Miracle-dz/UniFAR-FTUs huggingface dataset:
Abnormal spontaneous regional brain activity in primary insomnia: a resting-state functional magnetic resonance imaging study

Objective Investigating functional specialization is crucial for a complete understanding of the neural mechanisms of primary insomnia (PI). Resting-state functional magnetic resonance imaging (fMRI) is a useful tool to explore the functional specialization of PI. However, only a few studies have focused on the functional specialization of PI using resting-state fMRI and results of these studies were far from consistent. Thus, the current study aimed to investigate functional specialization of PI using resting-state fMRI with amplitude of low frequency fluctuations (ALFFs) algorithm. Methods In this study, 55 PI patients and 44 healthy controls were included. ALFF values were compared between the two groups using two-sample t-test. The relationship of abnormal ALFF values with clinical characteristics and duration of insomnia was investigated using Pearson’s correlation analysis. Results PI patients showed lower ALFF values in the left orbitofrontal cortex/inferior frontal gyrus, right middle frontal gyrus, left inferior parietal lobule, and bilateral cerebellum posterior lobes, while higher ALFF values in the right middle/inferior temporal that extended to the right occipital lobe. In addition, we found that the duration of PI negatively correlated with ALFF values in the left orbitofrontal cortex/inferior frontal gyrus, and the Pittsburgh Sleep Quality Index score negatively correlated with ALFF values in the left inferior parietal lobule. Conclusion The present study added information to limited studies on functional specialization and provided evidence for hyperarousal hypothesis in PI.
Design and simulation of 64 point FFT using Radix 4 algorithm for FPGA Implementation

The Fast Fourier Transform (FFT) is one of the rudimentary operations in field of digital signal, image processing and FFT processor is a critical block in all multi- carrier systems used primarily in the mobile environment. Fast Fourier transform (FFT) is an efficient implementation of the discrete Fourier transform (DFT). The portability requirement of these systems is mainly responsible for the need of low power FFT architectures. In this study, the development of 64 point FFT, based on Decimation-In- Time (DIT) domain using Radix-4 algorithm. The complex multiplier is one of the most power consuming blocks in the FFT processor. A significant property of the proposed method is that the critical path of the address generator is independent from the FFT transform length N, making it extremely efficient for large FFT transforms. The results confirm the speed and area advantages for large FFTs. Although only radix-4 FFT address generation is presented in the paper, it can be used for higher radix FFT.
Synchronization of fast (30-40 Hz) spontaneous cortical rhythms during brain activation

We investigated the synchronization of fast spontaneous oscillations (mainly 30–40 Hz) in anesthetized and behaving cats by means of simultaneous extra- and intracellular recordings from multiple neocortical areas. Fast Fourier transforms, auto- and cross- correlations, and spike- or wave-triggered averages were used to determine the frequency and temporal coherence of fast oscillations that outlasted the stimulation of ascending activating systems or that occurred naturally during behavioral states of waking and rapid eye movement (REM) sleep but also appeared during the depolarizing phases of slow sleep oscillations. In 90% of microelectrode tracks, the fast oscillations did not show field reversal at any depth of the cortex and were not observable in the underlying white matter. The negative field potentials of the fast oscillations were associated at all depths with neuronal firing. This field potential property of fast oscillations was in sharp contrast to the reversal of slow sleep oscillation or evoked potentials at depths of 0.25–0.5 mm. The coherence of fast spontaneous rhythms was spatially limited, being confined within a cortical column and among closely located neocortical sites, in contrast to the long- range synchronization of slow sleep rhythms. Depolarizing current pulses elicited spike-bursts (200–400 Hz) recurring at a frequency of 30–40 Hz. Our experiments demonstrate that the conventional notion of a totally desynchronized cortical activity upon arousal should be revised as fast rhythms are enhanced and synchronized within intracortical networks during brain activation. Spontaneously occurring, subthreshold membrane potential depolarizing oscillations may bias cortical and thalamic neurons to respond synchronously, at fast frequencies, to relevant stimuli in the wake state or to internally generated drives in REM sleep.
Using the Technology Acceptance Model in Understanding Academics' Behavioural Intention to Use Learning Management Systems

