Modeling Analysis Research Articles

Business continuity management in the sharing economy: Insights from Airbnb online reviews

The aim of this paper is to demonstrate how text mining of online reviews can support business continuity management in the sharing economy during market turbulence. We use topic modelling and sentiment analysis of Airbnb online reviews to identify specific areas where short-term rental hosts can harness the power of the sharing-economy business model to bounce back from market disruption. The dataset comprises 894,686 online Airbnb reviews from the pre- and post-Covid periods. We approach the pandemic as a paradigm example of a high-impact, external market shock and infer insights and recommendations from the dataset that are relevant to the general understanding of business continuity management in the short-term rental, peer-to-peer sharing economy.

Co-creation as open innovation and its impact on environmental performance: Comparative insights from university and vocational students

This study addresses the urgent need for innovative solutions to environmental issues by focusing on youth development within educational institutions, which play a crucial role in fostering environmentally conscious behaviors. Despite increasing awareness, there is a gap in understanding how educational settings can effectively promote sustainability through collaborative approaches, such as co-creation as an open innovation model and user engagement strategies. This research investigates the mediating role of co-creation between environmental knowledge and environmental performance, comparing university and vocational students. Data were collected from 678 respondents in Thailand and analyzed using structural equation modeling and multigroup analysis. The findings reveal that environmental knowledge positively influences environmental performance and co-creation activities for both groups, with a more significant mediating effect of co-creation among vocational students. This suggests that vocational students respond more effectively to practical, collaborative approaches to digital innovation in the environmental context. The study also highlights the relevance of the Information Deficit Model, which posits that individuals often do not engage in sustainable behaviors due to insufficient knowledge or information. These results demonstrate the critical role of educational institutions in enhancing sustainability practices by leveraging co-creation and environmental knowledge. The insights from this study are valuable for educators and policymakers seeking to develop user engagement strategies tailored to different student groups, ultimately improving environmental performance and fostering innovation in sustainability practices.

Exploring Public Emotions on Obesity During the COVID-19 Pandemic Using Sentiment Analysis and Topic Modeling: Cross-Sectional Study.

Obesity is a chronic, multifactorial, and relapsing disease, affecting people of all ages worldwide, and is directly related to multiple complications. Understanding public attitudes and perceptions toward obesity is essential for developing effective health policies, prevention strategies, and treatment approaches. This study investigated the sentiments of the general public, celebrities, and important organizations regarding obesity using social media data, specifically from Twitter (subsequently rebranded as X). The study analyzes a dataset of 53,414 tweets related to obesity posted on Twitter during the COVID-19 pandemic, from April 2019 to December 2022. Sentiment analysis was performed using the XLM-RoBERTa-base model, and topic modeling was conducted using the BERTopic library. The analysis revealed that tweets regarding obesity were predominantly negative. Spikes in Twitter activity correlated with significant political events, such as the exchange of obesity-related comments between US politicians and criticism of the United Kingdom's obesity campaign. Topic modeling identified 243 clusters representing various obesity-related topics, such as childhood obesity; the US President's obesity struggle; COVID-19 vaccinations; the UK government's obesity campaign; body shaming; racism and high obesity rates among Black American people; smoking, substance abuse, and alcohol consumption among people with obesity; environmental risk factors; and surgical treatments. Twitter serves as a valuable source for understanding obesity-related sentiments and attitudes among the public, celebrities, and influential organizations. Sentiments regarding obesity were predominantly negative. Negative portrayals of obesity by influential politicians and celebrities were shown to contribute to negative public sentiments, which can have adverse effects on public health. It is essential for public figures to be mindful of their impact on public opinion and the potential consequences of their statements.

State Analysis and Emergency Control of Planetary Rover with Faulty Drive Wheel

Wheel failure is one of the worst problems for a planetary rover working on Mars or the Moon, which may lead to the interruption of the exploration mission and even the loss of mobility. In this study, a driving test of a planetary rover prototype with a faulty drive wheel was conducted, and state analysis and dynamics modeling were carried out. The drag motion relationship between the faulty drive wheel and the normal wheels on the same suspension was established based on the targeted single wheel test (faulty wheel-soil bin). In order to maintain the subsequent basic detection capability of the planetary rover, an emergency control system is proposed that integrates the path planning strategy with faulty wheel priority and the motion control method of correcting heading and coordinating allocation. The experimental results and emergency strategies of this study on simulating Martian soil and terrain can provide researchers with ideas to solve such problems.

