bluuebunny/crossref_metadata_2025_split huggingface dataset:
Complexities of urban impacts on long-term seasonal trends in a mid-sized arid city
Authors: Chen Jingyi , Qian Yun , Chakraborty T C , Yang Zhao 
Published: February 2024

Abstract
The variability of surface air temperature is of great importance for both society and the environment, is impacted by global warming and local-scale changes. In the arid eastern part of Washington state of USA, substantial urbanization has transformed the Tri-cities into the state’s third-largest urban cluster. This study utilizes a combination of in situ observations and reanalysis datasets to investigate the influence of land use changes on the region’s 2-meter temperature, revealing local effects that compensate for the background global warming. Within the urban fabric, distinct microclimates have emerged due to varying land use, establishing unique relationships between greenness and temperature alterations caused by land use transitions. Notably, our findings demonstrate that the observed compensating signal in the temperature of farmland locations is primarily attributed to local vegetation increases. Through these observations, this research highlights the urban impacts on local climate, offering valuable insights into the complexities surrounding land use and its consequences on the environment.
Spectro-angular analysis of roadside-integrated bifacial solar power systems with reflecting sound barriers
Authors: Bundo Silvi , Pal Shweta , Ernst Marco , Saive Rebecca 
Published: February 2024

Abstract
Bifacial photovoltaic modules along highways provide energy supply and act as sound barriers simultaneously. This study examines the impact on energy production when incorporating sound barriers with varying light reflection properties into this integrated solar infrastructure along roadways. Specifically, we use advanced computational simulations to analyze the effects of integrating black, ideal specular, and ideal diffuse (Lambertian) reflectors into an existing highway solar power plant located in the Netherlands. Our analysis combines realistic spectro-angular irradiance data as input with our in-house reverse ray tracing software. Our calculations show that for an east-west facing system, an ideal diffuse reflector increases the annual yield by 70%, while a specular reflector decreases the yield due to shading. Most notably, the diffuse reflector doubles the energy yield during winter months, thereby offering a pathway to decrease the seasonal energy demand and supply gap.
An application of Gorilla troops optimizer in solving the problem of economic load dispatch considering valve point loading effect
Authors: Wadood Abdul , Ghani Abdul 
Published: February 2024

Abstract
Economic load dispatch (ELD) is one of the fundamental and important optimization problems in an electrical power system. The goal of the ELD problem is to minimize the overall cost of fuel used by generators while satisfying the different constraints like power balance limitations, operational capacity limits, ramp-rate limits, and prohibited operating zones and valve point loading effect (VPLE). The paper introduces a novel optimization technique, termed Gorilla Troop Optimization (GTO), inspired by the mimic’s behavior of gorilla troops, for solving the Economic Load Dispatch (ELD) Problem. The ELD Problem is assessed both with and without the valve-point effect, considering best, average, and worst fuel costs in dollars per hour ($/hr). The proposed GTO is applied to four different case studies to find the best global solution. The effectiveness of the GTO is evaluated using four distinct IEEE unit systems, including the IEEE 3-unit, 6-unit, 10-unit, and 40-unit test systems. From the simulation results, it has been realized that GTO show superior results as compared to other algorithms in terms of the total fuel cost minimization, convergence speed, and computation time to achieve the global optimal solution in all the case studies.
Ethnic politics and party realignment in African constitutional referendums: Understanding Kenya’s ‘industry of insults’
Authors: Harris Kirk A 
Published: February 2024

