bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of high-K dielectric HSS-DMG Junctionless FinFET using hetero GOS for nanoscale application
Authors: Kumar Appikatla Phani , Lorenzo Rohit 
Published: June 2024

Abstract
This article presents a detailed investigation of the High-K dielectric horizontal stack spacer (HSS) dual material gate junction-less FinFET device for analog and RF application using the gate oxide stack (GOS) approach. At first, the impact of the horizontal stack spacer (HSS) with different high-K spacer materials are investigated by placing different dielectric material like HfO2, SiO2, Si3N4, and TiO2 on the horizontal spacer. The simulation results of the device indicate that the High-K dielectric HSS makes the device high stability toward the leakage current and static power dissipation at the sub-nano scale regime. The DC characteristics of the device are also investigated alongside the AC/RF characteristics. The proposed device predominantly improves performance in terms of parameters like subthreshold swing, Ion/Ioff, and DIBL. The proposed device shows a high ON current of 8.56 × 10−5 A μm−1, which is about 15% higher than the existing literature, and the device also makes a notable impact on the leakage current by restricting it to 9.635 × 10−12 A/μm. The simulation of the device is carried out with optimization of the doping to investigate and improve the device’s performance. The device shows an excellent improvement in performance which is highly suitable for future-ready device applications.
Mapping construction sector greenhouse gas emissions: a crucial step in sustainably meeting increasing housing demands
Authors: Yoffe Hatzav , Rankin Keagan H , Bachmann Chris , Posen I Daniel , Saxe Shoshanna 
Published: June 2024

Abstract
This paper examines the tension between needing to build more infrastructure and housing and simultaneously reduce greenhouse gas emissions (GHG) to avoid the most catastrophic impacts of climate change. This study uses an Environmentally Extended Input-Output approach to conduct a high-resolution top-down analysis of Canada’s national construction GHG emissions. Our findings highlight that Canada’s current construction practices cannot accommodate the construction required to restore housing affordability by 2030 without substantial environmental consequences. On a consumption life cycle basis, the construction sector was responsible for approximately 90 Mt CO2e in 2018, equivalent to over 8% of Canada’s total GHG emissions, while delivering less than a third of Canada’s annual housing needs. Residential construction was responsible for the largest share (42%) of total construction emissions. Overall, 84% of emissions are from material manufacturing and 35% of construction emissions are imported, underscoring the need for a comprehensive regulatory framework addressing both domestic and imported emissions. Under current construction practices (i.e. current material use patterns and emissions intensities), meeting Canada’s 2030 housing affordability and climate commitments requires an 83% reduction in GHG emissions per construction product (i.e. per home) compared to the 40% economy-wide reduction promised in Canada’s international reduction commitments. Mitigating the GHG gap between emission caps and housing demand calls for changes in the ratio of housing to other infrastructure (e.g. fewer roads, less fossil fuel infrastructure), new construction approaches (e.g. increasing material efficiency) and/or disproportionally allocating climate budget to construction. The implications of our study extend beyond Canada, offering valuable insights for other growing countries with climate goals. The results emphasize the urgency in considering and establishing sectoral GHG budgets for construction and for transformative changes in the construction sector to meet national GHG emission reduction commitments.
Expanding renewable electricity use in global corporate supply chains
Authors: Sievert Katrin , Song Yi , Chen Yuang , Karplus Valerie J 
Published: June 2024

Abstract
Expanding renewable electricity (RE) use in global corporate supply chains can help to achieve global net-zero greenhouse gas emissions targets by mid-century, but efforts face several challenges. First, corporations and their suppliers may be subject to varying climate policy stringency, leading to a misalignment of incentives to act. Second, measuring true progress is difficult, because counterfactuals are unobserved, and measures of effort vary under policy. Third, relevant policy and broader stakeholder audiences differ in the standards of measurement they recognize. Transparent and broadly accepted, or at least interoperable, standards for assessing effort would help corporations and nations strengthen confidence in corporate claims that RE procurement efforts support international climate goals.
Drivers of agrivoltaic perception in California and North Carolina
Authors: Cuppari Rosa Isabella , Fernandez-Bou Angel Santiago , Characklis Gregory W , Ramirez Marielena , Nocco Mallika A , Abou-Najm Majdi 
Published: June 2024

