Miracle-dz/UniFAR-FTUs huggingface dataset:
Green Synthesis of Reduced Graphene Oxide Using Ascorbic Acid

A green and low-cost method was used to prepare graphene oxide (GO) and reduced graphene oxide (rGO) by chemical exfoliation of graphite powder by modified Hummers method, followed by reduction using ascorbic acid. X-ray diffractometry (XRD) and field emission scanning electron microscopy (FE-SEM) were used to analyze the structure and morphology of the synthesized materials. Fourier transform infrared spectroscopy (FTIR) and ultraviolet-visible spectroscopy were used to identify the formation of the GO and rGO
Using Analog Ensembles with Alternative Metrics for Hindcasting with Multistations

This study concerns the problem of making weather predictions for a location where no data is available, using meteorological datasets from nearby stations. The hindcast with multiple stations is performed with different variants of the Analog Ensemble (AnEn) method. In addition to the traditional Monache metric used to identify analogs in datasets from one or two stations, several new metrics are explored, namely cosine similarity, normalization and k-means clustering. These were analyzed and benchmarked to find the ones that bring improvements. The best results were obtained with the k-means metric, yielding between 3% and 30% of lower quadratic error when compared against the Monache metric. Also, making the predictors include two stations improved the performance of the hindcast, leading up to 16% of lower error, depending on the correlation between the predictor stations.
How does an Intelligence Chatbot Affect Customers Compared with Self-Service Technology for Sustainable Services?

To gain competitive advantages and sustainable service innovation, hotels are considering artificial intelligence technologies (AI), including robots, kiosks for service automation and chatbots. However, due to the change of the service process and unfamiliar communication interface, hotel customers may have difficulties in adopting the new change. In this paper, we tried to find out if the failure of AI-based services would affect customers’ perception. For this, we designed the experiment by separating AI (i.e., chatbot) services and self-service technology (SST, i.e., pad) services and service failures and successful cases, respectively. As a result, SST showed more positive perceptions and revisit intention in the successful service situation. The service failure situation showed no differences between chatbot and SST. In addition, novelty and the need for interaction characteristics of customers showed significant differences between groups in terms of service success and failure, respectively. Additionally, we explored negative word-of-mouth (WOM) to learn further effects by service failures and successes.
Azospirillum brasilense Can Impressively Improve Growth and Development of Urochloa brizantha under Irrigation

Development of strategies to ensure grazing systems are sustainably produced in harsh environments, while not fertilizing them conventionally, is challenging. Figuring out the extent to which dose of inoculation and period of watering can positively influence the establishment of an effective symbiosis between U. brizantha cv. Marandu and Azospirillum brasilense is the point of this research. The treatment consisted of mixing 1 kg seeds with the inoculant of the strains Ab-V5 and Ab-V6 at 5, 10, 20, and 40 mL kg−1, 2 × 108 CFU mL−1. The plants grew in pots watered 2, 4, 8, and 16 days after sowing over thirty-days, twice. The bioagent at 5–10 mL kg−1 enabled the plants watered up to 4 days after sowing to peak the production of dry mass of shoots (28.50 g) and roots (12.55 g). The efficiency of the symbiosis goes down quickly with increasing dose and delay of watering. Hence, if the dose of inoculant is higher than 10 mL kg−1, it cannot successfully act in plants watered at least 8 days after sowing anymore. In conclusion, A. brasilense can assist in U. brizantha cv. Marandu growth and healthy development unless a lack of water in the substrate and an overdose collectively deter its potential.
PTSD symptoms in religious leaders: Prevalence, stressors, and associations with narcissism

Religious leaders face numerous mental health challenges, and prior research suggests that some experience symptoms of post-traumatic stress disorder (PTSD) due to work-related experiences. This study employed a diverse sample of 274 religious leaders to (a) qualitatively describe the types of work-related experiences they identify as particularly stressful or overwhelming, (b) assess the prevalence of PTSD symptoms associated with these experiences, and (c) test hypothesized associations between PTSD symptoms and narcissism. The study found that the stressful experiences reported typically involved relational conflict, having limited resources, or caring for people suffering. Over half of the sample endorsed symptoms that were above the cutoff for a clinical concern for PTSD, and PTSD symptoms were significantly associated with symptoms of both vulnerable narcissism and grandiose narcissism. Practical implications for the ongoing formation and support of religious leaders are discussed.
Examining middle school teachers’ implementation of a technology-enriched problem-based learning program: Motivational factors, challenges, and strategies

