bluuebunny/crossref_metadata_2025_split huggingface dataset:
Privacy‐Preserving Optimization Algorithm for Distributed Energy Management Over Time‐Varying Graphs: A State Decomposition Method
Authors: Luan Meng , Wen Guanghui , Yang Tao 
Published: October 2024

ABSTRACTThe rapid advancements of intelligent technologies have brought about the potential vulnerability of confidential gradient information linked to cost functions when solving distributed optimization and its related problems. Within the context of distributed energy management, safeguarding such private information has risen to paramount importance. This article investigates a distributed energy management problem (DEMP) to minimize cost while simultaneously satisfying multiple local constraints and protecting the private gradient information of the cost function. To this end, a new privacy‐preserving distributed optimization algorithm under the framework of gradient tracking over time‐varying graphs is proposed for solving the DEMP. Specifically, the auxiliary variables are designed for each node in the algorithm to update the gradient while the original state variables are responsible for the interaction with original neighbors and auxiliary variables. Consequently, the devised algorithm can protect the confidentiality of private cost gradient information, even in the presence of eavesdroppers within the network. In contrast to the homomorphic encryption, signal masking method, and some other algorithms without utilizing the state decomposition, the designed algorithm does not require extra information or computing resources. Moreover, it is proven that the designed algorithm could theoretically converge to the exact optimum of the DEMP at a rate of under some mild assumptions.
Sampled‐Data Based Second‐Order Discrete‐Time Sliding Mode Control via Output Feedback
Authors: Chen Weile , Du Haibo , Li Shihua , Yu Xinghuo 
Published: October 2024

ABSTRACTThis article proposes a second‐order discrete‐time sliding mode controller (DSMC) by only using sampled‐data information of the system output. On one hand, different from the continuous‐time sliding mode control, the finite‐time stability of the closed‐loop system under DSMC is usually not kept due to the limited sampling frequency. On the other hand, in the output feedback framework, the second‐order sliding mode observer cannot independently estimate the internal state of the system if there exist unknown mismatched term and unknown time‐varying coefficient of the control input. To solve the above problems, a joint design strategy of second‐order discrete‐time sliding mode observer and sliding mode controller based on the “non‐separation principle” is proposed. The stability and robustness of the closed‐loop system is analyzed based on the Lyapunov design method. Finally, simulation example verifies the correctness of the theory.
Drainage gradient versus seasonal cycles: Differential response of microbial community composition to variations in soil moisture
Authors: Burgess Christopher J. , Myrold David D. , Mueller Ryan S. , Wanzek Thomas , Moore Jennifer M. , Kasschau Kristin D. , Kleber Markus 
Published: October 2024

AbstractThe variation in the soil microbial community composition over time was assessed at monthly time steps for 1 year in three neighboring Mollisols spanning a drainage gradient. This was done to distinguish between natural oscillations in the community composition versus lasting adaptations to environmental factors such as soil water availability. To isolate soil water availability as a controlling factor, we selected three soils sharing the same soil order (fine‐silty, superactive Argixerolls/Argialbolls); slope (0%–1%); temperature regime (mesic); moisture regime (xeric); and land use history (continuous grassland for the past 10 years) but differing in drainage class (well‐drained vs. moderately well‐drained vs. poorly drained). Changes in microbial diversity were quantified by monitoring the bacterial community at monthly intervals for 1 year. Within individual soils, α‐diversity varied little with season and drainage classes. Despite the three soils experiencing the same climate regime and vegetation/land use, they exhibited distinct community composition and turnover, which we attribute to differences in moisture availability across drainage and seasons. We posit that a seasonal recurring drop in soil redox potential induced by seasonal water saturation in the poorly drained soil is the most probable cause setting the microbial community of that soil apart from those in the better drained soils. Our investigation suggests that not all indicators of microbial diversity share the same sensitivity to seasonal and drainage‐related soil moisture variations.
Genetic Prediction Modeling in Large Cohort Studies via Boosting Targeted Loss Functions
Authors: Klinkhammer Hannah , Staerk Christian , Maj Carlo , Krawitz Peter M. , Mayr Andreas 
Published: October 2024

