Miracle-dz/UniFAR-FTUs huggingface dataset:
Problematic Video Gaming in a Young Spanish Population: Association with Psychosocial Health

Problematic video gaming (PVG) is a concern for psychologists attending children and adolescents. Uniform diagnostic criteria are lacking, and risk factors are poorly understood. Internet gaming disorder (IGD) was included in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and scales derived from its diagnostic criteria may be helpful to assess PVG. A multicenter study was conducted in secondary schools using an IGD-derived scale (dichotomous Nine-Item Internet Gaming Disorder Scale [IGD-9]), analyzing PVG-related variables. Seven hundred eight students (55.8 percent male) with mean age 15.6 ± 2.7 years were included. Seventy-three percent were gamers and 22 percent heavy gamers (HGs). Forty-five percent reported online gaming and 6.6 percent massive multiplayer online role-playing games (MMORPGs). Fifty-nine students (8.3 percent) scored 5 or more in IGD-9 and were classified as IGD+. HG and IGD+ subjects were more frequently male and online and MMORPG gamers (p < 0.01). However, IGD+ subjects had significantly worse psychosocial scores than IGD- (p < 0.001), while HGs did not significantly differ from casual gamers (p > 0.01). The multivariate analysis showed that IGD+ scores were significantly associated with worse psychosocial health and adjustment (p < 0.001), while the other variables (male sex, online and MMORPG gaming, and HG) were not significantly associated (p > 0.01). The IGD-9 scale scored positive in 8.3 percent of our sample. Unlike gaming time, this scale was associated with psychosocial disturbances, making it potentially useful as a screening method to detect candidates for clinical intervention.
Combined approach of shell and shear-warp rendering for efficient volume visualization

In Medical Imaging, shell rendering (SR) and shear-warp rendering (SWR) are two ultra-fast and effective methods for volume visualization. We have previously shown that, typically, SWR can be on the average 1.38 times faster than SR, but it requires from 2 to 8 times more memory space than SR. In this paper, we propose an extension of the compact shell data structure utilized in SR to allow shear-warp factorization of the viewing matrix in order to obtain speed up gains for SR, without paying the high storage price of SWR. The new approach is called shear-warp shell rendering (SWSR). The paper describes the methods, points out their major differences in the computational aspects, and presents a comparative analysis of them in terms of speed, storage, and image quality. The experiments involve hard and fuzzy boundaries of 10 different objects of various sizes, shapes, and topologies, rendered on a 1GHz Pentium-III PC with 512MB RAM, utilizing surface and volume rendering strategies. The results indicate that SWSR offers the best speed and storage characteristics compromise among these methods. We also show that SWSR improves the rendition quality over SR, and provides renditions similar to those produced by SWR.
Detecting cells in time varying intensity images in confocal microscopy for gene expression studies in living cells

In this work we present a time-lapsed confocal microscopy image analysis technique for an automated gene expression study of multiple single living cells. Fluorescence Resonance Energy Transfer (FRET) is a technology by which molecule-to-molecule interactions are visualized. We analyzed a dynamic series of ~102 images obtained using confocal microscopy of fluorescence in yeast cells containing RNA reporters that give a FRET signal when the gene promoter is activated. For each time frame, separate images are available for three spectral channels and the integrated intensity snapshot of the system. A large number of time-lapsed frames must be analyzed to identify each cell individually across time and space, as it is moving in and out of the focal plane of the microscope. This makes it a difficult image processing problem. We have proposed an algorithm here, based on scale-space technique, which solves the problem satisfactorily. The algorithm has multiple directions for even further improvement. The ability to rapidly measure changes in gene expression simultaneously in many cells in a population will open the opportunity for real-time studies of the heterogeneity of genetic response in a living cell population and the interactions between cells that occur in a mixed population, such as the ones found in the organs and tissues of multicellular organisms.
Delving into Fully Convolutional Networks Activations for Visual Recognition

