Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Institutional Determinants of E-Government Adoption in the National Government Administrative Units in Kenya: A Case of Migori County

: Implementation of electronic government initiatives is a major goal in Kenya as evident in the country’s National ICT Master Plan of 2018-2023. In 2011, the access and usage of computers was estimated at 8.4 per cent and the use of Internet to access government services was at 6.3 per cent. By 2017, the use of computers was reported by 75.1 per cent of public sector employees and the provision of online government services had increased to 43.4 per cent of the public institutions. However, even with the increased usage of modern technologies by most government institutions, the National Government Administrative Units in Kenya are not keeping pace in adopting new technologies. Paper-based service delivery in the sector has caused inefficiencies which has negatively affected provision of services. This study therefore evaluated the institutional determinants of electronic government adoption in the National Government Administrative Units in Kenya, with a reference to Migori County. The study specifically investigated the role of Top Management Support, ICT Policy Framework, Human Resource Capacity and ICT infrastructure in determining utilization of electronic government in National Government Administrative Units in Migori County. Two theories, the Diffusion of Innovation theory and the Unified Theory of Acceptance and Use of Technology were utilized to guide this study. The study employed quantitative research methodology and descriptive research design. The target population comprised the 340 National Government Administrative Officers in Migori County and a sample of 184 respondents was selected for the study using stratified sampling. Closed-ended questionnaires were used in the study. The questionnaires were validated by the researcher’s supervisor and their reliability was above 0.7. The response rate was 90.8%. The collected data was analyzed descriptively for mean, frequencies and standard deviation using SPSS version 22. The study also utilized inferential analysis for correlation and regression to provide complete relationships between the study variables. Regression and correlation results indicated a positive and significant relationship between institutional determinants and adoption of electronic government in National Government administrative units in Migori County. The study therefore concluded that a willing and supportive management, implementation of ICT policy framework, skilled human resource and good ICT infrastructure leads to adoption and smooth running of e-government platforms. Moreover, the study recommended managerial and policy adjustments so as to further enhance successful utilization of more electronic government programs in National Government Administrative Units.
Dynamic Written Corrective Feedback and Linguistic Accuracy of University Learners of Spanish

Dynamic Written Corrective Feedback and Linguistic Accuracy of University Learners of Spanish Maria Teresa Company Department of Spanish and Portuguese, BYU Master of Arts This study evaluated the efficacy of Dynamic Written Corrective Feedback (DWCF) on advanced students’ writing accuracy of Spanish. This method focuses on manageable, meaningful, timely and constant feedback. Previously, DWCF was studied in the context of English as a second language. The current study investigated the efficacy of DWCF in the context of students who were enrolled in an advanced Spanish grammar class at the university level. A comparative study was conducted measuring students’ writing accuracy who received the DWCF against students’ writing accuracy who did not receive this feedback methodology. Results showed that there was not a significant difference in writing accuracy between these two groups of students. However, both groups improved their writing accuracy over time. This study also provided a list of the most frequent writing errors made by 28 students in an advanced Spanish class. The results show that the most frequent linguistic errors for learners of Spanish are accent marks, prepositions, gender and number, punctuation, and word choice.
Information Disclosure Policy and Its Implications: Ratcheting in Supply Chains

Fear of escalating input prices in response to retail success is a commonly discussed phenomenon affecting supply chains. Such a ratchet effect arises when a retailer feels compelled to modify its investments to better serve the end customers in order to hide positive prospects and restrain future wholesale price hikes. In a two-period model of supply chain interactions, the authors demonstrate that such an endogenous ratchet effect can have multifaceted reverberations. A retailer fearing price hikes may be tempted to curtail near-term profits to ensure favorable long-term pricing. In response, the supplier can use deep discounts in its initial wholesale prices to convince the retailer to focus on its short-term profits rather than long-term pricing concerns. These deep discounts not only encourage mutually beneficial investments but also alleviate double marginalization inefficiencies along the supply chain. In light of these results, the authors show that a mandatory information disclosure policy to reduce the ratchet effect decreases total channel efficiency compared with no information disclosure, precisely because mandatory disclosure interrupts the healthy tension among supply chain partners. Thus, the model presents a scenario in which ratcheting concerns can create a degree of self-enforcing cooperation that results in socially beneficial responses in supply chains.
Report on Three Round COVID-19 Risk Blind Tests by Screening Eye-region Manifestations

