Miracle-dz/UniFAR-FTUs huggingface dataset:
Social capital and firm operational performance: The mediating roles of knowledge sharing

Abstract Personal or private relationships between leaders of construction firms and government officials are critical to a firm’s market success because they provide access to valuable information that their competitors do not. This study was carried out to investigate the associations between social capital dimensions, the sharing of knowledge and firm operational performance of small and medium-sized enterprises (SMEs) in the construction sector. Our study utilised a questionnaire-based survey design to gather online data using a convenience sampling method. To test the hypotheses, data obtained from 346 SMEs were analysed using structural equation modelling. Overall, other than the connection between structural social capital and explicit knowledge sharing, all social capital dimensions had a positive impact on both explicit and tacit knowledge sharing. Furthermore, explicit and tacit knowledge sharing positively influenced firm operational performance. Surprisingly, only cognitive social capital dimension was found to affect operational performance directly. Our study offers several practical implications regarding how firms can enhance improved operational performance in relation to advocating social capital dimensions and the sharing of knowledge.
Co-creation and co-production in municipal risk governance – A case study of citizen participation in a German city

ABSTRACT Municipal risk governance requires a communication-oriented approach that involves citizens in order to foster risk resilience. This study argues that citizen participation mechanisms enable citizens to co-create and co-produce risk governance. The paper draws on the case of a German city, including 45 interviews with experts from the municipality’s administration. The results indicate that citizens play a vital role in the risk identification and risk management of institutional and social, collective risks by providing time, information, and other resources. Specific citizen participation mechanisms can even help to handle system risks by fostering acceptance and loyalty.
A New Algorithm and Its Application in Detecting Community of the Bipartite Complex Network

The community division of bipartite networks is one frontier problem on the research of complex networks today. In this study, we propose a model of community detection of the bipartite network, which is based on the generalized suffix tree algorithm. First, extract the adjacent node sequences from the matrix of relation and use the obtained adjacent node sequences to build a generalized suffix tree; second, traverse the established generalized suffix tree to obtain the bipartite cliques; third, adjust the bipartite cliques; finally, dispose the isolated edges, get the communities, and complete the division of the bipartite network. This algorithm is different from the traditional community mining one since it uses edges as the community division medium and does not need to specify the number of the division of communities before the experiment. Furthermore, we can find overlapping communities by this new algorithm which can decrease the time complexity.
Prescribed Burning Reduces Large, High-Intensity Wildfires and Emissions in the Brazilian Savanna

Brazil has recently (2014) changed from a zero-fire policy to an Integrated Fire Management (IFM) program with the active use of prescribed burning (PB) in federal Protected Areas (PA) and Indigenous Territories (IT) of the Brazilian savanna (Cerrado). PB is commonly applied in the management of fire-prone ecosystems to mitigate large, high-intensity wildfires, the associated emissions, and high fire suppression costs. However, the effectiveness of such fire management in reducing large wildfires and emissions over Brazil remains mostly unevaluated. Here, we aim to fill the gap in the scientific evidence of the PB benefits by relying on the most up-to-date, satellite-derived fire datasets of burned area (BA), fire size, duration, emissions, and intensity from 2003 to 2018. We focused on two Cerrado ITs with different sizes and hydrological regimes, Xerente and Araguaia, where IFM has been in place since 2015. To understand fire regime dynamics, we divided the study period into three phases according to the prevalent fire policy and the individual fire scars into four size classes. We considered two fire seasons: management fire season (MFS, which goes from rainy to mid-dry season, when PBs are undertaken) and wildfires season (WFS, when PBs are not performed and fires tend to grow out of control). Our results show that the implementation of the IFM program was responsible for a decrease of the areas affected by high fire recurrence in Xerente and Araguaia, when compared with the Zero Fire Phase (2008–2013). In both regions, PB effectively reduced the large wildfires occurrence, the number of medium and large scars, fire intensity, and emissions, changing the prevalent fire season from the WFS to the MFS. Such reductions are significant since WFS causes higher negative impacts on biodiversity conservation and higher greenhouse gas emissions. We conclude that the effect on wildfires can still be reduced if effective fire management policies, including PB, continue to be implemented during the coming decades.
Integrating qualitative and quantitative analyses of stance: A case study of English that/zero variation