Abstract Literature has documented the benefits of problem-based learning (PBL), but also shown significant barriers to using PBL in K–12 education. Yet, the research describing why and how K–12 teachers implement PBL is insufficient. In this qualitative study, using semi-structured interviews, we investigate why 25 middle school teachers chose to implement a technology-enriched PBL program, challenges they encountered, and facilitation strategies they used to address those challenges. The findings of this study showed that teachers were motivated not only by PBL's alignment with their beliefs, but by their students' positive learning outcomes. The interviews revealed two significant pedagogical challenges for teachers: (a) knowing when to let go of control as opposed to when to step in to facilitate, and (b) determining how to provide additional support to students with special needs. Nine types of facilitation strategies to deal with these challenges were identified.
Effects of alien substitutions of chromosomes of homoeologous group 7 on the heading time of wheat–barley substitution lines (Triticum aestivum L. – Hordeum marinum ssp. gussoneanum 4x Hudson)

The effects of alien substitutions of chromosomes on the heading time of ditelosomic (DT) wheat–barley substitution lines in which the chromosome 7HLᵐᵃʳ from Hordeum marinum ssp. gussoneanum 4x replaced the chromosomes 7A, 7B and 7D of common wheat were studied. The plants were grown under short and long day illumination in greenhouse and in the field. The lines studied were found to differ in response to the length of the day. Under short day conditions, DT7HLᵐᵃʳ(7B) and DT7HLᵐᵃʳ(7A) showed an increase in the period before heading. In this case, the substitution effect of chromosome 7B was more significant than the effect of chromosome 7A. Under these conditions, the substitution of chromosome 7D did not have a significant effect on the heading time. Under long day conditions in the greenhouse and under natural conditions of a long day in the Novosibirsk region, substitution lines came into ear earlier than under a short day conditions and did not differ in the heading time. Allele-specific primers established the allelic composition of the genes Vrn-A1, Vrn-B1, Vrn-D1 and Vrn-B3 in ditelosomic lines. It was shown that the two DT7HLᵐᵃʳ(7A) and DT7HLᵐᵃʳ(7D) lines have the same genotype -VRN-A1b/VRN-B1c/vrn-D1/ vrn-B3 and that the DT7HLᵐᵃʳ(7B) line has the genotype -VRN-A1a/VRN-B1c/vrn-D1. The results show that regardless of the genotype for the Vrn genes, the wheat-barley substitution lines react to the change in the photoperiod, especially in the absence of chromosomes 7B and 7A.
Secure and communications‐efficient collaborative prognosis

: Collaborative prognosis is a technique that is used to enable assets to improve their ability to predict failures by learning from the failures of similar other assets. This is typically made possible by enabling the assets to communicate with each other. The key enabler of current collaborative prognosis techniques is that they require assets to share their sensor data and failure information between each other, which might be a major constraint due to commercial sensitivities, especially when the assets belong to different companies. This study uses federated learning to address this issue and examines whether this technique will enable collaborative prognosis while ensuring sensitive operational data is not shared between organisational boundaries. An example implementation is demonstrated for the prognosis of a simulated turbofan fleet, where federated averaging algorithm is used as an alternative for the data exchange step. Its performance is compared with a conventional collaborative prognosis that involves failure data exchange. The results confirm that federated averaging retains the performance of conventional collaborative prognosis while eliminating the exchange of failure data within assets. This removes a critical hindrance in industrial adoption of collaborative prognosis, thus enhancing the potential of predictive maintenance.
Improving ICT and renewable energy for environmental sustainability in sub-Saharan Africa

The study investigates the role of information and communication technology (ICT) and renewable energy on environmental sustainability in sub-Saharan Africa. The system generalized method of moments (GMM) was employed to estimate data of 45 sub-Saharan countries that cover the 2008 -2016 period. Result reveals that increasing ICT penetration and renewable energy use reduce CO2 emissions and improves environmental sustainability. Economic growth and population growth also mitigate CO2 emissions while education and trade openness have a neutral impact. These findings imply that increasing penetration of ICT facilities and renewable energy in the region will promote inclusive environmental sustainability. The interactive estimation of ICT variables was further considered to determine net effects and the ICT threshold that is relevant for policy implication.
Assessing the Importance and Cognition Level of ACCE’s Student Learning Outcomes: Industry, Educator, and Student Perceptions

ABSTRACT In 2014, the American Council for Construction Education (ACCE), the leading accreditation body for construction degree programs, formally approved new student learning outcome (SLO) based standards. As degree programs across the country begin to adopt these guidelines, it is important to assess the ability of these SLOs to address the needed knowledge base for new college graduates. This study is an attempt to gauge perceptions of ACCE’s Bachelor Degree SLOs and identify similarities and/or differences in both topic importance and cognition level recommendations between industry practitioners, faculty, and students. The data indicate that while there is strong alignment within each stakeholder group, there are few areas of agreement on topic importance between groups outside of the top and bottom ranking items. These include the highest importance being assigned to analyzing construction documents for planning and management of construction processes; and, the lowest importance generally being sustainable principles and surveying. The data also indicate that there is generally strong agreement between all stakeholders on the cognition levels for most SLOs. Lastly, the data reveal that there is no correlation between an SLO’s perceived importance and its expected cognition level – an indicator that there is no association between knowledge breadth and depth.
A Multilevel Research on the Factors Influencing Employee Loyalty Under the New Employer Economics

