bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of Wrinkled MoS2 Thin Films Using a Two-Step Method Consisting of Magnetron Sputtering and Sulfurization in a Confined Space
Authors: Mihai Claudia , Simandan Iosif-Daniel , Sava Florinel , Buruiana Angel-Theodor , Bocirnea Amelia Elena , Tite Teddy , Zaki Mohamed Yassine , Velea Alin
Published: May 2024

Considering the increasing need for sustainable and economical energy storage solutions, the integration of layered materials such as MoS2 into these systems represents an important step toward enhancing energy sustainability and efficiency. Exploring environmentally responsible fabrication techniques, this study assesses wrinkled MoS2 thin films synthesized from distinct Mo and MoS2 targets, followed by sulfurization conducted in a graphite box. We utilized magnetron sputtering to deposit precursor Mo and MoS2 films on Si substrates, achieving thicknesses below 20 nm. This novel approach decreases sulfur by up to tenfold during sulfurization due to the confined space technique, contributing also to avoiding the formation of toxic gases such as SO2 or the necessity of using H2S, aligning with sustainable materials development. Thinner MoS2 layers were obtained post-sulfurization from the MoS2 precursors, as shown by X-ray reflectometry. Raman spectroscopy and grazing X-ray diffraction analyses confirmed the amorphous nature of the as-deposited films. Post-sulfurization, both types of films exhibited crystalline hexagonal MoS2 phases, with the sulfurized Mo showing a polycrystalline nature with a (100) orientation and sulfurized MoS2 displaying a (00L) preferred orientation. The X-ray photoelectron spectroscopy results supported a Mo:S ratio of 1:2 on the surface of the films obtained using the MoS2 precursor films, confirming the stoichiometry obtained by means of energy dispersive X-ray spectroscopy. Scanning electron microscopy and atomic force microscopy images revealed micrometer-sized clusters potentially formed during rapid cooling post-sulfurization, with an increased average roughness. These results open the way for the further exploration of wrinkled MoS2 thin films in advanced energy storage technologies.
Standing Watch: Baselining Predictable Events That Influence Maritime Operations in the Context of the UN’s Sustainable Development Goals
Authors: Lambert Bruce , Merten James
Published: May 2024

The authors present a practical framework for assessing seasonal events that may influence maritime operations, seeking to tie in discussions about climate change adoption to maritime operational assessments. Most maritime-related research tends to focus on a single event, such as a storm, but maritime systems operate within complex systems that have some predictable patterns. These predictable patterns due to natural events, such as weather and water levels, can influence operations. By contrast, other factors, such as cargo peaks or cultural activities, could also shape maritime systems. The growing focus on adopting human activities to the United Nations’ Sustainability Development Goals means that system operations should consider their relationship to these broader goals. By integrating data from emergency management databases and weather information sources with other inputs, the authors, in collaboration with various stakeholder groups, created a matrix of regionally specific predictable events that may occur within a region by time of year that can be linked to the Sustainability Development Goals. The matrix was vetted to verify the information, ensuring that all perspectives were considered. The main findings were that a seasonal event matrix was not just a theoretical tool but a practical reference for examining operational patterns in a river for various uses, such as training, operational planning, and emergency response coordination.
In Pursuit of BRST Symmetry and Observables in 4D Topological Gauge-Affine Gravity
Authors: Belarbi Oussama Abdelghafour , Meziane Ahmed
Published: May 2024

The realization of a BRST cohomology of the 4D topological gauge-affine gravity is established in terms of a superconnection formalism. The identification of fields in the quantized theory occurs directly as is usual in terms of superconnection and its supercurvature components with the double covering of the general affine group GA¯(4,R). Then, by means of an appropriate decomposition of the metalinear double-covering group SL¯(5,R) with respect to the general linear double-covering group GL¯(4,R), one can easily obtain the enlargements of the fields while remaining consistent with the BRST algebra. This leads to the descent equations, allowing us to build the observables of the theory by means of the BRST algebra constructed using a sa¯(5,R) algebra-valued superconnection. In particular, we discuss the construction of topological invariants with torsion.
Second Hankel Determinant and Fekete–Szegö Problem for a New Class of Bi-Univalent Functions Involving Euler Polynomials
Authors: Gebur Semh Kadhim , Atshan Waggas Galib
Published: May 2024

Orthogonal polynomials have been widely employed by renowned authors within the context of geometric function theory. This study is driven by prior research and aims to address the —Fekete-Szegö problem. Additionally, we provide bound estimates for the coefficients and an upper bound estimate for the second Hankel determinant for functions belonging to the category of analytical and bi-univalent functions. This investigation incorporates the utilization of Euler polynomials.
Product Quality Anomaly Recognition and Diagnosis Based on DRSN-SVM-SHAP
Authors: Liu Yong , Wang Zhuo , Zhang Dong , Yang Mingshun , Gao Xinqin , Ba Li
Published: May 2024

