bluuebunny/crossref_metadata_2025 huggingface dataset:
Rural Buildings for Sustainable Development: A Real Estate Market Analysis in Southern Italy
Authors: Parete Giuseppe , Ottomano Palmisano Giovanni , De Boni Annalisa , Roma Rocco , Acciani Claudio
Published: May 2024

The profound transformations of traditional rural landscapes have heightened attention towards the recovery and valorisation of their buildings, often abandoned, to accommodate new landscape usage needs. This aligns with the principles of sustainable landscape management. However, knowledge of the rural real estate market remains largely unexplored. This research aims to define and examine the key features influencing the purchase of rural buildings, for shedding light on their market. The objective is to provide useful new insight to the property appraisers and real estate agents involved in the sale of traditional rural buildings, even if in conditions of degradation or abandonment and in traditional landscape contexts. Furthermore, these results could serve as a valuable resource for policymakers, enabling them to indirectly evaluate the impacts of urban and landscape policies on buyers’ preferences regarding key features of rural properties. The research focused on the ‘trulli’, traditional buildings located in the Valle d’Itria (Puglia, Southern Italy). First, a detailed market analysis was carried out with the support of local real estate experts, to survey the transactions of trulli and identify the features influencing their purchase. Second, the obtained dataset was analysed through network analysis, which enabled us to explore the role and importance assigned by buyers to the identified features. The results highlighted that the quality of the landscape where trulli are located changed the buyers’ viewpoint on the purchase features. In greater detail, price, area, potable water accessibility and level of maintenance of trulli were the most crucial features, particularly in high and medium landscape value zones, compatible with touristic and recreational activities. On the other hand, the annex agricultural surface covered a central function in low landscape value zone for possible agricultural uses.
Measuring Corporate Digital Transformation: Methodology, Indicators and Applications
Authors: Zou Limin , Li Wan , Wu Hongyi , Liu Jiawen , Gao Peng
Published: May 2024

With the rapid development of data science, digital technology is integrating deeply with enterprise management, driving companies towards digital transformation to achieve sustainable development. However, digital transformation is a systematic and comprehensive process, posing challenges in accurately depicting firm-level digitalization. Hence, this study systematically reviews measurement methods for digital transformation across various themes related to enterprise digitalization. Existing literature predominantly employs questionnaire analysis, quantitative statistics, and text analysis to gauge the extent of digital transformation. In terms of indicator construction, existing literature mainly relies on input, process, and outcome variables to construct measurement indicators. Nevertheless, due to the subjectivity of questionnaires, the uniqueness of industry data, and the limitations of textual information, these methods and the indicators derived from them possess distinct applicability scopes. Refining the measurement of digital transformation should hinge on both the research objectives and the characteristics of the data. Furthermore, through the analysis of industry cases such as agriculture, manufacturing and service industries, this study also reveals the unique characteristics encountered by these industries in the process of digital transformation, provides a more detailed summary of measurement methods for these specific industries, and emphasizes the importance of selecting measurement methods according to industry characteristics.
A Greenhouse Gas Footprint Analysis of Advanced Hardware Technologies in Connected Autonomous Vehicles
Authors: Zhang Haoyi , Zhao Fuquan , Song Haokun , Hao Han , Liu Zongwei
Published: May 2024

Greenhouse gas emissions are a critical concern for China’s automotive industry, especially for passenger cars due to their high sales’ volume. Recently, the trend towards connected and autonomous driving vehicles has been significant in the passenger car market. However, the impact of these systems on the life cycle emissions of vehicles remains unclear. This paper focuses on system function levels from driver assistance to full driving automation and studies their life cycle greenhouse gas emissions. This research establishes a component list for the hardware system and a material inventory. Then, this paper reveals significant differences in total system emissions at these technology levels, 540.1 kg for primary, 1318.7 kg for medium, and 2279.2 kg for advanced systems. Despite this difference, the total is less than 7.23% of the total vehicle emissions. To further reduce this portion of GHG emissions, it is recommended that vehicles favor millimeter-wave radar over solid-state LiDAR in their sensing system hardware, coupled with cameras as the primary sensing element. In addition, Intelligent Hardware Systems are not recommended for internal combustion engine passenger cars for optimal balance between functionality and environmental impact.
The Mediating Role of Corporate Governance in the Relationship between Net Profit and Equity and Voluntary Disclosure in the Context of Legitimacy Theory
Authors: Gezgin Talha , Özer Gökhan , Merter Abdullah Kürşat , Balcıoğlu Yavuz Selim
Published: May 2024

Amidst ongoing global economic and environmental crises, the concept of legitimacy has gained paramount importance for firms, which must not only survive but also maintain their legitimacy through comprehensive disclosures. This study investigates the mediating role of corporate governance in shaping firm performance and voluntary disclosure, emphasizing sustainability implications. Analyzing 82 firms across various sectors in Turkey from 2010 to 2020, the research reveals no direct relationship between corporate governance and equity. However, it identifies a partial mediation effect of corporate governance on the disclosure of general, strategic, and forward-looking financial information related to net profit. Critically, our findings demonstrate that corporate governance fully mediates the relationship between net profit and the disclosure of social and board information, with the magnitude of this indirect effect being complete. This underscores the fact that robust corporate governance enhances transparency in social and environmental reporting, thereby supporting firms in their efforts to align with sustainable business practices and stakeholder expectations. These results highlight the crucial role of effective governance in ensuring comprehensive disclosures that support the sustainability goals of modern enterprises.
Energy Assessment of Alternative City Bus Lines: A Case Study in Gijón, Spain
Authors: Diaz Jose , Pérez Borja , Fernández Francisco J.
Published: May 2024