Existing research shows that scholars try to achieve the goal of employee loyalty through human resource management practices at the organization level. However, the new employer economics proposes a tendency from “employer-centered” to “employee-centered”. Through a multi-level research method, this paper used 40 teams and found that employer brands had a significantly positive effect on employee loyalty. Basic psychological needs played a mediating role between employer brand and employee loyalty, but the team identification didn’t mediate the relationship between employer brand and employee loyalty. At last, the moderating role of servant leadership between employer brand and employee loyalty was not proved.
Phylogenetic relationship of Chinese pangolin (Manis pentadactyla aurita) revealed by complete mitochondrial genome

Abstract The Chinese pangolin (Manis pentadactyla) is an extremely endangered species, it has been banned from international trade due to a sharp decline of the population number in China. It is difficult to distinguish among subspecies, thus making it entangled in law enforement. In order to clarify this chaos, we determined and annotated the whole mtDNA genome of the Chinese pangolin. The complete mitogenome is 16 573 bp in length, includeing 13 protein-coding genes, 22 tRNA genes, 2 rRNA genes, and one control region. We built the phylogenetic tree of Chinese pangolinand other 7 most related Manis species.
Declining invasive grey squirrel populations may persist in refugia as native predator recovery reverses squirrel species replacement

1. Invasive species pose one of the most serious global threats to biodiversity. Investigations into the interactions of native and non-native species focus on the impacts of single species, despite being embedded in a network of direct and indirect interactions between multiple species and their environments. 2. We developed 1-km 2 resolution, single-species and multi-species occupancy models using quantitative camera trap data collected by citizen scientists at 332 sites in a regional survey comprising the 14,130 km 2 of Northern Ireland. 3. Recent research suggests that native red and invasive grey squirrels in Britain and Ireland are linked by resource and disease-mediated competition, and by a shared enemy, the European pine marten. We demonstrate that the presence of the pine marten reverses red squirrel replacement by grey squirrels on a regional basis, with red squirrel occupancy positively affected by exposure to pine marten. In contrast, the grey squirrel has a strongly negative response to the presence of pine marten. Modelling habitat suitability of pine marten and both squirrel species suggests that, despite the potentially strong effect of a recovering population of pine martens in controlling grey squirrel distribution, the latter is likely to persist in urban
Dragonfly (Odonata) community structure in the Eastern Highlands Biodiversity Hotspot of Zimbabwe: potential threats of land use changes on freshwater invertebrates

We examined the diversity and potential drivers of dragonfly distribution in a biodiversity hotspot of Southern Africa (Eastern Highlands, Zimbabwe) by surveying 30 sites (13 lentic and 17 lotic habitats) located within this region. Additionally, we identified the anthropogenic factors that may threaten Odonata diversity and abundance. Our results revealed that 27 odonate species are associated with dams and ponds, one species is associated with streams and four species are associated with swamp forests. Considering odonate diversity between protected and unprotected areas, we found significantly higher diversity of odonates in streams in protected areas compared to non-protected areas. Broadly, we found anthropogenic activities (e.g. commercial exotic tree plantations, mining activities, vegetation clearing) possibly affect Odonata diversity (by decreasing abundance and diversity) compared to those within protected and undisturbed habitats. Our results reveal that several human activities like human encroachment into riverine habitats potentially threaten the existence of freshwater species in this biodiversity hotspot and biodiversity hotspots elsewhere.
Real-Time Demand Response Using NB-IoT

The Internet of Things (IoT) already connects billions of devices and keeps growing exponentially. These devices are designed to be integrated with industrial machines, home appliances, and infrastructures. One such use case is to build a smart grid management system that relies on demand-response techniques to control the appliances automatically so that the power can be distributed optimally. The mission-critical smart grid communications require secure, reliable, two-way communicable, and latency bounded connections between the management system and the electrical appliances. To realize these, cellular technology is arguably the most feasible solution. 3GPP has already released the narrowband-IoT (NB-IoT) standards as the low-power dense-area coverage IoT cellular solution. In this article, we present an NB-IoT system to monitor and control the connected electrical appliances in a smart grid network. The platform is also capable of configuring the network dynamically. We assess the latency performance for our solution using the commercially available Orange network in Belgium. It is observed that NB-IoT enabled devices can be controlled and monitored with a maximum latency less than 8 s in the deep-indoor environment and within 2 s for the outdoor environment.
Acquisition target selection and technological relatedness: The moderating role of Top Management Team demographic faultlines

