Miracle-dz/UniFAR-FTUs huggingface dataset:
Channel Permutations for N: M Sparsity

We introduce channel permutations as a method to maximize the accuracy of N:M sparse networks. N:M sparsity requires N out of M consecutive elements to be zero and has been shown to maintain accuracy for many models and tasks with a simple prune and ﬁne-tune workﬂow. By permuting weight matrices along their channel dimension and adjusting the surrounding layers appropriately, we demonstrate accuracy recovery for even small, parameter-efﬁcient networks, without affecting inference run-time. We also present both a quality metric to simplify judging permutations as well as efﬁcient methods to search for high-quality permutations, including two optimizations to escape local minima. Finally, we share an ablation study to show the importance of each part of our search algorithm, experimental results showing correlation between our quality metric and ﬁnal network accuracy, improved sparse network accuracy using our techniques with insigniﬁcant overhead to training time, and the transformation of unstructured to structured sparse workloads. Code to use these techniques when generating a 2:4 sparse network is available at https://github.com/NVIDIA/apex/tree/master/apex/contrib/sparsity.
Commonality in Manufacturing Resources Planning - Issues and Models: A Review

Purpose – The main purposes of this paper are to enhance the understanding of commonality models in manufacturing resource planning by documenting the current state of affairs and to stimulate fruitful future research by identifying gaps between the relevant issues and the available academic literature. Methodology – This paper is based on a comprehensive review of the articles from authentic publications on resources commonality for the various product mixes and the pertinent models. The papers are analysed to identify the current scenarios and draw future research directions in the area. Findings – The use of common components for different products in a company is important for managing product variety and maintaining competitiveness in this age of mass customisation and supply chain management struggles. The paper finds that the development of a mathematical model to study the effects of commonality in multistage systems with multiple products and multiple common items remains in the virgin area of research. Effects of uncertainty factors on the models are other issues not yet covered in the literature. Experiments and empirical studies in this gap also need further attention. Originality/Value – The contribution of this paper is to provide a summary of the current state of affairs in component commonality and its models and predict the future research trends. This review also focuses on the expanding and complex area of demand, which identifies the issues in the area. [Received 03 October 2008; Revised 27 December 2008; Revised 20 March 2009; Accepted 02 April 2009]
Research on a permanent magnet tubular linear generator for direct drive wave energy conversion

An external tubular linear permanent magnet generator (ETLPMG) is proposed for direct drive wave energy conversion. ETLPMG with quasi-Halbach array is larger in the air gap magnetic flux density than the internal and radial magnetisation one. An assistant tooth and fractional slot are implemented to decrease the detent force. The power density of ETLPMG is about 7–8 times for that of the internal one and the efficiency reached 90.03% at 18 Ω condition. The characteristics of the ETLPMG are analysed with a finite element analysis. Finally, a prototype is manufactured to verify the simulation results by some experiment tests.
Running head: PEER VICTIMIZATION COLLEGE STUDENTS 1 PEER VICTIMIZATION IN COLLEGE SORORITY AND FRATERNITY STUDENTS: THE IMPACT OF GROUP IDENTITY AND CAMPUS

This study examined peer victimization, specifically indirect peer victimization and cyber victimization, in a sample of 311 college fraternity and sorority students at a large, public university in the southwestern United States. Of specific focus was the relationship between peer victimization—both within fraternity and sorority groups and between fraternity and sorority groups and outside members—and co-occurring psychological stress (i.e., anxiety, depression, stress). The potential mediating roles of group identity and campus connectedness were also examined. This study utilized the social psychological theory of Social Identity Theory to predict the relationships between the aforementioned variables. Results indicated that a majority of college fraternity and sorority students (58%) have experienced at least one instance of indirect peer victimization since being initiated into their respective organization. Collectively, the majority of respondents reported low levels of peer victimization and high levels of group identity and campus connectedness. As hypothesized, peer victimization was significantly and positively correlated with stress. In addition, higher ratings of withingroup peer victimization were related to lower ratings of group identity. However, ratings of between-group peer victimization were not significantly related to ratings of group identity, which did not support the hypothesis that there would be a significant and positive correlation between the two. It was also found that campus connectedness mediated the relationship between peer victimization and Stress. Specifically, campus connectedness served as a protective factor from stress. Alternately, group identity did not protect against stress. Lastly, a PEER VICTIMIZATION COLLEGE STUDENTS
Thermodynamic Study of a Cooled Micro Gas Turbine for a Range Extended Electric Vehicle