Abstract Previous work has shown that stance—the way speakers position themselves with respect to what they are talking about and who they are talking to—provides powerful insights into why speakers choose certain linguistic variants, beyond correlations with macro-social categories such as gender, ethnicity, and social class. However, as stancetaking moves are highly context-dependent, they have rarely been explored quantitatively, making the observed variable patterns difficult to generalize. This article seeks to contribute to this methodological gap by proposing a formal guide to coding stance and demonstrating how it can be operationalized quantitatively. Drawing on a corpus of eight individuals, self-recorded in three situations with varying levels of social distance, we apply this method to variation between English complementizers that and zero (i.e. no overt complementizer), providing a replicable and theoretically grounded protocol that incorporates both quantitative and qualitative analyses in a variationist sociolinguistic study. (Stance, complementizers, that, English)*
In-Wheel Two-Speed AMT with Selectable One-Way Clutch for Electric Vehicles

To improve the efficiency of the electric vehicle (EV) drive systems and EV performance, the use of multi-speed transmissions and distributed drives has been studied extensively. In addition, to develop efficient and compact drive systems, new clutch solutions are needed. In this paper, we propose an in-wheel two-speed automatic mechanical transmission (IW-AMT) with a selectable one-way clutch (SOWC). The IW-AMT consists of a high-speed motor and a mechanical shift actuator, and it can realize shifting without power interruption, thus effectively reducing the unsprung mass and the technical specifications of the motor. We established a virtual prototype model of the IW-AMT to show the shifting process and evaluate the quality of shifting. The simulation results of the upshifting process indicated that the vehicle torque and velocity changed smoothly, and the maximum jerk is less than 10 m/s3. Furthermore, to improve the jerk induced by the downshifting process, we analyzed the momentary state of the SOWC struts that are dropped and attempted to improve the jerk from two aspects: improving the wet multi-plate clutch (WMPC) combination curve and improving the SOWC structure. The results indicated that the downshift-induced jerk can be reduced to 13 m/s3.
Linked-Object Dynamic Offloading (LODO) for the Cooperation of Data and Tasks on Edge Computing Environment

With the evolution of the Internet of Things (IoT), edge computing technology is using to process data rapidly increasing from various IoT devices efficiently. Edge computing offloading reduces data processing time and bandwidth usage by processing data in real-time on the device where the data is generating or on a nearby server. Previous studies have proposed offloading between IoT devices through local-edge collaboration from resource-constrained edge servers. However, they did not consider nearby edge servers in the same layer with computing resources. Consequently, quality of service (QoS) degrade due to restricted resources of edge computing and higher execution latency due to congestion. To handle offloaded tasks in a rapidly changing dynamic environment, finding an optimal target server is still challenging. Therefore, a new cooperative offloading method to control edge computing resources is needed to allocate limited resources between distributed edges efficiently. This paper suggests the LODO (linked-object dynamic offloading) algorithm that provides an ideal balance between edges by considering the ready state or running state. LODO algorithm carries out tasks in the list in the order of high correlation between data and tasks through linked objects. Furthermore, dynamic offloading considers the running status of all cooperative terminals and decides to schedule task distribution. That can decrease the average delayed time and average power consumption of terminals. In addition, the resource shortage problem can settle by reducing task processing using its distributions.
Weighted Fractional-Order Transform Based on Periodic Matrix