Abstract
Kenya’s constitutional referendums in 2005 and 2010 stand out for their continuity with the national elections that followed both polls. During campaigns for and against the draft constitutions, politicians attempted to leverage their popularity amongst co-ethnics to signal their viability as coalition partners or ‘formateurs’ in subsequent general elections: rather than nuanced debates on constitutional issues, the campaigns became personal contests that one observer dubbed an ‘industry of insults’. A decade later, this process was repeated as the country’s political class considered further revisions to the constitution. Kenya’s referendum campaigns thus reflect a layer of strategic behaviour that has not been recognized in much of the contemporary literature on democratization and constitutional change in Africa. While the substance of the country’s constitution matters to Kenyan elites, referendum campaigns have added value to leaders independently of the outcomes of the polls themselves. The prominence of ethnicity as an organizing feature in Kenyan politics combined with high levels of party volatility produces an environment in which referendum campaigns serve as opportunities for Kenyan politicians to renegotiate political coalitions and realign party politics in between election cycles. In this way, the country’s referendum politics are a distinct byproduct of its historical and political circumstances.
An introduction to bayesian spatial smoothing methods for disease mapping: modeling county firearm suicide mortality rates
Authors: Gause Emma L , Schumacher Austin E , Ellyson Alice M , Withers Suzanne D , Mayer Jonathan D , Rowhani-Rahbar Ali 
Published: February 2024

Abstract
This article introduces bayesian spatial smoothing models for disease mapping—a specific application of small area estimation where the full universe of data is known—to a wider audience of public health professionals using firearm suicide as a motivating example. Besag, York, and Mollié (BYM) Poisson spatial and space–time smoothing models were fitted to firearm suicide counts for the years 2014-2018. County raw death rates in 2018 ranged from 0 to 24.81 deaths per 10 000 people. However, the highest mortality rate was highly unstable, based on only 2 deaths in a population of approximately 800, and 80.5% of contiguous US counties experienced fewer than 10 firearm suicide deaths and were thus suppressed. Spatially smoothed county firearm suicide mortality estimates ranged from 0.06 to 4.05 deaths per 10 000 people and could be reported for all counties. The space–time smoothing model produced similar estimates with narrower credible intervals as it allowed counties to gain precision from adjacent neighbors and their own counts in adjacent years. bayesian spatial smoothing methods are a useful tool for evaluating spatial health disparities in small geographies where small numbers can result in highly variable rate estimates, and new estimation techniques in R software have made fitting these models more accessible to researchers.
Understanding racial/ethnic disparities in COVID-19 mortality using a novel metric: COVID excess mortality percentage
Authors: Yuan Andy Ye , Atanasov Vladimir , Barreto Natalia , Franchi Lorenzo , Whittle Jeff , Weston Benjamin , Meurer John , Luo Qian (Eric) , Black Bernard 
Published: February 2024

Abstract
Prior research on racial/ethnic disparities in COVID-19 mortality has often not considered to what extent they reflect COVID-19–specific factors, versus preexisting health differences. This study examines how racial/ethnic disparities in COVID-19 mortality vary with age, sex, and time period over April-December 2020 in the United States, using mortality from other natural causes as a proxy for underlying health. We study a novel measure, the COVID excess mortality percentage (CEMP), defined as the COVID-19 mortality rate divided by the non-COVID natural mortality rate, converted to a percentage, where the CEMP denominator controls (albeit imperfectly) for differences in population health. Disparities measured using CEMP deviate substantially from those in prior research. In particular, we find very high disparities (up to 12:1) in CEMP rates for Hispanics versus Whites, particularly for nonelderly men. Asians also have elevated CEMP rates versus Whites, which were obscured in prior work by lower overall Asian mortality. Native Americans and Blacks have significant disparities compared with White populations, but CEMP ratios to Whites are lower than ratios reported in other work. This is because the higher COVID-19 mortality for Blacks and Native Americans comes partly from higher general mortality risk and partly from COVID-specific risk.
Development of occupation-based exposure matrix of lead for Korean workers: challenges and opportunities
Authors: Koh Dong-Hee , Choi Sangjun , Park Ju-Hyun , Lee Sang-Gil , Kim Hwan-Cheol , Kim Inah , Lim Daesung , Seo Hoekyeong , Park Dong-Uk 
Published: February 2024

Abstract

Objectives
Industry- and occupation-based carcinogen exposure matrices play a pivotal role in preventing occupational cancer. While the Korean CARcinogen EXposure (K-CAREX) has been developed in recent years to assess exposure prevalence and intensity by industry, the feasibility of constructing an occupation-based exposure matrix remains unexplored. Hence, the objective of this study is to explore the potential of combining the nationwide work environment measurement database (WEMD) and the special health examination database (SHED) to develop a comprehensive occupation-based exposure matrix.

