Miracle-dz/UniFAR-FTUs huggingface dataset:
Speaking right: HRDs role in mediating good boardroom conversations

PurposeThis paper aims to explore the impact discourse has on decision making practices within the boardroom and considers how personal proficiency in micro-language use can enhance an individual’s personal efficacy in influencing boardroom decisions. The work uses Habermas’ theory of communicative action to critique board talk, highlighting the need for greater understanding of the power of everyday taken for granted talk in strategy shaping. It illuminates the contribution that human resource development (HRD) professionals can make to the management of such behaviour and minimising dysfunctional behaviour and enabling effective boardroom practices.Design/methodology/approachTraditional governance theory from a business and organisational perspectives are provided before considering the boardroom environment and HRD’s role. The authors undertake ethnographic research supported by conversation analysis to explore how directors use talk-based interpersonal routines to influence boardroom processes and enact collective decision making. The authors provide one extract of directors’ talk to illustrate the process and demonstrate what the data “looks like” and the insights it holds.FindingsThe analysis suggests that the established underlying assumptions and rationale ideologies of corporate governance are misplaced and to understand the workings of corporate governance HRD academics and professionals need to gain deeper insight into the employment of talk within boards. Armed with such insights HRD professionals can become more effective in developing strategies to address dysfunctional leadership and promote good governance practice throughout their organisation.Social implicationsThe work raises a call for HRD to embrace a societal mediation role to help boards to become a catalyst for setting good practice which is strategically aligned throughout the organisation. Such roles require a more dialogical, strategic and critical approach to HRD, and professionals and academics take a more holistic approach to leadership development.Originality/valueThe paper considers the role of the development of HRD interventions that both help individuals to work more effectively within a boardroom environment and support development to shape a boardroom culture that promotes effective governance practice by influencing boardroom practice thereby promoting strong governance and broad social compliance throughout the organisation.
Interaction between Dietary Knowledge and Exercise Knowledge in Leading to Healthier Diet after Hypertension Diagnosis: Evidence from China

This paper examines how dietary knowledge and exercise knowledge are interacted each other in leading to healthier diet after hypertension diagnosis. It uses a sharp regression discontinuity design that exploits the exogenous cut-point of systolic blood pressure in the hypertension diagnosis. Using data from China, the results demonstrate that the influence of hypertension diagnosis on improving diet is significant only among people with good dietary knowledge; and within the people with good dietary knowledge, the influence is much larger among the people who do not believe the importance of exercise for health. The findings may imply that an equal emphasis on both diet and exercise might result in reducing the effect of dietary education on improving diet.
Antifertility studies of Phologacanthus Thyrsiflorus nees: A potential ethno-medicinal plant of north east India

1 Department of Horticulture, Aromatic & Medicinal Plants, Mizoram University, Aizawl-796004, India, Department of Botany, University of Lucknow, Lucknow226007, India King George Medical University, Lucknow226003, India Institute of Bioresources and Sustainable Development, Imphal-795001, India Email: amriteshcshukla@gmail.com Date of online publication: 31st December 2019 DOI:10.5958/2455-7218.2019. 00024.X
Employing the Technology Acceptance Model to Explore the Trends of Social Media Adoption and its Effect on Perceived Usefulness and Perceived Ease of Use

The purpose of this research is to explore the social media trend in communication in Kuwait by utilizing the technology acceptance model. Social media has been gaining extraordinary adoption in past years that requires further investigation into user’s adoption habits, the various kinds of social media, and its effect on their perceived usefulness and ease of use of social media. The study consists of a total of 250 participants that were asked to complete a questionnaire in a random sample. Important findings indicate that the highest number of participants uses Facebook, and the second highest number of participants use Twitter. In terms of usage habits, the highest number of participants uses social media for chatting and connecting with family and friends. The second highest number of participants uses social media for reading posts. In terms of perceived usefulness, the highest numbers of participants perceive social media as ‘usefulness’, and the second highest numbers of participants feel that ‘social media is faster’. In terms of perceived ease of use the highest numbers of participants feel that social media is an easy way to communicate, and the second highest numbers of participants feel that social media does not require a lot of effort. In terms of gender it has been evident that females feel higher perceived usefulness and perceived ease of use of social media than males. The study bears theoretical and practical implications that show TAM can be successfully applied to examine social media in the context of Kuwait population. Furthermore, results of this study can be further generalized to neighboring GCC countries as they share similar geographic, economic, cultural, and financial factors.
scFv against HSP60 of Strongyloides sp. and Its Application in the Evaluation of Parasite Frequency in the Elderly