Tao et al. proposed the definition of the linear summation of fractional-order matrices based on the theory of Yeh and Pei. This definition was further extended and applied to image encryption. In this paper, we propose a reformulation of the definitions of Yeh et al. and Tao et al. and analyze them theoretically. The results show that many weighted terms are invalid. Therefore, we use the proposed reformulation to prove that the effective weighted terms depend on the period of the matrix. This also shows that the image encryption methods based on the weighted fractional-order transform will lead to the security risk of key invalidation. Finally, our hypothesis is verified by the unified theoretical framework of multiple-parameter discrete fractional-order transforms.
A new hierarchy framework for feature engineering through multi‐objective evolutionary algorithm in text classification

Sentiment classification is a field of sentiment analysis concerned with analyzing opinions, emotions, evaluations, and attitudes regarding a special topic like a product, an organization, a person, or an incident. With the growth of user‐generated content on the Web, this field gained great importance in online reviews. With a wide range of reviews, customers cannot read all reviews. Considering the increasing rate of electronic documents and the urgent need manually mine for keywords that are hard and time‐consuming, doing the same automatically is of high demand. A new framework proposed here to mine and classify users' comments based on mining keywords by applying the sequence pattern mining through the Separation‐Power concept, a multi‐objective evolutionary algorithm based on decomposition with four objectives, and a neural network as the final classifier. Some modifications are made on multi‐objective evolutionary algorithm based on decomposition and Apriori algorithms to improve the text classification efficiency. To evaluate the proposed framework, three datasets applied; which compared with the two methods to measure accuracy, precision, recall, and error‐index. The results indicate that this framework provides a better outcome than its counterparts with 99.45 precision, 99.34 accuracy, 99.48 recall, and 99.28% f‐measure.
Accuracy Level Analysis of Pricing Model on State-Owned Enterprises Stocks

This study evaluates and compares the Capital Asset Pricing Model and Fama-French three-Factors (FF3) performance to explain the excess returns on state-owned companies listed on the Indonesia Stock Exchange. The results showed that the Fama-French Three-Factor Model was better than the Capital Asset Price Model to explain the excess returns in Indonesian state-owned companies. This study uses asset price factors of 2 x 3 types and excess returns of 6 Size-B / M as the dependent variable. This study uses Ordinary Least Square (OLS) with daily time-series data from 29 July 2019 to 10 December 2019. Based on the adjusted R2 average of the two models, FF3 explains that the portfolio's excess returns are better than the CAPM. For the Capital Asset Pricing Model, the average R2 value of the multiple linear regression results for the Size-BM portfolio group is 47%, and for the three-factor Fama-French model, the average R2 value of the multiple line regression results for the Size-BM portfolio is 52%. It can be said that the three-factor Fama-French model is more accurate in performing asset pricing on Indonesia State-Owned Enterprises.
Influence of avocado orchard landscapes on amphibians and reptiles in the trans‐Mexican volcanic belt

Commercial fruit orchards are embedded in a landscape of native forest and diverse kinds of agroecosystems. The landscape structure of these systems is a major driver of biodiversity response. Generally, it is assumed that high levels of biodiversity occur in perennial systems largely due to their high structural complexity. However, little is known about the influence of other landscape attributes on these levels of biodiversity. Avocado (Persea americana) constitutes about 25 percent of the global fresh fruit trade. In Mexico, avocado trees flourish about the same altitude as pine–oak forests (POFs). We studied the response of the local herpetofauna to conversion of POF to avocado orchards (AOs). We also explored the effects of forest cover on species that differ in their levels of habitat specialization. In the avocado belt in Michoacan, we sampled 12 sites representing a gradient of AO embedded in native POF to evaluate the variation in structure of local assemblages of amphibians and reptiles. Reduction of POF cover negatively affected specialist frog and snake species, but this relationship varied among buffers around sampling sites. Generalist species of amphibians and lizards showed increased abundances and richness in sites with low POF cover, whereas snake richness and abundance were higher in sites with high POF cover. Our study suggests that POF conversion to AO is a driver favoring the persistence and success of generalist but not specialist herpetofauna species. Therefore, to conserve the diversity of amphibians and reptiles in these agroecosystems, it is important to ensure high proportion of POF patches.
Supply Chain Practitioners’ Perception on Sustainability: An Empirical Study