Although e-learning is in its infancy in Saudi Arabia, most of the public universities in the country show a great interest in the adoption of learning and teaching tools. Determining the significance of a particular tool and predicting the success of implantation is essential prior to its adoption. This paper presents and modifies the technology acceptance model (TAM) in an attempt to assist public universities, particularly in Saudi Arabia, in predicting the behavioural intention to use learning management systems (LMS). This study proposed a theoretical framework that includes the core constructs in TAM: namely, perceived ease of use, perceived usefulness, and attitude toward usage. Additional external variables were also adopted— namely, the lack of LMS availability, prior experience (LMS usage experience), and job relevance. The overall research model suggests that all mentioned variables either directly or indirectly affect the overall behavioural intention to use an LMS. Initial findings suggest the applicability of using TAM to measure the behavioural intention to use an LMS. Further, the results confirm the original TAM's findings.
Curiosity and reward: Valence predicts choice and information prediction errors enhance learning.

Curiosity drives many of our daily pursuits and interactions; yet, we know surprisingly little about how it works. Here, we harness an idea implied in many conceptualizations of curiosity: that information has value in and of itself. Reframing curiosity as the motivation to obtain reward-where the reward is information-allows one to leverage major advances in theoretical and computational mechanisms of reward-motivated learning. We provide new evidence supporting 2 predictions that emerge from this framework. First, we find an asymmetric effect of positive versus negative information, with positive information enhancing both curiosity and long-term memory for information. Second, we find that it is not the absolute value of information that drives learning but, rather, the gap between the reward expected and reward received, an "information prediction error. " These results support the idea that information functions as a reward, much like money or food, guiding choices and driving learning in systematic ways.
Long-Term Impacts of Individual Development Accounts on Homeownership Among Baseline Renters: Follow-Up Evidence from a Randomized Experiment

We examine the long-term effects of a 1998-2003 randomized experiment in Tulsa, Oklahoma with Individual Development Accounts that offered low-income households 2:1 matching funds for housing down payments. Prior work shows that, among households who rented in 1998, homeownership rates increased more through 2003 in the treatment group than for controls. We show that control group renters caught up rapidly with the treatment group after the experiment ended. As of 2009, the program had an economically small and statistically insignificant effect on homeownership rates, the number of years respondents owned homes, home equity, and foreclosure activity among baseline renters. (JEL D14, H75, R21, R31)
Predictors of repeated sick leave in the workplace because of mental disorders

Introduction Mental disorders create a considerable burden to society. Previous studies have shown that productivity loss constitutes the largest proportion of the total societal burden. For depression and anxiety disorders, in particular, more than half of the associated productivity loss occurs in the workplace. Many previous studies have clarified the risk factors for the relapse/recurrence of mental disorders in health care settings. However, the risk factors for repeated sick leave among mental disorders prevalent in the workplace have not yet been adequately evaluated. Objective The objective of this study was to investigate which variables could predict repeated sick leave for workers with a history of sick leave because of mental disorders. Methods Data regarding 194 subjects employed at a manufacturing company were obtained. Mental disorders were defined as disorders listed in the Diagnostic and Statistical Manual of Mental Disorders, fourth edition (DSM-IV). The duration between the return to work (RTW) and the repeated sick leave was regarded as a dependent variable. The subjects’ age at the RTW, sex, age at the time of employment, job tenure, diagnosis, number of previous sick leave days, duration of most recent sick leave, and employee rank were examined as explanatory variables. Univariate analyses using a log-rank test and a multivariate analysis using the Cox proportional hazard model were conducted. Results The results of the univariate analyses showed that the number of previous sick-leave episodes was a significant predictor of repeated sick leave. A multivariate analysis revealed that age at RTW and the number of previous sick-leave episodes were significant variables. Conclusion Age and the number of previous sick-leave episodes appeared to be predictors of repeated sick leave. Therefore, effective intervention to prevent repeated sick leave for those with high risk is quite crucial. Analyses including various work-related factors with subjects from multiple companies should be conducted in future studies.
A SURVIVAL THEORY OF INTERNET FIRM DURATION

