Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Rural Innovation and Sustainability Through Impact Assessment: A Review of Methods and Tools

Assessing impacts in innovation contexts/settings with the aim of fostering sustainability requires tackling complex issues. Literature shows that key sources of this complexity relate to the need to integrate the local context; identify the underlying problems; engage key stakeholders; and reflect on their feedback throughout the innovation process. A systematic literature review on innovation impact assessment reveals that social impacts have been the most studied, thus, where promising methods and tools were used. Nevertheless, there are many unresolved issues beyond assessing social impacts in innovation processes. Literature highlights that building on co-creating innovation processes that respond to stakeholders’ real needs and context, and adapting to changing circumstances by integrating timely feedback from stakeholders are two critical challenges calling for a systems thinking approach. This study proposes Developmental Evaluation (DE) as a systemic approach to evaluation which supports adaptive development in complex environments and that adds value by integrating continuous feedback from diverse stakeholders. As a non-prescriptive evaluation approach in terms of methods and tools, DE can provide meaningful guidance to use diverse methods and tools in furthering ongoing development and adaptation in innovation processes by linking the evaluation activities—impact assessment among them—with the DE principles that are situational, adaptive and continuously responsive.
Mitigating Turnover with Code Review Recommendation: Balancing Expertise, Workload, and Knowledge Distribution

Developer turnover is inevitable on software projects and leads to knowledge loss, a reduction in productivity, and an increase in defects. Mitigation strategies to deal with turnover tend to disrupt and increase workloads for developers. In this work, we suggest that through code review recommendation we can distribute knowledge and mitigate turnover with minimal impact on the development process. We evaluate review recommenders in the context of ensuring expertise during review, Expertise, reducing the review workload of the core team, CoreWorkload, and reducing the Files at Risk to turnover, FaR. We find that prior work that assigns reviewers based on file ownership concentrates knowledge on a small group of core developers increasing risk of knowledge loss from turnover by up to 65%. We propose learning and retention aware review recommenders that when combined are effective at reducing the risk of turnover by −29% but they unacceptably reduce the overall expertise during reviews by −26%. We develop the Sofia recommender that suggests experts when none of the files under review are hoarded by developers, but distributes knowledge when files are at risk. In this way, we are able to simultaneously increase expertise during review with a $\Delta$ Expertise of 6%, with a negligible impact on workload of $\Delta$ CoreWorkload of 0.09%, and reduce the files at risk by $\Delta$ FaR −28%. Sofia is integrated into GitHub pull requests allowing developers to select an appropriate expert or “learner” based on the context of the review. We release the Sofia bot as well as the code and data for replication purposes.
BURDEN OF STROKE SURVIVORS ON CAREGIVER AND QUALITY OF LIFE

Aim: To assess level of burden and quality of life of caregivers of stroke survivors. Material survivors. Data were collected by demographic proforma, WHOQOL and Zarit Burden Interview (ZBI) questionnaire to assess level of burden of caregivers. Results: main component of burden was relationship and emotional well quality of life, all the domain were equally effected, while physical was a significant negative correlation between quality of life and burden scores of caregivers.
ELECTRICITY INFRASTRUCTURE AS AN IMPEDIMENT TO DIGITAL ECONOMY AND ECONOMIC GROWTH IN NIGERIA: AN EMPIRICAL ANALYSIS Obiamaka P. Department of Banking and Finance, University of Nigeria

Infrastructure determines the flexibility of a system to meet future requirements for the purposes of being efficient and productive. Electricity Infrastructure is a great force that drives industrialization. Electric Power supply in Nigeria becomes very c Unfortunately, one characterized by frequent power failures and load shedding. This Paper reveals the importance of Power Infrastructural develo and economic growth in Nigeria. It shows the relationship between economic growth and power infrastructural development as one of the key factors to attain a cashless economy. This st used annual time series variables computed from natural logarithms of gross domestic product (GDP) at current price and electricity production from 1971 to 2008, that is a period of 38years. It was revealed that there exist a long Also a short (ELECPRO) to economic growth (GDP). We therefore recommend that the government should to do all it takes in other to improve on the improving the status of digital economy in Nigeria.
Modeling in Biology: looking backward and looking forward

Understanding modeling in biology requires understanding how biology is organized as a discipline and how this organization influences the research practices of biologists. Biology includes a wide range of sub-disciplines, such as cell biology, population biology, evolutionary biology, molecular biology, and systems biology among others. Biologists in sub-disciplines such as cell, molecular, and systems biology believe that the use of a few experimental models allows them to discover biological universals, whereas biologists in sub-disciplines such as ecology and evolutionary biology believe that the use of many different experimental and mathematical models is necessary in order to do this. Many practitioners of both approaches misunderstand best practices of modeling, especially those related to model testing. We stress the need for biologists to better engage with best practices and for philosophers of biology providing normative guidance for biologists to better engage with current developments in biology. This is especially important as biology transitions from a “data-poor” to a “data-rich” discipline. If 21st century biology is going to capitalize on the unprecedented availability of ecological, evolutionary, and molecular data, of computational resources, and of mathematical and statistical tools, biologists will need a better understanding of what modeling is and can be.
Agriculture Supply Chain Traceability System Based on Blockchain

