bluuebunny/crossref_metadata_2025_split huggingface dataset:
Water quality indices for the evaluation of the groundwater quality in southwestern Libya
Authors: Elssaidi Mohamed Ali , Aishah Ramadan Mohamed , Panhwar Qurban Ali 
Published: June 2024

ABSTRACT

An investigation was undertaken to consider the quality of the groundwater. The samples were collected from the Southwestern Libya. Forty-one water samples (41) were analyzed for hydrochemical characteristics and suitability for drinking purposes. The parameters for water quality, including calcium, magnesium, sodium, potassium, chloride and bicarbonate, sulfate, nitrate, pH and total dissolved solids (TDS), were examined. The most common worldwide used standard (ST-WQI) and the weighted arithmetic (WA-WQI) water quality indices were selected. The majority of the samples (87.5% wells) described the quality of groundwater in the Alshatti area as excellent to moderate and in the Ghat region (three wells) water quality ranges from excellent to good and is appropriate for direct consumption. In the Wadi al-Ajal areas, 62.5% (10 wells) of samples described the groundwater quality as excellent to good and the rest of the others were poor or unsuitable water. In contrast, most of the obtained results from the Sabha and Ghadduwah areas showed poor to unsuitable water quality for drinking use. Furthermore, samples are higher with pH and alkalinity values. The alkalinity does not pose a health risk but can cause esthetic problems. Generally, most of the areas’ water quality indices for physicochemical parameters indicated suitability for drinking purposes.
An artificial neural network and SCS–CN-based model for runoff estimation: a case study of the Peddavagu watershed
Authors: Raj Raushan , Kumar Rohit , Aishwarya M. , Aswini Manda , Cheraku Srivalli 
Published: June 2024

ABSTRACT
The accurate prediction of runoff from rainfall events is crucial for effective water resource management, especially in regions with diverse climatic patterns like India. This study proposes a novel approach by integrating the soil conservation service (SCS)–curve number (CN) method with artificial neural networks (ANNs) to model rainfall–runoff relationships. In this research, an SCS–CN method is utilized to estimate initial runoff volumes, accounting for local soil and land-cover characteristics. Subsequently, an ANN-based model is developed to capture the complex nonlinear relationships between rainfall inputs and runoff outputs. Taking the rainfall of the watershed as the inputs, an ANN model was developed in MATLAB for runoff simulation at the main outlet of the Peddavagu watershed. A feed-forward back-propagation method is employed in the ANN model. The architecture with a 1-10-1 configuration based on tan–sig transfer function performed well in terms of MSE 0.019. The model efficiency was satisfactory with the coefficient of correlation (R), 0.96 for training, 0.98 for validation, and 0.98 for testing period. The overall value of R (0.96) indicates the utility of this ANN–SCS-based coupled model for rainfall–runoff simulation.
Biegły w sprawach o nieważność małżeństwa spowodowanych zaburzeniami nastroju – jeszcze dwa objaśnienia
Authors: Nowakowski Bartosz 
Published: June 2024

Niniejszy artykuł porusza dwa aspekty funkcji biegłego w sprawach o nieważność małżeństwa spowodowanych zaburzeniami nastroju. W pierwszej części autor zajmuje się problematyką technicznych aspektów ekspertyzy biegłego w diagnozowaniu zaburzeń nastroju z podziałem na osobiste badanie stron procesu oraz ocenę akt. Druga część artykułu ukazuje najczęstsze problemy w konstrukcji materialnej i formalnej wniosków biegłego i podaje rozwiązania tych trudności. Artykuł stanowi kontynuację wcześniej opublikowanych na łamach Ius Matrimoniale artykułów: Zaburzenia nastroju jako przyczyna niezdolności osoby do podjęcia istotnych obowiązków małżeńskich oraz Biegły w sprawach o nieważność małżeństwa spowodowanych zaburzeniami nastroju – trzy objaśnienia.
The epistemic role of language on the belief about Trinity and Incarnation
Authors: Miranda Rafael , Albornoz Olivares Mauricio 
Published: June 2024