Conventional quality control methodologies are inadequate for fully elucidating the aberrant patterns of product quality. A multitude of factors influence product quality, yet the limited number of controlled quality characteristics is insufficient for accurately diagnosing quality abnormalities. Additionally, there are asymmetries in data collection, data pre-processing, and model interpretation. In this context, a quality anomaly recognition and diagnosis model for the complex product manufacturing process is constructed based on a deep residual network, support vector machine (SVM), and Shapley additive explanation (SHAP). Given the numerous complex product quality characteristic indexes and unpredictable accidental factors in the production process, it is necessary to mine the deep relationship between quality characteristic data and quality state. This mining is achieved by utilizing the strong feature extraction ability of the deep residual shrinkage network (DRSN) through self-learning. The symmetry of the data within the model has also been taken into account to ensure a more balanced and comprehensive analysis. The excellent binary classification ability of the support vector machine is combined with the DRSN to identify the quality anomaly state. The SHAP interpretable model is employed to diagnose the quality anomaly problem of a single product and to identify and diagnose quality anomalies in the manufacturing process of complex products. The effectiveness of the model is validated through case analysis. The accuracy of the DRSN-SVM quality anomaly recognition model reaches 99%, as demonstrated by example analysis, and the model exhibits faster convergence and significantly higher accuracy compared with the naive Bayesian model classification and support vector machine classification models.
Optimizing Variance Estimation in Stratified Random Sampling through a Log-Type Estimator for Finite Populations
Authors: Triveni Gullinkala Ramya Venkata , Danish Faizan , Albalawi Olayan
Published: May 2024

In this research, a logarithmic-type estimator was formulated for estimating the finite population variance in stratified random sampling. By ensuring that the sampling process is symmetrically conducted across the population, biases can be minimized, and the sample is more likely to be representative of the population as a whole. We conducted a comprehensive numerical study and simulation study to evaluate the performance of the proposed estimator. The mean squared error values were computed for both our proposed estimator and several existing ones, including the standard unbiased variance estimator, difference-type estimator, and other considered estimators. The results of the numerical study and simulation study demonstrated that the proposed log-type estimator outperforms the other considered estimators in terms of MSE and percentage relative efficiency. Graphical representations of the results are also provided to illustrate the efficiency of the proposed estimator. Based on the findings of this study, we conclude that the proposed log-type estimator is a valuable addition to the existing literature on variance estimation in stratified random sampling. It provides a more efficient and accurate estimate of the population variance, which can be beneficial for various statistical applications.
Experimental Investigations on the Cavitation Bubble Dynamics near the Boundary of a Narrow Gap
Authors: Wang Zhifeng , Yang Yihao , Guo Zitong , Hu Qingyi , Wang Xiaoyu , Zhang Yuning , Li Jingtao , Zhang Yuning
Published: May 2024

Cavitation bubbles near narrow gaps widely exist within microfluidic control devices. In the present paper, a laser-induced cavitation bubble is arranged in a narrow gap composed of two parallel plates. The inception position of the bubble is set to be at the same distance from the two plates so that the dynamic behaviors of the bubble are symmetrical. The collapse and rebound dynamics of the bubble near the boundary of a narrow gap are investigated through high-speed photography. The bubble behaviors (e.g., shape deformation, translational movement, and jet characteristics) are analyzed while considering the influence of the dimensionless distance between the bubble and the boundary and the dimensionless gap width. The principal findings include the following: (1) When the dimensionless distance is small, a violent jet towards the gap is generated during the bubble collapse stage, along with a weak counter-jet towards the boundary appearing during the rebound stage. (2) As the dimensionless distance increases, the translational distance of the bubble during the collapse stage initially decreases, then increases, and finally decreases to zero. (3) Within the parameter range considered in this paper, the dimensionless width mainly affects the expansion degree and movement direction of the bubble cloud during its rebound and subsequent stages. The above research findings can provide experimental support for bubble-driven flow control, pumping, and liquid mixing in microfluidic channels.
A Novel Radar Cross-Section Calculation Method Based on the Combination of the Spectral Element Method and the Integral Method
Authors: Zhao Hongyu , Chen Jingying , Zhuang Mingwei , Yang Xiaofan , Zhuo Jianliang
Published: May 2024

This article proposes a novel method for calculating radar cross-sections (RCSs) that combines the spectral element method and the integral method, allowing for RCS calculations at any position in a free space or a half-space. This approach replaces the field source with an incident field using the scattered field equation of the spectral element method, enabling the arbitrary placement of the field source without being limited by the computational domain. By applying the superposition theorem and the volume equivalence principle, the scattered field of the objects at any position is obtained through integral equations, eliminating limitations on the computation points imposed by the computational domain. Based on Green’s function’s important role throughout the calculation process and its symmetry properties, the RCS calculation of symmetric models will be more advantageous. Finally, several examples, including symmetry models, are provided to validate both the feasibility and accuracy of this proposed method.
Research on Mathematical Modeling of Critical Impact Force and Rollover Velocity of Coach Tripped Rollover Based on Numerical Analysis Method
Authors: Wu Xinye , Wang Zhiwei , Chen Shenghui
Published: May 2024