The progressive substitution of traditional buses with electric ones in urban public transport constitutes a fundamental challenge towards sustainable mobility. This paper presents a methodological approach to assess energy consumption in urban bus networks, focusing on a city with varied topography and examining alternative bus lines for similar trips. Utilizing a quasi-static longitudinal model, real GPS data, and open access terrain models, the analysis aims to provide a nuanced understanding of energy performance, considering factors such as stop characteristics, gradients, and driving styles. The influence of driving style on commercial speed is observed to be modest, yet significant, in terms of energy efficiency. This research identifies the most advantageous line for transitioning from Internal Combustion Engine (ICE) to Electric Motor (EM) powertrains, resulting in a significant 68% reduction in energy consumption. Beyond specific line details, this methodology offers insights applicable to medium-sized cities, emphasizing efficient route prioritization and providing enhanced user information for informed decisions in the context of sustainable transportation solutions.
Evaluation of Perceptions Using Facial Expression Scores on Ecological Service Value of Blue and Green Spaces in 61 Parks in Guizhou
Authors: Wang Lan , Zhou Changwei
Published: May 2024

This study selected 61 parks in Guizhou province as research points and collected 3282 facial expression photos of park visitors in 2021 on the Sina Weibo platform. FireFACE v1.0 software was used to analyze the facial expressions of the visitors and evaluate their emotional perception of the landscape structure and ecosystem service value (ESV) of different landscape types of blue–green spaces. Research shows that the average ESV of green spaces in parks is USD 6.452 million per year, while the average ESV of blue spaces is USD 3.4816 million per year. The ESV of the blue–green space in the park shows no geographical gradient changes, while the happiness score in facial expressions is negatively correlated with latitude. Compared to blue spaces, green spaces can better awaken positive emotions among visitors. The ESV performance of different types of green spaces is as follows: TheroponcedrymV > GrasslandV > Shrubland V. The landscape structure and ESV of the blue–green space in the park can be perceived by visitors, and GreenV and vegetation height are considered the main driving factors for awakening positive emotions among visitors. In Guizhou, when the park area decreases, people are more likely to experience sadness. Regressions indicated that by increasing the green space area of the park and strengthening the hydrological regulation function of the blue–green space, people can achieve a more peaceful mood. Overall, people perceive more positive sentiments with high ESV in blue–green spaces of Karst parks but low ESV in shrubland.
Analysis of Factors Influencing Driver Yielding Behavior at Midblock Crosswalks on Urban Arterial Roads in Thailand
Authors: Pechteep Pongsatorn , Luathep Paramet , Jaensirisak Sittha , Kronprasert Nopadon
Published: May 2024

Globally, road traffic collisions cause over a million deaths annually, with pedestrians accounting for 23%. In developing countries, most pedestrian deaths occur on urban arterial roads, particularly at midblock crossings. This study analyzes the factors influencing driver yielding behavior at midblock crosswalks on urban arterial roads in Thailand. This study analyzed the factors influencing driver yielding behavior at the midblock crosswalk before and after the upgrade from a zebra crossing (C1) to a smart pedestrian crossing (C2), which is a smart traffic signal detecting and controlling pedestrians and vehicles entering the crosswalk. Video-based observations were used to assess driver yielding behavior, with multinomial logistic regression applied to develop driver yielding behavior models. The results revealed that the chances of a driver yielding at C2 were higher than at C1, and the yielding rate increased by 74%. The models indicate that the number and width of traffic lanes, width and length of crosswalks, vulnerable group, number of pedestrians, pedestrian crossing time, number of vehicles, vehicle speed, headway, post-encroachment time between a vehicle and pedestrian, and roadside parking are the significant factors influencing yielding behavior. These findings propose measures to set proper crosswalk improvements (e.g., curb extensions), speed reduction measures, enforcement (e.g., parking restrictions), public awareness campaigns, and education initiatives.
Research on the Impact of New Energy Vehicle Companies’ Marketing Strategies on Consumers’ Purchase Intention
Authors: Wei Shuo , Xu Hejun , Zheng Sijing , Chen Junxi
Published: May 2024

