bluuebunny/crossref_metadata_2025 huggingface dataset:
StackMFF: End-to-end Multi-Focus Image Stack Fusion Network
Authors: Xie Xinzhe , Jiang Qingyan , Chen Dong , Guo Buyu , Li Peiliang , Zhou Sangjun
Published: October 2024

Existing end-to-end multi-focus image fusion networks demonstrate efficacy in merging two images but often introduce various types of image degradation due to error accumulation resulting from iterative fusion when applied to image stacks. To address this limitation, we propose a novel approach that directly fuses the entire image stack using a specially designed 3D convolutional neural network. The proposed method leverages an innovative training pipeline based on monocular depth estimation to generate a large-scale dataset, ensuring robust performance across diverse scenarios. Furthermore, to facilitate comprehensive evaluation and comparison within the field, we establish a benchmark for this field and release a comprehensive toolbox encompassing 12 distinct algorithms. Extensive experimental results demonstrate that our proposed method effectively fuses multi-focus image stacks while mitigating image degradation, achieving state-of-the-art performance in both fusion quality and processing speed. The codes are available at https://github.com/Xinzhe99/StackMFF.
Adding Highly Variable Genes to Spatially Variable Genes Can Improve Cell Type Clustering Performance in Spatial Transcriptomics Data
Authors: Li Yijun , Stanojevic Stefan , He Bing , Jing Zheng , Huang Qianhui , Kang Jian , Garmire Lana X.
Published: October 2024

Spatial transcriptomics has allowed researchers to analyze transcriptome data in its tissue sample's spatial context. Various methods have been developed for detecting spatially variable genes (SV genes), whose gene expression over the tissue space shows strong spatial autocorrelation. Such genes are often used to define clusters in cells or spots downstream. However, highly variable (HV) genes, whose quantitative gene expressions show significant variation from cell to cell, are conventionally used in clustering analyses. In this report, we investigate whether adding highly variable genes to spatially variable genes can improve the cell type clustering performance in spatial transcriptomics data. We tested the clustering performance of HV genes, SV genes, and the union of both gene sets (concatenation) on over 50 real spatial transcriptomics datasets across multiple platforms, using a variety of spatial and non-spatial metrics. Our results show that combining HV genes and SV genes can improve overall cell-type clustering performance.
Pantoea osteomyelitidis sp. nov., a novel opportunistic human pathogen causing chronic osteomyelitis: case report, genomic characterization and literature review
Authors: Keidar-Friedman Danielle , Leshin-Carmel Daniel , Tsur Anka , Amsalem Muriel , Tolkach Daria , Brosh-Nissimov Tal , Sorek Nadav
Published: October 2024

Background: Pantoea species are increasingly recognized as opportunistic human pathogens. We describe a rare case of osteomyelitis that has developed slowly over two decades, with the identification of the causative agent as a novel species of Pantoea.
Case presentation: A 37-year-old generally healthy woman with suspected chronic osteomyelitis presented at our hospital. The condition was possibly related to an incident that occurred two decades before the onset of symptoms, involving a tibia fracture with a large open bleeding wound. The patient had undergone two aggressive debridement operations, systemic ciprofloxacin treatment, and local aminoglycoside therapy, eventually resulting in a full recovery.
Bone biopsy cultures revealed gram-negative coccobacilli that could not be identified by conventional clinical microbiology methods. Whole-genome sequencing and subsequent taxonomic and phylogenetic analyses revealed genetic relatedness to several Pantoea species. Comparative genomic analyses revealed conserved antibiotic resistance and virulence genes.
Conclusion: A literature review uncovered only five cases of osteomyelitis caused by Pantoea species that have been reported in the past, all of which were attributed to Pantoea agglomerans. We suggest that this new strain belongs to a yet unidentified Pantoea species, which we have named Pantoea osteomyelitidis. sp.nov. The high diversity of Pantoea and the obscured potential pathogenicity of this genus are discussed, emphasizing the need for further research into its clinical relevance.
Squamous cell carcinoma (SCC) of the cornea in French Bulldog: case report
Authors: Nedev Vladi , Kalkanov Ismet
Published: October 2024

Background: Corneal squamous cell carcinoma (SCC) is considered as a rare condition in dogs and our aim is to report a case of the disease in French Bulldog and discus the factors leading to development of it. Misdiagnosing of SCC can potentially delay treatment and increase morbidity
Case presentation: A 2.6-year-old French Bulldog, with growing, nonpainful mass on the left eye was examined in University veterinary hospital of Trakia university in Stara Zagora. During the examination, a brown mass located on 6 o’clock with oval shape and diameter 4 mm, affection 20% of the cornea, was suspected as squamous cell carcinoma. A clinical examination showed no evidence of metastases and superficial keratectomy with further conjunctival flap were made and the mass was histologically examined and conformed the clinical diagnose. After 6 months from the surgery, there is no evidence of local or general metastasis.
Conclusion: surgical treatment must be considered the best therapeutic approach for ocular SCC in dogs even it is rare diagnosis.
Influence of Tree Roots on Matric Suction and Soil Moisture Dynamics in Tropical Residual Soil Slopes
Authors: Daud Solahuddin , Ishak Mohd Fakhrurrazi , Zolkepli Muhammad Farhan , Hasbollah Dayang Zulaika Abang , Muhammad Nurmunira , Ismi Puteri Izrina
Published: October 2024