The Coronavirus disease 2019 (COVID-19) has affected several million people since 2019. Despite various vaccines of COVID-19 protect million people in many countries, the worldwide situations of more the asymptomatic and mutated strain discovered are urging the more sensitive COVID-19 testing in this turnaround time. Unfortunately, it is still nontrivial to develop a new fast COVID-19 screening method with the easier access and lower cost, due to the technical and cost limitations of the current testing methods in the medical resource-poor districts. On the other hand, there are more and more ocular manifestations that have been reported in the COVID-19 patients as growing clinical evidence[1]. This inspired this project. We have conducted the joint clinical research since January 2021 at the ShiJiaZhuang City, Heibei province, China, which approved by the ethics committee of The fifth hospital of ShiJiaZhuang of Hebei Medical University. We undertake several blind tests of COVID-19 patients by Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. Meantime as an important part of the ongoing globally COVID-19 eye test program by AIMOMICS since February 2020, we propose a new fast screening method of analyzing the eye-region images, captured by common CCD and CMOS cameras. This could reliably make a rapid risk screening of COVID-19 with the sustainable stable high performance in different countries and races. For this clinical trial in ShiJiaZhuang, we compare and analyze 1194 eye-region images of 115 patients, including 66 COVID-19 positive patients, 44 rehabilitation patients (nucleic acid changed from positive to negative), 5 liver patients, as well as 117 healthy people. Remarkably, we consistently achieved very high testing results (> 0.94) in terms of both sensitivity and specificity in our blind test of COVID-19 patients. This confirms the viability of the COVID-19 fast screening by the eye-region manifestations. Particularly and impressively, the results have the similar conclusion as the other clinical trials of the globally COVID-19 eye test program[1]. Hopefully, this series of ongoing globally COVID-19 eye test study, and potential rapid solution of fully self-performed COVID risk screening method, can be inspiring and helpful to more researchers in the world soon. Our model for COVID-19 rapid prescreening have the merits of the lower cost, fully self-performed, non-invasive, importantly real-time, and thus enables the continuous health surveillance. We further implement it as the open accessible APIs, and provide public service to the world. Our pilot experiments show that our model is ready to be usable to all kinds of surveillance scenarios, such as infrared temperature measurement device at airports and stations, or directly pushing to the target people groups smartphones as a packaged application.
"It's Stored, Hopefully, on an Encrypted Server": Mitigating Users' Misconceptions About FIDO2 Biometric WebAuthn

While prior attempts at passwordless authentication on the web have required specialized hardware, FIDO2’s WebAuthn protocol lets users sign into websites with their smartphone. Users authenticate locally via the phone’s unlock mechanism. Their phone then uses public-key cryptography to authenticate to the website. Using biometrics (e.g., ﬁngerprint, face) for this local authentication can be convenient, yet may engender misconceptions that discourage adoption. Through three complementary studies, we characterized and sought to mitigate misconceptions about biometric WebAuthn. We also compared it to non-biometric WebAuthn and traditional passwords. First, 42 crowdworkers used biometric WebAuthn to sign into a website and then completed surveys. Critically, 67% of participants incorrectly thought their biometrics were sent to the website, creating security concerns. In remote focus groups, 27 crowdworkers then co-designed short no-tiﬁcations to mitigate biometric WebAuthn misconceptions. Through a 345-participant online study, we found that some notiﬁcations improved perceptions of biometric WebAuthn and partially addressed misconceptions, yet key misconceptions about where the biometric is stored partially persisted. Nonetheless, participants were willing to adopt biometric WebAuthn over non-biometric WebAuthn or passwords. Our work identiﬁes directions for increasing the adoption of bio-metric WebAuthn by highlighting its security and usability.
Singing and music making: physiological responses across early to later stages of dementia

Background: Music based interventions have been found to improve wellbeing for people with dementia. More recently there has been interest in physiological measures to provide additional information about how music and singing impact this population. Methods: This multiple-case study design explored physiological responses (heart rate-HR, electrodermal activity-EDA, movement, and skin temperature-ST) of nine people with mild-to-moderate using simulation modelling analysis. Results: In study 1, the singing group showed an increase in EDA (p < 0.01 for 8/9 participants) and HR (p < 0.01 for 5/9 participants) as the session began. HR (p < 0.0001 for 5/9 participants) and ST (p < 0.0001 for 6/9 participants) increased during faster tempos. EDA (p < 0.01 all), movement (p < 0.01 for 8/9 participants) and engagement were higher during singing compared to a baseline control. In study 2 EDA (p < 0.0001 for 14/18 data points [3 music conditions across 6 participants]) and ST (p < 0.001 for 10/18 data points) increased and in contrast to the responses during singing, HR decreased as the sessions began (p < 0.002 for 9/18 data points). EDA was higher during slower music (p < 0.0001 for 13/18 data points), however this was less consistent in more interactive sessions than the control. There were no consistent changes in HR and movement responses during different music genre. Conclusions: Physiological measures provide valuable information about the experiences of people with dementia participating in musical activities, particularly for those with verbal communication difficulties. Future research should consider using physiological measures. video-analysis and observational measures to explore further how engagement in specific activities, wellbeing and physiology interact.
The Effectiveness of Online Coaching through Social Networking Site