In recent years, the globalized production and distribution of agriculture products have drawn focus on quality, safety and the validation of some important criteria in agriculture supply chains. Today’s agriculture supply chains are complex systems involving some stakeholders to validate some important criteria such as monitoring yields, stages in crop development, quality standards of crops. Since the traditional pattern of agriculture logistics cannot match the demands of the market, building an agriculture supply chain traceability system is becoming more urgent. There is a number of growing issues related to food safety so there is a need for an effective traceability solution that acts as a quality management tool to ensure the safety of products in the agriculture supply chain system. In this paper, we propose an approach of Blockchain, Ethereum, and smart contracts to perform efficiently of business transactions of crop tracking and traceability in the agriculture supply chain system. In our proposed solution we can realize the traceability of crops with trusted information in the entire agriculture supply chain system, which will eliminate the need for intermediaries and centralized authority. Thus, it provides high-level traceability and transparency in the agriculture supply chain system in a trusted, secure, reliable and efficient manner.
A New Species of Heterelmis from Texas (Coleoptera: Elmidae)

Heterelmis comalensis new species is described from Comal Springs, one of the headwaters of the Comal River, in New Braunfels, Texas. It is apparently endemic, hind wings brachypterous, and smaller in size than any other species known from the United States (1.7 to 2.1 mm in length, 0.8 to 0.91 mm in breadth). It is closest to Heterelmis glabra (Horn) from which it differs in body contour and in size, H. glabra being 1.9 to 2.35 mm long and 1.0 to 1.17 mm wide. The genus Heterelmis Sharp 1882 is primarily neotropical, with 13 species scattered throughout much of South and Central America (Brown, 1981). One of these, Heterelmis obesa, ranges northward into mountainous sections of the western United States, and three additional species, Heterelmis glabra, Heterelmis stephani, and Heterelmis vulnerata, also occur in the western states (Brown, 1983). In Texas, H. obesa is known from the Guadalupe Mountains and H. glabra from the Rio Grande, but H. vulnerata is widespread (Burke, 1963; Brown, 1972). We here describe a new species from the headwaters of the Comal River in New Braunfels, Texas. Heterelmis comalensis, new species
TEXT RECOGNITION IN PCBS: AN OBJECT CHARACTER RECOGNITION (OCR) ALGORITHM

The Optical Character Recognition (OCR), together with another inspection techniques, is the mostly method utilized in the PCB industry. This work have as objective to identify text characters in five main PCBs template samples. Further, through a “Guide User Interface” (GUI) developed in MATLAB software, estimate the parameters as the quantity of detected texts, plot the graphic with the mean time average, and classifying the text character detected. Results showing the efficacy detection capacity of the OCR algorithm also are described in this work.
Numerical investigation of fin geometry on the air-side heat transfer and pressure drop characteristics of heat exchangers using in-line rectangular microchannels

The objectives of this research is to investigate the effect of different fin geometries on the performances of a microchannel heat exchanger, using CFD simulations. The fin profiles include straight fins, triangular fins, wavy fins and offset fins. For each fin geometry, air-side heat transfer and pressure drop correlations were developed and defined in terms of Colburn j-factor and Fanning f-factor. The microchannels are square 2.00 mm x 2.00 mm and placed in-line by 4.50 mm longitudinal tube pitch. The transverse tube pitch and the fin pitch were varied from 9.00 mm to 19.00 mm and 2.50 mm to 10.00 mm respectively, to investigate their influences on the heat exchanger performances. Furthermore, the complete thermal and hydraulic fully developed flow was covered using one CFD simulation, allowing to extract heat transfer and pressure drop characteristics for any number of channels. The results show that the offset fins present the best performances, in term of volume goodness factor, compared to all geometries. Using offset fins offers better heat transfer capability at a lower volume, which is beneficial in the need of reducing charge for refrigeration systems.
Evaluating the Benefits of Team-Based Learning in a Systems Programming Class