With the rapid advancement of battery technology and the demand for environmental sustainability, new energy vehicles (NEVs) are becoming more and more popular. This research paper delves into the impact of marketing strategies employed by new energy vehicle companies on consumers’ purchase intentions. This paper begins by highlighting the unique benefits of NEVs, such as energy efficiency, environmental friendliness, and improved driving experience. Then, this research identifies gaps in existing research, particularly the lack of micro-market demand data and systematic empirical analyses of consumer purchase intentions for NEVs. The paper employs a quantitative analysis approach grounded in marketing theory to address these gaps and examine the relationship between NEV companies’ marketing strategies and consumers’ purchase intentions. The research design involves a questionnaire survey based on the 4C marketing theory, focusing on consumer demand, cost, communication, and convenience. The survey targets potential NEV buyers and car owners, and 247 valid responses were analyzed. The results reveal that various factors, including the price and environmental performance of NEVs, non-fiscal policies, vehicle performance, and consumer attributes such as education level and environmental awareness, influence consumers’ willingness to purchase NEVs. This study also employs structural equation modeling to explore the correlations between different issues and identifies three main factors: basic car needs, new energy needs, and consumer subjective perception. Lastly, the study concludes that while NEV companies have made significant strides in marketing strategies, there is still room for improvement. We suggest that companies should offer competitive pricing, enhance vehicle performance, and address consumer concerns to boost purchase intentions.
Combined Analysis of Neutrino and Antineutrino Charged Current Inclusive Interactions
Authors: Franco-Patino Juan M. , Gacino-Olmedo Alejandro N. , Gonzalez-Rosa Jesus , Dolan Stephen J. , Megias Guillermo D. , Munteanu Laura , Barbaro Maria B. , Caballero Juan A.
Published: May 2024

This paper presents a combined analysis of muon neutrino and antineutrino charged-current cross sections at kinematics of relevance for the T2K, MINERvA and MicroBooNE experiments. We analyze the sum, difference and asymmetry of neutrino versus antineutrino cross sections in order to get a better understanding of the nuclear effects involved in these processes. Nuclear models based on the superscaling behavior and the relativistic mean field theory are applied, covering a wide range of kinematics, from hundreds of MeV to several GeV, and the relevant nuclear regimes, i.e., from quasileastic reactions to deep inelastic scattering processes. The NEUT neutrino-interaction event generator, used in neutrino oscillation experiments, is also applied to the analysis of the quasielastic channel via local Fermi gas and spectral function approaches.
Stability and Hopf Bifurcation of a Delayed Predator–Prey Model with a Stage Structure for Generalist Predators and a Holling Type-II Functional Response
Authors: Liang Zi-Wei , Meng Xin-You
Published: May 2024

In this paper, we carry out some research on a predator–prey system with maturation delay, a stage structure for generalist predators and a Holling type-II functional response, which has already been proposed. First, for the delayed model, we obtain the conditions for the occurrence of stability switches of the positive equilibrium and possible Hopf bifurcation values owing to the growth of the value of the delay by applying the geometric criterion. It should be pointed out that when we suppose that the characteristic equation has a pair of imaginary roots λ=±iω(ω>0), we just need to consider iω(ω>0) due to the symmetry, which alleviates the computation requirements. Next, we investigate the nature of Hopf bifurcation. Finally, we conduct numerical simulations to verify the correctness of our findings.
A Novel Neutrosophic Likert Scale Analysis of Perceptions of Organizational Distributive Justice via a Score Function: A Complete Statistical Study and Symmetry Evidence Using Real-Life Survey Data
Authors: Bodur Seher , Topal Selçuk , Gürkan Hacı , Edalatpanah Seyyed Ahmad
Published: May 2024

In this study, ten questions measuring distributive justice on classical Likert and neutrosophic Likert scales consisting of two subdimensions—distributive and procedural justice—were used. Participants responded to the same questions for both the classical Likert and neutrosophic Likert scales within a single survey, with the neutrosophic method applied, for the first time, to the questions included in the scale. The neutrosophic scale responses were answered in percentages to resemble natural language, and the answers received for each question were reduced to the range [−1, 1] to grade the agreement approach through a score function used in neutrosophic decision-making theory. In this study, the neutrosophic scale, a scaling method with strong theoretical foundations, was compared with the traditional Likert scale. The results of the statistical analyses (exploratory factor analysis, reliability analysis, neural network analysis, correlation analysis, paired samples t-test, and one-way and two-way ANOVAs) and evaluations of the scales were compared to measure organizational justice within a single study. In this article, the symmetric and non-symmetric properties of statistical analysis that are specific to this paper in addition to general symmetric and non-symmetry properties are discussed. These symmetric and non-symmetric features are conceptualized according to the features on which each statistical analysis focuses. Finally, although this study presents a new area of research in the social sciences, we believe that the neutrosophic Likert scale and survey approach will contribute to collecting detailed and sensitive information on many topics, such as economics, health, audience perceptions, advertising responses, and product, market, and service purchase research, through the use of score functions.
Evolution of Hybrid Cellular Automata for Density Classification Problem
Authors: Anghelescu Petre
Published: May 2024

