Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychopathology and comorbidity of psychiatric disorders in patients with kleptomania.

OBJECTIVE This study compared patients with kleptomania, patients with alcohol abuse or dependence, and psychiatric patients without impulse-control disorders or substance-related disorders on several key psychopathological dimensions. In addition, the comorbidity of kleptomania with other psychiatric disorders was examined. METHOD Eleven patients with kleptomania recruited over a cumulative 2-year period and 60 patients with alcohol abuse or dependence and 29 psychiatric comparison patients recruited over a consecutive 6-month period participated in structured clinical interviews to determine the presence of impulse-control and substance-related disorders and of other psychiatric disorders that were comorbid with kleptomania. Psychopathological dimensions were measured with the Barratt Impulsiveness Scale, the Sensation Seeking Scale, the Montgomery-Asberg Depression Rating Scale, and the anxiety and depression subscales of the Hospital Anxiety and Depression Scale. RESULTS Significant group effects were found for the Barratt Impulsiveness Scale total and cognitive impulsivity scores, with the patients with kleptomania having higher impulsivity scores than the other groups. Significant group differences were found on the Sensation Seeking Scale total and disinhibition scores. No significant group effects were found for the mood and anxiety measures. Patients with kleptomania had high rates of comorbid psychiatric disorders, particularly mood disorders, other impulse-control disorders, and substance abuse or dependence (mainly nicotine dependence). CONCLUSIONS Kleptomania presented a specific psychopathological profile that distinguished patients with this disorder from patients with alcohol abuse or dependence and other psychiatric comparison patients. Impulsivity was the major psychopathological feature of kleptomania. A link between kleptomania and affective disorder was supported by the high rate of comorbid affective disorders in patients with kleptomania and a specific pattern of variation in the two conditions over time. Further prospective studies are needed to confirm this pattern. Because kleptomania is characterized by a low rate of comorbid substance-related disorders other than nicotine dependence and by severe psychopathology, it could be an appropriate disorder in which to study the information processes and psychobiology underlying impulsivity.
Transdermal iontophoresis of insulin. Part 1: A study on the issues associated with the use of platinum electrodes on rat skin

We have studied the issues associated with the use of platinum electrodes for transdermal iontophoretic delivery of peptides, using insulin as a model peptide. Insulin permeation was studied using full‐thickness rat skin by varying the donor solution pH as a function of electrode polarity. The stability of insulin under the iontophoretic conditions was studied using TLC, SDS‐polyacrylamide gel electrophoresis and HPLC. Large pH shifts were observed during anodal iontophoresis (AI), when the donor solution pH was above the isoelectric point of insulin and in cathodal iontophoresis (CI), when the donor solution pH was below the isoelectric point of insulin. The direction and magnitude of electroosmotic flow was influenced by pH of the donor solution and the electrode polarity. On the other hand, the buffer used to maintain the pH governed the contribution of electrorepulsion to the overall transport of insulin. Electrochemical degradation of insulin was significant during Al at pH 7.4. Among the pH investigated, Al of insulin at pH 3.6 and Cl at pH 8.35 were better, as the pH shift was relatively less and electrochemically more stable during iontophoresis as compared with other pH. In summary, the pH shift caused by platinum electrodes had a significant influence on the permeation and stability of insulin.
Generating boundary values from OCL constraints using constraints rewriting and search algorithms

A key component of model-based testing is the generation of test data from constraints (e.g., specified in the Object Constraint Language (OCL)) associated with models e.g., specified in the Unified Modeling Language (UML). The quality of test data eventually determines the effectiveness of test cases, e.g., fault detection and coverage. A simple way to generate test data from an OCL constraint is to find a set of values for all the variables that satisfies the constraint. One way of improving the quality of test data is by generating test data at the boundaries of each variable in the constraint. In this paper, we extend our search-based test data generation approach to generate test data at the boundaries of each variable involved in a constraint. We present different cases of constraints involving different types of variables and how we rewrite them in order to automatically generate boundary values using our existing OCL Solver called EsOCL based on a set of heuristics. We empirically evaluated our heuristics using three search algorithms, i.e., Genetic Algorithm, (1+1) Evolutionary Algorithm, and Alternating Variable Method, on industrial OCL constraints from our previous work. Results show that AVM on average achieved a 95% of success rate and outperformed the rest of the algorithms in finding all the boundary values of constraints in fewer generations.
A patient safety focused registered nurse transition to practice program

