Miracle-dz/UniFAR-FTUs huggingface dataset:
Child Under-weight and Agricultural Productivity in India

A recent global hunger index indicated a 12 percent decline in child underweight rates. This study attempts an empirical explanation of the factors that influence child underweight rates at the district level. Agricultural land productivity, share of women educated above the secondary level and participating in work, maternal, and child health seem to contribute to the reduction in child underweight. However government health and water supply facilities turn out to be ineffective.
Performance Evaluation of TDMR R/W Channel With Head Skew by LDPC Coding and Iterative Decoding System

2-D magnetic recording (TDMR) exploits 2-D signal processing using the waveforms reproduced by array head from the intended and adjacent tracks to mitigate the effects of intertrack interference. However, an array head has the issue on the degradation of bit error rate (BER) performance due to head skew. In this paper, we evaluate the BER performance of TDMR R/W channel with head skew under a specification of 4 Tbit/in2 employing low-density parity check coding and iterative decoding system using a 2-D finite-impulse response filter by computer simulation. The results show that our system can achieve the reliable BER performances by appropriately setting the reader scanning positions at the head skew angle between 0° and 3°.
Mirror Hand Deformity: A Report of Two Cases.

Mirror hand (ulnar dimelia) is an extremely rare congenital deformity in the upper extremity; only approximately seventy cases have been reported in the literature1,2 since the anomaly was first described in 1587 by Rueff3. The typical deformity consists of an absent radius, a duplication of the ulna, and polydactyly4,5. The elbow is generally stiff in extension, and the wrist is hyperflexed. The shoulder can be affected with instability and underdeveloped musculature1,6. The main functional problems that need to be resolved are the stiff elbow and the polydactylous hand. A resection of the olecranon process of one of the ulnae (usually the lateral “radial” one) is advised in order for the elbow7 to have improved flexion and pronation and supination. Early arthrolysis of the elbow joint has also been described8. For pollicization, the most normal finger is chosen to create a thumb9, and extensor tendons from the removed digits can be transferred to strengthen the new thumb7. We describe two patients who presented with mirror hand deformity. The patients and their parents were informed that data concerning their cases would be submitted for publication, and they provided consent. Case 1. A two-month-old girl presented with unilateral abnormalities to the left upper extremity (Fig. 1-A). There had been no perinatal medical problems, and the family history was negative for congenital anomalies. There was good movement in the shoulder. The elbow was extended with no sign of active flexion. The wrist was hyperflexed and could be passively extended to 0°. The hand had seven triphalangeal fingers. The most radial finger (number 1) did not show any sign of movement and was unstable. The other six fingers were active, but finger number 3 …
Solving Inverse Scattering Problems Using Truncated Cosine Fourier Series Expansion Method 455 Solving Inverse Scattering Problems Using Truncated Cosine Fourier Series Expansion Method

The aim of inverse scattering problems is to extract the unknown parameters of a medium from measured back scattered fields of an incident wave illuminating the target. The unknowns to be extracted could be any parameter affecting the propagation of waves in the medium. Inverse scattering has found vast applications in different branches of science such as medical tomography, non-destructive testing, object detection, geophysics, and optics (Semnani & Kamyab, 2008; Cakoni & Colton, 2004). From a mathematical point of view, inverse problems are intrinsically ill-posed and nonlinear (Colton & Paivarinta, 1992; Isakov, 1993). Generally speaking, the ill-posedness is due to the limited amount of information that can be collected. In fact, the amount of independent data achievable from the measurements of the scattered fields in some observation points is essentially limited. Hence, only a finite number of parameters can be accurately retrieved. Other reasons such as noisy data, unreachable observation data, and inexact measurement methods increase the ill-posedness of such problems. To stabilize the inverse problems against ill-posedness, usually various kinds of regularizations are used which are based on a priori information about desired parameters. (Tikhonov & Arsenin, 1977; Caorsi, et al., 1995). On the other hand, due to the multiple scattering phenomena, the inverse-scattering problem is nonlinear in nature. Therefore, when multiple scattering effects are not negligible, the use of nonlinear methodologies is mandatory. Recently, inverse scattering problems are usually considered in global optimization-based procedures (Semnani & Kamyab, 2009; Rekanos, 2008). The unknown parameters of each cell of the medium grid would be directly considered as the optimization parameters and several types of regularizations are used to overcome the ill-posedness. All of these regularization terms commonly use a priori information to confine the range of mathematically possible solutions to a physically acceptable one. We will refer to this strategy as the direct method in this chapter. Unfortunately, the conventional optimization-based methods suffer from two main drawbacks. The first is the huge number of the unknowns especially in 2-D and 3-D cases 22
EFFECT OF BOARD COMPOSITION ON FIRM'S PERFORMANCE: A CASE OF PAKISTANI LISTED COMPANIES