Carbon dioxide released by the transportation sector has a significant impact on the environment. Nowadays, the research efforts are thoroughly investing in the capability of series hybrid electric vehicles in reducing CO2 and NOX emissions. Many regulations are encouraging automakers to substitute internal combustion engines with electric vehicles. Although the latter are zero-emissions energy sources, they are expensive and have a limited autonomy range. Therefore, recent studies are interested in gas turbines (GTs) in series hybrid electric vehicles (SHEV). A gas turbine (GT) coupled to an alternator is considered as an auxiliary power unit capable of charging the battery of the electric vehicle once depleted. The microturbine is generally composed of a centrifugal compressor and a radial turbine mounted on the same shaft with a recuperator and air bearings. Based on previous researches and thermodynamic analysis, the most suitable gas turbine cycle with regard to the efficiency and the net specific work is composed of two compression stages with an intercooler, a regenerator, and two expansion stages with a reheater. It can be deduced that by increasing the turbine inlet temperature, the system efficiency increases. However, the inlet temperature is limited by turbine materials constraints and specifications. The present paper focuses on developing a more efficient GT cycle by reaching higher inlet temperatures by cooling the turbine blade. It consists of using compressed gas from the compressor and introduce them into the turbine blades. This technology takes into consideration the influence of the extracted mass of compressed air, the effectiveness of the coolant, and the turbine blade temperature on thermal efficiency. An increase of the cycle efficiency of 4.78 points is obtained for a turbine inlet temperature of 1,450 °C.
Online Facility Location with Multiple Advice

Clustering is a central topic in unsupervised learning and its online formulation has received a lot of attention in recent years. In this paper, we study the classic facility location problem in the presence of multiple machine-learned advice. We design an algorithm with provable performance guarantees such that, if the advice is good, it outperforms the best-known online algorithms for the problem, and if it is bad it still matches their performance. We complement our theoretical analysis with an in-depth study of the performance of our algorithm, showing its effectiveness on synthetic and real-world data sets.
Asymmetric of Income, Uneven Adaptive Capacities, and Determinants of Climate Change Adaptation Options among Poor and Non-Poor Rural Rice Farmers of Nepal

This study examines the determinants of adaptive capacities of poor and non-poor rural rice farmers in Nepal. A Cost of Basic Needs (CBN) approach is used to classify rural rice farmers as poor and non-poor, and a binary logistic regression model is used to identify the factors associated with adopting climate change adaptation options. The results show that about 20% of the total respondents in the study area were found to be poor with a moderate level of adaptive capacity. The study finds that poor farmers in rural areas are more vulnerable in terms of adaptive capacity and less able to 130 • Southeast Asian Journal of Economics 9(3), December 2021 adapt climate change adaptation options in comparison to non-poor farmers. It demands immediate action for greater investment, provision of subsidies, and institutional setup to strengthen rural rice farmers’ adaptive capacities.
Effects of Pre ‐ Treatment with GnRH on the Efficiency of Superstimulatory Protocol in Water Buffalo ( Bubalus bubalis )

Livestock sector is an integral component of agriculture farming system and have a pivotal role in the rural economy of India. The water buffalo is a premier dairy animal in India and many other south Asian countries. Poor reproductive performance of buffaloes due to delayed puberty, silent estrus, poor conception rates, long postpartum interval etc. causes heavy economic losses to the livestock farmers. This led to diminishing interest of the farmers in buffalo husbandry as indicated by declining growth rate of buffalo population during the last decade. Amongst the various reproductive biotechniques multiple ovulation embryo transfer technology (MOET) could be a viable option to augment the need of faster genetic gain for making buffalo farming profitable. The suitable superstimulatory and embryo flushing protocols for buffaloes are ideally different from cattle due to differences in species, ovarian follicular population and dynamics; and developmental rate and transport of early embryo. Generally, a greater dose of FSH The multiple ovulation embryo transfer technique (MOET) in buffalo has yielded poor superovulation response due to presence of large/dominant follicle(s) at the start of superstimulatory treatment. The aim of present study was to evaluate the effects of pretreatment with gonadotropin on number of total as well as viable and transferrable embryos recovered during MOET programme in Murrah buffaloes. Buffaloes (n=27) enrolled into two treatment (groups A and B, n=9 in each group) and one control (group C, n=9) groups were administered with 600 mg of follicle stimulating hormone (FSH) in 10 decreasing doses at 12 hourly interval for five days. Additionally, buffaloes were administered with a single dose of GnRH in group A (10 μg) and group B (06 μg) as a pre-treatment on 2.5 day prior to the start of FSH. Two doses of prostaglandin (500 μg) were administered with the 7 and 8 dose of FSH in all the buffaloes. Embryos were collected non-surgically on day 5.5 post-insemination. Number of total, transferrable and the non-transferrable embryos recovered were recorded in the 3 groups. Total as well as the viable transferrable number of embryos recovered were significantly higher (P<0.05) in the buffaloes of group B compared to the control (3.0 vs. 1.33 and 2.33 vs. 1.0, respectively). In all the three groups, about 75% of embryos recovered were of transferrable grade. The results of study indicated that administration of GnRH as a pre-treatment in superstimulatory treatment improved the MOET efficiency in buffalo.
Is your Broadband really broad? Internet Speed, Labour Demand and Productivity Outcomes: Evidence from Italian Firms ∗

