bluuebunny/crossref_metadata_2025_split huggingface dataset:
Amoxicillin and Favipiravir Bio-Degradation by Aspergillus Flavus Fungus
Authors: Al-Shammari Rana Hadi Hameed , Ali Shaimaa Satae M. , Al-Mamoori Ayad M.J. 
Published: March 2024

الهدف من هذه الدراسة هو عزل وتوصيف الفطريات القادرة على التحليل الحيوي للأموكسيسيلين و الفافيرافير وكذلك تحديد خصائصها ومسار التحلل. تم عزل الفطر الاسبرجلس من عينات المياه العادمة الملوثة باستخدام أجار البطاطا ووسط الجابك. تم دراسة المعالجة الحيوية في الوسط السابق باستخدام Amoxicillin و Favipiravir كمصدر وحيد للكربون. تم التحري عن المواد الناتجة من التحلل بواسطة كروماتوجرافيا سائلة عالية الأداء (HPLC) واستخدمت لاستنتاج مسار تحلل المضادات الحيوية بواسطة الفطر اسبرجلس. تم فحص الخيوط الفطرية عن طريق المجهر الإلكتروني الماسح قبل وبعد 7 أيام من العلاج لاكتشاف تراكم المضادات الحيوية والتغيرات الشكلية في الخيوط الفطرية. اذ يمكن للفطريات اعتماد المضادات الحيوية كمصدر وحيد للكربون.اذ لوحظ اقصى قدر من التحلل الحيوي هو 91٪ عند اقل تركيز من اموكسيللين. وفقًا لنتائج HPLC كان زمن الاحتجاز للأموكسيسيلين القياسي 8.12 دقيقة بعد التحلل الحيوي إلى مركبات أخرى مع زمن احتجاز 3.75 دقيقة بنسبة 73.25٪ ، وفي 5.81 دقيقة بنسبة 16.44٪ وفي 8.5 دقيقة بنسبة 8.59 ، وفقًا لمعيار احتباس فافيبيرافير. ظهر الوقت في 3.97 دقيقة ولكن بعد العلاج ظهرت مادتان في 2.20 دقيقة. حسب المنطقة: 62.58٪ وفي 6.16 دقيقة. حسب المنطقة: 20.15٪. لاوحظ تراكم جزيئات Favipiravir على الخيوط الفطرية A. flavus . تعطي هذه النتائج رؤى في تحسين طريقة المعالجة الحيوية لإزالة المضادات الحيوية من مياه الصرف الصحي قبل تصريفها في الأنهار .
Research on the Effects of an Electrode Drill Bit during the Rock Drilling Process by High-Voltage Electric Pulse
Authors: Duan Longchen , Liu Xianao , Li Changping , Kang Jifeng , Zhang Di , Yuan Zhong 
Published: March 2024

Summary
High-voltage electric pulse rock-breaking (HVEPB) has proved to be a novel and inexpensive method of breaking rock regardless of rock composition, but the design of the electrode drill bit lacks a theoretical basis. In this paper, we first establish a plasma channel model for electric breakdown and a numerical rock-breaking model for HVEPB, which can simulate the rock electrical breakdown plasma channel and the effect of different electrode drill bits on HVEPB. Second, we analyze the effects of different electrode arrangement structures and high-voltage electrode angles on plasma channels and the effects of internal cracks and rock-breaking processes through numerical simulation. Finally, we describe HVEPB experiments conducted using electrode drill bits with different electrode arrangement structures and high-voltage electrode angles, and with the boreholes reconstructed in three dimensions to analyze the effects of different electrode arrangement structures and high-voltage electrode angles on HVEPB drilling. The results show that the effects of the electrode drill bits on HVEPB are reflected mainly in the difference between the plasma channel and shock wave. Different electrode arrangement structures and high-voltage electrode angles result in different electric fields and energy utilization efficiencies within the rock, resulting in different shock waves and differences in the depth, shapes, and penetration of the plasma channels. The simulations and experimental studies in this paper can guide and optimize the design of the discharge tool to upgrade the drilling efficiency of HVEPB.
Metabolic rewiring underpins human trophoblast induction
Authors: Żylicz Jan , Nerum Karlien van , Wenzel Anne , Muntadas Lidia Argemi , Kafkia Eleni , Lavro Viktoria , Roelofsen Annina , Drews Anta , Arnal Sandra Bages , Zhao Cheng , Sanzo Simone di , Volker-Albert Moritz , Petropoulos Sophie , Moritz Thomas 
Published: March 2024

