Miracle-dz/UniFAR-FTUs huggingface dataset:
Customer’s acceptance of the e-hailing application. How well do ease, physical security, relative advantage, social influence, and trialablity matter?

E-hailing services have a pivotal role in mitigating traffic congestion and decreasing the volume of private vehicles on the streets, thereby amplifying the effectiveness of the road transportation network. It provides income opportunities for drivers who can work flexible hours and utilize their own vehicles to earn money. Nevertheless, various obstacles stand in the way of the growth of e-hailing services, with customer acceptance being a prominent concern. Consequently, the primary objective of this research is to assess the extent to which the community embraces e-hailing applications, specifically focusing on Grabcar. By employing a systematic random sampling technique, a total of 345 individuals participated in this comprehensive study. The outcomes, analyzed through the lens of the Diffusion of Innovations Theory, reveal that the relative advantages, ease of use, trialability, social influence, and physical security significantly shape individuals' acceptance to adopt the Grabcar application. The findings of this study carry substantial implications for academic scholars and policymakers alike, guiding the creation of innovative strategies to optimize the potential of digital application services. As future research evolves, it may diverge from these findings to delve into qualitative aspects within this research realm, encompassing vital economic, social, and governance components. Such exploration would align with the ambitious pursuit of Sustainable Development Goals, reflecting a broader commitment to holistic societal advancement and responsible technological integration. Focusing solely on a specific region or demographic, this study's limitation could restrict its findings' broader applicability to a diverse population.
Digital Detox: The effect of smartphone abstinence on mood, anxiety, and craving

11 Whether behavioural addictions should be conceptualised using a similar framework to substance-related 12 addictions remains a topic of considerable debate. Previous literature has developed criteria, which allows 13 any new behavioural addiction to be considered analogous to substance-related addictions. These imply 14 that abstinence from a related object (e.g. smartphones for heavy smartphone users) would lead to mood 15 fluctuations alongside increased levels of anxiety and craving. In a sample of smartphone users, we 16 measured three variables (mood, anxiety, and craving) on four occasions, which included a 24-hour period 17 of smartphone abstinence. Only craving was affected following a short period of abstinence. The results 18 suggest that heavy smartphone usage does not fulfil the criteria required to be considered an addiction. This 19 may have implications for other behavioural addictions.
Digital Detox

This book discusses the dangers of too much technology use, explores the benefits of digital detoxing, and outlines the different programs and approaches available to help you unplug. It's an invaluable resource for readers looking to establish a healthier relationship with the digital world. Health professionals and the general public are becoming increasingly aware that addiction to the internet, social media, online games, and other forms of technology has become a real problem with significant negative impacts on physical, psychological, and social health. To combat this issue, some are now undertaking a "digital detox," and many options have emerged to help individuals unplug, whether for a weekend or for longer-term change. Digital Detox: Why Taking a Break from Technology Can Improve Your Well-Being explores both the dark side of technology's ever-present existence in today's world and what individuals can do to find better balance in their digital lives. Part I explores addiction to the internet and other novel technologies. What effect does overindulgence in social media, gaming, online shopping, or even "doomscrolling" through internet news sites have on our self-esteem, relationships with others, and happiness? This section also explores how researchers study and quantify technology addiction. Part II focuses on the digital detox countermovement, examining how various programs, support groups, retreats, and even technology itself can help individuals conquer their digital addictions.
A rolling bearing fault diagnosis method based on Markov transition field and multi-scale Runge-Kutta residual network

In order to address the problem that one- dimensional convolutional neural networks is difficult to extract the local correlation information and mine multi-scale information of rolling bearing fault signals under variable working conditions, a novel fault diagnosis method for rolling bearings based on Markov transition field (MTF) and multi-scale Runge–Kutta residual attention network (MRKRA-Net) is proposed in this paper. Firstly, the original signal is encoded into a two-dimensional image using the MTF method. Then, a multi-scale network is constructed using pre-activation Runge–Kutta residual blocks to extract multi-level features. Secondly, a feature-guided attention mechanism is designed and embedded into the network model to enhance its generalization ability. Finally, the MRKRA-Net model is validated on two different bearing datasets, and the results show that compared with other popular intelligent fault diagnosis methods, MRKRA-Net has higher fault diagnosis accuracy and stronger robustness under both given and variable working conditions.
Measuring the Impact of Ease of Use, Usefulness, Attitude, and Enjoyment toward Intention to Play PUBG Mobile