Methods
The WEMD provides information on airborne lead measurements, including industry codes, but it does not include data related to occupations. In contrast, the SHED contains information on both occupation and blood lead levels. By integrating these 2 databases, we attempted to assess airborne lead exposure levels by occupation. Additionally, we performed a rank correlation analysis to compare the airborne exposure levels with corresponding blood lead levels according to occupation.

Results
A total of 35 425 workers who both wore air samplers for lead and underwent special health examinations for lead were extracted between 2019 and 2021. An occupation-based exposure matrix was developed to evaluate the intensity of lead exposure across a range of occupations, encompassing 51 minor occupations and 70-unit occupations. Rank correlation analyses showed strong positive correlations between airborne lead and blood lead measurements according to occupation.

Conclusions
Our study findings suggest that combining 2 nationwide surveillance databases can be an effective approach for creating an occupation-based exposure matrix. However, our results also highlight several limitations that need to be addressed in future studies to improve the accuracy and reliability of such matrices.
Oral Methotrexate Treatment of Delayed-Onset Inflammatory Reactions to Dermal Fillers
Authors: Landau Marina , Silikovich Fernando , Fida Monika , Cartier Hugues , Kroumpouzos George 
Published: February 2024

Abstract

Background
In aesthetic practice, delayed-onset (late) inflammatory reactions (DIRs) to dermal fillers are encountered. The treatment of DIRs can be challenging, with a response to established therapies, including oral antibiotics, intralesional and oral steroids, and hyaluronidase injection, occasionally reported as unsatisfactory.

Objectives
Evaluate the efficacy of low-dose oral methotrexate (MTX) therapy in treating recalcitrant DIRs.

Methods
We retrospectively reviewed cases of recalcitrant DIRs treated with oral MTX. Data collected included individuals' gender and age, medical history, filler type, facial area(s) injected, previous treatments attempted to dissolve the DIR, MTX treatment dosage and duration, and outcome. Adverse events were monitored throughout the treatment.

Results
Thirteen females with a mean age of 52.6 years (range, 31-67 years) who developed recalcitrant DIRs to dermal filler injection are included. Eight reactions were triggered by the injection of hyaluronic acid (HA) fillers, 4 by liquid injectable silicone (LIS), and 1 by polymethylmethacrylate (PMMA). The average starting dosage of MTX was 12.1 mg/week (range, 7.5-12.5 mg/week). Patients were treated for 2 to 3 months in most cases. The average follow-up post-MTX therapy was 11.8 months (range, 2-36 months). A complete response to MTX treatment was observed in 10 patients (6 HA and 4 LIS cases), partial response in 1 (HA case), and an unsatisfactory response in 2 (HA and PMMA cases). Treatment was well tolerated.

Conclusions
A short course of low-dose oral MTX is a possible treatment for DIRs that have not responded to established therapies. The promising results of this report require validation by powered studies.

Level of Evidence: 4
Novel symmetry-preserving neural network model for phylogenetic inference
Authors: Tang Xudong , Zepeda-Nuñez Leonardo , Yang Shengwen , Zhao Zelin , Solís-Lemus Claudia 
Published: February 2024

Abstract

Motivation
Scientists world-wide are putting together massive efforts to understand how the biodiversity that we see on Earth evolved from single-cell organisms at the origin of life and this diversification process is represented through the Tree of Life. Low sampling rates and high heterogeneity in the rate of evolution across sites and lineages produce a phenomenon denoted “long branch attraction” (LBA) in which long nonsister lineages are estimated to be sisters regardless of their true evolutionary relationship. LBA has been a pervasive problem in phylogenetic inference affecting different types of methodologies from distance-based to likelihood-based.