Certain aspects of the implementation of imputed insurance of environmental risks in the Russian Federation

Purpose: of this article is to justify the implementation of insurance of environmental risks in the Russian Federation in the form of a pilot project based on imputed insurance with the definition of the main conditions of insurance coverage.Methods: the presented work uses statistical and predictive methods and the integrated approach for processing data on natural, climatic and human activity risks. Correlation-regression analysis and actuarial modeling were used to determine the conditions for insuring environmental risks and calculate tariff rates.Results: the paper substantiates the possibility of carrying out insurance of environmental risks in the form of a pilot project using an imputed form of insurance. Approaches to the calculation of the main parameters of business civil liability insurance for causing environmental damage as a result of an accident within the framework of a pilot project are proposed, including the determination of the minimum and maximum non-aggregate insurance limit, the minimum number of insurance companies, and the calculation of tariff rates. Due to the lack of Russian statistics on insurance coverage of environmental risks, statistical data on global insurance catastrophic losses from natural events, climate risks and human actions, as well as judicial statistics on disputes over the application of environmental protection legislation, were used for the calculation. The regions of the Russian Federation were identified for the implementation of a pilot project of environmental risk insurance.Conclusions and Relevance: the implementation of a pilot project of environmental risk insurance in certain regions on the basis of imputed insurance will make it possible to assess the current and forecast level of environmental risks in the Russian Federation, the need for insurance and reinsurance protection, the possibility and necessity of state participation in covering environmental damage. Using insurance statistics, insurers will be able to develop adjustment factors that encourage enterprises to take preventive measures. Reflection in a special reporting section of the results of the participation of insurance companies in the insurance of environmental pollution risks will be considered as the implementation of ESG principles.

Gravity and magnetic study of the Xitle volcanic field, Basin of Mexico – Inferences on the pre-eruptive topography

Results of a gravity and magnetic study over a lava field in the southern Basin of Mexico are used to investigate on lava emplacement and pre-eruptive topography. The characteristics of lava flows depend on multiple factors, including the lava composition, effusion rate, rheology, fluid content and underlying terrain. The ∼2000 years old volcanic field, formed by seven flow units emplaced by the Xitle eruption, covers an extensive area >80 km2 characterized by topographic relief on the Ajusco volcano flank and surrounding plain. The study is conducted on the northern end of the volcanic field. The gravity and magnetic study is based on regional-residual separation, vertical and horizontal derivatives, reduced to the pole, analytical signal, spectral analysis and forward modeling. The regional gravity field shows two anomaly lows in the central sector, with the residual field showing trends of gravity highs. The residual magnetic anomaly is characterized by trends of magnetic highs associated to the lava field. Depths estimated from spectral analysis of gravity and magnetic anomalies show shallow sources at ∼22 m and ∼46 m, and deep sources at ∼469 m and ∼268 m, respectively. The underground sequence is modeled as a volcanoclastic succession of varying thickness. The first vertical derivatives, gradients and analytical signal enhance the anomalies associated to lava thickness variations. Joint gravity and magnetic analysis constraints the deep/shallow anomaly sources in the volcanic field and relations to pre-eruptive structure.

Tumor necrosis drives prognosis in osteosarcoma: No difference in chemotherapy response and survival between chondroblastic and osteoblastic osteosarcoma