In the more globalized world, social networking sites are used to connect people and popular as a learning platform. More people use webinars to talk about specific topics through a social network. The number of online courses raise and change the way people learn. People used to study in a classroom with a tutor in front of them, but now people only need to sit in front of a screen to learn new things. However, the effectiveness of this process is still questioned. Therefore, this study aims to analyse the effectiveness of online coaching through a social networking site and the critical challenge in online coaching and approach to tackle it. This study is qualitative research. The data is collected from online interviews with a semi-structured interview guide. The sample of the study is 12 mentees and 5 mentors who had been involved in 12 weeks of online scholarship coaching held by Coach Potato Indonesia. The data is analyzed using a thematic content method, and the effectiveness of online coaching is measured by using the Kirkpatrick Model. The result of the study is that online mentoring through social networking sites is effective and efficient, especially in particular related to geographical and financial issues. The authors found the critical challenges in online mentoring are internet connection and timing. Therefore, online mentoring should use multiple platforms to adjust with the technical issue that might occur.
A Novel Pornographic Visual Content Classifier based on Sensitive Object Detection

With the increasing amount of pornography being uploaded on the Internet today, arises the need to detect and block such pornographic websites, especially in Eastern cultural countries. Studying pornographic images and videos, show that explicit sensitive objects are typically one of the main charac-teristics portraying the unique aspect of pornography content. This paper proposed a classification method on pornographic visual content, which involved detecting sensitive objects using object detection algorithms. Initially, an object detection model is used to identify sensitive objects on visual content. The detection results are then used as high-level features combined with two other high-level features including skin body and human presence information. These high-level features finally are fed into a fusion Support Vector Machine (SVM) model, thus draw the eventual decision. Based on 800 videos from the NDPI-800 dataset and the 50.000 manually collected images, the evaluation results show that our proposed approach achieved 94.06% and 94.88% in Accuracy respectively, which can be compared with the cutting-edge pornographic classification methods. In addition, a pornographic alerting and blocking extension is developed for Google Chrome to prove the proposed architecture’s effectiveness and capability. Working with 200 websites, the extension achieved an outstanding result, which is 99.50% Accuracy in classification.
DESIGN AND ANALYSIS OF NEW LOGICAL LOW POWER FULL ADDER WITH LOW POWER TECHNIQUES

: In this work, a logical 1-bit full adder design employing complementary metal–oxide–semiconductor (CMOS) logic is described. The schematic plan was implemented using Microwind 9.1 version. In this full adder, numbers of transistors are reduced by logicism. Consequently average power and layout area also reduced. The proposed full adder is compared with hybrid full adder utilizing CMOS logic and transmission gate logic. The simulation results of proposed circuit for 1.2-V supply at cmos 0. 12µm technology, the average power consumption is 9.079 μW and layout area 213. 8µm 2 both performance parameters are reduced when compared to hybrid full adder. Hybrid full adder has 14.005 μW power consumption and 299.4 µm 2 layout area. Further reducing power the proposed full adder was implemented along with some low power techniques and their results are tabulated.
Efficient pure-mode elastic mode-converting diode

A pure-mode performance is critical for elastic diodes, but difficult to achieve because of the rich polarization characteristics of elastic waves. In this work, we propose a type of elastic mode-converting diode for an efficient and pure-mode asymmetric transmission. The diode consists of two components, one purely for mode-selecting and the other solely for mode-converting. The former is made of fluid-like metamaterials, which only support the transmission of longitudinal waves in a certain frequency range with a nearly 100% power efficiency. The latter works as a transmodal Fabry–Perot interferometer, and can convert the wave energy between longitudinal and transverse modes solely and maximally. With the designed diode, a pure-mode one-way transmission with a power efficiency of nearly 90% is realized in the ultralow frequency range. We expect that this effective and efficient device can offer a wide range of options for manipulating elastic waves, including mode isolation, selection, conversion, rectification, etc.
Coupling framework (1.0) for the PISM (1.1.4) ice sheet model and the MOM5 (5.1.0) ocean model via the PICO ice shelf cavity model in an Antarctic domain

