bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synthesis of NiO-SnO2 cauliflower-like gas sensor material using a facile hydrothermal method for acetone detection
Authors: Saber S , Rozali S , Haseeb A S M A 
Published: September 2024

Abstract
The present study has successfully synthesized a cauliflower-like hierarchy microstructure of NiO-SnO2 through a facile and cost-effective hydrothermal method for acetone detection. S2 sensor, containing 0.25 mole% Ni, exhibited great performance in acetone gas sensing, with a response of 1734 at 1000 ppm at 350 °C, two times more than pristine SnO2. At lower concentrations, the responses were recorded to be 325, 170, 70, and 35 for 200 ppm, 100 ppm, 50 ppm, and 20 ppm of acetone balanced in nitrogen, respectively. Moreover, at the optimal operating temperature, 350 °C, swift response and recovery times of 8 s and 2 min 18 s were recorded when exposed to 20 ppm of acetone balanced in nitrogen, respectively. Also, the sensor was further assessed for its ability to distinguish acetone from other gases by exposing it to equal concentrations of 200 ppm of acetone, carbon dioxide, ammonia, and ethanol, all balanced in nitrogen, and tested at 350 °C. The sensor showed 142.74-, 143.39-, and 2.42-times higher responses in acetone than carbon dioxide, ammonia, and ethanol, respectively, indicating outstanding selectivity for detecting acetone. Lastly, the sensor showed remarkable operational stability when tested over repeated exposure cycles of acetone gas.
Model-free distortion canceling and control of quantum devices
Authors: Fouad Ahmed F , Youssry Akram , El-Rafei Ahmed , Hammad Sherif 
Published: September 2024

Abstract
Quantum devices need precise control to achieve their full capability. In this work, we address the problem of controlling closed quantum systems, tackling two main issues. First, in practice the control signals are usually subject to unknown classical distortions that could arise from the device fabrication, material properties and/or instruments generating those signals. Second, in most cases modeling the system is very difficult or not even viable due to uncertainties in the relations between some variables and inaccessibility to some measurements inside the system. In this paper, we introduce a general model-free control approach based on deep reinforcement learning (DRL), that can work for any controllable closed quantum system. We train a deep neural network (NN), using the REINFORCE policy gradient algorithm to control the state probability distribution of a controllable closed quantum system as it evolves, and drive it to different target distributions. We present a novel controller architecture that comprises multiple NNs. This enables accommodating as many different target state distributions as desired, without increasing the complexity of the NN or its training process. The used DRL algorithm works whether the control problem can be modeled as a Markov decision process (MDP) or a partially observed MDP. Our method is valid whether the control signals are discrete- or continuous-valued. We verified our method through numerical simulations based on a photonic waveguide array chip. We trained a controller to generate sequences of different target output distributions of the chip with fidelity higher than 99%, where the controller showed superior performance in canceling the classical signal distortions.
A 1940-2020 spatiotemporal analysis of thermal discomfort days in Southeast Asian countries
Authors: Wong Meei Chyi , Wang Jingyu , Zhi Xiefei , Dong Luojie 
Published: September 2024

Abstract
The high temperature and humidity make Southeast Asia (SEA) one of the regions most susceptible to the occurrence of thermal discomfort days (TDDs) in the world. In the context of global warming, SEA’s rapid population growth and urban expansion further exacerbated the region’s exposure to TDD, posing greater risks in public health. However, there exists a significant knowledge gap in the understanding of the long-term spatiotemporal evolution of TDD, as well as its projection in the future. By utilizing the newly released ERA5 datasets of Universal Thermal Climate Index (UTCI) and Mean Radiant Temperature (MRT), this study presented the 81-year analysis of TDDs in SEA countries, spanning from 1940 to 2020, with projections extending to 2100. While the mean increase in UTCI was relatively modest, the corresponding rise in TDD likelihood was disproportionately larger, indicating a heightened risk of exposure. A distinct contrast was observed between continental and maritime regions, with maritime countries showing smaller absolute rises in both indices but larger trends in TDD frequency due to oceanic moderating effects. Seasonal analyses highlighted the dominant influence of the East Asia monsoon over SEA, and spatial analyses revealed a negative correlation between TDD occurrence and elevation, with low-lying areas being hotspots. Projections for 2050 suggest continued warming. These findings underscore the urgency of proactive measures to address climate change impacts, particularly in vulnerable maritime and low-lying areas, providing valuable insights for enhancing climate resilience and adaptation in SEA. Our findings reveal critical insights into the trends and future scenarios of thermal discomfort in the region, underscoring the urgent need for effective climate adaptation strategies.
On the use of kolmogorov–arnold networks for adapting wind numerical weather forecasts with explainability and interpretability: application to madeira international airport
Authors: Alves Décio , Mendonça Fábio , Mostafa Sheikh Shanawaz , Morgado-Dias Fernando 
Published: September 2024