Convolutional Neural Networks (CNNs) have attracted significant attention in visual recognition. To fully exploit the potential advantages of the CNN models for image classification, this paper introduces several new ideas, ranging from feature generation to classifier selection. We start by transforming the existing CNN models into fully convolutional networks (FCNs). This eliminates the restriction of image resolution and improves the efficiency for data augmentation. Next, we propose a cross pooling strategy to aggregate the top-layer activations, which combines the advantages of average pooling and max pooling, without enlarging the feature dimension. Moreover, we utilize the regularized logistic regression classifier for image classification, and demonstrate that it cooperates better with our feature than the commonly used linear SVM, both in terms of the accuracy and efficiency. By conducting extensive experiments on four frequently benchmarked datasets, we find our proposed scheme usually has better performance relative to other leading approaches which utilize similar-size features, while delivering comparable results with the state-of-the-art methods which depend on much larger dimensional features.
Face quality assessment for face verification in video

Performance of biometric systems depends on quality of acquired biometric samples. Low sample quality is the main reason for matching errors in biometric systems and may be the principal weakness of some implementations. Therefore, when a biometric system obtains a sequence of person images from a surveillance camera, the quality of the different face images has to be evaluated before performing any analysis on the face of a person. In this paper, we propose an approach for face image quality assessment, which is based on four facial features including facial symmetry, sharpness, quality of illumination and the image resolution. To produce overall face quality score we perform weighted fusion of facial features with automatically tuned weights. Experimental evaluation of the proposed method has demonstrated its high accuracy and efficiency.
Clinical aspects in patients with pulmonary infection caused by mycobacteria of the Mycobacterium abscessus complex, in the Brazilian Amazon

ABSTRACT Objective: To describe the clinical manifestations of patients with pulmonary infection caused by mycobacteria of the Mycobacterium abscessus complex (MABSC), and to compare these manifestations with those of patients infected with other nontuberculous mycobacteria (NTM). Methods: This was a retrospective cohort study involving 43 patients divided into two groups: the MABSC group, consisting of patients with pulmonary infection caused by MABSC (n = 17); and the NTM group, consisting of patients with pulmonary infection caused by NTM other than MABSC (n = 26). Patients were previously treated with a regimen of rifampin, isoniazid, pyrazinamide, and ethambutol before the diagnosis of NTM was confirmed by two culture-positive sputum samples. The nucleotide sequences of the hsp65, 16S rRNA, and/or rpoB genes were analyzed to identify the mycobacteria. Data were collected on demographic, clinical, and radiological characteristics, as well as on treatment responses and outcomes. Results: Loss of appetite was the only clinical manifestation that was significantly more common in the MABSC group than in the NTM group (p = 0.0306). The chance of having to use a second treatment regimen was almost 12 times higher in the MABSC group than in the NTM group. Treatment success was significantly higher in the NTM group than in the MABSC group (83.2% vs. 17.6%; p < 0.0001). The chance of recurrence was approximately 37 times higher in the MABSC group than in the NTM group. Conclusions: In the study sample, treatment response of pulmonary disease caused by MABSC was less favorable than that of pulmonary disease caused by other NTM.
Automaticity in the Recognition of Nonverbal Emotional Vocalizations

The ability to perceive the emotions of others is crucial for everyday social interactions. Important aspects of visual socioemotional processing, such as the recognition of facial expressions, are known to depend on largely automatic mechanisms. However, whether and how properties of automaticity extend to the auditory domain remains poorly understood. Here we ask if nonverbal auditory emotion recognition is a controlled deliberate or an automatic efficient process, using vocalizations such as laughter, crying, and screams. In a between-subjects design (N = 112), and covering eight emotions (four positive), we determined whether emotion recognition accuracy (a) is improved when participants actively deliberate about their responses (compared with when they respond as fast as possible) and (b) is impaired when they respond under low and high levels of cognitive load (concurrent task involving memorizing sequences of six or eight digits, respectively). Response latencies were also measured. Mixed-effects models revealed that recognition accuracy was high across emotions, and only minimally affected by deliberation and cognitive load; the benefits of deliberation and costs of cognitive load were significant mostly for positive emotions, notably amusement/laughter, and smaller or absent for negative ones; response latencies did not suffer under low or high cognitive load; and high recognition accuracy (approximately 90%) could be reached within 500 ms after the stimulus onset, with performance exceeding chance-level already between 300 and 360 ms. These findings indicate that key features of automaticity, namely fast and efficient/effortless processing, might be a modality-independent component of emotion recognition.
Problems Experienced in the First Month After Discharge From a Heart Failure-Related Hospitalization.

