Miracle-dz/UniFAR-FTUs huggingface dataset:
Revisiting the etiological aspects of dissociative identity disorder: a biopsychosocial perspective

Dissociative identity disorder (DID) is a chronic post-traumatic disorder where developmentally stressful events in childhood, including abuse, emotional neglect, disturbed attachment, and boundary violations are central and typical etiological factors. Familial, societal, and cultural factors may give rise to the trauma and/or they may influence the expression of DID. Memory and the construction of self-identity are cognitive processes that appear markedly and centrally disrupted in DID and are related to its etiology. Enduring decoupling of psychological modes may create separate senses of self, and metamemory processes may be involved in interidentity amnesia. Neurobiological differences have been demonstrated between dissociative identities within patients with DID and between patients with DID and controls. Given the current evidence, DID as a diagnostic entity cannot be explained as a phenomenon created by iatrogenic influences, suggestibility, malingering, or social role-taking. On the contrary, DID is an empirically robust chronic psychiatric disorder based on neurobiological, cognitive, and interpersonal non-integration as a response to unbearable stress. While current evidence is sufficient to firmly establish this etiological stance, given the wide opportunities for innovative research, the disorder is still understudied. Comparison of well-selected samples of DID patients with non-dissociative subjects who have other psychiatric disorders would further delineate the neurobiological and cognitive features of the disorder, whereas genetic research on DID would further illuminate the interaction of the individual with environmental stress. As such, DID may be seen as an exemplary disease model of the biopsychosocial paradigm in psychiatry.
Nanoscale Energy Transport and Harvesting: A Computational Study

Transport phenomena in energy systems including: -Dry cooling for Nanoscale Materials, Quebec City, Aug. 15-20 T.L. Bergman, A.S. Lavine, F.P. Incropera and D.P. DeWitt, Solutions Manual, Energy Conversion and Management. Nanoscale Energy Transport And Conversion: A Parallel Treatment Of (Mit-Pappalardo Series In Mechanical Engineering) Gang Chen ebook, pdf, download. independent work courses, and student elected PDF courses). ABET (formerly Mass, Momentum and Energy Transport. CBE 346 MAE 427. Energy Conversion and the Environment: Introduction to Nano/Microfabrication Panagiotopoulos Monte Carlo Simulation of Multiblock Copolymers in Solution. Priestley.
PAD: protecting anonymity in publishing building related datasets

The diffusion of low-cost sensor network technologies in smart buildings has enabled the collection of massive amounts of data regarding indoor environments, energy use and occupants, which, in turn, creates opportunities for knowledge- and information-based building management. Driven by benefits mutual to occupants, building managers, and research communities, there is a demand for data publication to foster more sophisticated and robust models and algorithms. Data in the original form, however, contains sensitive information about occupants' behavioral patterns, and publishing such data will violate individuals' privacy. The current practice on publishing building-related datasets relies primarily on policies for dictating which types of data can be published and agreements on the use of published data. This approach alone provides insufficient protection as it does not prevent privacy breaches from occurring in the first place. In this paper, we present PAD, which to our knowledge is the first system that provides a technological solution for publishing building related datasets in a privacy-preserving manner while maintaining high data quality. PAD is able to offer a strong anonymity guarantee by perturbing data records. The unique feature of PAD is that it offers an interface to incorporate dataset users into the loop of data publication and customizes the perturbation such that useful information in the dataset can be better retained. We study the efficacy of PAD using occupancy and plug load data collected in real buildings. The experiments demonstrate that PAD can achieve high resilience to privacy threats without introducing any significant data fidelity penalties.
Chapter 2 Reliability of 3 D NAND Flash Memories