Abstract
This study examines the application of machine learning to enhance wind nowcasting by using a Kolmogorov-Arnold Network model to improve predictions from the Global Forecast System at Madeira International Airport, a site affected by complex terrain. The research addresses the limitations of traditional numerical weather prediction models, which often fail to accurately forecast localized wind patterns. Using the Kolmogorov-Arnold Network model led to a substantial reduction in wind speed and direction forecast errors, with a performance that reached a 48.5% improvement to the Global Forecast System 3 h nowcast, considering the mean squared error. A key outcome of this study comes from the model’s ability to generate mathematical formulas that provide insights into the physical and mathematical dynamics influencing local wind patterns and improve the transparency, explainability, and interpretability of the employed machine learning models for atmosphere modeling.
Transforming martensite in NiTi within nanoseconds
Authors: Lünser Klara , Neumann Bruno , Schmidt Daniel , Ge Yuru , Hensel Daniel , Khosla Mallika , Gaal Peter , Fähler Sebastian 
Published: September 2024

Abstract
Martensitic transformations enable various emerging applications like the shape memory effect and elastocaloric applications in NiTi. Increasing the speed of this transformation can shorten the response time for actuation and increase the power density of caloric cooling systems. Up to now, research on the speed and possible time limits of the martensitic transformation in NiTi has been limited to milli- and microsecond experiments. The dynamics of the transformation for shorter time scales are therefore unknown. Here, we report the fastest transformations in NiTi so far by heating an epitaxial NiTi film with a ns laser pulse and tracking the martensitic transition with in-situ synchrotron x-ray diffraction. We find that the martensite to austenite transition upon heating can proceed within the 7 ns pulse duration of the laser, but it requires substantial overheating as the rate of the transformation increases with the driving energy. The austenite to martensite transition is slower because cooling proceeds by conductive heat transfer, but with appropriate undercooling, the complete transformation from martensite to austenite and back only takes 200 ns. We compare our results to previous experiments on the Heusler alloy Ni–Mn–Ga and (K, Na)NbO3 and find very similar trends, which reveal that fast martensitic transformations in general follow a universal scaling law.
Finding high-performance MOFs for effective SF6/N2 separation through high-throughput computational screening and machine learning
Authors: Sezgin Pelin , Gulbalkan Hasan Can , Keskin Seda 
Published: September 2024

Abstract
Given the rapidly expanding pool of synthesized and hypothetical metal–organic frameworks (MOFs), testing every single material for SF6/N2 separation by iterative experimental methods or computationally demanding molecular simulations is not practical. In this study, we integrated high-throughput computational screening and machine learning (ML) approaches to evaluate SF6/N2 mixture adsorption and separation performances of over 25 000 different types of synthesized and hypothetical MOFs (hypoMOFs), representing the largest set of structures studied for SF6/N2 separation to date. SF6/N2 mixture adsorption data that we produced for synthesized MOFs using molecular simulations were utilized to develop ML models to accurately and quickly predict SF6 and N2 uptakes, SF6/N2 selectivities, SF6 working capacities, adsorbent performance scores, and regenerabilities of both synthesized and hypoMOFs. Results showed the MOF space that we studied exhibits very high SF6/N2 selectivities in the range of 1.8–4204 at 1 bar in addition to high SF6 working capacities between 0.04–5.68 mol kg−1 at an adsorption pressure of 1 bar and desorption pressure of 0.1 bar at room temperature. The top-performing MOF adsorbents for SF6/N2 mixture separation were identified to have Zn, Cu, Ni metals; terphenyl, pyridine, naphthalene linkers; and medium pore sizes. Our comprehensive computational approach offers a highly efficient alternative to brute-force computer simulations by enabling the rapid assessment of the MOF adsorbents for SF6/N2 separation and provides molecular insights into the key structural features of the most promising adsorbents.
Taking dual function materials (DFM) from the laboratory to industrial applications: a review of DFM operation under realistic integrated CO2 capture and utilization conditions
Authors: Gharamaleki Soudabeh Bahrami , Reina Tomas Ramirez , Duyar Melis S 
Published: September 2024

