bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of Mobile Technologies on Consumer Behavior in Retail Marketing
Authors: Wilson George , Brown William , Johnson Oliver
Published: July 2024

This study explores the impact of mobile technologies on consumer behavior in retail marketing, examining how advancements in mobile platforms have transformed shopping habits and interactions with brands. Mobile technologies have revolutionized the retail experience by providing unprecedented convenience, allowing consumers to shop at any time and from any location. This shift has led to a marked preference for mobile shopping over traditional methods, fundamentally altering consumer behavior. Key findings reveal that personalization plays a crucial role in enhancing consumer engagement and satisfaction, with mobile technologies enabling tailored recommendations and offers based on individual preferences. Access to real-time information, such as product details and price comparisons, empowers consumers to make more informed purchasing decisions, reflecting a shift towards deliberate and confident buying choices. Social media and social commerce have also become significant factors, with consumers discovering new products and brands through these platforms and benefiting from integrated shopping features. Impulse buying behavior has increased due to the convenience of mobile shopping, with promotional alerts and simplified payment processes contributing to spontaneous purchases. The integration of mobile technologies with physical store experiences has created a more seamless shopping journey, bridging the gap between online and offline interactions. However, challenges such as privacy concerns, data security, and information overload remain significant. Consumers are increasingly aware of data collection risks and may experience fatigue from excessive marketing messages. To navigate this evolving landscape, retailers must balance the advantages of mobile technologies with addressing these challenges to effectively meet consumer needs and expectations.
Enhancing Spreading Factor Assignment in LoRaWAN with a Geometric Distribution Approach for Practical Node Distributions
Authors: Tempiem Phanupong , Silapunt Rardchawadee
Published: July 2024

This paper proposes the GD (Geometric Distribution) algorithm, a novel approach to enhance the default Adaptive Data Rate (ADR) mechanism in the Long Range Wide Area Network (LoRaWAN). By leveraging the Probability Mass Function (PMF) of the GD model, the GD algorithm effectively addresses massive device distribution challenges in real-life scenarios. To evaluate the algorithm's performance, the LoRaWAN simulations were conducted using the fixed node pattern derived from actual locations of dairy farms in Ratchaburi province, Thailand. The research established scenarios for assessing the network's performance namely, DER (Data Extraction Rate) and SF (Spreading Factor) assignment. Comparative analyses were performed against the uniform random node pattern and established algorithms, including the default ADR scheme, EXPLoRa, Quantile Classification of Variance from the Mean (QCVM), and Standard Deviation (SD). The GD algorithm demonstrated significant improvements over existing methodologies for both fixed and uniform random patterns. The fixed pattern exhibited an enhancement of 14.3%, while the uniform random pattern showed 4.8% enhancement over the default ADR scheme. Further assessments covered the coverage area, payload size, and energy consumption. The GD algorithm consistently achieved the optimal DER values with a coverage area and payload size, albeit often at the expense of increased energy consumption.
Towards More Nature-Positive Outcomes: A Review of Corporate Disclosure and Decision-Making on Biodiversity
Authors: Senanayake Maheshika , Harymawan Iman , Dorfleitner Gregor , Lee Seungsoo , Rhee Jay Hyuk , Ok Yong Sik
Published: July 2024

Biodiversity loss and nature degradation are pressing issues with huge impacts on our society and economy. Businesses, investors, and regulators focus on corporate efforts to support biodiversity and nature positive actions. This review provides a comprehensive overview about the importance of biodiversity in businesses, the materiality of biodiversity and the role of mandatory and non-mandatory regulations on corporate environmental reporting and sustainability disclosure frameworks. The review also discusses descriptive information on the evolution of sustainability frameworks with a comparison of most prominent sustainability frameworks with a key focus on the materiality approach and biodiversity-related disclosure recommendations. Further, we provide suggestions for more holistic approaches to improve the future sustainability frameworks focusing on the biodiversity impact while showing the necessity of more focus on the decision-making paradigm. Further research on measuring biodiversity impact and innovative trends in sustainability reporting are required to better reflect nature-positive outcomes in corporate sector businesses.
A Comparison of Tools That Identify Tumor Cells by Inferring CNVs from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma
Authors: Oketch Daisy J. A. , Giulietti Matteo , Piva Francesco
Published: July 2024

Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumour cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analysed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms.
Can Selected Parameters of Brain Injury Reflect Neuronal Damage in Smoldering Multiple Sclerosis?
Authors: Niedziela Natalia , Nowak-Kiczmer Maria , Malciene Lina , Stasiołek Mariusz , Zalejska-Fiolka Jolanta , Czuba Zenon P , Niedziela Jacek T , Szczygieł Jarosław , Lubczyński Michał , Adamczyk-Sowa Monika
Published: July 2024