Abstract

Development is driven by a sequence of molecularly interconnected transcriptional, epigenetic, and metabolic changes. Specific metabolites, like α-ketoglutarate (αKG), function as signalling molecules affecting the activity of chromatin modifying enzymes. It remains unclear, how such non-canonical function of metabolism coordinates specific cell-state changes especially in early development. Here we uncover that when naive human embryonic stem cells (nESC) are induced towards human trophoblast stem cells (hiTSC) a significant metabolic rewiring occurs, characterised by the accumulation of αKG. In vivo transcriptomic data further confirmed that metabolic rewiring likely takes place in the nascent trophectoderm (TE). We show that the intracellular αKG level is an important regulator of TE fate acquisition. Indeed, a dimethyl-αKG (dm-αKG) treatment of nESC increases their competence towards TE-like cells during hiTSC induction. Moreover, dm-αKG also increased the robustness of blastoid polarisation, marking the first step of TE induction. Surprisingly, dm-αKG treatment does not affect global histone methylation levels in nESC, but rather leads to decreased H3K27ac and weakening of the pluripotency network. Further functional assays confirmed that both reduced histone acetyltransferase activity and increased αKG level promote nESC competence towards TE-lineage but not extraembryonic mesoderm. We propose that an increased αKG level regulates pluripotency through deacetylation, thus creating a positive feedback loop promoting the induction of TE fate.
Morphology-based Machine-Learning for Predicting Lymph Node Status in Oral Tongue Squamous Cell Carcinoma
Authors: Zhu Yunjing , Ren Jiliang , Song Yang , Tao Xiaofeng , Yuan Ying 
Published: March 2024

Abstract

Purpose
To develop machine-learning models based on morphological features extracted from preoperative magnetic resonance imaging (MRI) to predict lymph node status in oral tongue squamous cell carcinoma (OTSCC).
Method
This study retrospectively enrolled 90 OTSCC patients, of whom 45 and 13 patients, respectively, had confirmed lymph node metastasis (LNM) and extranodal extension (ENE). Fourteen morphological features and two customized metrics were derived from T2-weighted (T2W) images. Tumor maximum diameter and MRI-derived depth of invasion (DOI) were measured on contrast-enhanced T1-weighted (ceT1W) images. Information gain algorithm was applied to select the top five attributes. Models were created using six machine-learning methods, including neural network (NN), random forest (RF), logistic regression (LR), support vector machine (SVM), naïve bayes (NB), and AdaBoost. An internal stratified 10-fold cross-validation was performed to assess their performance.
Results
For predicting LNM, the NN classifier, which included Situation, Elongation, Top Bottom Area, Least Axis Length, and Minor Axis Length, yielded the best model, with an AUC of 0.746 and accuracy of 72.2%. The performance of the NN model was slightly superior to that of MRI-derived DOI (0.746 vs. 0.655), although the difference was not significant (P = 0.122). For predicting ENE, the SVM classifier, which included situation, Elongation, Top Bottom Area, Least Axis Length, and Minor Axis Length, performed the best, with an AUC of 0.750 and accuracy of 85.6%.
Conclusions
Machine-learning models using MRI morphological features have potential in preoperative evaluation of cervical lymph node status in OTSCC.
Multi-Phenotyping and Genotyping of Spanish Groundnuts from Diverse Crosses to Identify Stable donors for Fresh Seed Dormancy and Selection of High-Yielding Stable Genotypes in the genetic background of dormant lines-BLUP, YREM, and AMMI model based stability
Authors: Rani Kirti , K Gangadhara , BC Ajay , Kona Praveen , Kumar Narendra , Bera Sandip 
Published: March 2024

Abstract
Breeding high yielding groundnut cultivars with 2–3 weeks of fresh seed dormancy, particularly in Spanish-type cultivars, enhances the sustainability of agriculture in groundnuts. In this context, we conducted a comprehensive phenotypic and genotypic evaluation of advanced breeding lines developed in the genetic background of Spanish types. By employing multi-phenotyping and marker data, we identified PBS 15044, 16004, 16013, 16015, 16016, 16017, 16020, 16021, 16026, 16031, 16035, 16037, 16038, 16039, 16041, and 16042 with 2–3 weeks dormancy (> 90%). AMMI1 biplots, ASI, BLUP and WAASB estimates identified the stable fresh dormant genotypes with one more superior economic trait. PBS 16021, 15044, 16038, and 16039 identified with high HPW were also reported having high intensity of dormancy (> 90% for up to 3 weeks); PBS 15044, 16016, PBS 16038 and PBS 16039 with high HKW also reported with up to 3 weeks fresh seed dormancy; and PBS 16013, 16031, and 16038 with up to 3 weeks fresh seed dormancy had high SP. They can be used to develop lines with the desired level of dormancy, and high yields, by designing appropriate breeding strategies.
Understanding the Diversity of Human Gut Microbes in Indigenous Populations Across the World
Authors: Mollick Sahid Afrid , Maji Suvendu 
Published: March 2024

