Miracle-dz/UniFAR-FTUs huggingface dataset:
Meta‐Analysis of Economics Research Reporting Guidelines

Meta‐regression analysis (MRA) can provide objective and comprehensive summaries of economics research. Their use has grown rapidly over the last few decades. To improve transparency and to raise the quality of MRA, the meta‐analysis of economics research‐network (MAER‐Net) has created the below reporting guidelines. Future meta‐analyses in economics will be expected to follow these guidelines or give valid reasons why a meta‐analysis must deviate from them.
Efficient Scheduling for Low-Power High-Performance DSP Applications �

To process high performance DSP applications in embedded systems, VLIW (Very Long Instruction Word) architecture is widely adopted in high-end DSP processors. While better performance is achieved, more power consumption may be needed in order to execute several instructions simultaneously in a VLIW processor. Therefore, an important problem is how to schedule an application on a VLIW processor such that the energy consumption of the application is minimized while the timing performance is satisfied. To solve this problem, we identify the two most important factors: switching activity and schedule length, that influence the energy consumption of an application executed on a VLIW processor. Considering these two factors together, we present a novel instruction-level energyminimization scheduling technique to reduce the energy consumption of an applications on a VLIW processors. We first formally prove that this problem is NP-complete. Then three heuristic algorithms, MSAS, MLMSA, and EMSA, are proposed and studied. While switching activity and schedule length are given higher priority in MSAS and MLMSA, respectively, EMSA gives the best result considering both of them. The experimental results show that EMSA gives a % reduction in energy compared with the standard list scheduling approach on average.
Synaptic Depression and the Temporal Response Characteristics of V1 Cells

We explore the effects of short-term synaptic depression on the temporal dynamics of V1 responses to visual images by constructing a model simple cell. Synaptic depression is modeled on the basis of previous detailed fits to experimental data. A component of synaptic depression operating in the range of hundreds of milliseconds can account for a number of the unique temporal characteristics of cortical neurons, including the bandpass nature of frequency–response curves, increases in response amplitude and in cutoff frequency for transient stimuli, nonlinear temporal summation, and contrast-dependent shifts in response phase. Synaptic depression also provides a mechanism for generating the temporal phase shifts needed to produce direction selectivity, and a model constructed along these lines matches both extracellular and intracellular data. A slower component of depression can reproduce the effects of contrast adaptation.
Learning to be a better q'er in social Q&A sites: Social norms and information artifacts

Social question and answer sites (SQAs) are increasingly popular knowledge sharing platforms. In this paper, we outline how an SQA site functions as a social learning community. The success of an SQA site depends not only on effectively organizing and delivering information, but also on whether it can provide the cues needed by community members to successfully learn to be productive contributors. We explore this learning process in four different SQAs that utilize the Stack Exchange platform: Science Fiction & Fantasy, Seasoned Advice (cooking), Database Administrators, and Android Enthusiasts. Using longitudinal fixed effects models, we examine whether users learn to be better question askers over time, and how user interface features and community norms affect the cultivation of this critical skill. The study offers design implications by highlighting factors that help users develop into literate and productive community contributors in social platforms.
Virtual environments and autism: a developmental psychopathological approach

Individuals with autism spectrum disorders supposedly have an affinity with information and communication technology (ICT), making it an ideally suited media for this population. Virtual environments (VEs) ‐ both two-dimensional and immersive ‐ represent a particular kind of ICT that might be of special benefit. Specifically, this paper discusses the importance of psychological theory for VE designed for this population. I describe the contribution that different theories of autism (e.g., theory of mind, executive function, weak central coherence theory) have made and can make, as well as the potential of other non-autism-specific theories (e.g., embodied cognition). These technologies not only illuminate our understanding of autism, but they can also be used to develop new technologies for people without autism. So, as well as being an area of specialism, I argue that VE research in autism has extended ‐ and will go onto ‐ the boundaries of human‐computer interaction more generally. This is because autism provides a unique window into human social communication and learning. Further, this field offers a chance for better inclusivity for individuals with autism within a digital society.
Mathematical model development for faults simulation in current-source PWM inverters

Despite of remarkable technological achievements reached in power electronics (both for devices and circuits) faults remains inevitable, being the main cause of power systems interrupts and failures. In the last decade the fault problem in power electronics has been investigated with more attention both from theoretical and experimental point of view. Following these trends, this paper is focused to introduce a novel mathematical model specially developed for simulation of faults in current-source inverters (CSIs) operating in high reliability servo-drive applications. By approaching a generalized fault-tolerant model development, it has been designed a CSI model able to simulate both unfaulty and faulty conditions when one or more power electronic devices fails in operation. In this way the drawback of building a separately model and a separately simulation program for each operation mode (both for unfaulty and faulty states) has been eliminated. The generalized model has been validated via careful computer-aided simulations in Matlab/Simulink software environment. In order to compare the obtained results in different failure states various faulty-state power converter architectures has been considered, their operating conditions being tested in a servo-drive application.
Experience and Technology Adoption