More than 5000 Internet firms have failed since the beginning of 2000. One common perception is that the downturn in the economy drove many firms out of business. However, why are some firms still alive while others are not? In this research, we examine the impact of various industry, firm and e-commerce-related drivers on Internet firm survival from the multiple perspectives of accounting and finance, information systems (IS), economics and organizational theory research. We analyze a panel data set of 115 public Internet firms using three different techniques: logit, nonparametric survival analysis and the semiparametric Cox proportional hazards model. The use of these econometric methods permits us to answer key research questions and cross-validate results. We characterize the survival rates throughout the lifetimes of the public Internet firms in our sample. Our results reveal that selling digital goods or services, entry of additional Internet firms via IPOs in the stock market, a larger firm size and a lower leverage (in terms of total debt/total assets) reduced the likelihood of failure.
Increased CSF Levels of Phosphorylated Neurofilament Heavy Protein following Bout in Amateur Boxers

Introduction Diagnosis of mild TBI is hampered by the lack of imaging or biochemical measurements for identifying or quantifying mild TBI in a clinical setting. We have previously shown increased biomarker levels of protein reflecting axonal (neurofilament light protein and tau) and glial (GFAP and S-100B) damage in cerebrospinal fluid (CSF) after a boxing bout. The aims of this study were to find other biomarkers of mild TBI, which may help clinicians diagnose and monitor mild TBI, and to calculate the role of APOE ε4 allele genotype which has been associated with poor outcome after TBI. Materials and Methods Thirty amateur boxers with a minimum of 45 bouts and 25 non-boxing matched controls were included in a prospective cohort study. CSF and blood were collected at one occasion between 1 and 6 days after a bout, and after a rest period for at least 14 days (follow up). The controls were tested once. CSF levels of neurofilament heavy (pNFH), amyloid precursor proteins (sAPPα and sAPPβ), ApoE and ApoA1 were analyzed. In blood, plasma levels of Aβ42 and ApoE genotype were analyzed. Results CSF levels of pNFH were significantly increased between 1 and 6 days after boxing as compared with controls (p<0.001). The concentrations decreased at follow up but were still significantly increased compared to controls (p = 0.018). CSF pNFH concentrations correlated with NFL (r = 0.57 after bout and 0.64 at follow up, p<0.001). No significant change was found in the other biomarkers, as compared to controls. Boxers carrying the APOE ε4 allele had similar biomarker concentrations as non-carriers. Conclusions Subconcussive repetitive trauma in amateur boxing causes a mild TBI that may be diagnosed by CSF analysis of pNFH, even without unconsciousness or concussion symptoms. Possession of the APOE ε4 allele was not found to influence biomarker levels after acute TBI.
Depressive symptomatology differentiates subgroups of patients with seasonal affective disorder

