Miracle-dz/UniFAR-FTUs huggingface dataset:
Social capital, person-organization fit and cynicism: a multi-stage mediation model of turnover intention in public organizations

PurposeThe informal dimension of organizational experience can shape performance-relevant employee behavior, including voluntary turnover. The authors develop a multi-stage model of turnover intention relevant to public organizations based on the quality of informal intra-organizational employee ties. Specifically, the authors argue that organizational social capital reduces turnover intention both directly and indirectly via its influence on person-organization fit, organizational cynicism and job satisfaction.Design/methodology/approachThe authors use data from a survey of 946 Korean public sector employees and partial least squares structural equation modeling to test our hypotheses. A number of checks are performed to evaluate the integrity of the data and probe the robustness of the results.FindingsThe authors find that there is a significant link between organizational social capital and turnover intention, but that this relationship is fully mediated by the specified intervening processes. Social capital is associated with increased P-O fit, increased job satisfaction and reduced cynicism. In turn, P-O fit reduces turnover intention both directly and indirectly via increased job satisfaction and reduced cynicism.Originality/valueWhile a number of studies demonstrate the value of organizational social capital, the current study works through the theoretical mechanisms by which social capital is transformed into valued organizational outputs. Some of these are specifically relevant to public organizations. The authors describe the model's practical relevance and suggest research questions that can build upon our findings. The authors also note the study's limitations.
The Climate Change Awareness and Literacy in Pakistan: Role of Media and Social Actors

The multidimensional impacts of climate change are increasing the vulnerability of Pakistan day by day. The government of Pakistan has framed polices and laws related to climate change however, the challenge is the implementation of these polices and initiatives which is directly related to climate change awareness and literacy. This study addresses the central question of what the status of climate change awareness and literacy and what role media and social actors play in this regard. To answer this question, a qualitative, descriptive, and analytical methodology has been employed. This study found that poor climate literacy and awareness among common masses is one of the key reasons that so far these initiatives are not successful. Since the real chain movers of any response and development are people not policy makers or power elites so nourishing eagerness for climate change literacy and awareness proves effective. This study recommends that as a nation, it is necessary to develop climate literacy and awareness to generate public response against the imminent threat of climate change.
Projecting the Impact of Climate Change on the Spatial Distribution of Six Subalpine Tree Species in South Korea Using a Multi-Model Ensemble Approach

Climate change is recognized as a major threat to global biodiversity and has already caused extensive regional extinction. In particular danger are the plant habitats in subalpine zones, which are more vulnerable to climate change. Evergreen coniferous trees in South Korean subalpine zones are currently designated as a species that need special care given their conservation value, but the reason for their decline and its seriousness remains unclear. This research estimates the potential land suitability (LS) of the subalpine zones in South Korea for six coniferous species vulnerable to climate change in the current time (1970–2000) and two future periods, the 2050s (2041–2060) and the 2070s (2061–2080). We analyze the ensemble-averaged loss of currently suitable habitats in the future, using nine species distribution models (SDMs). Korean arborvitae (Thuja koraiensis) and Khingan fir (Abies nephrolepis) are two species expected to experience significant habitat losses in 2050 (−59.5% under Representative Concentration Pathway (RCP) 4.5 to −65.9% under RCP 8.5 and −56.3% under RCP 4.5 to −57.7% under RCP 8.5, respectively). High extinction risks are estimated for these species, due to the difficulty of finding other suitable habitats with high LS. The current habitat of Korean fir (Abies koreana), listed as a threatened species on the International Union for Conservation of Nature (IUCN) Red List, is expected to decrease by −23.9% (RCP 4.5) to −28.4% (RCP 8.5) and −36.5% (RCP 4.5) to −36.7% (RCP 8.5) in the 2050s and 2070s, respectively. Still, its suitable habitats are also estimated to expand geographically toward the northern part of the Baekdudaegan mountain range. In the context of forest management and adaptation planning, the multi-model ensemble approach to mapping future shifts in the range of subalpine tree species under climate change provides robust information about the potential distribution of threatened and endanger
LensCast: Robust Wireless Video Transmission Over MmWave MIMO With Lens Antenna Array