IntroductionThe percentage of tumor necrosis is a crucial prognostic factor in osteosarcoma. Many studies adopt a 90 % cutoff based on osteoblastic osteosarcoma, but these findings are generalized to all conventional subtypes, including chondroblastic osteosarcoma. We sought to answer these questions: (1) Is tumor necrosis ≥90 % associated with better overall survival (OS) and disease-free survival (DFS) in osteoblastic and chondroblastic osteosarcoma? (2) Does the osteosarcoma subtype impact tumor necrosis? (3) Does the osteosarcoma subtype in “good” responders (tumor necrosis ≥90 %) affect OS and DFS?. Materials and methodsWe conducted a retrospective study of 156 patients with osteoblastic and chondroblastic osteosarcoma treated at our institution. All patients received a standardized chemotherapy protocol and underwent surgery with the goal of achieving negative margins (R0 resection). Propensity-score matching was performed to adjust for potential confounders. Kaplan-Meier survival analysis and Cox proportional hazards modeling were performed. ResultsPatients with osteoblastic osteosarcoma and tumor necrosis ≥90 % had higher 5- and 10-year OS and DFS compared to those with necrosis <90 %. In chondroblastic osteosarcoma, a trend towards higher OS and DFS was seen in patients with tumor necrosis ≥90 %; this, however, was not significant. Chondroblastic osteosarcoma was not a risk factor for either tumor necrosis <90 % (p = 0.89) or tumor necrosis <70 % (p = 0.57). Patients with osteoblastic or chondroblastic osteosarcoma that were deemed “good” responders (tumor necrosis ≥90 %) had similar OS and DFS at the 5- and 10-year marks. ConclusionConventional osteosarcoma subtype was not a risk factor for “poor” response. Survival outcomes (OS and DFS) were similar for osteoblastic and chondroblastic osteosarcoma with good response to chemotherapy.

Relationships among Dioxin-like Mitochondria Inhibitor Substances (MIS)-Mediated Mitochondria Dysfunction, Obesity, and Lung Function in a Korean Cohort.

Mitochondrial dysfunction is closely linked to obesity and diabetes, with declining lung function in aging increasing diabetes risk, potentially due to elevated serum levels of dioxin-like mitochondria inhibitor substances (MIS) from prolonged exposure to environmental pollutants. However, the mechanisms connecting MIS, mitochondria, lung function, and metabolic disorder remain unclear. In this study, we analyzed data from 1371 adults aged 40-69 years in the 2008 Korean Genome Epidemiologic Study (KoGES) Ansung cohort. We indirectly estimated dioxin-like MIS levels by measuring intracellular ATP (MISATP) and reactive oxygen species (MISROS) in cultured cells treated with the serum of participants. Using correlation analysis and structural equation modeling (SEM), we explored the relationships among MIS, mitochondrial function, body mass index (BMI), and lung function (FEV1 and FVC). Our findings revealed that MISATP was associated with BMI in females and with FVC in males, while MISROS correlated with both BMI and FVC in males, not in females. Significant associations between BMI and FVC were found in the highest MIS subgroup in both sexes. SEM analyses demonstrated that MIS negatively influenced mitochondrial function, which in turn affected BMI and lung function. Age-related declines in lung function were also linked to mitochondrial dysfunction. This study underscores the potential of MIS assays as alternatives for assessing mitochondrial function and highlights the importance of mitochondrial health in metabolic disorders and lung function.

Lifetime effects and cost-effectiveness of statin therapy for older people in the United Kingdom: a modelling study

BackgroundCardiovascular disease (CVD) risk increases with age. Statins reduce cardiovascular risk but their effects are less certain at older ages. We assessed the long-term effects and cost-effectiveness of statin therapy...

Nonlinear dynamic modeling and vibration analysis for early fault evolution of rolling bearings

In rotating machinery, the condition of rolling bearings is paramount, directly influencing operational integrity. However, the literature on the fault evolution of rolling bearings in their nascent stages is notably limited. Addressing this gap, our study establishes an innovative nonlinear dynamic model for early fault evolution of rolling bearings based on collision impact. Firstly, considering the fault evolution characteristics, the influence of the rolling element and fault structure, the dynamic model of early fault evolution between the rolling element and the local fault is established. Secondly, according to the Hertzian contact deformation theory, a nonlinear dynamic model of rolling bearings expressed as mass-spring is established. Thirdly, the energy contribution method is used to integrate the fault evolution model and the nonlinear dynamic model of the rolling bearing. A nonlinear dynamic model of early fault evolution of the rolling bearing is proposed by using the Lagrangian equation. Comparing the simulation results of the nonlinear dynamic with the experimental results, it can be seen that the numerical model can effectively predict the evolution process and vibration characteristics of the fault evolution of rolling bearings in the early stage.

