Miracle-dz/UniFAR-FTUs huggingface dataset:
Audio and Visual Rendering with Perceptual Foundations

Realistic visual and audio rendering still remains a technical challenge. Indeed, typical computers do not cope with the increasing complexity of today's virtual environments, both for audio and visuals, and the graphic design of such scenes require talented artists. In the first part of this thesis, we focus on audiovisual rendering algorithms for complex virtual environments which we improve using human perception of combined audio and visual cues. In particular, we developed a full perceptual audiovisual rendering engine integrating an efficient impact sounds rendering improved by using our perception of audiovisual simultaneity, a way to cluster sound sources using human's spatial tolerance between a sound and its visual representation, and a combined level of detail mechanism for both audio and visuals varying the impact sounds quality and the visually rendered material quality of the objects. All our crossmodal effects were supported by the prior work in neuroscience and demonstrated using our own experiments in virtual environments. In a second part, we use information present in photographs in order to guide a visual rendering. We thus provide two different tools to assist “casual artists” such as gamers, or engineers. The first extracts the visual hair appearance from a photograph thus allowing the rapid customization of avatars in virtual environments. The second allows for a fast previewing of 3D scenes reproducing the appearance of an input photograph following a user's 3D sketch. We thus propose a first step toward crossmodal audiovisual rendering algorithms and develop practical tools for non expert users to create virtual worlds using photograph's appearance.
Measuring grief and loss after spinal cord injury: Development, validation and psychometric characteristics of the SCI-QOL Grief and Loss item bank and short form

Abstract Objective To develop an item response theory (IRT) calibrated Grief and Loss item bank as part of the Spinal Cord Injury – Quality of Life (SCI-QOL) measurement system. Design A literature review guided framework development of grief/loss. New items were created from focus groups. Items were revised based on expert review and patient feedback and were then field tested. Analyses included confirmatory factor analysis (CFA), graded response IRT modeling and evaluation of differential item functioning (DIF). Setting We tested a 20-item pool at several rehabilitation centers across the United States, including the University of Michigan, Kessler Foundation, Rehabilitation Institute of Chicago, the University of Washington, Craig Hospital and the James J. Peters/Bronx Department of Veterans Affairs hospital. Participants A total of 717 individuals with SCI answered the grief and loss questions. Results The final calibrated item bank resulted in 17 retained items. A unidimensional model was observed (CFI = 0.976; RMSEA = 0.078) and measurement precision was good (theta range between −1.48 to 2.48). Ten items were flagged for DIF, however, after examination of effect sizes found this to be negligible with little practical impact on score estimates. Conclusions This study indicates that the SCI-QOL Grief and Loss item bank represents a psychometrically robust measurement tool. Short form items are also suggested and computer adaptive tests are available.
Emphysematous Cystitis in a Chemically-Induced Diabetic Dog

Emphysematous cystitis is a rare disorder caused by bacterial infection and characterized by gas accumulation within the bladder wall with cyst formation. This report describes the histopathological characteristics of emphysematous cystitis found in a diabetic female beagle induced by streptozotocin and alloxan. Macroscopically, multiple cyst-like structures were observed on the cut surface of the urinary mucosa. During fixation, small specimens cut from the mucosa floated on the surface of the fixative solution. Histopathologically, multiple cysts were lined with a single layer of flattened cells found to be immunohistochemically positive for vimentin, partially positive for α-smooth muscle actin or macrophage scavenger receptor, class A, and thought to be myofibroblasts, fibroblasts or macrophages. Multinucleated giant cells were observed around the cysts, and gram-negative short bacilli were observed in the lumen of the urinary bladder. From these findings, this case was diagnosed as emphysematous cystitis.
The implementation of turbo decoder on DSP in W-CDMA system

This paper describes the design and implementation of turbo decoder which has been selected for 3G mobile systems on TMS320C6201 DSP developed by Texas Instruments (TI) in 1998. With the incomparable operating speed, which is 200 MHz (5-ns cycle time), TMS320C6201 DSP can achieve the performance of up to 1600 million instructions per second (MIPS) and consequently has gained more and more popularity in many applications. In this paper a turbo decoder is implemented on the TMS320C6201 evaluation module(EVM) board with the code rate 1/3. To every step of the algorithm, we discussed the optimized C code and the minimum cycle time of CPU (best situation of the theory), and get pleasant decoding speed.
Streaming k-means on well-clusterable data

