Miracle-dz/UniFAR-FTUs huggingface dataset:
Regional Brain Activity During Rest and Gastric Water Load in Subtypes of Functional Dyspepsia: A Preliminary Brain Functional Magnetic Resonance Imaging Study

Background/Aims Functional dyspepsia (FD) remains a great clinical challenge since the FD subtypes, defined by Rome III classification, still have heterogeneous pathogenesis. Previous studies have shown notable differences in visceral sensation processing in the CNS in FD compared to healthy subjects (HS). However, the role of CNS in the pathogenesis of each FD subtype has not been recognized. Methods Twenty-eight FD patients, including 10 epigastric pain syndrome (EPS), 9 postprandial distress syndrome (PDS), and 9 mixed-type, and 10 HS, were enrolled. All subjects underwent a proximal gastric perfusion water load test and the regional brain activities during resting state and water load test were investigated by functional magnetic resonance imaging. Results For regional brain activities during the resting state and water load test, each FD subtype was significantly different from HS (P < 0.05). Focusing on EPS and PDS, the regional brain activities of EPS were stronger than PDS in the left paracentral lobule, right inferior frontal gyrus pars opercularis, postcentral gyrus, precuneus, insula, parahippocampal gyrus, caudate nucleus, and bilateral cingulate cortices at the resting state (P < 0.05), and stronger than PDS in the left inferior temporal and fusiform gyri during the water load test (P < 0.05). Conclusions Compared to HS, FD subtypes had different regional brain activities at rest and during water load test, whereby the differences displayed distinct manifestations for each subtype. Compared to PDS, EPS presented more significant differences from HS at rest, suggesting that the abnormality of central visceral pain processing could be one of the main pathogenesis mechanisms for EPS.
Development of a novel observational measure for anxiety in young children: The Anxiety Dimensional Observation Scale.

BACKGROUND Identifying anxiety disorders in preschool-age children represents an important clinical challenge. Observation is essential to clinical assessment and can help differentiate normative variation from clinically significant anxiety. Yet, most anxiety assessment methods for young children rely on parent-reports. The goal of this article is to present and preliminarily test the reliability and validity of a novel observational paradigm for assessing a range of fearful and anxious behaviors in young children, the Anxiety Dimensional Observation Schedule (Anx-DOS). METHODS A diverse sample of 403 children, aged 3 to 6 years, and their mothers was studied. Reliability and validity in relation to parent reports (Preschool Age Psychiatric Assessment) and known risk factors, including indicators of behavioral inhibition (latency to touch novel objects) and attention bias to threat (in the dot-probe task) were investigated. RESULTS The Anx-DOS demonstrated good inter-rater reliability and internal consistency. Evidence for convergent validity was demonstrated relative to mother-reported separation anxiety, social anxiety, phobic avoidance, trauma symptoms, and past service use. Finally, fearfulness was associated with observed latency and attention bias toward threat. CONCLUSIONS Findings support the Anx-DOS as a method for capturing early manifestations of fearfulness and anxiety in young children. Multimethod assessments incorporating standardized methods for assessing discrete, observable manifestations of anxiety may be beneficial for early identification and clinical intervention efforts.
Optimal power and rate allocation in buffer-aided NOMA relay networks

This paper studies the best-effort transmission policy that maximizes the sum rate by the joint power and rate allocation in the buffer-aided NOMA relay network. In particular, we first provide the sum-rate maximization formulation under the constraints of maximum transmit power and buffer size. We then derive a closed-form expression of optimal power and rate allocation that solves this optimization problem. Based on the derived closed-form expression, we further obtain the lower bound of the probability of using NOMA when adopting the best-effort transmission policy.
Shape and internal structure of silver nanoparticles embedded in glass