The sustainability of supply chains is now one of the major global issues due to the vision of the United Nations (UN). By 2030, it is the primary focus of the UN to attain all the seventeen sustainable development goals (SDG). Hence, the primary goal of this study is to examine how practitioners think about sustainable supply chains. Five hypotheses are established to assess the perceptions of supply chain professionals. Forty-two (42) indicators are gathered from the existing literature to establish the survey instrument to collect the responses from supply chain practitioners. Finally, Structural Equation Modeling (SEM) is used to evaluate the mediation effects. It is found that social aspects are significantly impacted by the environmental aspects, as compared to the economic aspects. None of these indicators play any mediation effect, as all three are equally important for the sustainable supply chains.
Elucidation of impact event recorded in the lherzolitic shergottite NWA 7397

The (plagioclase) lherzolitic shergottite Northwest Africa (NWA) 7397 consists of poikilitic and non‐poikilitic lithologies. Coarse‐grained low‐Ca pyroxene oikocrysts enclose olivine and chromite grains in the poikilitic lithology. The major constituents of the non‐poikilitic lithology are olivine, Ca‐pyroxene, and plagioclase. Minor amounts of chromite, ilmenite, alkali feldspar, Ca‐phosphate, and iron‐sulfide are included in the non‐poikilitic lithology. Most plagioclase grains in the non‐poikilitic lithology have become maskelynite. A melt pocket occurs in the non‐poikilitic lithology. Plagioclase in contact with the melt pocket has dissociated into zagamiite + stishovite. Apatite and merrillite entrained in the melt pocket have transformed into tuite. Olivine in contact with the melt pocket has dissociated into bridgmanite (almost vitrified) + ferroan‐periclase. Alteration products, iron oxides and hydroxides, also occur in the dissociated olivine although it is not clear when the aqueous alteration occurred. The dissociation reactions of olivine and plagioclase into the high‐pressure polymorphs (bridgmanite, ferroan‐periclase, zagamiite, and stishovite) are found from lherzolitic shergottites for the first time. The estimated peak shock‐pressure and ‐temperature conditions recorded in melt pockets of NWA 7397 are ˜23 GPa and 2,000 °C at least, respectively, based on the high‐pressure mineral assemblages.
Comparison Between Lumped-Mass Modeling and Flow Simulation of the Reed-Type Artificial Vocal Fold

The sound generated by a reed-type artificial vocal fold was predicted by a one-mass modeling and numerical flow simulation to examine the sound generation mechanisms of the artificial vocal fold. For the one-mass modeling, the reed oscillation was modeled with an equivalent spring constant, and the flow rate was estimated by Bernoulli’s equation. For the flow simulation, the flow and acoustic fields were predicted with compressible Navier-Stokes Equations, while the reed oscillation was calculated by a one-dimensional beam equation. The experimentation was conducted by measuring the sound of an artificial vocal fold in an anechoic chamber. The results of the acoustic measurement showed that the sound amplitudes in the flow simulation agreed well with the experiment, while the one-mass model underestimated the amplitudes in a higher frequency range. Reed displacement and flow rate comparisons indicated that the flow retention in the reed retainer caused the asymmetry in the flow rate waveform, hence producing larger amplitudes for the flow simulation in the higher frequency range. The flow simulation enabled to predict this flow retention which cannot be modeled in the one-dimensional one-mass model, and it is anticipated to apply the flow simulation to develop a better artificial vocal fold.
End-to-End Spelling Correction Conditioned on Acoustic Feature for Code-Switching Speech Recognition

