bluuebunny/crossref_metadata_2025 huggingface dataset:
A novel PGPR strain, Streptomyces lasalocidi JCM 3373T, alleviates salt stress and shapes root architecture in soybean by secreting indole‐3‐carboxaldehyde
Authors: Lu Liang , Liu Ning , Fan Zihui , Liu Minghao , Zhang Xiaxia , Tian Juan , Yu Yanjun , Lin Honghui , Huang Ying , Kong Zhaosheng
Published: February 2024

While soybean (Glycine max L.) provides the most important source of vegetable oil and protein, it is sensitive to salinity, which seriously endangers the yield and quality during soybean production. The application of Plant Growth‐Promoting Rhizobacteria (PGPR) to improve salt tolerance for plant is currently gaining increasing attention. Streptomycetes are a major group of PGPR. However, to date, few streptomycetes has been successfully developed and applied to promote salt tolerance in soybean. Here, we discovered a novel PGPR strain, Streptomyces lasalocidi JCM 3373T, from 36 strains of streptomycetes via assays of their capacity to alleviate salt stress in soybean. Microscopic observation showed that S. lasalocidi JCM 3373T does not colonise soybean roots. Chemical analysis confirmed that S. lasalocidi JCM 3373T secretes indole‐3‐carboxaldehyde (ICA1d). Importantly, IAC1d inoculation alleviates salt stress in soybean and modulates its root architecture by regulating the expression of stress‐responsive genes GmVSP, GmPHD2 and GmWRKY54 and root growth‐related genes GmPIN1a, GmPIN2a, GmYUCCA5 and GmYUCCA6. Taken together, the novel PGPR strain, S. lasalocidi JCM 3373T, alleviates salt stress and improves root architecture in soybean by secreting ICA1d. Our findings provide novel clues for the development of new microbial inoculant and the improvement of crop productivity under salt stress.
Lung ultrasound is a promising screening tool to rule out interstitial lung disease in patients with rheumatoid arthritis
Authors: Otaola M. , Paulin F. , Rosemffet M. , Balcazar J. , Perandones M. , Orausclio P. , Cazenave T. , Rossi S. , Marciano S. , Schneeberger E. , Citera G.
Published: February 2024

Background and Objective

It is still controversial how to screen for interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA). We aimed to evaluate the performance of lung ultrasound (LUS) as a screening tool for RA‐ILD and to compare it with the performance of chest auscultation, chest x‐ray and pulmonary function tests (PFTs).

Methods

Cross‐sectional study of consecutive RA patients evaluated at a Rheumatology Clinic in Buenos Aires between January and December 2022. High‐resolution computed tomography (HRCT) was the gold standard for diagnosing ILD and was performed within 30 days of the LUS, chest x‐ray and PFTs. Investigators were blinded to HRCT results and patients' clinical data. LUS was performed by exploring 14 areas and was considered positive when the sum of B lines was ≥5. Performance for the diagnosis of ILD was reported for each diagnostic test.

Results

One hundred and six patients were included; 87 (82%) were women. Median age was 60.9 (±9.5) years‐old. A total of 32 (30.2%, 95% CI: 21.6%–39.9%) had ILD. The sensitivity and negative predictive value of LUS were 90.6% (95% CI 75.0%–98.0%) and 94.7% (95% CI 85.4%–98.9%), respectively. LUS performance was superior to that of the other evaluated diagnostic tests for screening ILD.

Conclusions

Given that the US is a low‐cost point‐of‐care tool with a high negative predictive value, it is emerging as a valuable tool for ruling out ILD in patients with RA.

image
Spatial spillovers in trade agreement memberships: Does institutional proximity matter?
Authors: Liu Renliang , Stengos Thanasis , Sun Yiguo
Published: February 2024

This paper examines spatial spillovers in the formation of preferential trade agreements (PTAs) through a new channel of institutional proximity. Our dependent variable is the status of PTAs between country attributes within a country‐pair. The explanatory variable of interest is the status of PTAs in neighbouring country‐pairs that share proximity in institutional development. We consider democracy and economic freedom as the main aspects of institutions, and use both as the fundamental components of institutional distance between country‐pairs. Employing a spatial econometric method, we find strong evidence of the institutional interdependence of PTAs: country‐pairs tend to influence each other's decision on the formation and the chosen type of PTAs (i.e., deep or shallow), such a neighbourhood effect increases with institutional proximity and is more prominent for the decisions on the type of PTAs. The institutional spatial channel is robust to various robustness checks.
European long‐term care marketisation: A political economy framework
Authors: Mercille Julien
Published: February 2024