This article investigates active root tree zones on tropical residual soil slopes, specifically focusing on matric suction resulting from tree water uptake. Fieldwork involved collecting matric suction data with and without a mature tree (Alstonia Angustiloba) at the slope's top. The study examines how matric suction values and profiles respond to tree water intake and rainfall, revealing higher matric suction levels near the tree, significantly influenced by climate change, especially at the slope's surface. Prolonged extreme rainfall decreases matric suction, with most changes occurring within 4.4 m of tree trunks and at shallow depths (0.25 m). The findings suggest that preserving mature trees can enhance soil quality, particularly on slopes. Utilizing the unsaturated flow equation, this research confirms that tree transpiration induces suction in the unsaturated soil beneath the tree. Numerical simulations were conducted to compare soil moisture patterns with suction data from Pahang Matriculation College (PMC). Field equipment, including tensiometers, gypsum blocks, and rain gauges, recorded daily soil matric and rainfall from May 21 to June 12, 2019. The numerical model successfully simulated moisture transport patterns in the unsaturated zone near the mature tree, yielding satisfactory results. A comparison of actual soil suction patterns with simulated data indicated less than 5% variation, with discrepancies attributed to root density inconsistencies. This study highlights the critical role of trees in maintaining soil stability and moisture distribution.
Improving Growth and Nutrient Quality of Mustard Varieties Through Rhizobacterial Inoculation
Authors: Basharat Noman , Rashid Madiha , Noreen Zahra , Aslam Muhammad , Usman Sheeraz , Shah Anis Ali , Shakeel Muhammad , Shaffique Shifa , Gatasheh Mansour K.
Published: October 2024

The excessive feeding of chemical fertilizers into the soil has affected its fertility. The continued use of these fertilizers can impose serious environmental hazards on mankind. Biofertilizers are an alternative strategy and could improve the growth of different crops. The study was conducted in a completely randomized design to understand the effect of soil-borne rhizospheric bacteria (Bradyrhizobium japonicum & Burkholderia cepacia) on morphology, physiology, yield, antioxidants activity and protein content of four Mustard (Brassica juncea (L.) Czern.) varieties. Both the rhizospheric bacteria were cultured in LB (Luria-Bertani) broth to prepare the bacterial suspension. A single pot was inoculated with 25 ml of the bacterial suspension. The combined and individual treatments of both bacteria resulted in an increase in the plant heights, shoot and root lengths, shoot and root fresh weights, shoot and root dry weights and leaf yield, compared to control. The number of pods, weight of 1000 seeds, pod length and number of seeds per pod was also enhanced with these bacterial treatments. The B. japonicum treatment uplifted the total chlorophyll, carotenoids, and relative water content in mustard varieties. The treatment of B. cepacia raised the phenolic content, total soluble protein, and the CAT, and POD activity in Mustard plants. The results revealed that the use of B. japonicum and B. cepacia could be a better choice for plant breeders as a biofertilizer. However, the effects could vary depending upon the type of crops, as well as the varieties of the same crop.
Recycled cathode from Li-ion batteries applied to adsorption and demethylation of methylene blue for thionine formation
Authors: Garcia Eric M. , Teixeira Rodrigo G. , Taroco Hosane A. , Melo Julio O.F , Taroco Cristiane G.
Published: October 2024

This study explores the demethylation of methylene blue in an acidic pH, utilizing spent cathode from Li-ion batteries. The spent cathode has a composition of LiMn2O4 and a pcz close to pH = 2.1. In contact with methylene blue in an acidic medium (pH = 2), the spent cathode adsorbed and demethylated methylene blue to form thionine. This was confirmed by UV-vis and ESI measurements of the resulting solutions. The intermediate m/z = 300 was crucial for proposing the demethylation mechanism that is similar to a demethylation mechanism catalyzed by hemoproteins. FTIR measurements confirmed the adsorption of methylene blue onto the spent cathode. The rise in pH observed during demethylation can explain to the incomplete degradation of methylene blue stopping at the thionine stage. Consequently, the reaction involving spent cathode of Li-ion battery based on LiMn2O4 may be applicable to the demethylation of other molecules in future research.
Impact of Digital Marketing Strategies on the Entrepreneurial Orientations of Jordan's Commercial Banks
Authors: Al-Shourah Abdullah
Published: October 2024

Technology finance has an increasingly significant impact on the state of the financial industry around the world, including Jordan. Digital marketing has the potential to improve the efficiency, creativity and value of financial services, which can contribute to the resilience and prosperity of customers. This research aims to determine digital marketing strategies (DMSs) and their impact on the entrepreneurial orientation (EO) of Jordan's commercial banks. To realize the dimensions of the digital marketing strategy. The study answers the main question addressed by this research, including whether there was a correlation and impact of the digital marketing strategy on the entrepreneurial orientation of commercial banks. The method uses a basic type with a quantitative, nonexperimental approach. Essential information obtained through the questionnaire was organized for this purpose and distributed to a sample of 137 staff at various levels. Descriptive and analytical statistical methods have been adopted, including computational media and standard deviations, and the correlations between variables and tests (t) have been used. All the variables have α (0.823 ~ 0.989); to ascertain the stability of the search tool, the value (F) achieved (241.359). The results reveal various perspectives on key business aspects and show that the correlation factor (R=.926) indicates that digital marketing affects entrepreneurial orientation. The results of this study explain the structural impact of the digital marketing strategy (targeting strategy, attack strategy, and proactive strategy) on the entrepreneurial orientation (proactive risk tolerance and creative and innovation) of Jordanian commercial banks. Thus, these tools are potentially effective and should be adopted by Jordanian commercial banks to improve existing strategies through investments in technology, data analysis and staff training.
Botryosphaeriaceae Infections on Prunus Germplasm: Evaluation of Pathogenicity, Resistance Loci, and Detached Assays of Southeastern United States Isolates
Authors: Mancero-Castillo Daniel , Espinoza Lisbeth , Harmon Philip F. , Chaparro José X.
Published: October 2024

