Miracle-dz/UniFAR-FTUs huggingface dataset:
Valuing hypothetical wildfire impacts with a model of recreation demand

This study uses a nonmarket valuation method to investigate the recreation values of the San Jacinto Wilderness in southern California. The analysis utilizes survey data from a stated-choice experiment involving backcountry visitors who responded to questions about hypothetical wildfire burn scenarios. Benefits of landscape preservation are derived using a Kuhn-Tucker (KT) demand system. Model results suggest that recreationists are attracted to sites with recent wildfires that can be viewed up-close. For example, recreational welfare estimates increased for sites that were partially affected by different types of wildfires, with the greatest gains being observed for the most recent wildfires. Per person mean seasonal willingness-to-pay varied from a low of $1.23 to a high of $11.05, for total gains ranging from $8,758 to $146,993. However, wildfires that cause trail closures create welfare losses. Seasonal losses per person for complete closure of particular sites range from $3 to $221, for total losses ranging from $29,600 to $2.9 million.
iClarify – A Tool to Help Requesters Iteratively Improve Task Descriptions in Crowdsourcing

Quality control and assurance are among the most important challenges in crowdsourcing. Low quality and sub-optimal responses from crowdworkers have been found to often result from unclear or incomplete task descriptions, especially from novice or inexperienced task requesters. Creating clear task descriptions with adequate information however, is a com-plex task for requesters in crowdsourcing marketplaces. To meet this challenge, we present iClarify , a tool that enables requesters to iteratively discover and revise eight common clarity ﬂaws in their task description before deployment on the platform. A requester can use iClarify to formulate a task description from scratch or also to evaluate the clarity of pre-pared descriptions. The tool employs support vector regres- sion models based on various feature types that were trained on 1332 annotated real-world task descriptions. Using these models, it scores the task description with respect to the eight ﬂaws, and the requester can iteratively edit and evaluate the description until the scores shown by the tool reach a satisfactory level of clarity. We are currently conducting a usabil- ity study with both requesters and crowdworkers to assess to which extent the tool is effective in improving task clarity.
Low Overhead Remote Procedure Call System for Saturn DSP

System-on-a-Chip designs with specialized processors and domain-speciﬁc accelerators have grown in popu-larity over the last decade to meet ever-increasing compute demands. This is due to the superior performance-per-watt that can be obtained from such designs as well as the inherent limitations in scaling up traditional out-of-order superscalar CPUs. However, a heavy reliance on microarchitectural details and a lack of coordination between software writers and hardware designers makes targeting these specialized IPs highly non-trivial. In addition, ofﬂoading tasks from the CPU to an accelerator introduces overheads that may nullify the advantage of utilizing it in the ﬁrst place. This paper investigates a transparent method for allowing programmers to run user code on digital signal processing units (DSPs) and quan-tiﬁes the impact of such an ofﬂoad. We propose a lightweight framework at the system software level in the style of message passing Asymmetric Multiprocessing kernels. By pairing a large symmetric multiprocessing kernel with a lightweight real-time operating system, we ﬁnd that we can achieve near speed-of-light accelerator communication while maintaining a relatively straightforward programming model.
A survey on recent activation functions with emphasis on oscillating activation functions

The neural network learning and generalizing mechanisms of the brain have always intrigued scientists and researchers. Therefore, with the aim to mimic these “physiological workings” of the brain, the concept of using layers of artificial neurons (nodes) to make experienced predictions, accurate decisions, etc (Artificial neural network (ANN)) was introduced [5]. This paper briefly discusses few activation functions that have been used frequently over the years. In addition to that, the recent propositions regarding oscillating activation functions have been dealt with.
A Survey of Adversarial Attacks and Defenses for image data on Deep Learning

