bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Adaptive Learning Rate Deep Learning Optimizer Using Long and Short-Term Gradients Based on G-L Fractional-order Derivative
Authors: Chen Shuang , Zhang Changlun , Mu Haibing 
Published: September 2023

Abstract
Deep learning model is a multi-layered network structure, and the network parameters that evaluate the final performance of the model must be trained by a deep learning optimizer. In comparison to the mainstream optimizers that utilize integer-order derivatives reflecting only local information, fractional-order derivatives optimizers, which can capture global information, are gradually gaining attention. However, relying solely on the long-term estimated gradients computed from fractional-order derivatives while disregarding the influence of recent gradients on the optimization process can sometimes lead to issues such as local optima and slower optimization speeds. In this paper, we design an adaptive learning rate optimizer called AdaGL based on the Grünwald-Letnikov (G-L) fractional-order derivative. It changes the direction and step size of parameter updating dynamically according to the long-term and short-term gradients information, addressing the problem of falling into local minima or saddle points. To be specific, by utilizing the global memory of fractional-order calculus, we replace the gradient of parameter update with G-L fractional-order approximated gradient, making better use of the long-term curvature information in the past. Furthermore, considering that the recent gradient information often impacts the optimization phase significantly, we propose a step size control coefficient to adjust the learning rate in real-time. To compare the performance of the proposed AdaGL with the current advanced optimizers, we conduct several different deep learning tasks, including image classification on CNNs, node classification and graph classification on GNNs, image generation on GANs, and language modeling on LSTM. Extensive experimental results demonstrate that AdaGL achieves stable and fast convergence, excellent accuracy, and good generalization performance.
Instruction of Data Analysis: Take Wordle as an example
Authors: Jiang Yuchen 
Published: September 2023

Abstract
Have you ever been helpless with huge data? Don’t know how to extract useful information from massive data? This article is designed to help you analyze your data step by step through Wordle game. Wordle is a recently developed word game that offers instantaneous feedback for each attempt and attracts a substantial player base. The act of sharing daily play statistics on Twitter by a significant number of players generates a considerable volume of data. Therefore , a study is being conducted based on the aforementioned data. This paper centers on examining Wordle’s statistical metrics and formulating prognostica-tions regarding forthcoming player figures through a variety of models, including ARIMA, KNN and neural network. The Gradient Boosting Decision Tree algorithm was employed to forecast the number of attempts by leveraging the analysis of word frequency and letter repetition within words. The K-means and Gaussian mixture model were used for clustering the difficulty levels of all words. Subsequently , the difficulty level of the word ”EERIE” was predicted. These steps will provide guidance for conducting data analysis in the future work. Our code is available at https://github.com/3249514357enenenyue/wordle
Prediction and detection of localised corrosion attack of stainless steel in biogas production: Machine Learning Classification Approach
Authors: Jimenez-Come María Jesús , Gallero Francisco Javier González , Gómez Pascual Álvarez , Matres Victoria 
Published: September 2023

Abstract
Biogas contributes to environmental protection by reducing greenhouse gas emissions and promoting the recycling of organic waste. Its utilization plays a crucial role in addressing the challenges of climate change and sustainability. However, the deterioration of process plants involved in biogas production due to corrosion has a critical impact on the safety and durability of their operations. In order to maintain safety of structures in service life with respect to corrosion, it is essential to develop effective corrosion engineering control methods. The electrochemical techniques have become a useful tool to evaluate corrosion resistance. However, these techniques may require microscopic analysis of the material surface and the analysis may be influenced by subjective factors. To solve this drawback, this work proposes the use of SVM models to predict corrosion status of the material used in biogas production with no need to perform microscopic analysis after the electrochemical test. The obtained results of sensitivity and specificity equal to 0.94 and 0.97, respectively, revealed the utility of the proposed stochastic models to assure the corrosion state of the equipment involved in biogas production. SVM-based models become an effective alternative to evaluate material durability accurately.
Bevacizumab and Gamma Knife Radiosurgery for First-Recurrence Glioblastoma
Authors: Zhang Jeff F. , Okai Bernard , Iovoli Austin , Goulenko Victor , Attwood Kristopher , Lim Jaims , Hess Ryan M. , Abad Ajay P. , Prasad Dheerendra , Fenstermaker Robert A. 
Published: September 2023