Abstract New graduate registered nurses (NGRN’s) have an expectation of clinical support as they make the transition from novice to advanced beginner. In this 2008–2009 study of three rural transition to practice programs we found that clinical support did not eventuate. Consequently, NGRN’s reported feeling underprepared for practice, overwhelmed by responsibility and often abandoned. Against this background, many were concerned that their inexperience had implications for safe patient care. Graduate nurse transition programs need to have the physical and human resources necessary to deliver the clinical support as promised in their prospectus, to ensure patient safety. This grounded theory study identified three essential core elements – leadership support, clinical supervision, and effective interprofessional relationships. Recommendation is made to address these deficits by mandating their inclusion in all transition to professional practice programs.
Using Heteroscedasticity Consistent Standard Errors in the Linear Regression Model

Abstract In the presence of heteroscedasticity, ordinary least squares (OLS) estimates are unbiased, but the usual tests of significance are generally inappropriate and their use can lead to incorrect inferences. Tests based on a heteroscedasticity consistent covariance matrix (HCCM), however, are consistent even in the presence of heteroscedasticity of an unknown form. Most applications that use a HCCM appear to rely on the asymptotic version known as HC0. Our Monte Carlo simulations show that HC0 often results in incorrect inferences when N ≤ 250, while three relatively unknown, small sample versions of the HCCM, and especially a version known as HC3, work well even for N's as small as 25. We recommend that: (1) data analysts should correct for heteroscedasticity using a HCCM whenever there is reason to suspect heteroscedasticity; (2) the decision to use HCCM-based tests should not be determined by a screening test for heteroscedasticity; and (3) when N ≤ 250, the HCCM known as HC3 should be used. Since HC3 is simple to compute, we encourage authors of statistical software to add this estimator to their programs.
Supervised Learning for Autonomous Driving

In this work, we demonstrate end-to-end autonomous driving in a simulation environment by commanding steering and throttle control inputs from raw images. Supervised learning was used to map images to steering and throttle inputs based on example data from a human driver. The training data was augmented with adjusted images which allow the model to generalize better. Model selection was used to determine an appropriate neural network architecture and this process is documented. The capability of the model to drive autonomously in a real-time closed-loop simulation was evaluated. Further, the effect of smoothing data input and the augmentation of the data was explored. This work demonstrates the capability of a deep convolutional neural network with and without a Long ShortTerm Memory layer to accomplish aspects of autonomous driving using only direct image data as input.
Innovative approach to computer-guided surgery and fixed provisionalization assisted by screw-retained transitional implants.

PURPOSE The objectives of this case series are to describe a novel clinical approach to treat completely edentulous patients and determine its viability. Computer-guided implant planning was used to create a screw-retained surgical template (ST) supported by transitional implants and a fixed screw-retained provisional prosthesis supported by the transitional implants at the time of definitive implant placement. MATERIALS AND METHODS Five patients with at least one edentulous arch were treated. After the diagnostic tooth setup was performed, a duplicate with radiopaque acrylic resin was fabricated to serve as a surgical template (ST) for the placement of screw-form transitional implants and a radiographic guide (RG). Four transitional implants were strategically placed through the guide where they would not interfere with the future definitive implants. The transitional implants were used to support the RG during computed tomographic scanning. Subsequently, the RG was converted into a second ST based on three-dimensional virtual planning. Eight implants were placed by the computer-guided system, and an immediate prefabricated fixed provisional was connected to the transitional implants. RESULTS All the implants included in the study achieved primary stability and osseointegrated successfully. For 4 months, the transitional implants served successfully as abutments for the provisional prosthesis. CONCLUSION This innovative clinical approach overcomes the limitations of a mucosa/bone-supported ST by offering fixed, reproducible support for the RG and ST by means of transitional implants. The delivery of a prefabricated screw-retained provisional on transitional implants allows for passive healing and minimum chairside adjustments.
Lean body mass, not FFA, predicts VLDL‐TG secretion rate in healthy men

