Miracle-dz/UniFAR-FTUs huggingface dataset:
Gastrointestinal Stromal Tumors: A Clinicopathological and Immunohistochemical Study of 65 Cases.

OBJECTIVE The clinical behavior of gastrointestinal stromal tumors is divergent. The aim of the present study was to define the clinicopathological features that determine the patient's outcome. MATERIAL AND METHOD Sixty-five gastrointestinal stromal tumors were reviewed with their histological, immunohistochemical and clinical features and compared with their clinical outcome statistically. RESULTS Tumors were located in the stomach (n=39, 60%), small intestine (n=22, 33.8%) and large intestine (n=4, 6.2%). Immunohistochemically, CD 117 positivity was found in 90.8%, whereas CD34, Smooth muscle actin, Desmin and S100 positivity was found in 73.3%, 61.7%, 11.7% and 28.3% of tumors respectively. All six ''CD 117-negative'' cases expressed DOG-1. The mean Ki-67 proliferation index was 8.69%±12.76. Liver metastasis was detected in seven cases. A significant association was detected between decreased mean survival time and increased tumor size (p < 0.001), large bowel localization (p=0.047), mitosis (p < 0.001), the presence of necrosis (p=0.001), metastasis (p=0.033), Ki-67 proliferation index (p=0.002) and risk category (p < 0.001). CD 34 positivity was mostly seen in the stomach (p=0.001), and CD 34 positive tumors had longer overall survival (92.85.±5.77 months versus 67.21±13.68 months) (p=0.046). Higher Ki-67 proliferation index (≥6%) was also correlated with the presence of metastases (p=0.015). CONCLUSION Our study indicates that in addition to well-known risk factors such as increased tumor size, high mitotic activity and metastasis; higher Ki-67 proliferation index, the presence of necrosis, and CD34 negativity also correlate with shorter survival time.
Cranial index in a modern people of Thai ancestry

The present research aims to examine the cranial index in a modern people of Thai ancestry. Ultimately, this study will help to create a databank containing a cranial index for the classifications of the people from Asia. In this study, 185 modern crania of people of supposed Thai ancestry were examined. They were collected from the Department of Anatomy at Chulalongkorn University in Bangkok, Thailand. The maximum cranial length and breadth were measured using standard anthropometric instruments based on Martin's methods. The cranial index was calculated using the equation ([maximum cranial breadth/maximum cranial length]×100). The mean cranial indices for the male and female skulls examined were 81.81±4.23 and 82.99±4.37, respectively. The most common type of skull in the modern Thai people in this study was the brachycranic type with a frequency of 42.7%, followed by the mesocranic (27.03%) and hyperbrachycranic types (25.59%). The rarest type observed in this study was the dolichocranic type (4.32%). The present study provides valuable data pertaining to the cranial index in a modern Thai population and reveals that modern Thai males and females belong to the brachycranic group. The results of this study will be of forensic anthropological importance to populations in close proximity to the location where the skulls studied here were sourced.
Cortico-Amygdala-Striatal Activation by Modafinil/Flecainide Combination