This paper describes a solution for the image density classification problem (DCP) using an entirely distributed system with only local processing of information named cellular automata (CA). The proposed solution uses two cellular automata’s features, density conserving and translation of the information stored in the cellular automata’s cells through the lattice, in order to obtain the solution for the density classification problem. The motivation for choosing a bio-inspired technique based on CA for solving the DCP is to investigate the principles of self-organizing decentralized computation and to assess the capabilities of CA to achieve such computation, which is applicable to many real-world decentralized problems that require a decision to be taken by majority voting, such as multi-agent holonic systems, collaborative robots, drones’ fleet, image analysis, traffic optimization, forming and then separating clusters with different values. The entire application is coded using the C# programming language, and the obtained results and comparisons between different cellular automata configurations are also discussed in this research.
Emergence of Novel WEDEx-Kerberotic Cryptographic Framework to Strengthen the Cloud Data Security against Malicious Attacks
Authors: Zahra Syeda Wajiha , Nadeem Muhammad , Arshad Ali , Riaz Saman , Ahmed Waqas , Abu Bakr Muhammad , Alabrah Amerah
Published: May 2024

Researchers have created cryptography algorithms that encrypt data using a public or private key to secure it from intruders. It is insufficient to protect the data by using such a key. No research article has identified an algorithm capable of protecting both the data and the associated key, nor has any mechanism been developed to determine whether access to the data is permissible or impermissible based on the authentication of the key. This paper presents a WEDEx-Kerberotic Framework for data protection, in which a user-defined key is firstly converted to a cipher key using the “Secure Words on Joining Key (SWJK)” algorithm. Subsequently, a WEDEx-Kerberotic encryption mechanism is created to protect the data by encrypting it with the cipher key. The first reason for making the WEDEx-Kerberotic Framework is to convert the user-defined key into a key that has nothing to do with the original key, and the length of the cipher key is much shorter than the original key. The second reason is that each ciphertext and key value are interlinked. When an intruder utilizes the snatching mechanism to obtain data, the attacker obtains data or a key unrelated to the original data. No matter how efficient the algorithm is, an attacker cannot access the data when these methods and algorithms are used to protect it. Finally, the proposed algorithm is compared to the previous approaches to determine the uniqueness of the algorithm and assess its superiority to the previous algorithms.
Analyzing Dynamics: Lie Symmetry Approach to Bifurcation, Chaos, Multistability, and Solitons in Extended (3 + 1)-Dimensional Wave Equation
Authors: Riaz Muhammad Bilal , Jhangeer Adil , Duraihem Faisal Z. , Martinovic Jan
Published: May 2024

The examination of new (3 + 1)-dimensional wave equations is undertaken in this study. Initially, the identification of the Lie symmetries of the model is carried out through the utilization of the Lie symmetry approach. The commutator and adjoint table of the symmetries are presented. Subsequently, the model under discussion is transformed into an ordinary differential equation using these symmetries. The construction of several bright, kink, and dark solitons for the suggested equation is then achieved through the utilization of the new auxiliary equation method. Subsequently, an analysis of the dynamical nature of the model is conducted, encompassing various angles such as bifurcation, chaos, and sensitivity. Bifurcation occurs at critical points within a dynamical system, accompanied by the application of an outward force, which unveils the emergence of chaotic phenomena. Two-dimensional plots, time plots, multistability, and Lyapunov exponents are presented to illustrate these chaotic behaviors. Furthermore, the sensitivity of the investigated model is executed utilizing the Runge–Kutta method. This analysis confirms that the stability of the solution is minimally affected by small changes in initial conditions. The attained outcomes show the effectiveness of the presented methods in evaluating solitons of multiple nonlinear models.
Culicoides Midge Abundance across Years: Modeling Inter-Annual Variation for an Avian Feeder and a Candidate Vector of Hemorrhagic Diseases in Farmed Wildlife
Authors: Benn Jamie S. , Orange Jeremy P. , Gomez Juan Pablo , Dinh Emily T. N. , McGregor Bethany L. , Blosser Erik M. , Burkett-Cadena Nathan D. , Wisely Samantha M. , Blackburn Jason K.
Published: May 2024

(1) Background: Epizootic hemorrhagic disease virus (EHDV) and bluetongue virus (BTV) are orbiviruses that cause hemorrhagic disease (HD) with significant economic and population health impacts on domestic livestock and wildlife. In the United States, white-tailed deer (Odocoileus virginianus) are particularly susceptible to these viruses and are a frequent blood meal host for various species of Culicoides biting midges (Diptera: Ceratopogonidae) that transmit orbiviruses. The species of Culicoides that transmit EHDV and BTV vary between regions, and larval habitats can differ widely between vector species. Understanding how midges are distributed across landscapes can inform HD virus transmission risk on a local scale, allowing for improved animal management plans to avoid suspected high-risk areas or target these areas for insecticide control. (2) Methods: We used occupancy modeling to estimate the abundance of gravid (egg-laden) and parous (most likely to transmit the virus) females of two putative vector species, C. stellifer and C. venustus, and one species, C. haematopotus, that was not considered a putative vector. We developed a universal model to determine habitat preferences, then mapped a predicted weekly midge abundance during the HD transmission seasons in 2015 (July–October) and 2016 (May–October) in Florida. (3) Results: We found differences in habitat preferences and spatial distribution between the parous and gravid states for C. haematopotus and C. stellifer. Gravid midges preferred areas close to water on the border of well and poorly drained soil. They also preferred mixed bottomland hardwood habitats, whereas parous midges appeared less selective of habitat. (4) Conclusions: If C. stellifer is confirmed as an EHDV vector in this region, the distinct spatial and abundance patterns between species and physiological states suggest that the HD risk is non-random across the study area.
Retrospective Analysis of Severe Dengue by Dengue Virus Serotypes in a Population with Social Security, Mexico 2023
Authors: Hernández Bautista Porfirio Felipe , Cabrera Gaytán David Alejandro , Santacruz Tinoco Clara Esperanza , Vallejos Parás Alfonso , Alvarado Yaah Julio Elias , Martínez Miguel Bernardo , Anguiano Hernández Yu Mei , Arriaga Nieto Lumumba , Moctezuma Paz Alejandro , Jaimes Betancourt Leticia , Pérez Andrade Yadira , Orozco Oscar Cruz , Valle Alvarado Gabriel , Rivera Mahey Mónica Grisel
Published: May 2024