Results
Here, we present a novel neural network model that outperforms standard phylogenetic methods and other neural network implementations under LBA settings. Furthermore, unlike existing neural network models in phylogenetics, our model naturally accounts for the tree isomorphisms via permutation invariant functions which ultimately result in lower memory and allows the seamless extension to larger trees.

Availability and implementation
We implement our novel theory on an open-source publicly available GitHub repository: https://github.com/crsl4/nn-phylogenetics.
Geometry-complete perceptron networks for 3D molecular graphs
Authors: Morehead Alex , Cheng Jianlin 
Published: February 2024

Abstract

Motivation
The field of geometric deep learning has recently had a profound impact on several scientific domains such as protein structure prediction and design, leading to methodological advancements within and outside of the realm of traditional machine learning. Within this spirit, in this work, we introduce GCPNet, a new chirality-aware SE(3)-equivariant graph neural network designed for representation learning of 3D biomolecular graphs. We show that GCPNet, unlike previous representation learning methods for 3D biomolecules, is widely applicable to a variety of invariant or equivariant node-level, edge-level, and graph-level tasks on biomolecular structures while being able to (1) learn important chiral properties of 3D molecules and (2) detect external force fields.

Results
Across four distinct molecular-geometric tasks, we demonstrate that GCPNet’s predictions (1) for protein–ligand binding affinity achieve a statistically significant correlation of 0.608, more than 5%, greater than current state-of-the-art methods; (2) for protein structure ranking achieve statistically significant target-local and dataset-global correlations of 0.616 and 0.871, respectively; (3) for Newtownian many-body systems modeling achieve a task-averaged mean squared error less than 0.01, more than 15% better than current methods; and (4) for molecular chirality recognition achieve a state-of-the-art prediction accuracy of 98.7%, better than any other machine learning method to date.

Availability and implementation
The source code, data, and instructions to train new models or reproduce our results are freely available at https://github.com/BioinfoMachineLearning/GCPNet.
Fast and scalable querying of eukaryotic linear motifs with gget elm
Authors: Luebbert Laura , Hoang Chi , Kumar Manjeet , Pachter Lior 
Published: February 2024

Abstract

Motivation
Eukaryotic linear motifs (ELMs), or Short Linear Motifs, are protein interaction modules that play an essential role in cellular processes and signaling networks and are often involved in diseases like cancer. The ELM database is a collection of manually curated motif knowledge from scientific papers. It has become a crucial resource for investigating motif biology and recognizing candidate ELMs in novel amino acid sequences. Users can search amino acid sequences or UniProt Accessions on the ELM resource web interface. However, as with many web services, there are limitations in the swift processing of large-scale queries through the ELM web interface or API calls, and, therefore, integration into protein function analysis pipelines is limited.

Results
To allow swift, large-scale motif analyses on protein sequences using ELMs curated in the ELM database, we have extended the gget suite of Python and command line tools with a new module, gget elm, which does not rely on the ELM server for efficiently finding candidate ELMs in user-submitted amino acid sequences and UniProt Accessions. gget elm increases accessibility to the information stored in the ELM database and allows scalable searches for motif-mediated interaction sites in the amino acid sequences.

Availability and implementation
The manual and source code are available at https://github.com/pachterlab/gget.
Rapid IDH1-R132 genotyping panel utilizing locked nucleic acid loop-mediated isothermal amplification
Authors: Choate Kristian A , Raack Edward J , Mann Paul B , Jones Evan A , Winn Robert J , Jennings Matthew J 
Published: February 2024

