Miracle-dz/UniFAR-FTUs huggingface dataset:
Social screening and mutual fund performance: international evidence

This paper investigates the relationship between the risk-adjusted performance and the screening strategies of 330 US and European equity socially responsible mutual funds over the period 2003-2014. On aggregate, the results support the argument that investors can pursue their ethical investment policies without sacrificing financial returns. For US and Scandinavian funds, we find a curvilinear relationship between screening intensity and performance: US funds exhibit an inverted U-shaped effect, while Scandinavian funds, consistent with Barnett and Salomon (2006), show a U-shaped effect. Differently, for UK funds, there is a negative linear relationship between the number of screens and returns. For the other countries, there is no significant relationship between screening and fund performance. Furthermore, the results show that the type of the screening activities of US and UK socially responsible funds have a significant impact on risk-adjusted returns. For US funds, environment and products screens negatively impact performance, whilst corporate governance contributes to performance. In turn, UK funds that screen on the basis of products have relatively stronger performance. Finally, positive screening yields lower performance the global sample and for US funds.
Cash-In-Advance Constraints in a Schumpeterian Growth Model with an Endogenous Market Structure

This paper explores the macro e ects of monetary policy in a Schumpeterian growth model with an endogenous market structure and distinct cash-in-advance (CIA) constraints on consumption, production, and two distinct types of R&D investment in-house R&D and entry investment. We show that the CIA constraints work through various channels and the e ects of monetary policy depend on the strength of each channel. Although in ation seems like a uniform tax imposed on the whole economy, an identical monetary policy can render di erent distortions of in ation on the economy and give rise to quite di erent consequences. Speci cally, if in-house R&D or quality improvement-type R&D (entry investment or variety expansion-type R&D) is subject to the CIA constraint, raising the nominal interest rate decreases (increases) the rm's market size and economic growth. If either production or consumption is subject to the CIA constraint, growth is immune from money, while the market structure and employment are responsive. Besides, in the presence of various cash constraints our model also generates rich transitional dynamics in response to a change in monetary policy. JEL classi cation: O30, O40, E41.
“HOME SWEET HOME”: PRECLUDING TWO SOURCES OF ACADEMIC STRESS IN HIGHER EDUCATION THROUGH DISTANCE /E-LEARNING

This paper compares student psychological cost—especially in relation to stress and anxiety caused by academic requirements—of traditional higher education with that incurred by distance/e-learning, with the two kinds of track found to have both similarities and differences. Two potential sources of academic stress are then investigated more thoroughly. The first consists of requirements for class participation, which can cause stress and anxiety in shy or introverted students who find it difficult to speak before or within groups. The second consists of conflicts between student expectations of the educational situation and actual teacher or classmate behaviours and attitudes, a potentially stressful mismatch which occurs most often in cross-cultural education. These two sources of academic stress are found to be much more prevalent in traditional education venues than in distance/ e-learning. It is suggested that students, especially international students and those with social anxiety, take these factors into consideration when choosing whether to enter a traditional higher education or a distance/ e-learning track.
Exercise with Social Robots: Companion or Coach?

In this paper, we investigate the roles that social robots can take in physical exercise with human partners. In related work, robots or virtual intelligent agents take the role of a coach or instructor whereas in other approaches they are used as motivational aids. These are two"paradigms", so to speak, within the small but growing area of robots for social exercise. We designed an online questionnaire to test whether the preferred role in which people want to see robots would be the companion or the coach. The questionnaire asks people to imagine working out with a robot with the help of three utilized questionnaires: (1) CART-Q which is used for judging coach-athlete relationships, (2) the mind perception questionnaire and (3) the System Usability Scale (SUS). We present the methodology, some preliminary results as well as our intended future work on personal robots for coaching.
Combinatorial Multi-Armed Bandit Based Unknown Worker Recruitment in Heterogeneous Crowdsensing