Although the probability of a rollover accident is lower than that of other forms of collision, rollover is a serious accident that can break the symmetry of the vehicle and cause serious loss of life and property. There are many factors affecting rollovers, such as the environment, the vehicle, and the driving control. A coach comprises a complex dynamic system; as such, the accuracy and rationality of the used mathematical model are decisive in the study of coach rollover warning and control. By analogy with the modeling method of an automobile collision accident, the general process of a coach rollover accident is analyzed in this study in combination with the contact form and freedom of motion characteristic of the coach body and external environment. According to the principle of conservation of energy, the mathematical models of critical rollover impact force in a collision between vehicles and obstacles and in a collision between two vehicles are established, allowing for analysis of the relationships between the critical tripped rollover impact forces required for a 90° rollover and the continuous action time and collision point height. During the collision between the vehicle and the obstacle, the occurrence of a vehicle rollover is related not only to the impact force in the collision process but also to the collision duration time. Even if the impact force is relatively small, the collision lasts long enough that a second collision may occur until the vehicle rolls over. In the process of a two-vehicle collision, the critical rollover impact force is not only related to the vehicle mass but also to the vehicle wheelbase and the height of the collision point. Based on the law of conservation of momentum, the mathematic models of 90-degree rollover and 180-degree rollover are established, and the critical rollover velocities are calculated. The purpose of this study is to provide reference and guidance for the research methods of vehicle rollover stability and anti-rollover control in the intelligent vehicle era.
The Promises and Challenges toward Mass Customization of Healthcare Services
Authors: Ma Shuang , Zhang Xiaojin , Chen Songlin
Published: May 2024

The healthcare industry is confronted with the challenge to offer an increasing variety of healthcare services while in the meantime controlling rapidly increasing healthcare costs. Mass customization has been proven to be an effective strategy to fulfill customers’ individual specific needs with high efficiency and low cost in the manufacturing industry. This paper investigates the theoretical feasibility and practical applicability of adopting mass customization as a conceptual framework for designing a healthcare service delivery system. The nature of healthcare delivery systems and their evolution are discussed relative to those of manufacturing systems. Recent research in personalized medicine, consumer-driven healthcare, consumer healthcare informatics, and integrated healthcare delivery is reviewed as enabling technologies towards mass customization of healthcare services. By synthesizing these scattered efforts in different streams of literature, this paper concludes that mass customization can contribute to the redesign of healthcare service systems, and delineates a roadmap for future research.
Labor Mobility Networks and Green Total Factor Productivity
Authors: He Jiajia , Li Zhenghui
Published: May 2024

Population migration continues to reshape the spatial pattern of China’s population and regional economic development. During this internal migration process, production and consumption patterns often change, ultimately leading to changes in green total factor productivity. This paper, based on the Chinese population census data and 1% sampling survey data from 2005 to 2015, utilizes social network analysis methods to measure the labor mobility network indicators of 284 prefecture-level cities. Further, this paper analyzes the impact and mechanisms of regional network status on green total factor productivity using a panel fixed effects model. We find that as network density increases, the interpersonal connections between regions become closer, and the network exhibits a clear pattern of “concentrated inflows” and “dispersed outflows”, with the trend of forming strong alliances becoming increasingly apparent. Regions positioned centrally either in terms of network in-degree or out-degree exhibit higher green total factor productivity. Among these, the labor mobility network plays a crucial role in enhancing green total factor productivity through the channel of technology diffusion effects, which improve investment efficiency via knowledge exchange and material capital accumulation. The promotive effect of labor network status on green total factor productivity is more pronounced in the eastern regions, where talent quality is higher, and in areas with fewer restrictions from the household registration system.
Minimization of Costs with Picking and Storage Operations
Authors: Lopes Cristina , Oliveira Ana
Published: May 2024

This work presents two mixed-integer programming models that intend to minimize the costs of the picking and storage operation through better planning and organization of the places occupied by the products in the warehouse. A large customer that stores frozen goods in a Portuguese cold chain logistics company was selected for the analysis of the allocation of the products in the warehouse and of the corresponding outbound movements. Data with 8525 movements that occurred during 2021 were collected for 228 different product references. For this case study, the products that had a picking place in the initial scenario now have pallets with all the goods in the reserve area, and vice versa. The mathematical models were permitted to obtain savings for the logistics operator costs of around 30.9%. The proposed models can, in the future, be applied in other warehouse scenarios to companies in completely different sectors of activity.
Impact of Newly Measured Nuclear Reaction Rates on 26Al Ejected Yields from Massive Stars
Authors: Battino Umberto , Roberti Lorenzo , Lawson Thomas V. , Laird Alison M. , Todd Lewis
Published: May 2024

