bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dairy farmers’ levels of awareness of antibiotic use in livestock farming in Pakistan
Authors: Farhan Muhammad , Awan Namra , Kanwal Amina , Sharif Faiza , Hayyat Muhammad Umar , Shahzad Laila , Ghafoor Gul Zareen 
Published: January 2024

AbstractAntimicrobial resistance due to the irrational and non-sustainable use of antimicrobials poses a serious threat to animal health, human health and urban food security. This study aimed to access the knowledge and perceptions of dairy farmers regarding antimicrobial use and misuse in Lahore, Pakistan. This is the first study regarding antibiotic misuse in Lahore, Pakistan. A random sample of 270 dairy farmers from urban and suburban areas of Lahore participated in an interview-based survey conducted in 2019–20. The results were analyzed using SPSS version 16. About 22% of farmers do not consult a veterinarian, 32.9% do not follow correct dosage instructions and 39% discontinue treatment once the disease signs subside. Moreover, 40% of farmers were unaware of the dangers of misusing antibiotics and admitted to saving leftover antibiotics for future use. Alarmingly, over 20.7% of respondents share antibiotics with friends/farmers and 43% sought advice from non-veterinarian sources. Furthermore, 90% of farmers perceived self-medication as more economical than consulting a veterinarian. Dairy farmers have a wrong perception of antibiotic efficacy, use, expertise of veterinarians and cost of antibiotics. The absence of a food policy and lack of antibiotic use guidance is a serious gap in Pakistan. Antibiotic dispensing laws need to be developed and strictly implemented. Awareness campaigns need to be launched so that farmers get knowledge regarding the uses, overuse and misuse of antibiotics. A holistic approach is essential to address the potential food security crisis caused by non-sustainable farming practices. Policymakers must take action to bridge the gap in the Pakistani food supply chain and promote the sustainable use of antimicrobials/antibiotics.
Reinvestigating the environmental Kuznets curve (EKC) of carbon emissions and ecological footprint in 147 countries: a matter of trade protectionism
Authors: Wang Qiang , Wang Xiaowei , Li Rongrong , Jiang Xueting 
Published: January 2024

AbstractEnvironmental degradation has profoundly impacted both human society and ecosystems. The environmental Kuznets curve (EKC) illuminates the intricate relationship between economic growth and environmental decline. However, the recent surge in trade protectionism has heightened global economic uncertainties, posing a severe threat to global environmental sustainability. This research aims to investigate the intricate pathways through which trade protection, assessed by available trade openness data, influences the nexus between economic growth and environmental degradation. Leveraging comprehensive global panel data spanning 147 countries from 1995 to 2018, this study meticulously examines the non-linear dynamics among trade, economy, and the environment, with a particular emphasis on validating the EKC hypothesis. This study encompasses exhaustive global and panel data regressions categorized across four income groups. The research substantiates the validity of the EKC hypothesis within the confines of this investigation. As income levels rise, the impact of economic growth on environmental degradation initially intensifies before displaying a diminishing trend. Additionally, trade protection manifests as a detriment to improving global environmental quality. The ramifications of trade protectionism display nuanced variations across income strata. In high-income nations, trade protection appears to contribute to mitigating environmental degradation. Conversely, within other income brackets, the stimulating effect of trade protection on environmental pressure is more conspicuous. In other words, trade protectionism exacerbates environmental degradation, particularly affecting lower-income countries, aligning with the concept of pollution havens. The study’s results illuminate nuanced thresholds in the relationship between trade, economic growth, and environmental degradation across income groups, emphasizing the heterogeneous impact and underlying mechanisms. These findings provide valuable insights for policymakers, urging collaborative efforts among nations to achieve a harmonious balance between economic advancement and environmental preservation on a global scale.
Label-free and non-destructive histology of unprocessed biological tissues with ultraviolet single-plane illumination microscopy
Authors: Zhang Yan , Huang Bingxin , Dai Weixing , Kang Lei , Tsang Victor T. C. , Wu Jiajie , Lo Claudia T. K. , Wong Terence T. W. 
Published: January 2024

