Miracle-dz/UniFAR-FTUs huggingface dataset:
Peer-to-Peer Energy Trading in Micro/Mini-Grids for Local Energy Communities: A Review and Case Study of Nepal

Distributed Energy Resources (DERs) are being integrated into the power market by customers rather than large scale energy suppliers, thereby slowly transforming the centralized, unidirectional market to a decentralized, bidirectional market and transitioning customers into prosumers. Various system architectures are used in the real field to coordinate the energy distribution in the micro/ mini-grids integrated with DERs, all of which have their strengths, weaknesses and challenges. Peer-to-peer (P2P) is an emerging architecture in the field of electrical energy trading and Distributed Generation (DG) management that can be applied in local energy markets. This paper focuses on P2P energy trading, with an in-depth discussion on its various operating algorithms, their principles, characteristics, features and scope through state of art review on P2P. Furthermore, the energy system of Nepal is used as a case study in this paper, and the micro/mini-grids of Nepal and their associated challenges, constraints and opportunities for improvement are discussed. Finally, an energy trading model is proposed to address the problems occurring in the specific case of Nepalese energy market.
Voter Equalization and Turnout Bias After Electoral Reform: Evidence from Chile’s Voluntary Voting Law

ABSTRACT It has normally been argued that because compulsory voting systems present higher turnout rates relative to voluntary voting systems, they do not generate as many biases between different groups of voters. This article qualifies that view. It argues that in cases in which compulsory voting does not ensure near-universal participation, there is no certainty that switching to voluntary voting will increase inequalities. This issue is examined by looking at Chile, a democracy that moved from compulsory voting to voluntary voting in 2012. The research finds that while the reform generated class bias in urban districts, it also substantially reduced age bias and, in national elections, equalized participation between small and large districts. The conclusion is that abandoning compulsory voting does not necessarily increase turnout biases, since much depends on the structure of preexisting biases and how these are conditioned by particular electoral institutions.
A Time and Space-Efficient Compositional Method for Prime and Test Paths Generation

This paper investigates the problem of prime and test paths generation, which is an important problem in ensuring path coverage in software testing. Most existing methods for prime/test paths generation have little success in generating the set of all prime/test paths of structurally complex programs with high Npath complexity. This paper puts forward two novel methods for the generation of prime and test paths of highly complex programs, namely a vertex-based algorithm and a compositional method. The proposed vertex-based method enables a time-efficient approach for the generation of all prime paths, and the compositional method provides a highly time and space-efficient method for the generation of prime and test paths in cyclic control flow graphs with extremely large Npath complexity. We also implement the proposed algorithms as a software toolset for the generation of prime and test paths. Our experimental results on a set of complex programs indicate that the proposed approaches significantly outperform existing methods, especially for large and structurally complex programs.
The Culture of Long Term Care: Nursing Home Ethnography

Foreword by Philip B. Stafford Introduction Perspective on Ethnographic Methods, Analysis and Findings Nursing Home Research Comes of Age: Toward an Ethnological Perspective on Long Term Care by Maria D. Vesperi Perspective and Story in Nursing Home Ethnography by Jaber F. Gubrium Qualitative Research as a Tool Revealing Inappropriate Medicalization of Aging in Nursing Home Care by J. Neil Henderson You Say Respondent, I Say Informant: What Stories Told by Informants Can Tell Us by Lisa Groger Ethnography and the Nursing Home Ombudsman by Lynn D. Mason In and Out of Bounds: The Ethics of Respect in Studying Nursing Homes by Joel Savishinsky Ethics in the Nursing Home: Cases, Choices, and Issues by Renee Rose Shields The Head Nurse as Key Informant: How Beliefs and Institutional Pressure Structure Dementia Care by Athena McLean and Margaret Perkinson Staff/Resident Life Assessing Types of Residential Accommodation for the Elderly: Liminality and Communitas by Barbara Hornum Relatives as Trouble: Nursing Home Aides and Patient's Families by Nancy Foner From the Inside Out: The World of the Institutionalized Elderly by Bethel Ann Powers Continuities and Discontinuities in the Life Course: Experience of Demented Persons in a Residential Alzheimer's Facility by Myrna Silverman and Carol McAllister References Index
Distributed Clustering in General Metrics via Coresets

Center-based clustering is a fundamental primitive for data analysis and is very challenging for large datasets. We developed coreset based space/round-efficient MapReduce algorithms to solve the k-center, k-median, and k-means variants in general metrics. Remarkably, the algorithms obliviously adapt to the doubling dimension of the metric space, and attain approximation ratios that can be made arbitrarily close to those achievable by the best known polynomial-time sequential approximations.
Recent Advances in Identifying Biomarkers and High-Affinity Aptamers for Gynecologic Cancers Diagnosis and Therapy