The impact of ease of use, usefulness, attitude, and enjoyment toward intention to play PUBG Mobile as it relates to Indonesians, is explicitly examined in this study’s examination of the mobile gaming era because of the pandemic. This paper investigates the factors that influence an individual’s intention to play PUBG Mobile and the outcome of those factors towards its individuals, as well as the effects of knowledge about gaming behavior to its users. The study’s recommendations are to increase the intention to play mobile games so that the need for enjoyable aspects and the need for outside assistance become more apparent. Through an online survey, 223 individuals provided information for this study. The survey asked for responses from people who had played a mobile game, particularly Player Unknown Battle Ground Mobile version (PUBGM), millennials or members of Generation Z having enrolled in college and who previously had resided in Indonesia, had at least played PUBG Mobile in the past, and had played it more than one year. In this work, statistical analysis is carried out. The outcome demonstrates that perceived ease of use, usefulness, attitude, and perceived enjoyment have an impact toward Intention to play PUBG Mobile. This study closes a gap in the literature by concentrating on the behavioral intention to play PUBG through the playful-consumption experiences of a well-known online multiplayer game.
Split-Check: Boosting Product Recognition via Instance-Level Retrieval

AI-based methods are shining across a variety of industries, especially unmanned retail. Product recognition is the problem of recognizing the category and quantity of products (e.g., beverages and mineral water) in intelligent unmanned vending machines (UVMs) to automatic checkout during purchase. However, for similar products in hundreds of categories, the existing method is not accurate enough. Besides, they cannot be extended for new products without retraining. In this article, we propose a product recognition approach based on intelligent UVMs, called Split-Check, which first splits the region of interest of products by detection and then check product by instance-level retrieval. Split-Check is the combination of two important components. The preliminary detection distinguishes items that contain the different coarse-grained features, then locates items, and classifies them into coarse-grained categories as a candidate. The retrieval further distinguishes the candidate items that contain the different fine-grained features. Besides, we reconstruct a large-scale categories product dataset GOODS-85 based on actual UVMs scenarios, in which the number of categories of items is larger than the existing dataset. Experimental results demonstrate the effectiveness of the proposed approach. Our method significantly improves the recognition performance of hundreds of products and increases the scalability of products.
Change characteristics and influencing factors of grassland degradation in adjacent areas of the Qinghai–Tibet Plateau and suggestions for grassland restoration

Natural grasslands are being progressively degraded around the world due to climate change and socioeconomic factors. Most of the drivers, processes, and consequences of grassland degradation are studied separately, and it is not yet clear whether the change characteristics and influence factors of adjacent areas of grassland are identical. We analyzed changes in grassland area and quality, and the influences of climate changes and socioeconomic factors from 1980–2018 in Maqu County, Xiahe County and Luqu County on the eastern Qinghai-Tibet Plateau (QTP). We found that areas with high and medium coverage grassland in Maqu County and Luqu County decreased continuously with time, while low coverage grassland areas increased in three counties. In Xiahe County, the medium coverage grassland area reduced with time (except for 2010), while the high and low coverage grassland areas increased. The actual net primary productivity of the three counties showed a downward trend. In Maqu County, the total grassland area had an extremely significant positive correlation with number of livestock going to market, commodity rate, gross domestic product (GDP), primary industry, tertiary industry, household density, and levels of junior middle school education and university education in the area. In Luqu County, the total grassland area high coverage grassland area were significantly negatively correlated with total number of livestock, secondary industry, levels of primary school education, and temperature. Ecological education was positively correlated with high coverage grassland, and negatively correlated with low coverage grassland in all three areas. The results of this study suggest that the best ways to restore the area and quality of grasslands in these areas would be to reduce the local cultivated land area and slow down the development of the primary and tertiary industries in Maqu County, and to control industry development and the total number of livestock in Luqu County. This study also suggests that improving education level and strengthening the level of ecological education are conducive to the restoration of grasslands.
Quambalaria eucalypti found on Eucalyptus in Indonesia

The Eucalyptus plantation industry in Indonesia has expanded rapidly during the last few decades. During routine nursery disease surveys, symptoms of a leaf and shoot blight disease were detected on Eucalyptus mother plants. Isolates were obtained from symptomatic tissues and identified using DNA sequence analyses. Phylogenetic analyses showed that the isolates were those of Quambalaria eucalypti. Pathogenicity tests were conducted with isolates of Q. eucalypti on clones of E. pellita and E. grandis × E. pellita hybrids. These resulted in symptoms similar to those observed on naturally infected plants. Eucalyptus genotypes tested showed variation in their susceptibility, highlighting the potential to select and breed for resistance and thus to manage future outbreaks of the disease. This is the first report of the pathogen in Indonesia as well as in Southeast Asia.
The Impact of the Microsoft and Activision-Blizzard Merger on the Gaming Industry: A Theoretical and Analytical Examination