Over the last three years, the rates of all the main nuclear reactions involving the destruction and production of 26Al in stars (26Al(n, p)26Mg, 26Al(n, α)23Na, 26Al(p, γ)27Si and 25Mg(p, γ)26Al) have been re-evaluated thanks to new high-precision experimental measurements of their crosssections at energies of astrophysical interest, considerably reducing the uncertainties in the nuclear physics affecting their nucleosynthesis. We computed the nucleosynthetic yields ejected by the explosion of a high-mass star (20 M⊙, Z = 0.0134) using the FRANEC stellar code, considering two explosion energies, 1.2 × 1051 erg and 3 × 1051 erg. We quantify the change in the ejected amount of 26Al and other key species that is predicted when the new rate selection is adopted instead of the reaction rates from the STARLIB nuclear library. Additionally, the ratio of our ejected yields of 26Al to those of 14 other short-lived radionuclides (36Cl, 41Ca, 53Mn, 60Fe, 92Nb, 97Tc, 98Tc, 107Pd, 126Sn, 129I, 36Cs, 146Sm, 182Hf, 205Pb) are compared to early solar system isotopic ratios, inferred from meteorite measurements. The total ejected 26Al yields vary by a factor of ~3 when adopting the new rates or the STARLIB rates. Additionally, the new nuclear reaction rates also impact the predicted abundances of short-lived radionuclides in the early solar system relative to 26Al. However, it is not possible to reproduce all the short-lived radionuclide isotopic ratios with our massive star model alone, unless a second stellar source could be invoked, which must have been active in polluting the pristine solar nebula at a similar time of a core-collapse supernova.
Antibody Response after Homologous and Heterologous Prime–Boost COVID-19 Vaccination in a Bangladeshi Residential University Cohort
Authors: Adnan Nihad , Haq Md. Ahsanul , Akter Salma , Sajal S. M. Shafiul Alam , Islam Md. Fokhrul , Mou Taslin Jahan , Jamiruddin Mohd. Raeed , Jubyda Fatema Tuz , Islam Md. Salequl , Tuli Jamsheda Ferdous , Liza Syeda Moriam , Hossain Sharif , Islam Zinia , Ahmed Sohel , Khandker Shahad Saif , Hossain Rubel , Ahmed Md. Firoz , Khondoker Mohib Ullah , Azmuda Nafisa , Parvez Md. Anowar Khasru
Published: May 2024

COVID-19 vaccination strategies, including heterologous prime–boost regimens and additional booster doses, aim to optimize immune responses. However, seroepidemiological studies on immune responses to different COVID-19 vaccine types and schedules remain limited. This study investigated antibody levels following homologous and heterologous prime-and-boost COVID-19 vaccination in Bangladesh. In a cohort of 606 participants who received first/second/booster doses of vaccines (AstraZeneca, Moderna, Pfizer-BioNTech, and Sinopharm), anti-spike IgG and anti-nucleocapsid IgG levels were measured. Antibody titer variations with respect to age, gender, intervals between doses, and prior infection status were analyzed. mRNA vaccines elicited the highest antibody levels after homologous and heterologous boosting. The AstraZeneca booster resulted in a sharp titer decline rate of ~0.04 units per day. Second or booster vaccine doses significantly increased antibody levels, especially in males (p < 0.05). Older age correlated with higher titers, likely reflecting previous infection, which was further confirmed by the elevation of anti-nucleocapsid IgG levels. About 95.5% of non-Sinopharm recipients were anti-nucleocapsid IgG positive, suggesting prior exposure exceeding self-reported infections (12.5%). mRNA and heterologous COVID-19 boosting enhances humoral immunity over homologous prime–boost vector/inactivated vaccination. However, waning immunity merits further investigation across vaccine platforms.
Tuberculosis Vaccines and T Cell Immune Memory
Authors: Li Fei , Dang Wenrui , Du Yunjie , Xu Xiaonan , He Pu , Zhou Yuhe , Zhu Bingdong
Published: May 2024

Tuberculosis (TB) remains a major infectious disease partly due to the lack of an effective vaccine. Therefore, developing new and more effective TB vaccines is crucial for controlling TB. Mycobacterium tuberculosis (M. tuberculosis) usually parasitizes in macrophages; therefore, cell-mediated immunity plays an important role. The maintenance of memory T cells following M. tuberculosis infection or vaccination is a hallmark of immune protection. This review analyzes the development of memory T cells during M. tuberculosis infection and vaccine immunization, especially on immune memory induced by BCG and subunit vaccines. Furthermore, the factors affecting the development of memory T cells are discussed in detail. The understanding of the development of memory T cells should contribute to designing more effective TB vaccines and optimizing vaccination strategies.
Targeting Plasmodium Life Cycle with Novel Parasite Ligands as Vaccine Antigens
Authors: Khan Shan , Patel Manas Paresh , Patni Aleem Damji , Cha Sung-Jae
Published: May 2024

The WHO reported an estimated 249 million malaria cases and 608,000 malaria deaths in 85 countries in 2022. A total of 94% of malaria deaths occurred in Africa, 80% of which were children under 5. In other words, one child dies every minute from malaria. The RTS,S/AS01 malaria vaccine, which uses the Plasmodium falciparum circumsporozoite protein (CSP) to target sporozoite infection of the liver, achieved modest efficacy. The Malaria Vaccine Implementation Program (MVIP), coordinated by the WHO and completed at the end of 2023, found that immunization reduced mortality by only 13%. To further reduce malaria death, the development of a more effective malaria vaccine is a high priority. Three malaria vaccine targets being considered are the sporozoite liver infection (pre-erythrocytic stage), the merozoite red blood cell infection (asexual erythrocytic stage), and the gamete/zygote mosquito infection (sexual/transmission stage). These targets involve specific ligand-receptor interactions. However, most current malaria vaccine candidates that target two major parasite population bottlenecks, liver infection, and mosquito midgut infection, do not focus on such parasite ligands. Here, we evaluate the potential of newly identified parasite ligands with a phage peptide-display technique as novel malaria vaccine antigens.
Vaccination and Control Methods of West Nile Virus Infection in Equids and Humans
Authors: Cendejas Parker M. , Goodman Alan G.
Published: May 2024