In this paper, we present LensCast, a novel cross-layer video transmission framework for wireless networks, which seamlessly integrates millimeter wave (mmWave) lens multiple-input multiple-output (MIMO) with robust video transmission. LensCast is designed to exploit the video content diversity at the application layer, together with the spatial path diversity of lens antenna array at the physical layer, to achieve graceful video transmission performance under varying channel conditions. In LensCast, a transmission distortion minimization problem is formulated with the consideration of video chunk scheduling, path matching and power allocation, which is an intractable mixed integer non-linear programming (MINLP) problem. The solution of this MINLP problem is converted into resource allocation (i.e., joint path matching and power allocation) plus chunk scheduling. First, resource allocation is investigated with given chunk scheduling results. By analyzing the optimality of the resource allocation problem, a winner-takes-all assignment is obtained to guide resource allocation. After that, a greedy water-filling algorithm is proposed as a near-optimal solution. Second, we propose a low-complexity chunk scheduling algorithm to schedule chunks for each transmission. Simulation results demonstrate that the proposed LensCast achieves an improved performance in terms of both peak signal-to-noise ratio and visual quality comparing with reference schemes.
Errors In Using Convergence Tests In Infinite Series

Abstract: The present study aimed to identify the errors made by pre-service elementary mathematics teachers while investigating the convergence of infinite series. A qualitative exploratory case study design was used with a total of 43 undergraduate students. Data were obtained from a test administered in a paper-and-pencil form consisting of seven open-ended questions. The data analysis was done using descriptive and content analysis techniques. Findings were presented as follows: inappropriate test selections; failure to check convergence criteria; incorrect use of a comparison test; limit comparison test error; re-test convergence test results; considering ∑ as a multiplicative function; misunderstanding of special series; considering that series has no character when the convergence test is inconclusive; confusing sequences with series; misunderstanding of the nth-term test; misinterpretation of convergence test results. Findings showed that students with insufficient procedural knowledge had difficulty in solving the given problem even if they understood it, whereas those with insufficient conceptual knowledge could not literally understand what they did even if they solved the problem. Therefore, the establishment of a moderate balance between procedural and conceptual knowledge in the learning of the convergence of series is essential in reducing the errors or learning difficulties for developing deep mathematical understanding
Investigating the Appropriateness and Validity of the Academic Motivation Scale-College Version for South African First-Year University Students

South African universities have one of the lowest graduation rates in the world, especially amongst first-year university students. South Africa’s first-year university students are taxed with tremendous challenges. One of the most important amongst these challenges is considered to be academic motivation, which is strongly related to students’ academic success. Despite this, to date, little work has been undertaken to source and validate a reliable instrument to measure students’ academic motivation. This article is based on the proposition that there is a pressing need for a valid and reliable instrument that measures academic motivation and its effect on students’ academic success. The psychometric properties of the Academic Motivation Scale-College version were examined for first-year university students. The findings are promising for using this scale to measure academic motivation of first-year university students.
Preparation of magnetic metal organic framework composites for the extraction of neonicotinoid insecticides from environmental water samples

MOF-199/Fe3O4 nanoparticles were explored for the first time to purify environmental water samples and adsorb neonicotinoid insecticides as hybrid adsorbents. The composites were successfully synthesized by an in situ method at room temperature with electrostatic interaction to chemically stabilize the nanoparticles and metal ions. The nanoparticles were uniformly encoded with metal organic frameworks (MOFs). With the lowest loading amount of Fe3O4 applied to magnetic solid-phase extraction (MSPE) of six neonicotinoid insecticides in environmental water samples followed by high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) analysis, the extraction efficiency was the highest. The main influencing factors including the solution ionic strength, solution pH, extraction time, desorbing organic solvent, and solvent volume, were also evaluated. Considering the adsorbing conditions and insecticide structures, the adsorbing mechanism was preliminarily discovered to be largely dependent upon the π–π interaction with the benzene ring in MOF-199 and delocalized large π bonds in the insecticide molecules. Under optimal conditions, the limits of detection (LODs) were 0.3–1.5 ng mL−1 with a signal-to-noise ratio (S/N) of 3. All the analytes exhibited good linearity with correlation coefficients (r2) of higher than 0.9947. The relative standard deviations (RSDs) for six neonicotinoid insecticides in environmental samples in five replicates ranged from 1.5% to 11.6%, and good recoveries from 88.0% to 107.0% were obtained, indicating that the MOF-199/Fe3O4 composites are feasible for analysis of trace analytes in environmental water samples.
RF Plasma Modification of Supported Pt Catalysts for CO2-CH4 Reforming

Numerous studies dealing with CO2/CH4 reforming have been recently published. Edwards and Maitra (1), in a detailed review, have suggested that further catalyst development is the major hurdle before this reforming can be widely commercialized. Literature shows that the supported Group VIII elements in their reduced forms, especially Ni, Co, Ru, Rh, Pd, Ir and Pt, are active for CO2/CH4 reforming. Among these metals, Ni, Pt, Ru and Rh are the most studied elements.
Modeling the influence of the composition of refractory elements on the heat resistance of nickel alloys by a deep learning artificial neural network

