bluuebunny/crossref_metadata_2025_split huggingface dataset:
A pseudonymized corpus of occupational health narratives for clinical entity recognition in Spanish
Authors: Dunstan Jocelyn , Vakili Thomas , Miranda Luis , Villena Fabián , Aracena Claudio , Vera Paulina , Valenzuela Sebastián Viteri , Rocco Victor 
Published: January 2024

Abstract

Despite the high creation cost, annotated corpora are indispensable for robust natural language processing systems. In the clinical field, apart from annotating medical entities, personally identifiable information (PII) must be removed, especially in the era of large language models where unwanted memorization can occur. This paper presents a corpus annotated to anonymize personally identifiable information in 1,787 anamneses of work-related accidents and diseases in Spanish. In addition, we applied a previously released model for Named Entity Recognition (NER) trained on referrals from primary care physicians to identify diseases, body parts, and medications in this work-related text. We analyzed the differences between the models and the gold standard curated by a physician in detail. Moreover, we compared the performance of the NER model on the original narratives, in narratives where personal information has been masked, and in texts where the personal data is replaced by another similar expression (pseudonymization). Within this publication, we share the annotation guidelines and the annotated corpus.
Identification of exosome-related differentially expressed genes in ischemic stroke
Authors: Lin Ma , Xiaofang Xi , Yu Cao 
Published: January 2024

Abstract

An ischemic stroke is a pathological condition characterized by an abrupt cessation of blood flow to a specific cerebral region, leading to a concomitant impairment of neurological function. This form of stroke arises from occlusions or constriction of the cerebral arteries responsible for supplying blood to the brain, and may manifest as a consequence of diverse factors including thrombosis, embolism, or systemic hypoperfusion. The aim of the present study was to identify exosome-related differentially expressed genes (ERDEGs) for ischemic stroke (IS) by integrating and analyzing gene expression profiles from two independent datasets. Differential expression analysis yielded 16 ERDEGs (Aprt, Cd55, Ckap4, Ctsz, Cuta, Emg1, Imp3, Lamp2, Mgam, Mif, Mme, Mmp9, Sdcbp, Slamf1, Tln1, and Tubb), which were examined for functional similarities and differential expression between IS and control groups. Gene Set Enrichment Analysis (GSEA) revealed significant pathways involved in platelet aggregation and inflammatory responses. The diagnostic potential was assessed employing Support Vector Machine (SVM) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression methodologies, identifying a subset of genes exhibiting substantial diagnostic accuracy. Four ERDEGs (Tubb, Sdcbp, Tln1, and Ctsz) were identified as key biomarkers, with Sdcbp showing the highest utility. The clinical efficacy of the diagnostic model based on ERDEGs was evaluated, demonstrating significant prognostic significance for IS.
Safety and feasibility of early water consumption after general anesthesia recovery in patients undergoing daytime surgery
Authors: Lu Yixing , Liu Siyan , Jing Shunzhong , Zhao Xuefeng , Liang Jiamei , Sun Xiaoqiang , Lin Yunan 
Published: January 2024

Abstract

Following general anesthesia, many patients experience dry lips, throat discomfort, intense thirst, and a strong desire to drink water in the postanesthesia care unit (PACU). However, the safety of drinking water is often raised. In this prospective observational study we aimed to assess the safety and feasibility of allowing patients to drink water shortly after recovering from general anesthesia, particularly in the context of daytime surgery. Postoperative patients were given water intake in the PACU according to a standard assessment protocol. A total of 216 patients undergoing non-gastrointestinal surgery. For the per-protocol analysis, sixteen patients were excluded. They were divided into four groups based on the amount of water they consumed: group A (<1 mL kg–1), group B (1–2 mL kg–1), group C (>2 mL kg–1), and group D (no drinking). The incidence of post-drinking nausea and vomiting was only 0.67%（1/150）, with no differences in comparisons between groups (P =0.289). Drinking water resulted in a significant decrease in thirst, oropharyngeal discomfort, and pain scores, while significantly increasing the antral motility index (MI). This difference was statistically significant when compared to the pre-drinking values (P < 0.001). Notably, the more water patients consumed, the more pronounced their gastrointestinal peristalsis. A significant difference in antral MI was observed between groups B, C, and A (P < 0.001). Non-gastrointestinal surgical patients who pass a pre-drinking water assessment after resuscitation from general anesthesia can safely consume moderate amounts of water in the PACU. Early water intake is both safe and feasible to promote postoperative recovery.
Clinical trial registration: http://www.chictr.org.cn/usercenter.aspx identifier: ChiCTR2200063418.
Barriers Interfere with Wide Usage of NOAC for Prevention of Thromboembolic Events Among Doctors in Sudan: a Cross-Sectional Survey February 2023
Authors: Khalil Elaf Sabri , Husain Asmaa Elfatih , Nouh Waddaha Mohammed , Awad Mustafa Sabir Abakar 
Published: January 2024