ABSTRACTPolygenic risk scores (PRS) aim to predict a trait from genetic information, relying on common genetic variants with low to medium effect sizes. As genotype data are high‐dimensional in nature, it is crucial to develop methods that can be applied to large‐scale data (large and large ). Many PRS tools aggregate univariate summary statistics from genome‐wide association studies into a single score. Recent advancements allow simultaneous modeling of variant effects from individual‐level genotype data. In this context, we introduced snpboost, an algorithm that applies statistical boosting on individual‐level genotype data to estimate PRS via multivariable regression models. By processing variants iteratively in batches, snpboost can deal with large‐scale cohort data. Having solved the technical obstacles due to data dimensionality, the methodological scope can now be broadened—focusing on key objectives for the clinical application of PRS. Similar to most methods in this context, snpboost has, so far, been restricted to quantitative and binary traits. Now, we incorporate more advanced alternatives—targeted to the particular aim and outcome. Adapting the loss function extends the snpboost framework to further data situations such as time‐to‐event and count data. Furthermore, alternative loss functions for continuous outcomes allow us to focus not only on the mean of the conditional distribution but also on other aspects that may be more helpful in the risk stratification of individual patients and can quantify prediction uncertainty, for example, median or quantile regression. This work enhances PRS fitting across multiple model classes previously unfeasible for this data type.
Metal‐Catalyzed Polymer Dehydrochlorination and Hydrodefluorination
Authors: Varela‐Izquierdo Víctor , Ghosh Sourav , Hammoud Leila , Fazzini Pier‐Francesco , Guelen Simon , Marion Philippe , Chaudret Bruno 
Published: October 2024

AbstractDehydrochlorination (DHC) is of importance for modulating the physical properties of halogenated polymers. In this work, the DHC of commercial VDF‐CTFE (vinylidene fluoride‐co‐chlorotrifluoroethylene) (10 mol % CTFE) copolymer to VDF‐DB (vinylidene fluoride with unsaturated moieties‐Double Bond) was achieved in mild reaction conditions (150 °C and 3 bar hydrogen) using different supported nickel catalysts. A complete DHC was observed within four hours of the reaction. Additionally, a certain extent (8–35 %) of hydrodefluorination (HDF) of the polymer, a challenging transformation, can also be achieved after 72 hours. A plausible mechanism based on the nuclear magnetic resonance (NMR) spectroscopy study of DHC and HDF of VDF‐CTFE was proposed. The catalyst was recyclable and stable against leaching after at least three cycles.
Gamma Radiolysis of n‐Dodecane: Physicochemical Properties and Metal Retention Behavior
Authors: Mishra Satyabrata , Ghosh Debojyoti , Rajesh Puspalata , Narasimhan Desigan , Venkatesan Konda Athmaram 
Published: October 2024

AbstractThe gamma radiolytic degradation behavior of n‐dodecane (n‐DD) was investigated under conditions both with and without the presence of nitric acid. The physicochemical property alterations due to radiolysis were quantified and compared against an unirradiated system. Compositional changes in n‐DD post radiolysis was measured, and the degraded n‐DD was characterized using Fourier‐transform infrared (FT‐IR) spectroscopy, gas chromatography (GC), and gas chromatography–mass spectrometry (GC–MS) analysis. The presence of nitric acid was observed to accelerate the radiolytic degradation of n‐DD. The extent of diluent degradation caused by gamma irradiation was assessed through the retention behavior of uranium [U(VI)], plutonium [Pu(IV)], and zirconium [Zr(IV)] in 1.1 M tri‐n‐butyl phosphate (TBP) in irradiated diluent. Furthermore, the effectiveness of hydrazine carbonate (HC) as a solvent wash reagent for the removal of diluent degradation products was evaluated.
Zwitterionic Nanochannels in Covalent Organic Framework Membranes for Improved Flux and Antifouling Property
Authors: Ji Wenyan , Liu Ming , Li Yuping , Liu Lulu , Wang Yuhan , Duan Feng , Su Chunlei , Li Haibo , Cao Renqiang , Yin Jingya , Wei Mingjie , Jiang Zhongyi , Cao Hongbin 
Published: October 2024

