bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coupled model intercomparison project phase 6 (CMIP6) high resolution model intercomparison project (HighResMIP) bias in extreme rainfall drives underestimation of amazonian precipitation
Authors: Negron-Juarez Robinson , Wehner Michael , Silva Dias Maria Assunção F , Ullrich Paul , Chambers Jeffrey Q , Riley William J 
Published: August 2024

Abstract
Extreme rainfall events drive the amount and spatial distribution of rainfall in the Amazon and are a key driver of forest dynamics across the basin. This study investigates how the 3-hourly predictions in the High Resolution Model Intercomparison Project (HighResMIP, a component of the recent Coupled Model Intercomparison Project, CMIP6) represent extreme rainfall events at annual, seasonal, and sub-daily time scales. TRMM 3B42 (Tropical Rainfall Measuring Mission) 3 h data were used as observations. Our results showed that eleven out of seventeen HighResMIP models showed the observed association between rainfall and number of extreme events at the annual and seasonal scales. Two models captured the spatial pattern of number of extreme events at the seasonal and annual scales better (higher correlation) than the other models. None of the models captured the sub-daily timing of extreme rainfall, though some reproduced daily totals. Our results suggest that higher model resolution is a crucial factor for capturing extreme rainfall events in the Amazon, but it might not be the sole factor. Improving the representation of Amazon extreme rainfall events in HighResMIP models can help reduce model rainfall biases and uncertainties and enable more reliable assessments of the water cycle and forest dynamics in the Amazon.
Hybrid energy storage systems for fast-developing renewable energy plants
Authors: Zhao Junjie , Wang Fan , Ruan Qidong , Wu Yong , Zhang Bing , Lu Yingying 
Published: August 2024

Abstract
To achieve zero carbon emissions, renewable energy sources are highly promising alternatives to fossil fuels. However, the intermittency of renewable energy sources hinders the balancing of power grid loads. Because energy storage systems (ESSs) play a critical role in boosting the efficiency of renewable energy sources and economizing energy generation, different ESSs and their applications in various environments must be comprehensively investigated. With sustained growth in the global demand for ESSs, reliance on a single technology may not comprehensively fulfill the anticipated requirements for the ESS cycling life, efficiency, cost, and energy/power densities. Hence, hybrid ESSs (HESSs), combining two/multiple ESSs, offer a promising solution to overcome the constraints of a single ESS and optimize energy management and utilization. Therefore, this review extensively and comprehensively describes ESSs, including their classifications, mechanisms, strengths, and weaknesses, and introduces several typical HESS energy management strategies and application domains.
Compact narrow slot antenna with stable radiation pattern and wide bandwidth
Authors: Ashvanth Balu 
Published: August 2024

Abstract
One of the most crucial parameters for any antenna is bandwidth. Over the whole extended bandwidth, the antenna achieves a high gain of 5dBi and a steady bidirectional radiation pattern. A novel design concept for increasing bandwidth and maintaining a consistent radiation pattern has been proposed for the radiated fields of a slot antenna. First, the radiated fields of the standard slot antenna are examined theoretically using characteristic modes (CMs). Its three CMs vibrate at 2.45, 4.78, and 7.17 GHz, respectively, according to the results. CM1 and CM3 both continue to emit radiation in both directions, but CM2 generates a radiation null in the broadside direction. After that, the linear slot is appropriately folded to change CM2’s non-bidirectional pattern into a bidirectional one, allowing for the broad bandwidth use of the neighbouring CM1 and CM2. The narrow slot is then used to create the stepped scheme, which reallocates these dual modes in close proximity to one another. By using these designs, the antenna’s radiation pattern consistency and small size of 0.022λo can be preserved, but its impedance bandwidth can be significantly expanded. After that, the proposed antenna is constructed and assessed. Measurements show that the antenna has a broad bandwidth (|S11|<−10 dB) of around 35.14%, covering the frequency range of 3.3 to 4.6 GHz.
Single gate heterostructure dopingless TFET: a comprehensive sensitivity investigation with exposure to various chemical analytes
Authors: Panda Shwetapadma , Dash Sidhartha 
Published: August 2024