This paper analyzes some relevant aspects of the Incarnation of Jesus, the God-Son. It considers the tension between interpretations in favor of a metaphorical reading, and the problem that entails that this discards the historical character, the event of God made flesh. This is an ontological problem. At the same time, reflects on the role of the notion of mystery and the scope it has to believing in the Incarnation, that is, admitting an inherent epistemic limit as finite beings but at the same time making viable that the believer gradually understands what he believes, even if not fully. This constitutes an epistemic edge. In the same way, the role of language as a way of access and transmission of knowledge about the divine and sacred is evaluated, emphasizing the role of the names used to refer to the God-Father, the God-Son and the Holy Spirit, considering their logical implications.
¿Humanismo cristiano o paganismo posthumano?
Authors: Capelari Luis Gabriel , Petroni Pablo 
Published: June 2024

Partiendo de una experiencia supuestamente ‘liberadora’ del ser del hombre en la modernidad, correlato de la secularización, en este trabajo presentamos algunos trazos esenciales de la profunda crítica antihumanista -avanzado el siglo XX- a este hombre ideal ya en aguda crisis. En este sentido, la experiencia cultural actual considera en gran medida que este ‘hombre’ se ‘construye’ a sí mismo desde su voluntad y libertad desancladas de Dios y de la verdad, con el objetivo de una vida posthumana.
Sostenemos que se trata de un neopaganismo, caracterizado por un pensamiento inmanentista, postmetafísico y materialista que no reconoce la realidad del hombre y su trascendencia -licuada en gran medida en el poder y lo político o bien en el poder de la tecnociencia del ideal transhumanista-, verdad en la que únicamente puede vivir digna y felizmente. Se defenderá la importancia de restaurar la matriz cristiana -y más precisamente católica- para una formación integral de la persona como auténtico humanismo.
Biotechnological Breakthroughs in Resveratrol Synthesis and Health Advancements
Authors: Mittal Ravi K , Krishna Gaurav , Mishra Raghav , Sharma Vikram 
Published: June 2024

Abstract:
This academic review examines the latest biotechnology methods for resveratrol synthesis.
We aim to study the health advantages of resveratrol consumption beyond synthesis and
demonstrate its potential as a therapeutic agent. An extensive examination of the current state of
literature was performed, employing a diverse range of scholarly databases with the purpose of
collating pertinent information and conducting in-depth research on the subject matter. The main
goal was to find and assess research on resveratrol's health effects and the latest biotechnology
methods for synthesizing it. This review paper discusses resveratrol synthesis methods, including
their efficacy and current advances. The findings highlight the significant potential of biotechnological
methods in improving both the synthesis of resveratrol and its beneficial effects on
health. Our comprehensive analysis substantiates the importance of biotechnological methodologies
in synthesizing resveratrol. The literature review highlights resveratrol's therapeutic properties,
which have been scientifically approved for the prevention and treatment of various ailments,
such as cardiovascular disease, metabolic illnesses, cancer, aging, and immunomodulation.
A Prognostic Model to Improve Asthma Prediction Outcomes Using Machine Learning
Authors: M R Pooja , Ravi Vinayakumar , Lokesh Gururaj Harinahalli , Al Mazroa Alanoud , Ravi Pradeep 
Published: June 2024

Purpose
The utility of predictive models for the prognosis of asthma disease that rely on clinical history and findings has been on the constant rise owing to the attempts to achieve better disease outcomes through improved clinical processes. With the prognostic model, the primary focus is on the search for a combination of features that are as robust as possible in predicting the disease outcome. Clinical decisions concerning obstructive lung diseases such as Chronic obstructive Pulmonary Disease (COPD) have a high chance of leading to results that can be misinterpreted with wrong inferences drawn that may have long-term implications, including the targeted therapy that can be mistakenly beset. Hence, we suggest data-centric approaches that harness learning techniques to facilitate the disease prediction process and augment the inferences through clinical findings.

Methods
A dataset containing information on both symptomatic representations and medical history in the form of categorical data along with lung function parameters, which were estimated using a spirometer (with the data basically being quantitative (numerical) in nature) was used. The Naïve Bayes classifier performed comparatively well with the optimized feature set. The adoption of One-Class Support Vector Machines (OCSVM) as an alternative method to sampling data has resulted in the selection of an ideal representation of the data rather than the regular sampling approach that is used for undersampling.