Cancer is the uncontrollable abnormal division of cell growth, caused due to the varied reasons. Cancer can be expressed in any part of the body, and it is one of the death-causing diseases. Human reproductive organs are commonly damaged by cancer. In particular, the women reproductive system is affected by various cancers including ovarian, cervical, endometrial, vaginal, fallopian tube, and vulvar cancers. Identifying these cancers at earlier stages prevents the damage to the organs. Aptamer is the potential probe that can identify these cancers. Aptamer is an artificial antibody selected from the randomized library of molecules and has a high binding affinity to the target biomarker. Targeting cancers in the reproductive organs using aptamers showed an excellent efficiency of detection compared to other probes. Different aptamers have been generated against the gynaecological cancer biomarkers, which include HE4, CA125, VEGF, OCCA (for ovarian cancer), EGFR, FGFR1, K-ras (for endometrial cancer), HPV E-16, HPV E-7, HPV E-6, tyrosine, and kinase (for cervical cancer), which help to identify the cancers in woman reproductive organs. In this overview, the biomarkers for gynecologic cancers and the relevant diagnosing systems generated using the specific aptamers are discussed. Furthermore, the therapeutic applications of aptamer with gynaecological cancers are narrated.
Consumption dynamics and the expectation channel in a Small Open Economy

The transmission mechanism between consumption and its fundamentals has been under reviews in the literature from Friedman’s permanent income hypothesis to household’s liquidity constraints. One particular angle to explain consumption is focused on the role of consumer expectations as a determinant of consumption spending. Here we explore alternative measures for consumer expectations (captured by surveys to households) by taking into account general manager expectations and by using imports of durable consumption goods (which capture consumer confidence about future economic conditions). We argue that, for a small open economy, the expectations channel is well captured by alternative measures; find that even though there is a pass-through from expectations to consumption, this effect tends to have a short-period effect; and also report those values and periods of time for which the alternative measures have a significant impact on consumption.
Modeling Implicit Feedback and Latent Visual Features for Machine-Learning Based Recommendation

To leverage the rapid accumulation of rich media on the Internet, this paper proposes a Multi-View Bayesian Personalized Ranking (MVBPR) recommendation model, which combines visual and textual content, along with uncertainty modeling of consumer preference in form of implicit feedback and visual representation in form of latent factors. MVBPR is a machine-leaning framework integral of deep-learning (i.e., SCAE) and topic modeling (i.e., LDA) strategies to fuse image and text information. Moreover, extensive experiments demonstrate MVBPR’s advantages over baseline models, including its superiority in dealing with the cold start situation.
Lattice Instability and Elastic Response in the Heavy Electron System URu 2 Si 2

We have performed thermal expansion and elastic constant measurements of the heavy electron system URu 2 Si 2 , focusing attention on the Γ 3 ( x 2 - y 2 ) and Γ 4 ( x y ) symmetry of the tetragonal group D 4 h . It is reconfirmed that there is no sizable uniform spontaneous distortion for these two types of symmetry through the puzzling phase transition at T 0 =17.5 K. On the other hand, a weak but significant tendency of softening are found below about 70 K in the transverse ( c 11 - c 12 )/2 mode. The results strongly suggest the presence of a lattice instability in the Γ 3 symmetry. From the results, proposed crystalline-electric-field models are also discussed.
Cystic Fibrosis Infection with Clonal Strains of Pseudomonas Aeruginosa: Current Knowledge and Future Management

Cystic Fibrosis (CF) is a lethal disease affecting children, adolescents and mature adults. However, over the past three decades, as a direct consequence of the application of multidisciplinary care delivered by CF centres worldwide, the disease has changed from a childhood killer into prolonged adult survival. CONTENTS: New insights into the Pathophysiology of Lung Disease in Cystic Fibrosis Patients; Disease modifier genes in cystic fibrosis; Emerging pathogens; Treatment strategies for CF diabetes; Noninvasive ventilation; Diagnosis and management of cystic fibrosis related Low bone mineral density; Cystic fibrosis infection with clonal strains of Pseudomonas aeruginosa; current knowledge and future management; Difficult issues in the selection of cystic fibrosis patients for lung transplantation; Small airways disease in Cystic Fibrosis; Gene therapy for cystic fibrosis: successes and challenges; Atypical Cystic Fibrosis
Unpaid Labor and the Critique of Political Economy in Home Economics and New Household Economics:: From the Feminist Economics Perspective