Abstract
Introduction
Glioblastoma (GBM) is the most common central nervous system malignancy in adults. Despite decades of developments in surgical management, radiation treatment, chemotherapy, and tumor treating field therapy, GBM remains an ultimately fatal disease. There is currently no definitive standard of care for patients with recurrent glioblastoma (rGBM) following failure of initial management.
Objective
In this retrospective cohort study, we set out to examine the relative effects of bevacizumab and Gamma Knife radiosurgery on progression-free survival (PFS) and overall survival (OS) in patients with GBM at first-recurrence.
Methods
We conducted a retrospective review of all patients with rGBM who underwent treatment with bevacizumab and/or Gamma Knife radiosurgery at Roswell Park Comprehensive Cancer Center between 2012 and 2022. Mean PFS and OS were determined for each of our three treatment groups: Bevacizumab Only, Bevacizumab Plus Gamma Knife, and Gamma Knife Only.
Results
Patients in the combined treatment group demonstrated longer post-recurrence median PFS (7.7 months) and median OS (11.5 months) compared to glioblastoma patients previously reported in the literature, and showed improvements in total PFS (p=0.015), total OS (p=0.0050), post-recurrence PFS (p=0.018), and post-recurrence OS (p=0.0082) compared to patients who received either bevacizumab or Gamma Knife as monotherapy.
Conclusion
This study demonstrates that the combined use of bevacizumab with concurrent stereotactic radiosurgery can have improve survival in patients with rGBM.
Role of a cuproptosis-related prognostic signature in uveal melanoma tumor microenvironment and immune responses
Authors: Zhong Enyu , Yu Li , Cao Yuchang , Lu Ye , Cao Yang 
Published: September 2023

Abstract
Background
The most common intraocular cancer is uveal melanoma (UVM). A unique mechanism of cell death, known as cuproptosis, is linked to the development, prognosis, and immunity of tumors. Cuproptosis-related genes (CRGs) may play a role in UVM prognosis; however, this remains unclear.
Methods
We performed single-cell analysis and unsupervised cluster analysis from the Gene Expression Omnibus and The Cancer Genome Atlas (TCGA)-UVM databases. Weighted gene co-expression network analysis (WGCNA) was used to identify genes associated with molecular subtypes and cuproptosis scores. The least absolute shrinkage and selection operator, and multivariate Cox analysis were then used to build a prognostic risk model. Using Cox analysis, independent prognostic indicators were confirmed.
Results
We identified two prognostic genes (DLD and PDHB) to construct the CRGs signature. Using Cox regression analysis, the risk score was found to be an independent prognostic predictor. Significantly more patients in the low-risk group survived than those in the high-risk group. Meanwhile, nine immune cells (Monocytes, M1 macrophages, T cells CD8), immune score, stromal score, two immune cells and related functions (aDCs and Th2 cells), and immune checkpoint expression (ICOS, CD48, and CD70) were all related to the risk score. The correlation of DLD and Wnt.C59, Sinularin were investigated. And meanwhile, it was confirmed that PDHB was significantly relevant to fibroblasts and NK cells. Finally, the expressions of DLD and PDHB might be affected by the KEGG pathway of cell cycle and Ubiquitin mediated proteolysis.
Conclusion
This study identified cuproptosis-associated prognostic genes for UVM and provided new insights into its treatment.
STO-Enabled Double Perovskite Solar Cell Incorporating (FA) 2 BiCuI 6 as Absorber Material Without HTL
Authors: Yadav Shivangi , Lohia Pooja , Sahu Anupam 
Published: September 2023