Background: Risk factors for severe dengue manifestations have been attributed to various factors, including specific serotypes, sex, and age. Mexico has seen the re-emergence of DENV-3, which has not circulated in a decade. Objective: To describe dengue serotypes by age, sex, and their association with disease severity in dengue-positive serum samples from epidemiological surveillance system units. Materials and Methods: A descriptive analysis was conducted to evaluate the frequency of dengue severity by sex, age, disease quarter, geographical location, and dengue virus serotypes. The study was conducted using laboratory samples from confirmed dengue cases through RT-qPCR from the epidemiological surveillance laboratory network of the Mexican Social Security Institute, Mexico. Simple frequencies and proportions were calculated using the z-test for proportional differences between groups. Bivariate analysis with adjusted Chi2 was performed, and binary logistic regression models were constructed using the forward Wald method considering the model’s predictive capacity. The measure of association was the odds ratio, with 95% confidence intervals. Statistical significance was set to an alpha level of <0.05. Results: In 2023, 10,441 samples were processed for dengue RT-qPCR at the IMSS, with a predominance of serotype DENV-3 (64.4%). The samples were mostly from women (52.0%) and outpatient cases (63.3%). The distribution of dengue severity showed significant variations by age, with a lower proportion of severe cases in young children and a higher proportion in the 5- to 14-year-old group. Hospitalizations increased significantly with severity. Warm regions had more cases overall and severity. Cases were most frequent from July to September. While DENV-2 was associated with severity, DENV-4 was not. Binary regression identified higher risk in women, age extremes, and DENV-2, with an overall predictive model of 58.5%. Conclusions: Women, age groups at the extremes of life, and the DENV-2 serotype presented severe risk of dengue in a population with social security in Mexico during 2023.
Water Point and Non-Point Nitrogen Pollution Due to Land-Use Change and Nitrate Deposition in China from 2000 to 2020
Authors: Zhao Xiaoning , Shi Jiawei , Xue Lihua , Li Wenwen , Zamanian Kazem , Han Jiangang , Chen Shuang
Published: May 2024

Water N-NO3− (mg L−1) pollution is attracting global concern in the face of combating climate change and human health risks. However, there have been comparatively few comprehensively researched studies on water N-NO3− pollution with respect to N-NO3− deposition, soil nitrogen, and land-use changes. We collected a total of 7707 published sampling points on N-NO3− surface and groundwater during flooding and non-flooding seasons during 2000–2020 in China. The types of water N-NO3− pollution (>20) can be categorized as point pollution (ΔTN ≤ 0 or > 1.5) and non-point pollution (0 < ΔTN ≤ 1.5), which were then assessed with respect to soil nitrogen (ΔTN g kg−1) and water N-NO3− changes in this study. We found non-point pollution was concentrated in the Huaihe River Basin and Haihe River Basin with higher urbanization (+6%, +4%), cropland (72%, 45%), nitrogen fertilization (g m−2 yr−1) (>10), and increased wet N-NO3− deposition (WND) (kg ha−1 yr−1) (+4.6, +3). The Haihe River Basin was found to have the highest N-NO3− on its surface (306) and in its groundwater (868) and nitrogen fertilization (32). Point pollution was concentrated in the Songhua and Liaohe River Basin with the highest WND (+7.9) but slow urbanization (+1%). N-NO3− increased during the flooding season compared with the no-flooding season in serious pollution areas. N-NO3− increased in the Liaohe River and middle and low Yangtze River but was reduced in the Weihe River. Therefore, stringent criteria and management, especially during the flooding season are urgently required to mitigate the degree of N-NO3− water pollution that occurs due to intensive agriculture and urbanization with increased N-NO3− deposition.
Artificial intelligence in diagnosis of neurodegenerative disorders (literature review)
Authors:   Federal State Budgetary Educational Institution of Higher Education “Penza State University”, Penza, Russia, Petrova E. V. , Suchkova E. V. ,   Federal State Budgetary Educational Institution of Higher Education “Penza State University”, Penza, Russia, Haddad N. ,   Federal State Budgetary Educational Institution of Higher Education “Penza State University”, Penza, Russia, Ali-Hassan M. ,   Federal State Budgetary Educational Institution of Higher Education “Penza State University”, Penza, Russia, Bodrov V. A. ,   Federal State Budgetary Educational Institution of Higher Education “Samara State Medical University” of the Ministry of Health of the Russian Federation, Samara, Russia
Published: May 2024