Abstract

The microbial population of the human gut plays an important role in maintaining host homeostasis. The human digestive Microbiota is a diverse domain that lies behind the colorful fabric of indigenous civilizations. High-throughput 16S targeted amplicon sequencing has delineated the structural configuration of the gut metagenome in world indigenous populations. The gut microbiota of the indigenous populations holds a wide diversity due to their strategic geopolitical habitat, environment dependent lifestyles, adaptive strategies and unique cultural practices. People's dietary choices and preferences, as well as cultural norms and regulations of the society, shape the overall composition of their gut microbiota. . In this study we employed 16S sequencing data of the gut microbiota samples from 464 individuals of 21 indigenous populations with different socio-demographic background across diverse geographic locations. The study overall display the significant role of geography over the diet and lifestyle of a community. Moreover hunter-gatherers and pastoralists of different geographical location have unique gut microbial composition, suggesting the influence of environment over their subsistence economy. Specific bacterial groups like Prevotellaand Bacteroides are key players in shaping these gut landscapes, identifying the complex interplay between man-environment relationships.
Financial Inclusion among Indian States:An Analysis through the Financial Inclusion Index (FII)
Authors: Kasturi Alivelu , Annemalla Ramesh 
Published: March 2024

Abstract

This study aims to estimate the level of financial inclusion (FI) among the states of India for a two decades. To know this study constructed a FI index then a two-stage PCA method was used. Secondary data from the Reserve Bank of India (RBI) and Economic and Political Weekly Research Foundation (EPWRF) reports for 2000–2020 is used. The study has determined an overall FI index using the dimensions of availability, Penetration, and Usage. The results show that Goa, Kerala and Tamil Nadu states topped with high FI, while Mizoram, Nagaland, Manipur, and Meghalaya states ranked with low FI in the entire study period. The close coordination between the RBI, Government, NABARD, and the other implementing agencies will result in the achievement of financial inclusion in a short period.
JEL Classification: G21, G22, G28, C43, B26
Improving Quality Control of Whole Slide Images by Explicit Artifact Augmentation
Authors: Jurgas Artur , Wodzinski Marek , D'Amato Marina , Laak Jeroen van der , Atzori Manfredo , Müller Henning 
Published: March 2024

Abstract

The problem of artifacts in whole slide image acquisition, prevalent in both clinical workflows and research-oriented settings, necessitates human intervention and re-scanning. Overcoming this challenge requires developing quality control algorithms, that are hindered by the limited availability of relevant annotated data in histopathology. The manual annotation of ground-truth for artifact detection methods is expensive and time-consuming. This work addresses the issue by proposing a method dedicated to augmenting whole slide images with artifacts. The tool seamlessly generates and blends artifacts from an external library to a given histopathology dataset. The augmented datasets are then utilized to train artifact classification methods. The evaluation shows their usefulness in classification of the artifacts, where they show an improvement from 0.10 to 0.01 AUROC depending on the artifact type. The framework, model, weights, and ground-truth annotations are freely released to facilitate open science and reproducible research.
The analgesic effect of Preemptive multimodal analgesia in Direct Anterior Approach total hip arthroplasty：a randomized double-blind trial
Authors: Qi Shiyuan , Chen Xiaotong , Xu Ziwei , Yun Huifang , Zhao Zirui 
Published: March 2024