Abstract
In this study, an environmental friendly heterostructure perovskite solar cell is constructed using non-toxic, lead-free double perovskite material (FA)2BiCuI6 as an active layer. The proposed device architecture is FTO/STO/(FA)2BiCuI6/GO/Pd. An extensive theoretical analysis and optimization is conducted using SCAPS-1D simulation tool. The thickness of absorber layer, shallow acceptor density, back metal contact and operating temperature are varied to optimize performance parameter of device. Optimized results have been observed at 700 nm absorber thickness for shallow acceptor density 1.0 × 1019 cm− 3 and 300 K operating temperature. A small value of series resistance 1 Ω cm2 along with high shunt resistance 100000 Ω cm2 is incorporated from the initial condition. The solar cell characteristics obtained are as open circuit voltage 1.10 V, short circuit current density 26.03 mA/cm2, fill factor 86.62 %, and device power conversion efficiency 24.69 %. The study concludes that the metal-work function can be carefully modulated to further enhance the performance characteristics of a device. Further current density–voltage characteristics (J-V), capacitance-voltage (C-V), and capacitance-frequency (C-f) characteristics have also been studied to explore the electrical characteristics of device. These findings suggest that a thorough analysis of materials could lead to their potential use as a high-performance active material for solar applications.
Examining Factors Affecting Mobile Money Usage and Its Impact on Livelihood in Ghana
Authors: Adams Ekuban Charles Aaron , Gopakumar Shivapratap 
Published: September 2023

Abstract

The study examines factors affecting the acceptance of mobile money usage and its impact on livelihood in Ghana. A holistic view of mobile money usage suggests that, it is still a rapidly a novel area for research in developing countries and has the potential to better the livelihoods of people. For this reason, it is imperative to find out the factors affecting the wide usage of mobile money and its impact on livelihood. It used TAM as the theoretical lens to examine mobile money user’s acceptance and empirically validated data by using regression analysis. Data was collected from mobile money users through an online survey through a structured questionnaire. Purposive and Simple Random sampling approach, were used as the research methodology to select 385 mobile money users in Ghana. Results showed that all constructs (PU, PEOU, PS, PEOL) influenced consumers' desire to use mobile money services which has improved and facilitated the growth of small businesses, provided secure transactions, and provided savings. Mobile money services have also given access to credit, reduced corruption, and job opportunities in areas like customer service, mobile money agent networks. The study recommends that mobile money service providers should provide services that provide ease of use and usefulness to consumers.
Comparative Environmental Impact Analysis of Electric, Hybrid, and Conventional Internal Combustion Engine Vehicles
Authors: Sinha Rohit 
Published: September 2023

Abstract
This research paper presents a comprehensive wringer of the environmental impact of electric cars, hybrid cars, and conventional internal combustion engine (ICE) cars, with a focus on challenging the conventional weighing that electric cars are inherently increasingly environmentally friendly. Drawing inspiration from a recent study conducted by Prof. Avinash Agarwal of IIT Kanpur, this research seeks to provide a unique perspective on the topic by considering various factors and providing fresh insights into the sustainability of these automotive technologies. The study employs a holistic life cycle assessment (LCA) approach, examining not only tailpipe emissions but moreover manufacturing, electricity generation, and end-of-life disposal impacts. The findings of the research indicate that environmental advantages of electric cars are context-dependent and may not unchangingly outweigh those of hybrid and conventional ICE cars.
A cognitive study on hospital-acquired pneumonia among students from the Faculty of Medicine at the Syrian Private University
Authors: Alshebany Nour Alhuda , Al-Daher Nizar 
Published: September 2023