The study of European long‐term care (LTC) marketisation is dominated by institutional and ideational perspectives. In contrast, political economic theoretical frameworks have received little attention. This is paradoxical, because marketisation is an inherently political economic phenomenon. The financialisation of LTC systems, the growth of private for‐profit providers and the rise in cross‐national investments are proceeding apace, yet, they have been neglected by conventional approaches. This paper presents a political economy theoretical framework to study LTC marketisation. In contrast to conventional perspectives, it locates the drivers of marketisation within (neoliberal) capitalism; conceives of the state as significantly aligned with the interests of the business sector; interprets ideology as often originating in the material interests of the latter; examines ‘power struggles’ between, in particular, private providers on one hand and the public/non‐profit sector and care workers on the other hand. These power struggles take place in LTC financing, privatisation, regulation, financialisation and labour flexibility. In those struggles, private providers assert their power (structural, institutional and instrumental) to shape marketisation; however, they can encounter resistance. The framework also examines the outcomes of marketisation and is illustrated empirically by reference to Irish LTC.
The effects of science inquiry on engagement for elementary students with disabilities
Authors: Taylor Jonte C. , Stocker James D. , Sharp Starlette M. , Therrien William , Hand Brian
Published: February 2024

Students with disabilities (SWD) have consistently been excluded in science in science classrooms. As inquiry‐based instruction is the preferred method of science instruction, finding the best ways to teach using inquiry as an inclusive methodology is essential. The Science Writing Heuristic (SWH) is an argument‐based inquiry approach that has shown to be successful for SWD. The current study examines the efficacy of the SWH in inclusive elementary classrooms for SWD, specifically focusing on engagement. We introduce a theoretical framework for engagement for SWD across instructional needs. Additionally, the study analyzes behavioral observation data on engagement to evaluate the efficacy of the SWH for SWD. Randomly selected classrooms in treatment and control conditions across four rural midwestern schools participated in the current study. Teachers in the treatment group were trained in using the SWH approach for science instruction and compared to teachers in a control group who taught science using the district‐approved curriculum and methods. Mean scores were compared between SWD in SWH classrooms and their peers without disabilities and SWD in control classrooms. Multiple statistical and effect size analyses were conducted. Findings suggest that the SWH is an effective instructional approach that supports SWD in classroom engagement.
Participant‐driven salient beliefs regarding abortion: Implications for abortion attitude measurement
Authors: Jozkowski Kristen N. , Bueno Xiana , LaRoche Kathryn , Crawford Brandon L. , Turner Ronna C. , Lo Wen‐Juo
Published: February 2024

Objective

Guided by the Reasoned Action Approach, we used a salient belief elicitation (SBE) to elicit participant‐generated beliefs regarding abortion. SBE is a formative research technique used to elicit people's control (i.e., perceived facilitators and barriers associated with a behavior), behavioral (i.e., perceived positive and negative consequences of doing a behavior), and normative (i.e., influence of important people/peers regarding a behavior) beliefs regarding a particular behavior (i.e., abortion).

Methods

We administered our SBE to English‐ and Spanish‐speaking U.S. adults (N = 608) from NORC's AmeriSpeak® panel. We used inductive content and thematic analyses to assess open‐ended questions.

Results

We found that participants’ control and behavioral beliefs referenced circumstances used to assess abortion attitudes in polling item (e.g., rape) and reasons people seek abortion (e.g., financial reasons) as well as potential negative emotions (e.g., shame) and positive consequences (e.g., autonomy) associated with abortion. Participants indicated pregnant people's partners and people seeking abortion as salient referents.

Conclusion

Participants mentioned several contexts reflected in common measures used to assess abortion attitudes by national polls and surveys. However, we also found other relevant circumstances not reflected in common measures and a range of salient referents. We recommend abortion attitudes measures account for these participant‐driven salient beliefs.
Characterization of the novel HLA‐C*01:263 allele by sequencing‐based typing
Authors: Cargou Marine , Elsermans Vincent , Top Isabelle , Duclaut Marion , Visentin Jonathan
Published: February 2024

HLA‐C*01:263 differs from HLA‐C*01:02:01:01 by one nucleotide substitution in codon 98 in exon 3.
Characterization of the novel HLA‐DQB1*03:516 allele by next‐generation sequencing
Authors: Bian Cheng , Wang Zi‐Hao , Cheng Zi‐An , Sun Hao , Yang Zhao‐Qing
Published: February 2024

HLA‐DQB1*03:516 differs from DQB1*03:03:02:03 by one nucleotide substitution at position 197G>A in exon 2.
Characterization of the novel HLA‐B*51:394Q allele by sequencing‐based typing
Authors: Cargou Marine , Elsermans Vincent , Top Isabelle , Duclaut Marion , Visentin Jonathan
Published: February 2024

HLA‐B*51:394Q differs from HLA‐B*51:01:01:05 by one nucleotide substitution in codon 339 in exon 7.
Recognition of the HLA‐A*02:840 allele, a variant of A*02:07:01:01, in a Taiwanese individual
Authors: Yang Kuo‐Liang , Lin Py‐Yu
Published: February 2024

Two nucleotide substitutions in exon 3 of HLA‐A*02:07:01:01 result in the novel allele, HLA‐A*02:840.
Identification of the novel HLA‐C*01:65:02 allele by next‐generation sequencing
Authors: López‐Pérez Juan , Martínez‐Lostao Luis , Inda‐Landaluce Mercedes
Published: February 2024

The novel HLA‐C*01:65:02 allele was detected during routine HLA typing.
An analysis of keloid patient questions on Reddit
Authors: Wang Jennifer , Patel Paras , Jagdeo Jared
Published: February 2024