Patients with seasonal affective disorder (SAD) may vary in symptoms of their depressed winter mood state, as we showed previously for nondepressed (manic, hypomanic, hyperthymic, euthymic) springtime states [Goel et al., 1999]. Identification of such differences during depression may be useful in predicting differences in treatment efficacy or analyzing the pathogenesis of the disorder. In a cross‐sectional analysis, we determined whether 165 patients with Bipolar Disorder (I, II) or Major Depressive Disorder (MDD), both with seasonal pattern, showed different symptom profiles while depressed. Assessment was by the Structured Interview Guide for the Hamilton Depression Rating Scale—Seasonal Affective Disorder Version (SIGH‐SAD), which includes a set of items for atypical symptoms. We identified subgroup differences in SAD based on categories specified for nonseasonal depression, using multivariate analysis of variance and discriminant analysis. Patients with Bipolar Disorder (I and II) were more depressed (had higher SIGH‐SAD scores) and showed more psychomotor agitation and social withdrawal than those with MDD. Bipolar I patients had more psychomotor retardation, late insomnia, and social withdrawal than bipolar II patients. Men showed more obsessions/compulsions and suicidality than women, while women showed more weight gain and early insomnia. Whites showed more guilt and fatigability than blacks, while blacks showed more hypochondriasis and social withdrawal. Darker‐eyed patients were significantly more depressed and fatigued than blue‐eyed patients. Single and divorced or separated patients showed more hypochondriasis and diurnal variation than married patients. Employed patients showed more atypical symptoms than unemployed patients, although most of the subgroup distinctions lay on the Hamilton Scale. These results comprise a set of biological and sociocultural factors—including race, gender, and marital and employment status—which contribute to depressive symptomatology in SAD. Significant mood and sociocultural factors, in contrast to biological factors of gender and eye color, were similar to those reported for nonseasonal depression. Lightly pigmented eyes, in particular, may serve to enhance photic input during winter and allay depressive symptoms in vulnerable populations. Depression and Anxiety 15:34–41, 2002. © 2002 Wiley‐Liss, Inc.
PCR and Microscopic Identification of Isolated Leishmania tropica from Clinical Samples of Cutaneous Leishmaniasis in Human Population of Kohat Region in Khyber Pakhtunkhwa

Leishmania tropica was isolated from the clinical patients of cutaneous leishmaniasis in rural community of Kohat district in Khyber Pakhtunkhwa province and was identified through PCR, microscopy, and culture techniques. A total of 113 samples from the clinical patients were examined through PCR, microscopy, and culture which showed 87.61% (99/113), 53.98% (61/113), and 46.90% (53/113) prevalence. During the study, 186 bp Leishmania tropica was identified through PCR. Thus the sensitivity of PCR is very high as compared to the conventional techniques.
Low Dose Aerosol Fitness at the Innate Phase of Murine Infection Better Predicts Virulence amongst Clinical Strains of Mycobacterium tuberculosis

Background Evaluation of a quick and easy model to determine the intrinsic ability of clinical strains to generate active TB has been set by assuming that this is linked to the fitness of Mycobacterium tuberculosis strain at the innate phase of the infection. Thus, the higher the bacillary load, the greater the possibility of inducting liquefaction, and thus active TB, once the adaptive response is set. Methodology/Principal Findings The virulence of seven clinical Mycobacterium tuberculosis strains isolated in Spain was tested by determining the bacillary concentration in the spleen and lung of mice at weeks 0, 1 and 2 after intravenous (IV) inoculation of 104 CFU, and by determining the growth in vitro until the stationary phase had been reached. Cord distribution automated analysis showed two clear patterns related to the high and low fitness in the lung after IV infection. This pattern was not seen in the in vitro fitness tests, which clearly favored the reference strain (H37Rv). Subsequent determination using a more physiological low-dose aerosol (AER) inoculation with 102 CFU showed a third pattern in which the three best values coincided with the highest dissemination capacity according to epidemiological data. Conclusions/Significance The fitness obtained after low dose aerosol administration in the presence of the innate immune response is the most predictive factor for determining the virulence of clinical strains. This gives support to a mechanism of the induction of active TB derived from the dynamic hypothesis of latent tuberculosis infection.
Cache Decomposition for Energy Efficient Processors

The L1 data cache is a time-critical module and, at the same time, a major source of energy consumption. To reduce its energy-delay product, we apply two principles of low power design: specialize part of the cache structure and break dow n the cache into smaller caches. To this end, we propose a L1 cache that combines new designs of a stack cache and a PSA cache. Individually, our stack and PSA cache designs have a lower energy-delay product than previously proposed designs. In addition, their combined operation is very effect ive. Relative to a conventional 2-way 32KB data cache, our design containing a 4-way 32KB PSA cache and a 512B stack cache reduces the energy-delay product of several applications b y an average of 44%.
High Throughput, Pipelined Implementation of AES on FPGA