Abstract
The last decade has seen dramatic growth in solar power. In some regions, the most favorable land for solar panels is farmland, which is often flat and exposed to high levels of irradiance. At the same time, the agricultural sector is faced with growing challenges, notably changing water availability and increasingly frequent extreme weather events. The combination of these trends presents an opportunity for a synergistic relationship between the agriculture and solar sectors: agrivoltaic systems (AVS). In AVS, solar panels are placed above and between crops, such that the same land produces both food and energy. This system has beneficial microclimate impacts, such as reduced evapotranspiration. Yet, despite these benefits there has been limited uptake of AVS. One reason may be hesitation on the part of farmers, whose perceptions of AVS have been explored little. This analysis seeks to address part of this gap by exploring the relationship between farmer perceptions and interest in AVS. A Likert scale survey was designed and distributed to farmers across two large, agriculturally productive states, North Carolina and California. Responses from the 41 participants who fully completed the survey suggest that farmers who perceive AVS as diversifying their income or whose goals include reducing water use are the most interested in installing AVS. Respondents also identified financial viability as a major concern, agreeing that upfront cost is a major barrier to AVS, and markets as the most influential driver of crop decisions. These findings provide insights for policymakers interested in expanding AVS, particularly in response to environmental stressors, such as water scarcity and extreme weather events. They also suggest the aspects of AVS that may be most important to farmers, and most effective in encouraging AVS uptake. This information can support efforts to promote AVS, contributing to sustainable agriculture.
Electricity and electromagnetism
Authors: Kragh Helge 
Published: June 2024

Abstract
From their beginning in the eighteenth century, the electrical sciences have given rise to many new words such as electromagnetism, ion, electron, superconductivity, and transistor. The many-sided history of electricity is followed with an emphasis on neologisms and other linguistic aspects. Moreover, a number of related terms and concepts are investigated from a linguistic point of view, including the theory of relativity and the so-called Weber–Fechner law as manifested in various units and scales (decibel, the pH scale, and the Richter scale). One of the sections is devoted to the terminology of solid-state physics.
An assessment of beliefs about mental health care among community-based adults with severe, untreated alcohol use disorder
Authors: Hutchison Morica , Szafranski Sarah , Titus Caitlin , Abar Beau , Conner Kenneth R , Maisto Stephen , Stecker Tracy 
Published: June 2024

Abstract

Objective
Alcohol use disorder (AUD) is among the most prevalent substance use disorders in the USA. Despite availability of effective interventions, treatment initiation and engagement remain low. Existing interventions target motivation and practical barriers to accessing treatment among individuals established within treatment systems. In contrast, Cognitive Behavioral Therapy for Treatment-Seeking (CBT-TS) aims to elicit and modify treatment-seeking beliefs to increase treatment-seeking behaviors among treatment-naïve samples. We aim to understand which beliefs were endorsed by those who did/did not initiate treatment, including changes in number of drinking days.

Method
We examined treatment seeking beliefs elicited during CBT-TS among community-based adults with moderate–severe AUD with no treatment history. In this study, we discuss which beliefs were modifiable (i.e. those discussed during the intervention among individuals who subsequently attended treatment and may be associated with treatment-seeking behaviors).

Results
Of the 194 participants who received the intervention, 16 categories of beliefs were endorsed. Of the 38 participants (19.6%) who attended treatment, the most frequently endorsed belief was ‘Not wanting specific types of substance use treatment or supports’ (50%), a belief that may inhibit treatment seeking. The idea ‘Treatment is positive’ (47%) was also frequently cited, a belief that may facilitate treatment seeking.