Abstract
While the detection of single-nucleotide variants (SNVs) is important for evaluating human health and disease, most genotyping methods require a nucleic acid extraction step and lengthy analytical times. Here, we present a protocol which utilizes the integration of locked nucleic acids (LNAs) into self-annealing loop primers for the allelic discrimination of five isocitrate dehydrogenase 1 R132 (IDH1-R132) variants using loop-mediated isothermal amplification (LAMP). This genotyping panel was initially evaluated using purified synthetic DNA to show proof of specific SNV discrimination. Additional evaluation using glioma tumor lysates with known IDH1-R132 mutational status demonstrated specificity in approximately 35 min without the need for a nucleic acid extraction purification step. This LNA-LAMP-based genotyping assay can detect single base differences in purified nucleic acids or tissue homogenates, including instances where the variant of interest is present in an excess of background wild-type DNA. The pH-based colorimetric indicator of LNA-LAMP facilitates convenient visual interpretation of reactions, and we demonstrate successful translation to an end-point format using absorbance ratio, allowing for an alternative and objective approach for differentiating between positive and negative reactions. Importantly, the LNA-LAMP genotyping panel is highly reproducible, with no false-positive or false-negative results observed.
Efficacy of depatuxizumab mafodotin (ABT-414) in preclinical models of head and neck cancer
Authors: Mani Lucas , Naveed Abdullah , McAdoo Ashtyn , Rosenthal Eben , Hom Marisa 
Published: February 2024

Abstract
Epidermal growth factor receptor (EGFR) is highly expressed in 80–90% of head and neck squamous cell carcinomas (HNSCCs), making it an ideal target for antibody–drug conjugates. Depatuxizumab mafodotin (ABT-414), is an EGFR-targeting ADC comprised of the monoclonal antibody ABT-806 conjugated to monomethyl auristatin F, a tubulin polymerization inhibitor. This study assessed the in vivo efficacy of ABT-414 in HNSCC. The effects of ABT-414 on HNSCCs were determined using in vitro cytotoxicity assays and in vivo flank xenograft mouse models. The distribution of ABT-414 was assessed ex vivo via optical imaging methods using a conjugate of ABT-414 to the near-infrared agent IRDye800. In vitro treatment of high EGFR-expressing human HNSCC cell lines (UMSCC47 and FaDu) with ABT-414 (0–3.38 nM) resulted in dose-dependent cell death (IC50 values of 0.213 nM and 0.167 nM, respectively). ABT-414 treatment of the FaDu mouse xenografts displayed antitumor activity (P = 0.023) without a change in body mass (P = 0.1335), whereas treatment of UMSCC47 did not generate a significant response (P = 0.1761). Fluorescence imaging revealed ABT-414-IRDye800 accumulation in the tumors of both FaDu and UMSCC47 cell lines, with a signal-to-background ratio of &gt;10. ABT-414 treatment yielded antitumor activity in FaDu tumors, but not in UMSCC47, highlighting the potential for ABT-414 efficacy in high EGFR-expressing tumors. Although ABT-414-IRDye800 localized tumors in both cell lines, the differing antitumor responses highlight the need for further investigation into the role of the tumor microenvironment in drug delivery.
Synthesis, structure, and magnetic properties of cubane-type tetranuclear Ni(II) and Cu(II) complexes with amide-containing polydentate ligand
Authors: Tanaka Akihiro , Kusumoto Sotaro , Umeno Harue , Kim Yang , Nakamura Masaaki , Hayami Shinya 
Published: February 2024

Abstract
Synthesis, structure, and magnetic properties of a tetranuclear metal complex with a symmetrical polydentate ligand, trans-(±)-1,2-(2-hydroxy-3-methoxybenzamido)cyclohexane (H2L), were characterized. The complexes have tetranuclear cubane cores with the formulae [Ni4(L)2(μ3-OMe)4(CH3OH)4] (1) and [Cu4(L)2(μ3-OMe)4(CH3OH)2] (2), whose cluster units are each composed of chiral ligands [(R, R)- or (S, S)-L]. The magnetic properties of the two compounds were characterized by 1 being ferromagnetic and 2 being antiferromagnetic.