Abstract
Integrated CO2 Capture and Utilization (ICCU) is gathering momentum as a promising strategy to curb harmful CO2 emissions. This approach enables the use of dilute emissions as a source of carbon for chemical synthesis through processes like methanation, reverse water gas shift, or dry reforming of methane. One ICCU approach is performed using dual function materials (DFMs), which contain adsorbent and catalytic components. While utilizing DFMs for CO2 capture and conversion can potentially enhance reaction yields and lower costs by intensifying CO2 utilization processes, the practical use of these materials under relevant industrial settings is limited. Bringing this technology to real applications demands a deep scientific exploration, particularly regarding their behavior in the presence of impurities and high levels of oxygen. Herein we critically analyze the performance of different adsorbents and catalysts under realistic conditions for CO2 capture and conversion into methane or syngas. Additionally, we discuss the stability of DFMs when exposed to various contaminants that typically poison heterogeneous catalysts and identify several research gaps in this area.
Harms associated with retinal implantation of a stimulating electrode array to treat outer-retinal degeneration: a systematic review and meta-analysis of safety
Authors: Hallum Luke E , Cloherty Shaun L 
Published: September 2024

Abstract
Retinal implantation of an electrode array is an emerging treatment for vision loss caused by outer-retinal degeneration. This article collects and analyses harms associated with the treatment reported in the peer-reviewed literature, thus enabling informed decision-making by patients, clinicians, researchers, engineers, and policymakers. We searched MEDLINE, Embase, and clinical trials registries for peer-reviewed journal articles reporting harms outcomes. We extracted data from articles including study design, definitions of ‘serious adverse event’, and timing of adverse events. We applied the McMaster tool to these articles to assess the risk of bias in harms assessment and reporting. Our searches returned 585 abstracts. We reviewed the full text of 59 articles describing 11 different devices. McMaster scores ranged from 3 to 12 (maximum 15; higher scores indicate less risk). We compiled a comprehensive list of all serious and non-serious adverse events associated with retinal implantation. Several harms were common across devices. Our meta-analysis showed that serious adverse events are log-uniformly distributed throughout follow-up. Improved reporting and further clinical studies are needed to develop a reliable safety profile of retinal implantation. Our findings will help guide the design, conduct, and reporting of future clinical trials of retinal implantation and other emerging treatments for vision loss. (PROSPERO registration: CRD42022308123.)
Structural optimization and parameter investigation of trapezoidal shape soft pneumatic actuator
Authors: Vellaiyan Venkatesan , R Venkateshkumar , Bijalwan Vishwanath , Singh Yogesh 
Published: September 2024

Abstract
This study investigates the effects of actuator design parameters on the performance of developed trapezoidal shaped soft pneumatic actuator, optimizes its geometric structure using the finite element method and validates its performance experimentally. To optimize the soft pneumatic actuator, the effects of structural parameters such as wall thickness, gap between the adjacent chambers, passive layer thickness, width of inside chamber and the bending angle of the actuator were evaluated. Finite Element Analysis is used to determine the displacement variation of actuator with different levels of applied pressures. A Global Analysis of Variance was conducted to determine the influence of variables affecting the displacements of soft pneumatic actuator was determined. The ANOVA results, a geometric actuator with a wall thickness of 1.5 mm, gap between chambers of 4 mm, passive layer thickness of 2 mm and the width of inside chamber of 4 mm is recommended for the actuator to be achieve maximum bending angle. The proposed actuator model can be used to select the suitable actuator for grasping soft objects without deformation. In addition, experiment was conducted to correlate the results with finite element analysis data.
Public Life and Public Virtues
Authors: Sheldrake Philip 
Published: September 2024