Currently, there are virtually no objective diagnostic signs (markers) to diagnose neurodegenerative diseases, that is why it may take months of constant monitoring of symptoms to establish a reliable diagnosis. Now there is an increasing number of reports that artificial intelligence can provide a more accurate diagnosis of neurodegenerative diseases by identifying specific diagnostic features from electroencephalography data, neuroimaging, and wearable devices and smartphones. This study reviews the application of artificial intelligence to the diagnosis of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, and Huntington's disease. Using the international databases Scopus and PubMed, as well as the Russian Science Citation Index, we analysed studies that used artificial intelligence methods to detect, monitor, or control the progression of neurodegenerative diseases. The primary focus is on analysing electroencephalography data, neuroimaging data, and data from wearable devices and smartphones. The use of the latter may allow screening, diagnosis, and monitoring of the disease at home with a minimum economic cost. Artificial intelligence can be a useful tool for early, accurate, and non-invasive diagnosis of neurodegenerative diseases, as well as for assessing the effectiveness of treatment and predicting the course of the disease. However, for the widespread implementation of artificial intelligence in clinical practice, several issues related to the quality, availability, and standardization of data, validation and interpretation of results, ethical and legal aspects need to be resolved. The use of artificial intelligence requires both specialists from the IT industry with a deep understanding of the types and kinds of neural networks and physicians with fundamental knowledge of neurology, psychiatry, molecular biology, and biophysics.
True parahiatal hernia: a case of laparoscopic management for a rare type of diaphragmatic hernia
Authors:   Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, Moscow, Russian Federation, Lukanin D. V. , Rodoman G. V. ,   Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, City Clinical Hospital № 24, Moscow Health Department, Moscow, Russian Federation, Sokolov A. A. ,   Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation, Moscow, Russian Federation, Klimenko M. S. ,   Pirogov Russian National Research Medical University, Ministry of Health of the Russian Federation,
Published: May 2024

Parahiatal hernias are the rare variant of a diaphragmatic hernias. They are characterized by the formation of the neck of the hernia sac laterally to the diaphragm crura (usually the left), which distinguishes them from hiatal hernias. Hernia usually affects the fundus and body of the stomach, the esophagogastric junction remains below the level of the diaphragm, and clinical manifestations are associated with episodes of strangulation or axial volvulus. The article describes a case of parahiatal hernia complicated by chronic gastric volvulus with subsequent development of acute axial volvulus, which required urgent laparoscopic management.
Long-term results of rectocele surgical treatment by rectovaginal septum repair with a W-shaped mesh implant
Authors:   FSBI Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of Russia, Lukyanov A. S. , Kostarev I. V. ,   FSBI Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of Russia, Frolov S. A. ,   FSBI Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of Russia, Minbaev Sh. T. ,   FSBI Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of Russia, Biryukov O. M. ,   FSBI Ryzhikh National Medical Research Center of Coloproctology of the Ministry of Health of Russia
Published: May 2024

40 patients with grade 2 and 3 rectocele were included in the study. The long-term results of surgical treatment within a timeframe of 12–42 months after surgery were evaluated in 34 (85 %) patients. The average duration of the disease history amounted to 5 (0.7–19) years. The mean age of the patients was 53.1±10.3 (Me=54.5) years. Before the surgery, as well as 6 and 12 months after the surgery, all patients underwent radiological defecography and were interviewed by means of specialized questionnaires to determine the disorders of the evacuation function of the colon and comprehensively assess the symptomatology of pelvic organ prolapse. Late postoperative complications were revealed in 2 out of 35 (5.7 %) patients 6 months after the surgical intervention. Twelve months after surgery and over, 31 out of 34 (91 %) patients had good or satisfactory outcomes characterized by a significant decrease in the manifestations of obstructed defecation syndrome, confirmed by the results of defecography, which showed an improvement in all criteria of the rectal evacuation function evaluation. These data objectively confirm the effectiveness of this method of treatment. The comparative analysis of the results of the patient survey by means of specialized questionnaires demonstrated a statistically significant difference between the level of scores before the intervention and 12 months after rectovaginal septum repair with W-shaped mesh implant. In conclusion, the method of rectovaginal septum repair with W-shaped mesh implant demonstrated its high efficiency, including the evaluation in the long-term follow-up period.
Blockchain Integration with AIoT Data Security and Privacy for Sustainability
Authors: Arora Priyanka , Makani Ritu
Published: May 2024