Results
The model was able to predict the disease outcome with a precision of 86.1% and recall of 84.7%, accounting for an F1 measure of 84.5%.The Area under Curve(AUC) and Classification Accuracy (CA) were evaluated to be 92.2% and 84.7% respectively.

Conclusion
Incorporating domain knowledge into the prediction models involves identifying clinical features that are most relevant to the process of disease classification using prior knowledge about the disease and its contributing factors, which can significantly enhance the productivity of the models. Feature engineering is centric on the use of domain knowledge within clinical prediction models and commonly results in an optimized feature set. It is evident from the experimental results that using a combination of medical history data and significant clinical findings result in a better prognostic model
Agile 3+ and Metabolic Dysfunction-Associated Fatty Liver Disease:
Detecting Advanced Fibrosis based on Reported Liver Stiffness
Measurement in FibroScan and Laboratory Findings
Authors: Sotoudeheian Mohammadjavad 
Published: June 2024

:
Metabolic Dysfunction-Associated Fatty Liver Disease (MAFLD), formerly known as Non-alcoholic fatty liver disease (NAFLD), is characterized by fat accumulation in the liver and is associated with obesity, insulin resistance, and metabolic syndrome. Early detection and inter-vention are crucial to prevent disease progression to advanced fibrosis, cirrhosis, and liver failure. Non-invasive tests like transient elastography (TE), the Fibrosis-4 (FIB-4) index, the Enhanced Liver Fibrosis (ELF) score, and magnetic resonance imaging (MRI) are safer and more convenient than invasive procedures like liver biopsy for detecting advanced fibrosis in MAFLD patients. Agile 3+ is a non-invasive test that combines liver stiffness measurement (LSM) with clinical and laboratory findings to detect advanced fibrosis in MAFLD patients. It has shown high accuracy in detecting advanced fibrosis in MAFLD patients. The combination of LSM and laboratory find-ings provides a more accurate assessment of disease severity, making Agile 3+ a reliable, non-invasive test for assessing liver fibrosis in MAFLD patients. In summary, MAFLD is a common condition that can progress to advanced fibrosis and liver failure if left untreated. Non-invasive tests such as Agile 3+ have emerged as valuable tools for detecting advanced fibrosis in MAFLD patients, providing a more accurate assessment of disease severity and making it a reliable non-invasive test for assessing liver fibrosis in MAFLD patients
Artificial Intelligence in Modernization of Pharmaceutical and Healthcare
Industry: A Review
Authors: Kirtania Moumita Das , Sinha Dibya , Biswas Shreya , Sultana Sania , Kirtania Ranjan 
Published: June 2024

:
Artificial intelligence (AI) falls under the purview of computer technology, which analyzes
complex data and helps solve problems in different segments. Big Data, Machine Learning, and
AI are currently being used by the major pharmaceutical industries to minimize time and costs and
increase possibilities. Artificial intelligence is used in the pharmaceutical industry in diverse ways,
such as drug discovery and development, clinical trials, disease diagnosis, and different stages in
pharmaceutical manufacturing, data analysis, and supply management. Most of the cost and time are
involved in drug discovery and clinical trials. Artificial intelligence can minimize human error in
data processing, documentation, data integrity issues, and data selection throughout the journey. It
works in descriptive, diagnostic, predictive, and prescriptive mode. Major pharmaceutical conglomerates
like Pfizer, Roche, Novartis, and Johnson & Johnson have already applied Artificial Intelligence
in different segments of pharmaceutical and medicinal science. Tech companies like IBM
Watson, Catalia Health, Intel, Microsoft, and Google, in collaboration with pharmaceutical companies,
are working in the different areas of drug discovery, early diagnosis, and personalized medicine.
Further, AI finds application in the health sector for data management, scanning and evaluation
of medical history reports, and finding optimum treatment strategies for chronic care patients.
Though lots of research and development are being done on the utilization of artificial intelligence in
the pharmaceutical industry, it is still in the nascent stage. This article is our endeavor to study, in
detail, the present and future opportunities of machine learning and AI in the pharmaceutical industry
as a whole.
Neuro-regeneration or Repair: Cell Therapy of Neurological Disorders as A Way Forward
Authors: Song Xiao-Yan , Fan Cun-xiu , Atta-ur-Rahman  , Choudhary Muhammad Iqbal , Wang Xiao-Ping 
Published: June 2024