Does higher Internet speed connection in ﬁrms aﬀect labor productivity and production eﬃciency? And is the possibly induced technological change skill biased or factor neutral? We combine several Italian datasets to answer these questions. Internet speed varies signiﬁcantly across locations, even within the same municipality, due to technical characteristics of the broadband network: we exploit speed spatial heterogeneity to identify the impact of Internet speed connection on ﬁrms’productivity. By using a nested CES production function, we can account for substitutability/complementarity between skilled and unskilled labour. Our results suggest that higher broadband capacity improves the labor market outcomes and productivity of skilled workers. Furthermore, it enhances ﬁrms’eﬃciency (TFP). We ﬁnd suggestive evidence that higher broadband capacity in ﬁrms complements skilled workers in executing non-routine abstract tasks, and substitutes for unskilled workers in performing routine tasks. Taken together, our ﬁndings have important implications for the ongoing policy debate over government investment in ultra-broadband infrastructure to encourage productivity and ﬁrms’ performance growth.
The Persistence of Discrimination: An Experiment on Expectations of Being Discriminated Against I

This paper provides an experimental investigation of the role played by workers’ expectations of being discriminated against in explaining the persistence of observed unequal outcomes. Two ex-ante identical populations, one of which bearing the risk of being discriminated against, play an all-pay auction. The experiment investigates the behaviour of the disadvantaged players after the intensity of discrimination has been sharply reduced. The results confirm the multiplicity of equilibria of the underlying game and show that unequal outcomes may persist due to wrong expectations of being discriminated against that either are self-confirming or may take a long time to be dismantled. JEL Classifications: C92; J71; J15; D84.
How Women are Benefiting from Village Banking. A Case of Katuba Constituency

Microfinance (MF) is an initiative which provides financial services to the poor, low-income women and small and micro enterprises that have limited access to banks and similar services. Microfinance is aimed at providing small loans to people living in poverty meant to improve their living standards (Banerjee, 2017). It is proving to be significant in empowering women in some communities of Zambia. These funds are able to empower women from poor households so as to improve their contribution to their community which then translates into better lives and poverty reduction. Although some may criticize, there have been many development experts that have agreed that MF, if properly utilized and supported, can empower women socially and economically and Small and Medium Enterprises (SMEs) by enabling them to contribute and benefit from economic development (UN, 2013). Microfinance in form of village banking has become a familiar name in poor households including women in Zambia. This study focused on how women are benefiting from village banking in Katuba constituency of Lusaka District.
The influence of the online PhET simulation-assisted using direct instruction on student’s conceptual understanding of parabolic motion

This study aimed to investigate the effect of the online PhET simulation-assisted using the direct instruction on students’ conceptual understanding of the parabolic motion. It was quasi-experimental research with pretest-posttest control group design. The research subjects were 10th grade students, consisting of 20 students for each experimental and control groups. The data were collected using a concept understanding test. The research data were analyzed quantitatively by using descriptive and inferential statistics. The results show that the average score of the experimental class was higher than the control class. The hypothesis was tested using Mann-Whitney (U-Test) with a significance level of = 0.05. Based on data analysis, it can be concluded that there was a significant effect of online PhET simulation assisted learning model on students’ concept understanding on parabolic motion.
An Integration Model for Text Classification using Graph Convolutional Network and BERT

Recently, Graph Convolutional Neural Network (GCN) is widely used in text classification tasks, and has effectively completed tasks that are considered to have a rich relational structure. However, due to the sparse adjacency matrix constructed by GCN, GCN cannot make full use of context-dependent information in text classification, and cannot capture local information. The Bidirectional Encoder Representation from Transformers (BERT) has been shown to have the ability to capture the contextual information in a sentence or document, but its ability to capture global information about the vocabulary of a language is relatively limited. The latter is the advantage of GCN. Therefore, in this paper, Mutual Graph Convolution Networks (MGCN) is proposed to solve the above problems. It introduces semantic dictionary (WordNet), dependency and BERT. MGCN uses dependency to solve the problem of context dependence and WordNet to obtain more semantic information. Then the local information generated by BERT and the global information generated by GCN are interacted through the attention mechanism, so that they can influence each other and improve the classification effect of the model. The experimental results show that our model is more effective than previous research reports on three text classification data sets.
Towards Autonomous Satellite Communications: An AI-based Framework to Address System-level Challenges

