bluuebunny/crossref_metadata_2025_split huggingface dataset:
Faktor Determinasi Kinerja Guru Madrasah (Studi di MTs Se-Kecamatan Slahung)
Authors: Sholahuddin Afif Fanani  , Fadli Wirawan 
Published: July 2023

Guru memberikan peran penting dalam sistem pendidikan untuk meningkatkan pembelajaran siswa yang penting bagi kesuksesan masa depan mereka. Kinerja guru memiliki pengaruh langsung terhadap pembelajaran siswa dan kemajuan siswa adalah standar yang digunakan untuk menilai kinerja guru. Penelitian ini bertujuan untuk : (1) mengetahui pengaruh iklim kerja terhadap kinerja guru di MTs Se-Kecamatan Slahung, (2) mengetahui pengaruh gaya kepemimpinan kepala madrasah terhadap kinerja guru di MTs Se-Kecamatan Slahung, (3) mengetahui pengaruh iklim kerja dan gaya kepemimpinan kepala madrasah terhadap kinerja guru di MTs Se-Kecamatan Slahung. Jenis peneilitian ini adalah kuantitatif deskriptif. Sampel dalam penelitian ini adalah 100 orang. Pengumpulan data menggunakan angket atau kuesioner. Analisa data dengan menggunakan hasil uji dan regresi berganda. Hasil penelitian Variabel iklim kerja di MTs Kecamatan Slahung secara parsial berpengaruh secara signifikan terhadap kinerja guru MTs. Kecamatan Slahung. Diperoleh nilai t hitung sebesar 2,579 dengan nilai sig. sebesar 0,011. Nilai tersebut lebih besar apabila dibandingkan dengan nilai t tabel yang bernilai 1,661. Variabel kepemimpinan tidak mempengaruhi secara parsial kinerja guru MTs Se-Kecamatan Slahung. Dari hasil analisis diperoleh nilai t hitung sebesar 1,620, apabila dibandingkan dengan nilai t tabel sebesar 1,661, nilai t hitung lebih kecil dari t tabel (1,620 < 1,661) sehingga hipotesis dalam penelitian ini ditolak. Secara simultan terdapat pengaruh yang signifikan dari variabel iklim kerja dan gaya kepemimpinan terhadap variable kinerja guru MTs Se-Kecamatan Slahung Ponorogo. Hal tersebut berdasarkan hasil analisis uji F yang telah dilakukan, diperoleh nilai F hitung>F tabel (4,055> 3,09).
CRMetrics - an R package for Cell Ranger Filtering and Metrics Visualisation
Authors: Kick Fabienne Lorena , Holze Henrietta , Rydbirk Rasmus , Khodosevich Konstantin 
Published: July 2023

Abstract
Several pipelines exist for analysis of single-cell or single-nucleus RNA-sequencing (sxRNA-seq) data in multiple programming languages. Although filtering and quality control (QC) of data as preprocessing steps are included in several analytical pipelines, visual assessment of filtered cells is often lacking. Here, we present a streamlined pipeline for filtering of sxRNA-seq data and visualisation of every filtering step using existing software packages. This includes methods to remove ambient RNA, doublets, cells with a high fraction of mitochondrial genes expressed, and cells with low sequencing depth that are difficult to cluster and annotate. All steps are accompanied by plotting functions to ease the selection of thresholds for these crucial steps in data preprocessing.
Genome wide association study in goat identified novel SNPs and genes for growth
Authors: Moaeen-ud-Din Muhammad , Khan Muhammad Sajjad , Muner Raja Danish , Reecy James M. 
Published: July 2023

Abstract

A higher body weight at a younger age is an economically important trait for profitable goat farming. This study was focused on the identification of regions of the genome that harbor genetic variants associated with body weight using the Illumina GoatSNP50K Bead Chip. A total of 631 purebred Beetal goats (151 males and 480 females) were recorded for body weight, age and body measurement and then genotyped. Genome wide association analysis was carried out with GEMMA. After application of quality control filters with Plink 1.9, call rate less or equal than 0.9, minor allele frequency less than 0.05 and HWE P value lesser than 0.001, 594 animals and 45,744 SNPs were retained for association analysis. The association analysis for body weight with covariates of age, sex and morphometric measurements and contemporary group yielded 10 significant SNPs (P = -log10e-4 to -log10e-6). Three associated SNPs were within genes i.e.,BTAF1, NTMandGRID1when blasted against ARS1(accession GCA_001704415.1). Moreover, some associated SNPs were localized close toCEP78, ROBO1, ZFP36L2, SPTLC3, CTR9andZFHX3genes. The study identified SNPs and genes with potential role in growth of goat.
PDGF-D is de novo expressed after stroke and contributes to neurovascular protection by rescuing the function of pericytes
Authors: Bernard Maxime , Menet Romain , Lecordier Sarah , ElAli Ayman 
Published: July 2023