Histopathology has remained the gold standard for surgical margin assessment for decades. However, routine pathological examination based on formalin-fixed and paraffin-embedded (FFPE) tissues is laborious and time-consuming, failing to guide surgeons intraoperatively. Here, we propose a rapid, label-free, and non-destructive histological imaging method, termed microscopy with ultraviolet single-plane illumination (MUSI). With intrinsic fluorescence from deep ultraviolet excitation, MUSI enables both ex vivo and in vivo imaging of fresh and unprocessed tissues at the subcellular level with an imaging speed of 0.5 mm2/s, generating high-quality optically sectioned surface images from irregular surgical tissues with a long depth-of-field. We demonstrate that MUSI could differentiate between different subtypes of human lung adenocarcinomas (e.g., lepidic, acinar, papillary, and micropapillary), revealing diagnostically important features that are comparable to the gold standard FFPE histology. As an assistive imaging platform, MUSI can provide immediate feedback to surgeons and pathologists for intraoperative decision-making, holding great promise to revolutionize the current clinical practice in surgical pathology.
Wearable temperature sensor with moisture resistance based on MXene-embedded fiber
Authors: Yang Jonguk , Lee Jeong Hui , Lim Taekyung , Seo Hee Sung , Seo Keumyoung , Jeong Sang-Mi , Ju Sanghyun 
Published: January 2024

As climate change intensifies, summer temperatures are gradually rising, resulting in an increase in heat-related illnesses among individuals exposed to heatwaves. Consequently, wearable sensors for external environmental monitoring are gaining prominence as personal healthcare and safety diagnosis systems. Wearable temperature sensors must provide stable sensing even when subjected to various external environmental changes, such as repetitive movement, humidity, and water contact. In this study, a fiber-type temperature sensor with an embedded MXene (Ti3C2Tx) was fabricated. MXene was synthesized by etching aluminum (Al) from Ti3AlC2 (MAX phase powder) using a mixture of Li salt and hydrochloric acid (HCl) and then prepared as an aqueous dispersion. Subsequently, conductive fibers were fabricated by embedding MXene into polyester fibers via a dipping–drying process. To mitigate susceptibility to moisture, hydrophobic 3,3,4,4,5,5,6,6,7,7,8,8,9,9,10,10,10-heptadecafluorodecylphosphonic acid (HDF-PA) was applied to the surface of the MXene embedded in the fiber, providing hydrophobicity. The temperature range of 0–50 °C was monitored by measuring the resistance change in the fabricated HDF-PA-coated MXene-embedded fiber. Furthermore, sensing characteristics remained robust even under a bending radius of 15–3 mm. In addition, the sensor was confirmed to operate stably despite physical deformation from repeated bending up to 1000 times, as well as exposure to 50%–90% RH and 1 h of immersion in water, demonstrating excellent durability and water resistance.
Extraordinary transmission of intense short laser pulse through thin foil with near- and sub-wavelength slits
Authors: Lu Sidailuo , Zhang Xiaohai , Sheng Zhengmao , Yu Ming-Young 
Published: January 2024

To supplement our earlier study [Lu et al., AIP Adv. 10, 015209 (2020)] on the propagation of intense short laser pulse through foils with multiple sub-wavelength sized slits, here, we consider the effects of the interaction parameters on the occurrence of extremums in the light transmission. Our results suggest that for periodic slit distribution, maximum and minimum transmissions occur for L ± d = κλ and L = κλ, respectively, where L and d are the period and width of the slits, respectively, λ is the laser wavelength, and κ is a positive integer or a rational number.
Reverse effects of pre-deformation and traverse speed on the mechanical properties of friction stir processed pure copper
Authors: Mazaheri Hoora , Aval Hamed Jamshidi , Jamaati Roohollah 
Published: January 2024