AbstractThe book argues that “public life,” while embracing politics and economics, is an essential dimension of everyone’s lives. It is life lived together in society. In this “common space” we explore our identities and discover a sense of meaning and values. What are the most striking social challenges in the light of which we need to identify robust public virtues? The need is to understand “politics” differently as a way of serving society rather than a competition between political parties. Public virtues should include values that challenge the social status quo rather than values that simply reinforce “the establishment.” Against contemporary libertarian tendencies, we need to recover the notion of “self-discipline” as an important basis for a sense of social responsibility.
A Sense of Place
Authors: Sheldrake Philip 
Published: September 2024

AbstractA “sense of place” embraces the important value of rootedness and having a sense of identity and belonging. The vital question is who truly belongs in a place? Thomas Merton’s provocative essay “The Street is for Celebration” contrasts those who genuinely inhabit a place and those who are merely “dumped” and have to fight for recognition. “Place” obviously has a physical dimension but a deep “sense of place” also relates to being truly present and committed to a place. Being truly “placed” counters the privatization of public space which prioritizes commercial interests over what will benefit the whole community. A “sense of place” should no longer be limited to “the local” but should embrace a wider world and be just, beautiful, open-minded, ecological, humane, and diverse.
Cultivating Public Virtues
Authors: Sheldrake Philip 
Published: September 2024

AbstractHow are we to cultivate public virtues? This involves citizens working together to identify issues of mutual concern. There are a variety of ways in which public values or virtues can be cultivated—for example, by local faith communities or local clubs. However, the chapter focuses on two particular contexts—school education and public leadership. Schools need to encourage a sense of social responsibility and public service among their students. The educators should treat students with respect and also help them to orientate their lives towards purposeful ways of existing and acting. Turning to public leadership, what makes for “the good leader”? The chapter suggests that public leadership should go beyond efficient management or dominating personalities. The “good leader” seeks to contribute to the greater good of society. Leadership needs to be based on ethical strength, authenticity, honesty, and being committed to a sense of service.
Conclusion
Authors: Sheldrake Philip 
Published: September 2024

AbstractThe Conclusion outlines some contemporary dysfunctions that undermine public values. It then goes on to reflect briefly again on the thought of Michel de Certeau, the outstanding twentieth-century French Jesuit social scientist and spirituality scholar—especially in reference to public values. The Conclusion emphasizes that the public virtues outlined in the book seek to promote a vision of a “good society.” The Conclusion also briefly mentions the “Seven Principles of Public Life” set out by the British Committee on Standards in Public Life. The Conclusion ends by emphasizing the book’s provocative framework for creating a more equal and just society.
miniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data
Authors: Cui Miao , Liu Yadong , Yu Xian , Guo Hongzhe , Jiang Tao , Wang Yadong , Liu Bo 
Published: September 2024

Abstract
Nanopore sequence technology has demonstrated a longer read length and enabled to potentially address the limitations of short-read sequencing including long-range haplotype phasing and accurate variant calling. However, there is still room for improvement in terms of the performance of single nucleotide variant (SNV) identification and computing resource usage for the state-of-the-art approaches. In this work, we introduce miniSNV, a lightweight SNV calling algorithm that simultaneously achieves high performance and yield. miniSNV utilizes known common variants in populations as variation backgrounds and leverages read pileup, read-based phasing, and consensus generation to identify and genotype SNVs for Oxford Nanopore Technologies (ONT) long reads. Benchmarks on real and simulated ONT data under various error profiles demonstrate that miniSNV has superior sensitivity and comparable accuracy on SNV detection and runs faster with outstanding scalability and lower memory than most state-of-the-art variant callers. miniSNV is available from https://github.com/CuiMiao-HIT/miniSNV.
NeoDesign: a computational tool for optimal selection of polyvalent neoantigen combinations
Authors: Yu Wenqian , Yu Hongwu , Zhao Jingjing , Zhang Hena , Ke Kalam , Hu Zhixiang , Huang Shenglin 
Published: September 2024

Abstract

Motivation
Tumor polyvalent neoantigen mRNA vaccines are gaining prominence in immunotherapy. The design of sequences in vaccine development is crucial for enhancing both the immunogenicity and safety of vaccines. However, a major challenge lies in selecting the optimal sequences from the large pools generated by multiple peptide combinations and synonymous codons.

