Miracle-dz/UniFAR-FTUs huggingface dataset:
Returns to education, indeterminacy, and multiple balanced growth paths

We investigate the existence, multiplicity, and indeterminacy of balanced growth paths in an extended Lucas model incorporating physical capital inputs, human capital externalities, and decreasing returns to scale in education. With physical capital in education and increasing social returns in production, social returns to scale in education should be decreasing for the existence of balanced growth; indeterminacy can arise for weaker human capital externalities; and multiple balanced growth paths may emerge with perhaps distinctive dynamic properties: The high-growth steady state may be indeterminate, while the low-growth steady state may be determinate, but not vice versa.
The Effect of Celebrity Endorsement on Purchase Intention of Adidas Products Mediated by Customer’s Attitude Toward Brand

This study aims to determine the effect of celebrity endorsment on purchase intention of Adidas which mediates customer attitude towards brand. Big companies currently use celebrity to be able to market their products, one of which is a sportwear company, namely Adidas, which uses Kanye West as a celebrity endorser to be able to market their products. Companies are expected to pay attention to or see celebrity from several variables, namely celebrity trustworthiness, celebrity expertise, celebrity attractiveness, celebrity similarity, celebrity liking, celebrity familiarity and celebrity match-up congruence with the brand / product. This study uses individual primary data collection methods using a questionnaire. Researchers took respondents who live in the Tangerang and Jakarta areas. Respondents in this study were 150 respondents. This study uses data processing using Partial Least Square Structural Equation Modeling (PLS-SEM) and is processed using SmartPLS software. The results showed that the celebrity endorsement variable had a positive and significant effect on the response from prospective Adidas customers, The Effect of Celebrity Endorsement . 525 p-ISSN : 2685-9106 e-ISSN : 2686-0384 ADI International Conference Series so that customers would do Purchase Intention mediated by customer attitude toward the
Analyses of blood donor samples from eight provinces in Lao PDR suggest considerable variation concerning HBV exposure and carriage

Introduction Hepatitis B is endemic in Lao PDR and about 9% of the adult population is chronically infected. In this study, we investigated regional, occupational, age and sex-related differences in hepatitis B epidemiology in Lao blood donors. Methods 5017 voluntary blood donors from 8 different provinces were tested for hepatitis B markers by ELISA. Predictors for the prevalence of hepatitis B surface antigen (HBsAg) and antibodies against the core antigen (anti-HBc) were assessed by bivariate and multivariable analyses. Results In total, 41% of the participants were positive for anti-HBc; the HBsAg prevalence was estimated at 6.9% among all participants (9.2% among first-time donors and 3.9% among repeat donors). Among first-time donors, HBsAg positivity was associated independently with being male (p<0.001), being from the North (p<0.001) and being soldier (p<0.001). Participants were more likely to be anti-HBc positive when they were male (p<0.001), from the Northern provinces (p<0.001) and older than 20 years (p<0.01). Conclusion In conclusion, our study confirmed an overall high HBsAg and anti-HBc prevalence in Lao PDR, albeit with considerable regional variation. The identification of a sizeable number of HBsAg positives among repeat donors warrants a thorough investigation of current blood screening, record keeping, donor identification and counselling practises.
Helpmate: A Mobile Robot For Transport Applications

HelpMate is a mobile robotic materials transport system that performs fetch and carry tasks at Danbury Hospital. It navigates along the main arteries of the hospital, crossing between buildings via interconnecting corridors and uses infrared communication links to communicate with the elevator controller. HelpMate has been designed to work safely around humans, smoothly rerouting its local path to avoid obstacles while maintaining its mission. Safety features include both non-contact and contact obstacle sensing, emergency stop switches, auto/manual mode switches, flashing warning lights, turn indicators, and a failsafe controls design. HelpMate uses odometry, sonar and infrared proximity sensors, and vision as navigation inputs. An onboard card reader provides authorized personnel access to run time control and cargo transfer. Sensor information collected en route is used to build and maintain local navigation maps. A general knowledge of the structured properties of the world is assumed, and used both in collecting and rationalizing the sensor information and updating the robot's local knowledge base. All navigation and path planning is conducted under the direction of onboard processors.
Examination of the cognitive function of Japanese community-dwelling older adults in a class for preventing cognitive decline during the COVID-19 pandemic