This research attempted to assess the effect of board composition on firm’s performance, specifically a case of pakistani listed companies. A sample of 91 listed companies at karachi stock exchange kse-100 index was randomly selected. Group statistics and independent sample t-test were used as most appropriate measures of the categorical variable board composition. Results supported all three hypotheses by showing that the listed companies of pakistan at karachi stock exchange, which have independent board members in their board, were showing greater return on assets (roa), return on equity (roe) and tobin’s q. As these were the measures or components of firm’s performance, so it means that the listed companies of pakistan at karachi stock exchange with independent board were showing greater firm’s performance. Based on results and analysis it is concluded that companies heaving independent directors in their board composition will show greater firm performance.
An Effective and Efficient Truth Discovery Framework over Data Streams

Truth discovery, a validity assessment method for conflicting data from various sources, has been widely studied in the conventional database community. However, while existing methods for static scenario involve time-consuming iterative processes, those for streams suffer from much sacrifice on accuracy due to the incremental source weight learning. In this paper, we propose a novel framework to conduct truth discovery over streams, which incorporates various iterative methods to effectively estimate the source weights, and decides the frequency of source weight computation adaptively. Specifically, we first capture the characteristics of source weight evolution, based on which a framework is modelled. Then, we define the conditions of source weight evolution for the situations with relatively small unit and cumulative errors, and construct a probabilistic model that estimates the probability of meeting these conditions. Finally, we propose a novel scheme called adaptive source reliability assessment (ASRA), which converts an estimation problem into an optimization problem. We have conducted extensive experiments over real datasets to prove the high effectiveness and efficiency of our framework.
Developing a Bayesian Network Model for Supply Chain Risk Assessment

Abstract The Bayesian network based probability model is very new to the field of business management. Its use for risk assessment to predict the supply chain disruption and their consequences on the supply chain goals is very limited. The purpose of this research, is to develop a risk assessment tool to assess and to determine the risk exposure faced by a supply chain. In a global economy with ever-growing competition the firms are facing uncertain disruptions in their supply chains that further dent their brand value. The proposed probabilistic model that updates itself in the light of new evidences and calculates marginal probabilities for all risk variables and supply chain goals through conditional probability tables. The proposed model empowers the supply chain managers to predict the chances of any disruptive risk factors in the supply chain.
Clinical Epidemiology and Its Relevance for Public Health in Developing Countries

The current medical approach must contemplate the application of clinical epidemiology in the health establishments, patients; in general, epidemiologic research with its analytical designs and clinical trials allow the progress in treatments and managements, as well as defining the quality of auxiliary exams ever more sophisticated by means of the test of tests design and its cost-benefit approach [1,2] On the other hand, the field epidemiology is applied through descriptive studies of the population’s health situation with their analytical ap‐ proaches to the Situational Health Analysis (SHA), the study of epidemic outbreaks and evaluation of the respective answer of the community interventions [3,4]. This way, it allows carrying out an integral management of the epidemiology, both communal and individual, which will finally result in preventive medicine and public health
PREDICTION OF BREEDING VALUES AND SELECTION FOR EGG MASS IN A CLOSED FLOCK OF WHITE LEGHORN

A closed flock of White Leghorn was subjected to one cycle of selection for part year egg mass (at 120 d., of production). Best linear unbiased prediction selection method was used for predicting and ranking the breeding values and ranking then selecting hens for egg mass and some correlated traits. The correlated traits measured included egg number and egg weight at 90 and 120 d. , of production. The selection differential was 11 eggs, 2.0 g. , and 598 g. , for egg number, egg weight and egg mass at 90 d. , of production, respectively. These values equal to 0.9, 0.49 and 0.93 in stander units. The corresponding values at 120 d. , of production were 16 eggs, 1.6 g. , and 829 g. , equal to 0.89, 0.52 and 0.87 in stander units for the same traits. The realized genetic gain exceeded the expected genetic gain for egg mass at 90 d. , of production 202 vs.83. 7g. , and 354 vs.165. 8 g. , for egg mass at 120 d. , egg production. The realized genetic gains for different correlated traits were in the same direction. It was clear that a considerable increase in egg mass was achieved as a direct response. Consequently, provides an effective methodology of ranking and selecting hens given measurements on several traits including egg mass.
Identifying Conflicts through eMails by using an Emotion Ontology