Purpose Heart failure is a global health concern with high morbidity and mortality rates. Individuals with heart failure commonly experience problems that impact daily life. However, little is known regarding which problems are most significant during the immediate posthospitalization period. Thus, the purpose of this study was to identify high-priority problems experienced by individuals the first month after discharge from an acute care facility with a diagnosis of heart failure. Methods This descriptive, exploratory study was part of a 12-week randomized controlled pilot study that examined the efficacy of a coping partnership intervention (COPE-HF Partnership) between a trained research nurse and individuals with heart failure in managing self-care and depressive symptoms. Data from participants randomized to the intervention group (N=19; 58% Caucasian, 58% male) were used in this study. Participants were provided a list of potential heart failure-related problems, from which they identified those of highest priority. Content and quantitative data analysis was conducted. Results Difficulty in managing heart failure symptoms, adhering to treatment plan, completing daily activities, and experiencing negative emotions and moods were the most common problems experienced by individuals with heart failure. Other less common problems for the group were inadequate resources and managing interpersonal issues. Conclusions Individuals with heart failure experience complex problems in the home that impact all aspects of their lives. Incorporating strategies to address these problems could assist in the development of interventions to reduce negative heart failure outcomes.
Concerns for I l l ic it and Prescription Drug Use

Concern for illicit and restricted drug use in otolaryngology is similar to other surgical specialties with a few notable exceptions. First, many illicit drugs are consumed transnasally. Repeated nasal exposure to stimulants or narcotics can cause local tissue destruction that can present as chronic rhinosinusitis or nasoseptal perforation. Care must be taken to ensure exposure to offending agents has ceased before attempting repair and consequently, otolaryngologists may insist on drug testing before proceeding to surgery. Second, the US Food and Drug Administration (FDA) has taken a stance against the use of certain prescription narcotics in pediatric
Realistic prediction of individual facial emotion expressions for craniofacial surgery simulations

In addition to the static soft tissue prediction, the estimation of individual facial emotion expressions is an important criterion for the evaluation of the carniofacial surgery planning. In this paper, we present an approach for the estimation of individual facial emotion expressions on the basis of geometrical models of human anatomy derived from tomographic data and the finite element modeling of facial tissue biomechanics.
Effects of Different Drying Treatments on Preservation of Organic Compounds in Dalbergia bariensis Wood

Rosewood furniture and handicrafts are appreciated by Chinese people on account of their rich aroma and pleasing feel. The unique characteristics of rosewood are attributed to the presence of certain organic compounds in its gum canal and parenchyma cells. However, modern wood drying is different from traditional technology with respect to protecting those valuable organic compounds in wood. In this study, to investigate the valuable organic compounds in Dalbergia bariensis, and the effect of drying treatments on their preservation rates, wood extracts, untreated and treated with conventional drying (CD), vacuum drying (VD), and vacuum freeze drying (VFD), were analyzed by gas chromatography- mass spectrometry (GC-MS). The results indicated that there were some compounds with obvious pharmaceutical functions in Dalbergia bariensis, which can be used to improve the furniture function in health care. Also, the preservation of these compounds was affected by drying treatment; VFD drying preserved the maximum amount of organic compounds in wood.
Sleep respiratory disturbances during the ascent to Mount Aconcagua