—This article provides a detailed survey of the so-called adversarial attacks and defenses. These are special modifications to the input data of machine learning systems that are designed to cause machine learning systems to work incorrectly. The article discusses traditional approaches when the problem of constructing adversarial examples is considered as an optimization problem - the search for the minimum possible modifications of correlative data that ”deceive” the machine learning system. As tasks (goals) for adversarial attacks, classification systems are almost always considered. This corresponds, in practice, to the so-called critical systems (driverless vehicles, avionics, special applications, etc.). Attacks on such systems are obviously the most dangerous. In general, sensitivity to attacks means the lack of robustness of the machine (deep) learning system. It is robustness problems that are the main obstacle to the introduction of machine learning in the management of critical systems.
Short Turkish Version of Proactive Scale: A Study of Validity and Reliability

Accepted: 06.04. 2015 Proactivity is the most popular concept of positive psychology in industrial and psychological area. Thus the aim of this research is to adapt the Short Version of Proactive Personality Scale with 10–item (Claes, Beheydt, & Lemmens, 2005) into Turkish and to examine its psychometric properties. The research was conducted on 332 university students. Results of language equivalency showed that the correlations between Turkish and English forms were ranged from . 74 to . 90. The corrected item-total correlations ranged from . 52 to . 66. Results of confirmatory factor analysis demonstrated that the ten items loaded on one factor and the uni-dimensional model was well fit (x2= 47.91, df= 29, x2/df= 1,65, RMSEA= .044, NFI= .99, CFI= .99, IFI= .99, RFI= .97, GFI= .97, AGFI= .95, SRMR= .033). The internal consistency reliability coefficient of the scale was found as . 86. Thus this scale is a valid and
Supporting Social Discovery of Appropriate Candidates for Promotion to Administrative Status in Wikipedia

—Online systems that rely on their participants to provide oversight and governance face the challenge of assigning administrative rights to appropriate people in the community of users. This study examines how system tools in one such system, Wikipedia, support and constrain the social processes of administrative rights granting. Reporting on the results of a survey of community participants in the English Wikipedia “Request for Adminship” process, the study offers an analysis of system tools in support of a high-stakes social process. It discovers that the existing tools offering basic counts of user actions in the system are not generally perceived as valuable; instead, members of the community develop nuanced, individualized means of assessing administrative candidates. The study offers insights into the implications of tool design for self-governing online systems.
Vertical rescaled berger deformation metric on the tangent bundle

In this paper, we introduce the vertical rescaled berger deformation metric on the tangent bundle TM over an anti-paraK¨ahler manifold ( M 2 m , ϕ, g ) as a new natural metric with respect to g non-rigid on TM . Firstly, we investigate the Levi-Civita connection of this metric, Secondly we study the curvature tensor and also we characterize the scalar curvature.
Evaluation of Effectiveness of Aromatherapy in Managing Anxious Paediatric Dental Patient: An In-Vivo study

Aim : To evaluate the effectiveness of aromatherapy in the reduction of dental anxiety of pediatric dental patients. Methodology : Present In-Vivo study was conducted to evaluate the effect of aromatherapy on child anxiety during dental treatment. A total of 40 children, aged 6-10 years, attending for their first dental visit were included as study participants. Samples were randomly divided into two groups (Control group: Treatment in normal dental set-up, Experimental group: Treatment under aroma). Venham’s picture scale (VPS) was used to assess anxiety. The data were entered over a spreadsheet, and statistical analysis was performed using SPSS software version 16 (IBM, Chicago, United States). Result : The post- exposure mean scores of Venham’s picture scale (VPS) were lower in the experimental group. Conclusion : Aromatherapy is an effective alternative therapy that can be practiced in dentistry for anxious pediatric dental patients as it reduces anxiety while not affecting pain.
OPTIMAL TRANSPORT FOR DISCRETE DISTRIBUTIONS

In this note we describe and implement three algorithms related to computational optimal transport. We give a brief background on the associated problem and describe the network simplex algorithm in detail. We then proceed to consider the case of entropically regularized optimal transport, where we describe the sinkhorn and greenkhorn algorithms. Finally, after implementing these three algorithms, we compare to the benchmark [21] in a thorough performance analysis.
Wi-Lo: Emulation of LoRa using Commodity 802.11b WiFi Devices