Abstract

Background:
Ischemic heart disease and stroke kill 25% of people worldwide. Vitamin K antagonist (warfarin) is the most widely used oral anticoagulant. Although affordable and effective, its usage is limited in many patients due to anticoagulation level variability and other factors, its alternatives include new nonvitamin K antagonist oral anticoagulants (NOACs). The study aims to investigate NOAC usage barriers.
Methods:
This is an observational, cross-sectional study, involved 144 doctors from different specialties and different medical degrees in Khartoum state, the data were collected by an author designed close-ended questionnaire. Data were entered, cleared and analyzed using Statistical Package for Social Sciences (SPSS) V25.0 software
Results:
Medicine was most common (45.8%) among 144 medical department participants. The most prevalent medical degrees were registrars (25%) and doctors (25%). Specialists (22.9%), then house officers (15.3%). Over half (51.4%) had worked less than five years. 50% didn't know about the 2021 DOACs guideline, 13.9% wanted to prescribe but couldn't owing to scope of practice or supervisor preference. 60.4% claimed DOACs' unavailability inhibits prescription. The lack of a multidisciplinary team approach hinders DOACs prescription, said 70.2%.
Conclusion:
Sudanese clinicians' hurdles to using NOAC for thromboembolic episodes were explored. Lack of a reversal agent and multi-disciplinary team approach hinder DOAC prescription. Lack of information about international guidelines, since most participants preferred specialized advice or personal experience, and high DOAC costs and inaccessibility and unavailability are other important barriers. Medical practitioners should update guidelines and government insurance plans should include DOACs. Each department should start studies separately.
Optimizing Photovoltaic Power Plant Forecasting with Dynamic Neural Network Structure Refinement
Authors: Díaz-Bello Dácil , Vargas-Salgado Carlos , Alcázar-Ortega Manuel , Águila-León Jesus 
Published: January 2024

Abstract
Energy systems face a challenge characterized by the inherent uncertainty associated with accurate renewable power generation forecasts. Despite the availability of weather prediction methods, achieving precise predictions for photovoltaic (PV) power generation remains a critical necessity. In response to this challenge, this study presents a novel approach that leverages genetic algorithms to optimize PV power plant forecasting. The proposed algorithm dynamically refines the neural network's structure during training, minimizing the mean square error by adjusting parameters such as the number of neurons, transfer functions, weights, and biases. An evaluation of twelve representative days, each representing one month, is conducted using annual, monthly, and seasonal data. Evaluation metrics are employed to assess forecast accuracy, including root mean square error, R-value, and relative percentage error. The research uses MATLAB for modeling, training, and testing, with a 4.2 kW photovoltaic plant utilized for data validation. Results showcase the effectiveness of genetic algorithms, with mean squared errors as low as 20 on cloudy days and 175 on sunny days. Moreover, the genetic algorithm-based artificial neural network optimization methodology achieves forecasting vs. target regressions ranging from 0.95824 to 0.99980, underscoring its efficiency in providing reliable PV power generation predictions.
Exploring Morpho-syntactic Errors in English Compositions by University ESL Learners
Authors: Umarlebbe Jameela Hanoon , Said Seriaznita , Shamsudin Sarimah 
Published: January 2024