Vintage human capital models imply that young workers will be the primary adopters and beneficiaries of new technologies. Because technological progress in general, and computers in particular, may be skill-biased and because human capital increases over the lifecycle, technological change may favor experienced workers. This paper estimates the relationship between experience and technology adoption and the effect of technological change on the returns to experience. Estimates indicate that technological change is an important explanation for changes in experience premia. We find a complementarity between existing human capital and computer adoption and provide evidence that young workers are better able to adapt to new technologies. Our estimates also shed light on creative destruction models of the productivity slowdown.
An Efficient Software Fault Prediction Model using Cluster based Classification

Predicting fault -prone software components is an economically important activity due to limited budget allocation for software testing. In recent years data mining techniques are used to predict the software faults . In this research, we present a cluster based fault prediction classifiers which increases the probability of detection. The expectation from a predictor is to get very high probability of detection to get more reliable and test effective software. In our experiments, we used fault data from mission critical systems. In this paper we have used discretization as preprocessing and cluster based classification for prediction of fault-prone software modules. Clustering based classification allows production of comprehensible models of software faults exploiting symbolic learning algorithms. To evaluate this approach we perform an extensive comparative analysis with benchmark results of software fault prediction for the same data sets. Our proposed model shows better results than the standard and benchmark approaches for software fault prediction. Our proposed model gives superior probability of detection (pd) 83.3% and balance rates 685%.
The Precision of Anatomical Normalization in the Medial Temporal Lobe Using Spatial Basis Functions

We investigated the accuracy of spatial basis function normalization using anatomical landmarks to determine how precisely homologous regions are colocalized. We examined precision in terms of: (1) the number of nonlinear basis functions used by the normalization procedure; (2) the degree of (Bayesian) regularization; and (3) the effect of substituting different templates and how this interacted with the number of basis functions. The face validity of spatial normalization was assessed as a function of these parameters, using the colocalization of homologous landmarks in a test sample of 20 normally developing children and 5 children with bilateral hippocampal pathology. Our results suggest that when optimal normalization parameters are used, anatomical landmarks in the medial temporal lobes are colocalized to within a standard deviation of about 1 mm. When suboptimal parameters are used this standard deviation can increase up to 3 mm. Interestingly the optimal parameters are those that provide a rather constrained normalization as opposed to those that optimize intensity matching at the expense of rendering the warps "unlikely. " The implications of our results, for users of voxel-based morphometry, are discussed.
Software Systems as Complex Networks

As software systems become larger and more complex, in order to understand, manage and evolve these systems, we need better ways of characterizing and controlling their macroscopic properties. We suggest complex network theory may be useful for these purposes. In recent years, researchers have shown that many complex systems from different disciplines can be investigated as complex networks and most of them comply with a scale-free network model. We explore the view that a software system can be studied as a network with a number of components (classes) connected by dependency (integration) relationships; we call this network the component dependency network (CDN). The CDNs of several Java libraries and applications have been examined and all of them exhibit some scale-free characteristics. This result has some practical value including that it allows us to identify important components (classes) and thereby assists software maintenance and reengineering. We have built a tool to study software systems as complex networks. In the paper we also suggest ways of controlling and changing how systems evolve in order to improve their understandability and maintainability.
Effect of Twisted Fiber Anisotropy in Cardiac Tissue on Ablation with Pulsed Electric Fields

Background Ablation of cardiac tissue with pulsed electric fields is a promising alternative to current thermal ablation methods, and it critically depends on the electric field distribution in the heart. Methods We developed a model that incorporates the twisted anisotropy of cardiac tissue and computed the electric field distribution in the tissue. We also performed experiments in rabbit ventricles to validate our model. We find that the model agrees well with the experimentally determined ablation volume if we assume that all tissue that is exposed to a field greater than 3 kV/cm is ablated. In our numerical analysis, we considered how tissue thickness, degree of anisotropy, and electrode configuration affect the geometry of the ablated volume. We considered two electrode configurations: two parallel needles inserted into the myocardium (“penetrating needles” configuration) and one circular electrode each on epi- and endocardium, opposing each other (“epi-endo” configuration). Results For thick tissues (10 mm) and moderate anisotropy ratio (a = 2), we find that the geometry of the ablated volume is almost unaffected by twisted anisotropy, i.e. it is approximately translationally symmetric from epi- to endocardium, for both electrode configurations. Higher anisotropy ratio (a = 10) leads to substantial variation in ablation width across the wall; these variations were more pronounced for the penetrating needle configuration than for the epi-endo configuration. For thinner tissues (4 mm, typical for human atria) and higher anisotropy ratio (a = 10), the epi-endo configuration yielded approximately translationally symmetric ablation volumes, while the penetrating electrodes configuration was much more sensitive to fiber twist. Conclusions These results suggest that the epi-endo configuration will be reliable for ablation of atrial fibrillation, independently of fiber orientation, while the penetrating electrode configuration may experience problems when the fiber orientation is not consistent across the atrial wall.
Conditional ablation of p63 indicates that it is essential for embryonic development of the central nervous system