The structural characteristics of silver nanoparticles embedded in glass by various routes of fabrication were studied in detail using high-resolution electron microscopy to find out if they are influenced by interaction with the surrounding glass matrix. Besides the formation conditions, the strength of the interaction between metal and glass governs the size-dependent changes of lattice spacings in such nanoparticles. However, determination of these changes is not straightforward because of complicated particle configurations and the interference nature of the lattice imaging technique. Imaging of lattice plane fringes and careful diffractogram analysis allowed the exclusion of any kind of tetragonal lattice distortion or transformation to hexagonal lattice type that may be deduced at first sight. Instead, the formation of twin faults in these nanoparticles turned out to be the essential structural feature and the main source of confusion about the lattice structure observed. The variety of particle forms is comparable to particles supported on oxide carriers. It is composed of single-crystalline particles of nearly cuboctahedron shape, particles containing single twin faults, multiple twinned particles containing parallel twin lamellae, and multiple twinned particles composed of cyclic twinned segments arranged around axes of 5-fold symmetry. The more twin planes involved in the particle composition, the more complicated is the interpretation of lattice spacings and lattice fringe patterns due to superposition of several twin segments.
The UMD Neural Machine Translation Systems at WMT17 Bandit Learning Task

We describe the University of Maryland machine translation systems submitted to the WMT17 German-English Bandit Learning Task. The task is to adapt a translation system to a new domain, using only bandit feedback: the system receives a German sentence to translate, produces an English sentence, and only gets a scalar score as feedback. Targeting these two challenges (adaptation and bandit learning), we built a standard neural machine translation system and extended it in two ways: (1) robust reinforcement learning techniques to learn effectively from the bandit feedback, and (2) domain adaptation using data selection from a large corpus of parallel data.
Randomization of Statistical Queries of Type Median: A Simulation Approach

Researcher and third party access to data pertaining to individuals is becoming the norm. The conclusions drawn from such data can be extremely beneficial. However, data owners must maintain the secrecy of the sensitive data fields and make sure it is protected against inference attacks. There are several techniques and restrictions that can be made on queries to prevent adversaries from inferring and identifying sensitive data related to specific individuals. One of the proposed techniques to prevent the disclosure of private data is randomization. In this study, we demonstrate and analyze the implementation of randomization in statistical queries of the selector function median and the results of an extensive simulation. The randomization technique yields a possibly erroneous yet usually reasonably accurate response to every query. In addition, the inference procedure is explained and potential modifications to counter the randomization technique are analyzed and tested against it. We show that, despite these modifications, randomization protects the data by adding uncertainties into the inference procedure, thus, maintaining differential privacy. The results of an extensive simulation testing the various parameters of the randomization technique on randomly generated databases are shown and explained.
Model‐based shape from shading for microelectronics applications

Model‐based shape from shading (SFS) is a promising paradigm introduced by Atick et al. [Neural Comput 8 (1996), 1321–1340] in 1996 for solving inverse problems when we happen to have a lot of prior information on the depth profiles to be recovered. In the present work we adopt this approach to address the problem of recovering wafer profiles from images taken using a scanning electron microscope (SEM). This problem arises naturally in the microelectronics inspection industry. A low‐dimensional model, based on our prior knowledge on the types of depth profiles of wafer surfaces, has been developed, and based on it the SFS problem becomes an optimal parameter estimation. Wavelet techniques were then employed to calculate a good initial guess to be used in a minimization process that yields the desired profile parametrization. A Levenberg–Marguardt (LM) optimization procedure has been adopted to address ill‐posedness of the SFS problem and to ensure stable numerical convergence. The proposed algorithm has been tested on synthetic images, using both Lambertian and SEM imaging models. © 2006 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 16, 65–76, 2006
Mobile Shopping Consumers' Behavior: An Exploratory Study and Review