As a primary goal, AIoT (Artificial Intelligence of Things) is the fusion of AI (artificial intelligence) methods with IoT (Internet of Things) infrastructure, which is deployed there to enhance the overall system performance of AIoT. Artificial Intelligence of Things can be used to make Internet of Things operations more efficient, which will enhance data analysis and human-machine interactions. The system's general usefulness is further increased by applying artificial intelligence techniques to convert Internet of Things data into relevant information for improved decision-making processes. The Artificial Intelligence of Things frameworks have a wide range of applications, including eCommerce, logistics operations and control, smart homes, smart farms, intelligent transportation systems, industrial automation and control, eCommerce, secure as well as safe healthcare monitoring, and many more. AIoT frameworks, however, are susceptible to a variety of information security-related assaults, which could result in problems with data security and privacy. Serious repercussions, such as unapproved data updates and leaks, are also brought on by these problems. One particular kind of database is the blockchain. It's a digital record of all the transactions that's distributed throughout the whole network of systems. Data is stored in the blocks that are linked in a chained manner. Compared to conventional security methods, blockchain technology offers greater security and is impervious to tampering. Therefore, to increase security, blockchain can be used in a variety of AIoT applications. A safe authentication architecture for AIoT has been suggested, modelled after a generalised blockchain. The adversarial model, which handles most potential security threats in this kind of communication environment, is also highlighted. This framework is part of the blockchain-envisioned safe authentication framework for the Internet of Things. The suggested framework's numerous applications are also covered. Additionally, certain problems and difficulties with the suggested framework are emphasised. Finally, we also offer some suggestions for future research that are related to the framework that has been suggested.
ECORELEAF: An IOT based Eco-Solution
Authors: Panda Swagatika , Sahu Nikhil , Jain Yash , Behera Sasmita
Published: May 2024

Green space usually comes at a price when living in a city. The state of air pollution is escalating globally. A sustainable solution to this problem is to plant more trees, but it's not as simple as it seems. Selecting the right plants that will thrive in the local climate is also important. It has long been known that plants can help in the reduction of pollutants in the air. We introduce a novel solution, Ecorelaf: A Plantation Prediction Application, which leverages the integration of Artificial Intelligence and the Internet of Things (AIoT) for effective environmental monitoring and conservation. Through a network of sensors and IoTs strategically placed to monitor pollution levels, Ecoreleaf collects valuable data on air quality, which is then seamlessly transmitted to a centralized database. Which then calculates the AQI according to the various pollutant levels.Moreover, future levels of the air quality index (AQI) can be predicted using data on air quality.[13] Our Objective is to combine the pollution data i.e. AQI of an area to design a model which predicts suitable plants for that area. ECORELEAF is a user-friendly application designed for keeping Environmental Monitoring and Conservation in mind to bridge the gap between information and action.
Wyoming Conservation Exchange: A Case Study in Grassroots Conservation Program Design
Authors: Hansen Kristi , Brodnax Sara , Coupal Roger , Lamb Jennifer , MacKinnon Anne , Paige Ginger , Peterson Eric , Purcell Melanie
Published: May 2024

This article describes the conception and development of a market-based conservation program in Wyoming whose purpose was threefold: to compensate landowners for good stewardship of their land and water resources; facilitate meaningful conservation; and encourage environmentally responsible energy development. The program was developed with strong stakeholder support against a backdrop of significant regulatory change. The project, called the Wyoming Conservation Exchange (WCE), represents a project-based alternative to more traditional program-based Extension efforts. This article evaluates ways in which the WCE can act as a road map—but also a cautionary tale—for similar Extension efforts in the future.
Using Multimedia to Help Agricultural Producers Communicate with Consumers about GMOs
Authors: Stearns Stacey , Cushman Jennifer , Bonelli Joseph , Burr Bonnie
Published: May 2024

Genetically modified organisms (GMOs) and their uses are often misunderstood. Consumers are regularly unsure what GMOs are, or if they are safe for consumption and the environment. Contradictory and sometimes inaccurate information is available from numerous sources, and challenges consumers and others to separate the facts from sensationalized stories. Agricultural producers often communicate with consumers, neighbors, and members of the general public; however, they do not have information to share about GMOs. Multimedia resources can provide agricultural producers with science-based information to share with consumers. Agricultural communicators and Extension educators can create science-based multimedia resources to bridge the communication gap.
The Impact of the COVID-19 Pandemic on Cancer Patients’ Access to Diagnostic and Treatment Services in Kerman Province: A Qualitative Study
Authors: Jangipour Afshar Parya , Sadidi Nasrin , Nasiri Naser , Sharifi Hamid , Jaafari Zahra
Published: May 2024

Background: Pandemics affect patients’ access to diagnostic and treatment services. As cancer patients need regular follow-up, any obstacle in accessing services can affect the conditions of these patients. Therefore, this study was conducted to investigate the effects of the COVID-19 pandemic on cancer patients’ access to diagnostic and treatment services. Methods: In this qualitative study, 15 people were selected through a targeted sampling method among the patients who were referred to cancer treatment centers in Kerman. The interviews were semi-structured and face-to-face and were conducted in April 2021. The data were analyzed using directed content analysis. Results: Among the people included in this study, 10 (66.7%) were women and more than half of the investigated people were in the 36 to 55 years age group (53.3%). These patients faced challenges including delay in treatment, mental and psychological problems, financial problems, and delay in COVID-19 vaccination. Conclusion: Various challenges and factors play a role in cancer patients’ access to diagnostic and treatment services during the pandemic. Therefore, more physical space should be allocated to them in treatment environments to reassure them and facilitate their timely referral to doctors. In addition, psychiatric consultations to identify the problems of cancer patients and regular follow-up of these patients can reduce their problems during pandemics such as the COVID-19 pandemic.
Effect of the COVID-19 Pandemic on the Performance Indicators of Academic and Non-academic Hospitals in West Azerbaijan Province in 2020
Authors: Babaei Majid , Hasanzadeh Shila , Yousefi Yaghoub , Pashaei Mohammadreza
Published: May 2024

