen Wieland , Dienemann Christian , Lorenz Sonja 
Published: February 2024

AbstractUbiquitin ligases (E3s) are pivotal specificity determinants in the ubiquitin system by selecting substrates and decorating them with distinct ubiquitin signals. However, structure determination of the underlying, specific E3-substrate complexes has proven challenging owing to their transient nature. In particular, it is incompletely understood how members of the catalytic cysteine-driven class of HECT-type ligases (HECTs) position substrate proteins for modification. Here, we report a cryogenic electron microscopy (cryo-EM) structure of the full-length human HECT HACE1, along with solution-based conformational analyses by small-angle X-ray scattering and hydrogen–deuterium exchange mass spectrometry. Structure-based functional analyses in vitro and in cells reveal that the activity of HACE1 is stringently regulated by dimerization-induced autoinhibition. The inhibition occurs at the first step of the catalytic cycle and is thus substrate-independent. We use mechanism-based chemical crosslinking to reconstitute a complex of activated, monomeric HACE1 with its major substrate, RAC1, determine its structure by cryo-EM and validate the binding mode by solution-based analyses. Our findings explain how HACE1 achieves selectivity in ubiquitinating the active, GTP-loaded state of RAC1 and establish a framework for interpreting mutational alterations of the HACE1–RAC1 interplay in disease. More broadly, this work illuminates central unexplored aspects in the architecture, conformational dynamics, regulation and specificity of full-length HECTs.
Functional connectivity interacts with visual perceptual learning for visual field recovery in chronic stroke
Authors: Namgung Eun , Kim Yong-Hwan , Lee Eun-Jae , Sasaki Yuka , Watanabe Takeo , Kang Dong-Wha 
Published: February 2024

AbstractA reciprocal relationship between perceptual learning and functional brain changes towards perceptual learning effectiveness has been demonstrated previously; however, the underlying neural correlates remain unclear. Further, visual perceptual learning (VPL) is implicated in visual field defect (VFD) recovery following chronic stroke. We investigated resting-state functional connectivity (RSFC) in the visual cortices associated with mean total deviation (MTD) scores for VPL-induced VFD recovery in chronic stroke. Patients with VFD due to chronic ischemic stroke in the visual cortex received 24 VPL training sessions over 2 months, which is a dual discrimination task of orientation and letters. At baseline and two months later, the RSFC in the ipsilesional, interhemispheric, and contralesional visual cortices and MTD scores in the affected hemi-field were assessed. Interhemispheric visual RSFC at baseline showed the strongest correlation with MTD scores post-2-month VPL training. Notably, only the subgroup with high baseline interhemispheric visual RSFC showed significant VFD improvement following the VPL training. The interactions between the interhemispheric visual RSFC at baseline and VPL led to improvement in MTD scores and largely influenced the degree of VFD recovery. The interhemispheric visual RSFC at baseline could be a promising brain biomarker for the effectiveness of VPL-induced VFD recovery.
A deep learning framework for non-functional requirement classification
Authors: Rahman Kiramat , Ghani Anwar , Misra Sanjay , Rahman Arif Ur 
Published: February 2024

AbstractAnalyzing, identifying, and classifying nonfunctional requirements from requirement documents is time-consuming and challenging. Machine learning-based approaches have been proposed to minimize analysts’ efforts, labor, and stress. However, the traditional approach of supervised machine learning necessitates manual feature extraction, which is time-consuming. This study presents a novel deep-learning framework for NFR classification to overcome these limitations. The framework leverages a more profound architecture that naturally captures feature structures, possesses enhanced representational power, and efficiently captures a broader context than shallower structures. To evaluate the effectiveness of the proposed method, an experiment was conducted on two widely-used datasets, encompassing 914 NFR instances. Performance analysis was performed on the applied models, and the results were evaluated using various metrics. Notably, the DReqANN model outperforms the other models in classifying NFR, achieving precision between 81 and 99.8%, recall between 74 and 89%, and F1-score between 83 and 89%. These significant results highlight the exceptional efficacy of the proposed deep learning framework in addressing NFR classification tasks, showcasing its potential for advancing the field of NFR analysis and classification.
The germination response of Zea mays L. to osmotic potentials across optimal temperatures via halo-thermal time model
Authors: Amin Fazal , Shah Fakhra , Ullah Sami , Shah Wadood , Ahmed Iftikhar , Ali Baber , Khan Amir Abdullah , Malik Tabarak , Mustafa Abd El-Zaher M. A. 
Published: February 2024

