Miracle-dz/UniFAR-FTUs huggingface dataset:
15 Virtual Reality and Telemedicine Based Experiential Cognitive Therapy: Rationale and Clinical Protocol

In the past decade medical applications of virtual reality (VR) and telemedicine have been rapidly developing, and the technology has changed from a research curiosity to a commercially and clinically important area of medical informatics technology. The chapter details the characteristics of the Experiential Cognitive Therapy (ECT), an integrated in-patient/out-patient (4 weeks) and telemedicine approach (24 weeks), that tries to enhance the cognitive-behavioral therapy used in the treatment of eating disorders by means of VR sessions and telemedicine support in the follow-up stage. In particular, using VR and telemedicine, ECT is able to address body experience disturbances, interpersonal relationships, self efficacy and motivation to change, key issues for the development and maintenance of eating disorders that are somehow neglected by actual clinical guidelines. This approach will be highlighted by the presentation of the clinical rationale, its different phases and by systematic analysis of the results obtained in different preliminary studies.
Title: Internal Control Framework of a Compliant Erp System Internal Control Framework of a Compliant Erp System

After the occurrence of numerous worldwide financial scandals, the importance of related issues such as internal control and information security has greatly increased. An internal control framework that can be applied within an enterprise resource planning (ERP) system is developed in this study. A literature review is first conducted to examine the necessary forms of internal control in information technology (IT) systems. The control criteria for the establishment of the internal control framework are then constructed. A case study is conducted to verify the feasibility of the established framework. This study proposes a 12dimensional framework with 37 control items aimed at helping auditors perform effective audits by inspecting essential internal control points in ERP systems. The proposed framework allows companies to enhance IT audit efficiency and mitigates control risk. Moreover, companies that refer to this framework and consider the limitations of their own IT management can establish a more robust IT management mechanism.
On the interactions of critical curves , catastrophe points , scale space saddles , and iso-intensity manifolds in Gaussian scale space images under a one-parameter driven deformation

In this work we describe the possible transitions for the hierarchical structure that describes an image in Gaussian scale space. Until now, this structure has only been used for topological segmentation, while image matching and retrieval studies ignored the hierarchy. In order to perform such tasks based on the hierarchical structure, one needs to know which transitions are allowed when the structure is changed under influence of one control parameter.
Using culturally appropriate, trauma-informed support to promote bicultural self-efficacy among resettled refugees: A conceptual model

ABSTRACT Resettled refugees face pressure to integrate successfully into the culture of their resettlement country within a relatively short period of time. Though successful integration is important, research has shown that ethnic identity and participation in the ethnic culture of origin play a key role in supporting the mental health of resettled refugees. This paper presents a model that draws on social-cognitive theory, trauma theory, and models of second culture acquisition to reflect relationships between trauma, mental health, and self-efficacy. The model presents the concept of bicultural self-efficacy as a potential outcome measure for facilitating inter-disciplinary research and practice efforts.
Selective requantization for transcoding of MPEG compressed video

The paper addresses the problem of bit-rate conversion of MPEG compressed video. We present selective requantization, a method for reducing the requantization errors in transcoding. The proposed method is based on avoiding critical ratios of the two cascaded quantizations (encoding versus transcoding) that either lead to larger transcoding errors or require a higher bit budget. Results show that selective requantization improves the quality of the transcoded images. The presented method is simple to implement and does not require side information.
Receptor Binding and Activation of Polymorphonuclear Neutrophils by Tumor Necrosis Factor‐Alpha

The interaction of highly purified recombinant human tumor necrosis factor‐alpha (rTNF‐α) with human polymorphonuclear neutrophils (PMNs) was investigated. Binding of 125l‐rTNF‐α to PMN reached maximum levels in 30 min at 37°C and in 2 h at 4°C. Scatchard analysis of competitive binding data indicated approximately 6000 receptor sites per cell and a Kd of 1.37 nM. Binding data at 37°C indicated a rapid internalization of rTNF‐α. Following this receptor‐mediated interaction, recombinant TNF‐α was found to inhibit the migration of PMNs under agarose and to enhance PMN production of superoxide anion (O‐ 2) in a dose‐dependent manner. Furthermore, rTNF‐α‐activated PMNs caused a marked disruption of human umbilical‐vein‐derived endothelial cell monolayers and caused inhibition of their proliferative activities. These data substantiate the role of TNF‐α as an activator of PMN functions and indicate that PMN/TNF‐α/endothelial cell interactions may play a major role in inflammatory reactions.
Development of a field-friendly automated dietary assessment tool and nutrient database for India