AbstractZwitterionic membranes demonstrate excellent antifouling property in water purification. The covalent organic frameworks (COFs), due to the ordered channels and abundant organic functional groups, have distinct superiority in constructing zwitterionic surfaces.Here, the zwitterionic COF membrane is prepared with precise framework structures and uniform charge distribution. The negatively charged 4,4′‐diaminobiphenyl‐2,2′‐sisulphonic acid sodium (SA) and positively charged ethidium bromide (EB) fragments are used to react with 1,3,5‐triformylphloroglucinol (TP) at the gas‐liquid interface to prepare zwitterionic COF membrane. The complementary charged fragments in the inter‐layer and inner‐layer facilitate the formation of continuous and tight hydration layer on the membrane surface and pore walls to resist the adsorption of pollutants. The zwitterionic COF membrane effectively resists both negatively charged bovine serum albumin and positively charged lysozyme pollutants with flux recovery ratio (FRR) of 97% and 85%, respectively. Furthermore, the regular nano‐channels and balanced interactions between water and surface/pore walls of the zwitterionic membrane result in outstanding permeability of up to 146 L m−2 h−1 bar−1 and excellent dye/salt separation selectivity. The water permeation and antifouling mechanism of membranes are elucidated by experimental and molecular dynamics calculation. Zwitterionic COF membranes can find promising applications in preparing high‐performance antifouling membranes.
Metformin Syncs CeO2 to Recover Intra‐ and Extra‐Cellular ROS Homeostasis in Diabetic Wound Healing
Authors: Li Mengyang , Dong Yuhang , Shang Yage , Liu Jiaqi , Wang Yunchuan , Zhang Dongliang , Zhang Lixia , Han Chao , Zhang Yue , Shen Kuo , Yang Yaoxiang , Wang Hongtao , Guan Hao , Hu Dahai 
Published: October 2024

AbstractExcessive generation of reactive oxygen species (ROS) poses a huge obstacle to the healing process of diabetic wounds, resulting in chronic, non‐healing wounds. While numerous anti‐ROS therapeutics have been developed, satisfied intra‐ and extra‐ cellular ROS homeostasis is hard to be established in diabetic wounds. To address this issue, a nanoparticle via loading metformin and CeO2 into mesoporous silica (MSN@Met‐CeO2) is designed and synthesized, which is then encapsulated within ROS‐responsive hydrogel and shaped as microneedles (MNs) for better application in diabetic wounds. Interestingly, a unique metformin‐cerium chelate (Ce· 3Metformin) is formed during the synthesis of MSN@Met‐CeO2 MN, which significantly strengthened the inhibitory effect of metformin on mitochondrial complex I. With the presence of Ce· 3Metformin, MSN@Met‐CeO2 MN performed a remarkable effect on intracellular mtROS reduction as well as extracellular ROS elimination, the latter is primarily accomplished through the dissociative CeO2 in MSN@Met‐CeO2 MN. In the mouse diabetic wound model, MSN@Met‐CeO2 MN exhibited a superior pro‐healing effect with accelerated inflammation resolution and enhanced angiogenesis, thus highlighting its significant potential for clinical application
Recent Advances on the Construction of Functionalized Indolizine and Imidazo[1,2‐a]pyridine Derivatives
Authors: Liu Xiang , Fu Haifeng , Hu Qi , Cao Hua 
Published: October 2024

AbstractIndolizines and imidazo[1,2‐a]pyridines are commonly found in natural products, synthetic drugs, and bioactive molecules. These two types of derivatives possess good antibacterial, antiparasitic, anticancer activities, and so on. The functionalization of indolizines and imidazo[1,2‐a]pyridines has always been a hot topic in organic chemistry research and has made significant progress. In recent years, our group has been dedicated to developing diverse synthetic methods for the preparation of such important compounds. 1) We have developed diverse C−H functionalization reactions for efficient modification of the parent indolizines and imidazo[1,2‐a]pyridines. 2) A variety of cycloaddition reactions were established for the construction of indolizine and imidazo[1,2‐a]pyridine derivatives from simple raw materials. 3) We have developed intriguing deconstruction‐functionalization reactions of indolizines, enabling the reorganization of heterocyclic frameworks. This paper outlines our group's latest advancements in constructing structurally diverse indolizine and imidazo[1,2‐a]pyridine derivatives. We hope that this work will offer valuable insights and inspiration for the ongoing research in the field of N‐heterocyclic compounds.
Kinetics and Mechanism Study of Different Types of Surface‐Imprinted Polymers for CO2 Adsorption
Authors: Ishak Noorhidayah , Mohamed Nasir Azalina , Ibrahim Muthmirah , Ahmad Mohd Azmier , Hameed Bassim H. , Mohd Din Azam Taufik 
Published: October 2024