Research of peach fungal gummosis (PFG), which is a vascular disease caused by fungi in the Botryosphaeriaceae family, is particularly important in the southeastern United States, southern China, South Africa, and Western Australia. This disease has been a significant concern for the peach industry in the southeastern United States since the 1970s. The changing climatic conditions in the prunus production areas of the world have worsened the severity of PFG disease. A study of the morphological and genetic profiles of Botryosphaeriaceae species from diseased peach trees found four species in Georgia, Florida, Alabama, and South Carolina. Botryosphaeria dothidea, Lasiodiplodia theobromae, Diplodia seriata, and Neofusicocoum parvum were isolated and identified using conidiospore characters and rDNA sequences of internal transcribed spacer regions and elongation factor α-1 genes. B. dothidea was the most common species from diseased peach trees. A significant implication of this research is the potential resistance in Prunus germplasm, which was genotyped for the resistance locus Botd8 and evaluated for relative susceptibility to one isolate each from B. dothidea, L. theobromae, and D. seriata. Pathogenicity evaluations of peach, almond, and interspecific hybrids used detached stem and leaf assays for susceptibility to PFG based on lesion lengths and gumming scores. L. theobromae inoculation resulted in the most extensive lesions on stems and leaves. Detached stem and leaf assays indicated that Prunus with the Botd8 locus significantly differed in lesion size when infected with B. dothidea and D. seriata. However, the resistant locus had no significant effect on the relative susceptibility of Prunus to L. theobromae. Field and detached stem and leaf assays identified almond cultivars Pioneer and Golden State and Peach × Almond hybrids with Botd8 (+) as tolerant to PFG. Correlations between detached assays and field gumming scores suggested that inoculations on detached stems or leaves under controlled conditions can be used to preliminarily screen for resistance to PFG. These detached assays for specific pathogen isolates provide an opportunity for a relatively fast, nondestructive evaluation of Prunus germplasm and are tools that can be used to identify the components of disease resistance.
Integrated modeling of surface water and groundwater interactions in the Eastern Mitidja Plain, North Algeria: investigating the impact of human activities and climate change
Authors: Kastali Fatima , Meddi Mohamed , Boufekane Abdelmadjid , Longobardi Antonia
Published: October 2024

The interaction between surface water and groundwater is a crucial factor in understanding water resources' dynamics and in promoting sustainable groundwater development, particularly in regions affected by human activities and climate change. This work aims to investigate dynamic interactions between El Hamiz river and Eastern Mitidja alluvial aquifer (North Algeria) using a regional three-dimensional groundwater numerical model (MODFLOW 6). A typical scenario analysis approach was conducted using historical and projected climate data from CMIP5 and CMIP6 models, as well as current and projected groundwater abstraction rates. The findings demonstrate major shifts in the flow dynamics over time. In 1982, the aquifer replenished the river at a rate of 2.59 m3/s. However, in 2019 a new state was observed in which the aquifer was recharged by the river at a rate of 0.73 m3/s. This decrease in flow rate can be linked to over-pumping and decreased recharge rates, which are expected to continue in the future. Future forecasts show that groundwater misuse affects groundwater dynamics more than climate change. However, the Algerian government's projected saltwater desalination and upgraded irrigation methods could provide a substantial contribution to the sustainable growth of groundwater resources, with a potential increase of up to 14 meters.
Estimation of missing streamflow data using various artificial intelligence methods in peninsular Malaysia
Authors: Ng Jing Lin , Huang Yuk Feng , Chong Aik Hang , Ahmed Ali Najah , Syamsunurc Deprizon
Published: October 2024

Missing streamflow data is a common issue in Peninsular Malaysia, as the technologies used in hydrological studies often fail to collect data accurately. Additionally, conventional methods are still widely used in the region, which are less accurate compared to artificial intelligence (AI) methods in estimating missing streamflow data. Therefore, this study aims to estimate the missing streamflow data from 11 stations in Peninsular Malaysia by using different AI methods and determine the most appropriate method. Four homogeneity tests were applied to check the quality of data, and the results of the tests indicated that the streamflow data in most stations were homogenous. Two AI methods were applied in this study, which were artificial neural network and artificial neuro-fuzzy inference systems (ANFIS). The proposed AI methods were compared with five different conventional methods. All streamflow missing data, constituting 30% of data from each year were estimated on a daily time scale, and evaluated using root mean square error, mean absolute error and correlation coefficient values. The results indicated that ANFIS was the best due to its learning abilities and the fuzzy inference systems, which enable it to handle complicated input–output patterns and provide highly accurate estimation results.
Practical implications of adding powdered activated carbon in advanced wastewater treatment for process and plant design
Authors: Slavik Irene , Bechle Thomas S. , Uhl Wolfgang
Published: October 2024