Background: Inflammatory demyelination and impaired recovery processes result in permanent neurodegeneration and neurological disability in patients with multiple sclerosis (MS). In terms of smoldering MS, chronic neuroinflammation develops in the early period of the disease and leads to confirmed disability accumulation. There is a great need to identify biomarkers of neuro-degeneration and disease progression. Methods: We evaluated the concentrations of the param-eters of brain injury (NF-H, GPAF, S100B, UCHL1) in the cerebrospinal fluid (CSF) and the se-lected interleukins (ILs) in serum of 123 relapsing-remitting MS (RRMS) and 88 progressive MS (PMS) patients. Results: The levels of GFAP, S100B and UCHL were higher in the PMS group compared to RRMS as opposed to the levels of NF-H. We observed a positive correlation be-tween the selected pro-inflammatory cytokines and the parameters of brain injury. The Ex-panded Disability Status Scale score (EDSS) increased with GFA and NF-H levels and correlated with the selected ILs. The concentrations of S100B, UCHL1 and NF-H reflected the duration of MS symptoms. Conclusions: The levels of brain injury parameters in the CSF and the selected serum ILs in MS patients seem to be promising biomarkers to determine neurodegeneration and neuroinflammation in smoldering MS. Further studies are warranted in this respect.
2024 Update on Position Statement by Experts from the Polish Society of Allergology and the Polish Respiratory Society on the Evaluation of Efficacy and Effectiveness of Single Inhaler Triple Therapies in Asthma Treatment
Authors: Śliwiński Paweł , Antczak Adam , Barczyk Adam , Białas Adam Jerzy , Czajkowska-Malinowska Małgorzata , Jahnz-Różyk Karina , Kulus Marek , Kuna Piotr , Kupczyk Maciej
Published: July 2024

Medication non-adherence remains a substantial obstacle in asthma care, prompting the exploration of novel therapeutic modalities that prioritize rapid symptom relief, anti-inflammatory activity and facilitate patients’ compliance. This task is well served by a new form of therapy - inhaled triple-combination medications ICS/LABA/LAMA (inhaled glucocorticosteroid/long-acting beta2-agonist/long-acting muscarinic antagonist). The integration of three medications within a singular inhalation device culminates in the reduction of the effective dose of the principal therapeutic agent for asthma management, namely, ICS. This consolidation yields a dual benefit of minimizing the likelihood of adverse effects typically linked with ICS while concurrently optimizing bronchodilator efficacy. The accumulated evidence suggests that adding LAMA to a medium- or high-dose ICS/LABA results in a decrease of asthma exacerbations compared to medium- or high-dose ICS/LABA alone, accompanied by sustained enhancements in lung function parameters. We propose in adult patients experiencing suboptimal asthma control despite medium/high-dose ICS/LABA treatment - regardless of adherence to GINA-recommended strategies, such as MART therapy as a first-line approach or alternative second-line strategies - the preferred course for intensifying asthma therapy involves the addition of a LAMA, ideally in the form of SITT.
Utilization of the Fungus Pycnoporus sp. for Remediation of a Sugarcane Industry Effluent
Authors: Farfán Clara , Lozano Verónica Laura , Borja Claudia Nidia , Alvarez Dalinger Florencia , Muñoz Camila , Moraña Liliana
Published: July 2024

Lignocellulosic fungi are highly versatile organisms with valuable applications in bioremediation processes, including the biodegradation of agro-industrial effluents. In this work, the use of a native strain of the white-rot fungus, Pycnoporus aff. sanguineus, was studied for its use in the bioremediation of the sugar industry waste called vinasse, originating from the San Martín del Tabacal Sugar Mill, located in the north of the Salta province, Argentina. We studied under controlled laboratory conditions the bioremediation process of 3 concentrations of vinasse (5, 10, and 25% in distilled water) with a native isolated strain. The results showed biomass growth at all three tested concentrations, with a maximum at the highest vinasse concentration (25%), while the percentages of color and Chemical Oxygen Demand (COD) removal indicated that the most efficient treatment was with 10% vinasse. The results obtained are promising for the treatment of effluents from the sugar industry using white-rot fungi considering the valuable subproducts of Pycnoporus spp. biomass.
Proteomics and PTMomics to Unveil Metabolic Regulation
Authors: Zhang Hong
Published: July 2024

Proteomics is the study of cellular proteome by investigating how different proteins interact with each other and the roles they play in the organism. For mRNA expression levels do not always correlate well with protein expression levels, and the study of mRNA does not consider protein posttranslational modifications (PTMs), complex formation and localization; all of which are key to protein function. Quantitative proteomics uses mass spectrometry to identify and quantify proteins so as to find differentially expressed proteins under different condition. This allows us to gain biological insights under stress or other pathological conditions. posttranslational modifications, such as lysine acetylation, succinylation and lactylation, occur after protein biosynthesis and play vital roles in protein activity and cell physiology regulation. Here we present the mass spectrometry analysis in detail to unveil protein acylase and deacylase’ roles in metabolic regulation based on PTMomics lysine acetylome and suincylome.
Enhancing Coleoptile Length of Rice Seeds under Submergence through NAL11 Knockout
Authors: Zhao Zhe , Xie Yuelan , Tian Mengqing , Liu Jinzhao , Chen Chun , Zhou Jiyong 中国 , Guo Tao , Xiao Wuming
Published: July 2024