Abstract

Proficiency in English writing poses a pervasive challenge for second language learners globally, extending to Sinhala and Tamil-speaking students in Sri Lanka. Given English's role as the primary medium of instruction in Sri Lankan universities across most disciplines, it is a mandatory subject for all first-year students, irrespective of their field of study. This pilot study represents an initial exploration into the investigation of morpho-syntactic errors in the English compositions of university students in a Sri Lankan public institution. Sixteen participants’ answer scripts, evenly split between Sinhala-speaking and Tamil-speaking English learners, were selected for this study. The essays under investigation were sourced from year-end examination answer scripts, employing a purposive sampling method. The study seeks to discern prevalent morpho-syntactic errors in university-level ESL learners. This involves utilizing Corder's (1974)methodological steps for error analysis and categorizing errors through the Surface Strategy Taxonomy (SST) devised by Dulay et al. (1982). A total of 328 errors were identified and categorized into four SST types: omission, addition, misformation, and misordering. Findings reveal a prevalence of misformation errors, followed by omission, addition, and misordering. Sinhala-speaking learners exhibited a higher error percentage (54%) than their Tamil-speaking counterparts. Notably, within the Tamil-speaking group, a significant difference emerged, with Tamil-speaking Muslim learners demonstrating fewer errors than Tamil-speaking Hindu learners. These insights open avenues for broader research into the nuanced factors influencing morpho-syntactic errors in ESL learning contexts worldwide.
Study on the fire resistance of straight tenon joints with dowel
Authors: Wang Yong , Shao Jianhua , Wang Tingting , Wang Zhanguang , Xu Hongxuan , Zhang Xuan 
Published: January 2024

Abstract

In order to study the fire resistance of straight tenon joint with dowl, this paper uses finite element software to establish the joint temperature field model. Through this model, the temperature distribution of each part of the joint is obtained. In this paper, the sequential coupling method is used for the simulation of the heat-force coupling field, and the residual bearing capacity of the straight tenon joint with dowl at high temperature is modeled and analyzed. Through this analysis, the stress cloud diagrams of the damage modes of the joint under different high-temperature conditions were obtained, as well as the change curves of mechanical parameters such as the bending moment-angle curve, rotational stiffness, yielding angle, yielding moment and maximum moment of the joint at different temperatures. The simulation results show that the maximum heating temperature of the joint increases, the more easily the node is damaged. With the increase of the maximum temperature, the percentage of the residual bearing capacity of the joint in terms of rotational stiffness, yielding moment and maximum moment decreases gradually.
Bioproduction of yeast single cell oil with acute oral toxicity study intended for edible oil application
Authors: Nautiyal Abhilek Kumar , Singh Priyanka , Paul Pranoy , Raut Sachin , Bhasker Thallada , Chowdhury Nilotpal , Khatri Neeraj , Ghosh Debashish 
Published: January 2024

Abstract

Human nutrition and health rely on edible oils. Global demand for edible oils is expanding, necessitating the discovery of new natural oil sources subjected to adequate quality and safety evaluation. However, in contrast to other agricultural products, India's edible oil supply is surprisingly dependent on imports. The microbial oil is generated by fermentation of oleaginous yeast Rhodotorula mucilaginous IIPL32 MTCC 25056 using biodiesel plant byproduct crude glycerol as a fermentable carbon source. Enriched with monounsaturated fatty acid, nutritional indices mapping based on the fatty acid composition of the yeast SCO, suggested its plausible use as an edible oil blend. In the present study, acute toxicity evaluation of the yeast SCO in C57BL/6 mice has been performed by randomly dividing the animals into 5 groups with 50, 300, 2000, and 5000 mg/Kg yeast SCO dosage, respectively, and predicted the median lethal dose (LD50). Detailed blood biochemistry and kidney and liver histopathology analyses were also reported. The functions of the liver enzymes were also evaluated to check and confirm the anticipated toxicity. To determine cell viability and in vitrobiocompatibility, the 3T3-L1 cell line and haemolysis tests were performed. The results suggested the plausible use of yeast SCO as an edible oil blend due to its non-toxic nature in mice models.
Outdoor biohydrogen production by thermotolerant Rhodopseudomonas pentothenatexigens KKU-SN1/1 in a cluster of ten bioreactors system
Authors: Punriboon Netchanok , Sawaengkaew Jutaporn , Mahakhan Polson 
Published: January 2024