A digital twin modeling and application for gear rack drilling rigs lifting system

A comprehensive digital transformation has been undergone by the oil and gas industry, wherein digital twins are leveraged to enable real-time data analysis, providing predictive and diagnostic engineering insights. The potential for developing intelligent oil and gas fields is substantial with the implementation of digital twins. A digital twin framework for gear rack drilling rigs is proposed, built upon an understanding of the digital twin composition and characteristics of the gear rack drilling rig lifting system. The framework encompasses descriptions of digital twin characteristics specific to drilling rigs, the application environment, and behavioral rules. The modeling approach integrates mechanism modeling, real-time performance response, instantaneous data transmission, and data visualization. To illustrate this framework, exemplary case studies involving the transmission unit and support unit of the lifting system are presented. Mechanism models are constructed to analyze dynamic gear performance and support unit response. Real-time data transmission is facilitated through sensor-based monitoring, enhancing the prediction speed and accuracy of dynamic performance through a synergy of mechanism modeling, machine learning, and real-time data analysis. The digital twin of the lifting system is visualized utilizing the Unity3D platform. Furthermore, functionalities on data acquisition, processing, and visualization across diverse application scenarios are encapsulated into modular components, streamlining the creation of high-fidelity digital twins. The frameworks and modeling methodologies presented herein can serve as a foundational and methodological guide for the exploration and implementation of digital twin technology within the oil and gas industry, ultimately fostering its advancement in this sector.

Design and analysis of a high-efficiency bi-directional DAB converter for EV charging

The escalating demand for electric vehicles (EVs) arises from apprehensions regarding fossil fuel depletion and the ecological repercussions of conventional combustion engines, propelling the transition towards environmentally sustainable alternatives. EVs are conventionally comprised of a powertrain, battery management system, and communication infrastructure, with the battery playing a pivotal role. Achieving an efficient EV battery charger necessitates the implementation of a proficient charging algorithm and a high-power converter capable of adeptly regulating battery parameters. Among the array of available options, a bi-directional DC/DC converter is often employed for this purpose. This study predominantly focuses on the Bi-Directional Dual Active Bridge Converter with Single-Phase Shift Control. It is renowned for attaining a broad voltage range through transformer turn ratio adjustments. Its controllable parameters, such as phase shift ratio and duty cycle, bolster its versatility. Moreover, due to its input–output isolation and minimal passive elements, this converter exhibits superior efficiency due to its soft-switching capabilities. The analytical framework encompasses steady-state and dynamic assessments, small-signal modeling, and system transfer function analysis, all of which contribute to formulating an optimized controller design. Additionally, the study conducts simulations of various battery charging techniques, including constant current (CC), constant voltage (CV), and CCCV mode, employing a 1.5 kW Dual Active Bridge DAB-based charger through MATLAB/SIMULINK. Furthermore, voltage mode control simulations for a 5 kW DAB converter augment the study's insights into effective EV charging strategies.

All gain and no pain? Impacts of different green human resource management practices on employee green behavior: Evidence from Chinese electric vehicle sector

Despite much research focusing on green human resource management, there is still a lack of comprehension regarding when and how different green human resource management practices influence employee green behavior. This research aims to construct and verify a research model in which different green human resource management practices influence employee green behavior through mediated pathways of perceived organizational green support and by interactive impact of employee green value. Structural equation modeling and importance-performance map analysis were performed based on survey data collected from 333 employees working in Chinese electric vehicle companies. The results revealed that most investigated practices are positively related to employee green behavior, and most of these relationships are mediated by perceived organizational green support and moderated by employee green value. However, green reward management negatively influences employee green behavior, and perceived green support does not mediate this relationship. Meanwhile, employee green value weakens green reward management’s negative impact on employee green behavior, while it does not moderate relationships between green training and development, nor green performance management and green behavior. Additionally, findings indicate that green training and development exhibits the highest performance while green involvement and engagement has the greatest total effect on employee green behavior. This study is the first to compare the effectiveness and performance of different green human resource management practices using data from the Chinese electric vehicle industry, providing insights for industrial environmental management and contributing to the growing body of literature.