The recent move of LoRa towards the unlicensed 2.4GHz ISM spectrum band creates multiple opportunities for its broader usage in new IoT applications. However, the ISM band is already highly populated with diverse wireless systems, and interference issues are expected. We believe that cross-technology communication (CTC) can help to speed up LoRa adaptation and mitigate the coexistence problems. Therefore, in this paper, we introduce Wi-Lo, a novel signal emulation-based CTC approach, which allows a WiFi device to generate a valid LoRa waveform. Our scheme requires no hardware modifications but depends only on the careful selection of WiFi frame payload bits. We build our Wi-Lo prototype with commodity hardware. Our evaluation reveals that Wi-Lo enables reliable communication from WiFi to LoRa devices, which is comparable to the configurations using native LoRa nodes. Moreover, by leveraging the high link budget of LoRa, a long distance CTC can be established.
Design of Dual Band Dual Sense Circularly Polarized Wide Slot Antenna with C-shaped Radiator for Wireless Applications

Abstract A low profile wide slot antenna for dual band and dual sense circular polarization (CP) is proposed here and is simulated by using HFSS simulation software.The proposed antenna having a C shaped patch for dual band operation and a wide square slot etched on the ground with two strips for CP operation. In between radiating patch and ground plane, designed antenna has a layer of easily available dielectric (FR-4) material. Proposed antenna shows an impedance bandwidth of 13.8 % at 2.38 GHz of centre frequency and 9.7 % at 4.43 GHz of centre frequency for lower and upper band respectively. The 3-dB axial ratio (AR) bandwidths for lower and upper band are 18.8 % (at 2.44 GHz of centre frequency) and 13.3 % (at 4.29 GHz of centre frequency), respectively. The peak gain for the lower and upper band is found as 4.1 dBi and 3.3 dBi, respectively. A close agreement has been found between the simulated and the measured results.
LANDING SYSTEM USING EXTENDED DYNAMIC WINDOW APPROACH FOR FIXED-WING UAV

We have developed an autonomous landing system that considers some restrictions of the fixed-wing UAV. The control inputs may become a massive value to go along the landing trajectory that is designed before landing if the attitude of the UAV is disturbed by external disturbances. However, the control inputs of a fixed-wing UAV have saturations. Therefore, the landing guidance method should consider the constraints of the control inputs and the state variables. In the proposed method, The dynamic window approach (DWA) that considers some restrictions on velocity space is applied to the landing mission of a fixed-wing UAV. However, some problems arise when applying DWA to a UAV because DWA was developed for ground vehicles. In this paper, we propose the extended DWA that solves the problems in order to apply to a fixed-wing UAV. The numerical simulations are carried out to confirm the validity of the proposed method.
Influence of operating speed on the thermo-mechanical behaviour of cylindrical roller bearing

Ball and roller bearing, also known as rolling bearing are engineering components that are frequently used in rotating machinery where they function primarily as a support system (Sharma et al., 2018, Sharma et al.). Rolling components are designed to pose high carrying capacity, high strength and low-frictional properties which enable them to serve different engineering purposes (Sharma et al.). Thus, they are utilized in applications that require rotational motion or a component revolving around a shaft in a simple industrial or machinery device. An example of a simple industrial and commercial application of bearing includes electric motors, bicycles, wheels, and roller skates (Ricci, 2010). Similarly, they are utilized in complex engineering machinery applications such as gyroscopes, aircraft/power generation gas turbines, dental drills, power transmission and rolling drills (Ricci, 2010). Due to the conditions of application of roller bearings (exposure to cyclic loading), they often experience engineering failure as a result of different thermo-mechanical reasons. Among these are inherent materials defects developed during fabrication, working conditions, heat generation, high contact/Hertzian stress development and vibration (Ricci, 2010). More often, engineering failure due to bearing collapse mostly lead to breakdown and sometimes catastrophic failure of the equipment. Several bearings are available in the market, and radial bearings are considered one of the most important components in industrial applications because they are suitable and easily adaptable in various machinery (Shao et al.). Other types of bearing used in machinery include thrust bearings, spherical bearings, cylindrical roller bearings and tapered roller bearings (Upadhyay et al., 2013). Of all these bearings, a cylindrical roller bearing of the same size as the other bearings has a higher load-bearing capacity, as such, it is frequently used in moderate speed and heavy-duty applications (Sehgal et al., 2000, Upadhyay et al., 2013).
Understanding User Perceptions of Response Delays in Crowd-Powered Conversational Systems