Abstract
This study proposes a new chemical sensor designed using a single gate heterostructure dopingless tunnel field effect transistor (SG-HS-DLT). Combining Si0.6Ge0.4 in the source and HfO2 as the gate dielectric improves the sensor’s drain current sensitivity. Many chemical analytes, including hexane (C6H14), methanol (CH3OH), isopropanol (Iso-C3H7OH), dichloromethane (CH2Cl2), and chloroform (CHCl3) have been considered during the investigation. The conducting polymer is used as the gate metal due to its compatibility with the electronic chemical sensor. Modifying the gate work function with exposure to chemical substances is employed to determine the sensitivity of the reported chemical sensor. The electrical performance of the sensor is examined using transfer characteristics, switching ratio, average SS, BTBT rate, threshold voltage, electron concentration, energy band, and potential. Correspondingly, the sensitivity investigation comprises drain current sensitivity (SDrain), current ratio sensitivity (SR), average SS sensitivity (SAvgSS), and threshold voltage sensitivity (SVT). Further, the sensitivity analysis is extended for various temperatures and mole fractions (x). The SG-HS-DLT chemical sensor displays a higher value of SDrain of 3.64 × 105, SAvg.SS of 0.69444 for CHCl3 at room temperature. This article extensively uses the Silvaco TCAD simulation software to investigate the proposed chemical sensor.
Strategic DG placement and sizing in developing nations' power systems using ISNT and modified forward-backward sweep
Authors: Somefun Tobiloba , Abdulkareem Ademola , Popoola Olawale , Somefun Comfort , Ajewole Titus 
Published: August 2024

Abstract
The power sector in many developing nations faces challenges in meeting consumers’ demands for a reliable electricity supply due to increased load demand, primarily driven by population growth. Urban areas receive 24 h power, while extensive losses within the system limit coverage. Setting up centralised stations offers a temporary solution, but the capacity of the ageing transmission lines is uncertain. This study proposes integrating distributed generators (DG) into the power system, using Inherent Structural Network Topology (ISNT) for DG siting and a modified Forward-Backward Sweep model for sizing. Voltage Stability Index (VPI) assesses network stability. The model considers voltage profile and line losses, optimizing DG sites and sizes. Results demonstrate the model’s efficacy, offering insights for optimal DG planning to minimize losses and enhance voltage profiles. The study informs power system engineers for future planning, aiding decisions on DG location and size, potentially reducing line losses and improving voltage profiles, thus assisting in network upgrades or expansions.
Optimization of EDM input variables for machining of novel Al7010/B4C/BN hybrid metal matrix nanocomposite using multi objective grey relational analysis
Authors: Dirisenapu Gopichand , Salavaravu Laxmanaraju , Bandi Rajyalakshmi 
Published: August 2024

Abstract
In this research, the examination on the influence of EDM pulse variables during machining of Al7010/B4C/BN hybrid metal matrix nanocomposites (HMMNCs) manufactured by using ultrasonic assisted stir casting (UASC) route. The optimum input factors of die sinking EDM like pulse on time (Pon), discharge current (DC), gap voltage (GV) and pulse off time (Poff) on performance factors like tool wear rate (TWR), material removal rate (MRR), and surface roughness (SR) were studied. The Taguchi experimental design of L16 orthogonal array (OA) was selected for conducting experiments. The ANOVA route was utilized to obtain the % contribution of pulse parameters on response factors. The multi objective Grey relational analysis (GRA) was used for determining optimum machining condition. The results indicated that discharge current was more effects on output factors like SR, TWR and MRR followed by other parameters and that DC is the best substantial factor for multiple objective responses. The results exposed that the optimum EDM process factors condition is A1B1C1D3. The outcomes were further calculated by employing confirmatory experiment. Scanning electron microscope (SEM) was conducted to observe the surface properties of a specimen that underwent EDM. In the EDMed surface a complex combination surrounded by tiny and big melt droplets, various-sized fissures, microcracks, and void markings were presented. Moreover, observed the effects on the surface, such as the formation of a recast layer.
Active causal learning for decoding chemical complexities with targeted interventions
Authors: R Fox Zachary , Ghosh Ayana 
Published: August 2024

