bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Approach for Credit Card Fraud Transaction Detection Using Deep Reinforcement Learning Scheme
Authors: Qayoom Abdul , Khuhro Mansoor Ahmed , Kumar Kamlesh , Waqas Muhammad , Saeed Umair , Wu Yadong , Wang Song , Ur-Rehman Shafiq 
Published: June 2023

Abstract

Online transactions are the backbone of the financial industry globally. Millions of people are using credit cards daily, which has led to an exponential rise in their daily life that has led to an exponential rise in credit card frauds. With the passage of time, many variations and schemes of fraudulent transactions have been occurring. Real-time credit card fraud detection is still a challenging task. Every person has a unique transaction pattern. This pattern may vary over a period of time. Sometimes, credit card frauds have no constant pattern. This paper aims to 1) understand how deep reinforcement learning can play a vital role in detecting credit card fraud and 2) design solution architecture for real-time detection. Our proposed model uses the DeepQ network. A deep Q network has been utilized for real time detection. The online available Kaggle dataset hasbeen used for model training and testing, and 97% validation performance has been achieved via our proposeddeep learning component. The reinforcement learningcomponent has an 80% learning rate. Our proposedmodel was able to learn patterns itself based on previous history and adopted the pattern changes over timeand accommodate them without any further manualtraining.
An empirical model for branding oriented by the environmental sustainability of the Amazon Rainforest - A hybrid structural equation modeling with fsQCA approach
Authors: Santos Luiz Diego Vidal , Holanda Francisco Sandro Rodrigues , Pedrotti Alceu , de Medeiros Raphael Mario Bastos , Oliveira Catuxe Varjão de Santana , Villwock Ana Paula Schervinski 
Published: June 2023

Abstract

Using the theory of planned behavior, it is possible to establish a valuable connection between an organization and its consumers, which goes beyond appearance and involves emotions, relationships, and experiences with the brand. Based on these principles, the objective of this work was to present an empirical model guided by empirical evidence from the perception of entrepreneurs and consumers of brands related to environmental sustainability in the Brazilian Amazon. The proposed model uses mixed modeling, based on data analysis based on fuzzy-set qualitative comparative analysis (fsQCA), using two sets of data from independent research obtained from 8 companies operating in the Amazon rainforest and 535 potential consumers. Based on the observed data, the consumers' motivations for consumption, the practices adopted by entrepreneurs, and the role of traditional communities and the forest environment in the brand's conception were identified. The results show that for the interest in purchasing sustainable brands to be positive, from the perception of consumers, the brand must explore information regarding involvement with traditional communities, perception of brand quality, and brand innovation, also making clear the positioning strategy adopted since the constructs are central to the main solution. This article presents relevant information for entrepreneurs of sustainable brands in tropical forests, business policymakers in community-based entrepreneurship, researchers, and those interested in brand management as a strategy to boost small businesses with sustainable practices and involvement with traditional communities. The study's findings and recommendations can promote more sustainable and socially responsible business practices, strengthening the local economy and contributing to environmental preservation.
Gold nanowires based on photonic crystal fiber by laser ablation in liquid to improve colon biosensor
Authors: Fakhri Makram A. , Salim Evan T. , Sulaiman Ghassan M. , Albukhaty Salim , Ali Hiyam S. , Salim Zaid T. , Gopinath Subash C.B. , Hashim Uda , Al-aqbi Zaidon T. 
Published: June 2023