The addition of powdered activated carbon (PAC) in advanced wastewater treatment is increasingly recognized for its effectiveness in removing micropollutants from secondary effluents. This study investigates the implications of PAC dosing on treatment performance, particularly in terms of natural and effluent organic matter (OM) removal, turbidity reduction, and sludge characteristics. Results indicate that while PAC incorporation significantly enhances the adsorption of OM, it necessitates higher coagulant dosages to achieve comparable or improved turbidity levels. The study also reveals that lower pH levels facilitate the removal of OM, thereby increasing the availability of adsorption sites on PAC for micropollutants. Moreover, PAC addition results in the formation of larger, denser flocs that settle faster, leading to a reduction in sludge volume by approximately 20%. However, the increased coagulant demand and the subsequent rise in sludge volume highlight the need for the optimized process design to balance treatment efficiency with operational costs. This research provides valuable insights for the design and operation of wastewater treatment plants, emphasizing the importance of tailored coagulant dosing and process adjustments when integrating PAC into existing treatment frameworks.
Advances in the Study of the Pathogenesis of Vogt-Koyanagi-Harada Syndrome
Authors: Wang Meng-nan , Zhang Lin , Zhou Hong-Yan , Zhong Wei , Zhang Hong , Bi Miao-Miao , Wang Li , Lu Jia
Published: October 2024

Vogt-Koyanagi-Harada syndrome (VKHS) is a common type of uveitis
characterized by the invasion of melanocyte-rich tissues. In recent years, the incidence
of VKHS has been increasing yearly, and its specific pathogenesis has not yet been
elucidated. However, its pathogenesis has been a hot topic of research. The clinical
course of VKHS is characterized by the early involvement of the posterior segment of
the eye, including exudative retinal detachment, optic papillitis, bilateral diffuse
chorioretinitis, etc. If treated improperly or with delayed treatment, the inflammation
may gradually spread to the anterior segment of the eye, leading to vision loss or even
vision. This study examines the pathogenesis of VKHS. It reviews the progress of
research on the pathogenesis of VKHS, which will help to improve the understanding
of VKHS and provide a reference for subsequent studies.
Scientifc Validation and Chromatographic Method Development for the Estimation of Piperine in Herbal Formulation Babbularishta: A Quality Control Strategy for Critical Quality Attributes
Authors: Gidwani Bina , Kalyani Gunjan , Pandey Ravindra Kumar , Shukla Shiv Shankar
Published: October 2024

Background:

Babbularishta is an Ayurvedic medicine in liquid form used for the
treatment of phthisis, skin diseases, urinary disorders,, and breathing problems. It is also beneficial
in cases of blood disorders, acne, dermatitis, hemoptysis, lung injury, asthma, persistent
cough, whooping cough, etc.

Objective:

The functional role of this study is to develop a simple, novel, precise, accurate, reliable,
and selective RP-HPLC method for the estimation of piperine content in herbal drug formulations
(Babbularista).

Methods:

A traditional approach to method development could fail to meet the desired separation.
Consideration of the current regulatory requirement for analytical method development
and RP-HPLC method for routine analysis of piperine in the herbal formulation has been optimized
using an analytical Quality by Design (QbD) approach. Three laboratory formulations
and three marketed preparations of Babularishta were investigated for organoleptic parameters,
physicochemical parameters, and validation. The mobile phase composition (methanol and water
% as A), pH (B), and flow rate (mL/min as C) were selected as independent variable,. In
contrast, retention time (min. as Y2), area (AU as Y1) is selected as dependent variables.

Results:

The fingerprinting method was developed and optimized by using the AQbD approach.
Piperine content was found to be in Piper nigrum (Marica) 3.01±0.01527 % w/w and in
Piper longum (Pipali) 2.74±0.01154% w/w in Babbularista.

Conclusion:

An attempt has been made to develop quality control parameters of Babbularista
by developing a suitable and sensitive HPLC methods for the quantitation of piperine in herbal
drug formulations (Babbularista). The developed method was found to be simple, accurate, precise,,
and economical for the estimation of piperine in herbal formulations.
Arylcarboxamide Derivatives as Promising HDAC8 Inhibitors: An Overview in Light of Structure-activity Relationship and Binding Mode of
Interaction Analysis
Authors: Banerjee Suvankar , Baidya Sandip Kumar , Jha Tarun , Ghosh Balaram , Adhikari Nilanjan
Published: October 2024

HDAC8 is associated with several disease conditions as well as various cancers of several
organs and hematological malignancies. To counter such pathophysiological and disease conditions,
inhibition of HDAC8 may be a promising approach for anticancer drug development. In this
article, a detail of arylcarboxamide-based potential HDAC8 inhibitors has been outlined. Considering
their binding pattern of interactions along with the chemical features, effective and selective
novel HDAC8 inhibitors can be designed further. Therefore, modification of these compounds provides
greater possibilities for the development of novel HDAC8 inhibitors. Nevertheless, structural
modification of such arylcarboxamide derivatives may be able to produce potent dual-inhibitory
compounds along with HDAC8 inhibition. Thus, this article is quite useful for exploring and identifying
several possibilities for arylcarboxamide-based HDAC8 inhibitors. Moreover, it can be concluded
that further study of the arylcarboxamide-based HDAC8 inhibitors can be effectively used
for the treatment of different cancerous and non-cancerous diseases.
Effects of ethanol extract from senna leaf (EESL) on inflammation and oxidative stress in mice: A non-targeted metabolomic study
Authors: Huang Xiaoli , Sun Wen , Sun Chang , Tan Jiajun , Wu Liang , Yang Fumeng
Published: October 2024

Background:

Senna leaf is a commonly used medication for treating constipation, and
long-term use can cause damage to the intestinal mucosa and lead to drug dependence. But the exact
mechanism remains unclear.