Abstract
Predicting and enhancing inherent properties based on molecular structures is paramount to design tasks in medicine, materials science, and environmental management. Most of the current machine learning and deep learning approaches have become standard for predictions, but they face challenges when applied across different datasets due to reliance on correlations between molecular representation and target properties. These approaches typically depend on large datasets to capture the diversity within the chemical space, facilitating a more accurate approximation, interpolation, or extrapolation of the chemical behavior of molecules. In our research, we introduce an active learning approach that discerns underlying cause-effect relationships through strategic sampling with the use of a graph loss function. This method identifies the smallest subset of the dataset capable of encoding the most information representative of a much larger chemical space. The identified causal relations are then leveraged to conduct systematic interventions, optimizing the design task within a chemical space that the models have not encountered previously. While our implementation focused on the QM9 quantum-chemical dataset for a specific design task—finding molecules with a large dipole moment—our active causal learning approach, driven by intelligent sampling and interventions, holds potential for broader applications in molecular, materials design and discovery.
Explaining the sharp decline in birth rates in Canada and the United States in 2020
Authors: Sawant Amit N , Stensrud Mats J 
Published: August 2024

Abstract
Birth rates in Canada and the United States declined sharply in March 2020 and deviated from historical trends. This decline was absent in similarly developed European countries. We argue that the selective decline was driven by incoming individuals, who would have traveled from abroad and given birth in Canada and the United States had there been no travel restrictions during the COVID-19 pandemic. Furthermore, by leveraging data from periods before and during the COVID-19 travel restrictions, we quantified the extent of births by incoming individuals. In an interrupted time series analysis, the expected number of such births in Canada was 970 per month (95% CI, 710-1200), which is 3.2% of all births in the country. The corresponding estimate for the United States was 6700 per month (95% CI, 3400-10 000), which is 2.2% of all births. A secondary difference-in-differences analysis gave similar estimates, at 2.8% and 3.4% for Canada and the United States, respectively. Our study reveals the extent of births by recent international arrivals, which hitherto has been unknown and infeasible to study.
Generating CRISPR-edited clonal lines of cultured Drosophila S2 cells
Authors: Ryniawec John M , Amoiroglou Anastasia , Rogers Gregory C 
Published: August 2024

Abstract
CRISPR/Cas9 genome editing is a pervasive research tool due to its relative ease of use. However, some systems are not amenable to generating edited clones due to genomic complexity and/or difficulty in establishing clonal lines. For example, Drosophila Schneider 2 (S2) cells possess a segmental aneuploid genome and are challenging to single-cell select. Here, we describe a streamlined CRISPR/Cas9 methodology for knock-in and knock-out experiments in S2 cells, whereby an antibiotic resistance gene is inserted in-frame with the coding region of a gene-of-interest. By using selectable markers, we have improved the ease and efficiency for the positive selection of null cells using antibiotic selection in feeder layers followed by cell expansion to generate clonal lines. Using this method, we generated the first acentrosomal S2 cell lines by knocking-out centriole genes Polo-like Kinase 4/Plk4 or Ana2 as proof of concept. These strategies for generating gene-edited clonal lines will add to the collection of CRISPR tools available for cultured Drosophila cells by making CRISPR more practical and therefore improving gene function studies.
Association of Weather Variables With Pathogens Contributing to Conjunctivitis Worldwide
Authors: Yan Daisy , Prajna N Venkatesh , Lalitha Prajna , Sansanayudh Wiwan , Satitpitakul Vannarut , Laovirojjanakul Wipada , Chaudhary Meenu , Bountogo Mamadou , Sie Ali , Coulibaly Boubacar , Amza Abdou , Nassirou Beido , Almou Ibrahim , Tran Huy , Tran Yen , Tsui Edmund , Onclinx Tania , Sella Ruti , Goren Lee , McClean Esmeralda , Tham Vivien , Chen Cindi , Ouimette Kevin , Zhong Lina , Liu YuHeng , Yu Danny , Abraham Thomas , Lebas Elodie , Arnold Benjamin F , McLeod Stephen D , Deiner Michael S , Porco Travis C , Seitzman Gerami D , Lietman Thomas M , Shantha Jessica , Hinterwirth Armin , Doan Thuy 
Published: August 2024

Abstract

Purpose
To identify weather variables associated with pathogens contributing to infectious conjunctivitis globally.