Mobile crowdsensing, through which a requester can coordinate a crowd of workers to complete some sensing tasks, has attracted significant attention recently. In this paper, we focus on the unknown worker recruitment problem in mobile crowdsensing, where workers’ sensing qualities are unknown a priori. We consider the scenario of recruiting workers to complete some continuous sensing tasks. The whole process is divided into multiple rounds. In each round, every task may be covered by more than one recruited workers, but its completion quality only depends on these workers’ maximum sensing quality. Each recruited worker will incur a cost, and each task is attached a weight to indicate its importance. Our objective is to determine a recruiting strategy to maximize the total weighted completion quality under a limited budget. We model such an unknown worker recruitment process as a novel combinatorial multi-armed bandit problem, and propose an extended UCB based worker recruitment algorithm. Moreover, we extend the problem to the case where the workers’ costs are also unknown and design the corresponding algorithm. We analyze the regrets of the two proposed algorithms and demonstrate their performance through extensive simulations on real-world traces.
TEST FOR CREATIVE THINKING-DRAWING PRODUCTION (TCT-DP): A REVISED FACTORIAL STRUCTURE IN AN ADULT SAMPLE

This research aims to assess the factorial structure of the Test for Creative Thinking-Drawing Production (TCT-DP, Urban & Jellen, 1996) for a Portuguese adult sample, with 620 workers, revisiting the results obtained by Almeida, Ibérico Nogueira, and Lima (2018). Two studies were performed. In Study 1, an exploratory factor analysis (EFA) assessed the factorial structure of the TCT-DP, with three hundred and two individuals (N = 302), most of them women (55.6%), from 18 to 86 years (M = 41.1, SD = 10.7). In Study 2, a confirmatory factor analyses aimed to replicate the factorial solution identified in Study 1, with three hundred and eighteen individuals (N = 318), most of them women (56.6%), from 19 to 70 years (M = 40.6, SD = 10.1). The two-factor solution (F1Adaptiveness; F2Innovativeness) proposed in Study 1 had acceptable to marginal fit indices. As in the study of 2018, two factors emerged and are respectively composed by the same items. Once more, the results highlight the importance of both non-conventional and conventional thinking for the creative process, sustaining our TTT-Two Tracks of Thought model. Some of the items which belong to the Adaptiveness factor, lead us to reflect on the parental features and developmental path.
The Combined Effect of International Diversification and Product Diversification Strategies on the Performance of U.S.-Based Multinational Corporations

■ Multinational corporations (MNCs) pursue the dual strategies of product diversification a d international diversification a d attempt to achieve a combination which results in optimal worldwide performance. ■ Hypotheses were generated and tested by analyzing data on 53 U.S. MNCs. Multiple measures of both product and international diversification were used.
Facilitation of Research-Based Evidence within Occupational Therapy in Stroke Rehabilitation

Purpose: This study investigated the facilitation of evidence-based practice with the use of everyday life occupations and client-centred practice within occupational therapy in three settings of stroke rehabilitation. Method: The study was based on a phenomenological hermeneutical research approach, and inspired by participatory action research methods. Participant observations, focus group discussions and individual interviews took place over a period of 20 months. Text interpretation, developed by Ricoeur, was used in data analysis. Findings: The key role of the facilitator in the implementation of evidence-based practice as a change process was stressed. During the implementation, it was crucial that the therapists as a group had the opportunity to discuss local practice knowledge, and to appraise the knowledge use critically, in order to develop their practice knowledge and new skills adapted to local contexts. The implementation resulted in various new working routines. Learning processes became part of developing the occupational therapists' professional identities, expressed in more professional confidence. Collaboration in the organisation of the implementation process was significant. Conclusion: The main findings indicated that the use of participatory action research methods and theory of situated learning interacting with the Promoting Action on Research Implementation in Health Services framework provided useful perspectives and structures for the investigation of the implementation of evidence-based occupational therapy.
Incentives for Spot Market Labor When Output is Unverifiable∗