Studies of diet and disease risk in India and among other Asian-Indian populations are hindered by the need for a comprehensive dietary assessment tool to capture data on the wide variety of food and nutrient intakes across different regions and ethnic groups. The nutritional component of the India Health Study, a multicentre pilot cohort study, included 3908 men and women, aged 35–69 years, residing in three regions of India (New Delhi in the north, Mumbai in the west and Trivandrum in the south). We developed a computer-based, interviewer-administered dietary assessment software known as the ‘NINA-DISH (New Interactive Nutrition Assistant – Diet in India Study of Health)’, which consisted of four sections: (1) a diet history questionnaire with defined questions on frequency and portion size; (2) an open-ended section for each mealtime; (3) a food-preparer questionnaire; (4) a 24 h dietary recall. Using the preferred meal-based approach, frequency of intake and portion size were recorded and linked to a nutrient database that we developed and modified from a set of existing international databases containing data on Indian foods and recipes. The NINA-DISH software was designed to be easily adaptable and was well accepted by the interviewers and participants in the field. A predominant three-meal eating pattern emerged; however, patterns in the number of foods reported and the primary contributors to macro- and micronutrient intakes differed by region and demographic factors. The newly developed NINA-DISH software provides a much-needed tool for measuring diet and nutrient profiles across the diverse populations of India with the potential for application in other South Asian populations living throughout the world.
Using ecological interface design to develop an auditory interface for visually impaired travellers

This paper discusses the development of a prototype design of an auditory interface for the visually impaired based on the work domain analysis of ecological interface design. Secondary mobility devices have been developed to increase preview distances in addition to a long cane, but these have gained limited acceptance. These devices lack an easily interpreted interface. An interface design that provides the user with sufficient preview to avoid obstacles and plan a path among obstacles is presented
Design and implementation of a Bluetooth signal strength based location sensing system

In a ubiquitous computing environment, location awareness is a basic necessity. There are various research projects, which discuss the problem of indoor location sensing. We have recognized acceptability, low power consumption, and cost as the key design factors for developing widely deployable location sensing systems. As a good candidate technology that could satisfy these needs, we proposed a location sensing system based on the widely available Bluetooth medium. Location evaluation is preformed by sensing Bluetooth signal strength with a reference model based approach. We discuss problems which arise when the Bluetooth RSSI (received signal strength indicator) is used as a signal strength indicator, and propose a novel access point that supports variable attenuators to overcome these problems. This access point allows the reading of a wider range of signal strengths using RSSI. We show that our approach to location sensing has reduced the error rate about threefold compared to systems which do not use variable attenuator supported access points.
A new approach to the maximum flow problem

All previously known efftcient maximum-flow algorithms work by finding augmenting paths, either one path at a time (as in the original Ford and Fulkerson algorithm) or all shortest-length augmenting paths at once (using the layered network approach of Dinic). An alternative method based on the preflow concept of Karzanov is introduced. A preflow is like a flow, except that the total amount flowing into a vertex is allowed to exceed the total amount flowing out. The method maintains a preflow in the original network and pushes local flow excess toward the sink along what are estimated to be shortest paths. The algorithm and its analysis are simple and intuitive, yet the algorithm runs as fast as any other known method on dense. graphs, achieving an O(n)) time bound on an n-vertex graph. By incorporating the dynamic tree data structure of Sleator and Tarjan, we obtain a version of the algorithm running in O(nm log(n'/m)) time on an n-vertex, m-edge graph. This is as fast as any known method for any graph density and faster on graphs of moderate density. The algorithm also admits efticient distributed and parallel implementations. A parallel implementation running in O(n'log n) time using n processors and O(m) space is obtained. This time bound matches that of the Shiloach-Vishkin
On orientifolds of WZW models and their relation to geometry

We investigate D-branes in orientifolds of WZW models. A connection be- tween the conformal fleld theory approach to orientifolds and the target space motivated analysis is established. In particular, we associate previously constructed crosscap states to involutions of the group manifold and their flxed point sets. Whereas our analysis of D-branes in orientifolds of general WZW models is restricted to special D0-branes, we investigate all symmetry preserving branes of SU(2)-orientifolds in detail. For that case, the location of the orientifold flxed point set is independently determined by scattering localized graviton wave packets.
Adult Learning: Evaluation of Preferences for Technology and Learning Sources for Workplace Learning

The purpose of this research was to provide an initial investigation of the preferences for both technology and learning sources that are available today in the modern workplace at a large financial institution with a national presence in the USA. In addition to the preferences of the participants, the research includes insights about the culture of the learning organization by using the Dimension of Learning Organization Questionnaire (DLOQ) and two preference surveys. The research methods used in this study are categorized as mixed methods and include both quantitative and qualitative methods. This study is nonpositivist and descriptive. It is based on a triangulation design method which is comprised of analysis from data obtained from the DLOQ and preference surveys, as well as semi-structured interviews with several survey participants. The results of the studies provide the foundational information for an extended quantitative analysis.
Congestion control in CSMA-based vehicular networks: Do not forget the carrier sensing