Abstract
Ischemic stroke induces an angiogenic response at the lesion site to improve tissue vascularization, as an attempt to promote repair. Brain pericytes, which are critically involved in regulating neurovascular functions, potently respond to stroke stressors, varying from death to detachment. Platelet-derived growth factor (PDGF) receptor (PDGFR)β plays a central role in pericyte survival, proliferation, migration, and recruitment to endothelial cells. The role of PDGF-D, a recently identified ligand that specifically binds and activates PDGFRβ, in ischemic stroke pathobiology, remains unexplored. Herein, we show that PDGF-D is transiently induced in vascular structures at the lesion site in experimental ischemic stroke. Attenuation of PDGF-D subacute induction using siRNA exacerbates injury and impairs vascular integrity. Enhancing PDGF-D subacute bioavailability via the intranasal delivery of an active form, attenuates neuronal loss and improves neurological recovery. PDGF-D stimulates the formation of a stable vasculature, improves brain perfusion, and rescues pericyte coverage, associated with an increased expression of insulin growth factor (IGF)1, a vascular protective factor. PDGF-D stimulation enhances the survival of human brain pericytes exposed to ischemic-like conditions in vitro by increasing the expression of B-cell lymphoma (BCL)2, while reducing the expression of neurogenic locus notch homolog (NOTCH)3, involved in pathological fibrosis. PDGF-D stimulation enhances the migratory properties of pericytes exposed to ischemic-like conditions, required for vascular coverage, and induces the release of factors involved in fine-tuning vascular remodeling. Our study provides new insights into the role of PDGF-D in preserving neurovascular functions after stroke by rescuing the function of pericytes, outlining its therapeutic potential.
Variation in GDP and its Link with Ecological Footprint and Air Pollution- A Across Country Analysis
Authors: KUMAR PIYALI 
Published: July 2023

Abstract

This study attempts to detect the relation of ecological footprint and air pollutants- CO2, N2O, SO2& CH4 with economic growth, urbanization, foreign direct investment inflow and energy consumption through Environmental Kuznets Curve (EKC) framework by employing fixed effect and random effect model. This is a comparative study involving panel of 56 selected countries from several income groups- high, middle, low covering the period 1990–2019. A theoretical approach has been undertaken to analyze the pollution intensity of population, based on decomposition analysis coherent with application of the notion of Kaya identity. The results confirmed the existence of N-shaped relationship for the natural resource degradation model in the high and middle income countries. CO2 pollutant exhibits N-shaped pattern of change with economic growth for both high and middle income countries. N2O model confirms the existence of N-shaped EKC for high and low income group and inverse U-shaped curve for middle income group of countries. Further the results of pollution model confirmed the N-shaped relationship of SO2 and CH4 emission with income growth in middle and low income economies. The results suggest that reconsideration of some economic and environmental policies are necessary to mitigate environmental degradation issues.
Development of computationally-guided workflow for designing therapeutic phage cocktail: targeting multidrug-resistant (MDR) bacteria
Authors: Nawaz Rabia , Husnain Ali , Ali Muhammad , Sajjad Moin , Ahad Ammara , Shahid Muhammad , Mehmood Uqba , Razzaq Attia , Khan Idrees 
Published: July 2023

