Miracle-dz/UniFAR-FTUs huggingface dataset:
The Prevalence of Attention Deficient Hyperactivity Disorder Among Iranian Children: A Meta-Analysis

Context: Attention deficient hyperactivity disorder (ADHD), diagnosed in psychiatric outpatient clinics, is the most common psychiatric disorder among schoolchildren. The purpose of this study is to conduct a meta-analysis on subscales related to ADHD examined on schoolchildren. Moreover, it is tried to evaluate meta-analysis of ADHD and its subscales in primary school students in Iran. Evidence Acquisition: Searching through the databases of Magiran, SID, Google Scholar, etc. a total of 16 articles were collected and weighted based on the number of cases and prevalence in binomial distribution. By using a random effects model meta-analysis (I2 = 96.5%), data were analyzed by the use of R and STATA software (version 11.2). Results: In this analysis, 27 articles published between the years of 2001 and 2016 were used. The total sample size was 15124 students whose ages ranged from six to 14 years old. The prevalence of ADHD based on parents and teachers’ consensus was 12% (CI 95%: 9.0 - 15), from parents’ perspective 15.6% (CI 95%: 9.8 - 21.5), and from teachers’ perspective 17.2% (CI 95%: 12.7 - 21.8). The subgroups’ prevalence rates based on parents and teachers’ consensus were as follows: Attention deficit (AD) = 4.2%, hyperactive impulsive (HI) = 4.1%, and combined type (CT) = 3.5%. ADHD was more prevalent in boys than girls (7.9% versus 5.5%). Conclusions: The results indicated that the prevalence of ADHD among schoolchildren is moderate; therefore, considering the importance of students’ mental health, the needs for identification, prevention, and treatment of high-risk groups by responsible institutions become obvious.
A new frame for frame-of-reference training: enhancing the construct validity of assessment centers.

The authors undertook a comprehensive examination of the construct validity of an assessment center in this study by (a) gathering many different types of evidence to evaluate the strength of the inference between predictor measures and constructs (e.g., reliability, accuracy, convergent and discriminant relationships), (b) introducing a theoretically relevant intervention (frame-of-reference [FOR] training) aimed at improving construct validity, and (c) examining the effect of this intervention on criterion-related validity (something heretofore unexamined in the assessment center literature). Results from 58 assessees and 122 assessors suggested that FOR training was effective at improving the reliability, accuracy, convergent and discriminant validity, and criterion-related validity of assessment center ratings. Findings are discussed in terms of implications and future directions for both FOR training and assessment center practice.
A Study on Differences Between Taiwanese Mandarin and Mainland Mandarin in Vocabulary

There are many differences in pronunciation and vocabulary between Taiwanese mandarin and mainland mandarin, which are mainly due to the differences between the two sides in geography, history, politics, social culture and language environment. Coupled with lack of information communication during more than 40 years of cross-strait isolation, the differences in vocabulary, the most active factor reflecting social changes in language, is more prominent. Through investigation, it is found that the differences between Taiwanese mandarin and mainland mandarin in vocabulary are mainly as follows: different names for the same thing or phenomenon; same name for different things or phenomena; unique to one party, but the other party has no such thing or no corresponding fixed statement. In addition to the differences in meaning, there are some differences in the pronunciation of words in the same form on both sides of the strait. The main reasons for the differences in vocabulary include the influence of Japanese and hokkien, the different perspectives on things between Taiwan and the mainland and the different translations of foreign words. Keywords—Taiwanese mandarin; mainland mandarin; vocabulary; differences; reasons
Learning Discriminative Representations for Semantic Cross Media Retrieval