Crowd-powered conversational systems (CPCS) are gaining considerable attention for their potential utility in a variety of application domains, for which automated conversational interfaces are still too limited. CPCS currently suffer from long response delays, which hampers their potential as conversational partners. The majority of prior work in this area has focused on demonstrating the feasibility of the approach and improving performance, while evaluation studies have primarily focused on response latency and ways to reduce it. Relatively little is currently known about how response delays in a CPCS can affect user experience. While the importance of reducing response latency is widely recognized in the broader field of human-computer interaction, little attention has been paid to how response quality, response delay, conversational context, and the complexity of the task affect how users experience the conversation, and how they perceive waiting for responses in particular. We conducted a between-subjects experiment (N = 478), to examine the influence of these four factors on the overall waiting experience of users. Results show that users 1) evaluated the waiting experience more negatively when the response delay was longer than 8 seconds, 2) underestimated the elapsed time but experienced more frustration in tasks with high complexity, 3) underestimated the elapsed time and experienced less frustration with high quality bot's utterances, 4) judged response delays to be slightly longer, and experienced more frustration in an emotion-centric CPCS compared to a task-centric CPCS. Our insights can inform the design of future CPCSs with regards to defining performance requirements and anticipating their potential impact on the user experience they can facilitate.
A deep learning approach to prepare participants for negotiations by recognizing emotions with voice analysis

: Emotional intelligence plays an essential role in negotiations. In this work we present an approach for emotion recognition (sentiment detection) based on the characteristics of the human voice. It is shown how such an approach can support negotiators to train their emotional intelligence prior to negotiations. Using methods from the field of deep learning, in specific convolutional neural networks, a prototype was developed. The approach is tested and thus validated by various experiments on voice recordings, showing that it is possible to determine emotions to a certain accuracy in real time. This can help, especially young and inexperienced negotiators, to prepare for important negotiations. It is shown that the prototype can make a valuable contribution in the run-up to negotiations through constructive projects.
A Statistical Analysis on Forecasting Prices of Some Important Food Commodities in Bangladesh

: This paper investigates the best possible forecasting price models for three important agricultural products in Bangladesh namely potato, onion and garlic using time-series and secondary data from January 2000 to December 2014. The main objective of this paper is to find out the appropriate time series models using some of the latest selection criteria that could describe the best price patterns of the above mentioned three crops. To forecast the prices of the crops, the ARIMA models were used, based on model selection criteria and error statistics among the competing models. The overall findings of the study indicate that the fitted models are satisfactory for the respective commodities. The study observed increasing trends in forecasted prices of all three commodities. In particular, the increase in the price of garlic has been observed to be very high compared to that of potato and onion. The study also found that the best fitted SARIMA model for potato is SARIMA (1,0,0) (0,1,2) 12, for onion SARIMA (2,0,0) (0,1,1) 12, and for garlic SARIMA (2,1,3) (0,1,3) 12 .
Health Policy Statement on Patient-Centered Care in Cardiovascular Medicine

ardiology Foundation requests that this document be Bove AA, Cross RR, Ferdinand KC, Forman DE, American Co department at Brian MacDonnell David C. May, MD, PHD, FACC Joseph V. Messer, MD, MACC Susan J. Pressler, PHD, RN Mark L. Sanz, MD, FACC John A. Spertus, MD, MPH, FACC Sarah A. Spinler, PHARMD, AACC ouis Evan Teichholz, MD, FACC ohn B. Wong, MD atherine Doermann Byrd William R. Lewis, MD, FACC
Mathematical programming and metaheuristic approaches applied to biological-based ﬂuence map optimization in radiotherapy