Submergence stress challenges direct seeding in rice cultivation. In this study, we identified a heat shock protein, NAL11, with a DnaJ domain, which can regulate the length of rice coleoptiles under flooded conditions. Through bioinformatics analyses, we identified cis-regulatory elements in its promoter, making it responsive to abiotic stresses, such as hypoxia or anoxia. Expression of NAL11 was higher in the basal regions of shoots and coleoptiles during flooding. NAL11 knockout triggered the rapid accumulation of abscisic acid (ABA) and reduction of Gibberellin (GA), stimulating rice coleoptile elongation and contributes to flooding stress management. In addition, NAL11 mutants were found to be more sensitive to ABA treatments. Such knockout lines exhibited enhanced cell elongation for coleoptile extension. Quantitative RT-PCR analysis revealed that NAL11 mediated the gluconeogenic pathway, essential for the energy needed in cell expansion. Furthermore, NAL11 mutants reduced the accumulation of reactive oxygen species (ROS) and malondialdehyde under submerged stress, attributed to an improved antioxidant enzyme system compared to the wild-type. In conclusion, our findings underscore the pivotal role of NAL11 knockout in enhancing the tolerance of rice to submergence stress by elucidating its mechanisms. This insight offers a new strategy for improving resilience against flooding in rice cultivation.
Health-Related Quality of Life among Elderly Patients in Urban Bangladesh: A Cross-Sectional Study
Authors: Imran Joynal Abedin , Mitra Amal K. , Ria Marzana Afrooj , Mitra Tumpa , Konok Jannatul Ferdous , Shuchi Sadia Akter , Saha Pradip Kumar
Published: July 2024

Quality of life (QoL) focuses on a person’s ability to live a fulfilling life. In the elderly population, it helps in determining successful aging. Because of a scarcity of information regarding predictors of QoL in the elderly population in developing countries, this study was undertaken to assess the overall QoL and its predictors in the elderly population in an urban setting of Bangladesh. In this cross-sectional study, 275 participants were enrolled by systematic sampling at the outpatient department of a tertiary care hospital in Dhaka, Bangladesh. Data were collected by using a pretested semi-structured standard questionnaire for QoL (OPQOL-35). Pearson’s correlation was used to assess the association between QoL and sociodemographic factors. The Chi-square test was done for assessing the statistical significance between categorical variables. Multivariate linear regression was conducted to identify predictors of QoL, after controlling for potential confounders. The median age of the participants (n = 275) was 65 years (range, 60 to 85; 25th and 75th percentile, 60 and 68, respectively). The majority (78%) of them were married and 20% were widowed or divorced. The median score of QoL was 113 (25th and 75th percentile, 101 and 124, respectively). Most of the participants had a very poor (bad as can be) or poor (bad) QoL. Only 7.3% were observed to have “good” QoL (scores 140 or more). Females had significantly poorer QoL scores compared to males (p = 0.01). Educational status, marital status, body mass index and sleep duration significantly predicted QoL in a multiple regression analysis. In conclusion, the QoL of the elderly individuals in Bangladesh was very poor or poor. Future research should focus on service-oriented interventions, especially targeting women. Counseling of elderly people for enhancing their quality of life may include improving sleep patterns, healthy diets, regular exercise, and caring for their mental health.
Unlocking CBSD Resistance in Cassava: Insight From Genetic Variability and Combining Ability
Authors: Sichalwe Karoline Leonard , Kayondo Ismail S. , Edema Richard , Abubakar Mikidadi Omari , Kulembeka Heneriko , Rubaihayo Patrick , Kanju Edward
Published: July 2024

Cassava brown streak disease (CBSD) threatens cassava production in sub-Saharan Africa despite the availability of resistant varieties since extreme environmental factors weakens plant defenses hence reduce CBSD resistance. This study examined the inheritance of CBSD in cassava populations, assessed genetic variability and identified superior sources of resistance through F1, S1 and half-sib offspring of populations derived from resistant sources. The offsprings underwent field evaluation at two distinct sites from 2019 to 2021, and the symptoms free genotypes were analyzed using reverse transcription quantitative polymerase chain reaction (RT-qPCR). Resistance to CBSD was categorized as most resistant, resistant, most tolerant and tolerant based on symptoms and virus titer. The findings of the study indicate that the resistance to Cassava Brown Streak Disease (CBSD) is highly influenced by genotypes, F1/S1 types, and environmental conditions. The analysis of combining abilities revealed significant general combining abilities (GCA) for CBSD, cassava mosaic disease (CMD), and traits associated with yield. The heritability estimates for resistance to CBSD varied between 43.4% to 63.2% for foliar symptoms and 14.6% to 57.9% for root necrosis across locations. The inheritance pattern involved a combination of additive and recessive genes and selfed (S1) populations displayed stronger and effective resistance to the disease. There was a high prevalence of cassava brown streak virus (CBSV) and a low prevalence of Ugandan cassava brown streak virus (UCBSV). Four genotypes were identified to be highly resistant to Cassava Brown Streak Disease (CBSD) that could be used as key sources of resistance to CBSD.
The Decoded Indus Seal M-282
Authors: H Muhammad Mahaveer
Published: July 2024