Background: Hospitals are the most important pillar of the country›s health system, especially when faced with a crisis. One of the most important indicators in evaluating hospitals is performance indicators. This research was done to investigate the effect of the COVID-19 pandemic on the performance indicators of academic and non-academic hospitals in West Azerbaijan province in 2020. Methods: The present cross-sectional descriptive-analytical study was done on all academic and non-academic hospitals of West Azerbaijan province, which examined their performance indicators in 2019 and 2020. The data were analyzed using SPSS 16 software by repeated-measures analysis of variance (ANOVA). Results: The results of repeated-measures ANOVA demonstrated that the effect of time (coronavirus) on the index of bed occupancy ratio was significant (η2=0.24, P=0.006) so that it decreased this index in academic hospitals and had the opposite result in non-academic hospitals. The COVID-19 had a significant effect on the index of average patient stay (η2=0.47, P<0.001) and this index in both types of hospitals increased. Also, the COVID-19 had a significant effect on bed turnover rate (η2=0.32, P=0.001) and it decreased in both types of hospitals. Conclusion: Since academic hospitals are more responsible in dealing with epidemics, it is suggested to pay more attention to their infrastructures. Considering the financial burden of some non-communicable diseases, academic hospitals should be prepared to accept and support them, especially in the early period of the epidemic.
Optimization of Vancomycin Antibiotic Removal from Synthetic and Real Wastewater Using UV/Fe3 O4 @Alg-ZnO Nanocomposite Photocatalysis: Response Surface Methodology Based on a Box-Behnken Design
Authors: Rahrovan Mahsa , Rahmani Hasan , Rabbani Davarkhah , Miranzadeh Mohammadbagher , Rahimi Habibollah
Published: May 2024

Background: Vancomycin (VCM) is a critical antibiotic due to its high consumption and side effects, including increased bacterial resistance affecting treatment processes. This research investigated the efficiency of VCM antibiotic removal from an aqueous solution using a UV/Fe3 O4 @Alg-ZnO integrated process. Methods: Response surface methodology (RSM) and a Box-Behnken design were applied using Design-Expert software to optimize the number of samples and simultaneously understand the interactive effects between variables. X-ray diffraction (XRD), a vibrating-sample magnetometer (VSM), field effect scanning electron microscopy (FE-SEM), and Fourier transform infrared (FTIR) analyses were used to check the structural characteristics. The effects of initial catalyst concentration (0.1, 0.3, and 0.5 g/L), initial pollutant concentration (10, 30, and 50 mg/L), contact time (10, 30, and 50 minutes), and pH (3, 7, and 11) on VCM decomposition rate were investigated. Spectrophotometry, total organic carbon (TOC), and GC-MS analyses were used to check the efficiency of the process. Results: In this study, VCM and TOC removal efficiency was 92.64% and 85.38%, respectively, under optimal conditions. The reason for the reduction in the efficiency of the combined UV/Fe3 O4 @Alg-ZnO process in real raw sewage, after activated sludge (13%) and after activated sludge and stabilization ponds (24%), is the high COD, which causes the active radicals produced to be spent on other species instead of the VCM antibiotic. Conclusion: The current study showed that the UV/Fe3 O4 @Alg-ZnO process performs well in removing VCM and TOC. In real wastewater, this efficiency was significantly reduced.
Comprehensive Analysis of Nutrient Composition: Evaluating Vitamins, Essential Minerals, and Trace Metals in Neem (Azadirachta indica) Stem Bark Extract
Authors: Adeoye Ademola E. , Adeoye Akintunde M. , Mufliat Mustapha
Published: May 2024

The current study sought to investigate the nutrients in an aqueous extract of Neem (Azadirachta indica) stem bark. The bioactive chemical contents of Neem stem bark were isolated, separated, and studied to determine the presence of vitamins, vital minerals, and trace metals. A fresh Neem sample was collected and the sample was ground into powdered form and prepared via extraction using various solvents (n-hexane, ethyl acetate, and ethanol), and the chemical constituents were separated using the GC/MS technique. The Neem stem sample was later digested with nitric acid and hydrogen peroxide in the ratio 4:1 (acid ratio). The trace metals and important minerals in digested Neem samples were determined using an atomic absorption spectrophotometer (AAS), while Na+ and K+ were determined using a flame photometer. The results revealed that calcium is the most prevalent mineral in Neem stem bark, followed by potassium and sodium, but copper, magnesium, iron, zinc, and other minerals are present in trace amounts, while cadmium and lead are virtually missing. Furthermore, according to the results of the vitamin studies, the most abundant vitamins in Neem stem bark are vitamin B3 and vitamin C, but vitamins A, B1, B6, and B12 are present in trace amounts.