The present study is aimed at evaluating serological method using scFv anti-Strongyloides sp. and reporting the frequencies of the results with conventional parasitological technique (faeces) in elderly individuals. Among 112 elderly individuals (≥60 years of age), 14.28% were positive for at least one enteroparasite, with one individual positive for S. stercoralis. Sera were evaluated for the presence of anti-Strongyloides sp. antibodies using total or detergent fraction extracts of Strongyloides venezuelensis, which presented positivity rates of 19.64% and 10.71%, respectively. An anti-HSP60 single-chain variable fragment from Strongyloides sp. was used to detect parasite antigens, with 5.36% (6 individuals) of ELISA-positive individuals returning a positive result. While the serological test indicates previous or recent infection and may be limited by antigen purification, the anti-HSP60 method reflects the presence of Strongyloides sp. immune complexes and exhibits greater sensitivity and specificity. Our results demonstrate the variable occurrence of enteroparasites in elderly individuals residing in long-term nursing homes and validate a novel epidemiological tool to describe infection cases by Strongyloides sp.
Modelling and control of a triple‐active‐bridge converter

This study proposes a systematic approach to model and control a triple-active-bridge (TAB) converter for electric vehicle on-board charger applications. An innovative generalised-harmonic-approximation (GHA) modelling method is proposed to accurately predict the instantaneous current and voltage waveforms. Based on the GHA modelling, a control strategy for a TAB converter is proposed, which enables the power flow from grid to two batteries with high conversion efficiency while achieving zero-voltage switching operation. Compared to the conventional phase-shift modulation, the proposed control method achieves an extended operating range of simultaneous charging operation mode, especially under the unbalanced load conditions. As a proof-of-concept, a 600 W prototype is built and tested. The experimental results are presented including waveforms of different operation modes and efficiency measurements. The peak efficiency of the TAB converter under the G2B mode is measured as 97.6%. The experimental waveforms exhibit good agreement with the waveforms obtained through GHA modelling.
What's the same and what's different: The use of the Mathematics Mastery programme in a special school for pupils with moderate learning difficulties

In recent years, drawing on successful models of mathematics teaching in jurisdictions such as Shanghai and Singapore, mastery teaching in mathematics has become commonplace in England, yet there has been little research into the effectiveness of this method for students in English schools. Moreover, there is no research into its appropriateness for pupils with special educational needs. This paper outlines a case study carried out in one primary special school in outer London and discusses the approach taken by the school which had implemented a mastery teaching approach to mathematics. It examines the features of mastery teaching, the challenges faced by pupils with moderate learning difficulties and the adaptations needed in order to make the programme successful. This school found that adopting a mastery approach had a positive effect on teaching and learning in mathematics.
AmpliCI: a high-resolution model-based approach for denoising Illumina amplicon data

Motivation Next-generation amplicon sequencing is a powerful tool for investigating microbial communities. One main challenge is to distinguish true biological variants from errors caused by PCR and sequencing. In the traditional analysis pipeline, such errors are eliminated by clustering reads within a sequence similarity threshold, usually 97%, and constructing operational taxonomic units, but the arbitrary threshold leads to low resolution and high false positive rates. Recently developed “denoising” methods have proven able to resolve single-nucleotide amplicon variants, but they still miss low frequency sequences, especially those near abundant variants, because they ignore the sequencing quality information. Results We introduce AmpliCI, a reference-free, model-based method for rapidly resolving the number, abundance and identity of error-free sequences in massive Illumina amplicon datasets. AmpliCI takes into account quality information and allows the data, not an arbitrary threshold or an external database, to drive conclusions. AmpliCI estimates a finite mixture model, using a greedy strategy to gradually select error-free sequences and approximately maximize the likelihood. We show that AmpliCI is superior to three popular denoising methods, with acceptable computation time and memory usage. Availability Source code available at https://github.com/DormanLab/AmpliCI
Learning Visual Affordances for Robotic Manipulation