This article presents a novel analysis of Indus Seal M-282 [1] excavated from Mohenjo-Daro, a key Indus Valley Civilization site. Utilizing the proposed Sindhu Prakrit alphabet, the study investigates the relationship between the seal's iconography and the inscribed text. By examining the potential for a close correlation between these elements, the analysis aims to decipher the meaning embedded within the seal's motifs, potentially offering new insights into Indus Valley communication and symbolism.
Industrial Environmental Impact Assessment Method Based on Detection of Complex Anomalies in Time Series
Authors: Safonova Elena , Kravets Alla , Scherbakov Maxim , Kizim Alexey , Al-Gunaid Mohammad , Echin Alexander
Published: July 2024

In order to reduce the environmental impact of energy enterprises, it is important to promptly identify cases of possible changes in the quality of wastewater generated at power plants, that is cases of exceeding the maximum permissible concentrations of pollutants in wastewater. The goal of the method for detecting complex anomalies in multidimensional time series obtained from smart energy station’s sensor channels is to increase the accuracy of detecting pollution levels in industrial wastewater. To achieve this goal, the following tasks were solved: methods for detecting time series anomalies were analyzed, the method for detecting complex anomalies was developed, software implementation of the algorithm was carried out and experiments were conducted. The developed method is proposed to be used in an smart energy monitoring system.
A Tool for a Fast and Accurate Evaluation of the Energy Production of Bifacial PV Modules
Authors: D’Alessandro Vincenzo , Daliento Santolo , Dhimish Mahmoud , Guerriero Pierluigi
Published: July 2024

In this work, we propose an in-house simulation tool designed for the analysis and optimization of bifacial photovoltaic (PV) modules, which are currently under the spotlight in the renewable energy scenario. The tool is conceived to support researchers and engineers by providing fast and accurate predictions of the PV module yield under various operating and environmental conditions. For a chosen geographical site, the impact of module orientation, tilt, albedo, sky conditions, ambient temperature, and so on, can be effortlessly determined. In case of nonuniformity across the cells dictated by localized architectural shading, dirt, bird drops, defects, a circuit-based cell-level approach can be activated to compute the module production. An extensive simulation campaign is performed by assuming that the panels are installed in Naples without loss of generality. Results are shown to give detailed insights into the performance of bifacial modules, thus providing unambiguous guidelines for their correct installation. Further analyses are conducted to demonstrate the tool capability to quantify the detrimental influence of a poorly-irradiated cell on the backside, as well as of cracked cells.
The Role of Entrepreneur’s Face Disclosure on Crowdfunding Success
Authors: Mamaro Lenny Phulong , Sibindi Athenia Bongani
Published: July 2024

The evaluation of crowdfunding campaigns varies from person to person; some investors are more interested in the creativity of the project, and others are more concerned with the profiles of entrepreneurs. The study investigated how entrepreneurs’ face disclosure influenced the success of crowdfunding. Secondary data was collected from multiple crowdfunding platforms for projects in Africa, that is, cross-country data from 54 African countries, to overcome data limitations from a single country. Econometrics analysis revealed that the facial disclosure of entrepreneurs increases the probability of crowdfunding success. Images, videos, and backers had a positive influence on the success of crowdfunding. On the contrary, the duration of the crowdfunding campaign was negatively associated with its success. To reduce the knowledge asymmetry between creators and backers, those prepared to start a crowdfunding project must provide as much information as possible to show their abilities. This study contributes to understanding the role of disclosing an entrepreneur’s profile on economic exchanges in the success of online crowdfunding. The signalling and agency theories support the finding. The findings were limited to crowdfunding projects on the African continent and are not necessarily applicable to some developed countries.
Predicting Survival of Metastatic Clear Cell Renal Cell Carcinoma Treated With Tyrosine Kinase Inhibitor Based Sequential Therapy
Authors: Angulo Javier C. , Larrinaga Gorka , Lecumberri David , Iturregui Ane Miren , Solano-Iturri Jon Danel , Lawrie Charles H. , Armesto María , Dorado Juan F. , Nunes-Xavier Caroline E. , Pulido Rafael , Manini Claudia , López José I.
Published: July 2024

(1) Objective: To develop a clinically useful nomogram that may provide a more individualized and accurate estimation of cancer-specific survival (CSS) for patients with clear-cell (CC) metastatic renal cell carcinoma (mRCC) treated with nephrectomy and tyrosine kinase Inhibitor (TKI) based sequential therapy; (2) Methods: A prospectively maintained database of 145 patients with mRCC treated between 2008-2018 was analyzed to predict CSS of patients receiving sunitinib and 2nd and 3rd line therapies according to current standards of practice. A nomogram taking into account four independent clinical predictors (ECOG status, IMDC score, MASS and RECIST response criteria) was calculated. The corresponding 1- to 10-year CSS probabilities were then determined from the nomogram; (3) Results: The median age was 60 years (95% CI 57.9-61.4). Disease was metastatic at diagnosis in 59 (40.7%) and 86 (59.3%) developed metachronous metastasis after nephrectomy. Patients were followed for a median 48 (IQR 72; 95% CI 56-75.7) months after first-line TKI initiation. Concordance probability estimator for the nomogram is 0.778 ± 0.02 (mean ± SE); (4) Conclusions: A nomogram to predict CSS in patients with CC mRCC that incorporates patient status, clinical risk classification and response criteria to first-line TKI at 3 months is presented. This new tool may be useful to clinicians assessing risk and prognosis of patients with mRCC.
Test of Sugarcane Resistance of Genetically Engineered Products SPS Event Against Sugarcane Streak Mosaic Virus Infection
Authors: Pratama Muhammad Eqik
Published: July 2024