Reddit is one of the world's leading social media platforms, fostering active community discussions on a variety of topics including keloids. The prevalence and reach of conversations on Reddit underscore the need to investigate and understand patient perspectives and gaps in knowledge. Herein, we present an in‐depth analysis of questions and concerns of Reddit users on keloids, offering valuable insights into patient experiences, knowledge gaps and treatment preferences. The study presents a distinct approach by harnessing the power of social media data to understand patient perspectives, which may not be readily apparent in clinical settings. All posts on the ‘Hot’ page of the subreddit r/Keloids were analyzed. Questions were categorized and subcategorized to reveal common themes. A total of 644 questions from 513 posts between 26 March 2017 and 28 August 2023 were identified and analyzed. Reddit users most frequently asked questions regarding keloid management (57.5%). Other common categories included uncertainty regarding diagnosis or symptoms (15.1%), living with keloids (7.5%) and causes or triggers (6.2%). This analysis highlights critical areas of patient knowledge gaps and potential misconceptions regarding keloids. For dermatologists, understanding these patient questions is crucial. Such insights allow for patient‐centric education and treatments, ensuring more effective and comprehensive care.
Decay rates for the 4D energy‐critical nonlinear heat equation
Authors: Kosloff Leonardo , Niche César J. , Planas Gabriela
Published: February 2024

In this paper, we address the decay of solutions to the four‐dimensional energy‐critical nonlinear heat equation in the critical space . Recently, it was proven that the norm of solutions goes to zero when time goes to infinity, but no decay rates were established. By means of the Fourier Splitting Method and using properties arising from the scale invariance, we obtain an algebraic upper bound for the decay rate of solutions.
Myths and Methodologies: Understanding the health impact of head down bedrest for the benefit of older adults and astronauts. Study protocol of the Canadian Bedrest Study
Authors: Hajj‐Boutros Guy , Sonjak Vita , Faust Andréa , Balram Sharmila , Lagacé Jean‐Christophe , St‐Martin Philippe , Divsalar Donya Naz , Sadeghian Farshid , Liu‐Ambrose Teresa , Blaber Andrew P. , Dionne Isabelle J. , Duchesne Simon , Kontulainen Saija , Theou Olga , Morais José A.
Published: February 2024

Weightlessness during spaceflight can harm various bodily systems, including bone density, muscle mass, strength and cognitive functions. Exercise appears to somewhat counteract these effects. A terrestrial model for this is head‐down bedrest (HDBR), simulating gravity loss. This mirrors challenges faced by older adults in extended bedrest and space environments. The first Canadian study, backed by the Canadian Space Agency, Canadian Institutes of Health Research, and Canadian Frailty Network, aims to explore these issues. The study seeks to: (1) scrutinize the impact of 14‐day HDBR on physiological, psychological and neurocognitive systems, and (2) assess the benefits of exercise during HDBR. Eight teams developed distinct protocols, harmonized in three videoconferences, at the McGill University Health Center. Over 26 days, 23 participants aged 55–65 underwent baseline measurements, 14 days of −6° HDBR, and 7 days of recovery. Half did prescribed exercise thrice daily combining resistance and endurance exercise for a total duration of 1 h. Assessments included demographics, cardiorespiratory fitness, bone health, body composition, quality of life, mental health, cognition, muscle health and biomarkers. This study has yielded some published outcomes, with more forthcoming. Findings will enrich our comprehension of HDBR effects, guiding future strategies for astronaut well‐being and aiding bedrest‐bound older adults. By outlining evidence‐based interventions, this research supports both space travellers and those enduring prolonged bedrest.
A Bayesian Multi-Fidelity Neural Network to Predict Nonlinear Frequency Backbone Curves
Authors: Najera-Flores David A. , Ortiz Jonel , Khan Moheimin Y. , Kuether Robert J. , Miles Paul R.
Published: February 2024

The use of structural mechanics models during the design process often leads to the development of models of varying fidelity. Often low-fidelity models are efficient to simulate but lack accuracy, while the high-fidelity counterparts are accurate with less efficiency. This paper presents a multifidelity surrogate modeling approach that combines the accuracy of a high-fidelity finite element model with the efficiency of a low-fidelity model to train an even faster surrogate model that parameterizes the design space of interest. The objective of these models is to predict the nonlinear frequency backbone curves of the Tribomechadynamics research challenge benchmark structure which exhibits simultaneous nonlinearities from frictional contact and geometric nonlinearity. The surrogate model consists of an ensemble of neural networks that learn the mapping between low and high-fidelity data through nonlinear transformations. Bayesian neural networks are used to assess the surrogate model's uncertainty. Once trained, the multifidelity neural network is used to perform sensitivity analysis to assess the influence of the design parameters on the predicted backbone curves. Additionally, Bayesian calibration is performed to update the input parameter distributions to correlate the model parameters to the collection of experimentally measured backbone curves.
Physical rehabilitation while awake, intubated and proned for COVID-19-associated severe acute respiratory distress syndrome
Authors: Seth Bhavna , Oakman Brittany , Needham Dale M
Published: February 2024

This case study demonstrates the implementation of evidence-based guidelines in the intensive care unit setting, including light sedation and early physical rehabilitation while receiving prone positioning and lung protective mechanical ventilation for severe acute respiratory distress syndrome from SARS-CoV-2 infection.
Intrinsic ureteric obstruction secondary to endometriosis: a rare clinical entity causing obstructive uropathy and renal failure
Authors: Anton Sagayanathan Prasanth , Goai Xin Yi , Loganathan Ajanthan , Pridgeon Simon
Published: February 2024

Ureteral endometriosis is rare and can be a silent clinical entity, which can potentially lead to serious complications such as obstructive uropathy, sepsis and renal failure. A high clinical suspicion is required especially in childbearing age groups due to non-specific presentation such as renal colic, recurrent urinary tract infection (UTI), renal failure or asymptomatic hydronephrosis.