Triglyceride is a risk factor for cardiovascular disease. However, the impact of body composition and free fatty acid (FFA) levels on very‐low‐density‐lipoprotein triglyceride (VLDL‐TG) secretion remains controversial. The aim was to identify predictors of VLDL‐TG secretion in a data set compiled from seven previously published studies.
E-commerce adoption in small and medium enterprises (SMEs) in Asia: a study of the early stages of e-commerce uptake

E-commerce diffusion has had tremendous success stories in large businesses; however, organisational theories that are applicable to large businesses may not necessarily fit with Small and Medium Enterprises (SMEs) in the same way. This study identifies major factors at macro and micro levels that hindered SMEs' participation in e-commerce adoption in Asia during the early stages of e-commerce uptake over the period 1999–2001. Although, the study is limited to Asia, and is therefore limited in size and scope, the results could contribute to better understanding of the hindering factors in e-commerce adoption as they relate specifically to the business environment of SMEs.
Animal Models of Nutritional Induction of Type 2 Diabetes Mellitus

La diabetes mellitus tipo 2 (DM2) es la enfermedad metabolica cronica mas comun, afectando aproximadamente al 6% de la poblacion adulta en el mundo occidental. Esta condicion es una causa importante de las enfermedades cardiovasculares, la ceguera, la insuficiencia renal, y las amputaciones, con un aumento de su prevalencia en todo el mundo. El riesgo de obesidad en la diabetes tipo 2 esta determinado por el grado de obesidad y localizacion de la grasa corporal, siendo la resistencia a la insulina (RI) la principal relacion entre estas enfermedades metabolicas. Los estudios experimentales han demostrado que los factores dieteticos, y en particular los lipidos, se asocian de manera importante con la masa corporal (MC), la IR y la diabetes tipo 2. Asimismo, el consumo excesivo de alimentos ricos en carbohidratos de alto contenido energetico pueden provocar la diabetes tipo 2. Ademas, se ha sugerido que una dieta materna inadecuada al momento de concebir o durante el periodo de gestacion daria lugar al desarrollo de la excesiva MC y de trastornos metabolicos en los hijos, tales como la homeostasis anormal de la glucosa, reduccion de la sensibilidad a la insulina en todo el cuerpo, el deterioro en la funcion de celulas beta, resistencia a la insulina y cambios en la estructura del pancreas. La alteracion metabolica esta asociada de forma importante con los efectos daninos sobre el desarrollo y funcion de las celulas beta. Sin embargo, las alteraciones en la cantidad y la calidad de la grasa dietetica pueden modificar el metabolismo de la glucosa como tambien la sensibilidad a la insulina. De esta manera, la investigacion experimental ha enfocado la atencion en algunos aceites debido a sus efectos beneficiosos. El aceite de oliva, es una fuente de monoinsaturados y actualmente se sabe que este aceite tambien mejora la sensibilidad a la insulina y el control glucemico El aceite de canola, el aceite de linaza y especialmente el aceite de pescado (rico en omega-3 los acidos grasos poliinsaturados (PUFAs)) fueron descritos por primera vez como nutrientes de la dieta eficaces contra la hipertrigliceridemia, sin embargo, es sabido que ademas tienen efectos positivos sobre el metabolismo de la glucosa.
Mutual Information and Bit Error Rate Analysis of MIMO System Under Correlated Fading Channel

iii Table of Content
Generalized Classification Scheme of Toroidal and Helical Carbon Nanotubes

