Miracle-dz/UniFAR-FTUs huggingface dataset:
The altered complexity of cardiovascular regulation in depressed patients

Major depressive disorders (MDD) are associated with an increased risk for cardiovascular morbidity and mortality. Even if it is known that MDD are accompanied by an autonomic dysbalance with increased sympathetic and/or reduced parasympathetic activity, to date only limited information is available about the degree and complexity of cardiovascular regulation. The aim of this study was to investigate the influence of MDD on the autonomous nervous system and cardiovascular complexity by means of linear and nonlinear indices from heart rate and blood pressure variability (HRV, BPV). From 57 non-medicated patients and 57 matched healthy controls with respect to age and gender HRV and BPV in time and frequency domain, symbolic dynamics, compression entropy, multiscale entropy, detrended fluctuation analysis, Poincaré plot analysis and baroreflex sensitivity were analysed from 30 min short-term recordings. Complexity indices from nonlinear dynamics demonstrated considerable changes in autonomous regulation due to MDD. For the first time we could show that non-medicated depressed patients who were matched with respect to age and gender reveal a significantly changed short-term as well as long-term complexity of cardiovascular regulation. These results suggest substantial changes in autonomic control probably due to a change of interactions between different physiological control loops in MDD.
Logic synthesis of 100-percent testable logic networks

An approach is presented for the synthesis of 100% testable logic networks based on a test pattern generation system for the identification of redundant faults. A redundancy removal procedure for the elimination of redundant nodes and gates from the network is also presented. Elimination of redundancy is an important task in a logic synthesis system that aims at the synthesis of 100% testable logic networks. Logic synthesis algorithms tend to generate a large number of redundancies, most of which can be easily identified, but some of these redundancies are very hard to identify by logic minimization procedures as well as by conventional test pattern generation algorithms. <<ETX>>
Cortical and cancellous bone thickness on the anterior region of alveolar bone in Korean: a study of dentate human cadavers

PURPOSE The cortical bone thickness on the anterior region is important for achieving implant stability. The purpose of this study was to examine the thickness of the cortical and cancellous bones on the anterior region of the maxilla and mandible. MATERIALS AND METHODS Twenty-five cadaver heads were used (16 male and 9 female; mean death age, 56.7 years). After the long axis of alveolar process was set up, it was measured in 5 levels starting from 2 mm below the cementoenamel junction (L1) at intervals of 3 mm. All data was analysed statistically by one-way ANOVA at the . 05 significance level. RESULTS The cortical bone thickness according to measurement levels in both the labial and lingual sides increased from L1 to L5, and the lingual side below L3 was significantly thicker than the labial side on the maxilla and mandible. In particular, the labial cortical bone thickness in the maxilla was the thinnest compared to the other regions. The cancellous bone thickness according to measurement levels increased from L1 to L5 on the maxilla, and on the mandible it was the thinnest at the middle level of the root. CONCLUSION For implant placement on the anterior region, a careful evaluation and full knowledge on the thickness of the cortical and cancellous bone are necessary, therefore, these results may provide an anatomic guideline to clinicians.
Automated Melanoma Recognition

A system for the computerized analysis of images obtained from ELM has been developed to enhance the early recognition of malignant melanoma. As an initial step, the binary mask of the skin lesion is determined by several basic segmentation algorithms together with a fusion strategy. A set of features containing shape and radiometric features as well as local and global parameters is calculated to describe the malignancy of a lesion. Significant features are then selected from this set by application of statistical feature subset selection methods. The final kNN classification delivers a sensitivity of 87% with a specificity of 92%.
An Economic Evaluation of a Video- and Text-Based Computer-Tailored Intervention for Smoking Cessation: A Cost-Effectiveness and Cost-Utility Analysis of a Randomized Controlled Trial

Background Although evidence exists for the effectiveness of web-based smoking cessation interventions, information about the cost-effectiveness of these interventions is limited. Objective The study investigated the cost-effectiveness and cost-utility of two web-based computer-tailored (CT) smoking cessation interventions (video- vs. text-based CT) compared to a control condition that received general text-based advice. Methods In a randomized controlled trial, respondents were allocated to the video-based condition (N = 670), the text-based condition (N = 708) or the control condition (N = 721). Societal costs, smoking status, and quality-adjusted life years (QALYs; EQ-5D-3L) were assessed at baseline, six-and twelve-month follow-up. The incremental costs per abstinent respondent and per QALYs gained were calculated. To account for uncertainty, bootstrapping techniques and sensitivity analyses were carried out. Results No significant differences were found in the three conditions regarding demographics, baseline values of outcomes and societal costs over the three months prior to baseline. Analyses using prolonged abstinence as outcome measure indicated that from a willingness to pay of €1,500, the video-based intervention was likely to be the most cost-effective treatment, whereas from a willingness to pay of €50,400, the text-based intervention was likely to be the most cost-effective. With regard to cost-utilities, when quality of life was used as outcome measure, the control condition had the highest probability of being the most preferable treatment. Sensitivity analyses yielded comparable results. Conclusion The video-based CT smoking cessation intervention was the most cost-effective treatment for smoking abstinence after twelve months, varying the willingness to pay per abstinent respondent from €0 up to €80,000. With regard to cost-utility, the control condition seemed to be the most preferable treatment. Probably, more time will be required to assess changes in quality of life. Future studies with longer follow-up periods are needed to investigate whether cost-utility results regarding quality of life may change in the long run. Trial Registration Nederlands Trial Register NTR3102
Mobility modeling in third-generation mobile telecommunications systems