Sugarcane Streak Mosaic Virus (SCSMV) poses a significant threat to sugarcane productivity. PRG sugarcane is a product of genetic engineering aimed at enhancing resistance to various environmental stresses, pests, and diseases. This study aimed to test and compare the resistance of two PRG sugarcane SPS events to SCSMV infection. The study was conducted using a single-factor Completely Randomized Design (CRD), comprising four treatments: Bululawang sugarcane variety as a control, PS 882 as a susceptible variety, PRG Sugarcane SPS 1, and PRG Sugarcane SPS 3, with 15 replications of 60 sugarcane mules each. PCR results indicated that mosaic infection in the sugarcane plants was most likely caused by SCSMV. Based on the morphological identification of the SCSMV virus and RT-PCR testing, the sugarcane plants positively infected with SCSMV were SPS1 U1 R1, SPS3 U2 R4, SPS3 U3 R3, and PS882 U3 R4. The highest incidence rate of the disease was observed in the SPS3 variety, while the lowest incidence rate was in the Bululawang variety. The PS882 variety exhibited the slowest SCSMV incubation period, showing symptoms of infection, whereas the SPS1 variety showed the fastest incubation period. The highest disease severity was recorded in the SPS3 variety, and the lowest in the PS882 variety. The sugarcane varieties with the highest klorofil content were SPS3, while the SPS1 variety had the lowest klorofil content.
A Review of Optimization-Based Deep Learning Models for MRI Reconstruction
Authors: Bian Wanyu , Tamilselvam Yokhesh Krishnasamy
Published: July 2024

Magnetic resonance imaging (MRI) is crucial for its superior soft tissue contrast and high spatial resolution. Integrating deep learning algorithms into MRI reconstruction enhances image quality and efficiency, but a comprehensive review of optimization-based deep learning models for MRI reconstruction has been missing. This study fills that gap by examining the latest optimization-based algorithms in deep learning for MRI reconstruction, including gradient descent algorithms, proximal gradient descent algorithms, ADMM, PDHG, and diffusion models combined with gradient descent. Learnable optimization algorithms (LOA) are highlighted for their ability to map optimization processes to structured neural networks, improving model interpretability and performance. The study demonstrates significant advancements in MRI reconstruction through deep learning, with successful clinical applications. These findings provide valuable insights and resources for researchers aiming to advance medical imaging using innovative deep learning techniques.
Questioning the Lorentz Factor in Special Relativity: Introducing the Yuyunrui Factor
Authors: yu yunrui
Published: July 2024

Newton's kinetic energy equation delineates the laws of motion for objects travelling at speeds much less than the speed of light, an equation extensively validated at these lower velocities. Any new, more complete formulation of kinetic energy must approximate Newton's kinetic energy equation under these conditions. Einstein's special relativity, utilizing the Lorentz factor, introduces a new perspective on spacetime, adhering to the requirement that the Newtonian kinetic energy equation serves as an approximation at low velocities. In this paper, we identify all factor expressions satisfying the condition that their approximate solutions at low velocities align with Newton's kinetic energy equation. We introduce the Yuyunrui factor, incorporating two real number hyperparameters, $\alpha$ and $\beta$, encompassing all potentially correct factors, with the Lorentz factor as a specific instance where $(\alpha=0$, $\beta=1)$. We classify all potentially correct $(\alpha, \beta)$ combinations into six categories based on their distinct scaling effects and present the corresponding scaling effects. The combinations of $(\alpha, \beta)$ values applicable in the real world are necessarily included within these candidates, with the precise values requiring rigorous experimental validation. This work aims to refine our understanding of special relativity beyond the Lorentz factor.
The Association of High Burden Premature Ventricular Contractions With Esophageal/Upper GI Diseases
Authors: Khimani Faria , Haase Erin , Kulkarni Chandana , Moore Peyton , Murdock Paul , Ramanathan Akash V , Wolf Adam , Sathyamoorthy Mohanakrishnan
Published: July 2024

Seven patients in our clinical program who were diagnosed with high burden (>10%) premature ventricular contractions (PVCs) and concomitant significant upper GI disease with no other significant cardiac history demonstrated a significant reduction in the burden of PVCs following surgical or procedural interventions of the upper GI tract [68.34% reduction, p=0.024). Furthermore, in all cases, the origin of the PVCs was from the base of the right ventricular outflow tract (RVOT). This is the first report in the literature that we are aware of to report this unique association for which we propose a dual mechanism of action of vagally mediated upper GI driven PVCs and a direct anatomical effect of these upper GI anatomies on the right ventricular outflow tract (RVOT) of the heart. These are very prelimary findings that warrant larger clinical and mechanistic studies that may ultimately define a new subset of PVCs for which we propose a term, “E-PVCs”.
Bottom Crack Detection with Real-Time Signal Amplitude Correction Using EMAT-PEC Composite Sensor
Authors: Guo Yizhou , Hu Yu , Wang Kai , Song Yini , Feng Bo , Kang Yihua , Duan Zhaoqi
Published: July 2024