Intensity modulated radiation therapy (IMRT) is one of the most eﬀective techniques in cancer treatment. Its main goal is to eradicate all clonogenic cells from the tumour without compromise of surrounding normal tissues. One speciﬁc problem in IMRT is ﬂuence map optimization (FMO). The main goal of FMO is to ﬁnd the optimal set of beamlet intensities given some clinical criteria. Both physical and biological criteria have been developed to tackle the FMO problem. Although most physical models are mathematically tractable and can be solved to optimality they do not include some important clinical considerations as, for example, radio-biological tissue response. On the other hand, biological models although more meaningful usually do not have desirable mathematical features. In this paper we carry out a comparison between metaheuristics and exact methods applied to an unconstrained non-linear biological model based on the well-known generalized equivalent uniform dose. We compare the results in terms of objective function value, time and the obtained dose volume histogram. We apply our algorithms to a non-clinical prostate case.
for Parasite Persistence in Patent Lymphatic Filariasis: Implications Pathways Parasites Impair Both Th1 and Th2 Regulatory Networks Induced by Live

Patent lymphatic ﬁlariasis is characterized by a profound down-regulation of immune responses with both parasite Ag-speciﬁc tolerance and bystander suppression. Although this down-regulation is conﬁned to the Th1 arm of the immune system in response to parasite Ag, we hypothesized a more generalized suppression in response to live parasites. Indeed, when we examined the cytokine proﬁle of a cohort of ﬁlaria-infected ( n (cid:1) 10) and uninfected ( n (cid:1) 10) individuals in response to live infective-stage larvae or microﬁlariae of Brugia malayi , we found signiﬁcant impairment of both Th1 and Th2 cytokines characterized by diminished production of IFN- (cid:2) , TNF- (cid:3) , IL-4, IL-5, and IL-10 in infected patients. The molecular basis of this impaired Th1/Th2 response was examined, and we identiﬁed three major networks of immunoregulation and tolerance. First, impaired induction of T-bet and GATA-3 mRNA underlies the Th1/Th2 deﬁciency in infected individuals. Second, regulatory networks, as evidenced by signiﬁcantly increased expression of Foxp3 (natural regulatory T cell marker) and regulatory effectors such as TGF- (cid:4) , CTLA-4, PD-1, ICOS, and indoleamine 2,3-dioxygenase play an important role in immunosuppression. Third, the compromise of effector T cell function is mediated by the enhanced induction of anergy-inducing factors cbl-b , c-cbl ( cbl is abbreviation for Casitas B lym-phoma), Itch , and Nedd4 . Indeed, blocking CTLA-4 or neutralizing TGF- (cid:4) restored the ability to mount Th1/Th2 responses to live parasites and reversed the induction
The Effect of Emotion Induction on Situation Awareness and Driving Performance

This study investigates the effects of pre-induced emotions on situation awareness (SA) and driving performance. Twelve male students (mean age of 23.9 ±1.8 years old) with a valid driving license participated and attended two driving simulation sessions on separate days. Participants drove a driving scenario for each session after being presented with a series of pictures to induce positive or negative emotion. Participants’ SA was measured by quantitative analysis of situation awareness (QASA). Driving performance was determined in terms of the collisions’ number. The result showed that emotion induction significantly affected driving performance (p =0.005). The collisions’ number was higher after the induction of negative emotion than after positive emotion induction. Participants’ SA level 1 was also affected by the emotion inductions ( p = 0.042), where the SA level 1 after the induction of negative emotion was higher than that after the positive emotion induction. These results indicate that SA partially mediates the effect of emotion on driving performance. Our findings demonstrate the emotion induction effects on situation awareness and driving performance. The results of this study imply that an emotional state before driving is essential for transportation safety.