In mobile communications, mobility modeling is involved in several aspects related to signaling and traffic load analysis. In third-generation systems, the influence of mobility on the network performance (e.g., handover rate) will be strengthened, mainly due to the huge number of mobile users in conjunction with the small cell size. In particular, the accuracy of mobility models becomes essential for the evaluation of system design alternatives and network implementation cost issues. The authors propose three basic types of mobility models, which are appropriate for the analysis of the full range of mobile communications design issues. The models provide different levels of detail regarding the user mobility behavior. In particular, (a) the city area model traces user motion at an area zone level, (b) the area zone model considers users moving on a street network, and (c) the street unit model tracks user motion with an accuracy of a few meters. The validity of the basic models for mobile communications design aspects is highlighted. Moreover, an "integrated mobility modeling tool" which considers the basic mobility models as components is proposed, aiming at the development of a refined modeling approach. This is achieved by improving the accuracy of the input parameters of each basic model via the exchange of some specific (mobility-related) parameters among the component models. To justify the applicability of the proposed integrated tool for both the analysis of design aspects and network planning, indicative results are presented, derived from simulation-based application examples of the three basic mobility models.
The QC relaxation: A theoretical and computational study on optimal power flow

Convex relaxations of the power flow equations and, in particular, the Semi-Definite Programming (SDP) and Second-Order Cone (SOC) relaxations, have attracted significant interest in recent years. The Quadratic Convex (QC) relaxation is a departure from these relaxations in the sense that it imposes constraints to preserve stronger links between the voltage variables through convex envelopes of the polar representation. This paper is a systematic study of the QC relaxation for AC Optimal Power Flow with realistic side constraints. The main theoretical result shows that the QC relaxation is stronger than the SOC relaxation and neither dominates nor is dominated by the SDP relaxation. In addition, comprehensive computational results show that the QC relaxation may produce significant improvements in accuracy over the SOC relaxation at a reasonable computational cost, especially for networks with tight bounds on phase angle differences. The QC and SOC relaxations are also shown to be significantly faster and reliable compared to the SDP relaxation given the current state of the respective solvers.
Cancer Statistics in Korea: Incidence, Mortality, Survival, and Prevalence in 2009

Purpose This study overviews nationwide cancer statistics, including incidence, mortality, survival, and prevalence, and their trends in Korea based on 2009 cancer incidence data. Materials and Methods Incidence data from 1993-2009 were obtained from the Korea National Cancer Incidence Database, and vital status was followed through 31 December 2010. Mortality data from 1983-2009 were obtained from Statistics Korea. Crude rates and age-standardized rates for incidence, mortality, and prevalence; and relative survival were calculated. Results In total, 192,561 cancer cases and 69,780 cancer deaths were observed during 2009, and 808,503 10-year cancer prevalent cases occurred in Korea as of 1 January 2010. The incidence rate for all cancers combined showed an annual increase of 3.3% from 1999 to 2009. Conclusion Stomach, liver and cervical cancers have been decreasing and thyroid, breast and colorectal cancers have been increasing at large. In particular, in 2009, colorectal cancer became the third most common cancer in females and for the first time ranked higher than stomach cancer, which had been the long-standing common cancer in Korea. While overall cancer incidence has been rapidly increasing in Korea, age-standardized cancer mortality rates have been declining since 2002, and cancer survival has been improving.
Urp: a luminous-tangible workbench for urban planning and design

We introduce a system for urban planning - called Urp -thatintegrates functions addressing a broad range of the fieldsconcerns into a single, physically based workbench setting. The I/OBulb infrastructure on which the application is based allowsphysical architectural models placed on an ordinary table surfaceto cast shadows accurate for arbitrary times of day; to throwreflections off glass facade surfaces; to affect a real-time andvisually coincident simulation of pedestrian-level windflow; and soon. We then use comparisons among Urp and severalearlier I/O Bulb applications as the basis for anunderstanding of luminous-tangible interactions, which resultwhenever an interface distributes meaning and functionality betweenphysical objects and visual information projectively coupled tothose objects. Finally, we briefly discuss two issues common to allsuch systems, offering them as informal thought-tools for thedesign and analysis of luminous-tangible interfaces.
Dispersion-based prediction framework for estimating missing values in wireless sensor networks