Reliability represents one of the major antagonist towards the unstoppable technological evolution of hyperscaled NAND memories, since the correct operations must be assured throughout the entire lifetime. In particular, the ability of keeping unaltered the stored information even after a consistent number of write operations and for long times must be guaranteed. A growth of the memory devices storage capacity without increasing the area occupation is constantly requested by the market: in order to satisfy such requirements, an increase of the memory density and of cell shrinking is mandatory. Nowadays, the transition from planar to three-dimensional architectures appears as the most viable solution for the integration of non-volatile memory cells in Tera-bit arrays. Charge Trap (CT) NAND memory cells are considered as one of the most promising technology for 3D integration because of a better scalability than Floating Gate (FG) NAND. Despite the high theoretical potentialities demonstrated by CT memories, several reliability issues affect such technology. Moreover, the transition from 2D to 3D changed the impact of the previously known reliability issues and generated new problems. Recently, in order to overcome such problems, new 3D vertical FG type NAND cell arrays have been proposed with promising performances.
Aberrantly Expressed lncRNAs in Primary Varicose Great Saphenous Veins

Long non-coding RNAs (lncRNAs) are key regulatory molecules involved in a variety of biological processes and human diseases. However, the pathological effects of lncRNAs on primary varicose great saphenous veins (GSVs) remain unclear. The purpose of the present study was to identify aberrantly expressed lncRNAs involved in the prevalence of GSV varicosities and predict their potential functions. Using microarray with 33,045 lncRNA and 30,215 mRNA probes, 557 lncRNAs and 980 mRNAs that differed significantly in expression between the varicose great saphenous veins and control veins were identified in six pairs of samples. These lncRNAs were sub-grouped and mRNAs expressed at different levels were clustered into several pathways with six focused on metabolic pathways. Quantitative real-time PCR replication of nine lncRNAs was performed in 32 subjects, validating six lncRNAs (AF119885, AK021444, NR_027830, G36810, NR_027927, uc.345-). A coding-non-coding gene co-expression network revealed that four of these six lncRNAs may be correlated with 11 mRNAs and pathway analysis revealed that they may be correlated with another 8 mRNAs associated with metabolic pathways. In conclusion, aberrantly expressed lncRNAs for GSV varicosities were here systematically screened and validated and their functions were predicted. These findings provide novel insight into the physiology of lncRNAs and the pathogenesis of varicose veins for further investigation. These aberrantly expressed lncRNAs may serve as new therapeutic targets for varicose veins. The Human Ethnics Committee of Shanghai East Hospital, Tongji University School of Medicine approved the study (NO.: 2011-DF-53).
Inclusion of Unstructured Clinical Text Improves Early Prediction of Death or Prolonged ICU Stay*

Objectives: Early prediction of undesired outcomes among newly hospitalized patients could improve patient triage and prompt conversations about patients’ goals of care. We evaluated the performance of logistic regression, gradient boosting machine, random forest, and elastic net regression models, with and without unstructured clinical text data, to predict a binary composite outcome of in-hospital death or ICU length of stay greater than or equal to 7 days using data from the first 48 hours of hospitalization. Design: Retrospective cohort study with split sampling for model training and testing. Setting: A single urban academic hospital. Patients: All hospitalized patients who required ICU care at the Beth Israel Deaconess Medical Center in Boston, MA, from 2001 to 2012. Interventions: None. Measurements and Main Results: Among eligible 25,947 hospital admissions, we observed 5,504 (21.2%) in which patients died or had ICU length of stay greater than or equal to 7 days. The gradient boosting machine model had the highest discrimination without (area under the receiver operating characteristic curve, 0.83; 95% CI, 0.81–0.84) and with (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.88–0.90) text-derived variables. Both gradient boosting machines and random forests outperformed logistic regression without text data (p < 0.001), whereas all models outperformed logistic regression with text data (p < 0.02). The inclusion of text data increased the discrimination of all four model types (p < 0.001). Among those models using text data, the increasing presence of terms “intubated” and “poor prognosis” were positively associated with mortality and ICU length of stay, whereas the term “extubated” was inversely associated with them. Conclusions: Variables extracted from unstructured clinical text from the first 48 hours of hospital admission using natural language processing techniques significantly improved the abilities of logistic regression and other machine learning models to predict which patients died or had long ICU stays. Learning health systems may adapt such models using open-source approaches to capture local variation in care patterns.
The Emerging Role of Inhibitor of Growth 4 as a Tumor Suppressor in Multiple Human Cancers