Mobile Technology is creating a range of tremendous opportunities and new revenue streams for businesses across industry sectors through the delivery of chargeable mobile products and services via the deployment of innovative value-added solutions that exploit the commercial benefits of mobility. To keep up with the pace of change, companies increasingly want to understand the behavioral attitude of the modern mobile consumer. The aim of this paper is to find out users' reaction towards different parameters that would influence their intention to utilize their mobile devices in order to purchase products and services online focusing on the current Greek reality. The extant literature focuses on understanding the factors that might affect consumers' behavior intention to adopt m-shopping; these studies are mostly based on behavioral intention theories, such as Technology Acceptance Model, Diffusion of Innovation and Unified Theory of Acceptance and Use of Technology. In this study, new theoretical constructs are combined with existing evidence in order to extend the Technology Acceptance Model as it was initially established by Davis and later further enriched by other researchers. The proposed model includes behavioral intention, mobile skillfulness, enjoyment, anxiety, perceived usefulness, perceived ease of use, trust, relationship drivers, and innovativeness.
Linkage of Infection to Adverse Systemic Complications: Periodontal Disease, Toll-Like Receptors, and Other Pattern Recognition Systems

Toll-like receptors (TLRs) are a group of pattern recognition receptors (PRRs) that provide innate immune sensing of conserved pathogen-associated molecular patterns (PAMPs) to engage early immune recognition of bacteria, viruses, and protozoa. Furthermore, TLRs provide a conduit for initiation of non-infectious inflammation following the sensing of danger-associated molecular patterns (DAMPs) generated as a consequence of cellular injury. Due to their essential role as DAMP and PAMP sensors, TLR signaling also contributes importantly to several systemic diseases including cardiovascular disease, diabetes, and others. The overlapping participation of TLRs in the control of infection, and pathogenesis of systemic diseases, has served as a starting point for research delving into the poorly defined area of infection leading to increased risk of various systemic diseases. Although conflicting studies exist, cardiovascular disease, diabetes, cancer, rheumatoid arthritis, and obesity/metabolic dysfunction have been associated with differing degrees of strength to infectious diseases. Here we will discuss elements of these connections focusing on the contributions of TLR signaling as a consequence of bacterial exposure in the context of the oral infections leading to periodontal disease, and associations with metabolic diseases including atherosclerosis and type 2 diabetes.
Hematopoietic cells as site of first-pass catabolism after subcutaneous dosing and contributors to systemic clearance of a monoclonal antibody in mice

ABSTRACT The neonatal Fc receptor (FcRn) has been demonstrated to contribute to a high bioavailability of monoclonal antibodies (mAbs). In this study, we explored the cellular sites of FcRn-mediated protection after subcutaneous (SC) and intravenous (IV) administration. SC absorption and IV disposition kinetics of a mAb were studied in hFcRn transgenic (Tg) bone marrow chimeric mice in which hFcRn was restricted to radioresistant cells or hematopoietic cells. SC bioavailabilities close to 90% were observed in hFcRn Tg mice and chimeric mice with hFcRn expression in hematopoietic cells, whereas SC bioavailabilities were markedly lower when FcRn was missing in hematopoietic cells. Our study demonstrates: 1) FcRn in radiosensitive hematopoietic cells is required for high SC bioavailability, indicating first-pass catabolism after SC administration by hematopoietic cells; 2) FcRn-mediated transcytosis or recycling by radioresistent cells is not required for high SC bioavailability; and 3) after IV administration hematopoietic and radioresistent cells contribute about equally to clearance of the mAb. A pharmacokinetic model was devised to describe a mixed elimination via radioresistent and hematopoietic cells from vascular and extravascular compartments, respectively. Overall, the study indicates a relevant role of hematopoietic cells for first-pass clearance of mAbs after SC administration and confirms their role in the overall clearance of mAbs.
Fabrication and Photocatalytic Properties of MgFe2O4/rGO/V2O5 Heterostructure Nanowires