Wireless Sensor Networks (WSNs) have attracted many researchers in the past few years due to their applicability for a wide-range of applications. WSNs rely on unreliable sensing schemes in which a sensor might lose some data due to the inherent characteristics of such networks. Estimating missing values that cope with other collected ones is crucial for some applications. In this paper, we introduced a framework dedicated to predicting missing values in WSNs. The key idea is to estimate missing values according to the natural spread (i.e. dispersion) of the guilty sensors. The framework considers cases in which distance and time play a significant role in estimating missing values. Thus, accurate values might be generated as compared to state-of-the-art central tendency measurements such as mean, median, mode, and midrange.
Cognitive control in the self-regulation of physical activity and sedentary behavior

Cognitive control of physical activity and sedentary behavior is receiving increased attention in the neuroscientific and behavioral medicine literature as a means of better understanding and improving the self-regulation of physical activity. Enhancing individuals’ cognitive control capacities may provide a means to increase physical activity and reduce sedentary behavior. First, this paper reviews emerging evidence of the antecedence of cognitive control abilities in successful self-regulation of physical activity, and in precipitating self-regulation failure that predisposes to sedentary behavior. We then highlight the brain networks that may underpin the cognitive control and self-regulation of physical activity, including the default mode network, prefrontal cortical networks and brain regions and pathways associated with reward. We then discuss research on cognitive training interventions that document improved cognitive control and that suggest promise of influencing physical activity regulation. Key cognitive training components likely to be the most effective at improving self-regulation are also highlighted. The review concludes with suggestions for future research.
The Effects of Parameters on the Efficiency of DLLME in Extracting of PAHs from Vegetable Samples

An effective analytical method based on microwave-assisted extraction (MAE) and dispersive liquid-liquid microextraction (DLLME) followed by gas chromatography-flame ionization detector (GC-FID) was developed for the determination of polycyclic aromatic hydrocarbons (PAHs) in vegetable samples. In most cases, the details of the parameters influencing the efficiency of DLLME in extraction are not well studied. Understanding the reactions of solvents in extraction is the important task on selecting of an appropriate solvent in the process. The effects of parameters affecting the extraction efficiency of DLLME, including extraction solvent and dispersive solvent, extraction time and MAE, such as solvent, microwave power and irradiation time, were studied and explained. The impacts of physiochemical properties of the selected extraction solvents on the extraction efficiency were also investigated. The results indicated that extraction solvents with low viscosity and low polarity have better extraction efficiency in extraction of PAHs from vegetable sample. No significant difference was observed for the effects of selected dispersive solvents and extraction time on extraction efficiency. In MAE, the types of solvent, microwave power and irradiation time implied some critical effects on the extraction efficiency of DLLME.
Effects of Short-Term Warming and Altered Precipitation on Soil Microbial Communities in Alpine Grassland of the Tibetan Plateau

Soil microbial communities are influenced by climate change drivers such as warming and altered precipitation. These changes create abiotic stresses, including desiccation and nutrient limitation, which act on microbes. However, our understanding of the responses of microbial communities to co-occurring climate change drivers is limited. We surveyed soil bacterial and fungal diversity and composition after a 1-year warming and altered precipitation manipulation in the Tibetan plateau alpine grassland. In isolation, warming and decreased precipitation treatments each had no significant effects on soil bacterial community structure; however, in combination of both treatments altered bacterial community structure (p = 0.03). The main effect of altered precipitation specifically impacted the relative abundances of Bacteroidetes and Gammaproteobacteria compared to the control, while the main effect of warming impacted the relative abundance of Betaproteobacteria. In contrast, the fungal community had no significant response to the treatments after 1-year. Using structural equation modeling (SEM), we found bacterial community composition was positively related to soil moisture. Our results indicate that short-term climate change could cause changes in soil bacterial community through taxonomic shifts. Our work provides new insights into immediate soil microbial responses to short-term stressors acting on an ecosystem that is particularly sensitive to global climate change.
Phylogenetic Analysis Reveals a Cryptic Species Blastomyces gilchristii, sp. nov. within the Human Pathogenic Fungus Blastomyces dermatitidis