In this study, we develop a generalized classification scheme for toroidal (TCNT) and helical carbon nanotubes (HCNT) containing both pentagons and heptagons simultaneously. We show that a particular class of TCNTs with n-fold rotational symmetry and well-defined latitude coordinates can be uniquely characterized by a set of four indices, and each of the indices can be linked to the relative arrangement of pentagons and heptagons in the corresponding torus. Chiral isomers or the corresponding helical derivatives, HCNTs, can also be readily derived either by introducing a chiral vector or dissecting a distorted TCNT through certain longitude. This generalized scheme can generate the whole family of fullerenes with genus one, ranging from giant TCNTs down to small ones containing only a few hundred atoms. To the best of our knowledge, almost all of the construction methods for TCNTs in the literature belong to special cases of our generalized classification scheme.
Multi-objective optimization algorithm for efficient pin-constrained droplet routing technique in digital microfluidic biochip

Design automation for digital microfluidic biochip comprises of many combinatorial optimization problems, which are NP-complete in nature. Efficient optimization algorithms to solve them is in dearth till date. In this paper, we propose a multi-objective optimization algorithm that simultaneously minimizes several resources during bioassay operations in a digital microfluidic biochip. We design the progressive droplet routing as a constrained multi-objective optimization problem considering three objective functions to be optimized, named (i) electrode usages, (ii) routing completion time, or latest arrival time, and (iii) control pin allocation. A composite objective function is constructed by a weighted sum of the first two objective functions. This composite function is minimized pertaining to an upper bound on the third objective function, control pin allocation. A fractional constant weight factor (λ) is chosen to confer upon the necessary weightage on the two factors involved in the composite objective function for accurate optimization procedure. We perform experimentations with several existing benchmarks, and experimental results are quite encouraging.
Origin of ecdysosteroid UDP-glycosyltransferases of baculoviruses through horizontal gene transfer from Lepidoptera

Baculoviruses infecting Lepidoptera (butterflies and moths) encodes an enzyme known as ecdysosteroid UDP-glycosyltransferase (EGT), which inactivates insect host ecdysosteroid hormones, thereby preventing molt and pupation and permitting a build-up of the viral population within the host. Baculovirus EGT shows evidence of homology to insect UDP-glycosyltransferases (UGTs), and a phylogenetic analysis supported that the closest relatives of baculovirus EGT are the UGT33 and UGT34 families of lepidopteran UGTs. The phylogenetic analysis thus supported that baculovirus EGT arose by horizontal gene transfer of a UGT from a lepidopteran host, an event that occurred 70 million years ago at the earliest but possibly much more recently. Three amino acid replacements unique to baculovirus EGTs and conserved in all available baculovirus sequences were identified in the N-terminal region of the molecule. Because of their conservation, these amino acids are candidates for playing an important functional role in baculovirus EGT function.
Sustainability forecast for cloud migration

In this paper, a sustainability driven approach is proposed to measure the viability of cloud migration. The decision on cloud migration is based on sustainability dimensions, i.e., economic, environmental, social and technology, and risks associated with in these dimensions. We use Analytic Hierarchy Process and fuzzy scale to prioritize the sustainability dimensions based on a migration context to calculate Total Sustainability Index (TSI). TSI is then used to determine the viability of cloud migration according to three different scales, i.e., convincing, moderate, and ineffective. Finally, we used a practical migration use case from Ministry of Health (MoH), Malaysia to demonstrate the applicability of our work. The results from the studied context concluded that economic and business continuity are the key influential concerns for a sustainable cloud migration.
Cerebral microhemorrhage and iron deposition in mild cognitive impairment: susceptibility-weighted MR imaging assessment.