Abstract Background Modafinil, a nonamphetaminic wake-promoting compound, is prescribed as first line therapy in narcolepsy, an invalidating disorder characterized by excessive daytime sleepiness and cataplexy. Although its mode of action remains incompletely known, recent studies indicated that modafinil modulates astroglial connexin-based gap junctional communication as administration of a low dose of flecainide, an astroglial connexin inhibitor, enhanced the wake-promoting and procognitive activity of modafinil in rodents and healthy volunteers. The aim of this study is to investigate changes in glucose cerebral metabolism in rodents, induced by the combination of modafinil+flecainide low dose (called THN102). Methods The impact of THN102 on brain glucose metabolism was noninvasively investigated using 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography imaging in Sprague-Dawley male rats. Animals were injected with vehicle, flecainide, modafinil, or THN102 and further injected with 18F-2-fluoro-2-deoxy-D-glucose followed by 60-minute Positron Emission Tomography acquisition. 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography images were coregistered to a rat brain template and normalized from the total brain Positron Emission Tomography signal. Voxel-to-voxel analysis was performed using SPM8 software. Comparison of brain glucose metabolism between groups was then performed. Results THN102 significantly increased regional brain glucose metabolism as it resulted in large clusters of 18F-2-fluoro-2-deoxy-D-glucose uptake localized in the cortex, striatum, and amygdala compared with control or drugs administered alone. These regions, highly involved in the regulation of sleep-wake cycle, emotions, and cognitive functions were hence quantitatively modulated by THN102. Conclusion Data presented here provide the first evidence of a regional brain activation induced by THN102, currently being tested in a phase II clinical trial in narcoleptic patients.
Vertical Silicon Nanowires Based Directional Coupler Optical Router

A fully complementary metal-oxide-semiconductor compatible optical router is demonstrated. The router structure is built using the silicon-organic hybrid platform, while its mechanism is based on the directional coupler operation. The directional coupler waveguides are formed by the arrays of silicon nanowires, while the cladding and voids between the silicon nanowires are filled with an electro-optic polymer. Routing of the optical signal is demonstrated through the change of the coupling length of the directional coupler upon voltage application. The router is characterized by the short length directional coupler of <inline-formula> <tex-math notation="LaTeX">$24~\mu \text{m}$ </tex-math></inline-formula>, and total footprint of <inline-formula> <tex-math notation="LaTeX">$62~\mu \text{m}^{2}$ </tex-math></inline-formula>, high extinction ratio which reaches 33 dB and low insertion losses of 1.3 dB.
Autophagy Modulation in Cancer: Current Knowledge on Action and Therapy

In the last two decades, accumulating evidence pointed to the importance of autophagy in various human diseases. As an essential evolutionary catabolic process of cytoplasmatic component digestion, it is generally believed that modulating autophagic activity, through targeting specific regulatory actors in the core autophagy machinery, may impact disease processes. Both autophagy upregulation and downregulation have been found in cancers, suggesting its dual oncogenic and tumor suppressor properties during malignant transformation. Identification of the key autophagy targets is essential for the development of new therapeutic agents. Despite this great potential, no therapies are currently available that specifically focus on autophagy modulation. Although drugs like rapamycin, chloroquine, hydroxychloroquine, and others act as autophagy modulators, they were not originally developed for this purpose. Thus, autophagy may represent a new and promising pharmacologic target for future drug development and therapeutic applications in human diseases. Here, we summarize our current knowledge in regard to the interplay between autophagy and malignancy in the most significant tumor types: pancreatic, breast, hepatocellular, colorectal, and lung cancer, which have been studied in respect to autophagy manipulation as a promising therapeutic strategy. Finally, we present an overview of the most recent advances in therapeutic strategies involving autophagy modulators in cancer.
Effects of taste stimulation on gastric myoelectrical activity and autonomic balance