We investigate why some acquirers value targets’ technological relatedness (i.e. similarity and complementarity) more than others. We propose that the importance of technological relatedness as a target selection criterion is influenced by the extent to which an acquirer Top Management Team is divided into subgroups based on managers’ demographic characteristics (i.e. faultlines). That is because an acquirer Top Management Team’s understanding of technological relatedness depends on the team’s information processing capabilities, driven primarily by Top Management Team faultlines. Our analysis of 94 realized acquisitions among 2082 potential acquisition matches in high-technology industries shows that while both technological similarity and complementarity increase the likelihood of an acquisition match, only the impact of technological complementarity is affected by Top Management Team faultlines. Specifically, we find that Top Management Teams with moderately strong divisions between subgroups pay more attention to technological complementarities between their firm and potential acquisition targets than Top Management Teams with very strong or weak divisions.
Mining the Gap: Analysis of Early Mathematics Instructional Quality in Pre-Kindergarten Classrooms

ABSTRACT Research Findings A total of 54 videotaped mathematics activity observations drawn from 27 different pre-kindergarten classrooms in an urban public schools system in the U.S. were coded using 2 observational measures: (a) a general measure, the Classroom Assessment Scoring System (CLASS); and (b) a math-specific measure, the High Impact Strategies in Early Mathematics (HIS-EM). Criterion validity analysis revealed varying levels of convergent and discriminant patterns between the two tools. Indications of these results are twofold: (1) to some extend both tools document the similar aspects of quality of instruction (e.g., instructional support), and (2) a math-specific measure can be more sensitive to document the various levels of mathematics specific instructional support provided during teaching episodes (e.g., math representations, establishment of math learning communities). Results also indicated that the quality of mathematics instruction observed was revealed to be low to medium levels. Practice or Policy: Even though the CLASS may be a useful tool in terms of understanding overall instructional quality, as a subject-specific tool, the HIS-EM might offer a benefit of the multidimensional measure of mathematics teaching quality, which enables the researcher to pinpoint the kinds of strengths that teachers exhibited in math instruction and areas in need of improvement and may assist the field to better identify potential instructional areas to target with professional development.
Extractive Multi-Document Summarization Model Based On Different Integrations of Double Similarity Measures

Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload. Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and defined as a single-objective optimization problem. Also, for improving the performance of the proposed model, different integrations concerning two similarity measures have been introduced and applied to the proposed model along with the single similarity measures that are based on using Cosine, Dice and similarity measures for measuring text similarity. For solving the proposed model, Genetic Algorithm (GA) has been used. Document sets supplied by Document Understanding Conference 2002 ( ) have been used for the proposed system as an evaluation dataset. Also, as an evaluation metric, Recall-Oriented Understudy for Gisting Evaluation ( ) toolkit has been used for performance evaluation of the proposed method. Experimental results have illustrated the positive impact of measuring text similarity using double integration of similarity measures against single similarity measure when applied to the proposed model wherein the best performance in terms of and has been recorded for the integration of Cosine similarity and similarity.
Positioning Accuracy Comparison of GNSS Receivers Used for Mapping and Guidance of Agricultural Machines

Global Navigation Satellite Systems (GNSS) allow the determination of the 3D position of a point on the Earth’s surface by measuring the distance from the receiver antenna to the orbital position of at least four satellites. Selecting and buying a GNSS receiver, depending on farm needs, is the first step for implementing precision agriculture. The aim of this work is to compare the positioning accuracy of four GNSS receivers, different for technical features and working modes: L1/L2 frequency survey-grade Real-Time Kinematic (RTK)-capable Stonex S7-G (S7); L1 frequency RTK-capable Stonex S5 (S5); L1 frequency Thales MobileMapper Pro (TMMP); low-cost L1 frequency Quanum GPS Logger V2 (QLV2). In order to evaluate the positioning accuracy of these receivers, i.e., the distance of the determined points from a reference trajectory, different tests, distinguished by the use or not of Real-Time Kinematic (RTK) differential correction data and/or an external antenna, were carried out. The results show that all satellite receivers tested carried out with the external antenna had an improvement in positioning accuracy. The Thales MobileMapper Pro satellite receiver showed the worst positioning accuracy. The low-cost Quanum GPS Logger V2 receiver surprisingly showed an average positioning error of only 0.550 m. The positioning accuracy of the above-mentioned receiver was slightly worse than that obtained using Stonex S7-G without the external antenna and differential correction (maximum positioning error 0.749 m). However, this accuracy was even better than that recorded using Stonex S5 without differential correction, both with and without the external antenna (average positioning error of 0.962 m and 1.368 m).