This paper studies a novel contracting environment plagued by moral hazard. The setting differs from traditional agency theory along two dimensions: no signal about whether effort was exerted is available, and the firm is unable to threaten workers with negative wage payments. The paper characterizes the firm’s optimal incentive organization. The firm hires multiple workers to perform some tasks as a monitoring device. Consequently, monitoring is determined endogenously. The optimal mechanism features two distinctive features absent in standard contracting solutions. First, the firm monitors with nontrivial probability by hiring additional workers to complete a subset of the tasks it assigns to any agent. Second, the firm bundles multiple tasks together to reduce the per-task cost of monitoring. By assigning more tasks to each worker and conditioning wage payment for any task on satisfactory performance on all tasks, the firm approximates its first-best payoffs even when firing and large punishments are unavailable. ∗We thank Nageeb Ali, Cécile Aubert, Gordon Dahl, Roger Gordon, Kevin Lingerfelt, Mark Machina, David Miller, David Rahman, Joel Sobel, Ross Starr and Joel Watson.
DARK GRAVITATION THEORY FOR MILKY WAY AND M31 GOT BY BUCKINGHAM THEOREM –V6

1 Author Manuel Abarca Hernandez email mabarcaher1@gmail.com 1. ABSTRACT . 2 2. INTRODUCTION . 3 3. M31 OBSERVATIONAL DATA FROM SOFUE. 2015 PAPER. 4 3.1 POWER REGRESSION TO ROTATION CURVE. 5 4. DIRECT FORMULA FOR DM DENSITY ON M31 HALO GOT FROM ROTATION CURVE . 6 4.1 THEORETICAL DEVELOPPMENT FOR GALACTIC HALOS. 6 4.2 DIRECT DM DENSITY FOR M31 HALO . 7 5. DARK MATTER DENSITY AS POWER OF GRAVITATIONAL FIELD. 7 5.1 GRAVITATIONAL FIELD E BY VIRIAL THEOREM . 7 5.2 DARK MATTER DENSITY AS POWER OF GRAVITATIONAL FIELD . 7
Secure Service Provisioning Scheme for Lightweight IoT Devices With a Fair Payment System and an Incentive Mechanism Based on Blockchain

The Internet of Things (IoT) industry is growing very fast to transform factories, homes, farms and practically everything else to make them efficient and intelligent. IoT is applied in different resilient scenarios and applications. IoT faces lots of challenges due to lack of computational power, battery and storage resources. Fortunately, the rise of blockchain technology facilitates IoT in many security solutions. Using blockchain, communication between IoT and emerging computing technologies is made efficient. In this work, we propose a secure service provisioning scheme with a fair payment system for Lightweight Clients (LCs) based on blockchain. Furthermore, an incentive mechanism based on reputation is proposed. We use consortium blockchain with the Proof of Authority (PoA) consensus mechanism. Furthermore, we use Smart Contracts (SCs) to validate the services provided by the Service Providers (SPs) to the LCs, transfer cryptocurrency to the SPs and maintain the reputation of the SPs. Moreover, the Keccak256 hashing algorithm is used for converting the data of arbitrary size to the hash of fixed size. AES128 encryption technique is used to encrypt service codes before sending to the LCs. The simulation results show that the LCs receive validated services from the SPs at an affordable cost. The results also depict that the participation rate of SPs is increased because of the incentive mechanism.
Genetic Algorithm Based Approach for the Multi-Hoist Design and Scheduling Problem

Electroplating facilities often face the Cyclic Hoist Scheduling Problem when a repetitive sequence of moves is searched for the hoists. This paper addresses this optimization problem extended to the design of the workshop, where we aim to minimize both the cycle time and the number of hoists used. For this goal, we propose a genetic meta-heuristic approach which introduces a novel solution encoding to enlarge the solutions’ search space. Our encoding procedure is based on hoists’ empty moves, and includes separator characters. With the latter, we obtain solutions that were not reachable by previous approaches. Each solution obtained thanks to the genetic operators is evaluated by using a Mixed Integer Linear Program. This one checks the constraints of the problem (such as capacity constraints and soaking time bounds) and computes the smallest cycle time for a given moving sequence and its associated number of hoists. Some results are presented using benchmark instances for which our approach allows to improve the best known solutions.
Comparison of Various Instantaneous Power Methods for the Estimation of Time-Parameters of Poly Phase Coded Radar Signal