Methods
Sample collection and pathogen identification from patients with acute infectious conjunctivitis was performed from 2017 to 2023. We linked pathogens identified from 13 sites across 8 countries with publicly available weather data by geographic coordinates. Mixed effects logistic regression analysis was performed to estimate the associations between temperature, precipitation, and relative humidity exposures, and the prevalence of infection types (RNA virus, DNA virus, bacteria, and fungus).

Results
In total, 498 cases from the United States, India, Nepal, Thailand, Burkina Faso, Niger, Vietnam, and Israel were included in the analysis. The 8-day average precipitation (mm) was associated with increased odds of RNA virus infection (odds ratio [OR] = 1.47, 95% confidence interval [CI]: 1.12 to 1.93, P = .01) and decreased odds of DNA infection (OR = 0.62, 95% CI: .46 to .82, P &lt; .001). Relative humidity (%) was associated with increased odds of RNA virus infections (OR = 2.64, 95% CI: 1.51 to 4.61, P &lt; .001), and fungal infections (OR = 2.35, 95% CI: 1.19 to 4.66, P = .01), but decreased odds of DNA virus (OR = 0.58, 95% CI: .37 to .90, P = .02) and bacterial infections (OR = 0.42, 95% CI: .25 to .71, P &lt; .001). Temperature (°C) was not associated with ocular infections for any pathogen type.

Conclusions
This study suggests that weather factors affect pathogens differently. Particularly, humidity and precipitation were predictors for pathogens contributing to conjunctivitis worldwide. Additional work is needed to clarify the effects of shifts in weather and environmental factors on ocular infectious diseases.
Prediction of presence and severity of metabolic syndrome using regional body volumes measured by a multisensor white-light 3D scanner and validation using a mobile technology
Authors: Medina Inojosa Betsy J , Somers Virend K , Lara-Breitinger Kyla , Johnson Lynne A , Medina-Inojosa Jose R , Lopez-Jimenez Francisco 
Published: August 2024

Abstract

Aims
To test whether an index based on the combination of demographics and body volumes obtained with a multisensor 3D body volume (3D-BV) scanner and biplane imaging using a mobile application (myBVI®) will reliably predict the severity and presence of metabolic syndrome (MS).

Methods and results
We enrolled 1280 consecutive subjects who completed study protocol measurements, including 3D-BV and myBVI®. Body volumes and demographics were screened using the least absolute shrinkage and selection operator to select features associated with an MS severity score and prevalence. We randomly selected 80% of the subjects to train the models, and performance was assessed in 20% of the remaining observations and externally validated on 133 volunteers who prospectively underwent myBVI® measurements. The mean ± SD age was 43.7 ± 12.2 years, 63.7% were women, body mass index (BMI) was 28.2 ± 6.2 kg/m2, and 30.2% had MS and an MS severity z-score of −0.2 ± 0.9. Features β coefficients equal to zero were removed from the model, and 14 were included in the final model and used to calculate the body volume index (BVI), demonstrating an area under the receiving operating curve (AUC) of 0.83 in the validation set. The myBVI® cohort had a mean age of 33 ± 10.3 years, 61% of whom were women, 10.5% MS, an average MS severity z-score of −0.8, and an AUC of 0.88.