A woman in her 40s presented with febrile UTI and flank pain. She reportedly suffered from recurrent UTIs in the past. Initial workup revealed an infected, obstructed left renal collecting system with gross hydronephrosis and hydroureter to the distal ureter on a significant gynaecological background of severe endometriosis requiring hysterectomy in the past.

CT showed chronic obstructive changes and soft tissue nodules within the renal pelvis with no radio-opaque stones. She underwent emergent ureteric stent insertion. Functional imaging demonstrated only 1% contribution of the left kidney with a preserved estimated glomerular filtration rate of 65 mL/min/1.73 m2.

Endoscopic evaluation of ureters found extensive soft tissue lesions throughout the dilated left collecting system with biopsy-confirmed endometriosis. Subsequently, she underwent laparoscopic nephroureterectomy due to extensive ureteric involvement and chronically obstructed non-functioning kidney. Histopathology demonstrated completely obstructing ureteral endometriosis.

Ureteric obstruction secondary to endometriosis can be due to extrinsic or intrinsic disease. In addition to initial assessment with CT urogram MRI may be helpful to evaluate soft tissue thickening. Endoscopic assessment with ureteroscopy and biopsy is required for tissue diagnosis. Surgery is often the treatment of choice, ranging from ureteroureterostomy, ureteroneocystostomy or nephroureterectomy in severe cases.

Ureteral endometriosis is a rare clinical entity, clinicians should remain vigilant about common presentations of this rare entity, early diagnosis and prompt treatment is crucial to prevent progression to renal failure.
Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry
Authors: He Jie , Fan Baoqi , Lau Eric S H , Chu Natural , Ng Noel Yat Hey , Leung Kathy Ho Ting , Poon Emily W M , Kong Alice Pik Shan , Ma Ronald Ching Wan , Luk Andrea O Y , Chan Juliana C N , Chow Elaine
Published: February 2024

Introduction

Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT.

Research design and methods

We used baseline data of 1938 individuals from the community-based “Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort” recruited in 1998–2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation.

Results

The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ2=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764).

Conclusions

The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.
No scalar-haired Cauchy horizon theorem in charged Gauss–Bonnet black holes
Authors: Devecioğlu Deniz O. , Park Mu-In
Published: February 2024

Recently, a “no inner (Cauchy) horizon theorem” for static black holes with non-trivial scalar hairs has been proved in Einstein–Maxwell–scalar theories and also in Einstein–Maxwell–Horndeski theories with the non-minimal coupling of a charged (complex) scalar field to Einstein tensor. In this paper, we study an extension of the theorem to the static black holes in Einstein–Maxwell–Gauss–Bonnet-scalar theories, or simply, charged Gauss–Bonnet (GB) black holes. We find that no inner horizon with charged scalar hairs is allowed for the planar ($$k=0$$

k
=
0

) black holes, as in the case without GB term. On the other hand, for the non-planar ($$k=\pm 1$$

k
=
±
1

) black holes, we find that the haired inner horizon can not be excluded due to GB effect generally, though we can not find a simple condition for its existence. As some explicit examples of the theorem, we study numerical GB black hole solutions with charged scalar hairs and Cauchy horizons in asymptotically anti-de Sitter space, and find good agreements with the theorem. Additionally, in an Appendix, we prove a “no-go theorem” for charged de Sitter black holes (with or without GB terms) with charged scalar hairs in arbitrary dimensions.
Constraints on Lorentz violation parameter through electric dipole moments
Authors: Aghababaei Sarah
Published: February 2024

The electric dipole moments of leptons (l-EDMs) could arise from the electrodynamics part of standard model extension (SME). In this work, we investigate the cross section of electron-positron collision in the Lorentz violation (LV) background via the l-EDMs. We find that the Lorentz violation parameter magnitudes constraint using LEP data to the level of $$|d^{e}_{LV}| < 3.6 \times 10^{-17} $$

|

d

LV

e

|
<
3.6
×

10

-
17

, $$ |d^{\mu }_{LV}|< 9.5 \times 10^{-10} $$

|

d

LV

μ

|
<
9.5
×

10

-
10

, and $$ |d^{\tau }_{LV}|< 1.5 \times 10^{-6} $$

|

d

LV

τ

|
<
1.5
×

10

-
6

for electron, muon, and tau, respectively. Moreover, we show the time-location dependence of muon-EDMs and tau-EDMs in the LV background. Therefore, upper bounds for combinations of LV parameters are obtained by current and future terrestrial experiments.
Holographic matrix method for rapid material structural feature extraction and detection
Authors: Li Minghao , Wang Wenfu , Gao Tinghong , Wang Chenxu , Wang Qidan , An Ji , Tian Yuzhen
Published: February 2024