Abstract

Background:The purpose of this experiment was to investigate the effect of PMA protocol (pericapsular nerve group (PENG), oxycodone and parecoxib) postoperative pain in direct anterior approach total hip arthroplasty (DAA-THA) patients with consistent preoperative pain thresholds .Objectives:To explore effective preemptive multimodal analgesic protocols to meet the needs of enhanced recovery after surgery (ERAS) in joint surgery.Study Design:This study was a prospective, single-center, randomized, double-blind trial with four groups.Setting:In the Changzhou Second People's Hospital a single institution.Methods:We recruited 160 patients with consistent preoperative pain thresholds to enter the final study analysis, and according to the criteria were randomly divided into four groups: the placebo group (n = 38), parecoxib group (n = 39), oxycodone group (n = 43), and combination group (n = 40). According to the corresponding PMA protocol, all groups were given advanced analgesic drugs at 30 min before surgery and PENG after 30 min. The main result of the pain VAS scores at rest and during exercise, and secondary results postoperative inflammation index( erythrocyte sedimentation rate and C-reactive protein ), 5-hydroxytryptamine(5-HT) ,postoperative rescue opioids medicine (total volume and time), first walking time, postoperative adverse effects, postoperative delirium occur and length of stay (LOS) after DAA-THA .Results:The postoperative VAS scores in the combined group were significantly lower than those in the other three groups. The VAS scores between during exercise and at rest were significant differences in the four groups Within 48 hours after surgery (P < 0.05). The combination group had the lowest cumulative opioids dose and the first rescue analgesic is longer within 48 hours after surgery (P < 0.05). The inflammation indexes and 5-HT changes within 48 hours after surgery, the first walking time and the postoperative LOS of the combination group had significantly improved compared with the other three groups (P < 0.05). The postoperative adverse effects were no significantly difference in the four groups within postoperative 48 hours.Conclusions:The PMA regimen of oxycodone associate with parecoxib and assist PENG was effectively improved perioperative pain (acute), reduced the cumulative dose of postoperative opioids and promoted patient recovery after DAA-THA.
Revealing the mechanism of charge storage induced hole catalysis
Authors: Xiang Quanjun , Li Fang , Guan Chen , Yu Zhihan 
Published: March 2024

Abstract

Carrier dynamics modulation is intricately linked to semiconductor materials and device design. Elucidating carrier transport mechanisms and directing carrier transfer present significant yet arduous research challenges. Herein, we reveal the mechanism of charge transfer during accumulation and release through a series of in-situcharacterizations using Poly (heptanazinamide)（PHI) material as a model system. In contrast to previous reports of dark-state electron catalysis, the quantitative capture of holes and electron annihilation demonstrates that the catalytically active species in the dark-state charge release stage are holes rather than electrons. Specifically, the electrons captured during the photocharging stage are stored as long-lived radicals. Concurrently, holes are stored through hole scavenging. In the dark-state discharge stage, the released electrons reduce the oxidized hole sacrificial agents prompting the release of holes to participate in catalytic reactions. Analysis of the structural changes during the photocharging process suggests that the heptazine unit is destroyed and the carbonyl group formation underlie the observed charge storage phenomenon. This work provides insight into charge storage mechanisms and suggests potential applications in the development of self-charging devices.
Digital-analog hybrid matrix multiplication processor for optical neural networks
Authors: Kong Deming , Meng Xiansong , Kim Kwangwoong , Li Qiuchi , Dong Po , Cox Ingemar , Lioma Christina , Hu Hao 
Published: March 2024

Abstract
The computational demands of modern AI have spurred interest in optical neural networks (ONNs) which offers the potential benefits of increased speed and lower power consumption. However, current ONNs running analog optical signals face a fundamental limitation in calculation precision, typically around 4 bits, due to accumulated noise from electro-optical components. This obstacle is inherent to the analog computing nature of ONNs. The analog signals representing the inputs and the computational results require high-resolution signal format converters (digital-to-analogue conversions (DACs) and analogue-to-digital conversions (ADCs)), which pose a major obstacle in practical implementation. Here, we propose a digital analog hybrid optical computing architecture for ONNs, which utilizes digital optical inputs in the form of binary words. By introducing the logic levels and decisions based on thresholding, the calculation precision is significantly enhanced. The DACs for inputs are removed. And the resolution requirement of the ADCs becomes independent of the bitwidth of the inputs. This can increase the operating speed at a high calculation precision and facilitate compatibility with microelectronics. To validate our approach, we have fabricated a proof-of-concept photonic chip and built up a hybrid optical processor (HOP) system for neural network applications. We have demonstrated an unprecedented 16-bit calculation precision for high-definition image processing, with a pixel error rate (PER) as low as 1.8×10−3 at a signal-to-noise ratio (SNR) of 18.2 dB. We have also implemented a convolutional neural network for handwritten digit recognition that shows the same accuracy as the one achieved by a desktop computer. The concept of the digital-analog hybrid optical computing architecture offers a methodology that could potentially be applied to various ONN implementations and may intrigue new research into efficient and accurate domain-specific optical computing architectures for neural networks.
Probing Chiral-Symmetric Higher-Order Topological Insulators with Multipole Winding Number
Authors: Lee Chaohong , Lin Ling 
Published: March 2024