Inhibitor of growth 4 (ING4), a member of the conserved ING family, has been identified as an important tumor suppressor since it plays a critical role in the regulation of chromatin modification, cell proliferation, angiogenesis and cell migration. Some observations suggest that ING4 acts as a key regulator of tumorigenesis through modifying gene transcription in part by regulating the transcription factors p53 and NF-kappaB (NF-κB). However, these models have yet to be substantiated by further investigations. Numerous reports describe the reduced expression of ING4 in cancers, and the responsible mechanisms are involved in gene deletion, mutation, transcriptional and post-transcriptional dysregulation. This review aims to summarize the recent published literature that investigates the role of ING4 in regulating tumorigenesis and progression, and explore its potential for cancer treatment.
ECoG factors underlying multimodal control of a brain-computer interface

Most current brain-computer interface (BCI) systems for humans use electroencephalographic activity recorded from the scalp, and may be limited in many ways. Electrocorticography (ECoG) is believed to be a minimally-invasive alternative to electroencephalogram (EEG) for BCI systems, yielding superior signal characteristics that could allow rapid user training and faster communication rates. In addition, our preliminary results suggest that brain regions other than the sensorimotor cortex, such as auditory cortex, may be trained to control a BCI system using similar methods as those used to train motor regions of the brain. This could prove to be vital for users who have neurological disease, head trauma, or other conditions precluding the use of sensorimotor cortex for BCI control.
Interstitial brachytherapy of oral squamous cell carcinoma with ultrasound-guided iodine-125 radioactive seed implantation.

OBJECTIVE In this study, we investigated the clinical effect of interstitial brachytherapy on oral squamous cell carcinoma (OSCC) with ultrasound or CT-guided 125I radioactive seed implantation. PATIENTS AND METHODS 116 patients with advanced oral squamous cell carcinoma, who received initial treatment or retreatment, were enrolled. Therein, 35 patients in the control group were treated with external radiation, systemic chemotherapy or conservative treatment, 41 patients in the ultrasound group were treated with ultrasound-guided125I radioactive seed interstitial implantation brachytherapy, and 40 patients in the CT group were treated with CT-guided 125I radioactive seed interstitial implantation. The median follow-up time was 15.0 months. The clinical outcomes were compared. RESULTS At the time of one month after treatment, the tumor diameters of the ultrasound group and the CT group were significantly decreased (p<0.05), which were less than the control group (p<0.05), and there was no difference in comparison between the ultrasound group and the CT group (p>0.05). At the time of one month after treatment, the effective rates were significantly higher in the ultrasound group and the CT group than the control group (p<0.001), and there was no difference in comparison between the ultrasound group and the CT group. And there was no difference in comparison of complication between these two groups (p>0.05). At the time of one month after treatment, the VAS scores of pain were significantly lower in the ultrasound group and the CT group than the control group (p<0.05). There were no differences in comparisons of T lymphocyte subset percentages before and after treatment (p>0.05), and T lymphocyte subset percentages in the control group were significantly decreased (p<0.05). The progression-free survivals, median survival times, and survival rates were significantly higher in the ultrasound group and the CT group than those in the control group (p<0.05), and there were no differences in comparisons between the ultrasound group and the CT group (p>0.05). CONCLUSIONS Both ultrasound and CT-guided iodine-125 radioactive seed interstitial implantation brachytherapy in the treatment of OSCC can achieve better short-term and long-term clinical effects.
Generating Neural Networks with Optimal Features through Particle Swarm Optimization