Background/Aim: Sham feeding, reproducing the cephalic phase of digestion, and involving combined visual, olfactory, and taste stimulation affects gastrointestinal motility and secretory functions of the digestive system, as well as the sympathetic/parasympathetic balance (SPB). In this study, we aimed to check if taste stimulation with a single flavor affects the gastric myoelectrical activity (GMA) and/or SPB. Materials and Methods: Eighteen healthy volunteers underwent, on four separate days, 30-min electrogastrographic and electrocardiographic recordings: basal, with stimulation – while keeping in the mouth an agar cube with taste-delivering substance, and postexposure. Concentrations of saccharose, NaCl, citric acid, and quinine hydrochloride within the cubes were adjusted to 100-fold the individual taste recognition thresholds. SPB was determined from the heart rate variability (HRV) analysis of the recorded electrocardiograms. Results: A moderate but statistically significant increase in tachygastria and bradygastria percentage time share was observed, regardless of the type of taste applied. Bitter taste elicited a considerable decrease in the normogastria time share (from 82.8 ± 2.5% to 73.5 ± 3.5%, P = 0.00076) and a diminution of the dominant frequency (from 3.07 ± 0.08 to 2.90 ± 0.10 cycles per minute (cpm) postexposure, P = 0.01). Sour taste brought about a drop of the dominant power (from 42.5 ± 1.1 to 40.1 ± 1.4 dB, P = 0.0015). Two tastes hindered propagation of the gastric slow waves – the average percentage of slow wave coupling decreased from 77.9 ± 3.1% to 69.5 ± 3.1% (P = 0.0078) and from 74.6 ± 2.5% to 68.2 ± 2.8% (P = 0.0054) with the bitter and the salty taste, respectively. Stimulation with sweet, salty, or sour taste evoked a significant decrease in the high frequency component of the HRV, whereas bitter taste did not affect the SPB. Conclusions: Oral stimulation with tastes subjectively perceived as unpleasant brings about disturbances of the interdigestive GMA. This, however, does not coincide with its effect upon SPB.
Visual Semantic Enrichment for eReading

The current transition from physical to electronic books opens up opportunities to present semantic information about a book’s content. This paper reports on a project that aims to improve the eBook reading experience by presenting semantic information about the eBook content together with the text. Research challenges included suitable semantic information to be presented alongside a text and manners to display semantic information in an eReader application to supplement the text. We developed a web-based prototype that incorporates analysis of semantic content elements and explored the effectiveness of these in a user study with 30 participants. Our results indicate that dynamic semantic visualisations may assist comprehension of existing concepts within an eBook, and provide insight to information that could not be easily gleaned by simply reading the text. eReading. eBooks. Semantic content. Semantic Visualisations.
EMG-Torque Dynamics Change With Contraction Bandwidth

An accurate model for ElectroMyoGram (EMG)-torque dynamics has many uses. One of its applications which has gained high attention among researchers is its use, in estimating the muscle contraction level for the efficient control of prosthesis. In this paper, the dynamic relationship between the surface EMG and torque during isometric contractions at the human ankle was studied using system identification techniques. Subjects voluntarily modulated their ankle torque in dorsiflexion direction, by activating their tibialis anterior muscle, while tracking a pseudo-random binary sequence in a torque matching task. The effects of contraction bandwidth, described by torque spectrum, on EMG-torque dynamics were evaluated by varying the visual command switching time. Nonparametric impulse response functions (IRF) were estimated between the processed surface EMG and torque. It was demonstrated that: 1) at low contraction bandwidths, the identified IRFs had unphysiological anticipatory (i.e., non-causal) components, whose amplitude decreased as the contraction bandwidth increased. We hypothesized that this non-causal behavior arose, because the EMG input contained a component due to feedback from the output torque, i.e., it was recorded from within a closed-loop. Vision was not the feedback source since the non-causal behavior persisted when visual feedback was removed. Repeating the identification using a nonparametric closed-loop identification algorithm yielded causal IRFs at all bandwidths, supporting this hypothesis. 2) EMG-torque dynamics became faster and the bandwidth of system increased as contraction modulation rate increased. Thus, accurate prediction of torque from EMG signals must take into account the contraction bandwidth sensitivity of this system.
The Effects of Psychological Intervention on Atopic Dermatitis