We examined the changes in cognitive function due to restrictions in daily life during the coronavirus disease 2019 (COVID-19) pandemic in community-dwelling older adults with mild cognitive decline. This was a retrospective, case-control study. The participants include 88 older adults with mild cognitive decline (mean age = 81.0 [standard deviation = 6.5] years) who participated in a class designed to help prevent cognitive decline. This class was suspended from early-March to end of May 2020 to prevent the spread of COVID-19, and resumed in June 2020. We collected demographic and cognitive function test data (Touch Panel-type Dementia Assessment Scale [TDAS]) before and after class suspension and questionnaire data on their lifestyle and thoughts during the suspension. Change in TDAS scores from before and after the suspension was used to divide the participants into decline (2 or more points worsening) and non-decline (all other participants) groups, with 16 (18.2%) and 72 (81.8%) participants in each group, respectively. A logistic regression model showed that the odds ratio (OR) for cognitive decline was lower in participants whose responses were “engaged in hobbies” (OR = 0.07, p = 0.015), “worked on a worksheet about cognitive training provided by the town hall” (OR = 0.19, p = 0.026), and “had conversations over the phone” (OR = 0.28, p = 0.0495). There was a significant improvement in TDAS scores after class was resumed (p < 0.01). A proactive approach to intellectual activities and social ties may be important for the prevention of cognitive decline during periods of restrictions due to COVID-19. We found that cognitive function test scores before class suspension significantly improved after resuming classes. We speculate that continued participation in this class led to positive behavioral changes in daily life during periods of restriction due to COVID-19.
S WITCHING -A LIGNED -W ORDS D ATA A UGMENTATION FOR N EURAL M ACHINE T RANSLATION

In neural machine translation (NMT), data augmentation methods such as backtranslation make it possible to use extra monolingual data to help improve translation performance, while it needs extra training data and the in-domain monolingual data is not always available. In this paper, we present a novel data augmentation method for neural machine translation by using only the original training data without extra data. More accurately, we randomly replace words or mixup with their aligned alternatives in another language when training neural machine translation models. Since aligned word pairs appear in the same position of each other during training, it is helpful to form bilingual embeddings which are proved useful to provide a performance boost (Liu et al., 2019). Experiments on both small and large scale datasets show that our method significantly outperforms the baseline models.
The International Review of Financial Consumers

This paper investigates the relationship between marketing channels and underwriting service quality with focus on two major channels: salesperson and bancassurance. Based on the data of life insurance in Taiwan, the empirical analysis shows that the traditional salesperson channel has competitive advantages in underwriting service quality. This result supports the coexistence of salesperson and bancassurance because previous literature indicated bancassurance more cost-efficient than a salesperson. The empirical result shows that insurers with more dependence on salesperson channel present lower complaint ratio and higher contract persistency due to better service quality. The empirical result also indicates that service quality has a significantly positive impact on insurer’s reputation. This finding implies that the insurers with more dependence on bancassurance should take additional competitive strategies to maintain the long-term customer relation.
EU-China Joint V2X Trial

—This article summarizes the main research and trial results of the 5G-DRIVE project. The European 5G-DRIVE and Chinese 5G Large-Scale Trial projects were twinning projects that aim to design Cellular Vehicle-to-Everything (C-V2X) assisted automated driving use cases and to trial out these use cases in the field experiments under a harmonized trial framework. One of the main objectives was to benchmark C-V2X connectivity between Europe and China. Evaluating the benefits of C-V2X connectivity at urban intersection use cases has been conducted. The main Key Performance Indicators include coverage range at the urban intersection, packet error rate and latencies which depends on antenna height and channel load. The comparison between long-range LTE/5G and short-range C-V2X/PC5 channels has been conducted. C-V2X provides low latencies (< 40 milliseconds in average) and coverage is less than 800 meters. LTE/5G supports longer ranges but it cannot guarantee latencies less than 70 milliseconds, which reduces safe driving speed to 30 km/h to keep the safety-margin at 0,6 meters.
DEVELOPMENT OF ELECTRO-FENTON TECHNIQUE AND THE STUDY ON BACTERIAL INACTIVATION IN SEAWATER BY NB-TA / ACF BIPOLAR ELECTRO-FENTON

Electro-Fenton technology is a new type of electrochemical advanced oxidation technology in water treatment in recent years. The treatment for microorganisms, such as bacteria, has been the main problem of discharge of ballast water. In this paper, a new type of bipolar electro-Fenton of Nb-Ta/ACF was proposed, and the inactivation for bacteria by the bipolar electro-Fenton technology was studied. The results showed that the NbTa/ACF bipolar electro-Fenton technique is effective for the inactivation for bacteria, and the sterilization efficiency could reach up 99%. Electrodes materials, operation voltage, pH and electrolytic time have influence the sterilization efficiency. In experimental range, the optimum pH was 8.17, which is the pH of raw water without adjustment. High voltage is helpful to improve the sterilization efficiency. Electrodes materials affect the sterilization efficiency by the bipolar electro-Fenton process. Anode of Nb-Ta (Niobium Tantalum) is much better than the effect of anode of Fe.
Analysis of Trained Convolutional Neural Network using Generative Adversarial Network