:
The human central nervous system (CNS) has a limited capacity for regeneration and repair,
as many other organs do. Partly as a result, neurological diseases are the leading cause of medical burden globally. Most neurological disorders cannot be cured, and primary treatments focus on managing
their symptoms and slowing down their progression. Cell therapy for neurological disorders offers
several therapeutic potentials and provides hope for many patients. Here we provide a general overview of cell therapy in neurological disorders such as Parkinson’s disease (PD), Alzheimer’s disease
(AD), amyotrophic lateral sclerosis (ALS), Wilson’s disease (WD), stroke and traumatic brain injury
(TBI), involving many forms of stem cells, including embryonic stem cells and induced pluripotent
stem cells. We also address the current concerns and perspectives for the future. Most studies for cell
therapy in neurological diseases are in the pre-clinical stage, and there is still a great need for further
research to translate neural replacement and regenerative therapies into clinical settings.
Efficacy and Safety of Shi Cervical Rotational Manipulation in Patients With Atlantoaxial Joint Subluxation: Protocol for a Randomized Controlled Trial
Authors: Zhen Deng , Haibin Shang , Youli Ai , Weian Yuan , Huihao Wang , Hongsheng Zhan , Guozhong Li , Ren Ding , Zhibi Shen 
Published: June 2024

Background
The clinical diagnosis of atlantoaxial joint subluxation (AJS) in traditional Chinese medicine (TCM) is characterized by an unequal distance between the lateral mass of the atlas and the odontoid process on imaging, resulting in neck pain accompanied by symptoms such as dizziness, headache, and limited cervical mobility. In Shanghai, Shi cervical rotational manipulation (SCRM) is a commonly employed TCM manual therapy for treating this condition. Nevertheless, there is a lack of evidence-based medical information regarding the clinical efficacy and safety of this technique.

Objective
The principal aim of this study is to evaluate the efficacy and safety of SCRM in patients diagnosed with AJS.

Methods
This study is a prospective randomized controlled clinical trial that will be conducted at a single center and that has a follow-up period of 24 weeks. A total of 96 patients diagnosed with AJS will be recruited from outpatient and inpatient clinics at Shanghai Baoshan Hospital of Integrated Traditional Chinese and Western Medicine. These patients will be randomly assigned to either the experimental group (SCRM) or the comparison group (basic cervical manipulation [BCM]). Treatment sessions consisting of SCRM or BCM will be administered twice a week for a duration of 4 weeks. Clinical monitoring indicators include the presence or absence of clinical symptoms as recorded on a symptom recording form, cervical imaging examination findings using cervical computed tomography, degree of neck pain measured by a visual analog scale (VAS), cervical range of motion assessed through cervical mobility measurement, degree of vertigo evaluated using the Vertigo Symptoms Scale-Chinese Version (VSS-C), and adverse events that may occur during the follow-up period. The time points for data collection and follow-up are baseline and postintervention (weeks 4, 8, 12, 16, 20, and 24).

Results
This paper presents an overview of the reasoning and structure of a prospective randomized controlled trial with the objective of investigating the clinical efficacy and safety of SCRM in patients with AJS by assessing improvements in clinical symptoms, neck pain severity, and vertigo severity and evaluating changes in cervical imaging findings. Recruitment was started in March 2023. By the end of May 2024, 76 patients were included in this project. The last follow-up data are predicted to be collected by the end of February 2025.

Conclusions
This investigation will yield dependable evidence regarding the efficacy and safety of SCRM in patients with AJS.

Trial Registration
Chinese Clinical Trial Registry ChiCTR2300068510; https://www.chictr.org.cn/showprojEN.html?proj=186883

International Registered Report Identifier (IRRID)
DERR1-10.2196/57865
Latent autoimmune diabetes in adults: current data (review of literature and own data)
Authors: Pashkovska N.V. , Tsaryk I.O. 
Published: June 2024