Background: Psychological interventions may be valuable in atopic dermatitis. We systematically reviewed and carried out a meta-analysis of randomized controlled trials of psychological interventions. Methods: Electronic searches and manual journal searches were carried out. Two coders independently coded study designs, participants, treatments and outcome characteristics of the studies meeting the selection criteria. Results: Eight journal articles published between 1986 and 2006 were included. Eight types of intervention were tested: aromatherapy, autogenic training, brief dynamic psychotherapy, cognitive-behavioral therapy, dermatological education and cognitive-behavioral therapy, habit reversal behavioral therapy, a stress management program, and structured educational programs. Effect sizes were computed as correlation coefficient (r), and random effects models were used in the analysis. For eczema severity, the average effect size for the 8 trials including 8 interventions was –0.367 [χ2(1) = 7.452, p = 0.006; 95% CI –0.579 to –0.108]. The average effect sizes on itching intensity (5 trials with 5 interventions) and scratching (5 trials with 4 interventions) were –0.805 [χ2(1) = 4.719, p = 0.030; 95% CI –0.971 to –0.108] and –0.620 [χ2(1) = 24.24, p < 0.0001; 95% CI –0.767 to –0.410], respectively. Conclusions: Although the present meta-analysis revealed that psychological interventions had a significant ameliorating effect on eczema severity, itching intensity and scratching in atopic dermatitis patients, a definite conclusion about their effectiveness seems premature. Accordingly, future studies should involve more sophisticated methodologies, use established measures of outcome variables, adjust for possible confounders between the intervention and control groups, and provide sufficient data to calculate the effect sizes for future meta-analyses.
A Multi-Modal Person Recognition System for Social Robots

The paper presents a solution to the problem of person recognition by social robots via a novel brain-inspired multi-modal perceptual system. The system employs spiking neural network to integrate face, body features, and voice data to recognize a person in various social human-robot interaction scenarios. We suggest that, by and large, most reported multi-biometric person recognition algorithms require active participation by the subject and as such are not appropriate for social human-robot interactions. However, the proposed algorithm relaxes this constraint. As there are no public datasets for multimodal systems, we designed a hybrid dataset by integration of the ubiquitous FERET, RGB-D, and TIDIGITS datasets for face recognition, person recognition, and speaker recognition, respectively. The combined dataset facilitates association of facial features, body shape, and speech signature for multimodal person recognition in social settings. This multimodal dataset is employed for testing the algorithm. We assess the performance of the algorithm and discuss its merits against related methods. Within the context of the social robotics, the results suggest the superiority of the proposed method over other reported person recognition algorithms.
Fast hardware protection for a series-series compensated inductive power transfer system for electric vehicles

The paper proposes a simple solution to a safety problem encountered during the development of a series-series compensated IPT system for electric vehicles. This problem is related to the equivalent current source behavior of the receiver side in presence of an unpredicted load disconnection. A pure analog hardware system able to manage this fault protecting the filtering elements of the system is proposed. The system is investigated by means of a circuit simulation then its physical implementation is presented. The effectiveness of the proposed solution is experimentally proven.
WLC17-5: Improving Mobile Station Energy Efficiency in IEEE 802.16e WMAN by Burst Scheduling

In this paper, we tackle the packet scheduling problem in IEEE 802.16e wireless metropolitan area network (WMAN), where the Sleep Mode is applied to save energy of mobile stations (MSs). Our objective is to design an energy efficient scheduling policy which works closely with the sleep mode mechanism so as to maximize battery lifetime in MSs. To the best of our knowledge no power saving scheduling algorithms based on sleep mode defined in IEEE 802.16e have been proposed so far in the literature. We propose a longest virtual burst first (LVBF) scheduling algorithm which schedules packets of MSs in a virtual burst mode where there is one primary MS and multiple secondary MSs sharing the wireless link resource. LVBF prolongs MSs' lifetime by reducing the average time when MSs stay in the idle state and the number of state transitions between the awake and sleep states. Simulation results show that, in comparison with the round robin scheduling scheme, LVBF can produce significant overall energy saving, while guaranteeing the QoS requirements of MSs in terms of their minimum data rates.
The International Journal of Biostatistics The Relative Performance of Targeted Maximum Likelihood Estimators

