bluuebunny/crossref_metadata_2025_split huggingface dataset:
Estimating predation rates of stocked juvenile Chinook Salmon using novel acoustic predation transmitters
Authors: Gravenhof D. A. , Wuellner M. R. , Renner E. A. , Fincel M. J. 
Published: March 2024

Abstract

Objective
Acoustic telemetry is a tool commonly used to better understand the fates of fish following a stocking event. Until recently, predation on stocked fish could only be inferred by observing and identifying abrupt changes in tag detection histories. Recently, a novel predation transmitter has provided better insight into how predation affects poststocking survival. The main objective of this study was to use these transmitters to estimate predation rates on stocked juvenile Chinook Salmon Oncorhynchus tshawytscha in a landlocked system (Lake Oahe, South Dakota). Our secondary objectives were to determine how quickly predation was occurring, the time of day of predation events, and if there were differences in size between predated and nonpredated fish.

Methods
In 2021 and 2022, we surgically implanted Innovasea V5D 180-kHz transmitters in 110 juvenile Chinook Salmon. These tagged Chinook Salmon were stocked at two locations on Lake Oahe along with a large cohort of untagged individuals. The tagged Chinook Salmon were passively tracked using an array of Innovasea VR2W 180-kHz acoustic receivers.

Result
Across the two study years, we observed a mean predation rate (±SE) of 32.9 ± 6% on the tagged Chinook Salmon. Predation on the tagged Chinook Salmon occurred relatively quickly, with a mean time to predation of 86.7 ± 10.8 h. Additionally, 70% of the observed predation occurred during the daytime. Interestingly, results indicated that total length did not differ between fish that were preyed upon or and those that were, but there was a difference in total weight between the two groups.

Conclusion
Our results provide insight into recruitment bottlenecks within this population and offer information to other researchers regarding the advantages and limitations of this novel technology. Understanding how to mitigate predation could help to guide future stocking strategies to ensure a better return on investment for costly stocking programs.
Penalty‐free discontinuous Galerkin method
Authors: Jaśkowiec Jan , Sukumar N. 
Published: March 2024

AbstractIn this article, we present a new high‐order discontinuous Galerkin (DG) method, in which neither a penalty parameter nor a stabilization parameter is needed. We refer to this method as penalty‐free DG. In this method, the trial and test functions belong to the broken Sobolev space, in which the functions are in general discontinuous on the mesh skeleton and do not meet the Dirichlet boundary conditions. However, a subset can be distinguished in this space, where the functions are continuous and satisfy the Dirichlet boundary conditions, and this subset is called admissible. The trial solution is chosen to lie in an augmented admissible subset, in which a small violation of the continuity condition is permitted. This subset is constructed by applying special augmented constraints to the linear combination of finite element basis functions. In this approach, all the advantages of the DG method are retained without the necessity of using stability parameters or numerical fluxes. Several benchmark problems in two dimensions (Poisson equation, linear elasticity, hyperelasticity, and biharmonic equation) on polygonal (triangles, quadrilateral, and weakly convex polygons) meshes as well as a three‐dimensional Poisson problem on hexahedral meshes are considered. Numerical results are presented that affirm the sound accuracy and optimal convergence of the method in the norm and the energy seminorm.
Efficient and high‐resolution surface‐wave dispersive energy imaging using a proposed spatial smoothing propagation method
Authors: He Tao , Peng Suping , Geng Henggao 
Published: March 2024

AbstractSurface‐wave information from seismic data can be used for near‐surface analysis, static computation and noise suppression. The multichannel analysis of surface waves method is a useful approach for obtaining the shear wave velocity of the near surface; however, rapidly generating an image of dispersive energy in the presence of coherent noise is a challenge. In this study, we propose the imaging of the dispersive energy of the Rayleigh wave using a spatial smoothing propagation method. In this method, forward and backward spatial smoothing algorithms were used to restore the rank of the covariance matrix in strong coherent noise. Subsequently, an image of the dispersive energy was rapidly generated by the propagation method using a linear operation equivalent to the eigenvalue decomposition. The proposed method was evaluated using both synthetic and field data. The results showed that the method was easy to use and has higher resolution representation, efficiency and noise robustness compared with conventional methods.
The forgotten history of intercropping
Authors: Harwood Jonathan 
Published: March 2024