Key feature of the electronic intelligence (ELINT) setup as part of the electronic warfare is the interception and analysis of radar signals. This paper as part of ELINT provides a time parameter estimation algorithm associated with poly-phase pulsed radar signal of low probability of intercept (LPI) in a non-cooperative environment in order to identify its other characteristics. Three different methods based on power obtained at instants of time are used. The first two are obtained from the time-aspect approximation of a time-frequency distribution (TFD) while the third one is the traditional method of using its conjugate form. The main TFD used in this paper is Wigner-Ville distribution (WVD) of separable kernel and its brief heuristic approach was presented. Thereafter, an algorithm based on measuring the time-spectrum width is developed so as to determine two basic time parameter of the radar signal; either the pulse width (PW) or the pulse repetition period (PRP). The quality of the algorithm developed is tested at various signal-to-noise ratios (SNRs) in the presence of noise modeled by pseudorandom numbers of Gaussian nature. The Result obtained shows that for a fixed threshold of 37.5%, power at instants of time obtained from the TFD performs best at minimum SNR of −15 dB. The traditional method of getting power at instants of time performs very well if a variable threshold is applied at minimum SNR of −11 dB. The results shows that the proposed methods may be deployed in the practical ELINT field for analysis of radar signal
Studies of Electromagnetic Disturbances in Coupling Path by Application of Intentional Ultrashort Electromagnetic Pulses

An experimental stand has been developed for the study of electromagnetic disturbance in coupling paths of electronic system by intentional influence ultrashort electromagnetic pulses (. Electromagnetic disturbances is being studied using experimental methods and methods simulating of electromagnetic processes. Comparison of the research results using experimental methods and methods simulating of electromagnetic processes have been shown high convergence.
Energy-Efficient Power Allocation and Joint User Association in Multiuser-Downlink Massive MIMO System

Singular value decomposition is highly essential to achieve a higher performance in signal processing using massive multiple-input multiple-output (MIMO) systems. This paper aims to provide a solution to control power allocation problem identified as an essential metric in a massive MIMO system that maximizes energy efficiency (EE). The network performance was evaluated by measuring circuit power consumption to maximize EE. The computational efficiency to maximize EE power allocation is very important to fifth generation networks (5G). The study aims to maximize the non-convex EE in a downlink (DL) massive MIMO system using a proposed energy-efficient low-complexity algorithm (EELCA) that guarantees optimal power allocation solution based on Newton’s methods and joint user’s association based on the Lagrange’s decomposition method. An optimal power allocation solution in closed form to decrease the complexity of the power subject to both the maximum power and minimum data rate constrained systems was derived. Then, the unconstrained EE power allocation to solve the unconstrained optimal power was used to select the optimal power allocation by computing a root of the first derivative of the EE based on differentiating the instantaneous power allocation to maximize EE was formulated. Simulation results showed that the proposed EELCA with a total transmitted power allocation provided maximum EE for a large number of antennas at the base station (BS), Generally, non-linear schemes outperformed linear schemes. Finally, the large cost of circuit power consumption increased at the BS due to the large loss of radio frequency (RF) chains at every antenna when the signals were transmitted to all users. The maximum EE = 5.9 Mbits/joule when the number of distributed users, $K=33$ , with $\left ({p_{c}, M }\right )=\left ({ 1000\mathrm {mW},200 }\right )$ . The proposed low complexity algorithm provides the better result EE based on a training channel for a number of distributed users.
Users Supporting Multiple (Mobile) Electronic Payment Systems in Online Purchases: An Empirical Study of Their Payment Transaction Preferences