In this Research-to-Practice Full Paper, we present the results of adopting Team-Based Learning (TBL) for teaching a Sophomore-level Systems Programming course. The goal of TBL is to "provide opportunities for students to apply their knowledge in the classroom to solve problems rather than just covering content. " Based on the performance of the students in the course taught with TBL, we found that TBL had a statistically significant impact on student performance in 2 of the 5 programming assignments. Additionally, the end-of-semester student survey indicated that 88% of the students said that the team-based learning activities helped them understand the material better. Students mentioned that they felt like they belonged in Computer Science (fostering a sense of community in large classrooms) and frequently studied with some of their team members for the course assignments. Compared to a previous offering of the course that was purely lecture-based, the class as a whole received higher final grades and performed better on all of the programming assignments.
The Effect Of The Lifestyle, Exercise, And Nutrition (lean) Study On Alcohol Consumption Among Breast Cancer Survivors

Background Alcohol use is an established risk factor for the development of breast cancer. Additionally, there is evidence that consuming alcohol increases the risk of breast cancer recurrence among survivors. A randomized controlled weight loss intervention called the Lifestyle, Exercise, and Nutrition (LEAN) Study resulted in clinically meaningful weight loss and improvements in aspects of diet among a population of breast cancer survivors. Since the LEAN intervention included some content related to alcohol consumption, we hypothesized that the LEAN intervention would result in a reduction in alcohol consumption at 6 months. Methods A total of 151 overweight and obese breast cancer survivors, who had been diagnosed with Stage 0 to III breast cancer in the last 5 years, had completed chemotherapy and/or radiation, and had a BMI greater than 25, were randomized in the 6-month LEAN study to either the weight loss intervention or usual care. Alcohol consumption was assessed for the analytic sample size of 123 women via a dietary questionnaire at baseline and 6-months. t-tests were used to determine change in g/day of alcohol by group and McNemar’s test was used to determine change in the proportion of non-drinkers and drinkers. All statistical analyses were conducted in SAS Version 9.4. Results Of the 123 women in the analytic sample size, the intervention group (n=73) had a mean age of 59.0 ± 7.0 years, and a mean BMI of 32.3 ± 6.1 kg/m, while the control group (n=50) had a mean age of 56.9 ± 7.8 years, and a mean BMI of 34.3 ± 6.8 kg/m. The population was mostly white and highly educated. At baseline, the mean grams of alcohol consumed per day were 8.1 ± 14.4 g/day among the intervention group, and 7.7 ± 12.2 g/day among the control group. The mean change in the grams of alcohol consumed per day was -0.5 ± 8.5 g/day among the intervention group, and +0.2 ± 13.2 g/day among the control group, but this difference was
A multivariate statistical approach for ranking the best batsmen in test cricket

The primary objective of this paper is to devise a ranking system for individual test batsmen (from different eras) considering all possible factors like the difficulty of opposition bowlers, the batsman’s consistency, the contribution of the batsman in the success of his team, the era in which he played, etc. Due to the presence of such numerous factors—each one of them having a significance of its own, it is imperative that a multivariate statistical approach is employed in the ranking of Test batsmen. A total of eight factors were zeroed in on which were thought to influence the performance of a batsman. An index was developed for each of the eight factors, and thus each of the batsmen got eight different scores for the eight different factors. Consequently, the eight scores of the batsman act as the coordinates of a point/cluster in an eight-dimensional plane. In this way, each of the batsmen under study is represented by a point in an eight-dimensional plane. Finally, to determine the most exceptional batsmen among the batsmen under study, the concept of multivariate statistical outlier detection using Mahalanobis distances was used. However, the concept of Outlier Detection only gives us an idea of the most exceptional batsmen when compared to the others. In order to determine the best batsmen, the process of outlier detection is followed up with the determination of the efficiencies of each of the batsmen under study. The efficiencies of the batsmen are calculated by adopting the approach of Data Envelopment Analysis (DEA), wherein each batsman is likened to a machine or a Decision-Making Unit (DMU). The higher the efficiency of a batsman, the greater his success in converting low inputs (difficult input parameters) to high outputs.
Questioning the Use of Bilingual Lexicon Induction as an Evaluation Task for Bilingual Word Embeddings