This paper investigates the relationship between home economics and new household economics. In particular, I consider what is “new” in new household economics from the feminist economics perspective. Home economics was established in the 1920s and 1930s by Hazel Kyrk, Margaret Reid, and Elizabeth Hoyt, while new household economics was established in the 1960s by Jacob Mincer, Theodore Schultz, and Gary Becker. Before the 1960s, mainstream economics concentrated on production for the market. Later, the mainstream economics of the family culminated in Becker’s new household economics. The family, within which unpaid labor is carried out mostly by women, again became an important topic in feminist economics in the 1990s. In this paper, I focus on the theoretical meaning of unpaid labor in these two Chicago schools, home economics and new household economics. I insist that new household economics is not “new” in terms of its approach and method. Rather, its novelty is in the domain of the application of standard microeconomics to the household. I firstly explore the feminist economics perspective. Secondly, I discuss the theoretical meaning of the analysis of unpaid labor in home economics. Thirdly, I examine new household economics from the methodological point of view and policy implications. I then conclude by discussing the relationship between these two Chicago schools. JEL classification numbers: B00, B41, B54. Series: Women and Economics 〈2〉 Unpaid Labor and the Critique of Political Economy in Home Economics and New Household Economics: From the Feminist Economics Perspective
Developing a Framework for Child Welfare Supervision

The roles of the child welfare supervisor in guiding practice and in retaining child welfare workers are well established in the literature. In this article, we discuss a framework for child welfare supervision that was developed and implemented in the state of Iowa with support from the Children's Bureau through a five-year grant to improve recruitment and retention in public child welfare. The framework supports family centered practice through a parallel process of supervision reflecting these guiding principles: strength-based, competency-based, culturally competent, reflective, individualized to workers' learning styles and stages of development, and aimed at enhancing worker skill, autonomy, teamwork, and commitment to the organization. We present key elements of the framework, an overview of implementation, and evaluation results regarding knowledge gain, use of skills, and rates of worker retention.
Lexically Guided Perceptual Learning of a Vowel Shift in an Interactive L2 Listening Context

Lexically guided perceptual learning has traditionally been studied with ambiguous consonant sounds to which native listeners are exposed in a purely receptive listening context. To extend previous research, we investigate whether lexically guided learning applies to a vowel shift encountered by nonnative listeners in an interactive dialogue. Dutch participants played a two-player game in English in either a control condition, which contained no evidence for a vowel shift, or a lexically constraining condition, in which onscreen lexical information required them to re-interpret their interlocutor’s /ɪ/ pronunciations as representing /ɛ/. A phonetic categorization pre-test and post-test were used to assess whether the game shifted listeners’ phonemic boundaries such that more of the /ɛ//ɪ/ continuum came to be perceived as /ɛ/. Both listener groups showed an overall post-test shift toward /ɪ/, suggesting that vowel perception may be sensitive to directional biases related to properties of the speaker’s vowel space. Importantly, listeners in the lexically constraining condition made relatively more post-test /ɛ/ responses than the control group, thereby exhibiting an effect of lexically guided adaptation. The results thus demonstrate that non-native listeners can adjust their phonemic boundaries on the basis of lexical information to accommodate a vowel shift learned in interactive conversation.
Whose water? Whose profits? The role of informal water markets in groundwater depletion in peri-urban Hyderabad

Urbanising cities of India are engulfing the peri-urban land and water resources. Informal water sellers, who transfer water from peri-urban to urban areas, meet the growing water demand in Hyderabad, one of the fastest growing cities in India. This article qualitatively explores how informal water tankers are changing the flows of water, posing challenges to water access for peri-urban residents. We conclude that apart from the state's infrastructural and capacity challenges to provide piped water, power interplay between actors is responsible for the mushrooming of informal water markets. The transfer of water has contributed to groundwater depletion as well as to the water insecurity of peri-urban residents.
A New Users Rating-Trend Based Collaborative Denoising Auto-Encoder for Top-N Recommender Systems

To promote online businesses and sales, e-commerceindustry focuses to fulfill users’ demands by giving them top set ofrecommendations which are ranked through different ranking measures.Deep learning based auto-encoder models have further improved theperformance of recommender systems. Astate-of-the-art collaborative denoisingauto-encoder (CDAE) models user-item interactions as a corruptedversion of users rating inputs. However, this architecture stilllacks users’ ratings-trend information which is an important parameterto recommend top-N items to users. In this paper, buildingupon CDAE characteristics, we propose a novel users rating-trendbased collaborative denoising auto-encoder (UT-CDAE) whichdetermines user-item correlations by evaluating rating-trend(High or Low) of a user towards a set of items. This inclusion of auser’s rating-trend provides additional regularization flexibilitywhich helps to predict improved top-N recommendations. Thecorrectness of the suggested method is verified through different rankingevaluation metrics i.e., (mean reciprocal rank, meanaverage precision and normalized discounted gain), for various inputcorruption values, learning rates and regularization parameters.Experiments on standard ML-100K and ML-1M datasets showthat suggested model has improved performance overstate-of-the-art denoising auto-encodermodels.
Using Technology-Enabled Learning Networks to Drive Module Improvements in the UK Open University