West Nile virus (WNV) is capable of causing severe neurologic disease in both humans and equines, making it a disease of importance in both human medicine and veterinary medicine. No targeted treatments exist for WNV infection in either humans or equines. Infection is treated symptomatically through management of symptoms like fever and seizures. As treatment for WNV is purely supportive, the response to WNV has focused primarily on methods of disease prevention. To this end, research efforts have yielded several effective vaccines for equine use as well as numerous conventional mosquito control techniques. Even with the implementation of these techniques, disease caused by WNV remains a concern since no human vaccine exists. Due to the lack of a human vaccine, novel preventative strategies are under active research and development. Of these strategies, some of the most conceptually promising are techniques using genetically modified mosquitoes, addressing the disease at the vector level with minimal ecological side effects. Taken together, the use of combined, synergistic methods, such as physical barriers, transgenic mosquitoes, and immunological targets, will be the best way to prevent WNV disease.
Raising Epidemiological Awareness: Assessment of Measles/MMR Susceptibility in Highly Vaccinated Clusters within the Hungarian and Croatian Population—A Sero-Surveillance Analysis
Authors: Szinger Dávid , Berki Timea , Drenjančević Ines , Samardzic Senka , Zelić Marija , Sikora Magdalena , Požgain Arlen , Markovics Ákos , Farkas Nelli , Németh Péter , Böröcz Katalin
Published: May 2024

Perceptions of the complete eradication of vaccine-preventable diseases such as measles, mumps, and rubella (MMR) may foster complacency and compromise vaccination efforts. Decreased measles vaccination rates during the COVID-19 pandemic have heightened the risk of outbreaks, even in adequately vaccinated populations. To address this, we have aligned with ECDC recommendations, leveraging previous cross-border sero-epidemiological assessments between Pécs, Hungary, and Osijek, Croatia, to identify latent risk groups and uncover potential parallels between our nations. Testing 2680 Hungarian and 1764 Croatian serum samples for anti-MMR IgG via ELISAs revealed anti-measles seropositivity ratios below expectations in Croatian cohorts aged ~20–30 (75.7%), ~30–40 (77.5%) and ~40–50 years (73.3%). Similarly, Hungarian samples also showed suboptimal seropositivity ratios in the ~30–40 (80.9%) and ~40–50 (87.3%) age groups. Considering mumps- and rubella-associated seropositivity trends, in both examined populations, individuals aged ~30–50 years exhibited the highest vulnerability. Additionally, we noted congruent seropositivity trends across both countries, despite distinct immunization and epidemiological contexts. Therefore, we propose expanding research to encompass the intricate dynamics of vaccination, including waning long-term immunity. This understanding could facilitate targeted interventions and bolster public awareness. Our findings underscore persistent challenges in attaining robust immunity against measles despite vaccination endeavors.
Virological Traits of the SARS-CoV-2 BA.2.87.1 Lineage
Authors: Zhang Lu , Dopfer-Jablonka Alexandra , Nehlmeier Inga , Kempf Amy , Graichen Luise , Calderón Hampel Noemí , Cossmann Anne , Stankov Metodi V. , Morillas Ramos Gema , Schulz Sebastian R. , Jäck Hans-Martin , Behrens Georg M. N. , Pöhlmann Stefan , Hoffmann Markus
Published: May 2024

Transmissibility and immune evasion of the recently emerged, highly mutated SARS-CoV-2 BA.2.87.1 are unknown. Here, we report that BA.2.87.1 efficiently enters human cells but is more sensitive to antibody-mediated neutralization than the currently dominating JN.1 variant. Acquisition of adaptive mutations might thus be needed for efficient spread in the population.
Modeling of Biofoam Destabilization by Biodefoamers in Poultry Slaughterhouse Wastewater Treatment Activated Sludge
Authors: Dlangamandla Cynthia , Mpongwana Ncumisa , Ntwampe Seteno K. O. , Basitere Moses , Chidi Boredi S.
Published: May 2024

Biofoam formation in wastewater treatment is a challenge globally. Previously, we successfully proposed the use of biodefoamers instead of synthetic defoamers for environmental protection. In this study, we report on biodefoamation modeling using activated sludge organisms. Overall, the rate law model was determined to adequately describe foam drainage including collapse while applying biodefoamers. The target industry is the poultry processing industry whereby foam formation during wastewater treatment is an ongoing challenge.
Programa de Coaching Empresarial para Mejorar el Desempeño Laboral en el Hostal San José Potosí
Authors: Guizada Huanca Jadiel
Published: May 2024