p63 is a member of the p53 family that regulates the survival of neural precursors in the adult brain. However, the relative importance of p63 in the developing brain is still unclear, since embryonic p63−/− mice display no apparent deficits in neural development. Here, we have used a more definitive conditional knockout mouse approach to address this issue, crossing p63fl/fl mice to mice carrying a nestin-CreERT2 transgene that drives inducible recombination in neural precursors following tamoxifen treatment. Inducible ablation of p63 following tamoxifen treatment of mice on embryonic day 12 resulted in highly perturbed forebrain morphology including a thinner cortex and enlarged lateral ventricles 3 d later. While the normal cortical layers were still present following acute p63 ablation, cortical precursors and neurons were both reduced in number due to widespread cellular apoptosis. This apoptosis was cell-autonomous, since it also occurred when p63 was inducibly ablated in primary cultured cortical precursors. Finally, we demonstrate increased expression of the mRNA encoding another p53 family member, ΔNp73, in cortical precursors of p63−/− but not tamoxifen-treated p63fl/fl;R26YFPfl/fl;nestin-CreERT2+/Ø embryos. Since ΔNp73 promotes cell survival, then this compensatory increase likely explains the lack of an embryonic brain phenotype in p63−/− mice. Thus, p63 plays a key prosurvival role in the developing mammalian brain.
Microbial diversity in the floral nectar of seven Epipactis (Orchidaceae) species

Floral nectar of animal‐pollinated plants is commonly infested with microorganisms, yet little is known about the microorganisms inhabiting the floral nectar of orchids. In this study, we investigated microbial communities occurring in the floral nectar of seven Epipactis (Orchidaceae) species. Culturable bacteria and yeasts were isolated and identified by partially sequencing the small subunit (SSU) ribosomal RNA (rRNA) gene and the D1/D2 domains of the large subunit (LSU) rRNA gene, respectively. Using three different culture media, we found that bacteria were common inhabitants of the floral nectar of Epipactis. The most widely distributed bacterial operational taxonomic units (OTUs) in nectar of Epipactis were representatives of the family of Enterobacteriaceae, with an unspecified Enterobacteriaceae bacterium as the most common. In contrast to previous studies investigating microbial communities in floral nectar, very few yeast species (mainly of the genus Cryptococcus) were observed, and most of them occurred in very low densities. Total OTU richness (i.e., the number of bacterial and yeast OTUs per orchid species) varied between 4 and 20. Cluster analysis revealed that microbial communities of allogamous species differed from those of autogamous and facultatively autogamous species. This study extends previous efforts to identify microbial communities in floral nectar and indicates that the floral nectar of the orchids investigated mainly contained bacterial communities with moderate phylogenetic diversity.
Evaluation of Cross-Protocol Stability of a Fully Automated Brain Multi-Atlas Parcellation Tool

Brain parcellation tools based on multiple-atlas algorithms have recently emerged as a promising method with which to accurately define brain structures. When dealing with data from various sources, it is crucial that these tools are robust for many different imaging protocols. In this study, we tested the robustness of a multiple-atlas, likelihood fusion algorithm using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data with six different protocols, comprising three manufacturers and two magnetic field strengths. The entire brain was parceled into five different levels of granularity. In each level, which defines a set of brain structures, ranging from eight to 286 regions, we evaluated the variability of brain volumes related to the protocol, age, and diagnosis (healthy or Alzheimer’s disease). Our results indicated that, with proper pre-processing steps, the impact of different protocols is minor compared to biological effects, such as age and pathology. A precise knowledge of the sources of data variation enables sufficient statistical power and ensures the reliability of an anatomical analysis when using this automated brain parcellation tool on datasets from various imaging protocols, such as clinical databases.
Cross-layer wireless sensor network radio power management

With the progression of computer networks extending boundaries and joining distant locations, wireless sensor networks (WSNs) emerge as the new frontier in developing opportunities to collect and process data from remote locations. WSNs rely on hardware simplicity to make sensor field deployments both affordable and long-lasting without maintenance support. WSN designers strive to extend network lifetimes while meeting application-specific throughput and latency requirements. Effective power management places sensor nodes into one of the available energy-saving modes based upon the sleep period duration and the current state of the radio. The newest generation of sensor platform radios with a 250 kbps data rate does not provide adequate time to completely power off the radio during overheard 128-byte constrained IEEE 802.15. 4 transmissions. This paper proposes a new radio power management (RPM) algorithm which optimizes radio sleep capabilities by transitioning nodes to intermediate power level states. Additionally, the experimental work characterizes the radio power levels, state transition times, and state transition energy costs of an IEEE 802.15. 4 compliant sensor platform for improved accuracy in simulating WSN energy consumption
Noisy Inventory Announcements and Energy Prices