In recent years, the increasing burden on doctors due to the shortage of doctors has become a problem in the medical site, and CNN-based methods that can realize highly accurate diagnosis by image recognition are attracting attention as a method to automate diagnosis to ease the burden on doctors. However, in the medical site, it is required to provide explanations to patients, and CNN-based methods have not been introduced to the site because it is difﬁcult to explain the results. Therefore, we proposed a method using Attention-Guided CycleGAN as a method to analyze the differences in regions and patterns recognized by CNN for the explanation of diagnosis using CNN, and evaluated the validity of analysis from the results of the transformation, the similarity of regions of focus, and the effectiveness of transformation for diagnosis using CNN. The results show that Attention-Guided CycleGAN may be effective for the analysis of CNN, because the transformation results are in line with symptoms between cardiomegaly and asymptomatic patients, and be also effective for diagnosis by CNN.
A Prediction Method of Driving Range Based on LSTM Combined with Causal Convolution

Accurate prediction of driving range of electric vehicles (EVs) is critically important to help optimize energy management. In this paper, a novel method to perform accurate driving range prediction is investigated using long short-term memory(LSTM) recurrent neural network combined with convolution layers. The data used in this paper are obtained from the National Monitoring and Management Platform for New energy vehicles. First, the data cleaning is applied to deal with abnormal values and missing values. Then, the datasets are constructed by the sliding window method. Finally, the LSTM model is built and the convolution layers are connected to the model. Dropout method is also introduced to prevent the model from overfitting. The results show that the proposed method can accurately predict the driving range, and the average RMSPE 0.099.
On the Analytical Approach to Present Engineering Problems: Photovoltaic Systems Behavior, Wind Speed Sensors Performance, and High-Speed Train Pressure Wave Effects in Tunnels

At present, engineering problems required quite a sophisticated calculation means. However, analytical models still can prove to be a useful tool for engineers and scientists when dealing with complex physical phenomena. The mathematical models developed to analyze three different engineering problems: photovoltaic devices analysis; cup anemometer performance; and high-speed train pressure wave effects in tunnels are described. In all cases, the results are quite accurate when compared to testing measurements.
Identity-Based Encryption An Alternative to Public Key Encryption In Cloud Computing.

Identity-Based Encryption (IBE) which simplifies the public key and certificate management at Public Key Infrastructure (PKI) is an important alternative to public key encryption. However, one of the main efficiency drawbacks of IBE is the overhead computation at Private Key Generator (PKG) during user revocation. Efficient revocation has been well studied in traditional PKI setting, but the cumbersome management of certificates is precisely the burden that IBE strives to alleviate. In this paper, aiming at tackling the critical issue of identity revocation, we introduce outsourcing computation into IBE for the first time and propose a revocable IBE scheme in the server-aided setting. Our scheme offloads most of the key generation related operations during key-issuing and key-update processes to a Key Update Cloud Service Provider, leaving only a constant number of simple operations for PKG and users to perform locally. This goal is achieved by utilizing a novel collusion-resistant technique: we employ a hybrid private key for each user, in which an AND gate is involved to connect and bound the identity component and the time component. Furthermore, we propose another construction which is provable secure under the recently formulized Refereed Delegation of Computation model. Finally, we provide extensive experimental results to demonstrate the efficiency of our proposed construction.
Estimating the reliability of electrical connectors

Some current approaches to estimating the reliability of electrical contacts and connectors are discussed. These approaches center on the statistical analysis of test data and address the active degradation mechanisms, the determination of appropriate environmental tests with corresponding acceleration factors and exposures, the statistical analysis appropriate for the test data, and the establishment of appropriate acceptance criteria. Each of these issues is treated separately. Multiposition connectors and Mil-Hdbk-217 are discussed. The authors deprecate reliability predictions based on generic databases and failure rate models, such as Mil-Hdbk-217, and describe instead what should constitute a reliability qualification program. >
THE RHETORIC OF ECONOMICS AND FLECK’S CONSTRUCTIVISM AS A COHERENT ALTERNATIVE TO THE SCIENTIFIC REALISM IN THE PHILOSOPHY OF ECONOMICS

In this article, I analyze the case study of the Reinhart-Rogoff controversy from two perspectives: (1) scientific realism, the most popular approach to the philosophy of economics and (2) two constructivist approaches: the rhetoric of economics coined by Deidre McCloskey and constructivism developed by Ludwik Fleck. I aim at showing that the two explanations of the controversy present in the literature are inappropriate because of being committed to the philosophical assumptions of the scientific realism. On the contrary, if the Reinhart-Rogoff controversy is understood appropriately, i.e. as a result of alternative, similarly justified methodological decisions, then the constructivist approach offers a better descriptive adequacy and a more fruitful methodology. Additionally, I aim at showing that Fleck’s constructivism and McCloskey’s rhetoric of economics together constitute a coherent and attractive alternative for the scientific realism.
Consumer Decision to Upgrade Smart Phones : The Mediating Effects of the Fear of Product