Abstract
Background
Hospital acquired pneumonia (HAP), or nosocomial pneumonia, is an infection of the lower respiratory tract that was not incubated at the time of hospital admission and that presents clinically 2 or more days after hospitalization. Conducting research on nosocomial acquired pneumonia helps to raise awareness and raise awareness of the importance of preventing and avoiding infection with this disease, and also helps to identify best practices and preventive measures to avoid the spread of infection in hospitals. Our study mainly aimed at evaluating awareness among students of the Faculty of Medicine at the Syrian Private University.
Methods
A cross-sectional study, conducted at the Syrian Private University, included 250 male and female students from 3/6/2023 to 8/8/2023. It included students of the Syrian Private University, Faculty of Medicine.
Results
Out of 250 students who participated in the study, the percentage of females was 142 (56.8%), compared to 108 (43.2%). The largest percentage of sixth-year students was 112 (44.8%). The ages of the participating students ranged from 18–33 years, with an average age of 22 years. The source of information for students was university study 200 (43.1%), followed by clinical training in hospital 102 (22%). It was found that the students had a good awareness about the disease, which reached 220 (88%). Female students had more knowledge about the disease (94%), compared to males (79%). The knowledge of fourth-year students was the greatest, 36 (100%), followed by sixth-year students, 110 (98.2%).
Conclusion
The results of our study indicate an acceptable degree of awareness among medical students at the Syrian Private University. It is useful to conduct more studies that include a larger number of students in other universities to avoid bias. We also recommend generalizing the pattern of our studies to the rest of the Syrian universities to evaluate students’ knowledge of common cases in our country and their diagnosis constitutes Its management is of great importance because it is associated with high morbidity and mortality
Formation of postural control in infants of the first year of life with impaired motor development, born at different gestation periods
Authors: Samsonova T. V. , Krivonogov V. A. , Nazarov S. B. , Rylskaya Yu. A. 
Published: September 2023

The postural control development is a complex physiological process, which is the basis for the development of motor functions. Approaches to the assessment of postural control and the features of its formation in infants of the first year of life have not been studied enough. Purpose. To reveal the features of postural control development in infants of the first year of life with the consequences of perinatal lesions of the central nervous system in the form of impaired motor development, born at different gestational ages. Material and methods. We examined 120 infants of the first year of life with impaired motor development and 16 infants without neurological pathology. Infants with impaired motor development were divided into 4 subgroups: 1 (n = 30) — full-term, 2 (n = 30) — very preterm, 3 (n = 30) — moderately preterm, 4 (n = 30) — late premature children depending on their gestational age at birth. The examination was conducted at 3–4 months of calendar age in full-term and corrected in premature infants and included an assessment of the neurological status, a clinical assessment of postural control, and computer stabilometry. Results. Violation of postural control was found in infants of the first year of life with the consequences of perinatal lesions of the central nervous system in the form of impaired motor development, born at different gestational ages. These postural disorders may be associated with changes in muscle tone and impaired sensorimotor integration. Conclusion. Further research will enable the development of objective criteria for diagnosing postural disorders in infants of the first year of life, depending on the gestational age at birth. This will contribute to the timely start of treatment and rehabilitation measures, reducing the frequency and severity of disabling consequences of perinatal lesions of the central nervous system.
Idiopathic paroxysmal atrioventricular block
Authors: Kovalyov I. A. , Soloviov V. M. , Shabaeva E. R. , Egorov L. V. , Termosesov S. A. 
Published: September 2023

The article presents a clinical case of paroxysmal atrioventricular block, which is a rare and difficult to diagnose cause of syncope, which makes it difficult for specialists to make a correct diagnosis and determine the tactics of patient management. Purpose. To demonstrate a clinical case, in which comprehensive methods of examination were carried out to identify the cause of syncope, and to show the need of understanding its pathogenesis. For differential diagnosis, it is necessary to carry out not only routine examination methods, but also to use drug tests, as well as long-term monitoring devices (multi-day daily Holter monitoring, loop recorders of long-term ECG recording, smart watches, etc.), which help to find the cause of syncope. According to the clinical recommendations, patients with atrioventricular block and clinical symptomatology, require continuous cardiac pacing in order to prevent asystole with potential sudden cardiac death.
The implications of food loss on East Africa's environment and water resources
Authors: Kipkirui Edwin , Zhao Jianfu , Wang Tao , Bavumiragira Jean Pierre , James Joseph Cirily , Ndizeye Yves 
Published: September 2023