Heterogeneous gap among different modalities emerges as one of the critical issues in modern AI problems. Unlike traditional uni-modal cases, where raw features are extracted and directly measured, the heterogeneous nature of cross modal tasks requires the intrinsic semantic representation to be compared in a unified framework. This paper studies the learning of different representations that can be retrieved across different modality contents. A novel approach for mining cross-modal representations is proposed by incorporating explicit linear semantic projecting in Hilbert space. The insight is that the discriminative structures of different modality data can be linearly represented in appropriate high dimension Hilbert spaces, where linear operations can be used to approximate nonlinear decisions in the original spaces. As a result, an efficient linear semantic down mapping is jointly learned for multimodal data, leading to a common space where they can be compared. The mechanism of "feature up-lifting and down-projecting" works seamlessly as a whole, which accomplishes crossmodal retrieval tasks very well. The proposed method, named as shared discriminative semantic representation learning (\textbf{SDSRL}), is tested on two public multimodal dataset for both within- and inter- modal retrieval. The experiments demonstrate that it outperforms several state-of-the-art methods in most scenarios.
Beyond Leveraged Losses: The Balance Sheet Effects of the Home Price Downturn

This paper quantifies the impact of declining home prices, increasing mortgage credit losses, and the associated reduction in credit supply on real GDP growth. Using a state-level panel analysis, I first estimate the link between home prices and foreclosures. I estimate that an additional 15 percent home price decline from mid-2008 levels would be consistent with total residential mortgage credit losses over 2007–12 of $750 billion, although the uncertainty is high. I then gauge the impact of such losses on the supply of credit from banks, asset-backed security markets, and the government-sponsored enterprises, and in turn on real GDP growth. In the central scenario, the crisis could lower real GDP growth in 2008 and 2009 by an average of 2.6 percentage points per year. This estimate excludes both adverse multiplier effects (labor market deterioration, global trade repercussions, and credit quality feedback) and policy offsets.
Ultra-dynamic voltage scaling using sub-threshold operation and local voltage dithering in 90nm CMOS

Local voltage dithering combined with sub-threshold operation permits ultra-dynamic voltage scaling from 1.1 V to below 300 mV for a 90 nm CMOS adder test chip. Operating at 330 mV, it provides minimum energy per cycle with 9-times less energy than ideal shutdown for reduced-rate scenarios. Measurements characterize the minimum energy point across temperature.
Vibration Control of Flexible Base Mobile Manipulators under Impedance Controller Using New Control Element on the End Effector

Abstract — In this paper new method for vibration control of Flexible Base Mobile Manipulator (FBMM) under constrained motion control were proposed. When robotic manipulator with base flexibility contacts environment under impedance control, vibration occurs at transient and contact moments. Vibration causes position and force inaccuracy, instability and servicing requirements of equipment. Previous active vibration control is based on vibration control elements on the base of manipulator. As new method, control element on the manipulator’s End Effector was proposed for vibration control and vibration damping on the mechanism. This controller includes same or better response and lower control coefficients because of its performance on the End Effector instead of the base. Active Vibration Controller on the End Effector (AVEE) was simulated for two models. First model is a simple FBMM composed of a 2 DOFs planar manipulator and a single DOF moving base with flexibility in between. Second model is an advanced 10 DOF’s FBMM. Combined Impedance/AVEE controller provides desired position/force control with satisfactory damped vibration especially at the point of contact. Results show that control coefficients of active vibration controller on the Base (AVCB) are so bigger than these coefficients for AVEE.
Wireless electronic tourist guide system based on microcontroller

This article describes an intelligent electronic tourist guide system which is composed of microcontroller AT89S52, radio frequency chips nRF24L01 and audio decoder chip ATJ2051. The hardware and software used in the system were characterized. A proto-type has been built to overcome many of the limitations of the traditional information and navigation tools available to visitors. The system has shown a good performance in anti-interference, especially in handy operation and playing stability. In this article we present an evaluation of the proto-type, focusing on the quality and flexibility of the visitor's experience when using the system.
KEEPING YOUR SANITY WHILE KEEPING YOUR STUDENTS: HOW TEACHER ENGAGEMENT CAN INCREASE STUDENT PERSISTENCE WHEN TEACHING STUDENTS DURING THEIR FIRST COLLEGE COURSE