The past and future evolution of the Antarctic Ice Sheet is largely controlled by interactions between the ocean and floating ice shelves. To investigate these interactions, coupled ocean and ice sheet model configurations are required. Previous modelling studies have mostly relied on high-resolution configurations, limiting these studies to individual glaciers or regions over short timescales of decades to a few centuries. We present a framework to couple the dynamic ice sheet model PISM (Parallel Ice Sheet Model) with the global ocean general circulation model MOM5 (Modular Ocean Model) via the ice shelf cavity model PICO (Potsdam Ice-shelf Cavity mOdel). As ice shelf cavities are not resolved by MOM5 but are parameterized with the PICO box model, the framework allows the ice sheet and ocean components to be run at resolutions of 16 km and 3 respectively. This approach makes the coupled configuration a useful tool for the analysis of interactions between the Antarctic Ice Sheet and the global ocean over time spans of the order of centuries to millennia. In this study, we describe the technical implementation of this coupling framework: sub-shelf melting in the ice sheet component is calculated by PICO from modelled ocean temperatures and salinities at the depth of the continental shelf, and, vice versa, the resulting mass and energy fluxes from melting at the ice–ocean interface are transferred to the ocean component. Mass and energy fluxes are shown to be conserved to machine precision across the considered component domains. The implementation is computationally efficient as it introduces only minimal overhead. Furthermore, the coupled model is evaluated in a 4000 year simulation under constant present-day climate forcing and is found to be stable with respect to the ocean and ice sheet spin-up states. The framework deals with heterogeneous spatial grid geometries, varying grid resolutions, and timescales between the ice and ocean component in a generic way; thus, it can be adopted to a wide range of model set-ups.
To e-bike or not to e-bike? A study of the impact of the built environment on commute mode choice in small Chinese city

The use of electric bikes (e-bikes) is attracting increasing attention from researchers and policymakers as a way to promote sustainable transportation. However, knowledge about the built environment factors that influence e-bike use is lacking. In China, most evidence on e-bikes and travel behavior stems from big cities; there is much less evidence concerning small cities and their adjacent rural areas. Using travel data collected in a small Chinese city (Ganyu), the present research explores the impact of the built environment around residential and work locations on individuals’ commute mode choice, with a particular focus on e-bike use. Consistent with the few previous studies on travel behavior in small Chinese cities, we find that most residents of Ganyu commute only short distances and that the e-bike is the primary mode for their daily commutes. The results of a nested logit model show that e-bike use is more popular among females and low-income groups, and that certain built environment characteristics at the work location promote e-bike use. Moreover, the built environment in different geographical contexts has different influences on commute mode choice. In particular, the presence of city/town roads without bike lanes at work locations promotes e-bike use among rural residents but much less so among urban residents.
Towards Computer Vision and Deep Learning Facilitated Pollination Monitoring for Agriculture

Globally, pollinators affect 35% of agricultural land and play a key role in food production. Consequently, monitoring is useful to understand the contribution insects make towards crop pollination. Traditional sampling techniques used in insect monitoring have several drawbacks, including that they are labour intensive and potentially unreliable. Some of these drawbacks may be overcome using computer vision and deep learning-based approaches to automate pollination monitoring. In this paper, we present a pipeline for computer vision-based pollination monitoring and propose a novel algorithm, Polytrack, that tracks multiple insects simultaneously in complex agricultural environments. Our algorithm uses deep learning and fore-ground/background segmentation to detect and track in-sects. We achieved precision and recall rates of 0.975 and 0.972 respectively when monitoring honeybees foraging in our test sites within the polytunnels of an industrial straw-berry farm. Polytrack includes a flower identification module to automate collection of insect-flower interaction data, and a low-resolution processing mode that reduces computational demands placed on the processor to bring the software towards the requirements of low-powered monitoring hardware.
GENERALIZATION OF AN INEQUALITY BY TALAGRAND , AND LINKS WITH THE LOGARITHMIC SOBOLEV

We show that transport inequalities, similar to the one derived by Talagrand [30] for the Gaussian measure, are implied by logarithmic Sobolev inequalities. Conversely, Talagrand's inequality implies a logarithmic Sobolev inequality if the density of the measure is approximately log-concave, in a precise sense. All constants are independent of the dimension, and optimal in certain cases. The proofs are based on partial di erential equations, and an interpolation inequality involving the Wasserstein distance, the entropy functional and the Fisher information.