Abstract
In tropical regions, the viability of outdoor photo-fermentative biohydrogen production faces challenges arising from elevated temperatures and varying light intensity. This research aimed to explore how high temperatures and outdoor environments impact both biohydrogen production and the growth of purple non-sulfur bacteria. The findings revealed the potential of Rhodopseudomonas spp. as a robust outdoor hydrogen-producing bacteria, demonstrating its capacity to thrive and generate biohydrogen even at 40°C and under fluctuating outdoor conditions. Notably, Rhodopseudomonas pentothenatexigens KKU-SN1/1 exhibited the highest cumulative biohydrogen production of 400 mL/L under outdoor conditions. In addition, the outdoor enhancement of biohydrogen production was achieved through the utilization of a cluster of ten bioreactors system. The outcomes demonstrated a notable improvement in biohydrogen production efficiency, marked the highest daily biohydrogen production was 493 mL/L/day. Significantly, the highest biohydrogen production rate was noted to be 17 times greater than that observed in conventional batch production methods. This study is the first report represents the inaugural utilization of R. pentothenatexigens for sustained biohydrogen production in the outdoor conditions, facilitated by the cluster of ten bioreactors system over an extended operational period.
Research on the “combination punch” effect of heterogeneous environmental regulation linkage on carbon productivity
Authors: Han Dongri , Lv Xiaoli , Yan Su 
Published: January 2024

Abstract

Building an effective environmental regulation “combination punch” to improve carbon productivity is of great significance for achieving the “dual carbon” goal. Taking 30 provinces (municipalities and autonomous regions) in my country as research cases, the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method is used to explore the impact of command-and-control, market incentive, voluntary and recessive environmental regulation linkages on carbon productivity. The research found that: ① A single type of environmental regulation antecedent condition does not constitute a necessary condition for the improvement of carbon productivity, and the linkage of heterogeneous environmental regulation has a significant “combination punch” effect on the improvement of carbon productivity. ②There are three configuration paths to achieve high carbon productivity, namely active environmental protection under the leadership of market incentive, government restraint and public supervision and promotion type I, and government restraint and public supervision and promotion type II. ③ There is a potential substitution relationship between the combination of robust market incentive and robust voluntary environmental regulation and a single robust command-and-control environmental regulation. The conclusions can provide policy suggestions and useful references for formulating an effective and diversified environmental regulation tool portfolio.
Bone marrow fibrosis in newly diagnosed multiple myeloma and its correlation with clinicopathological factors
Authors: Hu Xiumei , Dai Xiangyang , Guo Xinmeng , Jiang Xingran , Li Yunlong , Zhao Hongying , Lu Jun , Li Xue , Jin Mulan 
Published: January 2024

Abstract

Background: Our study aimed to determine the incidence, patient characteristics, and clinical outcomes of patients with newly diagnosed myeloma (NDMM) with bone marrow fibrosis (BMF).
Methods:
The clinical data, histological features, and clinical outcomes of patients with NDMM were collected. Reticular fiber staining was performed on the enrolled cases, the degree of reticular fiber hyperplasia was graded, and the incidence of BMF was calculated. The differences in clinical data, histological features, and clinical outcomes between the BMF+ group and the BMF– group were compared.
Results:
The study involved a consecutive series of 146 patients with NDMM. The incidence of MF-0, MF-1, MF-2, and MF-3 was 7.53% (11/146), 34.93% (51/146), 51.37% (75/146), and 6.16% (9/146), respectively. Patients with MF-2 and MF-3 were classified as the BMF+ group, and those with MF-0 and MF-1 were classified as the BMF- group. The incidence of BMF, namely MF-2 and MF-3, was observed to be 57.53% (84/146). A significant correlation was identified between the pattern of infiltration and BMF (P<0.001); furthermore, BMF was associated with a diffuse infiltration pattern. The overall survival (OS) of the BMF+ group (39.177 months; 95% confidence interval [CI]: 34.031–44.323) was lower than that of the BMF- group (45.430 months; 95% CI: 39.524–51.337), but there was no significant difference between the two groups (P = 0.221). Univariate and multivariate analysis showed that the BMF+ status was not associated with OS in patients with NDMM (P = 0.381,0.748).
Conclusions:
Our findings suggest that BMF is linked to a diffuse infiltration pattern, and its occurrence is not related to the prognosis of patients with NDMM. Thus, this study provides a basis for further exploring the value of BMF in the diagnosis and treatment of NDMM.
Radio Signal Classification by Adversarially Robust Quantum Machine Learning
Authors: Wu Yanqiu , Adermann Eromanga , Thapa Chandra , Camtepe Seyit , Suzuki Hajime , Usman Muhammad 
Published: January 2024