The extraction of the structural features of materials is fundamental for investigating novel properties in fields such as electronic information and biochemistry. However, existing experimental methods have limitations in analyzing material structures with sufficient depth. Therefore, rapid and accurate extraction and analysis of structural features from atomic coordinates obtained through simulation calculations are crucial for advancing the exploration of new material properties. Herein, we propose an approach for extracting the structural features of materials by combining the holographic matrix method with Bayesian optimization and tensor flow operations. The proposed algorithm efficiently classifies and statistically analyzes cluster structures within materials. Experimental validation conducted on a system comprising 8000 atoms demonstrated a correct recognition rate exceeding 99.213%. Moreover, the algorithm achieved an average recognition time of approximately [Formula: see text][Formula: see text]s. The proposed analytical framework exhibits scalability and robustness, establishing an algorithmic foundation for future advancements in big data analytics for complex materials.
MICRO-EDM OF TI–6AL–4V USING VARIOUS TOOL MATERIALS: MULTI-RESPONSE OPTIMIZATION AND SURFACE CHARACTERIZATION
Authors: PAL MANAS RANJAN , DEBNATH KISHORE , RAO GORREPOTU SURYA , MAHAPATRA RABINDRA NARAYAN
Published: February 2024

In this paper, experimental analysis was performed during micro-electrical discharge machining (micro-EDM) of titanium alloy Ti–6Al–4V (grade 5) using three types of tools viz. copper (Cu) tool, tungsten carbide (WC) tool, and synthetic graphite (Gr) grade three tool. The main process parameters were taken as (a) pulse on time ([Formula: see text]), (b) pulse off time ([Formula: see text]), (c) voltage (V), and (d) capacitance (C). The output responses were taken as the material removal rate (MRR) and tool wear rate (TWR). Taguchi method coupled with grey relational analysis (GRA) (L[Formula: see text] orthogonal array) technique was applied to optimize the input process parameters for both the responses. Scanning electron microscopy (SEM) analysis of the workpiece and tool was also performed to investigate the morphology of the machined surface and tool surface. Energy-dispersive spectroscopy (EDS) analysis was performed to investigate the elemental composition of the machined surface. The experimental finding reveals that tungsten carbide is the most suitable tool material for machining the chosen workpiece for obtaining optimal MRR and TWR. The optimum condition for the copper tool was found as 180[Formula: see text]V, 1000[Formula: see text]pf, 10[Formula: see text][Formula: see text]s ([Formula: see text]), and 10[Formula: see text][Formula: see text]s ([Formula: see text]). Meanwhile, the optimum parametric condition for tungsten carbide and graphite tools was found to be the same as 240[Formula: see text]V, 100[Formula: see text]pf, 20[Formula: see text][Formula: see text]s ([Formula: see text]), and 5[Formula: see text][Formula: see text]s ([Formula: see text]).
Sustainability reporting and bank performance in a developing country
Authors: Halim Md. Abdul , Lima Reshma Pervin , Islam Md. Nazmul
Published: February 2024

The purpose of this study is to test whether sustainability reporting leads to better performance and creates value for investors in developing markets. This study examined the 32 Bangladeshi banks. The generalized method of moments (GMM) is used to analyze this study. Ordinary least square (OLS) is used for robustness check in this study. The finding of this study shows that there is a significant corporate social responsibility (CSR) and a negative association between environmental, social, and corporate governance (ESG) scores and bank performance of Bangladeshi banks. The result of ESG indicates that environmental, social and governance performances reduce both banks’ profitability and values. The results of the research show that ESG has a significant CSR, insignificant ED and CG and negative impact on the performance of banks and the economic benefits of shareholders. Unfortunately, this study also shows that there is no relationship between environmental disclosure, corporate governance (ECG) and bank performance (ROE). Finally, this study provides a policy implication and future guidelines to all stakeholders.
Geogas prospecting for igneous ore deposits covered by regolith: the Zijinshan high-sulfidation epithermal Cu–Au deposit in the Cathaysia Block
Authors: Li Quanheng , Ye Rong , Duan Haichuan , Xu Kequan , Shen Shuoguo , Tian Yufeng
Published: February 2024