In the logic of text classification, this paper presents an approach to detect emails conflict exchanged between colleagues, who belong to a geographically distributed enterprise. The idea is to inform a team leader of such situation, hence to help him in preventing serious disagreement between team members. This approach uses the vector space model with TF*IDF weight to represent email; and a domain ontology of relational conflicts to determine its categories. Our study also addresses the issue of building ontology, which is made up of two phases. First we conceptualize the domain by hand, then we enrich it by using the triggers model that enables to find out terms in corpora which correspond to different conflicts.
Impact of Wireless Channel Model on 802.15.6 Standard Performance for Wireless Body Sensor Networks

Wireless Body Sensor Network (WBAN) is a set of wearable and implantable devices capable of measuring physiological parameters and monitoring patient with chronic disease where early diagnosis is highly demanded. Several models introduced the general characterization of WBAN devices path loss considering possible shadowing due to obstruction of the signal (by the human body or any other obstacles) as well as the different postures of the human body. This paper aims at reporting an overview of WBSNs technologies, particular applications, system architecture and channel modeling. Emphasis is given to the IEEE 802.15. 6 standard which enables the development of WBAN for medical and non- medical applications. The standard's performance within a time based variation and log-distance path loss is presented based on various simulations.
Aggregating Local Preferences To Guide Policy

How could well-being data, for example those based on survey measures, be used for guiding policy? Exploring one direction, we analyze a mechanism that takes as inputs estimates of policy effects on different groups’ utility proxies (constructed from the well-being data), and aggregates them into policy-change recommendations. We develop three justifications for the mechanism based on: an analogy with social welfare maximization, a formal equivalence to a voting procedure, and an axiomatic characterization. We show that iterated application of the mechanism has a stationary point that is Pareto efficient. Through analytic results and simulations, we assess potential limitations of the mechanism, such as its sensitivity to the units in which policies are measured. JEL Classification: D69, H0, I38
Optimization of the Fano Resonance Lineshape Based on Graphene Plasmonic Hexamer in Mid-Infrared Frequencies

In this article, the lineshape of Fano-like resonance of graphene plasmonic oligomers is investigated as a function of the parameters of the nanostructures, such as disk size, chemical potential and electron momentum relaxation time in mid-infrared frequencies. Also, the mechanism of the optimization is discussed. Furthermore, the environmental index sensing effect of the proposed structure is revealed, and a figure of merit of 25.58 is achieved with the optimized graphene oligomer. The proposed nanostructure could find applications in the fields of chemical or biochemical sensing.
Italian Norms for the Stanford Hypnotic Susceptibility Scale, Form C1

Abstract This paper presents norms for an Italian translation of the Stanford Hypnotic Susceptibility Scale, Form C (SHSS:C; Weitzenhoffer & Hilgard, 1962). Archival data on hypnosis research subjects recruited over a 10-year period of research on hypnosis were pooled, resulting in an aggregate sample of 356 participants (263 female and 93 male). Score distribution, item difficulty levels, and reliability of the SHSS:C were computed. Of this group, 218 subjects were administered the Harvard Group Scale of Hypnotic Susceptibility approximately 3 weeks prior to administration of the SHSS:C. The remaining 138 subjects received only the SHSS:C. Results suggest that the Italian version of the SHSS:C is a reliable and valid measure.
Mutual Fund Performance and Private Information

This paper examines the use of private information by mutual funds with unconditional and conditional performance models. Using daily data for 35 countries over the 1990-2015 period, we find evidence that the use of conditioning information provides a more accurate estimation of fund performance. The use of conditioning information in mutual fund performance measurement is both statistically and economically significant. We show that unconditional alphas and betas are slightly smaller than the average conditional estimates. However, we do not find a robust evidence of private information in mutual fund performance.
Platelet gel and fibrin sealant reduce allogeneic blood transfusions in total knee arthroplasty

Background: Total knee arthroplasty (TKA) is often associated with a considerable amount of post‐operative blood loss, necessitating the transfusion of allogeneic blood, which can add to the complications. Optimization of strategies to reduce the need for blood transfusion is desired. This study was designed to evaluate the efficacy of autologous platelet gel and fibrin sealant in unilateral TKA.
A peak power optimization scheduling algorithm for multi-cycle operation

This paper proposes a force-directed scheduling algorithm for peak power optimization based on multi-cycle operations. Utilizing the basic idea of traditional force-directed scheduling algorithm and resetting the parameters related to force, this new algorithm has realized the balanced distribution of cycle power in scheduling process, thus minimizing peak power. Experimental results show that with the same control step constraint and resource consumption, the algorithm proposed in this paper has been improved in the aspect of peak power optimization compared with traditional force-directed scheduling algorithms, and bears comparison with the integer linear programming method.
Nonconscious Emotional Activation Colors First Impressions