A humans remarkable ability to manipulate unfamiliar objects with little prior knowledge of them is a constant inspiration for robotics research. Despite the interest of the research community, and despite its practical value, robust manipulation of novel objects in cluttered environments still remains a largely unsolved problem. Classic solutions (e.g. involving 6D object pose estimation) typically require prior knowledge of the objects (e.g. class categories or 3D CAD models), which may not be available outside of highly constrained settings. More recent deep learning methods using end-to-end convolutional networks (e.g. raw pixels to motor torques) have the potential to model complex skills that generalize, but they remain highly data inefficient – and robot data (e.g. trial and error) is expensive. In this thesis, we consider an approach to learning manipulation called visual affordances. The idea is to use classic controllers to design motion primitives, then use convolutional networks to map from visual observations (e.g. images) to the perceived affordances (e.g. confidence scores or action-values) of the primitives for every pixel of the input. By leveraging dense equivariant state and action representations, this formulation can be used to acquire complex vision-based manipulation skills (e.g. pushing, grasping, throwing) on real robot platforms that generalize to novel objects, while using orders of magnitude less data. While visual affordances may not be directly compatible with classic planning frameworks that involve explicit forward simulation or propagation, in this thesis we show that it is possible to workaround this limitation by extending it with model-free reinforcement learning to sequence primitive picking motions for more complex manipulation policies. We also study how it can be combined with residual physics (learning to predict residual values on top of control parameter estimates from an initial analytical controller) to enable learning end-to-end visuomotor policies that leverage the benefits of analytical models while still maintaining the capacity (via data-driven residuals) to account for real-world iii dynamics that are not explicitly modeled. Finally, we conclude by discussing the limitations of learning visual affordances, which suggest directions for future work.
Who is afraid of a change? Ideological differences in support for the status quo in direct democracy

ABSTRACT Research has documented that individuals display a bias for preserving the status quo across numerous domains of decision-making, including elections for candidates and referendums. Yet, it is not clear whether thinking about a political reform as a change to the status quo actually makes voters less likely to support it. We investigate this possibility in a referendum campaign, in which we prime a representative sample of voters with a “change cue” evoking the modification of the status quo related to a proposed reform. Our findings show that support for a referendum proposal decreases when voters consider that it will change the status quo, but only among right-wing voters. The effect is stronger among less knowledgeable voters on the right (but not on the left) of the political spectrum. Furthermore, we find that the priming manipulation has no effect in the presence of campaign arguments, thus suggesting that voters might discard peripheral cues when substantial policy information is available. These findings have relevant implications for the goal of achieving political change in democratic politics, and highlight the key role of ideology in moderating the status-quo bias in political decision-making.
Numerical and Experimental Investigation of Wave Overtopping of Barriers

We present a study of wave overtopping of barriers. The phenomenon of the wave overtopping over emerged structures is reproduced both numerically and experimentally. The numerical simulations are carried out by a numerical scheme for three-dimensional free-surface flows, which is based on the solution of the Navier–Stokes equations in a novel integral form on a time-dependent coordinate system. In the adopted numerical scheme, a novel wet–dry technique, based on the exact solution of the Riemann problem over the dry bed, is proposed. The experimental tests are carried out by adopting a nonintrusive and continuous-in-space image-analysis technique, which is able to properly identify the free surface even in very shallow waters or breaking waves. A comparison between numerical and experimental results, for several wave and water-depth conditions, is shown.
Mosquepreneur in Perak: Reality or Fantasy?

Social activities at the mosque are still something new in Malaysia and it has not received a lot of attention. However, there are still a few mosque institutions which have focused on social entrepreneurship activities for increasing the mosque’s income source. The questionnaires were distributed to 52 mosque chairmen and observation was done to see the potential of local social entrepreneurship activities based on factors such as the organisational profile, the mosque demographics, assets, income acceptance, social and finance business activities. The data was analysed quantitatively using descriptive analysis. The findings showed that most mosque institutions were able to raise income from entrepreneurial activities. The social activities conducted can increase the mosque income and bring benefit to the local community especially the Muslim community in general. As such, the study findings can provide inspiration and indication for other mosques to take part in social entrepreneurial activities in order to intensify the mosquepreneur efforts.
Building Energy Simulations at Urban Scale Based on Standardized Data Models Using a Transparent Enrichment Process

A fundamental problem to perform reliable energy simulation on urban level is that available data from statistics or cadastral agencies is not sufficient. To perform an energetic simulation based on such data, each simulation tool has its own strategies to enrich the data with missing, energy relevant information. In most cases, these enrichment mechanisms are not transparent for the user and the obtained results are strongly dependent on the used tool. The present paper describes a new approach to achieve more transparency in analysing the energetic performance of buildings on urban scale. Thereby a transparent enrichment process based on the standardized 3D city model CityGML and its energy-related extension (EnergyADE) is used. Basic concepts of this process and its implementation with two building energy simulation systems are described.
Sensorimotor learning under switching dynamics