Development of green clean energy has become one of promising challenge recently. One popular application of solar energy is photocatalysis, where semiconductors were used as photocatalyst to convert solar light into photoelectrons/holes. Photocatalysis technology has been widely applied for water splitting and degradation. Tetracycline (TC) is a sort of popular anthropogenic emissions in wasted water, which will caused seriously environmental pollution. A novel MgFe2O4/GO/V2O5 heterostructure has been successfully prepared by electrospinning method and high temperature chemical vapor deposition. The structure of samples was systematically characterized by XRD patterns and SEM images. The morphology of MgFe2O4 and MgFe2O4/GO/V2O5 was both uniform one-dimensional nanowires. The degradation ratios of TC by MgFe2O4 and MgFe2O4/rGO/V2O5 were 18% and 40%, respectively. The enhanced photocatalytic property of MgFe2O4/GO/V2O5 indicated that the GO and V2O5 played an important role in the separation of photogenerated holes and electrons. Therefore, MgFe2O4/rGO/V2O5 can be used efficient photocatalyst for sewage treatment in environment. Keywords-heterostructure; MgFe2O4/rGO/V2O5; electrospinning; nanowires; photocatalytic property;
Discriminant Analysis by Locally Linear Transformations

We present a novel discriminant analysis learning method which is applicable to non-linear data structures. The method can deal with pattern classification problems which have a multi-modal distribution for each class and samples of other classes may be closer to a class than those of the class itself. Conventional linear discriminant analysis (LDA) and LDA mixture model can not solve this linearly non-separable problem. Several local linear transformations are considered to yield locally transformed classes that maximize the between-class covariance and minimize the within-class covariance. The method invloves a novel gradient based algorithm for finding the optimal set of local linear bases. It does not have a local-maxima problem and stably converges to the global maximum point. The method is computationally efficienct as compared to the previous non-linear discriminant analysis based on the kernel approach. The method does not suffer from an overfitting problem by virtue of the linear base structure of the solution. The classification results are given for both simulated data and real face data.
Keratocyte Apoptosis After Corneal Collagen Cross-linking Using Riboflavin/UVA Treatment

Purpose Combined riboflavin/UVA treatment inducing collagen cross-links in the cornea has been shown to increase the biomechanical rigidity of the cornea and has been used successfully in the treatment of progressive keratoconus. The current study was undertaken to investigate the possible cytotoxic effect of combined riboflavin/UVA treatment on corneal keratocytes in vivo. Methods Thirty-four New Zealand white rabbits were treated with 0.1% riboflavin solution and surface UVA irradiances ranging from 0.75 to 4 mW/cm2 (1.35– 7.2 J/cm2) for 30 minutes. The animals were euthanized either 4 (n = 6) or 24 (n = 28) hours postoperatively. Four additional control eyes underwent epithelial debridement alone. The corneas of the enucleated eyes were evaluated in routine histologic sections. In addition, the TUNEL technique and transmission electron microscopy were used for the detection of keratocyte apoptosis. Results In the control eyes with corneal epithelial debridement only, apoptotic keratocytes were found in the anterior 50 &mgr;m of the corneal stroma 4 hours postoperatively. However, riboflavin/UVA-induced apoptosis was only visible in the rabbit eyes enucleated 24 hours postoperatively. In these eyes, we found apoptosis of keratocytes down to a variable stromal depth depending on the applied UVA irradiance. A cytotoxic UVA irradiance for keratocytes in the range of 0.5–0.7 mW/cm2 could be deduced. Conclusions Riboflavin/UVA treatment leads to a dose-dependent keratocyte damage that can be expected in human corneas down to a depth of 300 &mgr;m using a surface UVA dose of 5.4 J/cm2. Future studies should be done to examine the keratocyte repopulation and exclude possible adverse sequelae of keratocyte loss like stromal scarring or thinning.
Group music therapy for patients with persistent post-traumatic stress disorder--an exploratory randomized controlled trial with mixed methods evaluation.