Emotions can color people’s attitudes toward unrelated objects in the environment. Existing evidence suggests that such emotional coloring is particularly strong when emotion-triggering information escapes conscious awareness. But is emotional reactivity stronger after nonconscious emotional provocation than after conscious emotional provocation, or does conscious processing specifically change the association between emotional reactivity and evaluations of unrelated objects? In this study, we independently indexed emotional reactivity and coloring as a function of emotional-stimulus awareness to disentangle these accounts. Specifically, we recorded skin-conductance responses to spiders and fearful faces, along with subsequent preferences for novel neutral faces during visually aware and unaware states. Fearful faces increased skin-conductance responses comparably in both stimulus-aware and stimulus-unaware conditions. Yet only when visual awareness was precluded did skin-conductance responses to fearful faces predict decreased likability of neutral faces. These findings suggest a regulatory role for conscious awareness in breaking otherwise automatic associations between physiological reactivity and evaluative emotional responses.
Contrastive Analysis of Lexical Choice and Ideologies in News Reporting the Same Accidents between Chinese and American Newspapers

This article probes into the lexical choice of six pieces of news reporting three safety accidents in China in China Daily and The Washing Post . By analyzing the difference of the word choice and verbal messages, the article aims to reveal the hidden ideologies in the news discourse covertly implied and unbeknownst to the readers. Guided by assumptions of critical discourse analysis and drawing on the framework of lexical classification in Halliday’s (1994) systemic-functional grammar, the study finds that the seemingly impersonal, objective news reports are not neutral at all; rather, they encode ideologies to exert influence on readers’ view towards the world. The article demonstrates how the two newspapers represented the same event in vastly different ways through the particular uses of lexicon that reflected their differing ideological standpoints and national interests.
The Perception and Use of Electronic Banking among Business Executives in Lagos State, Nigeria

The study focused on perception and use of e-banking services among business executives in Ikeja Local Government Area, Lagos, Nigeria. The study aimed at finding out what influence the use of e-banking services by business executives. The study made use of cross-sectional survey design. The study area was stratified into communities and organizations sampled randomly as possible for the study. A questionnaire was used to collect data from one hundred and fifty one business executives’ selected using accidental sampling method. Statistical methods used for the analyses were frequencies for descriptive statistics, while regression analysis was used to test the hypotheses. Findings revealed that ATM is the most used e-banking service while International Card Scheme is the least used. Gender and level of education are the two demographic variables that influenced business executives the most in their use of e-banking services. There are generally both positive and negative reviews about service quality and security/privacy of the e-banking services. The study revealed that business executives believe that the e-banking services were easy to use, useful and convenient. The study recommended that security/privacy and service quality of e-banking services/platforms should be improved and that effort should be directed to improving users’ confidence in the use of the platform.
A vendor-buyer integrated model under production uncertainty

Abstract This paper examines the benefits of supply chain integration for a single-vendor, single-buyer system in which production runs of the vendor are subject to random interruptions and demand at the buyer is continuous, of fixed, known rate. Both the vendor and the buyer consider the fixed setup cost, the variable ordering cost, and the inventory holding cost. The system can be operated under the vendor-led, buyer-led, or integrated mode with the order quantity set to be optimal for any of the modes. In all modes, the vendor schedules production runs to provide the buyer a new batch, possibly a partial batch cut short by a random interruption, right when the buyer runs out of inventory. Supported by theories, the paper conducts sensitivity analysis on the optimal order quantities with respect to system parameters. The numerical experiments also provide insights for the optimal order quantities not covered by the theoretical results.
Generalized serial schedules for iterative decoding of LDPC codes

Efficient serial decoding schedules for LDPC codes are described. The schedules are based on dividing the Tanner graph to sub-graphs. This yields an improvement in complexity and performance over the standard schedules. An application of the introduced schedules to decoding codes based on lifted graphs is described. An analysis based on density evolution is presented and is used to predict the behavior of different schedules.
Detecting Computer Generated Images with Deep Convolutional Neural Networks

Computer graphics techniques for image generation are living an era where, day after day, the quality of produced content is impressing even the more skeptical viewer. Although it is a great advance for industries like games and movies, it can become a real problem when the application of such techniques is applied for the production of fake images. In this paper we propose a new approach for computer generated images detection using a deep convolutional neural network model based on ResNet-50 and transfer learning concepts. Unlike the state-of-the-art approaches, the proposed method is able to classify images between computer generated or photo generated directly from the raw image data with no need for any pre-processing or hand-crafted feature extraction whatsoever. Experiments on a public dataset comprising 9700 images show an accuracy higher than 94%, which is comparable to the literature reported results, without the drawback of laborious and manual step of specialized features extraction and selection.