There is an active debate in the literature on censored data about the relative performance of model based maximum likelihood estimators, IPCW-estimators, and a variety of double robust semiparametric efficient estimators. Kang and Schafer (2007) demonstrate the fragility of double robust and IPCW-estimators in a simulation study with positivity violations. They focus on a simple missing data problem with covariates where one desires to estimate the mean of an outcome that is subject to missingness. Responses by Robins, et al. (2007), Tsiatis and Davidian (2007), Tan (2007) and Ridgeway and McCaffrey (2007) further explore the challenges faced by double robust estimators and offer suggestions for improving their stability. In this article, we join the debate by presenting targeted maximum likelihood estimators (TMLEs). We demonstrate that TMLEs that guarantee that the parametric submodel employed by the TMLE procedure respects the global bounds on the continuous outcomes, are especially suitable for dealing with positivity violations because in addition to being double robust and semiparametric efficient, they are substitution estimators. We demonstrate the practical performance of TMLEs relative to other estimators in the simulations designed by Kang and Schafer (2007) and in modified simulations with even greater estimation challenges.
Protease-Activated Receptor 1 Contributes to Angiotensin II-Induced Cardiovascular Remodeling and Inflammation

Background: Angiotensin II (Ang II) plays an important role in cardiovascular disease. It also leads to the activation of coagulation. The coagulation protease thrombin induces cellular responses by activating protease-activated receptor 1 (PAR-1). We investigated whether PAR-1 contributes to Ang II-induced cardiovascular remodeling and inflammation. Methods and Results: PAR-1+/+ (wild-type; WT) and PAR-1-/- mice were infused with Ang II (600 ng/kg/min) for up to 4 weeks. In WT mice, this dose of Ang II did not cause a significant increase in blood pressure but it did cause pathological changes in both the aorta and the heart. Ang II infusion resulted in vascular remodeling of the aorta, demonstrated by a significant increase in medial wall thickening and perivascular fibrosis. Importantly, both parameters were significantly attenuated by PAR-1 deficiency. Furthermore, perivascular fibrosis around coronary vessels was reduced in Ang II-treated PAR-1-/- mice compared to WT mice. In addition, PAR-1 deficiency significantly attenuated Ang II induction of inflammatory cytokines and profibrotic genes in the aortas compared to WT mice. Finally, PAR-1 deficiency had no effect on Ang II-induced heart hypertrophy. However, the heart function measured by fractional shortening was less impaired in PAR-1-/- mice than in WT mice. Conclusion: Our data indicate that PAR-1 plays a significant role in cardiovascular remodeling mediated by a blood pressure-independent action of Ang II.
Evolving Attacker Perspectives for Secure Embedded System Design

In our increasingly connected world, security is a growing concern for embedded systems. A systematic design and verification methodology could help detect vulnerabilities before mass production. While Attack Trees help a designer consider the attacks a system will face during a preliminary analysis phase, they can be further integrated into the design phases. We demonstrate that explicitly modeling attacker actions within a system model helps us to evaluate its impact and possible countermeasures. This paper describes how we evolved the SysML-Sec Methodology with ``Attacker Scenarios'' for the improved design of secure embedded systems.
Face Anti-spoofing based on Deep Stack Generalization Networks

Thanks for the recent development of Convolutional Neural Networks (CNNs), the performance of face anti-spoofing methods has been improved by extracting more distinguishing features between genuine and fake faces than the hand-crafted texture features. As known, the way of fraud is diverse, thus the fake class has large intra-class variations, so training as a binary classification problem is hard to learn the distinguishing features. In this work, our contribution is a novel model fusion approach for face antispoofing, which can reduce the intra-class variations. According to the type of fraud, we firstly train different models for face anti-spoofing problem by CNN, thus the intra-class variations of fake class has reduced during training each model. Distinguishing features can be learned more easily. Then the stacked generalized method is used for combining the lower models to achieve better predictive accuracy. For perfecting the generalized accuracy, the stacked generalized approach changes the weight of each model's prediction, so that the model after fusion can predict precisely whether the face image is fake or genuine. Meanwhile, the experimental results indicate our method can obtain excellent results compared to the state-