AbstractThe maize (Zea mays L.) is a monocot that is a member of the Poaceae family and a valuable feed for livestock, human food, and raw material for various industries. The halothermal time model determines how plants respond to salt (NaCl) stress under sub-optimal conditions. This model examines the relation between NaClb (g), GR, GP, salinity and temperature stress on germination of seeds dynamics in various crops. Five constant temperatures i.e. 20, 25, 30, 35, and 40 °C and five ψ levels (NaCl concentrations converted to ψ − 0, − 0.2, − 0.4, − 0.6, and − 0.8 MPa) were used in this experiment. In light of the results, the maximum halo-thermal time constant value was recorded at 35 °C temperature, while maximum germination percentage was detected at 30 °C in the controlled condition. Moreover, the lowermost value was recorded at 20 °C at − 0.8 MPa osmotic potential. The highest CAT, APX, and GPX activities were recorded at 15 °C at − 0.8 MPa, while the lowest values were observed for 0 MPa at 30 °C temperature. In conclusion, by employing the halo thermal time model, the germination of maize variety (var.30W52) was accurately predicted for the first time under varying levels of temperature and osmotic potentials.
A novel strategy towards efficient and reliable electric vehicle charging for the realisation of a true sustainable transportation landscape
Authors: Kumar B. Anil , Jyothi B. , Singh Arvind R. , Bajaj Mohit , Rathore Rajkumar Singh , Berhanu Milkias 
Published: February 2024

AbstractThis paper proposes an innovative approach for improving the charging efficiency of electric vehicles (EVs) by combining photovoltaic (PV) systems with AC–DC Power Factor Correction (PFC). The proposed approach employs bi-directional power flow management within the PFC system, allowing for enhanced resource utilization and EV battery capacity under a variety of environmental circumstances. A modified Lyapunov-based robust model reference adaptive controller (M-LRMRAC) is developed to provide real-time Maximum Power Point Tracking (MPPT) for the PV array. By quickly recording the MPP, this controller skilfully adjusts to shifting radiation and temperature dynamics. A noteworthy accomplishment is that the M-LRMRAC outperforms traditional Perturb and Observe (P&O) techniques by achieving quick MPP convergence (0.54 s). Additionally, the benefits of this integrated system go beyond effective MPPT. The method achieves operating at unity power factor and reduces total harmonic distortion, which results in improved power quality when charging EV Batteries (EVB). The entire solution provided by this multifaceted architecture improves the quality of electricity delivered to EV batteries while also increasing energy efficiency. This research helps to the evolution of sustainable and dependable EV charging infrastructure by solving difficulties and optimising performance. The combination of PV systems with AC–DC PFC, aided by the M-LRMRAC technology, presents a viable route for attaining efficient, clean, and high-quality EV charging, hence supporting the shift to a greener and more sustainable transportation landscape.
Correlation between skeletal muscle acetylcarnitine and phosphocreatine metabolism during submaximal exercise and recovery: interleaved 1H/31P MRS 7 T study
Authors: Klepochová Radka , Niess Fabian , Meyerspeer Martin , Slukova Dorota , Just Ivica , Trattnig Siegfried , Ukropec Jozef , Ukropcová Barbara , Kautzky-Willer Alexandra , Leutner Michael , Krššák Martin 
Published: February 2024

AbstractAcetylcarnitine is an essential metabolite for maintaining metabolic flexibility and glucose homeostasis. The in vivo behavior of muscle acetylcarnitine content during exercise has not been shown with magnetic resonance spectroscopy. Therefore, this study aimed to explore the behavior of skeletal muscle acetylcarnitine during rest, plantar flexion exercise, and recovery in the human gastrocnemius muscle under aerobic conditions. Ten lean volunteers and nine overweight volunteers participated in the study. A 7 T whole-body MR system with a double-tuned surface coil was used to acquire spectra from the gastrocnemius medialis. An MR-compatible ergometer was used for the plantar flexion exercise. Semi-LASER-localized 1H MR spectra and slab-localized 31P MR spectra were acquired simultaneously in one interleaved exercise/recovery session. The time-resolved interleaved 1H/31P MRS acquisition yielded excellent data quality. A between-group difference in acetylcarnitine metabolism over time was detected. Significantly slower τPCr recovery, τPCr on-kinetics, and lower Qmax in the overweight group, compared to the lean group was found. Linear relations between τPCr on-kinetics, τPCr recovery, VO2max and acetylcarnitine content were identified. In conclusion, we are the first to show in vivo changes of skeletal muscle acetylcarnitine during acute exercise and immediate exercise recovery with a submaximal aerobic workload using interleaved 1H/31P MRS at 7 T.
Identification of potential inhibitor against Leishmania donovani mitochondrial DNA primase through in-silico and in vitro drug repurposing approaches
Authors: Nath Mitul , Bhowmik Deep , Saha Satabdi , Nandi Rajat , Kumar Diwakar 
Published: February 2024