Introduction: Mountaineers exposed to hypobaric hypoxia (HH) show high-altitude periodic breathing (PB). Objective: To analyze high-altitude PB during the ascent of Mount Aconcagua (Argentina). Materials and Methods: Descriptive study in healthy volunteers using respiratory polygraphy (RP) at different altitudes. Results: We studied 8 andinist, mean age: 36 years old (25-51), body mass index (BMI) of 23.6 (20.9-28.7) and 22.77 (20.9-27.7) upon return, p <0.01. RP without PB showed a lower Oxygen Desaturation Index (ODI) and a lower Apnea-Hypopnea-Index (AHI); 5.43 (0 - 20) versus 45.95 (2-122) p <0.001 and 3.9 (0-15.5) versus 44.35 (4-115) p <0.001. AHI increased with altitude at the expense of central apneas and hypopneas: p <0.05. Conclusion: High-altitude PB is frequent above 2,581m.a. s.l. And it is characterized by short cycles. None of the mountaineers showed PB at baseline; however, high-altitude PB occurred in all subjects above 4,900 m.a.s.l
D B ] 20 A pr 2 01 3 A Markov Model for Ontology Alignment

The explosion of available data along with the need to integrate and utilize that data has led to a pressing interest in data integration techniques. In terms of Semantic Web technologies, Ontology Alignment is a key step in the process of integrating heterogeneous knowledge bases. In this paper, we present the Edge Confidence technique, a modification and improvement over the popular Similarity Flooding technique for Ontology Alignment.
Testing a stepped care model for binge-eating disorder: a two-step randomized controlled trial

Abstract Background A stepped care approach involves patients first receiving low-intensity treatment followed by higher intensity treatment. This two-step randomized controlled trial investigated the efficacy of a sequential stepped care approach for the psychological treatment of binge-eating disorder (BED). Methods In the first step, all participants with BED (n = 135) received unguided self-help (USH) based on a cognitive-behavioral therapy model. In the second step, participants who remained in the trial were randomized either to 16 weeks of group psychodynamic-interpersonal psychotherapy (GPIP) (n = 39) or to a no-treatment control condition (n = 46). Outcomes were assessed for USH in step 1, and then for step 2 up to 6-months post-treatment using multilevel regression slope discontinuity models. Results In the first step, USH resulted in large and statistically significant reductions in the frequency of binge eating. Statistically significant moderate to large reductions in eating disorder cognitions were also noted. In the second step, there was no difference in change in frequency of binge eating between GPIP and the control condition. Compared with controls, GPIP resulted in significant and large improvement in attachment avoidance and interpersonal problems. Conclusions The findings indicated that a second step of a stepped care approach did not significantly reduce binge-eating symptoms beyond the effects of USH alone. The study provided some evidence for the second step potentially to reduce factors known to maintain binge eating in the long run, such as attachment avoidance and interpersonal problems.
Narrow band spectral analysis for onset detection in asynchronous BCI

Asynchronous Brain-Computer Interfaces (BCI) offer more natural mode of human-machine interaction, allowing users to make voluntary and selfpaced mental activities. However, it is difficult to discriminate intentional user control from idle with this approach. In this paper, we propose an approach that requires minimal user training for accurate onset detection of real movements using optimal spectral features from selected electrodes. We obtained true positive rates of 100%, 88%, and 73% for 3 subjects respectively. The results also indicate a potential of the approach for detecting onset of imagery movements.
Automatic Coronary Artery Segmentation in X-ray Angiograms by Multiple Convolutional Neural Networks

Accurate coronary artery segmentation in X-ray angiographic images is a challenging task due to the low image quality and presence of artifacts. This paper proposes an automatic vessel segmentation method in the X-ray angiographic images using correspondence matching and convolutional neural networks (CNN). First, a dense correspondence between the live image and the mask image is generated. Second, patches from live images as well as patches from mask images are put into a two-channel network to achieve a coarse segmentation for the region of interest. Third, a one-channel CNN is used to generate the fine segmentation result. Experiments demonstrate that our method is very effective and robust for coronary artery segmentation, which is better than the other three state-of-the-art methods.
Risk factors for early-onset ventilator-associated pneumonia in aneurysmal subarachnoid hemorrhage patients