This paper describes a work-in-progress action research project to investigate how technology-enabled learning networks may achieve practical organisational improvement outcomes in the author’s own institution, a UK distance learning higher education (HE) context. Collaborative learning technology, typically used for academic learning or professional development, affords the geographically scattered and disparate practitioner stakeholders involved in distance learning module design and delivery the ability to grapple together with a problem area requiring improvement. In this particular context, there is a perennial organisational need to close a feedback loop between remote module tutors and campus based teams, to develop a joint understanding of teaching and learning design challenges, and to put tutors as close as possible to the development of solutions. However, there is insufficient conceptual and practical understanding about the mechanisms by which this unfolding process of technology-enabled organisational learning might happen. Conceptual frameworks in the field of learning networks and networked learning are still developing (Sloep, 2016). The aim of this research is to investigate the active use of learning networks to achieve practical improvement outcomes, and to explore a new conceptual framework covering all stages of the required learning process. The research aims to make an original contribution to the call for actionable knowledge in organisational research, using a collaborative, equitable and rigorous action-oriented and theory-building approach, which also aims to achieve measurable impact.
The role of cognitive appraisal, emotion and commitment in affecting resident support toward tourism performing arts development

Abstract While residents’ perceptions of tourism development have been widely explored through a rational cost-benefit lens, little is known about residents’ emotional responses and their influences on resident support toward tourism development. By integrating cognitive appraisal theory and affect theory of social exchange, this study examines the psychological factors (cognitive appraisals, emotions, and commitment) that underlie residents’ behaviors toward Tourism Performing Arts (TPA) development. Based on a survey of 435 residents undertaken in Yangshuo, China, the results reveal that outcome desirability, fairness and coping potential are significant antecedents differentiating resident positive and negative emotional responses toward TPA developments. Commitment was found to moderate the relationship between resident negative emotions and supportive behaviors and played a significant role in shaping resident behaviors. Additionally, resident support was found to be influenced by negative emotions rather than positive emotional responses toward TPA development. The findings have implications for alleviating resident hostility, cultivating commitment toward specific types of tourism, reducing community conflicts and obtaining local support for sustainable tourism development.
Factors that affect the perception of a tourist resource’s value: the case of the Caminito del Rey

This study’s primary objective was to analyse the factors influencing overall customer satisfaction with tourism resources by applying two similar techniques with different approaches. A survey was conducted between June and December 2017, producing a total of 171 valid forms. Importance performance analysis (IPA) and asymmetric impact-performance analysis (AIPA) were used to process the data. The results suggest that El Caminito managers give low priority to generating tourist information about and satisfaction with this resource’s features. In addition, managers need to concentrate on improving signposting. IPA highlighted that the environment’s assessment is an overexploited factor, but AIPA suggested that this factor can still contribute to shaping customer satisfaction. The AIPA’s results also show that environmental cleanliness and El Caminito’s regular cleaning are fundamental factors in visitors’ high general satisfaction. This study’s systematic use of these analytical tools facilitated the identification of factors that add to or reduce the value of tourism resources, thereby helping to improve these resources’ quality and sustainability. The findings’ application could ultimately enhance this destination’s competitiveness and its overall success.
Task-space Control of Electrically Driven Robots

Actuators of robot operate in the joint-space while the end-effect or of robot is controlled in the task-space. Therefore, designing a control system for a robotic system in the task-space requires the jacobian matrix information for transforming joint-space to task-space, which suffers from uncertainties. This paper deals with the robust task-space control of electrically driven robot manipulators. In conventional robust control approaches, the uncertainty upper bound is required to design the control law. This type of controller design is conservative that may increase the amplitude of the control signal and damage the system. Moreover, calculation of this bound requires some feedbacks of the system states which may be expensive. The novelty of this paper is addressing a robust control law in which the lumped uncertainty is modeled by a differential equation. The control design is simple, robust against uncertainties, and less computational. Simulation results verify the effectiveness of the proposed control approach applied on a two-link robot manipulator driven by geared permanent magnet DC motors.
Emotion Analysis of Different Age Groups From Voice Using Machine Learning Approach

Emotion detection from voice is a complex task, whereas from the facial expression it is easy. In this chapter, an attempt is taken to detect the emotion through machine using neural network-based models and compared. As no complete database is available for different age groups, a small database is generated. To know the emotion of different age groups substantially, three groups have been generated with each group of 20 subjects. The efficient prosodic features are considered initially. Further, the combination of those features are taken. Each set of features are fed to the models for classification and detection. Angry, happy, and sad are the three emotions verified for different group of persons. It is found that the classifier provides 96% of accuracy. In earlier work, cluster-based techniques with simple features pitch, speech rate, and log energy were verified. As an extension, the combination of features along with machine learning model is verified in this work.