In this paper, we propose a new algorithm for generating Neural Network architectures with optimal features through Particle Swarm Optimization. Selecting the best architecture for a Neural Network is usually done through a trial and error process, in which the number of layers is selected usually based on previous experience and then the network is trained and tested. When using Neural Networks as classifiers in feature selection algorithms, usually the number of layers in the Neural Network is selected prior to using the Neural Network as a classifier to the feature selection algorithm. In this paper we propose a new generative algorithm based on PSO which combines the feature selection process with the Neural Network topology selection process in one algorithm which generates the Neural Network topology while at the same time performs feature selection and evaluates the Neural Network topology to determine its quality. With the proposed algorithm, given a dataset, it is possible to end up with the optimal features on the dataset and with an optimal Neural Network classifier for such features.
Characterization of Mechanically Enhanced FRP Bonding System

Despite extensive research on externally bonded fiber-reinforced polymer (EB-FRP) for rehabilitation of concrete structures in the past two decades, the industry has been slow to embrace the technology owing to some difficult problems that are yet to be resolved fully. Among these, premature debonding is one of the critical problems. Since the tensile strength of concrete is inherently low and unreliable (in the long term), EB-FRP by surface adhesion might not be the final solution; augmentation of the interfacial bond by mechanical fastening may be unavoidable. To this end, the first author proposed a bond augmentation system, hybrid-bonded FRP (HB-FRP), where a special type of mechanical fasteners are used to enhance the interfacial bond. Although the HB-FRP system has been experimentally shown to increase bond strength several fold, effectively overcoming the debonding problem, there has been no systematic theoretical study of the system. In this paper, HB-FRP joints are characterized through experimental testing and analytical modeling, leading to a theory for design and construction of the HB-FRP system.
Global epidemiology and patterns of cerebral venous thrombosis: a systematic review and meta-analysis protocol

Introduction Venous thrombosis can affect all veins in the body including cerebral veins, where it causes cerebral venous thrombosis (CVT). CVT is an aetiology of stroke, particularly in children and young adults. Its clinical features vary widely according to the occluded vessel. Data concerning the epidemiology of CVT are scant. This protocol for a systematic review and meta-analysis aims to critically synthesise data concerning prevalence, incidence, risk factors, anatomical patterns, diagnostic and therapeutic delays, and mortality rate of CVT in the global population. Methods and analysis MEDLINE, EMBASE and ISI Web of Science databases will be searched for relevant abstracts of studies published between 1 January 1990 and 31 October 2017, without language restriction. After the screening of abstracts, study selection, data extraction and assessment of risk of bias, we will assess studies individually for heterogeneity. Random effects meta-analysis will then be used to pool studies judged to be clinically homogenous. Funnel plot analysis and Egger’s test will be used to detect publication bias. Results will be presented according to economic level of the various countries (high-income vs low/middle-income countries). Ethics and dissemination Since the current study will be based on published data, ethical approval is not required. This review is expected to provide relevant data to help in evaluating the global burden of CVT. The final report of this study will be published in a peer-reviewed journal. PROSPERO registration number CRD42017074266.
Better Early Than Never: Performance Test Acceleration by Regression Test Selection

Currently, performance tests take much time and are therefore not able to provide fast feedback. Fast feedback on performance tests would support finding performance problems. In order to accelerate performance tests we provide a regression test selection method for performance tests. It is based on test selection by (1) code analysis and (2) trace analysis. We show the efficiency of our approach by comparison with the test selection tools EKSTAZI and Infinitest.
Distributed Maximal Independent Set on Scale-Free Networks

The problem of distributed maximal independent set (MIS) is investigated on inhomogeneous random graphs with power-law weights by which the scale-free networks can be produced. Such a particular problem has been solved on graphs with $n$ vertices by state-of-the-art algorithms with the time complexity of $O(\log{n})$. We prove that for a scale-free network with power-law exponent $\beta > 3$, the induced subgraph is constructed by vertices with degrees larger than $\log{n}\log^{*}{n}$ is a scale-free network with $\beta' = 2$, almost surely (a.s.). Then, we propose a new algorithm that computes an MIS on scale-free networks with the time complexity of $O(\frac{\log{n}}{\log{\log{n}}})$ a.s. , which is better than $O(\log{n})$. Furthermore, we prove that on scale-free networks with $\beta \geq 3$, the arboricity and degeneracy are less than $2^{log^{1/3}n}$ with high probability (w.h.p.). Finally, we prove that the time complexity of finding an MIS on scale-free networks with $\beta\geq 3$ is $O(log^{2/3}n)$ w.h. p.
Epidemiology of substance use in a representative sample of 18-year-old males.