In this work, we propose a new end-to-end (E2E) spelling correction method for post-processing of code-switching automatic speech recognition (ASR). Existing E2E spelling correction models take the hypotheses of ASR as inputs and annotated text as the targets. Due to the powerful modeling capabilities of the E2E model, the training of the correction system is extremely prone to over-ﬁtting. It usually requires sufﬁcient data diversity for reliable training. Therefore, it is difﬁcult to apply the E2E correction models to the code-switching ASR task because of the data shortage. In this paper, we introduce the acoustic features into the spelling correction model. Our method can alleviate the problem of over-ﬁtting and has better performance. Meanwhile, because the acoustic features are encode-free, our proposed model can be applied to the ASR model without sig-niﬁcantly increasing the computational cost. The experimental results on ASRU 2019 Mandarin-English Code-switching Challenge data set show that the proposed method achieves 11.14% relative error rate reduction compared with baseline.
Safe sex practices among women who have sex with women in Tanzania: implications for HIV and STIs control among this group

Background: Women who have sex with women (WSW) are at an increased risk of sexually transmitted infections (STIs) due to engagement in high-risk sexual behaviors. Safe sex practice is hence critical for the WSW. The aim of the study was to assess safe sex health behaviors and practices among WSW to inform sexual and reproductive interventions targeting this group in Tanzania.Methods: This study was cross-sectional descriptive and retrospective conducted in Dar-es-Salaam region, the largest commercial city in Tanzania. Study population included WSW aged 18 years and above who met inclusion criteria. Data was collected using focus group discussions, in-depth interviews, key informant interviews and life stories. Data analysis applied thematic analysis.Results: Few WSW reported practicing safe sex. WSW used condoms only when engaging in sex with men. Some WSW lacked information on availability of protective devices; while some WSW did not use of protection despite having information on availability of protective devices. Majority of WSW used good hygiene practice (cleaning body, vagina, mouth, and sex toys) before and after sex to prevent transmission of infections; and some WSW used pre- and post- exposure prophylaxes. Low access and high cost of protective devices, being in a monogamous relationship, low health risk perception, fear of developing cancer from using lubricants, and advise from health worker against using lubricants, were reasons given by WSW for not practicing safe sex.Conclusions: Given the current evidence of overlap between the homosexual and heterosexual populations in STI transmission, comprehensive education on potential routes of STI transmission among WSW is critical.
The Relationship Between Human Resource Management Practices, Knowledge Management Practices, and Performance: Evidence from the Healthcare Industry in India

The objective of the present study is to examine the impact of human resource management (HRM) practices on organizational performance. Knowledge management (KM) practices as a moderator in the relationship between HRM practices and organizational performance are studied by developing a conceptual model. Using a structured survey instrument, the data were collected from 979 employees from 10 hospitals in the southern part of India (Tiruchirappalli District of Tamil Nadu). After thoroughly checking the instrument’s measurement properties using the LISREL, hierarchical regression was performed to test the hypotheses. The results support (a) compensation and rewards, performance appraisal and learning culture that are positively and significantly related to organizational performance; (b) recruitment and selection, training and development that are not significantly related to organizational performance; and (c) KM practices that moderate the relationship between (a) training and development and organizational performance, and (b) learning culture and organizational performance. Finally, the implications for HRM and KM are discussed.
Indian Telemedicine Industry: Evolving Nature of Business Models and Customer Interactions

During the COVID-19 pandemic, the telemedicine industry evolved rapidly in India. The purpose of this case research was to map the evolution of the telemedicine industry in India. This was studied from the perspectives of present business models and customer engagement methods practised in India by different telemedicine firms. The research case study approach as advocated by Yin (1994, 2011), Eisenhardt (1989, 1991) and Woodside (2010) was followed. For the purpose of this study, the authors collected the data related to telemedicine firms’ business leaders in India through primary and secondary sources from October 2020 to February 2021. An array of appropriate methods was applied to compare, analyse, conduct pattern mapping, pattern matching and illustrate the subject to support the arguments of this research study. Specifically, a theoretical contribution was made on business models (Acheampong & Vimarlund, 2015; Peters et al., 2015) and customer interaction (Broens et al., 2007; Gackowski et al., 2011).