Societal Impact StatementOver the last 50 years, the practice of ‘intercropping’ (planting a mixture of several crops on the same field) has drawn growing attention in crop science. Given its high yields but low requirement for fertiliser or pesticides, it offers considerable advantages over conventional ‘industrial’ agriculture. Nevertheless, although research on intercropping has been conducted since the late 19th century, that work became largely invisible after 1945 as the rapid rise of industrial agriculture erased alternative approaches from view. Since the 1970s, however, intercropping and other alternatives have reappeared on the research agenda as the damaging impacts of industrial agriculture have become evident.SummaryIntercropping has long been of interest in agro‐ecology. Indeed, as the first generation of (English‐speaking) agro‐ecologists saw it, research on intercropping began in the 1970s and 1980s just as the field was beginning to emerge. Although the evidence confirms a rapid increase in such work from the 1970s, however, what nearly all agro‐ecologists then overlooked was the existence of two older traditions of work dating from the late 19th century. The aim of this paper is to explain why early agro‐ecologists were unaware of previous work. The history of research on intercropping in both the English‐ and German‐speaking worlds was traced using the journal literature as well as textbooks of agronomy. What this survey revealed is that in Europe and North America, agronomists had been working on intercropping since the 1890s, and during the interwar period and into the 1950s, the practice attracted considerable attention from colonial agronomists. Although this early work was in the public domain during the 1970s, however, few agro‐ecologists noticed it. There are various reasons why the first generation of agro‐ecologists might have known about but chose to ignore earlier work on intercropping. But more likely is that most members of that generation were simply unaware of the older work. For the forgotten history of intercropping, research appears to be just one aspect of a more general phenomenon during the 20th century in which a wide variety of ‘alternative’ cultivation practices were marginalised after 1945, only to re‐emerge from the 1970s as the social and environmental consequences of industrial agriculture came under attack.
The Mass Gap of the Space‐time and its Shape
Authors: Ali Ahmed Farag 
Published: March 2024

AbstractSnyder's quantum space‐time which is Lorentz invariant is investigated. It is found that the quanta of space‐time have a positive mass that is interpreted as a positive real mass gap of space‐time. This mass gap is related to the minimal length of measurement which is provided by Snyder's algebra. Several reasons to consider the space‐time quanta as a 24‐cell are discussed. Geometric reasons include its self‐duality property and its 24 vertices that may represent the standard model of elementary particles. The 24‐cell symmetry group is the Weyl/Coxeter group of the group which was found recently to generate the gauge group of the standard model. It is found that 24‐cell may provide a geometric interpretation of the mass generation, Avogadro number, color confinement, and the flatness of the observable universe. The phenomenology and consistency with measurements is discussed.
Evaluation of covariate effects in item response theory models
Authors: Wellhagen Gustaf J. , Yassen Ashraf , Garmann Dirk , Bröker Astrid , Solms Alexander , Zhang Yang , Kjellsson Maria C. , Karlsson Mats O. 
Published: March 2024

AbstractItem response theory (IRT) models are usually the best way to analyze composite or rating scale data. Standard methods to evaluate covariate or treatment effects in IRT models do not allow to identify item‐specific effects. Finding subgroups of patients who respond differently to certain items could be very important when designing inclusion or exclusion criteria for clinical trials, and aid in understanding different treatment responses in varying disease manifestations. We present a new method to investigate item‐specific effects in IRT models, which is based on inspection of residuals. The method was investigated in a simulation exercise with a model for the Epworth Sleepiness Scale. We also provide a detailed discussion as a guidance on how to build a robust covariate IRT model.
Adaptive iterative learning control for high‐order nonlinear systems with different types of uncertainties
Authors: Li Xuefang , Chen Yanfang , Sun Hui‐Jie , Liu Wanquan 
Published: March 2024