The article provides up-to-date information on latent autoimmune diabetes in adults (LADA), presents data on epidemiology, factors and mechanisms of development, clinical features of this disease. The phenotypic variants of the course of LADA are described, the issues of diagnostic features and differential diagnosis are revealed. LADA is a form of diabetes characterized by a less intense autoimmune process and a wide range of clinical signs compared to classical type 1 diabetes mellitus (T1DM) and can have features of both major types of diabetes. Based on the results of epidemiological studies, the prevalence of LADA is approximately 12 % of all cases of diabetes, it is the second most common form of diabetes after type 2 diabetes mellitus (T2DM) and is the most common type of autoimmune diabetes in adults. According to the modern classification, LADA belongs to the autoimmune subtype of T1DM. Since patients do not need insulin at the beginning of the disease, the course of LADA is similar to T2DM, which is the cause of diagnostic errors. The literature data and the results of the conducted research have shown that, in addition to autoimmune damage to pancreatic beta cells, insulin resistance plays a key role in the mechanisms of LADA development, with an increase in the frequency and degree of abdominal obesity, which not only worsens metabolic control and increases the risk of metabolic syndrome, but also causes a decrease in insulin secretion and progression of the autoimmune process. In patients with LADA, the prevalence and degree of obesity, hypertension and dyslipidemia occupy an intermediate position between the classical types of diabetes. Despite having fewer metabolic risk factors compared to T2DM, patients with LADA have the same or even higher risk of death and cardiovascular diseases. The most important diagnostic markers of LADA are levels of C-peptide and autoantibodies against islet antigens. The possibility of a clear diagnosis of LADA is limited due to the significant heterogeneity of the disease due to an overlap of T1DM and T2DM symptoms. According to modern guidelines, therapeutic approaches to LADA, which are based on insulin therapy and metformin, depend on the level of C-peptide. More research is needed to improve personalized approaches to the treatment of this disease.
Gut microbiota changes and novel markers associated with liver steatosis in obese patients
Authors: Moskva Kh.A. , Kikhtyak O.P. , Kondratyuk M.O. , Farmaha M.L. , Leshchuk Ya.L. , Fediaieva S.I. , Leshchuk Ye.S. , Kikhtiak T.A. 
Published: June 2024

Background. Liver steatosis is a common condition that can progress to steatohepatitis, fibrosis, and cirrhosis and increases the risk of death from cardiovascular and liver complications. Understanding the link between steatosis and non-alcoholic fatty liver disease, obesity, and gut microbiota is essential. Recent studies have revealed that gut microbiota plays a crucial role in developing this condition, highlighting the importance of microbiota control. The purpose of the study was to detect changes in gut microbiota and new markers associated with hepatic steatosis in obese patients. Materials and methods. The study involved 60 men aged 38 to 65, divided into two groups: 32 patients with hepatic steatosis (experimental group) and 28 with no steatosis (controls). As part of the study, the levels of the lipogram were determined, anthropometric measurements were made, a bioimpedance analysis of the body was performed, as well as liver ultrasound and shear wave elastography. The gut microbiota of all participants was also examined using sequencing techno­logies (material collected from stool samples). Results. In the experimental group, there are significantly more patients with overweight, dyslipidemia (hypercholesterolemia, triglyceridemia, high low-density lipoproteins, high atherogenicity coefficient, and low high-density lipoproteins). Also, patients with hepatic steatosis are more likely to have an excessive percentage of fat and an excessive amount of visceral fat, hepatomegaly due to the craniocaudal size of the liver, and increased liver stiffness. Regarding the intestinal microbiota, there is an increase in bacterial groups belonging to the Bacteroidetes. Our analysis showed that specific markers such as body mass index, blood lipid profile, body fat percentage, and liver ultrasound parameters are essential for diagnosing steatosis. Body mass index above 24.9 kg/m2 and increased waist circumference were associated with steatosis. Bioimpedance analysis parameters, including body fat percentage and relative visceral fat level, were also crucial indicators. Dyslipidemia, with increased levels of total cholesterol, triglycerides, low-density lipoproteins, high atherogenicity coefficient, and lower high-density lipoproteins, was related to steatosis. The liver stiffness was significantly higher among patients with steatosis, indicating additional risk of liver fibrosis. Shear wave elastography can be a valuable tool for detecting liver steatosis. Conclusions. Patients with steatosis were characterized by signs of obesity (increased waist circumference, body mass index) and dyslipidemia, higher percentage of adipose tissue, relative amount of visceral fat, craniocaudal liver size, liver stiffness, and low levels of high-density lipoproteins. An increase in the gut microbiota of bacterial groups belonging to the Bacteroidetes has been observed.