Objective:

Using non-targeted metabolomics technology to study the mechanism of senna leaf
ethanol extract (EESL) inducing inflammation and oxidative stress in mice and causing side effects.

Methods:

EESL was administered to mice by gavage to detect inflammation and oxidative stressrelated
factors in mice, and the EESL components and differential metabolites in mouse plasma
were analyzed using non-targeted metabolome techniques.

Results:

23 anthraquinone compounds were identified in the EESL, including sennoside and their
derivatives. Administration of EESL to mice resulted in a significant increase in pro-inflammatory
factors, IL-1β, and IL-6 in the plasma, while the levels of IgA significantly decreased. The levels
of oxidative stress significantly increased, and the intestinal mucosal integrity was impaired. 21 endogenous
in plasma metabolites were identified as differential metabolites related with taurine and
taurine metabolism, glycerophospholipid metabolism, arachidonic acid metabolism, tryptophan
metabolism, and sphingolipid metabolism. These metabolic pathways are related to oxidative
stress and inflammation.

Conclusion:

Senna leaf can inhibit the expression of tight junction proteins in the intestinal mucosa
and disrupt intestinal mucosal barrier integrity, exacerbating oxidative stress and inflammation
induced by bacterial LPS entering the bloodstream. In addition, the impact of Senna leaf on
tryptophan metabolism may be linked to the occurrence of drug dependence.
Preclinical Aspects of [89Zr]Zr-DFO-Rituximab: A High Potential Agent for Immuno-PET Imaging
Authors: Rouhollahi Zahra , Aghamiri Seyed Mahmoud Reza , Yousefnia Hassan , Alirezapour Behrouz , Moghaddasi Ali , Zolghadri Samaneh
Published: October 2024

Background:

An early diagnosis of cancer can lead to choosing more effective
treatment and increase the number of cancer survivors. In this study, the preparation and preclinical
aspects of [89Zr]Zr-DFO-Rituximab, a high-potential agent for PET imaging of Non-
Hodgkin Lymphoma (NHL), were evaluated.

Methods:

DFO was conjugated to rituximab monoclonal antibody (mAb), and DFO-rituximab
was successfully labeled with zirconium-89 (89Zr) at optimized conditions. The stability of the
complex was assessed in human blood serum and PBS buffer. Radioimmunoreactivity (RIA) of
the radioimmunoconjugate (RIC) was evaluated on CD20-overexpressing Raji cell line and
CHO cells. The biodistribution of the radiolabeled mAb was studied in normal and tumorbearing
rodents. Finally, the absorbed dose in human organs was estimated.

Results:

The radiolabeled compound was prepared with radiochemical purity (RCP)
>99% (RTLC) and a specific activity of 180±1.8 GBq/g. The RCP of the final complex PBS
buffer and human blood serum was higher than 95%, even after 48 h post incubation. The RIA
assay demonstrated that more than 63% of the radiolabeled compound (40 ng/ml, 0.5 mL) was
bound to 5×106 Raji cells. The biodistribution of the final product in tumor-bearing mice
showed a high accumulation of the RIC in the tumor site in all intervals post-injection. Tumor/
non-target ratios were increased over time, and longer imaging time was suggested. The
dosimetry data indicated that the liver received the most absorbed dose after the complex injection.

Conclusion:

[89Zr]Zr-DFO-Rituximab represents a significant advancement in the field of oncological
imaging and offers a robust platform for both diagnostic and therapeutic applications in
the management of B-cell malignancies.
La economía de los recursos naturales
Authors: Rodríguez Carbajal Genaro Armando
Published: October 2024

El libro “La economía de los recursos naturales”, editado por el Centro de Investigación de la Universidad del Pacífico y escrito por Elsa Galarza Contreras, adquiere notable relevancia en el contexto de la actual emergencia mundial frente al cambio climático (incluyendo eventos como temperaturas extremas) y las respuestas de los países y organismos internacionales al respecto. El contenido del libro destaca por su interés en vincular los recursos naturales con la economía, incorporando los fundamentos de la ciencia ambiental. La autora sustenta su análisis en cada capítulo, abordando temas sensibles como naturaleza, ecología, población, externalidades, la renta, los impuestos, el equilibrio bioeconómico, la eficiencia social, las concesiones, el derecho de propiedad, la disposición privada y estatal, así como el papel de los gobiernos, dinamizando la agenda mediante la remediación, la salvaguarda y la búsqueda de soluciones sostenibles para los problemas medioambientales vinculados a los recursos naturales.
Zoönotisch belang van gastrale Helicobacter-species die voorkomen bij katten, honden en varkens
Authors: Taillieu E. , Van Steenkiste C. , Chiers K. , Haesebrouck F.
Published: October 2024