Abstract

The interplay between crystalline symmetry and band topology gives rise to unprecedented lower-dimensional boundary states in higher-order topological insulators (HOTIs).
However, the measurement of the topological invariants of HOTIs remains a significant challenge.
Here, we define a {multipole winding number} (MWN) for chiral-symmetric HOTIs by applying a corner twisted boundary condition.
The MWN, arising from both bulk and boundary states, accurately captures the bulk-corner correspondence including boundary-obstructed topological phases.
To address the measurement challenge, we leverage the perturbative nature of the corner twisted boundary condition and develop a real-space approach for determining the MWN in both two-dimensional and three-dimensional systems.
The real-space formula provides an experimentally viable strategy for directly probing the topology of chiral-symmetric HOTIs through dynamical evolution.
Our findings not only highlight the twisted boundary condition as a powerful tool for investigating HOTIs, but also establish a paradigm for exploring real-space formulas for the topological invariants of HOTIs.
Diagnostic Deep Learning Framework for Heart Failure
Authors: Chanprasertpinyo Wisit , Phongkitkarun Sith , Sriprachya Apichaya , Nitiwarangkul Chayanin , Thammasudjarit Ratchainant , Lolak Sermkiat , Yingchoncharoen Teerapat 
Published: March 2024

Abstract
Background
In the precision medicine era, leveraging advanced technology, including deep learning, has the potential to enhance diagnostic accuracy across various diseases. However, chest radiography (CXR), pivotal for heart failure (HF) diagnosis, currently has limited precision.
Methods
Through a retrospective cohort study encompassing 144 participants from the RAMA dataset at Ramathibodi Hospital (spanning January 1, 2010, to December 31, 2019), 240 HF CXR images were scrutinized and annotated by cardiologists and radiologists. Clinical diagnosis was confirmed by cardiologists using HF signs and symptoms, pulmonary capillary wedge pressure, natriuretic peptide, and ejection fraction. The developed model, HFNet, was trained on the RAMA dataset and incorporated these clinical factors.
Results
This study evaluated the performance of the HFNet model in predicting radiographic findings related to heart failure and achieved excellent results. The model demonstrated high precision (for cardiomegaly, 1.0; for pulmonary edema, 0.9; for pleural effusion, 0.8) and good accuracy (for cardiomegaly, 0.9; for pulmonary edema, 0.6; and for pleural effusion, 0.7), coupled with respective AUC values of 1.00, 0.96, and 0.49. Concomitant recall figures stood at 0.9, 0.6, and 0.7, while F1 scores were 0.9 for cardiomegaly and 0.7 for both pulmonary edema and pleural effusion. These findings highlight the potential of HFNet to aid clinicians in the precise detection and diagnosis of HF-associated radiographic cues.
Conclusions
The development of the HFNet model introduces a promising tool for clinicians, facilitating accurate and precise diagnosis of HF-related radiographies.
Assessing the Impact of Environmental Factors on Geo-based Technology Acceptance Model (GTAM) Among Pedestrian Tourists
Authors: Zeng Zhanjing , Xu Minghui , Qiu Mengyuan , Chi Ya 
Published: March 2024

Abstract

Geo-based technology has become an integral tool in tourism activities, offering vital assistance to travelers in making spatial transit decisions at unfamiliar destinations. The widespread adoption raises the issue of whether technology diminishes or augments the role of environmental cues in wayfinding behavior. To address this gap, we incorporated environmental factors and constructing a Geo-based Technology Acceptance Model (GTAM) that integrates Perceived Environmental Complexity (PEC) and Perceived Map-Alignment (PMA) as external variables. Through an onsite survey conducted in the historic Lijiang Ancient Town with 636 participants, we developed a model to understand the adoption of navigation apps by tourist pedestrians. The significant influence of PEC and PMA on Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) demonstrates how navigation apps, as an extension of traditional maps, systematically and abstractly consolidate human spatial cognition and thinking. By visually presenting geographic information, these apps enhance users’ environmental perception and provide guided pathways in wayfinding decisions, offering a nuanced understanding of the interplay between technology and natural orientation instincts of travelers. This study underscores the pivotal role of geo-based technology in reshaping tourists’ interaction with unfamiliar environments, highlighting its potential to enrich the travel experience through enhanced spatial awareness and decision-making support.