Estimasi Sumberdaya Bauksit Menggunakan Metode Ordinary Kriging Pada PT. Wahana Petra Sejahtera Kabupaten Bengkayang Provinsi Kalimantan Barat

PT. Wahana Petra Sejahtera, which operates in the bauxite mining sector, requires resource calculations as a basis for carrying out its mining activities. This research aims to determine the levels and distribution of Al2O3, SiO2, and Fe2O3 and estimate bauxite resources using the ordinary kriging method. This research uses secondary data in coordinates, elevation, test pit depth, and slope data. Data processing uses software in database creation, statistical analysis, block and composite modeling, variogram analysis, resource estimation, and model validation. The calculation results for the Jirak block show that the Al2O3 waste content is 1,488,000 tons, low-grade 4,532,000 tons, medium-grade 1,824,000 tons, and high-grade 32,000 tons. For SiO2 the average content is 13.54% and the average Fe2O3 content is 13.50%. Meanwhile, in the Sindu block the Al2O3 waste content is 64,000 tons, medium-grade 1,188,000 tons, and high-grade 3,056,000 tons. Meanwhile, the average SiO2 content is 9.13% and the average Fe2O3 content is 12.06%. The total resources in the Jirak block are 7,696,000 tons with the amount meeting the COG of 800 tons. Meanwhile, in the Sindu block, the total resources are 5,008,000 tons with an amount that meets the COG of 1,280,000 tons.

Human resources management practices and organisational performance in the Nepalese development banks: Insights from structural equation modelling

Purpose: Effective human resource management (HRM) practices are essential factors that provide organizations with a competitive edge and contribute to their overall performance. This study examines the impact of HRM practices, including recruitment and selection (RS), training and development (TD), compensation policies (CPs), and performance appraisal (PA), on the organizational performance (OP) of the Nepalese development banks (DBs). Design/methodology/approach: The study followed a causal-comparative research approach. It employed a structured questionnaire to gather the necessary data from 257 working representatives of the ten selected Nepalese DBs. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to examine the association between the variables and validate the study hypotheses. Findings: The HRM practices exhibit a significant and positive association with OP (β = 0.910; p &lt; 0.05), indicating their influence on achieving organisational success. Such findings offer a pragmatic perspective for achieving HRM excellence and organisational effectiveness in the Nepalese DBs. Research constraints/implications: Analysis of cross-sectional data from development banks cannot be extrapolated to other sectors. This study emphasises the importance of compensation, performance measurement, hiring and selection, development, and training in improving OP, confirming and expanding prior findings. These insights may benefit policymakers, HR managers, and executives in enhancing HR operations by improving employee performance and business productivity.Originality/value: This study's unique contribution is its examination of HRM dynamics and their direct impact on OP, notably in the Nepalese DBs. The DBs may optimise their HR, enhancing OP and a long-lasting competitive advantage.

Modulation of SpyCatcher Ligation Kinetics by SpyTag Thioamide Substitution.

Thioamide substitutions have been shown to impart valuable properties on peptides for biophysical experiments as well as cell or in vivo studies, but a rational understanding of thioamide effects on protein structure and protein-protein interactions is lacking. To elucidate their effects in β-sheet structures, we have used SpyCatcher003-SpyTag003 as a host-guest system to study individual thioamide incorporation at eight different positions in the SpyTag peptide. We have demonstrated that incorporating thioamides into SpyTag at specific positions can result in a ∼2-fold faster ligating complex, as well as >2000-fold slower ligating complex. Biophysical analysis and structural modeling provide a reasonable explanation for most of the thioamide effects, altering hydrogen bond networks as well as modulating an n→π* interaction within the SpyTag peptide. Our findings have important implications for potential applications of thioamide SpyTag variants, where the thioamide could impart protease stability in cells while also controlling the rate of ligation to SpyCatcher. These SpyCatcher-SpyTag host-guest experiments will also help to build a database for predicting thioamide effects on protein structure and function.