Sinds enkele decennia is bekend dat de maag geen steriele omgeving is. In de diergeneeskunde zijn er tal van niet-Helicobacter pylori Helicobacter (NHPH) species die de maag van onder andere katten, honden en varkens koloniseren. Binnen de humane geneeskunde werd tot voor kort aangenomen dat H. pylori de enige klinisch relevante pathogeen is die de maag koloniseert. Recent onderzoek wijst echter uit dat meerdere gastrale NHPH’s over een zoönotisch potentieel beschikken. Binnen patiëntengroepen met chronische gastritis, maagulcera en mucosa associated lymphoid tissue (MALT) lymfomen, waarbij tot nu toe geen oorzaak kon worden vastgesteld, (zoals H. pylori of het regelmatig gebruik van niet-steroïdale, anti-inflammatoire geneesmiddelen (NSAID’s)), blijken ze frequenter voor te komen dan eerst aangenomen werd en spelen ze mogelijk een pathofysiologische rol.
Interplay of High Performing Work Practices with Career Satisfaction, Extra-Role Behavior and Job Embeddedness: Study on Frontline Employees in Hospitality Industry
Authors: Bumrah Megha , Malhotra Meenakshi , Aggarwal Neeraj , Gupta S. K.
Published: October 2024

Frontline employees play a critical role in providing exceptional customer service, essential for both; overall customer satisfaction and the long term success of the hospitality industry. Their satisfaction enables effective resource allocation and strategic planning for the growth and development of the industry. The present study focuses on the relationship of high performing work practices (HPWPs) with career satisfaction (CS) and extra-role behavior (ERB) via job embeddedness (JE) among frontline hotel employees. The measurement model was assessed using Smart Partial Least Squares (PLS) SEM, version 4.0.9.0. The results of the study indicated that HPWPs directly and indirectly (through the mediating effects of JE) affect CS of frontline employees and also boost ERB among them. The findings suggested that the adoption of HPWPs, such as comprehensive training, rewards, and empowerment initiatives, cultivates positive attitudes among employees, which in turn encourages proactive customer handling, leading to customer satisfaction.
HYBRID NEURO-FUZZY-GENETIC ALGORITHMS FOR OPTIMAL CONTROL OF AUTONOMOUS SYSTEMS
Authors:   Theni Kammavar Sangam College of Technology, India, Arunprasad Veeranan , Gupta Brijendra ,   Siddhant College of Engineering, India, T Karthikeyan ,   University College of Technology and Applied Sciences - Salalah, Sultanate of Oman, Ponnusamy Muruganantham ,   Indian Institute of Information Technology Kalyani, India
Published: October 2024

In recent years, there has been an increasing demand for efficient and robust control algorithms to optimize the performance of autonomous systems. Traditional control techniques often struggle to handle the complexity and uncertainty associated with such systems. To address these challenges, hybrid neuro-fuzzy-genetic algorithms have emerged as a promising approach. This paper presents a comprehensive review of the application of hybrid neuro-fuzzy-genetic algorithms for optimal control of autonomous systems. The proposed algorithms combine the strengths of neural networks, fuzzy logic, and genetic algorithms to achieve adaptive and optimal control in real-time scenarios. The neuro-fuzzy component provides the ability to model and handle complex and uncertain systems, while the genetic algorithm component facilitates the optimization of control parameters. The combination of these techniques enables autonomous systems to adapt and optimize their control strategies based on changing environments and objectives. The paper discusses the underlying principles of hybrid neuro-fuzzy-genetic algorithms, their advantages, and challenges. It also provides a review of the state-of-the-art research in this field, highlighting successful applications and potential future directions. Overall, the integration of neuro-fuzzy-genetic algorithms in autonomous systems holds great promise for achieving optimal control in various domains, including robotics, aerospace, and autonomous vehicles.
AUTOMOBILE BONUS-MALUS SYSTEM MODELLING USING MACHINE LEARNING ALGORITHMS
Authors:   University Hassan II, Casablanca, Morocco, Yassine Kouach , Abderrahim EL Attar ,   University Hassan II, Casablanca, Morocco, Mostafa EL Hachloufi ,   University Hassan II, Casablanca, Morocco
Published: October 2024

Third-party liability is the most important sub-category in automobile insurance, that is why actuaries seek always to design the ideal price list by classifying the insureds into homogeneous classes. However, the heterogeneity persists in the priori tariffication. For that, actuaries use the Bonus Malus system to redistribute the cost of claims more equitably between insureds by rewarding good insureds with a bonus and penalizing bad insureds with a Malus. Nevertheless, the classical approach used in the conception of Bonus Malus systems is limited to the parametric methods that need to make the hypothesis of the number of claims distribution and don’t consider the cost of claims. In this direction, this paper seeks to avoid this issue by using machine learning algorithms, in response to offering a fair Bonus Malus System. Two models of posteriori tariffication will be built. In addition, three algorithms will be used, in occurrence, the CART Classification And Regression Tree method, SVM the Support Vector Machine for regression, and KNN the K-Nearest Neighbor. The suggested models take into account, not only the number of claims but also the importance of the cost of claims. A numerical illustration shows the flexibility of posteriori premiums calculated by our models in relation to the risk levels. This work is a start for new actuarial research which seeks to use artificial intelligence in the design of bonus malus systems.
SWARM INTELLIGENCE OPTIMIZATION FOR RESOURCE ALLOCATION IN CLOUD COMPUTING ENVIRONMENTS
Authors:   St. Joseph’s Institute of Technology, India, Sheeba Adlin , Gupta Brijendra ,   Siddhant College of Engineering, India, L Malathi ,   Government Polytechnic College, Namakkal, India, D Saravanan ,   VIT Bhopal University, India
Published: October 2024