OBJECTIVES Not all patients with post-traumatic stress disorder (PTSD) respond to cognitive behavioural therapy (CBT). Literature suggests group music therapy might be beneficial in treating PTSD. However, feasibility and effectiveness have not been assessed. The study objectives were to assess whether group music therapy was feasible for patients who did not respond to CBT, and whether it has an effect on PTSD symptoms and depression. DESIGN The study employed mixed methods comprising of an exploratory randomized controlled trial, qualitative content analysis of therapy, and patient interviews. METHOD Patients with significant PTSD symptoms (n = 17) following completion of CBT were randomly assigned to treatment (n = 9) or control groups (n = 8). The treatment group received 10 weeks of group music therapy after which exit interviews were conducted. Control group patients were offered the intervention at the end of the study. Symptoms were assessed on the Impact of Events Scale-Revised and Beck Depression Inventory II at the beginning and end of treatment. RESULTS Treatment-group patients experienced a significant reduction in severity of PTSD symptoms (-20.18; 95% confidence interval [CI]: [-31.23, -9.12]) and a marginally significant reduction in depression (-11.92; 95%CI: [-24.05, 0.21]) at 10 weeks from baseline compared to the control. Patients viewed music therapy as helpful and reported experiences concur with current literature. CONCLUSIONS Group music therapy appears feasible and effective for PTSD patients who have not sufficiently responded to CBT. Limitations include the small sample size and lack of blinding. Further research should address these limitations, test sustainability, and identify specific factors that address symptoms in treatment.
Music Performer Recognition Using an Ensemble of Simple Classifiers

This paper addresses the problem of identifying the most likely music performer, given a set of performances of the same piece by a number of skilled candidate pianists. We propose a set of features for representing the stylistic characteristics of a music performer. A database of piano performances of 22 pianists playing two pieces by F. Chopin is used in the presented experiments. Due to the limitations of the training set size and the characteristics of the input features we propose an ensemble of simple classifiers derived by both subsampling the training set and subsampling the input features. Preliminary experiments show that the resulting ensemble is able to efficiently cope with this difficult musical task, displaying a level of accuracy unlikely to be matched by human listeners (under similar conditions).
Biodecolorization of Textile Effluents by Autochthonous Fungi

Textile effluents contain different kinds of chemical dyes and many mutagenic and carcinogenic substances. Discharge of these effluents into terrestrial and aquatic ecosystems causes harmful effects. In this research, decolorization of a textile effluent by nineteen different strains of fungi was investigated. Removal activity of dyes was in order of Aspergillus > Rhizopus > Fuzarium > Penicillium > Saccharomyces. The selected fungal strain was capable of decolorizing textile effluent at original pH of effluent (8.5- 9) by adding 0.6 and 0.2 g/L of sucrose and NH4Cl as additional carbon and nitrogen sources respectively at 30ᵒC. 98 % of dyes were absorbed from effluent during the exponential growth phase in the presence of a biodegradable substrate such as sucrose under shake flask conditions. Dyes strongly bound to the fungal biomass required extraction with methanol for their removal. The dyes pigment yellow (PY 74) and reactive blue (RB 38) were totally decolorized after 6 days at initial concentration of 250 ppm by terrestrial Aspergillus niger.Keywords: Biodecolorization, Textile Effluent, Carcinogen, Aspergillus niger
UvA-DARE ( Digital Academic Repository ) Who times the foreign exchange market ? Corporate speculation and CEO characteristics

This paper shows that managers’ personal beliefs and individual characteristics explain a large share of the substantial time-variation of derivatives use beyond firm, industry, and market fundamentals. We construct a panel data set of foreign currency derivatives holdings and currency exposures for U.S. non-financial firms. We use a novel approach to build a firm-specific foreign exchange return. We find that managers adjust derivatives notional amounts in response to past foreign exchange returns, as if they were forming views on future currency prices. We then construct an empirical measure of speculative behavior for each firm to investigate the profile of the speculator. Firms where the CEO holds an MBA degree, is younger, and has less previous working experience speculate more. These results are consistent with overconfident managers taking more risk.
A multiplicity result for a nonlinear degenerate problem arising in the theory of electrorheological fluids

We study the boundary value problem in , u=0 on , where is a smooth bounded domain in and is a -Laplace type operator, with . We prove that if λ is large enough then there exist at least two non-negative weak solutions. Our approach relies on the variable exponent theory of generalized Lebesgue–Sobolev spaces, combined with adequate variational methods and a variant of the Mountain Pass lemma.