Background Analysis of the population genetic structure of microbial species is of fundamental importance to many scientific disciplines because it can identify cryptic species, reveal reproductive mode, and elucidate processes that contribute to pathogen evolution. Here, we examined the population genetic structure and geographic differentiation of the sexual, dimorphic fungus Blastomyces dermatitidis, the causative agent of blastomycosis. Methodology/Principal Findings Criteria for Genealogical Concordance Phylogenetic Species Recognition (GCPSR) applied to seven nuclear loci (arf6, chs2, drk1, fads, pyrF, tub1, and its-2) from 78 clinical and environmental isolates identified two previously unrecognized phylogenetic species. Four of seven single gene phylogenies examined (chs2, drk1, pyrF, and its-2) supported the separation of Phylogenetic Species 1 (PS1) and Phylogenetic Species 2 (PS2) which were also well differentiated in the concatenated chs2-drk1-fads-pyrF-tub1-arf6-its2 genealogy with all isolates falling into one of two evolutionarily independent lineages. Phylogenetic species were genetically distinct with interspecific divergence 4-fold greater than intraspecific divergence and a high Fst value (0.772, P<0.001) indicative of restricted gene flow between PS1 and PS2. Whereas panmixia expected of a single freely recombining population was not observed, recombination was detected when PS1 and PS2 were assessed separately, suggesting reproductive isolation. Random mating among PS1 isolates, which were distributed across North America, was only detected after partitioning isolates into six geographic regions. The PS2 population, found predominantly in the hyper-endemic regions of northwestern Ontario, Wisconsin, and Minnesota, contained a substantial clonal component with random mating detected only among unique genotypes in the population. Conclusions/Significance These analyses provide evidence for a genetically divergent clade within Blastomyces dermatitidis, which we use to describe a novel species, Blastomyces gilchristii sp. nov. In addition, we discuss the value of population genetic and phylogenetic analyses as a foundation for disease surveillance, understanding pathogen evolution, and discerning phenotypic differences between phylogenetic species.
Increasing the Density in W7-X: Benefits and Limitations

In stellarators, increasing the density is beneficial for the energy confinement. While there is probably not one single reason for this observation, it is still very robust across different devices. This is, for example, reflected in the empirical energy confinement time scaling for stellarators, ISS04. In order to study whether this is also true for Wendelstein 7-X, the energy confinement time scaling for the first divertor experiments is analyzed and compared to ISS04. When the density is increased too much, however, radiative collapses are frequently observed. Existing analytical models for the critical density are revisited to assess whether they can predict the accessible density range. Furthermore, since close to the collapse the radiation losses increase substantially, the impact of the global energy confinement is investigated. It is found that energy confinement starts to become affected as soon as the radiation losses reach 50 % of the heating power. In the second half of the first divertor campaign, boronization has been applied to W7-X for the first time. This broadened the operational window, allowing for operation at higher density and, hence, higher stored energy.
A Discriminative Approach to Robust Visual Place Recognition

An important competence for a mobile robot system is the ability to localize and perform context interpretation. This is required to perform basic navigation and to facilitate local specific services. Usually localization is performed based on a purely geometric model. Through use of vision and place recognition a number of opportunities open up in terms of flexibility and association of semantics to the model. To achieve this, the present paper presents an appearance based method for place recognition. The method is based on a large margin classifier in combination with a rich global image descriptor. The method is robust to variations in illumination and minor scene changes. The method is evaluated across several different cameras, changes in time-of-day and weather conditions. The results clearly demonstrate the value of the approach
Benefits of textural characterization for the classification of hyperspectral images

Several spatial features are compared for the spatial/spectral classification of hyperspectral data. These features are extracted from texture spectra, co-occurrence matrices and morphological profiles. First, a PCA (Principal Components Analysis) is carried out on the hyperspectral image and textural features are computed on the first principal components. These textural features are concatenated together with spectral features (the principal components previously used) and the resulting image vector is then classified using SVM (Support Vector Machines) and a gaussian mixture algorithm. In the latter case, a hierarchical classification is used as a post-processing in order to reach a desired number of classes.
A Family of Exponential Step-Down Switched-Capacitor Converters and Their Applications in Two-Stage Converters

This paper presents a family of exponential voltage step-down switched-capacitor (ESC) converters. Considering the demand of large-voltage-gain step-down converters in the market, it is difficult to achieve the step-down requirement with good efficiency for a single-stage buck converter. The two-stage converter has been an effective solution for high-voltage-step-down applications. In this paper, making use of the large-voltage-gain conversion property of the ESC converter, a two-stage ESC-buck converter is proposed. A mathematical tool for the accurate calculation of efficiency is developed. The efficiency characteristic of the proposed ESC converter is established. Experimental efficiency measurements are carried out using the ESC converter proposed and two different types of commercially available buck converter ICs. The results show that the efficiency of the ESC-buck converter is higher than that of a single buck converter for large-voltage-gain applications.