ABSTRACTThe increased level of CO2 in the atmosphere has led to global warming and climate change. To mitigate these problems, solid adsorbents have become attractive materials for capturing excess CO2 in the post‐combustion method. Molecularly imprinted polymer (MIP) can be applied to prepare highly selective adsorbents that could capture CO2 molecules. The MIP was prepared using the surface imprinted polymer technique in this preliminary work. Only two types of support materials were used (graphite and silica gel) to screen the best support material that could enhance the CO2 adsorption capacity of the resulting adsorbent, which was analyzed using a fixed‐bed column reactor. Graphite‐imprinted polymer (GMIP) was found to be a good potential for CO2 adsorption. The Avrami model best described the adsorption system, while the fixed‐bed curve data fit the Yoon–Nelson model well. The semi‐empirical method was used to assess the interaction mechanism of the molecularly imprinted polymer with CO2 during adsorption. This investigation involved testing four different ratios of the template complex to functional monomers. The ratio of 1:4 (CO2:Allylthiourea) demonstrated the highest binding energy, with a higher formation of hydrogen bonds. Film diffusion and intraparticle diffusion were the main rate‐limiting steps that played vital roles at different stages of CO2 adsorption. This preliminary work has enhanced the development of MIP for CO2 adsorption and showcased the integration of computational approaches in tailoring specific MIPs.
ROBERT: Bridging the Gap Between Machine Learning and Chemistry
Authors: Dalmau David , Alegre‐Requena Juan V. 
Published: October 2024

ABSTRACTBeyond addressing technological demands, the integration of machine learning (ML) into human societies has also promoted sustainability through the adoption of digitalized protocols. Despite these advantages and the abundance of available toolkits, a substantial implementation gap is preventing the widespread incorporation of ML protocols into the computational and experimental chemistry communities. In this work, we introduce ROBERT, a software carefully crafted to make ML more accessible to chemists of all programming skill levels, while achieving results comparable to those of field experts. We conducted benchmarking using six recent ML studies in chemistry containing from 18 to 4149 entries. Furthermore, we demonstrated the program's ability to initiate workflows directly from SMILES strings, which simplifies the generation of ML predictors for common chemistry problems. To assess ROBERT's practicality in real‐life scenarios, we employed it to discover new luminescent Pd complexes with a modest dataset of 23 points, a frequently encountered scenario in experimental studies.
Boost heat transfer efficiency through thermal radiation and electrical conductivity in nanofluids
Authors: Majeed Aaqib , Saidani Taoufik , Ijaz Nouman , Ibrahim Ahmed Osman , Gnaba Hela , Ali Sadia Samar 
Published: October 2024

AbstractThermal radiation and electrical conductivity in nanofluids are crucial for their heat transfer characteristics, especially in applications with elevated temperatures or significant radiative heat transfer. The suspension of nanoparticles in suspension contributes to the fluid's electrical conductivity, which is essential for efficient heat dissipation in electronic cooling systems. Understanding the behavior of electroconductive nanofluids is particularly important in electronic cooling applications, where effective heat dissipation is crucial to prevent overheating. A study using a similarity parameter transformed a system of coupled PDEs into a set of nonlinear ordinary differential equations, revealing significant changes in key physical characteristics, such as temperature distribution, cubic concentration field, and velocity field. The study also examined the effects of parameters like Brownian motion, Rayleigh number, Peclet number, thermophoresis parameter, and buoyancy ratio parameter. The research provides valuable insights into the complex dynamics of magnetized non‐Newtonian nanofluids and offers practical implications for applications like microbial fuel cells and heat transmission equipment.
An Overview on E-Participation
Authors: Mariani Ilaria , Mortati Marzia , Rizzo Francesca , Deserti Alessandro 
Published: October 2024

AbstractThis chapter provides an overview of e-participation, tracing its evolution from early public involvement initiatives to its current integration with digital technologies. It provides examples of implementations and highlights both the potential and challenges of e-participation practices and platforms. The cases are used to discuss the strategic importance of e-participation in enhancing transparency, legitimacy, and trust in public governance, pointing out the role of digital technologies in broadening the scope and depth of public engagement, transforming traditional models and fostering more direct and meaningful interactions between citizens and governments. Ultimately, it explores open challenges in need to be addressed.
Design Thinking Practices for E-Participation
Authors: Mariani Ilaria , Mortati Marzia , Rizzo Francesca , Deserti Alessandro 
Published: October 2024