Both Activision and Blizzard are regarded as two of the most successful and influential game development companies in the world. Due to the vast number of businesses that are contending for a share of the market, the commercial sector is characterized by a high degree of competitiveness. This is the case because of the presence of so many businesses. Mergers and acquisitions are common practices among gaming industry companies as they strive to fulfill their aims. The purpose of this study is to investigate the impact of the recent merger between Microsoft and Activision-Blizzard on the gaming industry from a theoretical and analytical perspective. Specifically, the study will examine how the gaming industry has been affected by the merger of these three companies. The main questions of this study are about three aspects of the impact of the merger between Microsoft and Activision-Blizzard on the competitive landscape of the gaming industry, the potential impact of this merger on innovation in the gaming industry, and what makes it different from previous mergers in the gaming industry. This study will examine the impact of the Microsoft-Activision-Blizzard merger on the gaming industry through the use of industry data, economic analysis, and case studies. The author will also consider previous research on mergers and acquisitions in the gaming industry to provide context for our analysis. The aim of this paper is to provide a detailed examination of the potential impact of the merger on competition and innovation in the gaming industry.
Tolerance and Oncological Outcomes of In-Field Reirradiation for Locally Recurrent Breast Cancer: A Long-Term Single-Center Experience

Simple Summary Breast reirradiation could represent a valuable option for local recurrence of breast cancer in previously irradiated sites. We aimed to report on the efficacy and tolerability of this treatment in our institution. The results of this series combined with those available in the literature indicate that breast/chest wall reirradiation is feasible with good oncological results and low toxicity rates. Abstract Background: The management of cancer relapse in previously irradiated tissues is a challenging therapeutic issue. The aim of this work was to report our experience with breast reirradiation for locoregionally recurrent breast cancer. Methods: All patients who underwent breast or chest wall in-field reirradiation at the Institut Curie, Paris, France, between 2003 and 2019, were identified. Efficacy outcomes and physician-reported toxicities were retrospectively assessed. Results: A total of 21,372 patients underwent breast irradiation in our institution. Of these, 28 received a second course of radiotherapy to the homolateral breast/chest wall. A total of 18 (64%) patients were treated with a curative intent, and 10 (36%) were treated for palliative purposes. Only one acute and one late grade 3 adverse events were reported. One patient with major cardiovascular risk factors died of myocardial infarction 13 months after left breast reirradiation. The 2-year LRFS, OS, DSS, PFS and MFS were 59%, 79%, 82%, 46% and 75%, respectively, in the whole cohort. The 2-year LRFS (72% vs. 31%, p = 0.02), OS (94% vs. 50%, p < 0.01), DSS (94% vs. 56%, p < 0.01) and PFS (61% vs. 20%, p = 0.02) differed significantly between patients treated with curative or palliative intent but not the MFS (78% vs. 69%, p = 0.77). Among the patients, eight (29%) remained relapse-free 5 years after reirradiation. Conclusion: Breast/chest wall reirradiation appears to be feasible with good disease control, especially in patients treated with a curative intent, and presents acceptable toxicity rates.
IWH Discussion Papers

In this paper we analyze the small sample properties of full information and limited information estimators in a potentially misspecified DSGE model. Therefore, we conduct a simulation study based on a standard New Keynesian model including price and wage rigidities. We then study the effects of omitted variable problems on the structural parameters estimates of the model. We find that FIML performs superior when the model is correctly specified. In cases where some of the model characteristics are omitted, the performance of FIML is highly unreliable, whereas GMM estimates remain approximately unbiased and significance tests are mostly reliable.
Nonlinear-Drifted Fractional Brownian Motion With Multiple Hidden State Variables for Remaining Useful Life Prediction of Lithium-Ion Batteries

Lithium-ion rechargeable batteries are widely used in various electronic products and equipment due to their immense benefits in power supplying. The exact remaining useful life (RUL) prediction of lithium-ion batteries has shown excellent achievements in preventing severe economic and security consequences incurred in failing to provide necessary power levels. Recently, the nonlinear-drifted fractional Brownian motion made quite a splash in RUL prediction, since its first hitting time distribution can be approximated by weak convergence theorem and time-space transformation. However, the previous RUL prediction methods based on fractional Brownian motion only considered current state measurement. In this paper, a prediction framework based on nonlinear-drifted fractional Brownian motion with multiple hidden state variables is put forward to estimate RUL. Specifically, all the parameters of nonlinear function are defined as specific hidden state variables of lithium-ion battery degradation model, and all the state measurements are used to posteriorly estimate the distribution of the multiple hidden state variables by unscented particle filter algorithm. Four sets of lithium-ion battery degradation data provided by NASA Ames Research Center are used to validate the proposed prediction framework. According to comparison study with other methods, the proposed prediction framework demonstrates greater precision in the RUL prediction.
A POI Recommendation Model for Intelligent Systems Using AT-LSTM in Location-Based Social Network Big Data