AbstractThe present work aims at investigating the adaptive iterative learning control (AILC) design for uncertain high‐order fully actuated nonlinear systems. In order to show the design principles, three types of nonlinear systems are considered, including systems with just parametric uncertainty, systems with both parametric and input distribution uncertainties as well as systems with both parametric uncertainty and an unknown control gain matrix. For different systems, the corresponding AILC schemes are proposed with different techniques in dealing with various system uncertainties, for which the convergence analysis are conducted rigorously based on the composite energy function. The effectiveness of the proposed AILC strategies is verified through numerical simulations.
Marginal clustered multistate models for longitudinal progressive processes with informative cluster size
Authors: Feng Sean Xinyang , Mitani Aya A. 
Published: March 2024

AbstractInformative cluster size (ICS) is a phenomenon where cluster size is related to the outcome. While multistate models can be applied to characterize the unit‐level transition process for clustered interval‐censored data, there is a research gap addressing ICS within this framework. We propose two extensions of multistate model that account for ICS to make marginal inference: one by incorporating within‐cluster resampling and another by constructing cluster‐weighted score functions. We evaluate the performances of the proposed methods through simulation studies and apply them to the Veterans Affairs Dental Longitudinal Study (VADLS) to understand the effect of risk factors on periodontal disease progression. ICS occurs frequently in dental data, particularly in the study of periodontal disease, as people with fewer teeth due to the disease are more susceptible to disease progression. According to the simulation results, the mean estimates of the parameters obtained from the proposed methods are close to the true values, but methods that ignore ICS can lead to substantial bias. Our proposed methods for clustered multistate model are able to appropriately take ICS into account when making marginal inference of a typical unit from a randomly sampled cluster.
Application programming interface recommendation for smart contract using deep learning from augmented code representation
Authors: Cai Jie , Cai Qian , Li Bin , Zhang Jiale , Sun Xiaobing 
Published: March 2024

AbstractApplication programming interface (API) recommendation plays a crucial role in facilitating smart contract development by providing developers with a ranked list of candidate APIs for specific recommendation points. Deep learning‐based approaches have shown promising results in this field. However, existing approaches mainly rely on token sequences or abstract syntax trees (ASTs) for learning recommendation point‐related features, which may overlook the essential knowledge implied in the relations between or within statements and may include task‐irrelevant components during feature learning. To address these limitations, we propose a novel code graph called pruned and augmented AST (pa‐AST). Our approach enhances the AST by incorporating additional knowledge derived from the control and data flow relations between and within statements in the smart contract code. Through this augmentation, the pa‐AST can better represent the semantic features of the code. Furthermore, we conduct AST pruning to eliminate task‐irrelevant components based on the identified flow relations. This step helps mitigate the interference caused by these irrelevant parts during the model feature learning process. Additionally, we extract the API sequence surrounding the recommendation point to provide supplementary knowledge for the model learning. The experimental results demonstrate our proposed approach achieving an average mean reciprocal rank (MRR) of 68.02%, outperforming the baselines' performance. Furthermore, through ablation experiments, we explore the effectiveness of our proposed code representation approach. The results indicate that combining pa‐AST with the API sequence yields improved performance compared with using them individually. Moreover, our AST augmentation and pruning techniques significantly contribute to the overall results.
Hot‐Pressing Enhances Mechanical Strength of PEO Solid Polymer Electrolyte for All‐Solid‐State Sodium Metal Batteries
Authors: Zhao Lanqing , Hou Minjie , Ren Kun , Yang Dongrong , Li Fupeng , Yang Xiecheng , Zhou Yingjie , Zhang Da , Liu Shan , Lei Yong , Liang Feng 
Published: March 2024