The next generation of satellite constellations is designed to better address the future needs of our connected society: highly-variable data demand, mobile connectivity, and reaching more under-served regions. Artificial Intelligence (AI) and learning-based methods are expected to become key players in the industry, given the poor scalability and slow reaction time of current resource allocation mechanisms. While AI frameworks have been validated for isolated communication tasks or subproblems, there is still not a clear path to achieve fully-autonomous satellite systems. Part of this issue results from the focus on subproblems when designing models, instead of the necessary system-level perspective. In this paper we try to bridge this gap by characterizing the system-level needs that must be met to increase satellite autonomy, and introduce three AI-based components (Demand Estimator, Offline Planner, and Real Time Engine) that jointly address them. We first do a broad literature review on the different subproblems and identify the missing links to the system-level goals. In response to these gaps, we outline the three necessary components and highlight their interactions. We also discuss how current models can be incorporated into the framework and possible directions of future work.
Knowledge Management Implementation In Malaysian Public Institution of Higher Education

Strategic Information System Planning (SISP) has been of critical importance to any type of organization for a number of years. It is also significance in the implementation of Knowledge Management in Malaysian Public Institution of Higher Education (PIHE). A study has been conducted to get the currents status of KM implementation in Malaysian PIHE and how far Strategic Information System Planning (SISP) has been used in the implementation process. The findings will shows the needs of specific methodology for formulating Knowledge, Information and Communication Technology Strategic Planning (KICTSP) Methodology as a guideline that contains a systematic description on how to implement Knowledge Management in Malaysian Public Institution of Higher Education (PIHE).
Students’ understanding of electric fields in the context of multiple representation

This study aims to describe physics students’ understanding of the concept of electric fields through a multi-representation review in a qualitative way. This research is a qualitative research using test and interview techniques to obtain the data. The research subjects consisted of 6 students from Physics Education department. The test used is an essay test which includes indicators of translation, interpretation and extrapolation on the concept of an electric field. The more in-depth interviews with respondents related to the concept of the electric field were carried out in this study. Based on data analysis, it can be concluded that students’ conceptual understanding is in the moderate category. The highest scores obtained are in translation, interpretation, and extrapolation respectively, which show that the level of indicator complexity affects student achievement. This research implies that the poor conceptual understanding of students on extrapolation indicators caused by the lack of creativity in students’ thinking in exploring the whole information presented on a particular issue. Thus, a learning method that priorities high-level critical thinking skills is extremely needed.
Effect of Use Some Plant Tubers in the Manufacture of Yoghurt Ice Cream

Quick Response Code Abstract: Yoghurt ice cream can be regarded as a healthy alternative to plain ice cream. Also use of some plant tuber in food formulations can lead to the development of products of improved manufacture, nutritional and health promoting values. So, the present study was produced healthy yoghurt ice cream mixes by replacement of stabilizer with some plant tuber mill and studies their effect at different concentration (A 5%, B 10% and C 15%) on the physicochemical, rheological, microbiological and sensory properties. The result indicated that, Total solid (%) was increased with added the powder of tubers in all mixes and the highest total solid in all samples were yellow sweet potato mix C (35.51%). Protein ranged from 2.44 to 3.24% and Fat % ranged from 4.09 to 4.14%. Total carbohydrate increased with adding the plant tuber and yellow sweet potato mix C had the highest carbohydrate and fiber values. Viscosity of yoghurt ice cream mixes reported showed that yoghurt ice cream of potato mix A was the lowest viscosity (1950.0 cP/s) and the highest values was yellow sweet potato mix C (4053.3 cP/s) in all samples. The yoghurt ice cream sample get highly significant effect of sensory evaluation by control followed by cassava containing 5%, 10 % then 15% and yellow sweet potato 5%. While yoghurt ice cream containing 15% potato got the lowest scores. These results concluded cassava concentration 5 &10 % can be a cost effective and good alternate of traditional stabilizers used for yoghurt ice cream preparation. Keyword: Plant tubers flour, yoghurt ice cream, physicochemical and Sensory properties. Copyright © 2021 The Author(s): This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY-NC 4.0) which permits unrestricted use, distribution, and reproduction in any medium for non-commercial use provided the original author and source are credited.
Collective Bargaining about Corporate Social Responsibility

If a firm can credibly commit to an employment-enhancing Corporate Social Responsibility (CSR) objective in negotiations with a trade union, the union can reduce its wage demands. Lower wages, ceteris paribus, raise profits, while the increase in employment enhances the payoff of a wage-setting trade union. Therefore, both the firm and the trade union can be better off in the presence of a collectively bargained CSR-objective than in its absence. Moreover, such Pareto-improvement can arise endogenously from collective bargaining. In consequence, CSR can mitigate the inefficiency arising from collective wage negotiations.