Nickel alloys are widely used in the manufacture of gas turbine parts. The alloys show resistance to mechanical and chemical degradation under prolonged loads and high temperatures. The properties of an alloy are determined by its composition and are subject to careful modeling. A set of basic refractory elements makes a special contribution to the parameters of the alloy. One of the main mechanical properties of the alloys is the high‐temperature tensile strength. Determining the influence of certain elements on certain properties of an alloy is a complex scientific and engineering problem that affects the time and cost of developing new materials. Simulation is a great chance to cut costs. In this article, we predict high temperature strength based on the composition of refractory elements in alloys using a specially designed deep learning artificial neural network. We build the model based on prior knowledge of alloy composition, information on the role of alloying elements, type of crystallization, test temperature and time, and tensile strength. Successful simulation results show the applicability of this method in practice.
Resource Offload Consolidation Based on Deep-Reinforcement Learning Approach in Cyber-Physical Systems

In cyber-physical systems, it is advantageous to leverage cloud with edge resources to distribute the workload for processing and computing user data at the point of generation. Services offered by cloud are not flexible enough against variations in the size of underlying data, which leads to increased latency, violation of deadline and higher cost. On the other hand, resolving above-mentioned issues with edge devices with limited resources is also challenging. In this work, a novel reinforcement learning algorithm, Capacity-Cost Ratio-Reinforcement Learning (CCR-RL), is proposed which considers both resource utilization and cost for the target cyber-physical systems. In CCR-RL, the task offloading decision is made considering data arrival rate, edge device computation power, and underlying transmission capacity. Then, a deep learning model is created to allocate resources based on the underlying communication and computation rate. Moreover, new algorithms are proposed to regulate the allocation of communication and computation resources for the workload among edge devices and edge servers. The simulation results demonstrate that the proposed method can achieve a minimal latency and a reduced processing cost compared to the state-of-the-art schemes.
Ethical leadership in organizations: evidence from the field

Owing to the significant and critical role of ethical leadership in organizations, this study aims to explore and understand the perceptions about ethical leadership in organizations. It empirically investigates whether the individual attributes of gender, age, work experience, executive level and qualification of members and other demographic variables, such as industry and sector, affect the perception of members toward ethical conduct of their supervisors. ,This is a quantitative study where the analysis is based on the data collected from 419 members of 3 different industries, namely, public sector research and development organizations, information technology organizations and academic universities and colleges. ,The results reveal that perception of ethical leadership does not vary across gender and qualification of members but varies across age, work experience, management level, industry and sector. ,This study helps to understand the importance and role of various individual attributes that affect the perception of ethical leadership by followers. This study will make leaders to be more aware and behave in ethical manner with respect to different groups of followers. ,Because of occurrence of many scandals and fraudulent behaviors in organizations, business ethics has caught the attention of policy makers, corporate organizations and academic. Ethical leadership is very crucial for organizational success on a sustainable basis. To the best of authors’ knowledge, this study is among the early studies conducted to investigate the influence of the individual attributes and other demographic variables on the perception of members toward ethical conduct of their supervisors.
Messengers of the Universe-Cosmic Rays Exploring Supermassive Black Holes

Cosmic rays were discovered over one hundred years ago but there are still unsolved problems. One of the hot problems is the origin of cosmic rays of the highest energies. Sources are still unclear and it is neither clear how particles gain ultra-high energies. Possible sources of cosmic rays at the highest energies are supermassive black holes. From this perspective we discuss in a popular form some recent developments in cosmic ray studies along with author’s recent results. The paper also offers materials for further reading.
Comparative study of single and multi domain CVD graphene using large‐area Raman mapping and electrical transport characterization

We systematically investigate the impact of granularity in CVD graphene films by performing Raman mapping and electrical characterization of single (SD) and multi domain (MD) graphene. In order to elucidate the quality of the graphene film, we study its regional variations using large‐area Raman mapping and compare the G and 2D peak positions of as‐transferred chemical vapor deposited (CVD) graphene on SiO2 substrate. We find a similar upshift in wavenumber in both SD and MD graphene in comparison to freshly exfoliated graphene. In our case, doping could play the dominant role behind the observation of such upshifts rather than the influence due to strain. Interestingly, the impact of the polymer‐assisted wet transfer process is the same in both the CVD graphene types. The electrical characterization shows that SD graphene exhibits a substantially higher (a factor 5) field‐effect mobility when compared to MD graphene. We attribute the low sheet resistance and mobility enhancement to a decrease in charge carrier scattering thanks to a reduction of the number of grain boundaries and defects in SD graphene.
Influence of Consumer Buying Orientation and Pro-environmental Values on their Willingness to Patronise Green Hotels