Student persistence is a common concern for online educators. Previous research has shown that student persistence rates are effected by instructor presence, creating a sense of community in the classroom, and varying classroom activities for students (Croxton, 014). Based on the authors’ experiences, there Using Web 2.0 tools (Zoom, Loom, Remind, and Flipgrid), increasing discussion board posts containing personal experiences, and using effective time management tools can allow instructors to increase student persistence rates. This article provides a brief literature review regarding student persistence and an explanation of the authors’ experiences for increasing student persistence, as well as suggestions for further research in the area of student persistence and instructor strategies. self-awareness, self-esteem, effective communication, decision-making acumen, and the ability to promote
Moving the Needle on Evaluating Multivariate Screening Accuracy

The assessment of screening accuracy and setting of cut points for a universal screener have traditionally been evaluated using logistic regression analysis. This analytic technique has been frequently used to evaluate the trade-offs in correct classification with misidentification of individuals who are at risk of performing poorly on a later outcome. Although useful statistically, coefficients from a multiple logistic regression can be difficult to explain to practitioners as it pertains to classification decisions. Moreover, classifications based on multivariate assessments are challenging to understand how performance on one assessment compensates for performance on another. The purpose of this article is to demonstrate and compare the use of logistic regression with classification and regression tree (CART) models in the identification of students who are at risk of reading comprehension difficulties. Data consisted of 986 Grade 1 students and 887 Grade 2 students who were administered a screening assessment at the middle of the school year as well as the 10th edition of the Stanford Achievement Test. Results indicated that CART performs comparably with logistic regression and may assist researchers and practitioners in explaining classification rules to parents and educators.
An Automated Retesting Approach for Wafer Probing Test Systems Using Neural Networks

—As the semiconductor industry market becomes more competitive, it is essential for raising semiconductor wafer yields to reduce product costs. For saving yields, many engineers have improved the many steps of wafer fabrication processes. However, stabilization in the fabrication steps is hard because there are many variations to control. We focus on the wafer probing test process to find factors of raising yields because it is not more complicate than the fabrication process to save wafer yield. Furthermore, it is more effective than the fabrication process in the aspect of the cost. There are two kinds of failures in the wafer probing test step. One is originated from the bad quality of wafers and the other is originated from the unstable probing equipments irrelevant to the quality of wafers. Thus, it is very important to remove the second types of failure. In order to remove this type of failure, if wafers are tested as failure at the wafer probing test step, experts inspect those to determine the type of failure. If it is determined originated from the unstable equipments, the wafer will be tested once more. Since all fail wafers are inspected by human experts, the decision of retest is very time-consuming and the reliability is also very low. In this paper, an automated wafer retesting system is proposed for raising yields in the wafer probing test. We develop an artificial neural network model to distinguish the types of wafer failures. We use the EBP (Error Back Propagation) algorithm for training the neural network. We obtain a meaningful accuracy of the failure type discrimination. The proposed system has been adopted into the mass production fields and the total wafer yields was improved by about 0.1% and the total wafer testing time was reduced by about 80%.
Treadmill exercise enhances spatial learning ability through suppressing hippocampal apoptosis in Huntington’s disease rats