Cloud computing has emerged as a powerful paradigm for resource allocation due to its scalability and flexibility. Efficient resource allocation is critical for optimizing the performance and utilization of cloud resources. In this context, swarm intelligence optimization algorithms, such as Salp Swarm Optimization (SSO), have shown promising results in solving complex optimization problems. This paper presents a novel approach that utilizes SSO for resource allocation in cloud computing environments. The proposed approach aims to maximize resource utilization, minimize response time, and improve overall system performance. The SSO algorithm is used to dynamically allocate virtual machines (VMs) to physical hosts based on their resource demands and availability. Experimental results demonstrate that the proposed approach outperforms existing methods in terms of resource utilization and response time, thereby enhancing the efficiency of cloud computing environments.
ENHANCING CREDIT CARD FRAUD DETECTION IN FINANCIAL TRANSACTIONS THROUGH IMPROVED R
CHALLENGES, OPPORTUNITIES AND RISK ANALYSIS OF ADOPTION OF DECENTRALIZED FINANCE APPLICATIONS
Authors:   Maitreyi College, India, Ahuja Rupali , Khandelwal Janhavi ,   Maitreyi College, India, K Anjali ,   Maitreyi College, India
Published: October 2024

Decentralised Finance or DeFi has emerged as a transformative and disruptive force within the financial industry, offering innovative financial services powered by blockchain technology and smart contracts. This paper provides in-depth knowledge of DeFi, its evolution, applications, and their adoption. It identifies the opportunities brought about by DeFi, comparing it with the traditional CeFi (Centralized Financial) system, including financial inclusion, transparency, and programmable money. It highlights the potential of applications of DeFi for decentralized lending, decentralized exchanges, and yield farming as innovative and promising avenues within the DeFi space. A SWOT analysis comparing DeFi and CeFi was performed to delve into the strengths, weaknesses, opportunities, and threats associated with DeFi. This study explored the intricate challenges and inherent risks involved in the adoption of DeFi applications, offering insights into the hype, fear, and apprehensions among governments and the masses regarding its adoption. The findings offer a nuanced understanding of the current state of DeFi, providing valuable insights for researchers, policymakers, and industry practitioners.
INTEGRATING NEURO-FUZZY SYSTEMS FOR ENHANCED CANCER DATA ANALYSIS AND PREDICTION
Authors:   IIMT College of Engineering, India, R Nandhakumar , M Sathya Priya ,   IIMT College of Engineering, India, Kumar Rotash ,   IIMT College of Engineering, India, Yadav Dinesh Kumar ,   IIMT College of Engineering, India, Ansari Mohammed Saleh Al ,   University of Bahrain, Bahrain
Published: October 2024

The abstract for Integrating Neuro-Fuzzy structures for more significant most cancers statistics analysis and Prediction describes research carried out to examine using a sort of artificial intelligence, known as a Neuro-Fuzzy device, to analyze and expect facts from most cancer sufferers. by leveraging the strengths of both Neural Networks and Fuzzy common sense structures, Neuro-Fuzzy systems provide a powerful answer for complicated statistics analysis. This research examines and tests the overall performance of Neuro-Fuzzy systems on hard and fast benchmark datasets from most cancers Toolbox Markup Language (TMX). Consequences showed that Neuro-Fuzzy yielded a higher accuracy charge when compared to different device learning algorithms in studying information from a diverse set of patients. Furthermore, the researchers also stated that Neural-Fuzzy systems were able to discern subtypes of cancer in an affected person population, which had not been formerly feasible with different techniques. The work defined in the abstract could have a long way to attaining implications for the remedy and prognosis of most cancer patients. With the promising results of this, have a look at showing that Neuro-Fuzzy structures are able to distinguish between particular forms of cancer correctly; a more precise treatment plan might be created for people living with cancer. Additionally, with the improved accuracy of Neuro-Fuzzy structures, more excellent dependable predictions will be made about the progression of most cancers in a selected patient, helping doctors to plan treatments. Ordinary, the findings of the research summarized in this summary are especially significant as the advanced accuracy and capacity to figure out subtle differences in most cancer types keep the promise of improved remedies and prognoses for people living with cancer.
Cadence-Based Pedometer App With Financial Incentives to Enhance Moderate-to-Vigorous Physical Activity: Development and Single-Arm Feasibility Study
Authors: Hayashi Kosuke , Imai Hiromitsu , Oikawa Ichiro , Ishihara Yugo , Wakuda Hirokazu , Miura Iori , Uenohara Shingo , Kuwae Asuka , Kai Megumi , Furuya Ken'ichi , Uemura Naoto
Published: October 2024

Background

High levels of physical activity are key to improving health outcomes, yet many people fail to take action. Using pedometers to target steps per day and providing financial incentives is a simple and scalable approach to promoting public health. However, conventional pedometers do not account for “intensity” and “duration,” making it challenging to efficiently increase people’s moderate-to-vigorous physical activity (MVPA), which is expected to improve health outcomes. Based on these rationales, we developed a smartphone app that sets step cadence as a goal (defined as a daily challenge of walking more than 1500 steps in 15 minutes twice a day, which is a heuristic threshold for moderate physical activity) and provides financial incentive when the challenge is met.