Abstract
In this work, gold nanoparticles have been synthesized using second harmonic generation ND-YAG laser ablation in Ethanol employing 532 nm and 1.064 nm wavelengths. Field emission scanning electron microscope (FESEM), Transmission electron microscopy (TEM)X-Ray diffraction (XRD), Atomic force microscopy (AFM), photoluminescence (PL) spectroscopy, and UV–Vis absorption were employed to examine the structural, chemical and optical properties of Au NPs. XRD results showed that all synthesized Au nanoparticles are crystalline in nature. the optical band gap upon ablation using the higher wavelength (1064 nm) was about (4.02 eV). While the value of the optical bandgap increases to reach a value of (4.22 eV) at the shorter wavelength (532 nm The FESEM results reveal the formation of smaller nano rode size at second-harmonic generation (SHG) wavelength was found to be about (30 nm at wavelength 532 nm and 44 nm at 1064nm). After that, Finite Element Analysis is used to simulate the photonic crystal fiber (PCF) as biosensors, depending on the surface Plasmon resonance (SPR) phenome-non using COMSOL Multiphasic program. The hollow core-photonic crystal fiber (HC-PCF) HC-800 was thus overfilled with (water). The confinement loss (CL) of the fundamental mode for the proposed PCF with and without the gold nanoparticles was calculated, we observe without gold NPs the CL at the water and Colon tissue about (1.08E+03, 5.46E+02) dB/m, while at use the deposited PCF with gold NPs the results ensured the decrease more than in the confinement loss at the water and Colon tissue about (1.01E+03, 3.16E+02) dB/m with a clear shift toward higher wavelengths, also when calculating the sensitivity, to increase HC-PCF bio-sensor performance by using wavelength interrogation and amplitude measurements, it found the bio-liquid (colon tissue) has the best electric field using the gold NWs layer in the biosensor equal to 68.8 V/m by comparison when without using the gold NWs layer which leads to high sensitivity.
A comparative study of machine learning approaches to heart disease prediction: an empirical analysis
Authors: Hidayaturrohman Qisthi Alhazmi , Clarke Hulya Gokalp , Taflan Gaye Yesim , Sancaktar Idris 
Published: June 2023

Abstract

Purpose:
This paper compares five supervised learning algorithms (support vector machines, k-nearest neighbor, decision tree, random forest, and AdaBoost) for predicting heart disease and examines the impact of normalization and GridSearch hyper-parameter tuning on model performance.
Methods:
The study utilizes the Cleveland database from the University of California-Irvine (UCI) repository, comprising data on 918 instances of heart disease patients with 12 attributes. Eleven attributes serve as predictors, while one attribute represents the target class. Models are built and tested using this dataset.
Results:
Comparing the algorithm performances with existing literature, accuracies range from 89.13–91.85%. AdaBoost exhibits the highest performance, whereas the decision tree performs the least effectively. Results surpass those reported in the literature. Normalization improves prediction performance by 17% for Support Vector Machines (SVM) and 14% for k-nearest neighbor (kNN). SVM does not benefit from GridSearch, while GridSearch enhances the decision tree and AdaBoost by 7% and 4% respectively. Normalization combined with GridSearch improves kNN and random forest by 2–3%.
Conclusion:
This study compares supervised learning algorithms for heart disease prediction. AdaBoost emerges as the top-performing algorithm, while the decision tree performs relatively poorly. The findings surpass those in the literature. Normalization significantly improves performance for SVM and kNN, while GridSearch enhances the decision tree and AdaBoost. Combined, normalization and GridSearch yield performance improvements for kNN and random forest. These results contribute to the field of heart disease prediction, offering valuable insights for algorithm selection and guiding future research.
Frame Duplication and Insertion Forgery Detection in Surveillance Videos Using Optical Flow and Texture Features
Authors: Akhtar Naheed , Hussain Muhammad , Habib Zulfiqar 
Published: June 2023

Abstract
Surveillance cameras are widely used to provide protection and security through online tracking or investigation of stored videos of an incident. Furthermore, footage of recorded videos may be used as strong evidence in the courts of law or insurance companies, but their authenticity cannot be taken for granted. Two common video inter-frame forgery types are frame duplication (FD) and frame insertion (FI). Several techniques exist in the literature to deal with them by analyzing the abnormalities caused by these operations. However, they have limited applicability, poor generalization, and high computational complexity. To tackle these issues, we propose a robust hybrid forensic system based on the idea that FD or FI causes motion inconsistency at the start and end of duplicated/inserted frames. These inconsistencies, when analyzed in an appropriate manner, help reveal the evidence of forgery. The system encompasses two forensic techniques. The first is a novel method based on the texture of motion residual component where a motion residual-based local binary pattern histogram (MR-LBPH) and an SVM classifier with the linear kernel are employed to detect suspected tampered positions. The second component is the sum consistency of optical flow (OF) and standard deviation of MR-LBPH of consecutive frames to remove false positives and precise localization of forgery. By taking the intersection of the frames detected by the two methods, we remove the false positives and get the frames bounding the duplicated/inserted region. The methods were trained and tested on our developed large Video Tampering Evaluation Dataset (VTED) and cross-validated on publicly available datasets. Cross-dataset evaluation yielded detection accuracy above 99.5%, ensuring the proposed method’s generalization; it also precisely locates the locations of tampering. As the public datasets used for cross-dataset validation include videos of different formats and frame rates, it ensures the wide applicability of the method. Moreover, the method is computationally efficient and can be run in a matter of microseconds.
A Comparison of the Surface Water Quality in Distinct Areas of The Southern Black Sea Coast under Various Pressures
Authors: TAN İbrahim , ATABAY Hakan , MUTLU Sabri , TOLUN Leyla Gamze , BEKEN Sevcan Çolpan POLAT 
Published: June 2023