Sensorimotor learning under switching dynamics James Barry Heald Humans have a remarkable capacity to learn new motor behaviours without forgetting old ones. This capacity relies on the ability to acquire and express multiple motor memories without interference. Here we combine behavioural experiments and computational modelling to investigate how the sensorimotor system uses contextual information to create, update and recall motor memories. We first examine the role of muscle co-contraction in the learning of novel movement dynamics. We show that muscle co-contraction, as measured by surface electromyography, accelerates motor learning. We then explore the role of control points on objects in the formation of motor memories during object manipulation. We show that opposing dynamic perturbations, which interfere when controlling a single location on an object, can be learned when each is associated with a separate control point. To account for these results, we develop a parametric switching state-space model, in which the association between cues (control points) and contexts (dynamics) is learned from experience rather than fixed. We then extend this model to a Bayesian nonparametric switching state-space model, in which the number of contexts and cues are learned online rather than specified in advance. This model can instantiate new memories when novel perturbations are experienced and exhibits spontaneous recovery of a memory that has been ostensibly overwritten. To test the model, we perform an experiment in which we briefly present a previously experienced perturbation after behaviour has returned to baseline. As predicted, we observe a qualitatively distinct and more pronounced form of recovery, which we refer to as evoked recovery. Finally, we investigate Bayesian context estimation using single-trial learning. We show that people are able to learn novel associations between cues and contexts and that they use both contextual cues and state feedback to infer the current context and partition learning between memories. Taken together, these findings further the understanding of the behaviour and computational principles of sensorimotor learning under switching dynamics.
New public auditing protocol based on homomorphic tags for secure cloud storage

Outsourcing datum to the cloud servers is more and more popular for most data owners and enterprises. However, how to ensure the outsourced datum to be kept secure is very important. Especially, how to check the outsourced datum's integrity is a very challenge problem. Until now, there are many cryptographic protocols proposed to solve this problem, such as (dynamic) provable data position protocol, (dynamic) proof of retrievability protocol, etc. Recently, Tian et al proposed a dynamic‐hash‐table‐based public auditing scheme for secure cloud storage, which aims at simultaneously supporting secure dynamic data updating and secure public auditing for cloud storage. However, we find a security flaw in this protocol; concretely, the signature algorithm for the data blocks in their protocol is not secure; the cloud servers can easily modify the outsourced data blocks without detecting. Finally, we give a new protocol by using homomorphic tags based on their protocol and roughly analysis its security.
Integrating a Social Norms Perspective to Address Community Violence against Sri Lankan Women and Girls: A Call for Research and Practice

ABSTRACT Whilst violence against women and girls (VAWG) by intimate partners has received increasing research attention in the last decade, non-partner violence in public spaces remains an underexplored area. With rapid urbanization, violence against women and girls (VAWG) in public spaces, including on public transport, has become increasingly relevant. Global initiatives, such as UN Women’s ‘safe cities and safe public spaces’ have begun unpacking harmful gender and social norms, which both excuse and legitimize violence and drive bystander inaction and survivor underreporting. However, there is a dearth of literature on the social norms that sustain VAWG in public spaces in South Asia, particularly in the Sri Lankan context. The following commentary will first make the case for a social norms approach to understanding and tackling VAWG in public spaces. Moving forward, alongside prevalence studies, we hope to see further normative research on VAWG in public spaces in Sri Lanka, which can inform programming and interventions that tackle the root causes of violence.
A Novel Spectrum Sharing Scheme Using Dynamic Long Short-Term Memory With CP-OFDMA in 5G Networks

With the rapid increase in communication technologies, shortage of spectrum will be a major issue faced in the coming years. Cognitive radio is a promising solution to this problem and works on the principle of sharing between cellular subscribers and ad-hoc Device to Device (D2D) users. Existing 5G spectrum sharing techniques work as per a fixed rule and are pre-established. Also, recent game theoretic approaches for spectrum sharing uses unrealistic assumptions with less likely practical implications. Here, a novel spectrum sharing technique is proposed using 5G enabled bidirectional cognitive deep learning nodes (BCDLN) along with dynamic spectrum sharing long short-term memory (DSLSTM). A joint spectrum allocation and management is carried out with wireless cyclic prefix orthogonal frequency division multiple access (CP-OFDMA). The BCDLN self-learning nodes with decision making capability route information to several destinations at a constant spectrum sharing target, and cooperate via DSLSTM. BCDLN based on time balanced and unbalanced channel knowledge is also examined. With the proposed framework, expressions are derived for the spectrum allocated to multiple sources to obtain their spectrum targets as a variant of the participation node spectrum sharing ratio (PNSSR). The impression of noise when all nodes broadcast with equal spectrum allocation is also investigated.