The online payment for products or for the access to payment-based services can be made by means of a range of (mobile) electronic payment systems – (M)EPS. Both the industrial sector and research community, mainly World Wide Web Consortium (W3C), are working on facilitating these payment methods on Web and supporting the multiple users on how they can select the suitable (M)EPS. However, to the best of our knowledge, there were no thorough studies considering consumer’s preferences when they support multiple (M)EPS. To address this issue, we have performed a survey on an international participants (n=272) aiming to (i) developed a theoretical model to determine their preferences when they are supporting more than one (M)EPS, (ii) find the most valuable option according to them and (iii) determine the surrounding conditions that support their decision to use a specific (M)EPS. The theoretical framework of this study was based on the Technology Acceptance Model (TAM). According to our statistical analysis (Chi-square test), consumers that can pay using different (M)EPS during their online payment transaction, have a preferred payment system based on its security, fees, usefulness, and ease of use as well as on their favorite Web browser for these transactions. Factor analysis was also performed to identify factors that much influence the (M)EPS. Results revealed that the factors influencing online payment preferences differ from those involved in traditional payment methods. Our findings allowed, therefore, providing practical suggestions for supporting payment processes with Web browsers and the W3C payment Application Program Interface (API).
Economic ordering model for deteriorating items with limited price information

Traditional economic ordering model for deteriorating items assume the procurer have full information about the procurement price. In this paper, we study an economic ordering model for constant deteriorating rate items with limited price information under relative performance criterion of the competitive ratio (CR). We provide a simply procurement strategy as well as the optimal ordering quantity for each case. This procurement strategy is real-time and doesn’t require any forecast, i.e., upon the arrival of price, the strategy concerning procurement time and quantity only be made based on arriving price and current inventory level, with entirely arbitrary non-stationary and even adversarial price sequence arrivals. A theoretical closed-form CR is also proven to give the performance guarantee. Our numerical experiments demonstrate even better empirical performance than the corresponding proven worst-case bounds.
Admittance Control Based Humanoid Robot Standing Balance Control

Balance Control has always been an important research area for humanoid robot. In this paper, admittance control was used as a basic control scheme for humanoid robot to withstand external force disturbances while standing. This paper addresses three typical disturbances, which include tilted ground with unknown angles, placing foot on ground with unexpected obstacles and external forces on upper body due to unexpected contacts, and applies admittance control and some specific adaptations to each disturbance setting to improve the standing stability of the robot.
A New Tunnelling Model To Calculate GIDL Current For MOSFET And TFET

This paper has proposed an innovative band to band tunneling current model using De- Casteljau’s algorithm, followed by Bezier curve method and WKB approximation. After verifying the validity of this proposed tunneling model with respect to electron energy and tunnel width, the expression of tunneling probability is applied to the graded drain MOSFET and TFET to find out the expression of Gate-Induced-Drain- Leakage current. The variation of this leakage current of this proposed model is verified by comparing with other previous models and the result is well matched.
Auto Tuning Self-Optimization Algorithm for Mobility Management in LTE-A and 5G HetNets

Ultra-dense networks represent the trend for future wireless 5G networks, which can provide high transmission rates in dense urban environments. However, a massive number of small cells are required to be deployed in such networks, and this requirement increases interference and number of handovers (HOs) in heterogeneous networks (HetNets). In such scenario, mobility management becomes an important issue to guarantee seamless communication while the user moves among cells. In this paper, we propose an auto-tuning optimization (ATO) algorithm that utilizes user speed and received signal reference power to adapt HO margin and time to trigger. The proposed algorithm aims to reduce the number of frequent HOs and HO failure (HOF) ratio. The performance of the proposed algorithm is evaluated through simulation with a two-tier model that consists of 4G and 5G networks. Simulation results show that the average rates of ping-pong HOs and HOF are significantly reduced by the proposed algorithm compared with other algorithms from the literature. In addition, the ATO algorithm achieves a low call drop rate and reduces HO delay and interruption time during user mobility in HetNets.