Spatially Explicit Impact of Land Use Changes in the Bay Area on Anthropogenic Phosphorus Emissions and Freshwater Eutrophication Potential.

Land use changes significantly impact anthropogenic phosphorus (P) emissions, their migration to a water environment, and the formation of freshwater eutrophication potential (FEP), yet the spatiotemporally heterogeneous relationships at the regional scale have been less explored. This study combines land use classification, P-flow modeling, spatial analysis, and cause-effect chain modeling to assess P emissions and P-induced FEP at a fine spatial resolution in Guangdong-Hong Kong-Macao Greater Bay Area and reveals their dynamic responses to land use changes. We find that land conversion from cultivated land to impervious land corresponded to an increase in P emissions of 4.1, 1.8, and 0.5 Gg during 2000-2005, 2005-2010, and 2010-2015 periods, respectively, revealing its dominant but weakening role in the intensification of P emissions especially in less-developed cities. Expansion of aquacultural land gradually became the primary contributor to the increase in both the amount and intensity of P emissions. Land conversions from cultivated land to impervious land and from natural water bodies to aquacultural land led to 35.9% and 25.3% of the increase in FEP, respectively. Our study identifies hotspots for mitigating the environmental pressure from P emissions and provides tailored land management strategies at specific regional development stages and within sensitive areas.

Unveiling the impact of school organizational justice on students’ professional commitment through academic stress mediation

Accurately understanding the critical elements influencing college students’ professional commitment is both an urgent practical requirement and a critical theoretical proposition in today’s intensely competitive job market. In order to provide new light on career development in the context of higher education, this study intends to investigate the complex interactions among college students between perceived organizational justice, academic stress, and professional commitment. Using descriptive statistics, correlation analysis, regression analysis, and structural equation modeling, we carried out a thorough investigation of H University’s full-time undergraduate students in Central China in order to thoroughly examine our hypothesis. The results show that students’ professional commitment is much lower when they view organizational justice to be lacking, and that there is a partial mediating role for academic stress in this relationship. Interestingly, organizational justice has a positive correlation with professional commitment and a negative correlation with academic stress. These findings provide educators and policymakers with insightful information, indicating that, in an increasingly competitive labor market, professional commitment is largely dependent on students’ ability to manage their academic stress and develop a sense of organizational justice. This study adds a new understanding of career development in higher education settings by merging professional commitment research with organizational justice theory. It also has significant implications for educational practices and career support measures.

Weaving the tastes of tradition: Uncovering the threads of India’s culinary identity amid globalisation

ABSTRACT In the face of globalisation’s homogenising wave, this study serves as a beacon, illuminating the intricate web of factors that safeguard culinary heritage in India. The study hypothesised that a myriad of elements interweaves to form the fabric of food traditions, which in turn fortify collective identity. To validate this, the study engaged 696 individuals via an online survey, employing advanced statistical tools such as path analysis and partial least squares structural equation modelling (PLS-SEM) to unearth the core determinants of gastronomic lineage. Moreover, multiple regression analysis was utilised to measure the impact of these culinary practices on personal and cultural identity. The study’s revelations are profound, demonstrating that each of the 18 determinants meticulously chosen for this research significantly contributes to the crafting of Indian food heritage, thereby seasoning the identity of the future with the flavours of the past.

Modeling and numerical analysis of Kangaroo lower body based on constrained dynamics of hybrid serial–parallel floating-base systems

This paper presents the modeling and numerical analysis of the Kangaroo lower body prototype, a novel bipedal humanoid robot developed and manufactured by PAL Robotics. Kangaroo features high-power linear electric actuators combined with unique serial–parallel hybrid chains, which allow for the positioning of all the leg actuators near the base of the robot to improve the overall mass distribution. To model and analyze such complex nonlinear mechanisms, we employ a constrained formulation that is extended to account for floating-base systems in contact with the environment. A comparison is made to demonstrate the significant improvements achieved with TALOS, another humanoid bipedal robot designed by PAL Robotics, in terms of equivalent Cartesian inertia at the feet and centroidal angular momentum. Finally, the paper includes numerical experiments conducted through simulation and preliminary tests performed on the actual Kangaroo platform.