El coaching empresarial juega un papel crucial en la retención del talento al promover cambios de conductas, emociones y conocimientos en las personas y equipos. El objetivo de esta investigación fue mejorar el desempeño laboral en el Hostal San José Potosí a través de un Programa de Coaching Empresarial, basado en el modelo GROW. La investigación aplicada utilizó un diseño pretest-postest, con diagnóstico inicial, aplicación del programa y evaluación posterior. Los resultados evidenciaron que la empresa priorizó la infraestructura y los servicios, pero descuidó el capital humano, provocando desmotivación e ineficiencia. La implementación del programa de coaching tuvo un impacto significativo, empoderando al talento y fortaleciendo las habilidades blandas, lo que aumentó el compromiso y el sentido de pertenencia de los trabajadores, mejorando su motivación y desempeño. Se recomienda al Hostal San José Potosí integrar el coaching empresarial en su filosofía corporativa.
Las 5E del Endomarketing para reducir la rotación de personal en las Pymes
Authors: López Damián Jesús Alberto , Yee Villanueva Elizabeth
Published: May 2024

El Endomarketing surge entonces como una estrategia que busca fortalecer las relaciones al interior de la organización, involucrando a los colaboradores en la construcción de la cultura organizacional. Con el objetivo de realizar una propuesta integradora del endomarketing, identificando cinco dimensiones consideradas muy importantes con beneficios notables para las organizaciones. El estudio constituye una investigación básica, en la que se realizó una revisión de literatura sobre sobre las estrategias de las 5E del endomarketing 1963 hasta el 2023. La investigación es cualitativa y se utilizó el método descriptivo - explicativo. Para la recolección de información se empleó como instrumento la ficha de análisis documental, la cual registró la información recolectada de los recursos promocionales de la página de empresas, google scholar, bases de datos como SCIELO, SCOPUS, redes sociales como Facebook e Instagram, de la plataforma de YouTube, entre otros medios digitales. Como resultado, se presenta la propuesta que incluye cinco elementos esenciales para la implementación del endomarketing con el propósito de fortalecer aspectos que no se han considerado en las organizaciones. Las 5E del endomarketing que incluye los elementos externos, elementos internos, elaboración de estrategias, ejecución de estas y evaluación de los resultados. Las organizaciones deben atender y considerar los elementos exógenos que tienen los colaboradores, debido a que inciden y son determinantes en la rotación de personal; Esta propuesta es aplicable en medianas y pequeñas empresas porque todos los componentes que conforman las 5E son características y condiciones que se presentan en ellas, sin embargo, puede ser adaptado a diferentes organizaciones.
Determining PolyCystic Ovarian Syndrome Severity from Reddit Posts using Topic Modelling and Association Rule Mining
Authors: Selvaraj Santhi , Sundaradhas Selva Nidhyananthan
Published: May 2024

Nowadays social media plays a vital role in various real-time applications, especially in healthcare applications. PolyCystic Ovarian Syndrome (PCOS) is a condition that affects females between the ages of 15 and 35 who are of reproductive potential. The symptoms of PCOS are hormonal issues, irregular periods, weight gain, follicles, infertility, excessive hair growth in the skin, hair loss, acne, pimples, dark scars, and depression. Most of the earlier researchers analyzed the PCOS based on clinical text and health records using a machine learning approach. The main motivation of this proposed work is to predict the upcoming PCOS symptoms based on current symptoms and find the severity of the PCOS from Reddit users. This is done by collecting head symptoms from Gynecologists, gathering present symptoms from Reddit users, collecting unstructured data is pre-processed and PCOS sub symptoms are extracted using Bag of Words. The sub symptoms are mapped into head symptoms using Latent Dirichlet Allocation (LDA) for dimension reduction. The major issue in that approach is a single user has experienced the same type of symptom multiple times. This issue is solved by implementing a novel method called Symptom Segmentation and grouping Labeled Latent Dirichlet Allocation (SSG_LLDA) is designed to reduce the dimensionality and map the social media users sub symptoms into head symptoms. Association Rule Mining (ARM) with Apriori is employed to produce the frequent symptoms, and effective rule sets, and form the distinctive symptom patterns. Among several mini-mum support and confidence metrics, 0.02 and 0.1 delivers the best rule sets and symptom patterns. Based on rulesets of symptom patterns and combinations, the severity of PCOS is determined for Reddit users. The novelty of this work is the construction of PCOS symptom patterns from topic modelling results instead of original data so the dimensionality of the features is reduced and more scalable
Effect of Convergence Plant Selection of Wildflower Mixtures in China on the Plant Invasion
Authors: Hu Wenhao , Huang Yangchao , Duan Yun , He Lan , Wu Wei , Kong Yimiao , Huang Lu , Zhang Haijiang , Xu Wenhui
Published: May 2024