The FPGA-based high throughput 128 bits AES cipher processor is proposed in this paper. We present an equivalent pipelined AES architecture working on CTR mode to provide the highest throughput up to date through inserting some registers in appropriate points making the delay shortest, when implementing the byte transformation in one clock period. The equivalent pipelined architecture does not change the data stream direction but change the inner process order in round transformation. Xilinx Foundation ISETM 10.1 FPGA design tool is used in the synthesis of the design. And the throughput of 73.737Gbps, clock frequency of 576.07MHz and resource efficiency of 3.21Mbps/LUT are provided by the proposed equivalent pipelined AES architecture. The proposed design reach higher throughput than the other designs up to date, and its resource efficiency is also very high.
Continuous Dependence with Respect to the Input of Trajectories of Control-Affine Systems

We study the continuous dependence on the input of trajectories of control-affine systems belonging to the class C0(m) of all systems $\Sigma$ of the form $$\Sigma: \ \ \ \ \ \ \dot{x}=f_0(x)+\sum_{i=1}^m u_i(t)f_i(x),$$ where f0,. fm are continuous vector fields on some open subset of $\mathbb{R}^n$ and the control functions belong to $L^1([0,T],\mathbb{R}^m)$. We give a simple necessary and sufficient condition for a control sequence $\{u^j\}_{j=1}^{\infty}$ to "${\cal T}^0$-converge" to a control $u^\infty$, i.e., to be such that, for every system $\Sigma$ in C0, the trajectories generated by the uj converge as $j\rightarrow\infty$ to the trajectories generated by $u^\infty$. We also characterize ${\cal T}^k$-convergence (the concept of control convergence that arises when we use, instead of C0(m), the class Ck(m) of systems $\Sigma$ where the fi are of class Ck) for $k\ge 1$ in the scalar input case, and we explain how the analogous characterization for the multi-input case fails to be true, unless one restricts oneself to the class $C^k_{comm}(m)$ of systems for which the vector fields f0,. fm commute. As a preliminary, we define a "topology of trajectory convergence" (or "T-convergence") on the set of all time-varying vector fields $\Omega\times I\ni (x,t)\mapsto f(x,t)\in\mathbb{R}^n$, where $\Omega$ is an open subset of $\mathbb{R}^n$ and I is an interval, and we study some of its properties. This enables us to make the definition of ${\cal T}^k$-convergence precise for sequences and, more generally, for nets, by saying that a net $\{u^\alpha\}_{\alpha\in A}$ in $L^1([0,T],\mathbb{R}^m)$ ${\cal T}^k$-converges to a limit $u^\infty$ if for every system $\Sigma$ in C0(m) the time-varying vector fields $(x,t)\mapsto f_0(x)+\sum_{i=1}^m u_i^\alpha(t)f_i(x)$ ${\cal T}^k$-converge to $(x,t)\mapsto f_0(x)+\sum_{i=1}^m u_i^\infty(t)f_i(x)$.
The Influence of Country-Level Governance on Business Environment and Entrepreneurship: a Global Perspective

The main purpose of this study is to analyze the influence of country-level governance on business environment and entrepreneurship for an international large sample of countries for a period of six years (2007-2012). The dimensions of country-level governance at macroeconomic level will be captured by using the following six indicators developed by the World Bank: 1. Voice and accountability; 2. Political stability and absence of violence; 3. Government effectiveness; 4. Regulatory quality; 5. Rule of law; 6. Control of corruption. To capture the quality of business environment we use the Ease of doing business index developed by the World Bank in its Doing Business report series. To measure entrepreneurship we use the World Bank Group Entrepreneurship Survey where the number of new registered businesses, as a percentage of the working age population is defined as a measure of formal entrepreneurship. In order to capture the extent to which country-level governance does influence business environment and entrepreneurship, we analyze the data using cross-sectional time-series random effects generalized least square (GLS) models. The results of this panel data analysis clarifies and quantifies the influence that various characteristics of country-level governance could have on business environment and entrepreneurship. Therefore, this study could have significant implications for policy-makers as well as for businesses.