The mining industry faces a challenge due to the scarcity of outcrop or near-surface mineral deposits, necessitating the development of low-cost and efficient prospecting methods to explore through cover. Inductively coupled plasma mass spectrometry has been applied to geological sample analysis, and scientists have gradually improved the method of geogas prospecting. As a result, geogas prospecting has shown promising results in detecting underlying concealed Au, U and Cu–Ni deposits covered by Gobi sand and Quaternary sediments. To verify the effectiveness of this method for exploring underlying concealed mineral deposits developed in igneous covered areas, the Zijinshan high-sulfidation epithermal Cu–Au deposit, a concealed mineral deposit in southeastern China, was selected as the experimental field. Our experiments revealed nanoscale particles composed of Au, Cu–Fe and Cu–other elements in the geogas captured above the ore bodies of the deposit. Furthermore, Cu–nanoscale particles retain the isotopic composition of copper found in both the oxidation zone and deep copper ores. The geogas samples exhibited similar C1-chondrite normalized REE distributions, with REE patterns indicating significant enrichment of LREE relative to HREE and similar (La)N/(Sm)N and (Gd)N/(Yb)N ratios. These characteristics are similar to those of the gold ores, copper ores, altered rock and bedrock near the ore bodies. These findings suggest that deep-penetration geochemical methods using geogas can be a valuable tool for uncovering underlying concealed mineral deposits in igneous covered areas.
Testing the salinity of Cambrian to Silurian epicratonic seas
Authors: Liu Zhanhong , Algeo Thomas J. , Arefifard Sakineh , Wei Wei , Brett Carlton , Landing Ed , Lev Steven M.
Published: February 2024

Ancient epicratonic formations, which represent the bulk of pre-Jurassic sedimentary rocks, have been widely interpreted as marine deposits, but recently developed bulk-shale elemental proxies for palaeo-watermass salinity (i.e. B/Ga, Sr/Ba and S/TOC, where TOC is total organic carbon) have shown this inference to be frequently incorrect. Here, we use these proxies to test the salinity conditions of 22 representative shale and marl formations of early Cambrian to early Silurian age from five cratons (Laurentia, Avalonia, Baltica, Iran and South China) in the context of formation-specific palaeogeographical and palaeoclimatic reconstructions. Our dataset shows that around half of these formations were probably deposited under brackish or mixed brackish–marine conditions rather than fully marine conditions (as previously inferred), and that one of them represents a freshwater facies (previously interpreted as marine mainly on the basis of
Cruziana
traces). In most cases, the development of reduced-salinity conditions can be related to the coastal and/or humid climate belt setting in which the formation of interest was deposited. Our dataset also reveals systematically low Sr/Ba values (i.e. relative to modern brackish and marine facies), suggesting that seawater Sr concentrations were lower during the Early Paleozoic than at present. Our findings suggest that re-evaluation of the salinity characteristics of many ancient epicratonic shale and marl formations is necessary.

Supplementary material:
A supplementary figure and tables are available at
https://doi.org/10.6084/m9.figshare.c.7063365

Thematic collection:
This article is part of the Chemical Evolution of the Mid-Paleozoic Earth System and Biotic Response collection available at:
https://www.lyellcollection.org/topic/collections/chemical-evolution-of-the-mid-paleozoic-earth-system
Natural Language Processing System for Text Classification Corpus Based on Machine Learning
Authors: Su Yawen
Published: February 2024

A classification system for hazardous materials in air traffic control was investigated using the Human Factors Analysis and Classification System (HFACS) framework and natural language processing to prevent hazardous situations in air traffic control. Based on the development of the HFACS standard, an air traffic control hazard classification system will be created. The dangerous data of the aviation safety management system is selected by dead bodies, classified and marked in five levels. Time Frame Return Frequency TextRank text classification method based on key content extraction and text classification model based on Convolutional Neural Network and Bidirectional Encoder Representations from Transforms models were used in the experiment to solve the problem of small samples, many labels and random samples in hazardous environment of air pollution control. The results show that the total cost of model training time and classification accuracy is the highest when the keywords are around 8. As the number of points increases, the time spent in dimensioning decreases and affects accuracy. When the number of points reaches about 93, the time spent in determining the size increases, but the accuracy of the allocation remains close to 0.7, but the increase in the value of time leads to a decrease in the total cost. It has been proven that extracting key content can solve text classification problems for small companies and contribute to further research in the development of security systems.
Dual-Side Adversarial Learning Based Fair Recommendation for Sensitive Attribute Filtering
Authors: Liu Shenghao , Zhang Yu , Yi Lingzhi , Deng Xianjun , Yang Laurence T. , Wang Bang
Published: February 2024

With the development of recommendation algorithms, researchers are paying increasing attention to fairness issues such as user discrimination in recommendations. To address these issues, existing works often filter users’ sensitive information that may cause discrimination during the process of learning user representations. However, these approaches overlook the latent relationship between items’ content attributes and users’ sensitive information. In this article, we propose DALFRec, a fairness-aware recommendation algorithm based on user-side and item-side adversarial learning to mitigate the effects of sensitive information on both sides of the recommendation process. First, we conduct a statistical analysis to demonstrate the latent relationship between items’ information and users’ sensitive attributes. Then, we design a dual-side adversarial learning network that simultaneously filters out users’ sensitive information on the user and item side. Additionally, we propose a new evaluation strategy that leverages the latent relationship between items’ content attributes and users’ sensitive attributes to better assess the algorithm’s ability to reduce discrimination. Our experiments on three real datasets demonstrate the superiority of our proposed algorithm over state-of-the-art methods.
AxOMaP
: Designing FPGA-based

A

ppro

x

imate Arithmetic

O

perators using

Ma

thematical

P

rogramming
Authors: Sahoo Siva Satyendra , Ullah Salim , Kumar Akash
Published: February 2024