Abstract
Background:
Antibiotic misuse and overuse have contributed to the emergence of multi-drug resistant bacteria (MDR), a serious public health problem across the globe. Phage cocktails, which combine several phages to destroy various bacterial strains, offer a more thorough and efficient method of battling MDR illnesses. This might revolutionize the looming threat of reemergence of untreatable bacterial diseases. To provide a focused strategy to tackle the rising incidence of MDR bacterial infections, a phage cocktail against Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa was intended to be made computationally. Predicting a group of prophages which can successfully lyse and disrupt these three MDR bacterial strains and might help to lessen the severity and occurrence of illnesses caused by these notorious pathogens.
Methods:
The genomes of selected MDR bacteria were accessed through NCBI GenBank, and prophages targeting them were selected. The prophages were further annotated for ORFs, putative promotors, virulence factors, transcriptional terminators, and tRNAs. Dot plot was created to investigate the similar phages and phylogenetic analysis was performed.
Results:
A total of 11 prophages were predicted from three MDR bacterial genomes, the investigation identified 472 ORFs and CDS, rRNA, and tRNA regions in 11 prophage genomes were predicted. The presence of 3 tRNAs encoded by the predicted prophages suggests a possible reliance on the host translation machinery for protein synthesis. The presence of transcription terminators and promotors were detected to understand the transcriptional and translational regulation of prophage genes. The comparative genomic and phylogenetic analyses of predicted prophages provided important insights into diversity and relatedness of the phages. The final selected five prophages included Acinetobacter baumannii prophage (2759376-2809756), Acinetobacter baumannii prophage (3311844-3364667), Klebsiella pneumoniae (1288317-1338719), Klebsiella pneumoniae prophage (1778306-1808606), and Klebsiella pneumoniae prophage (2280703-2325555).
Conclusion:
In conclusion, our work provides an example of developing a phage cocktail to combat multidrug resistant Acinetobacter baumannii and Klebsiella pneumoniae. Sequence similarity analyses revealed that the cocktail is capable of targeting Enterobacter hormaechei and other carbapenemase-producing K. pneumoniae strains also. The phage cocktail indicates the possibility of being employed as a therapeutic agent for reducing harmful bacterial infections, where conventional antibiotic therapeutics fail.
Valproic Acid For Agitation In The Intensive Care Unit: a Retrospective Analysis Of Psychiatric Consults
Authors: White Geneviève , Adessky Noah , Chen Fei-Wen , Regazzoni Anne , Tourian Leon , Chagnon Miguel , Gursahaney Ashvini , Alharbi Majed , Williamson David , Perreault Marc 
Published: July 2023

Abstract
Background
Agitation is a common clinical problem encountered in the intensive care unit (ICU). Treatment options are based on clinical experience and sparse quality literature.
Aim
The aim of this study was to evaluate the effect of valproic acid (VPA) as adjuvant treatment for agitation in the ICU as well as to identify independent predictors of response.
Method
This retrospective single center observational study evaluated adult patients admitted to the ICU for whom a psychiatric consultation was requested for agitation management, with agitation defined as a Richmond Agitation Sedation Score of 2 or greater. A descriptive analysis of the proportion of agitation-free patients per day of follow-up, the incidence of agitation-related-events, as well as the evolution of co-medications use over time are presented. A logistic regression model was used to assess predictors of VPA response, defined as being agitation-free on Day 7 and GEE models were used to evaluate the independent effect of VPA as adjuvant therapy for agitation in the critically ill.
Results
One hundred seventy-five (175) patients were included in the study with 78 receiving VPA. The percentage of agitation-free patients was 6.5% (5/77) on Day 1, 14.1% (11/78) on Day 3 and 39.5% (30/76) on Day 7. Multivariate regression model for clinical and demographic variables identified female gender as predictor of response on Day 7 (OR 6.10 [1.18–31.64], p = 0.03). The independent effect of VPA was non-significant when compared to a control group.
Conclusion
Although VPA used as adjuvant treatment was associated with a decrease in agitation, its effect when compared to a control group did not yield significant results.
Association between gestational exposure and risk of orofacial Clefts: A systematic review and meta-analysis
Authors: Huang ZhiMeng , Wu JinZhun , Qiu Yue , Lin Jiayan , Huang Wanting , Ma Xiaohui , Yang Xiaoqing , zhang huifen 
Published: July 2023