Huntington’s disease is a chronic neurodegenerative disorder inherited in an autosomal dominant fashion, and characterized as involuntary movement. Quinolinic acid has been used to produce an animal model of Huntington’s disease. In the present study, the effect of treadmill exercise on spatial-learning ability and motor coordination focusing on the apoptosis in the hippocampus was investigated using quinolinic acid-induced Huntington’s disease rats. Huntington’s disease was induced by unilateral intrastriatal injection of quinolinic acid (2 μL of 100 nmol) using stereotaxic instrument. The rats in the treadmill exercise groups were subjected to run on a treadmill for 30 min once a day during 14 days. Spatial learning ability and motor coordination were determined by radial 8-arm maze test and rota-rod test. Immunohistochemistry for caspase-3 and western blot for Bax and Bcl-2 were also conducted for the detection of apoptosis. In the present results, spatial learning ability and motor coordination were deteriorated by intrastriatal injection of quinolinic acid. In contrast, treadmill exercise exerted ameliorating effect on quinolinic acid-induced deterioration of spatial learning ability and motor coordination. Bcl-2 expression in the hippocampus was de-creased and expressions of casepase-3 and Bax in the hippocampus were increased in the quinolinic acid-induced Huntington’s disease rats. Treadmill exercise increased Bcl-2 expression and decreased expressions of casepase-3 and Bax in the Huntington’s disease rats. The present results showed that treadmill exercise might ameliorate quinolinic acid-induced loss of spatial learning ability and motor coordination by suppressing apoptosis in the hippocampus.
Computer Music Meets Unconventional Computing: Towards Sound Synthesis with In Vitro Neuronal Networks

The feasibility of synthesizing sounds with hybrid wetware-silicon devices has been explored with the use of in vitro neuronal networks. The basics of culturing brain cells has been introduced while the procedures that has been established to stimulate the in vitro neuronal networks has been presented. Then, the technique on sonifying the behavior of neuronal networks which has been developed was described while the initial results of developing the techniques to steer the behavior of the networks have been reported. The main goal of this paper is to have some form of controllability and repeatability in the system. This sound-synthesis technique has an important property in that it has the ability to produce different types of sounds with a certain degree of predictable control.
A COMPARISON OF TWO PARADIGMS FOR DISTRIBUTED COMPUTING

This paper argues that a distributed system should support two communication paradigms: Remote Procedure Call (RPC) and group communication. The former captures point-to-point communication; the latter captures one-to-many communication. We demonstrate that group communication is an important paradigm by showing that a fault-tolerant directory service is much easier to implement with groups than with RPC and is also more efficient. The directory service exemplifies distributed services that provide high reliability and availability by replicating data.
Double diabetes in Saudi Arabia: A new entity or an underestimated condition

AIM To determine the clinical and biological characteristics of double diabetes (DD) among young people in Saudi Arabia. METHODS This was a retrospective descriptive chart review study including 312 young newly diagnosed diabetic patients (aged 12-20 years), whom were admitted over a five year period (January 2009 to December 2013). Family history of diabetes mellitus (DM) (first degree), physical body mass index (BMI), acanthosis nigricans, history of auto-immune disease and laboratory information for glycosylated hemoglobin, basal C peptide level and diabetes autoantibody response (anti-GAD, anti-IA2 and anti-ICA) were collected from medical report. A mean follow-up of 3 years for these patients was performed. RESULTS Patients were categorized into 4 groups, based on the autoantibody response (Ab+ or Ab-) and C-peptide secretion (β+ for fasting level 0.4-2.1 ng/mL and β- if < 0.4 ng/mL). Group1 (type 1a): Ab+ β- (21%), group 2 (type 1b): Ab- β- (9%), group 3 (DD): Ab+ β+ (31%) and group 4 (classic type 2 DM): Ab- β+ (39%). The mean age of the DD patients in our study was 15.1 ± 6.4 years. A total of 41% of the study population presented with diabetic ketoacidosis and 61% of the study population presented with positive family history of DM. The mean BMI was 26.8 kg/m2 with 64% of overweight or obese patients. Ninety two percent of the patients were started on insulin at the time of diagnosis. During a mean follow-up of 3 years, only 32% of the patients with DD required insulin and 78% were on metformin alone or with insulin. CONCLUSION Our findings enable us to arrive at the conclusion that almost one-third of the young Saudi diabetic patients reveal atypical forms of DM (double diabetes) expressing features resulting from both T1D and T2D.
A novel high step-up DC-DC multilevel buck-boost converter using voltage-lift switched-inductor cell