Inter-vehicular communications are considered to be an efficient proactive approach for reducing the number and the consequences of road accidents. After a series of remarkable standardisation efforts, one of the last points needing to be addressed in order for safety vehicular networks to become a reality is the scalability problem of the CSMA-based medium access control layer. With node densities that can range from very sparse to several hundred contending stations, the MAC protocol needs the capacity to adapt to the state of the vehicular network without compromising the performance of the safety applications. While previous studies focused on individual mechanisms for data rate selection or transmission power control from a global point of view, this paper proposes a complete congestion control framework aiming to increase the message reception probability in the immediate neighbourhood under heavy congestion conditions. We propose a new concept for physical carrier sensing, which takes into account the location of the transmitter, and we combine it with transmission power control and a recently proposed backoff mechanism to obtain an important improvement over the original protocol. Several implementation problems are discussed, showing the feasibility of the solution using existing hardware, and a simulation study confirms the performance of this enhanced channel access method.
Waiting for Anonymity : Understanding Delays in Tor

Although Tor is the most widely used system for providing anonymity services, its users often experience very high delays. Because much of Tor usage is for Web applications, which are sensitive to latency, it is critical to reduce delays in Tor. To take an important step in this direction, we seek an in-depth understanding of delays in Tor. By taking snapshots of the entire Tor network within a short time window, we are able to study the delay distribution of the entire router population. We also monitor delays introduced by individual Tor routers over extended periods of time. Our results indicate that apart from delays introduced by routers, overlay network latency also plays a significant role in delays in Tor. We have also observed that at any time, there exist huge differences in the delays introduced by different routers. Our results reveal key performance characteristics of Tor system behavior and provide valuable insights for improving the Tor performance.
Introduction to Neural and Cognitive Modeling

From the Publisher: This thoroughly and thoughtfully revised edition makes the principles and the details of neural network modeling accessible to cognitive scientists of all varieties as well as other scholars interested in these models. " "Features of the second edition include: a new section on spatiotemporal pattern processing; coverage of ARTMAP networks (the supervised version of adaptive resonance networks) and recurrent back-propagation networks; a vastly expanded section on models of specific brain areas, such as the cerebellum, hippocampus, basal ganglia, and visual and motor cortex; and up-to-date coverage of applications of neural networks in areas such as combinational optimization and knowledge representation.
The Role of Aberrant VHL/HIF Pathway Elements in Predicting Clinical Outcome to Pazopanib Therapy in Patients with Metastatic Clear-Cell Renal Cell Carcinoma

Purpose: Inactivation of von Hippel-Lindau (VHL) gene in clear-cell renal cell carcinoma (RCC) leads to increased levels of hypoxia-inducible factors (HIF) and overexpression of HIF target genes, such as VEGF and others. VEGF-targeted agents are standard in advanced clear-cell RCC but biomarkers of activity are lacking. Experimental Design: We analyzed tumor tissue samples from metastatic clear-cell RCC patients who received pazopanib as part of clinical trial VEG102616. We evaluated several components of the VHL/HIF pathway: VHL gene inactivation (mutation and/or methylation), HIF-1α and HIF-2α immunohistochemistry staining, and HIF-1α transcriptional signature. We evaluated the association of these biomarkers with best overall response rate (ORR) and progression-free survival (PFS) to pazopanib, a standard first-line VEGF-targeted agent. Results: The VEG102616 trial enrolled 225 patients, from whom 78 samples were available for tumor DNA extraction. Of these, 70 patients had VHL mutation or methylation. VHL gene status did not correlate with ORR or PFS. Similarly, HIF-1α (65 samples) and HIF-2α (66 samples) protein levels (high vs. low) did not correlate with ORR or PFS to pazopanib. The HIF-1α transcriptional signature (46 samples) was enriched in tumors expressing high HIF-1α levels. However, the HIF-1α gene expression signature was not associated with clinical outcome to pazopanib. Conclusions: In patients with advanced clear-cell RCC, several potential biomarkers along the VHL/HIF-1α/HIF-2α axis were not found to be predictive for pazopanib activity. Additional efforts must continue to identify biomarkers associated with clinical outcome to VEGF-targeted agents in metastatic RCC. Clin Cancer Res; 19(18); 5218–26. ©2013 AACR.
Structural relationships for large-scale learning of answer re-ranking