Abstract
Background:
The occurrence of orofacial Clefts (OFCs) is a congenital disease caused by many factors. According to recent studies, air pollution has a strong correlation with the occurrence of OFCs. However, there are still some controversies about the current research results, and there is no relevant research to review the latest results in recent years.
Objective:
In this paper, the authors conducted a systematic review and meta-analysis to explore the correlation between ambient air pollution and the occurrence of neonatal OFCs deformity.
Methods:
We searched Pubmed, Web of science, and Embase databases from the establishment of the database to May 2023. We included observational studies on the relationship between prenatal exposure to fine particulate matter 2.5 (PM2.5), fine particulate matter 10 (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO) and the risk of cleft lip (CL), cleft palate (CP), cleft lip with or without palate (CL/P). the Newcastle-Ottawa quality assessment scale (NOS) was used to evaluate the quality of the literature. Funnel plot and Egger's regression were used to verify the publication bias. Random effect model or fixed effect model was used to estimate the combined relative risk (RR) and 95% confidence interval (95%CI).
Results:
A total of eleven studies were included in this study, including four cohort studies and seven case-control studies, including 22453 cases of OFCs. Ten studies had low risk of bias and only one study had high risk of bias. Three studies reported that PM2.5 was positively correlated with CL and CP, with a combined RR and 95%CI of 1.287(1.174,1.411) and 1.267 (1.105,1.454). Two studies reported a positive correlation between O3 and CL, with a combined RR and 95%CI of 1.132(1.047,1.225). Two studies reported a positive correlation between PM10 and CL, with a combined RR and 95%CI of 1.108 (1.017,1.206). No association was found between SO2, CO, NO2 exposure during pregnancy and the risk of OFCs.
Conclusion:
The results of this study showed that there was a significant statistical correlation between exposure to PM10, PM2.5, O3 and the risk of OFCs in the second month of pregnancy. Exposure assessment, research methods and mechanisms need to be further explored.
Unilateral Intrathoracic Extramedullary Hematopoiesis: A Rare Case Report
Authors: MOHAMMED QUADER NASEER , MOHAMMED AFSHAR ALAM , HOOR IQRA ,   4.	UDAY SANKAR AKASH VANKAYALA, SHAIK SUBHANA MUSQUAN 
Published: July 2023

Abstract

Intrathoracic extramedullary hematopoiesis (ITEMH) is an extremely rare condition characterized by the abnormal proliferation of hematopoietic tissue outside the bone marrow. Here, we present a case of unilateral ITEMH in a 56-year-old male without a history of hematological disorders, which to the best of our knowledge, represents the first reported occurrence of this rare tumor condition. The patient presented with respiratory symptoms and was initially misdiagnosed with a mediastinal mass. Subsequent imaging studies revealed a localized lesion in the left thoracic cavity, which was surgically excised. Histopathological examination confirmed the diagnosis of intrathoracic extramedullary hematopoiesis. This case highlights the importance of considering ITEMH in the differential diagnosis of intrathoracic masses, even in the absence of underlying haematological disorders. Categories: Family/General Practice, Internal Medicine, GEN SURGERY.
Analysis on Novel Feature-Independent CAD Design/Modelling Approach Combined with a Neural Network for Random Parametric 3D Boundary Representation Modelling
Authors: Angajala Nikhil Chaitanya , Balla Srinivasa Prasad , Resapu Rajeswara Reddy 
Published: July 2023

Abstract

In the era of competitive digital innovation, product manufacturing companies need rapid customisation and ability to create uniqueness in new product development to stay competitive in the consumer market. Till recent times, this requirement heavily depended on CAD designer’s ability and experience to produce creative designs. This paper presents a novel feature-independent CAD design/modelling approach combined with a neural network that enables the creation of random parametric 3D CAD design variants using the Boundary Representation (B-Rep) method. This method is rapid and thus offers about 10 to 100 concept alternatives to the client in 10 to 30 minutes. Additionally, the paper also highlights the suitability of the proposed Neural Network method in creating 3D deep learning datasets to train generative design models like 3D GANs to further enhance 3D designs specifically targeted in product design problems.
American Sign Language Detection using YOLOv5 and YOLOv8
Authors: Tyagi Shobhit , Upadhyay Prashant , Fatima Hoor , Jain Sachin , Sharma Avinash Kumar 
Published: July 2023

Abstract

In the modern world, culture and religion are diverse and widespread. Sign language culture had grown since its emergence in the American School for the Deaf (ASD) in 1817. In a world where computers are now solving real-time applications and issues using deep learning, Sign language (SL) is one of those. YOLO is an object detection and classification algorithm that uses Convolutional neural network (CNN) to achieve high performance and accuracy. The paper aims to detect American sign language using YOLO models and compare different YOLO algorithms by implementing a custom model for recognizing sign language. The experiments show that the latest YOLOv8 gave better results than other YOLO versions regarding precision and mAP, while YOLOv7 has a higher recall value during testing than YOLOv8. The proposed model is lightweight, fast and uses the American sign language letters dataset for training and testing. The custom model achieved 95% precision, 97% recall, and 96% mAP @0.5, showing the model capabilities in real-time hand gesture recognition.
Pearl farming micro-nanoplastics affect both oyster physiology and pearl quality
Authors: Gardon Tony , Luyer Jérémy Le , Moullac Gilles Le , Soyez Claude , Lagarde Fabienne , Dehaut Alexandre , Paul-Pont Ika , Huvet Arnaud 
Published: July 2023