Abstract
In the present work, the effects of pre-strain and traverse speed on the microstructural evolution and tensile behavior of friction stir processed (FSPed) pure copper were investigated. In the samples without pre-deformation (0% samples), with the increment of the traverse speed from 100 mm min−1 to 200 mm min−1, the grain size decreased from 5.2 to 2.5 μm due to heat input domination. In the 60% pre-rolled samples (60% samples), interestingly, with an increase in the traverse speed (from 100 mm min−1 to 200 mm min−1), the average grain size increased from 2.4 to 6.8 μm owing to the domination of deformation degree. With the increment of speed from 100 mm min−1 to 200 mm min−1 in the 0% samples, the YS and UTS increased from 158.6 and 244.6 MPa to 190.7 and 253.9 MPa, respectively, due to decrement in the mean grain size. In addition, the increment of speed from 100 mm min−1 to 200 mm min−1 in the 60% samples reduced the YS and UTS from 177.9 and 261.7 MPa to 138.9 and 234.8 MPa, respectively, due to the increase in the mean grain size. In the 0% FSPed copper, by increasing the speed, the depth and size of dimples reduced, while, in the 60% FSPed samples, when the traverse speed increased, the dimples became larger.
Low power CNTFET-based ternary multiplier for digital signal processing applications
Authors: Chauhan Katyayani , Bansal Deepika 
Published: January 2024

Abstract
Multiplication is a fundamental arithmetic process, although it necessitates more hardware resources. Researchers in advanced technology attempted to boost the speed and lower the power in digital signal processing applications by utilizing multipliers. The majority of digital signal processing applications demanded increased speed. In addition, ternary logic based on CNTFETs is a feasible alternative for Si-MOSFETs. The article proposes a ternary multiplier, which is designed using proposed ternary logical and combinational circuits that includes STI, TNAND, TNOR, and ternary decoder. The proposed and existing designs are simulated, compared, and analysed on the parameters of delay, average power, and noise using the HSPICE simulator. Therefore, the results show 10%, 81% and 81% improvement in delay, average power, and PDP respectively for proposed TMUL. The noise margin of the proposed TMUL is increased up to 54% over existing circuits. The proposed TDecoder, STI, TNAND, and TNOR are 95%, 97%, 81%, and 95% more energy efficient than existing designs, respectively.
The effects of resourcefulness-based instrumental reminiscence therapy on psychological adjustment in nursing home residents: a randomised controlled trial
Authors: Pan Xiaohui , Huang Qiyuan , Zhang Zhefu , Liu Huangqin , Xiao Huimin 
Published: January 2024

Abstract

Background
Older adults do not always adapt successfully to nursing homes. Learning resourcefulness and instrumental reminiscence may contribute to the psychological adjustment made by nursing home residents. How both attributes can be combined to enhance residents’ adjustment remains unclear.

Objectives
This study examined the effects of resourcefulness-based instrumental reminiscence therapy (RBIRT) on psychological adjustment, learned resourcefulness, self-efficacy, social support and quality of life (QoL) of nursing home residents.

Methods
A randomised, controlled, assessor-blinded, parallel-arm trial was conducted between January 2022 and February 2023 in Fujian, China, with 120 participants (intervention = 60, comparison = 60) from two separate nursing homes. The intervention group participants received a 6-week RBIRT, involving Reminiscence Interview, Emotional Venting, Reconstruction Strategies, Planning for the Future and Strengthening Support. The control group participants received routine institutional care. Participants were assessed using the Nursing Home Adjustment Scale, Resourcefulness Scale, General Self-efficacy Scale, Perceived Social Support Scale and the 12-item Short-Form Health Survey. Outcomes were evaluated at baseline (T0), immediately post intervention (T1) and at 1-month (T2) and 3-months (T3) post-intervention.

Results
Participants in the intervention group showed significant improvement in ‘psychological adjustment,’ ‘learned resourcefulness,’ ‘self-efficacy,’ ‘social support’ and ‘QoL-mental health dimension’ compared to the control group (P &lt; 0.001). These effects were sustained at the 1- and 3-month follow-ups.