In electromagnetic ultrasonic testing, it is difficult to recognize small-size bottom cracks by time of flight (ToF), and the lift-off fluctuation of the probe affects the accuracy and consistency of the inspection results. In order to overcome the difficulty, a novel EMAT (electromagnetic acoustic transducer)-PEC (pulse eddy current) composite sensor is designed. We use amplitude of bottom echo recorded by EMAT to identify the tiny bottom crack as well as the amplitude of PEC signals picked up by the integrated symmetric coils to measure the average lift-off of the probe in real time. Firstly, the effects of lift-off and bottom cracks on amplitude of bottom echo are distinguished combining the theoretical analysis and finite element method (FEM). And then an amplitude correction method based on the fusion of EMAT and PEC signals is proposed to reduce the impact of lift-off on the defect signal. The experimental results demonstrate that the designed composite sensor can effectively detect the bottom crack as small as 0.1mm* 0.3mm. The signal fusion method can accurately correct the amplitude of defect signal and the relative error is less than ±8%.
Credit Card Fraud: Analysis of Feature Extraction Techniques for Ensemble Hidden Markov Model Prediction Approach
Authors: Ogundile Olayinka , Babalola Oluwaseyi , Ogunbanwo Afolakemi , Ogundile Olabisi , Balyan Vipin
Published: July 2024

Credit card payment platforms are increasingly used for e-commerce activities. Credit cards are payment cards issued to individuals so they can purchase products and services based on their accumulated debt. Since credit cards are becoming very popular and widely used, the number of related fraud cases is likewise increasing. Whereas, there are large numbers of credit card transactions daily; thus, it becomes complex to differentiate between fraudulent and non-fraudulent transactions. Accordingly, different machine learning (ML) tools have been deployed in the literature to filter credit card transactions to prevent cardholders and financial institutions from losing money. In this article, the ensemble hidden Markov model (EHMM) approach is deployed to predict credit card fraud. EHMM is a popular and flexible ML tool that can easily model randomly changing datasets. Yet, the performance of the EHMM solely depends on the adopted feature extraction technique. The more reliable the feature extraction technique, the better the performance of the EHMM. In this vein, this article analyses two feature extraction techniques that can be combined with the EHMM for the prediction of credit card fraud. First, the principal component analysis (PCA) feature extraction techniques are combined with the EHMM to effectively predict credit card fraud. Yet, the PCA increases the computational time complexity of the EHMM. Therefore, this article adapts some statistical features to reduce the computational time complexity imposed on the EHMM. These robust but simple statistical features termed MRE; Mean, Relative Amplitude, and Entropy, are merged to form a feature vector that can be combined with the EHMM to effectively predict credit card frauds. The performance of the PCA-EHMM and MRE-EHMM are evaluated using the credit card transactions dataset of European cardholders gathered within two days in September 2013. The results were documented using different performance metrics such as recall/sensitivity, specificity, precision, and F1-score. The findings of this article will offer solutions to the loss experienced by cardholders and financial institutions as a result of online banking which requires credit card details.
Prognostic Properties of Instantaneous Amplitudes Maxima of Earth Surface Tremor
Authors: Lyubushin Alexey , Rodionov Eugeny
Published: July 2024

A method is proposed for analyzing the tremor of the earth's surface, measured by GPS, in order to highlight prognostic effects. The method is applied to analysis of daily time series of vertical displacements in Japan. The network of 1047 stations is divided into 15 clusters. The Huang Empirical Mode Decomposition (EMD) is applied to the time series of principal components from clusters with subsequent calculation of instantaneous amplitudes using the Hilbert transform. To ensure the stability of estimates of the waveforms of the EMD decomposition, 1000 independent additive realizations of white noise of limited amplitude were averaged before the Hilbert transform. Using a parametric model of the intensities of point processes, we analyze the connections between the instants of sequences of times of the largest local maxima of instantaneous amplitudes averaged over the number of clusters and the times of earthquakes in the vicinity of the Japan with minimum magnitude thresholds of 5.5 for the time interval 2012-2023. It is shown that part of the intensity of the sequence of times of seismic events, due to the influence of the times of the most expressive local extrema of instantaneous amplitudes, significantly exceeds the reverse influence.
Transthoracic Cross Clamp Versus Endoaortic Balloon Occlusion in Minimally Invasive Mitral Valve Surgery: A Pooled Study with Subgroup Analyses
Authors: Magouliotis Dimitrios E. , Sicouri Serge , Baudo Massimo , Yamashita Yoshiyuki , Xanthopoulos Andrew , Arjomandi Rad Arian , Athanasiou Thanos , Ramlawi Basel
Published: July 2024