Conclusions
This study describes the beliefs that were more frequently endorsed among adults with moderate–severe, but untreated AUD who reported attending treatment following CBT-TS. Findings point to the potential of discussing and modifying treatment-seeking beliefs among treatment-naïve adults with severe AUD to increase treatment-seeking behaviors.
On the agent-relativity of ‘ought’
Authors: Lee Junhyo 
Published: June 2024

Abstract
In the standard theory of deontic modals, ‘ought’ is understood as expressing a propositional operator. However, this view has been called into question by Almotahari and Rabern’s puzzle about deontic ‘ought’, according to which the ethical principle that one ought to be wronged by another person rather than wrong them is intuitively coherent but the standard theory makes it incoherent. In this paper, I take up Almotahari and Rabern’s challenge and offer a refinement of the standard theory to handle the puzzle. I propose that ‘ought’ is evaluated relative to contextual parameters (e.g. Kratzer’s conversational backgrounds, Finlay and Snedegar’s alternative sets) and those contextual parameters are sensitive to agents as well as possible worlds.
Development of a crosswalk to convert French PCS2003 into international ISCO88 occupational classifications. Application to the Occupational Asthma-specific Job-Exposure Matrix (OAsJEM)
Authors: Pilorget Corinne , Dananché Brigitte , Garras Loïc , Orsi Florence , Sit Guillaume , Ribet Céline , Houot Marie-Tülin , Goldberg Marcel , Dumas Orianne , Le Moual Nicole 
Published: June 2024

Abstract

Introduction
The problem of transcoding is recurrent when researchers wish to link occupational data from cohorts to Job-Exposure Matrices (JEMs) which were not set up in the same classifications. The Occupational Asthma-specific JEM (OAsJEM) is a JEM developed for assessing exposure to agents known at risk for asthma for jobs coded with ISCO88 occupation classification. To apply the OAsJEM in the CONSTANCES cohort, in which jobs and industries were coded with French PCS2003 and NAF2008 classifications respectively, we developed a crosswalk to convert jobs from PCS2003 into ISCO88 classification.

Methods
This work was carried out by 2 skilled coders and 1 novice coder who have worked independently by using different tools and transcoding strategies defined a priori. Consensus meetings were organized with skilled coders to define the final crosswalk. This work was elaborated in 2 steps: (i) for 38 ISCO88 codes classified as potentially exposed to cleaning and disinfection products by the OAsJEM, and (ii) for all jobs from the ISCO88 classification. A comparison between the 3 initial coder’s crosswalk proposals and the final crosswalk was made for the 38 ISCO codes in step (i).

Results
The final crosswalk provided 998 matches between the 482 4-digit PCS2003 codes, 308 4-digit ISCO88 codes, and 31 3-digit ISCO88 codes. Information regarding the NAF2008 industry classification was also used in some cases to improve the final crosswalk. For the selected 38 ISCO88 codes, the final crosswalk provided 110 combinations, but the number of proposed ISCO88–PCS2003 couples by each of the 3 coders varied greatly from 68 to 153. In addition, an important variability between the 3 coders were observed among the number of common combinations between the initial coder’s proposals and the final crosswalk (from 47% to 78%).

Discussion
We have developed a crosswalk specifically for an application of the OAsJEM in population-based surveys using the PCS2003 occupation classification. The development of this crosswalk is of great interest for the use of OAsJEM on the data of the CONSTANCES cohort and on any other survey with occupational data coded according to the French classifications. This OAsJEM crosswalk could be used by other teams to evaluate occupational exposures known to be at risk of asthma from occupational calendars coded with French classifications.
Prediction of disease-free survival for precision medicine using cooperative learning on multi-omic data
Authors: Hahn Georg , Prokopenko Dmitry , Hecker Julian , Lutz Sharon M , Mullin Kristina , Sejour Leinal , Hide Winston , Vlachos Ioannis , DeSantis Stacia , Tanzi Rudolph E , Lange Christoph 
Published: June 2024