Abstract
The Black Sea is a significant European watershed, more productive than the nearby Mediterranean, with dynamic wetland habitats along the shore and at the river mouths. Seasonal dynamics that sustain food webs that are adapted to the brackish, nutrient-rich environments are determined by the physiochemical conditions. River discharges carry phosphorus and nitrogen ions with high molar ratios into the Black Sea coasts. The present study evaluated the variations in water quality parameters between the winter season of 2020 and summer season of 2019 at 54 stations representing the two major rivers mounts (the Sakarya and Yeşilırmak), Samsun’s port and urban wastewater treatment outflow. Yeşilırmak River showed much higher nitrogen concentrations in the winter (̴ 1.46 µM) compared to the summer (̴ 0.10 µM). In addition, the Sakarya River nitrogen concentrations were similar between winter and summer seasons. The total phosphorus (̴ 2.25 µM) and chlorophyll-a (̴ 6.36 µg/L) concentrations were high at Samsun stations in the summer season 2019, where the pressure of urban wastewater is significant. The state of pollution, the sources of pollution, and their quantitative contributions in river basins and coastal regions must be determined for effective pollution control and water resource management.
A targeting nanoplatform for chemo-photothermal synergistic therapy of small-cell lung cancer
Authors: Yin Moli , Liu Lei , Yan Yu , Wang Huiyan , Li Wenliang , Dong Yuan , Kong Guangyao 
Published: June 2023

Abstract

The chemo-photothermal cotherapy has created a breakthrough in cancer treatment, but the precise delivery of drugs to tumor sites and the thermoresistance of tumors remain major challenges in photothermal therapy (PTT). Due to its overexpression in small cell lung cancer (SCLC) and limited normal tissue expression, Somatostatin receptor 2 (SSTR2) is proposed as an ideal target for the precise treatment of SCLC. We first developed a novel anti-SSTR2 monoclonal antibody (MAb), which showed strong and specific affinity toward SSTR2 receptor overexpressed on SCLC cells. Then, a targeting nano-drug delivery system comprising anti-SSTR2 MAb surface-modified poly (lactic-co-glycolic acid) (PLGA) nanoparticles co-encapsulating Cypate and gambogic acid (GA) is prepared for achieving specific tumor targeting and chemo-photothermal combination therapy. The formed SGCPNs nanoparticles demonstrated excellent monodispersity, physiological stability, preferable biocompatibility, and resultant efficient photothermal conversion efficacy. Confocal microscopy images showed that SGCPNs were quickly internalized by SSTR2-overexpressing SCLC cells, triggering the release of GA under acidic and near-infrared (NIR) laser irradiation environments, leading to their escape from lysosomes to the cytosol and then diffusion into the nucleus. At the same time, GA molecules can not only decrease the cell survival rate but also inhibit the activity of HSP90 to enhance PTT efficacy. SGCPNs can be precisely delivered to xenograft tumors of SSTR2-positive SCLC in vivo and decrease the undesirable effects on healthy organs. Upon NIR laser irradiation, therapy of SGCPNs showed significant tumor regression. In conclusion, SGCPNs provide a new chemo-photothermal synergistic treatment strategy for targeting SCLC.
D-amino acids trigger an inflammatory environment in vitro: potential role in modulating age-associated inflammation
Authors: Yap Siew Hwei , Lee Cheng Siang , Zulkifli Nur Diyana , Suresh Darshinie , Hamase Kenji , Das Kumitaa Theva , Rajasuriar Reena , Leong Kok Hoong 
Published: June 2023