Conclusion
The described BVI model was associated with an increased severity and prevalence of MS compared with BMI and waist-to-hip ratio. Validation of the BVI had excellent performance when using myBVI®. This model could serve as a powerful screening tool for identifying MS.
Over- and underreporting of prices: most hospitals are not compliant with the Hospital Price Transparency Rule
Authors: Mead Mitchell , Ibrahim Andrew M 
Published: August 2024

Abstract
Concern has been raised about the effectiveness of the Hospital Price Transparency Rule to facilitate a clear understanding of health care prices due to poor reporting by hospitals. However, the relationship between what services the hospital provides and what prices they report is not clear. We assessed reported prices in the Turquoise Health database and compared them at the hospital level with the CMS Provider of Services File to identify if a shoppable service was provided at a hospital. We found significant mismatch between the hospital prices being reported and the services being provided. For example, 56% of hospitals providing at least 1 shoppable service that requires public price reporting did not report any prices. Of hospitals reporting prices, most hospitals (66%) reported prices for only a portion of the services they provide. In addition, 12% of hospitals reported prices for services they do not provide. Only 6% of hospitals had complete concordance with price reporting and services they actually provide. Current compliance enforcement and penalties do not appear to be adequate to achieve the goals of the Hospital Price Transparency Rule.
Dissociable Roles of the mPFC-to-VTA Pathway in the Control of Impulsive Action and Risk-Related Decision-Making in Roman High- and Low-Avoidance Rats
Authors: Urueña-Méndez Ginna , Arrondeau Chloé , Marchessaux Florian , Goutaudier Raphaël , Ginovart Nathalie 
Published: August 2024

Abstract

Background
Impulsive action and risk-related decision-making (RDM) are associated with various psychiatric disorders, including drug abuse. Both behavioral traits have also been linked to reduced frontocortical activity and alterations in dopamine function in the ventral tegmental area (VTA). However, despite direct projections from the medial prefrontal cortex (mPFC) to the VTA, the specific role of the mPFC-to-VTA pathway in controlling impulsive action and RDM remains unexplored.

Methods
We used positron emission tomography with [18F]-fluorodeoxyglucose to evaluate brain metabolic activity in Roman high- (RHA) and low-avoidance (RLA) rats, which exhibit innate differences in impulsive action and RDM. Notably, we used a viral-based double dissociation chemogenetic strategy to isolate, for the first time to our knowledge, the role of the mPFC-to-VTA pathway in controlling these behaviors. We selectively activated the mPFC-to-VTA pathway in RHA rats and inhibited it in RLA rats, assessing the effects on impulsive action and RDM in the rat gambling task.

Results
Our results showed that RHA rats displayed higher impulsive action, less optimal decision-making, and lower cortical activity than RLA rats at baseline. Chemogenetic activation of the mPFC-to-VTA pathway reduced impulsive action in RHA rats, whereas chemogenetic inhibition had the opposite effect in RLA rats. However, these manipulations did not affect RDM. Thus, by specifically targeting the mPFC-to-VTA pathway in a phenotype-dependent way, we reverted innate patterns of impulsive action but not RDM.

Conclusion
Our findings suggest a dissociable role of the mPFC-to-VTA pathway in impulsive action and RDM, highlighting its potential as a target for investigating impulsivity-related disorders.
Mass, momentum and energy preserving FEEC and broken-FEEC schemes for the incompressible Navier–Stokes equations
Authors: Carlier Valentin , Campos Pinto Martin , Fambri Francesco 
Published: August 2024

Abstract
In this article we propose two finite-element schemes for the Navier–Stokes equations, based on a reformulation that involves differential operators from the de Rham sequence and an advection operator with explicit skew-symmetry in weak form. Our first scheme is obtained by discretizing this formulation with conforming FEEC (Finite Element Exterior Calculus) spaces: it preserves the point-wise divergence free constraint of the velocity, its total momentum and its energy, in addition to being pressure robust. Following the broken-FEEC approach, our second scheme uses fully discontinuous spaces and local conforming projections to define the discrete differential operators. It preserves the same invariants up to a dissipation of energy to stabilize numerical discontinuities. For both schemes we use a middle point time discretization that preserve these invariants at the fully discrete level and we analyze its well-posedness in terms of a CFL condition. While our theoretical results hold for general finite elements preserving the de Rham structure, we consider one application to tensor-product spline spaces. Specifically, we conduct several numerical test cases to verify the high order accuracy of the resulting numerical methods, as well as their ability to handle general boundary conditions.