With the increasing application of machine learning (ML) algorithms in embedded systems, there is a rising necessity to design low-cost computer arithmetic for these resource-constrained systems. As a result, emerging models of computation, such as approximate and stochastic computing, that leverage the inherent error-resilience of such algorithms are being actively explored for implementing ML inference on resource-constrained systems. Approximate computing (AxC) aims to provide disproportionate gains in the power, performance, and area (PPA) of an application by allowing some level of reduction in its behavioral accuracy (BEHAV). Using approximate operators (AxOs) for computer arithmetic forms one of the more prevalent methods of implementing AxC. AxOs provide the additional scope for finer granularity of optimization, compared to only precision scaling of computer arithmetic. To this end, the design of platform-specific and cost-efficient approximate operators forms an important research goal. Recently, multiple works have reported the use of AI/ML-based approaches for synthesizing novel FPGA-based AxOs. However, most of such works limit the use of AI/ML to designing ML-based surrogate functions that are used during iterative optimization processes. To this end, we propose a novel data analysis-driven mathematical programming-based approach to synthesizing approximate operators for FPGAs. Specifically, we formulate
mixed integer quadratically constrained programs
based on the results of correlation analysis of the characterization data and use the solutions to enable a more directed search approach for evolutionary optimization algorithms. Compared to traditional evolutionary algorithms-based optimization, we report up to 21% improvement in the hypervolume, for joint optimization of PPA and BEHAV, in the design of signed 8-bit multipliers. Further, we report up to 27% better hypervolume than other state-of-the-art approaches to DSE for FPGA-based application-specific AxOs.
Uromodulin in sepsis and severe pneumonia: a two-sample Mendelian randomization study
Authors: Eriksson Mikael , Lipcsey Miklós , Ilboudo Yann , Yoshiji Satoshi , Richards Brent , Hultström Michael
Published: February 2024

The presence of acute kidney injury in severe infections increases the likelihood of poor outcome severalfold. A decrease in serum uromodulin (sUMOD), synthetized in the kidney, has been proposed as a mediator of this effect. Using the Mendelian randomization technique, we tested the hypothesis that increased sUMOD is protective in severe infections. Analyses, however, showed no evidence of a protective effect of higher levels of sUMOD in sepsis or severe pneumonia.
Reliable Breast Cancer Diagnosis with Deep Learning: DCGAN‐Driven Mammogram Synthesis and Validity Assessment
Authors: Shah Dilawar , Ullah Khan Mohammad Asmat , Abrar Mohammad
Published: February 2024

Breast cancer imaging is paramount to quickly detecting and accurately evaluating the disease. The scarcity of annotated mammogram data presents a significant obstacle when building deep learning models that can produce reliable outcomes. This paper proposes a novel approach that utilizes deep convolutional generative adversarial networks (DCGANs) to effectively tackle the issue of limited data availability. The main goal is to produce synthetic mammograms that accurately reproduce the intrinsic patterns observed in real data, enhancing the current dataset. The proposed synthesis method is supported by thorough experimentation, demonstrating its ability to reproduce diverse viewpoints of the breast accurately. A mean similarity assessment with a standard deviation was performed to evaluate the credibility of the synthesized images and establish the clinical significance of the data obtained. A thorough evaluation of the uniformity within each class was conducted, and any deviations from each class’s mean values were measured. Including outlier removal using a specified threshold is a crucial process element. This procedure improves the accuracy level of each image cluster and strengthens the synthetic dataset’s general dependability. The visualization of the class clustering results highlights the alignment between the produced images and the inherent distribution of the data. After removing outliers, distinct and consistent clusters of homogeneous data points were observed. The proposed similarity assessment demonstrates noteworthy effectiveness, eliminating redundant and dissimilar images from all classes. Specifically, there are 505 instances in the normal class, 495 instances in the benign class, and 490 instances in the malignant class out of 600 synthetic mammograms for each class. To check the further validity of the proposed model, human experts visually inspected and validated synthetic images. This highlights the effectiveness of our methodology in identifying substantial outliers.
Higher Atherogenic Index of Plasma Is Associated with Hyperuricemia: A National Longitudinal Study
Authors: Xu Feifei , Ma Chengyong , Wang Shouping , Li Qin , Zhang Zhongwei , He Min
Published: February 2024

Background. The association between atherogenic index of plasma (AIP) and hyperuricemia remains indistinct. This study was aimed to examine the relationship between AIP and hyperuricemia among the middle-aged and the elderly Chinese population. Methods. Datasets were retrieved from the China Health and Retirement Longitudinal Study (CHARLS) survey conducted in 2011 and 2015. 13,021 participants in the CHARLS in 2011 and 7,017 participants involved both in 2011 and 2015 were included, respectively. The measurement of AIP and hyperuricemia was based on the test of fasting blood. Association between AIP and hyperuricemia was assessed by logistic regression, and the nonlinear association was examined by restricted cubic splines (RCS). The cutoff point of AIP was calculated using receiver operator curve (ROC). 1 : 1 propensity score matching (PSM) was adopted to further explore the relationship between AIP and hyperuricemia. Results. In the section of a cross-sectional study, a positive association between AIP and hyperuricemia was found. The odds ratios (ORs) of hyperuricemia were 1.00 (reference), 1.52 (1.10–2.10), 1.80 (1.31–2.47), and 3.81 (2.84–5.11). Nonlinear association was not detected using RCS analysis. There were 664 hyperuricemia cases during the four years follow-up. The hyperuricemia prevalence was 9.5%. In the fully adjusted longitudinal analysis, the ORs for hyperuricemia across the quartiles of AIP were 1.00 (reference), 1.00 (0.74–1.37), 1.59 (1.20–2.11), and 2.55 (1.94–3.35), respectively. In the longitudinal analysis after PSM, the OR of hyperuricemia were 1.91 (1.45, 2.51) and 1.92 (1.45, 2.54) in the univariate and multivariate model, respectively. Conclusion. AIP can predict the prevalence of hyperuricemia in the Chinese middle-aged and elderly population.
Cultural Myths, Superstitions, and Stigma Surrounding Dementia in a UK Bangladeshi Community
Authors: Hussain Nazmul , Clark Andrew , Innes Anthea
Published: February 2024