Abstract
Studies in vivo have demonstrated that the accumulation of D-amino acids (D-AAs) is associated with age-related diseases as well as increased immune activation. However, the underlying mechanisms are not well defined. The metabolism of D-AAs produces hydrogen peroxide (H2O2), a reactive oxygen species that involves several physiological processes including immune response, cell differentiation and proliferation. Excessive levels of H2O2 contributes to oxidative stress and eventually causes cell death, a characteristic of age-related pathology. We explored the molecular mechanisms of D-serine (D-Ser) and D-alanine (D-Ala) in human liver cancer cells, HepG2 cells, with attention to the production of H2O2, due to the oxidation of D-AAs by D-amino acid oxidase (DAO), and secretion of pro-inflammatory cytokine and chemokine, which subsequently leads to inflammation and cell death. In HepG2 cells, we demonstrated that D-Ser decreased H2O2 production and induced concentration-dependent depolarization of MMP, with upregulation of activated NF-кB and pro-inflammatory cytokine, TNF-α, and chemokine, IL-8, which subsequently led to apoptosis. Conversely, D-Ala-treated cells induced H2O2 production, accompanied by the upregulation of activated NF-кB, TNF-α and IL-8, but did not cause significant apoptosis. The present study confirms to the role of both D-Ser and D-Ala in inducing inflammatory responses but each via unique activation pathways. This response was associated with apoptotic cell death only with D-Ser. Further research is required to gain a better understanding of the mechanisms underlying inflammation induced by D-AAs and downstream consequences especially in the context of aging given the wide detection of these entities in systemic circulation.
Epigenetic regulation of co-transcriptional R-loops via IGF2BPs drives SEMA3F-mediated prostate cancer growth retardation and docetaxel chemosensitivity enhancement
Authors: Ying Yufan , Tang Yijie , Wu Yuqing , Yi Jiahe , Liu Zixiang , Ma Xueyou , Fang Jiajie , Li Jiangfeng , Chen Danni , Wang Xiao , Liu Xiaoyan , Liu Ben , Luo Jindan , Zheng Xiangyi , Xie Liping 
Published: June 2023

Abstract
R-loops are prevalent three-stranded nucleic acid structures, comprising a DNA-RNA hybrid and a displaced single-stranded DNA, that frequently form during transcription and may be attributed to genomic stability and gene expression regulation. It was recently discovered that RNA modification contributes to maintain the stability of R-loops such as N6-methyladenosine (m6A). Yet, m6A-modified R-loops in regulating gene transcription remains poorly understood. Here, we demonstrated that insulin-like growth factor 2 mRNA-binding proteins (IGF2BPs) recognize R-loops in an m6A-dependent way. Consequently, IGF2BPs overexpression leads to increased overall R-loop levels, cell migration inhibition, cell growth retardation and docetaxel chemosensitivity in prostate cancer (PCa) via precluding the binding of DNA methyltransferase 1(DNMT1) to semaphorin 3F (SEMA3F) promoters. Moreover, the K homology (KH) domains of IGF2BPs are required for their recognition of m6A-containing R-loops and are required for tumor suppressor functions. Our findings point to a distinct R-loop resolution pathway mediated by IGF2BPs, emphasizing the functional importance of IGF2BPs as epigenetic R-loop readers in transcriptional genetic regulation and cancer biology.
Recent Advances and Prospective on the effect of processing parameters, additives, and applications of silica aerogel nanocomposites
Authors: Jadhav Sapna B. , Sarawade Pradip B. 
Published: June 2023

Abstract
Silica Aerogels have emerged as a new class of porous solid-state nanomaterials which consist of a three‐dimensional (3D) solid silica network with a huge air-filled space of highly cross-linked structures. Due to the distinct features, such as high porosity, large surface area, extremely low density, and low thermal conductivity, they show potential applicants in various emerging fields. Silica aerogel limits its application due to its fragile nature; as a result, it is essential to develop mechanical strength. To enhance the widespread industrial application of silica aerogel in the future, reinforcement of fiber/polymer/metal oxide has been widely studied. This overview particularly emphasizes achieving mechanisms of mechanical strength on the recent advances regarding various additives into the silica matrix. Also, the outline of the significant improvements in the resultant mechanical strength, thermal conductivity, porosity, and surface area of the nanocomposites are represented. In this review, we have elaborated on the synthesis of the silica aerogel, fillers trapped inside the silica matrix aerogel pores, and its application in potential fields.
Numerical Analysis of Prey Refuge Effects on the Stability of Holling Type III Four-Species Predator-Prey System
Authors: Odhiambo Francis , Aminer Titus , Okelo Benard , Manyala Julius 
Published: June 2023