AbstractPoly(ethylene oxide) (PEO)‐based solid polymer electrolytes (SPEs) are widely utilized in all‐solid‐state sodium metal batteries (ASSSMBs) due to their excellent flexibility and safety. However, poor ionic conductivity and mechanical strength limit its development. In this work, an emerging solvent‐free hot‐pressing method is used to prepare mechanically robust PEO‐based SPE, while sodium superionic conductors Na3Zr2Si2PO12 (NZSP) and NaClO4 are introduced to improve ionic conductivity. The as‐prepared electrolyte exhibits a high ionic conductivity of 4.42 × 10−4 S cm−1 and a suitable electrochemical stability window (4.5 V vs Na/Na+). Furthermore, the SPE enables intimate contact with the electrode. The Na||Na3V2(PO4)3@C ASSSMB delivers a high‐capacity retention of 97.1% after 100 cycles at 0.5 C and 60 °C, and exhibits excellent Coulombic efficiency (CE) (close to 100%). The ASSSMB with the 20 µm thick electrolyte also demonstrates excellent cyclic stability. This study provides a promising strategy for designing stable polymer‐ceramic composite electrolyte membranes through hot‐pressing to realize high‐energy‐density sodium metal batteries.
Understanding and unveiling the electro‐chemo‐mechanical behavior in solid‐state batteries
Authors: Zhong Yunlei , Zhang Xia , Zhang Yong , Jia Peng , Xi Yuebin , Kang Lixing , Yu Zhenjiang 
Published: March 2024

AbstractSolid‐state batteries (SSBs) are attracting growing interest as long‐lasting, thermally resilient, and high‐safe energy storage systems. As an emerging area of battery chemistry, there are many issues with SSBs, including strongly reductive lithium anodes, oxidized cathodes (state of charge), the thermodynamic stability limits of solid‐state electrolytes (SSEs), and the ubiquitous and critical interfaces. In this Review, we provided an overview of the main obstacles in the development of SSBs, such as the lithium anode|SSEs interface, the cathode|SSEs interface, lithium‐ion transport in the SSEs, and the root origin of lithium intrusions, as well as the safety issues caused by the dendrites. Understanding and overcoming these obstacles are crucial but also extremely challenging as the localized and buried nature of the intimate contact between electrode and SSEs makes direct detection difficult. We reviewed advanced characterization techniques and discussed the complex ion/electron‐transport mechanism that have been plaguing electrochemists. Finally, we focused on studying and revealing the coupled electro‐chemo‐mechanical behavior occurring in the lithium anode, cathode, SSEs, and beyond.
Developing the Healthy Actions and Lifestyles to Avoid Dementia or Hispanos y el ALTo a la Demencia program
Authors: Moukarzel Sara , Zlatar Zvinka Z. , Hartman Sheri J. , Lomas Derek , Feldman Howard H. , Banks Sarah J. ,   HALT‐AD Study Group
Published: March 2024

AbstractINTRODUCTIONWith Alzheimer's disease and related dementias (ADRD) representing an enormous public health challenge, there is a need to support individuals in learning about and addressing their modifiable risk factors (e.g., diet, sleep, and physical activity) to prevent or delay dementia onset. However, there is limited availability for evidence‐informed tools that deliver both quality education and support for positive behavior change such as by increasing self‐efficacy and personalizing goal setting. Tools that address the needs of Latino/a, at higher risk for ADRD, are even more scarce.METHODSWe established a multidisciplinary team to develop the Healthy Actions and Lifestyles to Avoid Dementia or Hispanos y el ALTo a la Demencia (HALT‐AD) program, a bilingual online personalized platform to educate and motivate participants to modify their risk factors for dementia. Grounded in social cognitive theory and following a cultural adaptation framework with guidance from a community advisory board, we developed HALT‐AD iteratively through several cycles of rapid prototype development, user‐centered evaluation through pilot testing and community feedback, and refinement.RESULTSUsing this iterative approach allowed for more than 100 improvements in the content, features, and design of HALT‐AD to improve the program's usability and alignment with the interests and educational/behavior change support needs of its target audience. Illustrative examples of how pilot data and community feedback informed improvements are provided.DISCUSSIONDeveloping HALT‐AD iteratively required learning through trial and error and flexibility in workflows, contrary to traditional program development methods that rely on rigid, pre‐set requirements. In addition to efficacy trials, studies are needed to identify mechanisms for effective behavior change, which might be culturally specific. Flexible and personalized educational offerings are likely to be important in modifying risk trajectories in ADRD.
Recent advances of ring opening of epoxidation of palm oil derived from oleic acid via in situ hydrolysis under moderate temperature
Authors: Yeop Mohamad Zarqani , Azmi Intan Suhada , Rahman Siti Juwairiyah A. , Jalil Mohd. Jumain , Ibrahim Izni Mariah 
Published: March 2024