One of the central problems in data-analysis is k-means clustering. In recent years, considerable attention in the literature addressed the streaming variant of this problem, culminating in a series of results (Har-Peled and Mazumdar; Frahling and Sohler; Frahling, Monemizadeh, and Sohler; Chen) that produced a (1 + ε)-approximation for k-means clustering in the streaming setting. Unfortunately, since optimizing the k-means objective is Max-SNP hard, all algorithms that achieve a (1 + ε)-approximation must take time exponential in k unless P=NP. Thus, to avoid exponential dependence on k, some additional assumptions must be made to guarantee high quality approximation and polynomial running time. A recent paper of Ostrovsky, Rabani, Schulman, and Swamy (FOCS 2006) introduced the very natural assumption of data separability: the assumption closely reflects how k-means is used in practice and allowed the authors to create a high-quality approximation for k-means clustering in the non-streaming setting with polynomial running time even for large values of k. Their work left open a natural and important question: are similar results possible in a streaming setting? This is the question we answer in this paper, albeit using substantially different techniques. We show a near-optimal streaming approximation algorithm for k-means in high-dimensional Euclidean space with sublinear memory and a single pass, under the same data separability assumption. Our algorithm offers significant improvements in both space and running time over previous work while yielding asymptotically best-possible performance (assuming that the running time must be fully polynomial and P ≠ NP). The novel techniques we develop along the way imply a number of additional results: we provide a high-probability performance guarantee for online facility location (in contrast, Meyerson's FOCS 2001 algorithm gave bounds only in expectation); we develop a constant approximation method for the general class of semi-metric clustering problems; we improve (even without σ-separability) by a logarithmic factor space requirements for streaming constant-approximation for k-median; finally we design a "re-sampling method" in a streaming setting to convert any constant approximation for clustering to a [1 + O(σ2)]-approximation for σ-separable data.
tDCS for Memory Enhancement: Analysis of the Speculative Aspects of Ethical Issues

Transcranial direct current stimulation (tDCS) is a promising technology to enhance cognitive and physical performance. One of the major areas of interest is the enhancement of memory function in healthy individuals. The early arrival of tDCS on the market for lifestyle uses and cognitive enhancement purposes lead to the voicing of some important ethical concerns, especially because, to date, there are no official guidelines or evaluation procedures to tackle these issues. The aim of this article is to review ethical issues related to uses of tDCS for memory enhancement found in the ethics and neuroscience literature and to evaluate how realistic and scientifically well-founded these concerns are? In order to evaluate how plausible or speculative each issue is, we applied the methodological framework described by Racine et al. (2014) for “informed and reflective” speculation in bioethics. This framework could be succinctly presented as requiring: (1) the explicit acknowledgment of factual assumptions and identification of the value attributed to them; (2) the validation of these assumptions with interdisciplinary literature; and (3) the adoption of a broad perspective to support more comprehensive reflection on normative issues. We identified four major considerations associated with the development of tDCS for memory enhancement: safety, autonomy, justice and authenticity. In order to assess the seriousness and likelihood of harm related to each of these concerns, we analyzed the assumptions underlying the ethical issues, and the level of evidence for each of them. We identified seven distinct assumptions: prevalence, social acceptance, efficacy, ideological stance (bioconservative vs. libertarian), potential for misuse, long term side effects, and the delivery of complete and clear information. We conclude that ethical discussion about memory enhancement via tDCS sometimes involves undue speculation, and closer attention to scientific and social facts would bring a more nuanced analysis. At this time, the most realistic concerns are related to safety and violation of users’ autonomy by a breach of informed consent, as potential immediate and long-term health risks to private users remain unknown or not well defined. Clear and complete information about these risks must be provided to research participants and consumers of tDCS products or related services. Broader public education initiatives and warnings would also be worthwhile to reach those who are constructing their own tDCS devices.
Good-Enough Security: Toward a Pragmatic Business-Driven Discipline

Today, security is a major concern at the top corporate, government, and academic levels, and security problems in cyberspace are unlikely to disappear or be solved any time soon. Indeed, new problems and requirements are likely to emerge, and we can anticipate continued interest in the field. The author discusses user friendly security and considers business-driven security.
Future challenges in efficiently supporting M 2 M in LTE standards

This chapter will describes some of the key challenges that are faced to make LTE suitable for Machine-to-machine (M2M) communications. These are related to handling large number of devices, attaining very low energy consumption, ensuring low-complexity protocols to bring down the cost of devices, and extending coverage to facilitate one-hop transmissions. Beyond being technical feasible, any network optimization must be approved by network operators; therefore, an additional techno-economic perspective will be presented in this chapter. Business related requirements and implications that emerge from the traffic mix (humans and machines) will also be covered, including scalability and deployment cost issues, as well as migration options from current solutions.
Clarithromycin-induced rhabdomyolysis: a case report

Rhabdomyolysis is a clinical and laboratory syndrome that is caused by various etiologies, involving the skeletal muscle. Clarithromycin, like other macrolides, is an inhibitor of CYP450 3A4, the major enzyme responsible for the metabolism of several drugs, in particular some statins. Rhabdomyolysis related to macrolide–statin interaction has previously been described. To date, rhabdomyolysis induced by clarithromycin has been described in only one previous report. We describe the case of a 90-year-old Caucasian male, admitted to the University Hospital of Pisa for dyspnea, who developed rhabdomyolysis associated with clarithromycin administration.
Neural network based threat assessment for automated visual surveillance