Abstract
In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the classical epidemiological predictor variables, data from multiple (omic) platforms are increasingly available. To integrate this wealth of information, we propose new methodology to combine both cooperative learning, a recent approach to leverage the predictive power of several datasets, and polygenic hazard score models. Polygenic hazard score models provide a practitioner with a more differentiated view of the predicted disease-free survival than the one given by merely a point estimate, for instance computed with a polygenic risk score. Our aim is to leverage the advantages of cooperative learning for the computation of polygenic hazard score models via Cox’s proportional hazard model, thereby improving the prediction of the disease-free survival. In our experimental study, we apply our methodology to forecast the disease-free survival for Alzheimer’s disease (AD) using three layers of data. One layer contains epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status and 10 leading principal components. Another layer contains selected genomic loci, and the last layer contains methylation data for selected CpG sites. We demonstrate that the survival curves computed via cooperative learning yield an AUC of around $0.7$, above the state-of-the-art performance of its competitors. Importantly, the proposed methodology returns (1) a linear score that can be easily interpreted (in contrast to machine learning approaches), and (2) a weighting of the predictive power of the involved data layers, allowing for an assessment of the importance of each omic (or other) platform. Similarly to polygenic hazard score models, our methodology also allows one to compute individual survival curves for each patient.
CLEAPA: a framework for exploring the conformational landscape of cryo-EM using energy-aware pathfinding algorithm
Authors: Lin Teng-Yu , Chung Szu-Chi 
Published: June 2024

Abstract

Motivation
Cryo-electron microscopy (cryo-EM) is a powerful technique for studying macromolecules and holds the potential for identifying kinetically preferred transition sequences between conformational states. Typically, these sequences are explored within two-dimensional energy landscapes. However, due to the complexity of biomolecules, representing conformational changes in two dimensions can be challenging. Recent advancements in reconstruction models have successfully extracted structural heterogeneity from cryo-EM images using higher-dimension latent space. Nonetheless, creating high-dimensional conformational landscapes in the latent space and then searching for preferred paths continues to be a formidable task.

Results
This study introduces an innovative framework for identifying preferred trajectories within high-dimensional conformational landscapes. Our method encompasses the search for the minimum energy path in the graph, where edge weights are determined based on the energy estimation at each node using local density. The effectiveness of this approach is demonstrated by identifying accurate transition states in both synthetic and real-world datasets featuring continuous conformational changes.

Availability and implementation
The CLEAPA package is available at https://github.com/tengyulin/energy_aware_pathfinding/.
Drug–target interaction predictions with multi-view similarity network fusion strategy and deep interactive attention mechanism
Authors: Song Wei , Xu Lewen , Han Chenguang , Tian Zhen , Zou Quan 
Published: June 2024

Abstract

Motivation
Accurately identifying the drug–target interactions (DTIs) is one of the crucial steps in the drug discovery and drug repositioning process. Currently, many computational-based models have already been proposed for DTI prediction and achieved some significant improvement. However, these approaches pay little attention to fuse the multi-view similarity networks related to drugs and targets in an appropriate way. Besides, how to fully incorporate the known interaction relationships to accurately represent drugs and targets is not well investigated. Therefore, there is still a need to improve the accuracy of DTI prediction models.

Results
In this study, we propose a novel approach that employs Multi-view similarity network fusion strategy and deep Interactive attention mechanism to predict Drug–Target Interactions (MIDTI). First, MIDTI constructs multi-view similarity networks of drugs and targets with their diverse information and integrates these similarity networks effectively in an unsupervised manner. Then, MIDTI obtains the embeddings of drugs and targets from multi-type networks simultaneously. After that, MIDTI adopts the deep interactive attention mechanism to further learn their discriminative embeddings comprehensively with the known DTI relationships. Finally, we feed the learned representations of drugs and targets to the multilayer perceptron model and predict the underlying interactions. Extensive results indicate that MIDTI significantly outperforms other baseline methods on the DTI prediction task. The results of the ablation experiments also confirm the effectiveness of the attention mechanism in the multi-view similarity network fusion strategy and the deep interactive attention mechanism.