AbstractEpoxidized oleic acid was considered a more sustainable alternative to traditional plasticizers such as phthalates, which have been linked to potential health and environmental hazards. This study aims to synthesize and characterize the formation of dihydroxystearic acid (DHSA) from the ring opening of epoxidized oleic acid. The optimal reaction parameters to produce DHSA were found using sulfuric acid as catalyst in which the maximum relative conversion was reached up to 86%. The detection of hydroxyl group was using Fourier Transform Infrared Spectroscopy. Then, a mathematical model was developed using MATLAB software, and as a result the kinetic model provided a good description of the reaction process, and it could be used to predict the behavior of the reaction under different conditions. Overall, the optimal reaction conditions and the maximum relative conversion of palm oleic acid to oxirane, are important contributions to the field of green chemistry.
Flavonoids from Alpinia vietnamica, and their cytotoxic, antioxidative, and α‐glucosidase inhibitory activities
Authors: Tra Nguyen Thanh , Hoa Nguyen Thi Thuy , Linh Nguyen Thi Thuy , Ha Nguyen Thi Thu , Cham Ba Thi , Anh Le Thi Tu , Son Ninh The 
Published: March 2024

AbstractPhytochemical research of the 80% EtOH whole plant extract of Alpinia vietnamica H.Ð. Tran, Luu & Skornick resulted in the isolation and structural elucidation of seven compounds 1–7, including two flavones quercetin‐3‐O‐α‐l‐rhamnosyl (1→2)‐α‐l‐rhamnoside (1) and diosmetin (2), three flavanones pinocembrin (3), alpinetin (4) and 5‐O‐methylnaringenin (5), and two chalcones cardamonin (6) and helichrysetin (7). The isolated compounds have shown biological effects at different levels. Two chalcones 6–7 showed cytotoxicity toward four cancer cell lines KB, MCF7, A549, and HepG2, especially compound 7 strongly inhibited the growth of A549 cancerous cells with the IC50 of 6.81 µm. Flavone 1 strongly exhibited antioxidative activity to scavenge DPPH radicals with the IC50 of 51.68 µm. Flavone 2 and flavanone 4 moderately inhibited enzyme α‐glucosidase with the IC50 values of 296.34–324.64 µm.
Electrochemical determination of salbutamol in aqueous solutions with UiO‐66/rGO‐modified electrodes
Authors: Thanh Nhi Le Thi , Hoa Le Thi , Uyen Dam To , Sinh Le Hoang , Nguyen Do Mai , Bach Ta Ngoc , Tam Toan Tran Thanh , Quang Khieu Dinh 
Published: March 2024

AbstractThe synthesis of the UiO‐66/rGO material involved combining UiO‐66 with reduced graphene oxide (rGO). This resulting composite found application in the electrochemical determination of salbutamol (SAL) through modification of a glassy‐carbon electrode (GCE) with UiO‐66/rGO. Differential pulse voltammetry served as the chosen technique, offering a wide linear range spanning 1–160 µm and demonstrating a low limit of detection at 0.84 µm. To ensure the reliability of the electrode, various aspects such as sensitivity, repeatability, reproducibility, and stability were meticulously studied. When applied to the analysis of SAL in swine urine solutions (n = 3), the electrode exhibited good recovery rates. Remarkably, the results obtained through this method correlated well with those acquired using ultra‐high performance liquid chromatography (UPLC).
Principles of Rigorous Development and of Appraisal of ML and AI Methods and Systems
Authors: Aliferis Constantin , Simon Gyorgy 
Published: March 2024

AbstractThe chapter outlines a comprehensive process, governing all steps from analysis and problem domain needs specification, to creation and validation of AI/ML methods that can address them. The stages are explained and grounded using existing methods examples. The process discussed equates to a generalizable Best Practice guideline applicable across all of AI/ML. An equally important use of this Best Practice is as a guide for understanding and evaluating any ML/AI technology under consideration for adoption for a particular problem domain.