Results
We introduce NeoDesign, a computational tool designed to tackle the challenge of sequence design. NeoDesign comprises four modules: Library Construction, Optimal Path Filtering, Linker Addition, and λ-Evaluation. It aims to identify the optimal protein sequence for tumor polyvalent neoantigen vaccines by minimizing linker usage, avoiding unexpected neoantigens and functional domains, and simplifying the structure. It also provides a preference scheme to balance mRNA stability and protein expression when designing mRNA sequences for the optimal protein sequence. This tool can potentially improve the sequence design of tumor polyvalent neoantigen mRNA vaccines, thereby significantly advancing immunotherapy strategies.

Availability and implementation
NeoDesign is freely available on https://github.com/HuangLab-Fudan/neoDesign and https://figshare.com/projects/NeoDesign/221704.
Patient-derived tau and amyloid-β facilitate long-term depression in vivo: role of tumour necrosis factor-α and the integrated stress response
Authors: Hu Neng-Wei , Ondrejcak Tomas , Klyubin Igor , Yang Yin , Walsh Dominic M , Livesey Frederick J , Rowan Michael J 
Published: September 2024

Abstract
Alzheimer’s disease is characterized by a progressive cognitive decline in older individuals accompanied by the deposition of two pathognomonic proteins amyloid-β and tau. It is well documented that synaptotoxic soluble amyloid-β aggregates facilitate synaptic long-term depression, a major form of synaptic weakening that correlates with cognitive status in Alzheimer’s disease. Whether synaptotoxic tau, which is also associated strongly with progressive cognitive decline in patients with Alzheimer’s disease and other tauopathies, also causes facilitation remains to be clarified. Young male adult and middle-aged rats were employed. Synaptotoxic tau and amyloid-β were obtained from different sources including (i) aqueous brain extracts from patients with Alzheimer’s disease and Pick’s disease tauopathy; (ii) the secretomes of induced pluripotent stem cell-derived neurons from individuals with trisomy of chromosome 21; and (iii) synthetic amyloid-β. In vivo electrophysiology was performed in urethane anaesthetized animals. Evoked field excitatory postsynaptic potentials were recorded from the stratum radiatum in the CA1 area of the hippocampus with electrical stimulation to the Schaffer collateral–commissural pathway. To study the enhancement of long-term depression, relatively weak low-frequency electrical stimulation was used to trigger peri-threshold long-term depression. Synaptotoxic forms of tau or amyloid-β were administered intracerebroventricularly. The ability of agents that inhibit the cytokine tumour necrosis factor-α or the integrated stress response to prevent the effects of amyloid-β or tau on long-term depression was assessed after local or systemic injection, respectively. We found that diffusible tau from Alzheimer’s disease or Pick’s disease patients’ brain aqueous extracts or the secretomes of trisomy of chromosome 21 induced pluripotent stem cell-derived neurons, like Alzheimer’s disease brain-derived amyloid-β and synthetic oligomeric amyloid-β, potently enhanced synaptic long-term depression in live rats. We further demonstrated that long-term depression facilitation by both tau and amyloid-β was age-dependent, being more potent in middle-aged compared with young animals. Finally, at the cellular level, we provide pharmacological evidence that tumour necrosis factor-α and the integrated stress response are downstream mediators of long-term depression facilitation by both synaptotoxic tau and amyloid-β. Overall, these findings reveal the promotion of an age-dependent synaptic weakening by both synaptotoxic tau and amyloid-β. Pharmacologically targeting shared mechanisms of tau and amyloid-β synaptotoxicity, such as tumour necrosis factor-α or the integrated stress response, provides an attractive strategy to treat early Alzheimer’s disease.