Objective

This study aimed to evaluate the feasibility of our novel app and explore whether its use can increase users’ daily MVPA.

Methods

A single-arm pre-post study evaluated the feasibility and efficacy of the app. A total of 15 participants used app 1 (an app without financial incentives) for the first period (4 weeks) and then switched to app 2 (an app with financial incentives) for the second period (4 weeks). The primary outcome was the difference between the first and second periods in the number of successful challenge attempts per week. Secondary outcomes were differences between the first and second periods in daily steps and distance walked. Exploratory outcomes included the difference between the first and second periods in daily “heart points” as measured by Google Fit, a publicly available app that measures users’ daily MVPA.

Results

The number of successful challenge attempts per week increased significantly compared to the first period (5.6 times per week vs 0.7 times per week; P<.001). Although not statistically significant, there was a trend toward an increase in the mean steps per day and distance walked per day (6586 steps per day vs 5950 steps per day; P=.19; and 4.69 km per day vs 3.85 km per day; P=.09, respectively). An exploratory end point examining daily MVPA by “heart points” collected from Google Fit also showed a significant increase compared to the first period (22.7 points per day vs 12.8 points per day; P=.02).

Conclusions

Our app using step cadence as a goal and providing financial incentives seemed feasible and could be an effective app to increase users’ daily MVPA. Based on the results of this study, we are motivated to conduct a confirmatory study with a broader and larger number of participants.

Trial Registration

UMIN 000050518; https://center6.umin.ac.jp/cgi-open-bin/ctr/ctr_view.cgi?recptno=R000057420
Evaluating the Economic Impact of the PedAMINES App in Reducing Medication Errors in Pediatric Emergency Care: Cost-Effectiveness Analysis (Preprint)
Authors: Brunner Loïc , Siebert Johan N , Ehrler Frédéric , Manzano Sergio , Marti Joachim
Published: October 2024

BACKGROUND

The administration of drugs in pediatric emergency care is a time-consuming process and is associated with a higher occurrence of medication errors compared with adult care. This is attributed to the intricacies of administration, which involve calculating doses based on the child’s weight or age. To mitigate the occurrence of adverse drug events (ADEs), the PedAMINES (Pediatric Accurate Medication in Emergency Situations; Geneva University Hospitals) mobile app has been developed. This app offers a step-by-step guide for preparing and administering pediatric drugs during emergency interventions by automating the dose calculation process. Although previous simulation-based randomized controlled trials conducted in emergency care have demonstrated the efficacy of the PedAMINES app in reducing drug administration errors, there is a lack of evidence regarding its economic implications.

OBJECTIVE

This study aims to evaluate the cost-effectiveness of implementing the PedAMINES app for 4 emergency drugs: epinephrine, norepinephrine, dopamine, and midazolam.

METHODS

The economic evaluation was conducted by combining hospital data from 2019, previous trial outcomes, information extracted from existing literature, and PedAMINES maintenance costs. The cost per avoided medication error was calculated, along with the number of administrations needed to achieve a positive return on investment. Subsequently, Monte Carlo simulations were used to identify the key parameters contributing to result uncertainty.

RESULTS

The study revealed the number of preventable errors per administration for the 4 examined drugs: 0.513 for epinephrine, 0.484 for norepinephrine, 0.500 for dopamine, and 0.671 for midazolam. The cost-effectiveness ratios per ADE prevented were computed as follows: US $4808 for epinephrine, US $9705 for norepinephrine, US $6957 for dopamine, and US $2074 for midazolam. Accounting for the economic impact of ADEs, the analysis estimated that 16 administrations of epinephrine, 17 of norepinephrine and dopamine, and 13 of midazolam would be required to attain a positive return on investment. This corresponds to roughly one-third of the annual administrations at a major university hospital in Switzerland. The primary factors influencing the uncertainty in the estimated cost per ADE include the cost of maintenance of the app, the likelihood of an ADE resulting from an administration error, and the frequency of underdosing in the trial’s control group.

CONCLUSIONS

A dedicated mobile app presents an economically viable solution to alleviate the health and economic burden of drug administration errors in in-hospital pediatric emergency care. The widespread adoption of this app is advocated to pool costs and extend the benefits on a national scale in Switzerland.
The Value of Smartwatches in the Health Care Sector for Monitoring, Nudging, and Predicting: Viewpoint on 25 Years of Research (Preprint)
Authors: Köhler Charlotte , Bartschke Alexander , Fürstenau Daniel , Schaaf Thorsten , Salgado-Baez Eduardo
Published: October 2024

UNSTRUCTURED

We propose a categorization of smartwatch use in the health care sector into 3 key functional domains: monitoring, nudging, and predicting. Monitoring involves using smartwatches within medical treatments to track health data, nudging pertains to individual use for health purposes outside a particular medical setting, and predicting involves using aggregated user data to train machine learning algorithms to predict health outcomes. Each domain offers unique contributions to health care, yet there is a lack of nuanced discussion in existing research. This paper not only provides an overview of recent technological advancements in consumer smartwatches but also explores the 3 domains in detail, culminating in a comprehensive summary that anticipates the future value and impact of smartwatches in health care. By dissecting the interconnected challenges and potentials, this paper aims to enhance the understanding and effective deployment of smartwatches in value-based health care.