AbstractLeishmania donovaniis the causal organism of leishmaniasis with critical health implications affecting about 12 million people around the globe. Due to less efficacy, adverse side effects, and resistance, the available therapeutic molecules fail to control leishmaniasis. The mitochondrial primase ofLeishmania donovani(LdmtPRI1) is a vital cog in the DNA replication mechanism, as the enzyme initiates the replication of the mitochondrial genome ofLeishmania donovani. Hence, we target this protein as a probable drug target against leishmaniasis. The de-novo approach enabled computational prediction of the three-dimensional structure ofLdmtPRI1, and its active sites were identified. Ligands from commercially available drug compounds were selected and docked againstLdmtPRI1. The compounds were chosen for pharmacokinetic study and molecular dynamics simulation based on their binding energies and protein interactions. TheLdmtPRI1gene was cloned, overexpressed, and purified, and a primase activity assay was performed. The selected compounds were verified experimentally by the parasite and primase inhibition assay. Capecitabine was observed to be effective against the promastigote form ofLeishmania donovani, as well as inhibiting primase activity. This study's findings suggest capecitabine might be a potential anti-leishmanial drug candidate after adequate further studies.
Pre-electoral coalition agreement from the Black–Scholes point of view
Authors: Mitrović D. 
Published: February 2024

AbstractA political party can be considered as a company whose value depends on the voters support i.e. on the percentage of population supporting the party. Dynamics of the support is thus as a stochastic process with a deterministic growth rate perturbed by a white noise modeled through the Wiener process. This is in an analogy with the option modeling where the stock price behaves similarly as the voters’ support. While in the option theory we have the question of fair price of an option, the question that we ask here is what is a reasonable level of support that the coalition of a “major” party (safely above the election threshold) and a “minor” party (under or around the election threshold) should achieve in order for the “minor” party to get one more representative. We shall elaborate some of the conclusions in the case of recent elections in Montenegro (June, 2023) which are particularly interesting due to lots of political subjects entering the race.
Identification of self- and pathogen-targeted miRNAs from resistant and susceptible Theobroma cacao variety to black pod disease
Authors: Septiani Popi , Pramesti Yonadita , Ningsih Devi Ulfa , Pancaningtyas Sulistyani , Meitha Karlia 
Published: February 2024

AbstractCacao (Theobroma cacao) is a highly valuable crop with growing demand in the global market. However, cacao farmers often face challenges posed by black pod disease caused byPhytophthoraspp., withP. palmivorabeing the most dominant.Regulations of various gene expressions influence plant resistance to pathogens. One mechanism involves targeting the mRNA of virulence genes in the invading pathogens, suppressing their infection. However, resistance also could be suppressed by plant-derived miRNAs that target their own defence genes. The objective of this study is to identify differentially expressed miRNAs in black pod-resistant and susceptible cacao varieties and to predict their targets inT. cacaoandP. palmivoratranscripts. Extracted miRNA from resistant and susceptible varieties ofT. Cacaowas sequenced, identified, and matched to host and pathogen mRNA. In total, 54 known miRNAs from 40 miRNA families and 67 novel miRNAs were identified. Seventeen miRNAs were differentially expressed in susceptible variety compared to resistant one, with 9 miRNAs upregulated and 8 miRNAs downregulated. InT. cacaotranscripts, the upregulated miRNAs were predicted to target several genes, including defence genes. The suppression of these defense genes can lead to a reduction in plant resistance against pathogen infection. InP. palmivoratranscripts, the upregulated miRNAs were predicted to target several genes, includingP. palmivoraeffector genes. In the future, limiting expression of miRNAs that targetT. cacao’s defence genes and applying miRNAs that targetP. palmivoraeffector genes hold promise for enhancing cacao plant resistance againstP. palmivorainfection.
Effects of low temperatures on quiescence in Trichogramma evanescens Westwood and T. chilonis Ishii reared on Plodia interpunctella (Hübner): implications for mass rearing
Authors: Hasan Md. Mahbub , Parvin M. Nishat , Athanassiou Christos G. 
Published: February 2024

AbstractThe egg parasitoids of the genus Trichogramma are important potential biological control agents for a wide range of lepidopteran pests. Cold storage of host eggs has been proposed as a valuable technique for ensuring the release of sufficient parasitoid numbers whenever it is needed. In this context, the impact of low temperatures to induce quiescence in T. evanescens Westwood and T. chilonis Ishii was studied using eggs of Indian meal moth Plodia interpunctella (Hübner). Prepupae of the parasitoids were stored for 15, 30, 45, 60 and 75 d at 4 °C, following a 7 d period of acclimation at 10 °C. Both parasitoid species seem to survive unfavorable temperature conditions by entering a state of quiescence. Parasitism, adult emergence, sex ratio and progeny quality were not affected by cold storage in either parasitoid species for up to 30 d of storage. Parasitized host eggs of P. interpunctella can be stored for up to 60 d at 4 °C for both parasitoids, but there was no emergence at 75 d. General productivity values gradually decreased as the duration of storage lengthened for both species. Our results clearly reveal that the eggs parasitized by these species can be stored for up to 30 d at 4 °C in a state of quiescence without much loss of their performance compared to the control eggs.