Objective – Based on the theory of planned behaviour, this study empirically investigated and significantly validated the relationship among hedonistic buying orientation, utilitarian buying orientation, pro-environmental orientation. and willingness to patronise green hotels. Methodology/Technique – This quantitative study used the survey technique in data collection among hotel customers. 208 online surveys were gathered for data analysis. Sem-pls was used to analyse the hypothesised objectives. Findings – The findings indicated that pro-environmental values, hedonistic buying orientation and utilitarian buying orientation all have a positive and significant relationship with their willingness to patronise green hotels. Novelty - The value of this study lies in the novel use of consumer buying orientation as a predictive factor of consumers’ willingness to patronise green hotels, and to the best of the authors knowledge, it is among the first to empirically test such relationship. This study is useful to key stakeholders in the hospitality sector and managers of hotels to understand consumers pro-environmental patronage. Type of Paper: Empirical. JEL Classification: M31, M39. Keywords: Consumer Buying Orientation; Willingness to Patronise Green Hotel; Pro-Environmental Value. Reference to this paper should be made as follows: Nimo, C.A, Agyapong, G.K. Q; Ofori, D. (2020). Influence of Consumer Buying Orientation and Pro-environmental Values on their Willingness to Patronise Green Hotels, J. Mgt. Mkt. Review, 5(4) 251 – 259. https://doi.org/10.35609/jmmr.2020. 5.4(7)
Chemical and homogeneity changes of a Nafion membrane surface associated to its doping with the cation of the room‐temperature ionic liquid AliquatCl

Chemical and textural changes in a commercial Nafion‐112 membrane as a result of its doping with the cation of the room temperature ionic liquid (RTIL) tricaprylmethylammonium chloride (Aliquat+) are analysed by X‐ray photoelectron spectroscopy (XPS), contact angle and atomic force microscopy (AFM). The XPS results show changes in the membrane surface as a result of partial coverage by the RTIL‐cation, taking into account the increase in the doped sample surface of the atomic concentration percentage of nitrogen (Aliquat+ characteristic element) and the reduction in the percentage of fluorine (Nafion characteristic element), as well as the reorientation of the sulfonic groups. Nafion surface modification also causes a decrease in the hydrophobic character according to water contact angle values. Moreover, the AFM measurements demonstrate an increase in the surface roughness of the doped membrane, and the presence of clusters of different shapes and sizes, being consistent with a rearrangement of the Nafion surface, in agreement with XPS results. Copyright © 2016 John Wiley & Sons, Ltd.
Multiple MIMO with Joint Block Antenna Number Modulation and Adaptive Antenna Selection for Future Wireless Systems

Multiple MIMO with joint block Antenna Number Modulation (M-MIMO-ANM) is proposed in this paper as a novel transmission method that exploits the features of both Massive Multiple Input Multiple Output (M-MIMO) and Antenna Number Modulation (ANM) concepts. In this scheme, the main purpose is to increase the number of additionally transmitted data bits, which are sent without any consumption in the bandwidth. To achieve this, the antenna elements of a large array are divided into blocks, whose numbers are utilized to convey additional data bits along with those bits sent by the number of antenna elements within each block as well as those sent by conventional modulation schemes (e.g., BPSK). The implementation of M-MIMO-ANM scheme relies on the idea of dividing the whole antenna array into blocks, where each block corresponds to a group of bits depending on the total number of available blocks, thus ANM concept is applied not only to the antennas within each block but also to the blocks forming the entire antenna array. This creates an opportunity to convey even more additional data bits, compared with the conventional ANM scheme, while there is a noticeable improvement in the reliability of data transmission. With all these dynamics, M-MIMO-ANM concept is a candidate to create a new perspective to the Internet of Things (IoT) applications, with its energy efficient, spectrum efficient, robust, and both data and channel dependent data transmission nature that comes from the properties of Massive MIMO and ANM. The introduced system is investigated, and its validity is proven, where analytical and simulation results in terms of the bit error rate (BER) and throughput of the system are given. The numerical computer simulations furthermore compare the performances of M-MIMO-ANM with MIMO-ANM to show its superiority, and the advantages of the concept are discussed. M-MIMO-ANM is promising a highly reliable and resilient system thanks to its cascaded simultaneous bit transmission by the different number of both antenna blocks and antenna elements within each block.