This study examines the effect of oil and gas inventory announcements on energy prices. Previous estimates of this effect suffer from bias due to measurement error in inventory surprises. We utilize intraday futures data for three petroleum commodities and natural gas to estimate the price response coefficients using traditional event study regressions and the identification‐through‐censoring (ITC) technique proposed by Rigobon and Sack [Rigobon and Sack (2008). Asset prices and monetary policy (pp. 335–370). Chicago: University of Chicago Press]. The results show that the bias in OLS estimates of the price impact of inventory surprises is quite large. The ITC coefficient estimates are about twice as large as OLS estimates for petroleum commodities and about four times as large as OLS estimates for natural gas. These results imply that energy prices are more strongly influenced by unexpected changes in inventory than shown in previous research. © 2013 Wiley Periodicals, Inc. Jrl Fut Mark 34:911–933, 2014
Study of Sleep Disorders in Resistant Hypertensive Patients on Conventional Hemodialysis

Background: Every year more people suffer from end stage renal disease (ESRD). Sleep disturbances have been reported to be frequent in dialysis patients. Sleep disturbances could be sleep apnea, periodic limb movements in sleep or restless leg syndrome. Patients and methods: Sixty patients were chosen from Ain Shams University Hospitals dialysis units, between July 2010 and March 2012. Patients were divided into 6 groups: Group A: 10 patients with resistant HTN and ESRD on conventional HD having a PSQI score > 5. Group B: 10 patients with resistant, HTN and ESRD on conventional HD having a PSQI score < 5. Group C: 10 patients with ESRD only on conventional HD having a PSQI score > 5. Group D: 10 patients having ESRD only on conventional HD having a PSQI score < 5. Group E: 10 patients having resistant HTN normal renal function. They had PSQI score > 5. Group F: 10 patients having resistant HTN and normal renal function. They had PSQI score < 5.For all groups, creatinine, BUN, Hb, albumin, Na, K, PO4, Ca and uric acid were done. Polysomnography was done for bad sleeper groups (group A, group C and group E). Results: Creatinine and BUN were significantly higher in bad sleeper groups than good sleeper groups (group A than group B and group C than group D). Nearly all polysomnographic parameters were abnormal in group A, group C and group E. In group A and group C, creatinine was positively correlated to parameters of obstructive sleep apnes OSA and periodic limb movement PLM (P < 0.05). In group A and group E, SBP and DBP were positively correlated to parameters of OSA and PLM. Conclusion: ESRD induces sleep disorders exacerbated by resistant HTN. Also resistant HTN alone can induce sleep disorders. [Mohamed Ali Ibrahim, Mona Hosny Abd El Salam, Tarek Asaad Abdo, and Heba Alloush. Study of Sleep Disorders in Resistant Hypertensive Patients on Conventional Hemodialysis. Life Sci J 2012;9(4):1887-1900] (ISSN:1097-8135). http://www.lifesciencesite. com. 287
HEATS OF K/Ca AND K/Pb EXCHANGE IN TWO TROPICAL SOILS AS MEASURED BY FLOW CALORIMETRY 1

Flow calorimetry can provide useful information about surface chemical reactions in soils that cannot be obtained readily by other methods. When flow calorimetry is conducted over a range of surface coverages, different sorption heats can be calculated to yield information about how binding energies vary with coverage, i.e., surface heterogeneity. The purpose of this study was to determine heats of exchange for K/Ca and K/Pb systems using flow calorimetry and to evaluate the degree of surface heterogeneity with respect to cation exchange. Surface horizon samples from a Typic Acrorthox and Typic Tropohumult from Puerto Rico were used. Lead was adsorbed specifically in both soils, but no adsorption heat was detected for this reaction in either soil. However, heats associated with reversible cation exchange between K and Pb were observed. Heats for K/Ca exchange were greater than those generated for K/Pb exchange in both soils. Heats of exchange were greater in the Ultisol than in the Oxisol. The differential heats of exchange were independent of exchange composition for both K/Pb and K/Ca exchange in the Oxisol, indicating that all cation exchange sites were similar energetically. In the Ultisol, the differential heats of exchange increased as exchangeable K decreased, indicating that the exchange sites were not similar energetically. These differences were attributed to the presence of smectite in the Ultisol, which was able, in part, to collapse when saturated with K.