Conclusions
Innovative RBIRT improved psychological adjustment, learned resourcefulness, self-efficacy, social support and mental health-related QoL among nursing home residents.
Baclofen in the treatment of alcohol use disorder: tailored doses matter
Authors: de Beaurepaire Renaud , Jaury Philippe 
Published: January 2024

AbstractAimsTo address the question of tailored baclofen prescribing in alcohol use disorder (AUD) in relation to dose-dependent efficacy and the potential danger of high doses and to provide suggestions for the use of high doses of baclofen in the treatment of AUD. The context is the approvement in France of baclofen in the treatment of AUD without dose limitation, making French physicians, who usually prescribe baclofen in a tailored manner, often use high or very high doses.MethodsA narrative review of the results of randomized controlled trials (RCTs) and observational studies that used tailored baclofen prescribing and of the severe adverse effects of baclofen that have been reported in the literature.ResultsThe results show that RCTs using tailored doses of baclofen in AUD are not completely demonstrative, though they are encouraging according to certain meta-analyses, while observational studies that used tailored doses constantly show a good effectiveness of baclofen treatment. The results suggest that many severe adverse effects of baclofen could be related to a nonrespect by physicians of prescription rules and appropriate treatment monitoring.ConclusionsThe use of tailored doses shows that the dose required to suppress cravings is highly variable, low or high, depending on each case. Analysis of the circumstances in which severe adverse effects occur suggest that a careful monitoring of baclofen prescribing might prevent a large majority of severe adverse effects. We propose that the education of the patients and the prescription skills, seriousness, and availability of the prescribing physicians are of major importance in the managing of tailored baclofen treatment of AUD.
SPREd: a simulation-supervised neural network tool for gene regulatory network reconstruction
Authors: Wu Zijun , Sinha Saurabh 
Published: January 2024

AbstractSummaryReconstruction of gene regulatory networks (GRNs) from expression data is a significant open problem. Common approaches train a machine learning (ML) model to predict a gene’s expression using transcription factors’ (TFs’) expression as features and designate important features/TFs as regulators of the gene. Here, we present an entirely different paradigm, where GRN edges are directly predicted by the ML model. The new approach, named “SPREd,” is a simulation-supervised neural network for GRN inference. Its inputs comprise expression relationships (e.g. correlation, mutual information) between the target gene and each TF and between pairs of TFs. The output includes binary labels indicating whether each TF regulates the target gene. We train the neural network model using synthetic expression data generated by a biophysics-inspired simulation model that incorporates linear as well as non-linear TF–gene relationships and diverse GRN configurations. We show SPREd to outperform state-of-the-art GRN reconstruction tools GENIE3, ENNET, PORTIA, and TIGRESS on synthetic datasets with high co-expression among TFs, similar to that seen in real data. A key advantage of the new approach is its robustness to relatively small numbers of conditions (columns) in the expression matrix, which is a common problem faced by existing methods. Finally, we evaluate SPREd on real data sets in yeast that represent gold-standard benchmarks of GRN reconstruction and show it to perform significantly better than or comparably to existing methods. In addition to its high accuracy and speed, SPREd marks a first step toward incorporating biophysics principles of gene regulation into ML-based approaches to GRN reconstruction.Availability and implementationData and code are available from https://github.com/iiiime/SPREd.
The predictive capacity of polygenic risk scores for disease risk is only moderately influenced by imputation panels tailored to the target population
Authors: Levi Hagai , Elkon Ran , Shamir Ron 
Published: January 2024

Abstract

Motivation
Polygenic risk scores (PRSs) predict individuals’ genetic risk of developing complex diseases. They summarize the effect of many variants discovered in genome-wide association studies (GWASs). However, to date, large GWASs exist primarily for the European population and the quality of PRS prediction declines when applied to other ethnicities. Genetic profiling of individuals in the discovery set (on which the GWAS was performed) and target set (on which the PRS is applied) is typically done by SNP arrays that genotype a fraction of common SNPs. Therefore, a key step in GWAS analysis and PRS calculation is imputing untyped SNPs using a panel of fully sequenced individuals. The imputation results depend on the ethnic composition of the imputation panel. Imputing genotypes with a panel of individuals of the same ethnicity as the genotyped individuals typically improves imputation accuracy. However, there has been no systematic investigation into the influence of the ethnic composition of imputation panels on the accuracy of PRS predictions when applied to ethnic groups that differ from the population used in the GWAS.