Abstract

Radio signal classification plays a pivotal role in identifying the modulation scheme used in received radio signals, which is essential for demodulation and proper interpretation of the transmitted information. Researchers have underscored the high susceptibility of ML algorithms for radio signal classification to adversarial attacks. Such vulnerability could result in severe consequences, including misinterpretation of critical messages, interception of classified information, or disruption of communication channels. Recent advancements in quantum computing have revolutionized theories and implementations of computation, bringing the unprecedented development of Quantum Machine Learning (QML). It is shown that quantum variational classifiers (QVCs) provide notably enhanced robustness against classical adversarial attacks in image classification. However, no research has yet explored whether QML can similarly mitigate adversarial threats in the context of radio signal classification. This work applies QVCs to radio signal classification and studies their robustness to various adversarial attacks. We also propose the novel application of the approximate amplitude encoding (AAE) technique to encode radio signal data efficiently. Our extensive simulation results present that attacks generated on QVCs transfer well to CNN models, indicating that these adversarial examples can fool neural networks that they are not explicitly designed to attack. However, the converse is not true. QVCs primarily resist the attacks generated on convolutional neural networks (CNNs). Overall, with comprehensive simulations, our results shed new light on the growing field of QML by bridging knowledge gaps in QML in radio signal classification and uncovering the advantages of applying QML methods in practical applications.
Performance evaluation of Trichoderma reseei in tolerance and biodegradation of diuron herbicide in agar plate, liquid culture and solid-state fermentation
Authors: Reyes-Cervantes Alejandro , Robles-Morales Diana Laura , Tec-Caamal Edgar Noe , Jiménez-González Angélica , Medina-Moreno Sergio Alejandro 
Published: January 2024

Abstract

The present work evaluated the performance of the fungus Trichoderma reesei to tolerate and biodegrade the herbicide diuron in its agrochemical presentation in agar plate, liquid culture, and solid-state fermentation. The tolerance to diuron was characterized through a non-competitive inhibition model, showing higher tolerance on the PDA agar plate (Ki=98.63 mg L− 1) than liquid culture with glucose and ammonium nitrate as carbon and nitrogen sources (Ki=39.4 mg L− 1). Diuron biodegradation was characterized through the model of inhibition by the substrate. Trichoderma reesei had a maximum radial growth rate (vrmax) of 1.17 cm d− 1 on agar plate. In liquid culture, Trichoderma reesei biotransformed diuron in 3,4-dichloroaniline using the amide group from the diuron structure as a carbon and nitrogen source, with a maximum specific growth rate (µmax) of 0.0245 h− 1 and a yield of the biomass on the substrate (YXD) of 0.154 mg mg− 1. In solid-state fermentation with a mix of barley straw and agrolite (70:30) as support-substrate, the maximum diuron removal percentage (97.26%) was reached with a specific aeration rate of 1.0 vkgm, inoculum of 2.6x108 spores g− 1, and an initial diuron concentration of 160.81 mg kg− 1. The diuron removal in solid-state fermentation by sorption on the barley straw and agrolite was discarded compared with the removal magnitude of the biosorption and biodegradation mechanisms of Trichoderma reesei. The Trichoderma reesei performance in its tolerance and capability to remove diuron in liquid and solid culture media displays its potential to be used in bioremediation technologies of herbicides polluted sites.