AIMS To assess recent drug use through urine testing as well as the prevalence of tobacco and alcohol dependence among young males and to analyse the associations between tobacco dependence and cannabis use (delta-9-tetrahydrocannabinol, THC), tobacco dependence, and alcohol dependence as well as between THC use and other illicit drug use. METHODS Urine samples were collected, and nicotine and alcohol questionnaires were administered. Carbon monoxide was assessed in exhaled air. Data from young males from representative, selected districts of Lower Austria were recorded during the annual physical examination for mandatory military service. Out of all 18-year-old males in Austria 3.8% (n = 1902) were included in the study. Prevalence of recent illicit drug use, tobacco dependence (heavy smoking index, HSI), alcohol dependence (The 4-item cutting down, annoyance by criticism, guilty feeling, and eye-openers (CAGE) questionnaire), and associations between substance categories by means of logistic regression analyses were calculated. RESULTS Alcohol abuse was found in 15.1% and alcohol dependence was found in 3.2%. According to the HSI 51.5% of males reported daily smoking, of whom 43.7% showed a mild level, and 7.8% a high level, of nicotine dependence. About 5.1% of the sample evidenced THC in urine. Opiates were identified in 2.7% of urine samples. Smokers showed a higher risk of THC use. THC users had a tendency to use cocaine and amphetamines more frequently than THC abstainers. CONCLUSION Nicotine and alcohol dependence is common among young males. Biological assessment of illicit drug use seems to confirm previous questionnaire-based findings of associations between THC use and other illicit drugs. Urine testing seems to be an adequate method to analyse associations of THC use and other illicit drugs. In combination with questionnaires urine testing may be used for the assessment of associations of tobacco dependence and recent illicit drug use based on epidemiological surveys.
Mediators and intracellular mechanisms of NANC relaxation of smooth muscle in the gastrointestinal tract.

Tension of the skeletal muscle is solely controlled by excitatory cholinergic motor neurons. By contrast, the peripheral smooth muscle tissues are dual-controlled by nonadrenergic noncholinergic (NANC) inhibitory neurons as well as excitatory neurons. In the gastrointestinal tract, many possible candidates, including peptides, amino acids, nucleotides and gaseous compounds, for the inhibitory mediator and mechanisms of their inhibitory control have been extensively studied. This article introduces the diversity of inhibitory mediators and their probable intracellular mechanisms on the basis of recent findings on this theme, many of which are unexpected interesting findings.
Energy-Quality Scaling in Analog Mesh Computers

The recent push for post-Moore computer architectures has introduced a wide variety of application-specific accelerators. One particular accelerator, the resistance network analogue, has been well received due to its ability to efficiently solve partial differential equations by eliminating the iterative stages required by today's numerical solvers. However, in the ago of programmable integrated circuits, the static nature of the resistance network analogue, and other analog mesh computers like it, has relegated it to an academic curiosity. Recent developments in materials, such as the memristor, have made the resistance network analogue viable for inclusion in future heterogeneous computer architectures. However, selection of an appropriate sized mesh to be incorporated into a computer system requires that energy-quality trade-offs are made regarding the problem size and required resolution of the solution. This paper provides an in-depth study of the scaling of analog mesh computer hardware, from the perspective of energy per bit and required resolution, introduces a metric to aid in quantifying analog mesh computers with different parameters, and introduces a method of virtualization which enables an analog mesh computer of a fixed size to approximate the calculations of a larger-sized mesh.