PURPOSE To test whether susceptibility-weighted magnetic resonance imaging at baseline may help predict cognitive decline. MATERIALS AND METHODS This prospective study was approved by the institutional review board, and written informed consent was obtained from all participants. Thirty-five healthy control subjects and 69 patients with mild cognitive impairment were included. Patients with mild cognitive impairment underwent neuropsychologic follow-up after 1 year (40 patients with stable mild cognitive impairment, 27 with progressive mild cognitive impairment, and two lost to follow-up). Cerebral microhemorrhages were visually analyzed by two experienced neuroradiologists in consensus. Iron deposition in deep gray matter was assessed with voxel-wise and region-of-interest analysis after nonlinear spatial registration. In addition, individual classification of mild cognitive impairment was analyzed by using a support vector machine (SVM). RESULTS At baseline, the number of cerebral microhemorrhages was significantly higher in the mild cognitive impairment group than in the control group (P < .01) but did not differ between the patients with stable and those with progressive mild cognitive impairment. Compared with the control group, patients with mild cognitive impairment had increased iron concentration in the right pallidum (P < .01) and right substantia nigra (P < .01) but decreased concentration in the right red nucleus (P < .05). The classification based on the SVM successfully helped discriminate patients with mild cognitive impairment from the healthy control subjects (accuracy, 84%; sensitivity, 89%; specificity, 85%) and those with stable from those with progressive mild cognitive impairment (accuracy, 85%; sensitivity, 84%; specificity, 83%). CONCLUSION The findings reveal an accumulation of cerebral microhemorrhage in patients with mild cognitive impairment that is present at baseline, independent of subsequent cognitive decline, as well as an altered iron distribution in subcortical nuclei between the healthy control subjects and patients with mild cognitive impairment. Analysis of iron deposition at baseline performed with an SVM might help identify individual patients with mild cognitive impairment at risk for cognitive decline. SUPPLEMENTAL MATERIAL http://radiology.rsna. org/lookup/suppl/doi:10.1148/radiol.10100612/-/DC1.
Receptor-dependent transcriptional activation of cytochrome P4503A genes: induction mechanisms, species differences and interindividual variation in man

1 The importance of CYP3A enzymes in drug metabolism and toxicology has yielded a wealth of information on the structure, function and regulation of this subfamily and recent research emphasis has been placed on the human forms, namely CYP3A4, CYP3A5, CYP3A7 and CYP3A43. 2 The current review will focus on the receptor-dependency of CYP3A regulation and includes consideration of the regulatory roles of the glucocorticoid (GR), pregnane X (PXR) and constitutive androstane (CAR) receptors. 3 Emphasis has been placed on the topics of expression and substrate specificity, assessment of induction, species differences in induction, CYP3A promoter sequences and regulation of gene expression, structural and functional aspects of receptor-mediated, CYP3A gene activation, receptor variants and interindividual variation in human CYP3A expression, the latter encompassing environmental, physiological and genetic aspects. 4 An outline of future research needs will be discussed in the context of receptor-mediated molecular mechanisms of CYP3A gene regulation and the impact on interindividual variations in CYP3A expression. 5 Taken collectively, this review highlights the importance of understanding the molecular mechanisms of CYP3A induction as a means of rationalizing human responses to many clinically used drugs, in addition to providing a mechanistically coherent platform to understand and predict interindividual variations in response and drug-drug interactions.
Atomic Layer Deposition of Stable LiAlF4 Lithium Ion Conductive Interfacial Layer for Stable Cathode Cycling.

Modern lithium ion batteries are often desired to operate at a wide electrochemical window to maximize energy densities. While pushing the limit of cutoff potentials allows batteries to provide greater energy densities with enhanced specific capacities and higher voltage outputs, it raises key challenges with thermodynamic and kinetic stability in the battery. This is especially true for layered lithium transition-metal oxides, where capacities can improve but stabilities are compromised as wider electrochemical windows are applied. To overcome the above-mentioned challenges, we used atomic layer deposition to develop a LiAlF4 solid thin film with robust stability and satisfactory ion conductivity, which is superior to commonly used LiF and AlF3. With a predicted stable electrochemical window of approximately 2.0 ± 0.9 to 5.7 ± 0.7 V vs Li+/Li for LiAlF4, excellent stability was achieved for high Ni content LiNi0.8Mn0. 1Co0.1O2 electrodes with LiAlF4 interfacial layer at a wide electrochemical window of 2.75-4.50 V vs Li+/Li.