With increasing requirements for better functions, performance and appearance of smart phones, consumers upgrade their smart phones more frequently than before. The pursuit of upgrading may provide many market opportunities, as well as great business risks, to firms. In line of the research streams in replacement behavior, this study focuses on consumers’ decision of upgrading smart phones. The framework of this research stems from the rationale of consumer psychology and the corresponding hypotheses are proposed. We analyzed the data collected in China for hypothesis testing. Our findings show that consumers’ personal traits (conformity and need of uniqueness) positively influence the intention to upgrade smart phones. The fear of product obsolescence also exerts a partial mediating effect on the trait-intention relationship.
High genetic diversity despite drastic bottleneck in a critically endangered, long-lived seabird, the Mascarene Petrel Pseudobulweria aterrima

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. High genetic diversity despite drastic bottleneck in a critically endangered, long-lived seabird, the Mascarene Petrel Pseudobulweria aterrima Jade Lopez, Natacha Nikolic, Martin Riethmuller, Jérôme Dubos, Patrick Pinet, Patxi Souharce, François-xavier Couzi, Matthieu Le Corre, Audrey Jaeger, Laurence Humeau
Electricity price short-term forecasting using artificial neural networks

This paper presents the system marginal price (SMP) short-term forecasting implementation using the artificial neural networks (ANN) computing technique. The described approach uses the three-layered ANN paradigm with backpropagation. The retrospective SMP real-world data, acquired from the deregulated Victorian power system, was used for training and testing the ANN. The results presented in this paper confirm considerable value of the ANN based approach in forecasting the SMP.
Effect of loading, voltage difference and phase angle on the synchronisation of a small alternator

Synchronisation of small distributed generation, 30 kVA-2 MVA, employing salient-pole synchronous machines is normally performed within a narrow range of tolerances for voltage, frequency and phase angle. However, there are situations when the ability to synchronise with non-ideal conditions would be beneficial. Such applications include power system islanding and rapid generator start-up. The physical process and effect of out-of-phase synchronisation is investigated both through simulation and experimental tests on a salient-pole alternator. There are many factors that affect synchronisation, but particular attention is given to synchronisation angle, voltage difference and, as generators will be loaded during islanding, the load angle. The results suggest that it would be acceptable for the maximum synchronisation angle of distributed generation to exceed that of current practice. Interesting observations on the nature of out-of-phase synchronisation are made, including some specific to small salient-pole synchronous machines. Furthermore, recommendations are made for synchronisation under different system conditions.
An Assessment of Wind Energy Potential to Meet Electricity Demand and Economic Feasibility in Konya, Turkey

In this study, wind energy potential of Selcuk University campus region was investigated by means of wind data, which were obtained locally from a special observation station. The wind data were collected during the year 2005 at three different heights and were statistically analyzed with the help of MS office, Alwin, Wasp, and Witerm software. It is obtained that yearly averaged wind velocities of the region in 2005 at 10, 20, and 40 m of the mass height were found to be 5.36, 5.40, and 6.05 m/s, respectively. The power density of the region at 40 m was in the range of 260–308 W/m2 with a medium level. For consideration of the calculation, wind speed frequency histogram, Rayleigh and Weibull distributions, wind direction, and temperature data were also used. The obtained results were used for evaluating electricity production of a 6 MW capacity wind farm composed of 1.0, 1.5, and 2.0 MW wind turbines. In addition, the planned wind farm was economically evaluated by means of the basic payback, the net present value, and the internal rate of return methods. The minimum basic payback period was found to be 6.44 years. The results were discussed and interpreted to encourage the investors for establishing wind farm in the region.
A Memory Matching Algorithm Based on Box IoU Features for Pedestrian Flow Counting

Automatic pedestrian ﬂow counting on street view surveillance video is faced with challenges such as occlusion, illumination changes and scale changes. These challenges lead to misdetection which affect the accuracy of pedestrian ﬂow counting. Aiming at these problems, a memory matching algorithm based on box Intersection over Union (IoU) features of inter frame bounding box is proposed. By memorizing the box IoU features between frames, the algorithm can ignore the false detected pedestrians and track the lost pedestrians to a certain extent, so as to improve the accuracy of counting. The experimental results on the UCSD data set show that the algorithm has high accuracy which reaches 97.2%.