Results
We estimated the effect of imputation of the target set on prediction accuracy of PRS when the discovery and the target sets come from different ethnic groups. We analyzed binary phenotypes on ethnically distinct sets from the UK Biobank and other resources. We generated ethnically homogenous panels, imputed the target sets, and generated PRSs. Then, we assessed the prediction accuracy obtained from each imputation panel. Our analysis indicates that using an imputation panel matched to the ethnicity of the target population yields only a marginal improvement and only under specific conditions.

Availability and implementation
The source code used for executing the analyses is this paper is available at https://github.com/Shamir-Lab/PRS-imputation-panels.
3D Optical Coherence Tomography image processing in BISCAP: characterization of biofilm structure and properties
Authors: Narciso Diogo A C , Pereira Ana , Dias Nuno O , Monteiro Manuel , Melo Luis F , Martins Fernando G 
Published: January 2024

Abstract

Motivation
BISCAP is a state-of-the-art tool for automatically characterizing biofilm images obtained from Optical Coherence Tomography. Limited availability of other software tools is reported in the field. BISCAP’s first version processes 2D images only. Processing 3D images is a problem of greater scientific relevance since it deals with the entire structure of biofilms instead of their 2D slices.

Results
Building on the image-processing principles and algorithms proposed earlier for 2D images, these were adapted to the 3D case, and a more general implementation of BISCAP was developed. The primary goal concerns the extension of the initial methodology to incorporate the depth axis in 3D images; multiple improvements were also made to boost computational performance. The calculation of structural properties and visual outputs was extended to offer new insights into the 3D structure of biofilms. BISCAP was tested using 3D images of biofilms with different morphologies, consistently delivering accurate characterizations of 3D structures in a few minutes using standard laptop machines. Low user dependency is required for image analysis.

Availability and implementation
BISCAP is available from https://github.com/diogonarciso/BISCAP. All images used in the tutorials and the validation examples are available from https://web.fe.up.pt/∼fgm/biscap3d.
Post-stroke upper limb recovery is correlated with dynamic resting-state network connectivity
Authors: Tang Chih-Wei , Zich Catharina , Quinn Andrew J , Woolrich Mark W , Hsu Shih-Pin , Juan Chi-Hung , Lee I Hui , Stagg Charlotte J 
Published: January 2024

Abstract
Motor recovery is still limited for people with stroke especially those with greater functional impairments. In order to improve outcome, we need to understand more about the mechanisms underpinning recovery. Task-unbiased, blood flow–independent post-stroke neural activity can be acquired from resting brain electrophysiological recordings and offers substantial promise to investigate physiological mechanisms, but behaviourally relevant features of resting-state sensorimotor network dynamics have not yet been identified. Thirty-seven people with subcortical ischaemic stroke and unilateral hand paresis of any degree were longitudinally evaluated at 3 weeks (early subacute) and 12 weeks (late subacute) after stroke. Resting-state magnetoencephalography and clinical scores of motor function were recorded and compared with matched controls. Magnetoencephalography data were decomposed using a data-driven hidden Markov model into 10 time-varying resting-state networks. People with stroke showed statistically significantly improved Action Research Arm Test and Fugl-Meyer upper extremity scores between 3 weeks and 12 weeks after stroke (both P &lt; 0.001). Hidden Markov model analysis revealed a primarily alpha-band ipsilesional resting-state sensorimotor network which had a significantly increased life-time (the average time elapsed between entering and exiting the network) and fractional occupancy (the occupied percentage among all networks) at 3 weeks after stroke when compared with controls. The life-time of the ipsilesional resting-state sensorimotor network positively correlated with concurrent motor scores in people with stroke who had not fully recovered. Specifically, this relationship was observed only in ipsilesional rather in contralesional sensorimotor network, default mode network or visual network. The ipsilesional sensorimotor network metrics were not significantly different from controls at 12 weeks after stroke. The increased recruitment of alpha-band ipsilesional resting-state sensorimotor network at subacute stroke served as functionally correlated biomarkers exclusively in people with stroke with not fully recovered hand paresis, plausibly reflecting functional motor recovery processes.