Availability and implementation
https://github.com/XuLew/MIDTI.
Bigtools: a high-performance BigWig and BigBed library in Rust
Authors: Huey Jack D , Abdennur Nezar 
Published: June 2024

Abstract

Motivation
The BigWig and BigBed file formats were originally designed for the visualization of next-generation sequencing data through a genome browser. Due to their versatility, these formats have long since become ubiquitous for the storage of processed sequencing data and regularly serve as the basis for downstream data analysis. As the number and size of sequencing experiments continues to accelerate, there is an increasing demand to efficiently generate and query BigWig and BigBed files in a scalable and robust manner, and to efficiently integrate these functionalities into data analysis environments and third-party applications.

Results
Here, we present Bigtools, a feature-complete, high-performance, and integrable software library for generating and querying both BigWig and BigBed files. Bigtools is written in the Rust programming language and includes a flexible suite of command line tools as well as bindings to Python.

Availability and implementation
Bigtools is cross-platform and released under the MIT license. It is distributed on Crates.io, Bioconda, and the Python Package Index, and the source code is available at https://github.com/jackh726/bigtools.
Evidence for metabolism of creatine by the conceptus, placenta, and uterus for production of adenosine triphosphate during conceptus development in pigs
Authors: Lefevre Carli M , Cain Joe W , Kramer Avery C , Seo Heewon , Lopez Arianna N , Sah Nirvay , Wu Guoyao , Bazer Fuller W , Johnson Gregory A 
Published: June 2024

Abstract
In pigs, the majority of embryonic mortality occurs when free-floating conceptuses (embryos/fetuses and associated placental membranes) elongate, and the uterine–placental interface undergoes folding and develops areolae. Both periods involve proliferation, migration, and changes in morphology of cells that require adenosine triphosphate (ATP). We hypothesize that insufficient ATP in conceptus and uterine tissues contributes to conceptus loss in pigs. Creatine is stored in cells as phosphocreatine for ATP regeneration through the creatine–creatine kinase– phosphocreatine pathway. However, the expression of components of this pathway in pigs has not been examined throughout gestation. Results of qPCR analyses indicated increases in AGAT, GAMT, CKM, CKB, and SLC6A8 mRNAs in elongating porcine conceptuses, and immunofluorescence microscopy localized guanidinoacetate N-methyltransferase, creatine kinase M, and creatine kinase B proteins to the trophectoderm of elongating conceptuses, to the columnar chorionic epithelial cells at the bottom of chorioallantoic troughs, and to endometrial luminal epithelium at the tops of the endometrial ridges of uterine–placental folds on Days 40, 60, and 90 of gestation. Guanidinoacetate N-methyltransferase protein is expressed in endometrial luminal epithelium at the uterine–placental interface, but immunostaining is more intense in luminal epithelium at the bottoms of the endometrial ridges. Results of this study indicate that key elements of the pathway for creatine metabolism are expressed in cells of the conceptus, placenta, and uterus for potential production of ATP during two timepoints in pregnancy with a high demand for energy; elongation of the conceptus for implantation and development of uterine–placental folding during placentation.
Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes
Authors: Liu Xueqing , Qian Tianchen , Bell Lauren , Chakraborty Bibhas 
Published: June 2024

ABSTRACT
In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the “gold-standard” methodology for developing such interventions. Analyzing data from these trials provides insights into the efficacy of interventions and the potential moderation by specific covariates. The “causal excursion effect,” a novel class of causal estimand, addresses these inquiries. Yet, existing research mainly focuses on continuous or binary data, leaving count data largely unexplored. The current work is motivated by the Drink Less micro-randomized trial from the UK, which focuses on a zero-inflated proximal outcome, i.e., the number of screen views in the subsequent hour following the intervention decision point. To be specific, we revisit the concept of causal excursion effect, specifically for zero-inflated count outcomes, and introduce novel estimation approaches that incorporate nonparametric techniques. Bidirectional asymptotics are established for the proposed estimators. Simulation studies are conducted to evaluate the performance of the proposed methods. As an illustration, we also implement these methods to the Drink Less trial data.