Objective: We reviewed the available literature on patients undergoing minimally invasive mitral valve surgery (MIMVS) with either transthoracic clamping (TTC) or endoaortic balloon occlusion (EABO). Methods: Original research studies that evaluated the perioperative outcomes of TTC versus EABO group were identified, from 2000 to 2024. The incidence of all-cause mortality, cerebrovascular accidents (CVA), and aortic dissections were the primary endpoints. The cardiopulmonary bypass (CPB), cross-clamp, and ventilation time, along with the incidence of conversion to sternotomy, re-exploration, new-onset atrial fibrillation (AF), postoperative acute kidney injury (AKI), ICU stay, and LOS were the secondary endpoints. Subgroup analyses were performed regarding EABO cannulation approach (femoral and aortic) and MIMVS approach (video-assisted and robotic-assisted). Sensitivity analyses were performed including risk-adjusted populations and with the leave-one-out method. Results: Sixteen studies were included in the qualitative and quantitative synthesis. After pooling data from 6,335 patients, both groups demonstrated similar outcomes on all primary and secondary endpoints in the non-adjusted and adjusted total cohort analyses. These outcomes were further validated by the leave-one-out sensitivity analysis. In addition, the aortic cannulation EABO was associated with lower cross-clamp time, followed by TTC and femoral cannulation EABO approach. Furthermore, in the video-assisted subgroup analysis, the EABO approach was associated with a higher incidence of CVA, conversion to sternotomy, and longer ICU stay compared to the TTC group. Conclusions: The present meta-analysis indicates that both aortic occlusion techniques are safe and feasible in the context of MIMVS. A future well-designed Randomized-Control Trial should further validate the current outcomes.
Malaria Public Health Status: Global Context and Update on Gulf Cooperation Council Countries
Authors: Ahmad Tanveer , Alhammadi Bushra A. , Almaazmi Shaikha Y. , Arafa Sahar , Blatch Gregory , Dutta Tanima , Gestwicki Jason E. , Keyzers Robert A. , Meskiri Aisha , Sharafeldin Ahmed , Shonhai Addmore , Singh Harpreet
Published: July 2024

The human malaria parasite, Plasmodium falciparum, accounts for more than 500,000 deaths worldwide per year. From 2000 to 2019, the malaria global death toll fell from 864,000 to 576,000 deaths; however, progress on reducing this toll has since slowed, with the COVID-19 pandemic contributing to an increase in the mortality rate since 2020. The emergence of widespread resistance in P. falciparum to first-line treatment drugs has highlighted the need for new antimalarial drugs, and smarter approaches, including better combination therapies and mass drug administration. Nevertheless, recent successes of the first malaria vaccine (RTS,S/AS01) and the approval of a second (R21/MM), have renewed the promise of widely applicable vaccines in the future. Since 2015, the Eastern Mediterranean Region has experienced an overall increase in malaria cases and deaths. In the Arabian Peninsula, while most of the Gulf Cooperation Council (GCC) countries have been declared free of indigenous malaria (Bahrain, Kuwait, Qatar, and the United Arab Emirates), malaria is still endemic in two GCC countries (Saudi Arabia and Oman) and its neighbors (Yemen). Furthermore, a number of factors threaten malaria control in this region, at the level of the parasite (antimalarial drug resistance), the mosquito (the emergence of highly invasive species), the environment (climate change and increasing average temperatures), and society (imported malaria). In this review, we assess the current world-wide status of malaria in terms of public health, prevention and treatment, before providing an Arabian regional perspective, with a critical evaluation of the malaria situation in the GCC countries.
Effects of Ammonia Mitigation on Secondary Organic Aerosol and Ammonium Nitrate Particle Formation in Photochemical Reacted Gasoline Vehicle Exhausts
Authors: Hagino Hiroyuki
Published: July 2024

Gaseous air pollutants emitted from anthropogenic sources are diverse and form secondary products through photochemical reactions, complicating the regulatory analysis of anthropogenic emissions in the atmosphere. Here, we used an environmental chassis dynamometer and a photochemical smog chamber to conduct a parameter sensitivity experiment to investigate the formation of secondary products from a direct-injection gasoline passenger car. To simulate the mitigation of ammonia (NH3) emissions from gasoline vehicle exhausts assuming future emission controls and to allow photochemical oxidation and aging of the vehicle exhaust, NH3 was selectively removed by a series of five denuders installed between the vehicle and the photochemical smog chamber. Overall, there were no differences in the formation of secondary organic aerosols and ozone with or without NH3 mitigation. However, the secondary particle formation potential of ammonium nitrate (NH4NO3) was significantly reduced with NH3 mitigation. In addition, NH3 mitigation resulted in increased particle phase acidity due to HNO3 in the gas phase not being neutralized by NH3 and condensing onto the liquid particle phase, indicating a potentially important secondary effect associated with NH3 mitigation. The present study provides new insights into the effects of NH3 mitigation on secondary emissions from gasoline vehicle exhaust and the experimental approach.
Geological Wonders of Italy: The Coveted Privilege of Disseminating Geology and Geomorphology through Science Documentaries
Authors: Farabollini Piero , Bendia Fabrizio , Bignami Luigi
Published: July 2024