Supervised learning applied to answer re-ranking can highly improve on the overall accuracy of question answering (QA) systems. The key aspect is that the relationships and properties of the question/answer pair composed of a question and the supporting passage of an answer candidate, can be efficiently compared with those captured by the learnt model. In this paper, we define novel supervised approaches that exploit structural relationships between a question and their candidate answer passages to learn a re-ranking model. We model structural representations of both questions and answers and their mutual relationships by just using an off-the-shelf shallow syntactic parser. We encode structures in Support Vector Machines (SVMs) by means of sequence and tree kernels, which can implicitly represent question and answer pairs in huge feature spaces. Such models together with the latest approach to fast kernel-based learning enabled the training of our rerankers on hundreds of thousands of instances, which previously rendered intractable for kernelized SVMs. The results on two different QA datasets, e.g., Answerbag and Jeopardy! data, show that our models deliver large improvement on passage re-ranking tasks, reducing the error in Recall of BM25 baseline by about 18%. One of the key findings of this work is that, despite its simplicity, shallow syntactic trees allow for learning complex relational structures, which exhibits a steep learning curve with the increase in the training size.
Developing Population Codes by Minimizing Description Length

The Minimum Description Length principle (MDL) can be used to train the hidden units of a neural network to extract a representation that is cheap to describe but nonetheless allows the input to be reconstructed accurately. We show how MDL can be used to develop highly redundant population codes. Each hidden unit has a location in a low-dimensional implicit space. If the hidden unit activities form a bump of a standard shape in this space, they can be cheaply encoded by the center ofthis bump. So the weights from the input units to the hidden units in an autoencoder are trained to make the activities form a standard bump. The coordinates of the hidden units in the implicit space are also learned, thus allowing flexibility, as the network develops a discontinuous topography when presented with different input classes. Population-coding in a space other than the input enables a network to extract nonlinear higher-order properties of the inputs. Most existing unsupervised learning algorithms can be understood using the Minimum Description Length (MDL) principle (Rissanen, 1989). Given an ensemble of input vectors, the aim of the learning algorithm is to find a method of coding each input vector that minimizes the total cost, in bits, of communicating the input vectors to a receiver. There are three terms in the total description length: • The code-cost is the number of bits required to communicate the code that the algorithm assigns to each input vector.
Development and Dynamic Modeling of a New Hybrid Thermopiezoelectric Microactuator

This paper presents a new hybrid microactuator based on the combination of piezoelectric and thermal effects. The proposed actuator can perform both a high-stroke coarse positioning through the thermal actuation and a high-resolution fine positioning through the piezoelectric actuation. The microactuator structure is a unimorph piezoelectric cantilever, which also constitutes a thermal bimorph that is very sensitive to temperature variation. While electrical voltage is used to control the piezoelectric actuation, we use a Peltier module to provide the temperature variation and to control the thermal functioning. In order to understand the behavior of the hybrid actuator, a model is developed. For better precision, but at the same time for model simplicity, the thermal part is modeled with the thermal network, whereas the Prandtl-Ishlinskii (PI) hysteresis approach is used to model the nonlinearity of the piezoelectric part. Finally, a series of experimental results validate the developed model.
The Induction Levels of Heat Shock Protein 70 Differentiate the Vulnerabilities to Mutant Huntingtin among Neuronal Subtypes

The reason why vulnerabilities to mutant polyglutamine (polyQ) proteins are different among neuronal subtypes is mostly unknown. In this study, we compared the gene expression profiles of three types of primary neurons expressing huntingtin (htt) or ataxin-1. We found that heat shock protein 70 (hsp70), a well known chaperone molecule protecting neurons in the polyQ pathology, was dramatically upregulated only by mutant htt and selectively in the granule cells of the cerebellum. Granule cells, which are insensitive to degeneration in the human Huntington's disease (HD) pathology, lost their resistance by suppressing hsp70 with siRNA, whereas cortical neurons, affected in human HD, gained resistance by overexpressing hsp70. This indicates that induction levels of hsp70 are a critical factor for determining vulnerabilities to mutant htt among neuronal subtypes. CAT (chloramphenicol acetyltransferase) assays showed that CBF (CCAAT box binding factor, CCAAT/enhancer binding protein ζ) activated, but p53 repressed transcription of the hsp70 gene in granule cells. Basal and mutant htt-induced expression levels of p53 were remarkably lower in granule cells than in cortical neurons, suggesting that different magnitudes of p53 are linked to distinct induction levels of hsp70. Surprisingly, however, heat shock factor 1 was not activated in granule cells by mutant htt. Collectively, different levels of hsp70 among neuronal subtypes might be involved in selective neuronal death in the HD pathology.