Abstract
The widespread contamination of pearl farming lagoons in French Polynesia by microplastics has led to questions about risks for the pearl industry. The aim of this study was to test the effects of micro-nanoplastics (MNPs) on the pearl oyster (Pinctada margaritifera) over a 5-month pearl production cycle. MNPs were produced from plastic pearl farming gear and used at a concentration that oysters may encounter in lagoons. MNP exposure led to the alteration of energy metabolism, mostly driven by a lower assimilation efficiency of microalgae, with modulation of gene expression patterns. Pearl biomineralization was impacted by thinner aragonite crystals, with harvest marked by the presence of abnormal biomineral concretions, called keshi pearls. These experimental results demonstrated that MNPs threaten pearl oyster biology, with potential detrimental effects on pearl quality. Ecological approaches are now required to test the holistic impact of MNPs on population sustainability in the Polynesian pearl industry.
Household conditions, COVID-19, and equity: Insight from two nationally representative surveys
Authors: Kim Nathan , Anneser Elyssa , Chu MyDzung T. , Nguyen Kimberly H. , Stopka Thomas J. , Corlin Laura 
Published: July 2023

Abstract
Background: With people across the United States spending increased time at home since the emergence of COVID-19, housing characteristics may have an even greater impact on health. Therefore, we assessed associations between household conditions and COVID-19 experiences.
Methods: We used data from two nationally representative surveys: the Tufts Equity Study (TES; n = 1449 in 2021; n = 1831 in 2022) and the Household Pulse Survey (HPS; n = 147,380 in 2021; n = 62,826 in 2022). In the TES, housing conditions were characterized by heating/cooling methods; smoking inside the home; visible water damage/mold; age of housing unit; and self-reported concern about various environmental factors. In TES and HPS, household size was assessed. Accounting for sampling weights, we examined associations between each housing exposure and COVID-19 outcomes (diagnosis, vaccination) using separate logistic regression models with covariates selected based on an evidence-based directed acyclic graph.
Results: Having had COVID-19 was more likely among people who reported poor physical housing condition (odds ratio [OR] = 2.32; 95% confidence interval [CI] = 1.17-4.59; 2021), visible water damage or mold/musty smells (OR = 1.50; 95% CI = 1.10-2.03; 2022), and larger household size (5+ versus 1-2 people; OR = 1.53, 95% CI = 1.34-1.75, HPS 2022). COVID-19 vaccination was less likely among participants who reported smoke exposure inside the home (OR = 0.53; 95% CI = 0.31-0.90; 2022), poor water quality (OR = 0.42; 95% CI = 0.21-0.85; 2021), noise from industrial activity/construction (OR = 0.44; 95% CI = 0.19-0.99; 2022), and larger household size (OR = 0.57; 95% CI = 0.46-0.71; HPS 2022). Vaccination was also positively associated with poor indoor air quality (OR = 1.96; 95% CI = 1.02-3.72; 2022) and poor physical housing condition (OR = 2.27; 95% CI = 1.01-5.13; 2022). Certain heating/cooling sources were associated with COVID-19 outcomes.
Conclusions: Our study found poor housing conditions associated with increased COVID-19 burden, which may be driven by systemic disparities in housing, healthcare, and financial access to resources during the COVID-19 pandemic.
Design for Resource-Efficient Parallel Solution to Real-Data Sparse FFT
Authors: Jones Keith John 
Published: July 2023

Abstract
The maximum size of data set being presented to the discrete Fourier transform (DFT) is becoming increasingly large to reflect the increasingly challenging problems being faced in today’s ‘big data’ era, in areas such as astronomy, medical imaging and the real-time spectrum analysis of multiGHz radio frequency signals for cognitive radio networks. Such problems are typically addressed by means of the fast Fourier transform (FFT), but there will always be data sets – typically realvalued in nature – that are too large to be efficiently processed in real time with existing computing technology, so that alternative approaches are needed. The approach pursued here for the spectrum analysis problem assumes that a relatively small number of outputs are likely to contain detectable levels of signal energy with such signals being detected through the use of a sparse version of the FFT (sFFT). A flexible and scalable sFFT design has been sought for implementation with silicon-based computing technology that’s able to yield resourceefficient lowpower solutions by maximizing the computational density through exploitation of both partitioned memory and the realvalued nature of the data. A theoretical analysis shows how this may be achieved with a parameterized solution which, with a low-end fieldprogrammable gate array (FPGA) device, a 2 GHz sampling rate and a 100 MHz clock rate, is able to achieve a latency of < 1 ms for a 2 millionpoint real-data sFFT together with low resource utilization and which compares favourably with other recently published FFT and sFFT solutions.