This paper proposes an unusual method for the dissemination of geological sciences and the promotion of geotourism: the scientific documentary, where a representative itinerary of geological and geomorphological evolution of this portion of the Apennines was presented. The considerations that led to the identification of the geological route proposed to the editorial staff of FOCUS TV are presented in detail. At each stop there was an explanation by academic professors and researchers, mainly from the Geology Division of the University of Camerino (MC), who explained in detail the outcrops. During the episode, insights were also given into the anthropogenic frequentation of the epigean caves in Frasassi (AN), ancient places of frequentation and worship thanks to their suggestiveness and the sense of sublime that they can elicit.
In addition to the illustration of the individual stops, the article offers further insights into the geomorphology of the most important geosites depicted, all of which are in nature parks or protected areas and characterized by a high landscape value.
The result was the production of an episode of the television program 'Geological Wonders of Italy: The Marche and Umbria Regions', which was broadcast in October 2022 by the Italian national Mediaset group.
Methyl Orange Adsorption Using Chitosan-Based Composite Aerogels Produced by Supercritical Gel Drying
Authors: Zanotti Alessandra , Baldino Lucia , Cardea Stefano , Reverchon Ernesto
Published: July 2024

Chitosan-based composites are interesting materials for dye adsorption. In this work, methyl orange (MO) adsorption using chitosan (CH) and chitosan-graphene oxide (CH-GO) aerogels produced by supercritical gel drying was assessed, by studying the effect of driving force (25-100 ppm) and adsorbent dosage (1-8 g/L). It was highlighted that the difference in the performance between the two adsorbents was non-negligible only at high concentrations, due to more intense interactions between the adsorbent active sites and MO molecules. Starting from a 10 ppm MO solution, using a dosage of 8 g/L it was possible to achieve adsorption efficiency of about 85%, meaning that small amounts of nanostructured devices can result in good process outcomes. Freundlich isotherm reliably describes the system behavior, leading to the consideration that adsorption between MO and CH-GO takes place between different active sites. Moreover, PSO kinetic describes the general trend of this system through time, unveiling heterogeneous chemisorption; lastly, the multi-linear IPD kinetic model confirms that in the case of nanostructured porous devices, there are different mass transfer phenomena that control molecule diffusion through the system.
Primary Cable Position Effect on Non-Toroidal Shape Pass Through Current Transformer Accuracy
Authors: Guerrero José M. , Platero Carlos A. , Blázquez Francisco , Sánchez Jose A.
Published: July 2024

Non-toroidal shape primary pass through protection current transformers (CTs) are used to measure high currents. Their design provides them with a big airgap that allow passing several cables per phase though them, which is the main advantage versus toroidal types, as the number of CTs required to measure the whole phase current is drastically reduced. The cables pass through the transformer window can be in several positions. As the isolines of the magnetic field generated by the primary currents are centered in the cables, if these cables are not centered in the transformer window, the magnetic field will be non-uniform along the transformer core. Consequently, local saturations can appear if the cables are not properly disposed causing the malfunction of the CT. In this paper, the performance of a non-toroidal shape protection CT is studied. The research is focused on the cable position influence in possible partial saturations of the CT when it is operating near to its accuracy limit. Depending on the cable position, the ratio of the primary and secondary currents can depart from assigned ratio. The validation of this phenomenon has been carried out via Finite Element Analysis (FEA) showing that partial transformer core saturations appears in areas of the magnetic core close to the cable. Applying FEA, also the admissible accuracy region for cable positioning inside the CT is delimited. Finally, the simulation results are ratified with experimental tests performed in non-toroidal protection CTs varying the primary cables’ positions, which are subjected to currents up to 5 kA, achieving satisfactory results. From this analysis, installation recommendations are given.
Insights into the Metabolite Profiles of Two Camellia (Theaceae) Species in Yunnan Province through Metabolomic and Transcriptomic Analysis
Authors: Niu Miao , Li Ranyang , Li Xiongyu , Yang Hongyan , Ding Jianliang , Zhou Xianxiu , He Yuqi , Xu Yawen , Qu Qian , Liu Zhiwei , Li Jiahua
Published: July 2024

Tea (Camellia L.) falls into the family Theaceae, is a valuable commercial crop, and tea products made from its buds and young leaves are favored by consumers all over the world. The more common Thea plant is Camellia sinensis (C. sinensis), but its most important relative, Camellia taliensis (C. taliensis), is also utilized by locals in the area of cultivation to manufacture tea. In this investigation, C. taliensis (DL) and C. sinensis (QJZ) were characterized in terms of their agronomic traits, physicochemical indices, metabolomics, and transcriptomics. The leaf area of DL is larger than that of QJZ; the color of DL’s buds and leaves is yellowish-green, while that of QJZ’s is green. DL’s buds and leaves are more densely velvety than those of QJZ. The HPLC results indicated that the physicochemical contents varied considerably between the two samples, with DL having greater concentrations of EGCG and GABA than QJZ, while QJZ had remarkably higher concentrations of C, CA, and EGC than DL. A total of 2269 metabolites and 362,190,414 genes were positively identified, with the number of DAMs and DEGs being 1001 and 34,026, respectively. The flavonoids, phenolic acids, and alkaloid metabolites were dramatically different between the two tea group plants. Bioinformatics profiling revealed that the DAMs and DEGs of the two tea group plants interacted with each other and were involved in metabolic pathways including “biosynthesis of secondary metabolites”, “biosynthesis of amino acids”, “biosynthesis of cofactors”, “phenylpropanoid biosynthesis”, and “flavonoid biosynthesis”. Overall, these results provide statistical support for germplasm conservation and production for both C. taliensis and C. sinensis.