AbstractThis chapter identifies design thinking practices for supporting e-participation. The chapter presents the five practices of (i) Meaning creation and sense-making, (ii) Publics formation, (iii) Co-production, (iv) Experimenting and prototyping, and (v) Changing organisational culture. Each of these practices is discussed against relevant case studies.
Deployment and performance of a Low-Energy-Threshold Skipper-CCD inside a nuclear reactor
Authors: Depaoli E. , Rodrigues D. , Sidelnik I. , Bellino P. , Botti A. , Delgado D. , Cababié M. , Chierchie F. , Estrada J. , Moroni G. Fernández , Perez S. , Tiffenberg J. 
Published: October 2024

Abstract
Charge Coupled Devices (CCD) are being used for reactor neutrino experiments and have already demonstrated their potential in constraining new physics models. The prospect of a Skipper-CCD experiment looking for standard and beyond standard model (BSM) physics in a nuclear reactor has been evaluated for different benchmark scenarios. Here, we report the first installation of a 2-g Skipper-CCD inside the containment building of a 2 GWth nuclear power plant and analyze its performance throughout its first 18 months of operation. The sensor was successfully deployed at Atucha II, in Argentina, 12 meters away from the center of the reactor core. We discuss the challenges involved in the commissioning of the detector and present data acquired during reactor ON and reactor OFF periods, with the sensor functioning with a sub-electron readout noise of 0.17 e−. Based on an exposure of 56.8 g day reactor ON and two reactor OFF data sets with a total exposure of 118.1 g day we characterize the system and evaluate the sensitivity to CEvNS. We achieved a background rate of 33 kdru and a low threshold of 45 eVee. The ongoing efforts to improve sensitivities to CEvNS and BSM interaction are also discussed.
Adler function, Bjorken polarized sum rule: confirmation of elements of the {β}-expansion and the diagrams
Authors: Mikhailov S. V. 
Published: October 2024

Abstract
Different ways exist to obtain the elements of the {β}-expansion for renormgroup invariant quantities. Here we consider independent confirmation within the standard QCD of a number of our results [1] for the values of elements of this expansion for the nonsinglet Adler DA-function, Bjorken polarized sum rules SBjp up to the order N4LO. We suggest an approach to estimate the results of high order QCD calculations using a smaller number of diagrams of the specific type. This type is based on a proposed generalization of Naive NonAbelianization.
Ferulic acid ameliorates bisphenol A (BPA)-induced Alzheimer’s disease-like pathology through Akt-ERK crosstalk pathway in male rats
Authors: Khalifa Mhasen , Fayed Rabie H. , Ahmed Yasmine H. , Abdelhameed Mohamed F. , Essa Ahmed F. , Khalil Heba M. A. 
Published: October 2024

Abstract

Objectives
This study investigated the neuroprotective effect of ferulic acid (FA) against bisphenol A (BPA) induced Alzheimer’s disease-like pathology in male rats.

Methods
Rats were allocated into four groups, control, BPA, BPA + FA, and FA, respectively, for 40 days. Spatial working memory and recognition memory were evaluated. Moreover, the brain levels of oxidative stress biomarkers, proinflammatory cytokines, extracellular signal-regulated kinase (ERK), and phosphorylated serine/threonine protein kinase (p-Akt) were measured. We also determined the brain neuropathological protein levels, including Beta-Amyloid 1–42, total Tau (tTau), and phosphorylated Tau (pTau) proteins. Furthermore, brain levels of Acetylcholinesterase (AChE) and Beta-secretase (BACE) were assessed. Brain histological investigation and immunohistochemistry determination of glial fibrillar acidic protein (GFAP) were also performed. Moreover, docking simulation was adapted to understand the inhibitory role of FA on AChE, BACE-1, and ERK1/2.

Results
Interestingly, the BPA + FA treated group showed a reversal in the cognitive impairments induced by BPA, which was associated with improved brain redox status. They also exhibited a significant decrease in brain inflammatory cytokines, ERK, and p-Akt levels. Moreover, they revealed a decline in beta-amyloid 1–42 and a significant improvement in tTau expression and pTau protein levels in the brain tissue. Further, the brain levels of AChE and BACE were substantially reduced in BPA + FA rats. The neuroprotective effect of FA was confirmed by restoring the normal architecture of brain tissue, which was associated with decreasing GFAP.

Conclusion
FA could be a potent neuroprotectant agent against AD with a possible prospect for its therapeutic capabilities and nutritional supplement value due to its antioxidant and antiapoptotic properties.