This paper presents a novel high step-up DC-DC multilevel buck-boost converter using voltage-lift switched-inductor (VLSI) cell. To achieve high conversion ratio cascading of conventional DC-DC converter is not a practical solution. Thus high step-up multilevel buck-boost converters are employed to achieve high conversion ratio. The proposed high step-up DC-DC multilevel buck-boost converter is a non-isolated topology which combines the function of voltage-lift switched-inductors (VLSI) cell and voltage multiplier. In this paper voltage-lift switched-inductor (VLSI) cell is used to advance the boost capability of multilevel buck-boost converter. 2N+3 diodes, 2N capacitors, two inductors and single switch are needed to design proposed N-level buck-boost topology. Proposed DC-DC multilevel buck-boost topology can be synthesized by using low voltage rating devices because voltage stress across each power devices is less. The main advantage of proposed DC-DC multilevel topology is high conversion ratio is achieved without using coupled inductor, transformer and extreme duty cycle. The voltage gain of proposed buck-boost multilevel converter is depends upon the duty cycle and number of levels. The proposed buck-boost multilevel converter has been designed for three levels with rated power 200W and output voltage is 220V Input supply voltage is 12V, duty cycle is 70% and switching frequency is 50KHz. The proposed buck-boost multilevel converter topology is simulated in MATLAB/SIMULINK.
SMART TOOLS FOR VIRTUAL REALITY BASED CAD

Usability in virtual reality based design tools (VRAD) is a major issue since its interaction techniques are not yet fully investigated. Human factors such as pointing precision, fatigue, hand vibrations, lack of limb support, and interaction anisotropy should be taken into account for a more effective interface as compared to the 2D. This work presents an ongoing study addressing human performances in VR during common CAD tasks: picking, pointing, and line drawing. Tests confirm performances reduction along the user’s head to hand direction, mainly due to occlusion and lack of appropriate feedback. Three virtual tools are here presented in order to overcome the interaction anisotropy: the “Ortho Tool”, the “Smart Transparency”, and the “Smart Object Snap”. The new interface has shown better user performances and improved model understanding. Results achieved in this work contribute not only toVRAD development, but also to other virtual reality applications, because their context can be easily extended.
Semantic clustering for adaptive language modeling

In this paper we present efficient clustering algorithms for two novel class-based approaches to adaptive language modeling. In contrast to bigram and trigram class models, the proposed classes are related to the distribution and co-occurrence of words within complete text units and are thus mostly of a semantic nature. We introduce adaptation techniques such as the adaptive linear interpolation and an approximation to the minimum discriminant estimation and show how to use the automatically derived semantic structure in order to allow a fast adaptation to some special topic or style. In experiments performed on the Wall-Street-Journal corpus, intuitively convincing semantic classes were obtained. The resulting adaptive language models were significantly better than a standard cache model. Compared to a static model a reduction in perplexity of up to 31% could be achieved.
AN ARCHITECTURE FOR A GENERALIZED SPACECRAFT TRAJECTORY DESIGN AND OPTIMIZATION SYSTEM

The elements of a general high precision system for trajectory design and optimization for single or multiple spacecraft using one or more distinct propulsion systems, and operating in any gravitational environment within the solar system are discussed. The system architecture attempts to consolidate most all spacecraft trajectory design and optimization problems by using a single framework that requires solutions to either a system of nonlinear equations or a parameter optimization problem with general equality and/or inequality constraints. The use of multiple reference frames that generally translate, rotate, and pulsate between two arbitrary celestial bodies facilitates the analysis of multiple celestial body force field trajectories such as those associated with libration point missions, cycling trajectories between any set of celestial bodies, or any other type of trajectory or mission requiring the use of multiple celestial bodies. A basic trajectory building block, referred to as the basic segment, that can accommodate impulsive maneuvers, maneuver and non-maneuver based mass discontinuities, and finite burn or finite control acceleration maneuvers, is used to construct single or multiple spacecraft trajectories. The system architecture facilitates the modeling and optimization of a large range of problems ranging from single spacecraft trajectory design around a single celestial body to complex missions using multiple spacecraft, multiple propulsion systems, and operating in multiple celestial body force fields.