Abstract
The dynamic behavior of a multi-species system that includes a prey refuge and a Holling type III functional response is examined in this work. The pre-requisites for the presence of the equilibrium points, as well as their local and global stabilities, for the suggested system are analyzed and derived. The Routh-Hurwitz criterion and the eigenvalue technique are used to study the local stabilities. On the other hand, the global stabilities have been studied using the Lyapunov technique. Numerical simulations have been carried out using the Matlab ode45 solver software to verify the analytical results. The findings show that refuge plays a significant part in improving the dynamical stability of the system.
Assessment of the association between D-dimer levels and clinicopathological characteristics of pancreatic cancer and its role in prognosis: a systematic review and meta-analysis
Authors: wu bin , Zhang ming guang , Zhao shuang xia , Wang jie , Wang da , Zhang peng yi , Yu Miao , Cai hui 
Published: June 2023

Abstract

Background: According to previous studies, D-dimer levels are associated with prognosis in patients with pancreatic cancer (PC). However, the current results are limited and controversial. Therefore, we conducted this meta-analysis to assess the relationship between D-dimer levels and the prognosis and pathological characteristics of patients with PC.
Method: A computer search of PubMed, Embase, The Cochrane Library, Web Of Science, CBM, VIP, CNKI and Wanfang databases was conducted to identify available studies. The association between pre-treatment d -dimer levels and the prognosis of PC patients was assessed using a combined hazard ratio (HR) and 95% confidence interval (CI). The combined odds ratio (OR) and 95% confidence in CI were applied to assess the relationship between D-dimer levels and the pathological characteristics of patients with PC. For all of the statistical analyses, Stata 12.0 software was used.
Result: A total of 13 studies involving 2777 patients were included in this meta-analysis. The results showed that elevated pre-treatment d -dimer levels were significantly associated with worsening OS (HR = 1.46 95% CI: 1.34-1.59; p＜0.001). We also performed subgroup analyses based on sample size, d -dimer threshold, follow-up time and source of HR to further validate the prognostic value of pre-treatment d -dimer levels in PC. In addition, according to the analysis, high pre-treatment d -dimer levels in PC patients were associated with late tumour stage (OR = 4.78, 95% CI 1.73-13.20, p＜0.005), larger tumours (OR = 1.72, 95% CI 1.25 ~ 2.35, p＜0.005) and distant metastases in tumours (OR = 5.06, 95% CI 2.45- 10.43, p＜0.005) were significantly associated. In contrast, other clinicopathological factors, including age, sex and lymph node metastasis, were not associated with d -dimer levels.
Conclusion: High levels of d-dimer prior to treatment are associated with poor prognosis in patients with PC and are associated with more advanced tumour stage, larger tumours and the occurrence of distant metastases. Plasma d-dimer levels can be used as a biomarker of prognosis in patients with PC.
La escena de la música rock en la frontera entre Estados Unidos y México: traducción y adaptación cultural
Authors: Sánchez José , Soto-Vázquez Arthur 
Published: June 2023

Este estudio aborda cómo la música rock se integró en la cultura local de una región donde los géneros musicales dominantes eran el tejano y otras formas de inﬂuencia mexicana. Usando una serie de entrevistas cualitativas y profundas con músicos de larga práctica, discutimos cómo se formó el rock y cómo se mezcló con las costumbres y prácticas locales. Los músicos hablaron sobre ser ﬂexibles en sus presentaciones en vivo, tocar canciones de la invasión británica justo después de un corrido, ser marginados y actuar en ranchos fuera de los límites de la ciudad cuando los clubes no los presentaban. Sin embargo, la escena de la música rock local se desarrolló en el sur de Texas y se convirtió en un híbrido cultural único. Usamos este ejemplo para discutir cómo se ve la hibridez cultural en el contexto de la interpretación musical, el papel de los nuevos medios en su avance y lo que significa para la identidad fronteriza.