In location-based social networks (LBSN), users can check-in at points of interest (POI) to record their trips. POI recommendation is an important service provided by LBSN; it can help users quickly find POI of interest, and also help POI providers more comprehensively understand user preferences and improve service quality. This paper proposes a POI recommendation algorithm that is based on attention mechanism. The sequence characteristics and short-term preferences of historical data are captured through the attention mechanism module and long short-term memory network (LSTM), and the POI location prediction is carried out in combination with the user embedding characteristics, and a better prediction accuracy is obtained. These results simulated show that the proposed method can realize the reliable analysis of complex data sets, and its precision index remains above 0.1 and recall index remains above 0.08, and it can also alleviate the cold start problem and better meet the personalized needs of users.
Framework for Environmental and Socially Responsible Economic Growth

Objective: Sustainable development is being propelled forward by a confluence of factors, social commerce efforts, the collaborative economy, and education. With steady agricultural production capacities, there is a growing need to increase the intensity of food over product production. The main drawbacks of this are current global population situation, profitability of the consumer sector and the issue of insecurity. The rising cost of food is another issue that has motivated researchers to look for ways to improve agricultural productivity through the use of cutting-edge technology. All of these factors could significantly impact the future of sustainable development and social enterprise. Consequently, this aims on the lookout for creative answers how to boost output without significantly raising prices based on social economics. New business models are being established on the back of ideas like social commerce, the collaborative economy, and virtual currencies, in which people are looking for ways to redistribute wealth more fairly through exchanges of equity, trust, and collaboration. Method: The purpose of this research is to examine how these factors contribute to sustainable growth by developing Legal Framework for Socially Sustainable Economic Development [LF-SSED]. As a result, the use of cutting-edge technologies in digital transformation, it might be an important milestone in the business world, ushering in new ways of doing things and unlocking dormant potential. Result: To begin, it is necessary to define some of the more essential concepts in this research. Conclusion: Preparing students to take advantage of environmentally friendly development and economic prospects brought forth by technological progress is a top priority a constructivist approach centered on the learner is then used.
Tertiary Pongidae of East Africa: Evolutionary Relationships and Taxonomy

A tube servicing device having a pair of rollers, each rotatably supported by a resiliently flexible leg of a strap frame in opposing relation whereby when the legs are pushed together the rollers pinch between them the flexible tube to be serviced, and as the frame is drawn along the tube, the rollers travel in rolling contact engagement therewith to expel by squeegee action material within the tube over the length traversed.
El desarrollo regional mediante la red de contactos empresariales.

En este articulo aplicaremos la iniciativa empresarial, concebida como una red de contactos (networking), una forma creativa organizativa, a un sistema espacial; a una localidad. Crearemos un vocabulario y unos conceptos que reconozca la importancia de la red de contactos como concepto socioeconomico y al territorio como un «contexto organizativo». La «sociedad empresarial» frente a la «constituida» se presentan como ideales contrapuestos, respecto al posible alcance del desarrollo economico local. Aplicaremos las redes locales como instrumento organizativo generico a tres pequenos escenarios empresariales suecos. La corriente empirica sugerira que las imagenes tradicionales de control, asociadas con la regulacion del marco de actuacion, las acciones o el resultado de la actividad organizada, sean reemplazadas por el «control relacional», el cual pretende fomentar y revitalizar la autoorganizacion. Todo esto sera posible mediante un dialogo plural, que involucre tanto a empresas locales como a otros miembros interesados de la localidad.
A modified partial envelope tensor response regression

The envelope model is a useful statistical technique that can be applied to multivariate linear regression problems. It aims to remove immaterial information via sufficient dimension reduction techniques while still gaining efficiency and providing accurate parameter estimates. Recently, envelope tensor versions have been developed to extend this technique to tensor data. In this work, a partial tensor envelope model is proposed that allows for a parsimonious version of tensor response regression when only certain predictors are of interest. The consistency and asymptotic normality of the regression coefficients estimator are also established theoretically, which provides a rigorous foundation for the proposed method. In numerical studies using both simulated and real‐world data, the partial tensor envelope model is shown to outperform several existing methods in terms of the efficiency of the regression coefficients associated with the selected predictors.