The rapid development of urbanization and urban land-use intensification have substantially reduced biodiversity and ecosystem services. Wildflower mixtures can improve regional biodiversity and habitat heterogeneity by establishing flower-rich habitats and providing multiple ecosystem services, which were considered one of the most favorable landscape ecological restoration technologies approaches. How to design wildflower mixtures to achieve optimal eco-efficiency is currently unclear. In China, wildflower mixture is one of landscape architecture’s most popular methods for establishing herbaceous vegetation. Currently, there is a notable lack of systematic research regarding species selection, and concerns have been raised about the design approach that introduces convergent species, which may potentially become invasive. This research integrated a wildflower mixture design database currently published in China and discovered community composition and construction methods. Based on this, we compared the species composition of wildflower mixtures in China and assessed the potential invasive species. Additionally, we attempted to explore the distribution over time and space, their potential invasion risk, and the main factors influencing species selection through modeling approaches. The results highlighted that species selection of mixture converged with different spatiotemporal attributes and design intentions, despite designed wildflower mixtures in China having gradually increased in recent years. A large number of species from North America and Europe have been causing an increase in potential invasion annually. Furthermore, the research confirmed that the convergence contributes to the homogenization of urban landscape vegetation communities, which leads to biological invasion from the design level, and revealed the possibility that ineffective ecological restoration techniques may cause adverse environmental impacts.
Identifying Risk Indicators of Cardiovascular Disease in Fasa Cohort Study (FACS): An Application of Generalized Linear Mixed-Model Tree
Authors: Asadi Fariba , Homayounfar Reza , Farjam Mojtaba , Mehrali Yaser , Masaebi Fatemeh , Zayeri Farid
Published: May 2024

Background: Today, cardiovascular disease (CVD) is the most important cause of death around the world. In this study, our main aim was to predict CVD using some of the most important indicators of this disease and present a tree-based statistical framework for detecting CVD patients according to these indicators. Methods: We used data from the baseline phase of the Fasa Cohort Study (FACS). The outcome variable was the presence of CVD. The ordinary Tree and generalized linear mixed models (GLMM) were fitted to the data and their predictive power for detecting CVD was compared with the obtained results from the GLMM tree. Statistical analysis was performed using the RStudio software. Results: Data of 9499 participants aged 35‒70 years were analyzed. The results of the multivariable mixed-effects logistic regression model revealed that participants’ age, total cholesterol, marital status, smoking status, glucose, history of cardiac disease or myocardial infarction (MI) in first- and second-degree relatives, and presence of other diseases (like hypertension, depression, chronic headaches, and thyroid disease) were significantly related to the presence of CVD (P<0.05). Fitting the ordinary tree, GLMM, and GLMM tree resulted in area under the curve (AUC) values of 0.58 (0.56, 0.61), 0.81 (0.77, 0.84), and 0.80 (0.76, 0.83), respectively, among the study population. In addition, the tree model had the best specificity at 81% but the lowest sensitivity at 65% compared to the other models. Conclusion: Given the superior performance of the GLMM tree compared with the standard tree and the lack of significant difference with the GLMM, using this model is suggested due to its simpler interpretation and fewer assumptions. Using updated statistical models for more accurate CVD prediction can result in more precise frameworks to aid in proactive patient detection planning.
Effectiveness of Applying Green Heart, a Smartphone-Based Self-management Intervention to Control Smoking: A Randomized Clinical Trial
Authors: Ghavami Mojgan , Abdshah Alireza , Ahmadi Ayat , Akbarzadeh Diba , Mofidi Ali , Ashoorkhani Mahnaz , Sadeghian Saeed
Published: May 2024

Background: Cardiovascular diseases (CVDs) pose a significant global health concern and are the most common cause of death and disability, necessitating preventive interventions targeting modifiable risk factors. Recently, mobile-health technology has been developed to improve the delivery of cardiovascular prevention by risk factor modification. The "Green Heart" mobile application (app) was designed to aid in risk factor control among coronary artery disease (CAD) patients. Methods: This parallel-group, single-blinded randomized controlled trial enrolled 1590 CAD patients, including 668 current smokers, randomly assigned to control (paper-based education) and intervention (application-based) groups. The app encompassed three modules targeting smoking cessation, dyslipidemia control, and blood pressure management. This study evaluated the impact of the smoking cessation module on behavioral change among current smokers. Green Heart assesses nicotine dependence, offering personalized quit plans, educational content, motivational messages, and automated progress tracking. The odds of smoking behavior changes during the 24-week follow-up underwent assessment. Results: The intention-to-treat analysis highlighted significantly elevated rates of smoking cessation and reductions in the intervention group versus the control group. Adherence to the app (per-treatment analysis) also demonstrated significantly more favorable smoking behavior changes among the application users. Logistic regression emphasized higher odds of quitting and reduction in smoking in the application group, showing an odds ratio of 2.14 (95% CI: 1.16–3.97) compared to those not using the app (P=0.015). Conclusion: Our results confirmed that complete adherence to the app for at least 24 weeks was linked to alterations in cigarette smoking behavior among CAD patients. Trial Registration Number: IRCT20221016056204N1
Pathological Assessment of the Appendix in Appendectomies Performed in Children
Authors: Javanmard Farzaneh , Hasanzadegan Sadegh Yasin
Published: May 2024