This study aimed to investigate the risk factors related to ventilator-acquired pneumonia (VAP) in aneurysmal subarachnoid hemorrhage (SAH) patients. From January 2011 to December 2015, a single-center retrospective study including 200 SAH patients requiring mechanical ventilation (MV) ≥48 h was performed. The clinical data of these patients were collected and analyzed. The age range of the patients were 41–63 and 72 (36%) were male. The Glasgow coma scale score range was 5–15 and the Simplified Acute Physiology Score II range was 31–52. One hundred and forty-eight (74%) patients had a World Federation of Neurosurgeons (WNFS) score ≥III. Aneurysm was secured with an endovascular coiling procedure in 168 (84%) patients and 94 (47%) patients presented VAP. Male gender (OR=2.25, 95%CI=1.15–4.45), use of mannitol (OR=3.02, 95%CI=1.53–5.94) and enteral feeding above 20 kcal·kg−1·day−1 (OR=2.90, 95%CI=1.26–6.67) after day 7 were independent factors for VAP. Patients with early-onset VAP had a longer duration of sedation (P=0.03), MV (P=0.001) and ICU length of stay (P=0.003) and a worse Glasgow Outcome Scale score (P<0.001), but did not have a higher death rate.
Benchmarking of CNNs for Low-Cost , Low-Power Robotics Applications

This article presents the first known benchmark of Convolutional Neural Networks (CNN) with a focus on inference time and power consumption. This benchmark is important for low-cost and low-power robots running on batteries where it is required to obtain good performance at the minimal power consumption. The CNN are benchmarked either on a Raspberry Pi, Intel Joule 570X or on a USB Neural Compute Stick (NCS) based on the Movidius MA2450 Vision Processing Unit (VPU). Inference performance is evaluated for TensorFlow and Caffe running either natively on Raspberry Pi or Intel Joule and compared against hardware acceleration obtained by using the NCS. The use of the NCS demonstrates up to 4x faster inference time for some of the networks while keeping a reduced power consumption. For robotics applications this translates into lower latency and smoother control of a robot with longer battery life and corresponding autonomy. As an application example, a low-cost robot is used to follow a target based on the inference obtained from a CNN.
Reaction-diffusion processes and metapopulation models on duplex networks

Reaction-diffusion processes, used to model various spatially distributed dynamics such as epidemics, have been studied mostly on regular lattices or complex networks with simplex links that are identical and invariant in transferring different kinds of particles. However, in many self-organized systems, different particles may have their own private channels to keep their purities. Such division of links often significantly influences the underlying reaction-diffusion dynamics and thus needs to be carefully investigated. This article studies a special reaction-diffusion process, named susceptible-infected-susceptible (SIS) dynamics, given by the reaction steps $\ensuremath{\beta}\ensuremath{\rightarrow}\ensuremath{\alpha}$ and $\ensuremath{\alpha}+\ensuremath{\beta}\ensuremath{\rightarrow}2\ensuremath{\beta}$, on duplex networks where links are classified into two groups: $\ensuremath{\alpha}$ and $\ensuremath{\beta}$ links used to transfer $\ensuremath{\alpha}$ and $\ensuremath{\beta}$ particles, which, along with the corresponding nodes, consist of an $\ensuremath{\alpha}$ subnetwork and a $\ensuremath{\beta}$ subnetwork, respectively. It is found that the critical point of particle density to sustain reaction activity is independent of the network topology if there is no correlation between the degree sequences of the two subnetworks, and this critical value is suppressed or extended if the two degree sequences are positively or negatively correlated, respectively. Based on the obtained results, it is predicted that epidemic spreading may be promoted on positive correlated traffic networks but may be suppressed on networks with modules composed of different types of diffusion links.