The last three census data highlighted that UK Bangladeshi communities have the worst health outcomes. This includes a higher risk of type two diabetes and heart diseases; both are risk factors for developing vascular dementia. However, little is known about Bangladeshi community members’ understandings of dementia, including cultural myths. This paper focuses on the cultural myths, superstitions, and stigma surrounding dementia in an English Bangladeshi community from the direct experiences of people living with dementia, their caregivers, and the views of dementia service providers/stakeholders. This qualitative research was undertaken with three distinct participant groups using semistructured interviews (n = 25), who were recruited from community settings. The first and second participant groups explored the experiences of people with dementia (n = 10) and their family caregivers (n = 10). The third group examined stakeholders’/service providers’ views (n = 5). Interviews were recorded digitally and transcribed verbatim. Findings were reached using an interpretive approach, emphasising the sense people make in their own lives and experiences and how they frame and understand dementia. The study revealed that participants with dementia and their caregivers have “alternative” knowledge about dementia and do not necessarily understand dementia in a Westernised scientific/biomedical context. Misconceptions about dementia and belief in various myths and superstitions can lead people to go to spiritual healers or practice traditional remedies rather than to their GPs, delaying their dementia diagnosis. This paper concludes that there is a lack of awareness among the Bangladeshi participants and a need for targeted awareness about dementia to help dispel cultural myths and combat the stigma surrounding dementia within the Bangladeshi community.
The Effect of Motivational Incentives and Time Perspectives on Predicting Youth Emigration Intentions and the Agency of Potential Migrants: The Case of Serbia
Authors: Polovina Nada , Tošković Oliver ,   University of Belgrade, Faculty of Philosophy, Laboratory for Experimental Psychology, Belgrade, Gundogan Dragana ,   Institute for Educational Research, Belgrade
Published: February 2024

This article aims to test the predictive potential of frequently researched socio-demographic and motivational incentives and time perspectives as a still unexplored personal-level factor affecting the strength of youth emigration intentions and the agency of potential migrants (i.e., activities related to emigration). We tested the incremental validity of motivational incentives and time perspectives in predicting emigration intention and potential migrants’ agency, after accounting for socio-demographic variables. Furthermore, to strengthen the estimation of the effect of education on outmigration propensity, we included respondents’ grade attainment in their current educational level (upper secondary education), their highest intended level of education, and their parents’ level of education. Drawing on psychosocial conceptualisations (Bandura, 2001; Zimbardo and Boyd, 1999) this quantitative study was conducted on a representative sample of 1973 students enrolled in the final grade of upper secondary schools in Serbia. A three-step hierarchical multiple regression analysis was employed for this purpose. The results reveal that emigration intention, as well as potential migrants’ agency, cannot be predicted only based on socio-demographic characteristics. However, motivational incentives are important correlates of both emigration intention and migrants’ agency. Social motivation¬al incentives tend to reduce both emigration intention and migrants’ agency, while economy-related motivational incentives tend to increase emigration intention and migrants’ agency. On the other hand, while time perspectives are not significantly agency. Concretely, present hedonistic and future time perspective orientations tend to increase migrants’ agency. The findings indicate the need for a more differentiated approach in theoretical, empirical and policy considerations.
Unraveling the Therapeutic Benefit of Sequenced Chemo-immunotherapy
Authors: Vignali Paolo D.A. , Luke Jason J.
Published: February 2024

Combination immune-checkpoint inhibition with chemotherapy is a clinical standard, yet concurrent administration may limit the full benefit of immunotherapy by blunting the proliferation and differentiation of CD8 T cells. Identifying patients in whom sequential chemo-immunotherapy or immunotherapy alone is feasible should be a priority to optimize long-term outcomes.

See related article by Mariniello et al., p. 1833
Supplementary Figure 1 from Anti-Vα24Jα18 TCR Antibody Tunes iNKT Cell Responses to Target and Kill CD1d-negative Tumors in an FcγRII (CD32)-dependent Manner
Authors: Takami Mariko , Aoki Takahiro , Nishimura Katsuhiro , Tanaka Hidekazu , Onodera Atsushi , Motohashi Shinichiro
Published: February 2024

Cytotoxic activity of iNKT cells toward K562 cells gradually decreases daily.