Background: Acute appendicitis is known as the most common diagnosis of acute abdomen leading to surgery. Therefore, timely diagnosis is of special importance. This study was conducted with the aim of pathological assessment of the appendix in appendectomies performed in children to determine the rate of negative appendectomies and the predictors of negative appendectomy and to evaluate the paraclinical tools used in the diagnosis of acute appendicitis. Methods: This is a cross-sectional descriptive study. All children who underwent appendectomy at Shahid Motahari Hospital in Urmia from March 2021 to March 2022 were examined. The required data including demographic, paraclinical, and final pathology characteristics were collected and recorded. The investigated cases were classified into positive and negative appendectomy categories for comparison. Results: Among 234 pathology samples of the appendix, 22 cases were related to accidental appendectomy. In addition, 11.3% of cases were negative appendectomy and 88.7% were positive appendectomy. The age range of 8 to 14 years and male gender were associated with a lower negative appendectomy rate (both P<0.001). Inflammatory (49.5%) and gangrenous appendicitis (30.2%) were the most commonly reported histopathologies. Sonography had a sensitivity of 84%, a specificity of 79%, and an overall diagnostic accuracy of 83%. Conclusion: A relatively significant number of accidental and negative appendectomies are performed. More careful investigation and the use of expectant and medical treatment instead of surgery, especially in females and young children, can be effective in improving diagnostic accuracy and preventing negative appendectomies.
Analysis of the development of the carbon oxidation reaction of low-carbon steel in a bucket under vacuum
Authors: O.H. Velichko , V.Yu. Kamkin , K.V. Rudko , L.V. Kamkina
Published: May 2024

The object of research is the process of vacuuming steel in a ladle. The purpose of the study is to determine the degree of approach of degassing reactions to equilibrium and removal rates by articles. Research methods - theoretical studies are based on the basic provisions of physical chemistry and the theory of metallurgical processes, thermodynamic calculations of the non-equilibrium reactions of degassing. Scientific novelty - in vacuum degassing processes, the approximation of the corresponding reactions to equilibrium plays a significant role, in industrial vacuum installations, the equilibrium between carbon and oxygen dissolved in steel is not achieved due to ex-tremely small concentrations of interacting substances, the speed of the chemical reaction decreases so much that it does not allow for processing time to even approach the state of thermodynamic equilibrium. Practical significance - to ensure a high degree of implementation of the deoxidizing ability of carbon in vacuum conditions, it is neces-sary to: apply the main lining of steel pouring ladles; maintain a high basicity of slag and a minimum content of iron oxides in it; mix the melt in the ladle with an inert gas to facilitate the conditions for the nucleation of carbon oxidation reaction products.
Implementation of satelite image classification using PyTorch
Authors: M. Mishchenko , Vik. Hnatushenko , Anastasiia-Dzhei Sinher
Published: May 2024

This article presents a practical implementation of the satellite image classification task using the PyTorch deep learning library. The aim of the work is to develop a neural network model capable of classifying satellite images into four classes: water, sands, clouds, and greenery. The model is trained using the pre-trained ResNet architecture. The proposed approach allows for automatic classification of satellite images, fa-cilitating the analysis of large amounts of data, and has been tested on Sentinel-2 satellite images acquired from March to August 2023 for parts of Kherson and Mykolaiv regions, Ukraine, and achieved an average accuracy of 95%. The presented research demonstrates the practical use of modern deep learning methods, in particular the PyTorch library, to solve actual problems of satellite image analysis and classification.
DESIGN OF A CONTROL SYSTEM WITH A PREDICTIVE MODEL FOR A TWO-DRIVE MANIPULATOR WITH A PARALLEL STRUCTURE
Authors: A. Rudakova , Y. Lebedenko , H. Rudakova , D. Nilova
Published: May 2024

This work intends to contribute to the corpus of knowledge on parallel manipulators and their control by making the most use of Model Predictive Control. We aim to investigate parallel manipulator kinematics, dynamics, and control strategies in detail in order to open up opportunities for enhanced performance, flexibility, and precision in these robotic systems.
Analisis Alokasi Waktu Terhadap Tingkat Pendapatan Petani Padi Yang Menggunakan Mekanisasi Pertanian di Desa Sugihwaras Kecamatan Wonomulyo Kabupaten Polewali Mandar
Authors: Asri Asri , Kusmiah Nurhaya , Karim Harli A
Published: May 2024

Sektor pertanian merupakan proses pembangunan produksi pertanian untuk meningkatkan usaha pertanian utuk dapat meningkatkan tingkat pendapatan serta produktuvitas. HOK atau Hari orang kerja adalah satuan tenaga kerja yang digunakan biasanya dalam menghitung analisis usahatani atau farming. Penelitian ini bertujuan untuk mengetahui jumlah waktu yang dialokasikan petani padi sawah dalam menjalankan usahataninya di Desa Sugihwaras Kecamatan Wonomulyo Kabupaten Polewali Mandar. Analisis data yang digunakan dalam penelitian ini adalah dengan analisis kuantitatif, deskriptif, dan rumus HOK. Jumlah HOK yang digunakan oleh petani dari pindah tanam sampai dengan panen adalah berbeda-beda dari 3 responden, yaitu responden pertama dengan luasan 1 Ha dengan jumlah HOK = 450 Jam, responden kedua dengan luasan lahan 1,2 Ha dengan jumlah HOK = 265 Jam, dan responden yang ketiga dena luasan 1,3 Ha dengan jumlah HOK = 761,25 Jam.