Abstract

Food losses threaten food security and sustainability in East Africa, a region that faces recurrent droughts and socio-economic shocks. The research utilized the water footprint method and the carbon emission factor to quantify the water footprint and the carbon footprint of food losses of five plant-based food varieties: cereals, vegetables, oil crops, fruits, and pulses. The study focused on the actual food losses in East Africa – Kenya, Uganda, and Tanzania – obtained from the enhanced food balance sheets in 2017. The study finds that the volume of the water wasted associated with the food losses (green + blue) was 6,164.1 million m3 (M.m3). Food loss also contributes to the degradation of the environment in the form of greenhouse gases (e.g. CO2 and CH4) and a source of non-point pollution of water resources. As a result, the greywater footprint was 838.1 M.m3 and carbon emissions were 5.53 million tons. In contrast to Kenya and Tanzania, Uganda had the lowest carbon and water footprint. These results can further clarify our understanding of the regional and global impacts of food losses on the environment and suggest that reducing food losses can help improve food security, conserve water resources, and protect the environment.
Effect of ultrasound-assisted EDTA and citric acid washing on heavy metal removal, residual heavy metal mobility, and sewage sludge quality
Authors: Lu Hongpei , Wu Yonggui , Luo Youfa , Li Ziran , Wang Ziqi , Peng Xiaoyu , Qiang Yibin 
Published: September 2023

Abstract

We investigated the effects of ultrasound-assisted ethylenediaminetetraacetic acid (EDTA) and citric acid (CA) washing on heavy metal (HM) removal, residual HM mobility, and sewage sludge quality. EDTA and CA washing of sewage sludge successfully reduced the total concentration of HMs after one round of washing, but the mobility of residual HMs increased significantly. The eluate had a high concentration of HMs and nutrients (nitrogen, phosphorus, potassium, and total organic carbon), although the nutritional content of the sludge remained high. The three-phase ratio of the sludge after six rounds of washing by CA was closest to the ideal three-phase ratio, and the degree of influence on the physical structure of the soil after a land application was reduced, according to the fluctuation of generalized soil structure index (GSSI) and soil three-phase structure distance (STPSD) values. The results indicate that CA as an environmental-friendly washing agent can be the superior choice for sludge HM washing; single washing of sewage sludge may increase the mobility of residual HMs, so multiple washings should be considered for land application of sludge.
Applying Natural Language Processing to Textual Data From Clinical Data Warehouses: Systematic Review
Authors: Bazoge Adrien , Morin Emmanuel , Daille Béatrice , Gourraud Pierre-Antoine 
Published: September 2023

Background
In recent years, health data collected during the clinical care process have been often repurposed for secondary use through clinical data warehouses (CDWs), which interconnect disparate data from different sources. A large amount of information of high clinical value is stored in unstructured text format. Natural language processing (NLP), which implements algorithms that can operate on massive unstructured textual data, has the potential to structure the data and make clinical information more accessible.

Objective
The aim of this review was to provide an overview of studies applying NLP to textual data from CDWs. It focuses on identifying the (1) NLP tasks applied to data from CDWs and (2) NLP methods used to tackle these tasks.

Methods
This review was performed according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. We searched for relevant articles in 3 bibliographic databases: PubMed, Google Scholar, and ACL Anthology. We reviewed the titles and abstracts and included articles according to the following inclusion criteria: (1) focus on NLP applied to textual data from CDWs, (2) articles published between 1995 and 2021, and (3) written in English.

Results
We identified 1353 articles, of which 194 (14.34%) met the inclusion criteria. Among all identified NLP tasks in the included papers, information extraction from clinical text (112/194, 57.7%) and the identification of patients (51/194, 26.3%) were the most frequent tasks. To address the various tasks, symbolic methods were the most common NLP methods (124/232, 53.4%), showing that some tasks can be partially achieved with classical NLP techniques, such as regular expressions or pattern matching that exploit specialized lexica, such as drug lists and terminologies. Machine learning (70/232, 30.2%) and deep learning (38/232, 16.4%) have been increasingly used in recent years, including the most recent approaches based on transformers. NLP methods were mostly applied to English language data (153/194, 78.9%).

Conclusions
CDWs are central to the secondary use of clinical texts for research purposes. Although the use of NLP on data from CDWs is growing, there remain challenges in this field, especially with regard to languages other than English. Clinical NLP is an effective strategy for accessing, extracting, and transforming data from CDWs. Information retrieved with NLP can assist in clinical research and have an impact on clinical practice.