Word embeddings have been shown useful in a wide range of natural language processing tasks. Recently, many methods have been proposed to transform monolingual word embeddings into bilingual word embeddings (BWE), relying on a small seed bilingual lexicon as a weak supervision (Mikolov et al., 2013). More recently, unsupervised methods, i.e., that do not use bilingual resources for training, have also been proposed (Artetxe et al., 2017; Lample et al., 2018). Most of the methods for learning BWE are evaluated through bilingual lexicon induction (BLI) tasks, where a test set comprises 1k–3k source words each paired with one or several correct word translations in the target language. For each source word, a translation is retrieved from the target language vocabulary relying only on the BWE to be evaluated. Then, the accuracy of the retrieval, i.e., the percentage of source words for which one of the correct word translations has been retrieved, is computed as a quality measure of the BWE. Previous work on BWE has claimed the superiority of a method for learning BWE if its accuracy is higher than other evaluated methods. BLI remains the most used evaluation task since the work by Mikolov et al. (2013), mainly because of its low computational cost and the relatively low cost of creating many test sets for several language pairs. In this paper, we focus on assessing how general are the conclusions drawn from BLI-based evaluations of BWE. The purpose of this paper is to shed light on the limits of current practices rather than proposing alternative evaluation methods or finding which BWE performs the best. We re-evaluate nine methods for learning BWE through BLI tasks with various experimental settings varying in the test set, the monolingual word embeddings to transform, and the method for retrieving word translations. These are independent of the methods used for training BWE. In other words, the methods and their parameters remain unchanged across our experiments. Through our experiments to highlight the significant limits of evaluating BWE on BLI tasks, we identify several incorrect practices, such as the use of inconsistent evaluation settings. One of our most surprising findings is that the seminal work by Mikolov et al. (2013) still remains a very competitive method for BLI.
DHANILA V. PARBOTEEAH-ALEX Affiliation Eastern New Mexico University, United States

Generation Y (Gen Y) dominates the Internet-using population. Their personal values and attitudes are crafted through online interactions. One such societal value is materialism, which determines how individuals regard material possession and its importance in life. Environmental factors such as interpersonal communication can influence materialism and are facilitated by the Internet and social media, making Gen Ys more susceptible to materialism. Thus, there is a need to understand Gen Y’s Internet usage and its linkage to materialism in an effort to address the adverse effects of materialism on their personal well-being. A survey methodology was used to collect data from students from four Southwestern and Northeastern American universities. Pearson r correlations and t-test analyses were performed for hypothesis testing. Technology was found to allow societal values to be evenly shared among the Internet-using Gen Y without geographic limitations. Further, materialistic Gen Ys spend more time browsing websites looking for products/services. Implications are discussed in relation to educating Gen Ys about the influences of environmental factors on materialism and to thinking more consciously about consumption.
Augmented visual phrase in mobile product recognition

With the rapid advancement in mobile device technologies and connectivity, the use of mobile devices for visual object recognition is emerging as an application with great commercialization potentials. However, query images captured by mobile devices often suffer from various conditions such as illumination, scale, and viewpoint changes. To handle these, several detectors and descriptors have been proposed. However, recognition remains a challenge under strong photometric or geometric variation. In view of this, we propose a new Augmented Visual Phrase (AVP) framework that addresses this issue by using augmented features from transformed images. We propose a recognition framework based on the Bag of Phrase (BoP) structure which in turn is built on the Bag of Words (BoW) model. The proposed method can provide better performance by incorporating the spatial relationship of visual elements detected by keypoint detectors. To further eliminate spurious matches of visual phrases, Geometric Verification (GV) is applied to the top-ranked images. Experimental results show that the proposed AVP method outperforms the current BoP method by 9% in recognition rate.
A Study on Entrepreneurial Orientation and Startup Performance: The Moderating Effect of Social Responsibility Orientation

This study aims at examining the effect of Entrepreneurial orientation on startup performance and analyzing the moderating effect of social responsibility orientation in the relationship. To confirm this, an empirical study was conducted on 99 startups residing in startup support organizations, etc., and the suitability of the research model was evaluated using PLS-SEM. As a result of confirming the moderate role of the Social responsibility orientation in the relationship between Entrepreneurial orientation and firm performance, it was confirmed that the Entrepreneurial orientation played a role of positive role. In addition, it was confirmed that the Social responsibility orientation does play a positive moderating role in the relationship between Entrepreneurial orientation and firm performance. The results of this study are expected to present the direction of management of enterprises in the future by confirming the moderating effect of social responsibility orientation, which is considered more important in the management of enterprises in modern society, and which cannot be excluded.
Mimetic Finite Difference Modeling Of 2D Elastic P-SV Wave Propagation

Recently, efforts have been made by Kristek et al.(2002) toward the implementation of a zero-traction boundary condition for an elastic medium by using high-order staggered-grid finite-difference modeling and avoiding symmetry conditions, vacuum formulations, or, other approaches that require grid points located beyond the physical boundary (ghost points). In this work, a new set of numerical differentiators known as “mimetic” finite differences have been used to explicitly solve the exact boundary conditions and fully compute the displacement vector along a planar free surface of a 2D half space. No ghost points are used in our schemes. Two classical grids, the rotated staggered grid (RSG) and the standard staggered grid (SSG), have been enhanced by the inclusion of Compound nodes along the free surface boundary to allow this discretization process and place the displacement vector. Thus, three new algorithms are proposed here, one that works over a RSG, and two implemented using a SSG. Accuracy of these solvers is measured in terms of the dispersion of the numerical Rayleigh wave, and comparisons against Kristek et al.’s algorithm are presented.