In automated visual surveillance systems (AVSS), reliable detection of suspicious human behavior is of great practical importance. Many conventional classifiers have shown to perform inadequately because of unpredictable nature of human behavior. Flexible models such as artificial neural network (ANN) models can perform better; however, computational requirement of ANN models can be prohibitively large for realtime video processing. It is interesting to construct a small-sized ANN classifier that can perform well for threat assessment in video-based surveillance system. In this paper, modified probabilistic neural network (MPNN) is introduced that can achieve reliable classification, with significantly reduced computation. Experiment on visual surveillance application shows that MPNN achieves good classification but with much reduced computation compared to other ANN models. In this application, trajectory profile and motion history image information from the observed human subject are used for threat assessment.
A System Dynamic Model of Drinking Events: Multi‐Level Ecological Approach

Drinking events are dynamic. The interactions of individuals, groups, and the environment as they relate to drinking behaviour are overwhelmingly complex. This paper presents an empirically grounded dynamic conceptual model to better understand drinking events. Using a collaborative mixedâ€ methods approach, we developed an aggregated system dynamic model of drinking events. The process began with identification of system elements and boundaries. Once the first aspects of the model were completed, we constructed a causal loop diagram, an aggregated causal loop diagram, and stock and flow diagrams. Finally, we developed and ran computer simulations of the dynamical models. The model presented here can be used to guide future agentâ€ based, system dynamics, or differential equationâ€ based models. Such models can help inform future empirical work and modelling to increase the understanding of drinking events and provide solutions to the problems that happen proximal to these events. Copyright Â© 2018 John Wiley & Sons, Ltd.
A stimulatory TSH receptor antibody enhances adipogenesis via phosphoinositide 3-kinase activation in orbital preadipocytes from patients with Graves' ophthalmopathy

Graves' ophthalmopathy (GO) is characterized by expanded volume of the orbital tissues associated with elevated serum levels of TSH receptor (TSHR) autoantibodies. Because previous studies have demonstrated evidence of adipogenesis within the GO orbit, we sought to determine whether M22, a human monoclonal antibody directed against TSHR, enhances adipogenesis in orbital fibroblasts from patients with GO and, if so, to identify signaling mechanisms involved. GO orbital fibroblast cultures (n=10) were treated for 10 days with bovine TSH (1 or 10·0 U/l) or M22 (1 or 10 ng/ml) in serum-free adipocyte differentiation medium. Some cultures also received a phosphoinositide 3-kinase (PI3K) inhibitor or an inhibitor of cAMP production. In other experiments, confluent cultures (n=8) were treated for between 1 and 30 min with TSH (0·1–10·0 U/l) or M22 (0·1–100 ng/ml) with measurement of cAMP production or levels of phosphorylated AKT (pAKT). We found levels of adiponectin, leptin, and TSHR mRNA to be increased in GO cultures treated for 10 days with either M22 (2·6 mean fold ±0·7; P=0·03) or TSH (13·2±5·8-fold, P=0·048). In other studies, M22 and TSH stimulated cAMP production and pAKT levels in GO cells. Inhibition of PI3K activity during 10 days in culture decreased the levels of M22-stimulated mRNA encoding adiponectin (67±12%; P=0·021), as well as adiponectin and CCAAT/enhancer-binding protein α protein levels. In conclusion, M22 is a pro-adipogenic factor in GO orbital preadipocytes. This antibody appears to act via the PI3K signaling cascade, suggesting that inhibition of PI3K signaling may represent a potential novel therapeutic approach in GO.
Data warehouse architecture and design

A data warehouse is attractive as the main repository of an organization’s historical data and is optimized for reporting and analysis. In this paper, we present a data warehouse the process of data warehouse architecture development and design. We highlight the different aspects to be considered in building a data warehouse. These range from data store characteristics to data modeling and the principles to be considered for effective data warehouse architecture.
Incorporating QoS Awareness in Routing Metrics for Wireless Mesh Networks

Wireless mesh networks (WMNs) consist of mesh clients that can be either stationary or mobile, and static mesh routers through which the clients communicate with each other and with the Internet or other networks. Wireless mesh networks have established their presence with a promise of supporting variegated traffic ranging from real-time to best- effort while providing coverage to large metropolitan areas. Multihop communication, the existence of inherently error- prone wireless channel, the static nature of mesh nodes, the availability of sufficient bandwidth resources and the need to transport multimedia traffic with different QoS budgets necessitate the design of QoS-aware routing metrics to improve the performance of routing algorithms. We study the motivations for new and quality-aware routing metrics and provide a detailed comparative analysis supported by NS-2 simulations of some routing metrics that attempt to address these goals. The routing metrics we compare include the traditional shortest-hop, ETX (Expected Transmission Count), ML (Minimum Loss) and MD (Minimum Delay). We observe that ETX improves throughput while MD reduces delay for different packet rates, proving that the right metric should be chosen based on user requirements.
Supranormal Stimulation of D 1 Dopamine Receptors in the Rodent Prefrontal Cortex Impairs Spatial Working Memory Performance

Although previous research has emphasized the beneficial effects of dopamine (DA) on functions of the prefrontal cortex (PFC), recent studies of animals exposed to mild stress indicate that excessive DA receptor stimulation may be detrimental to the spatial working memory functions of the PFC (Arnsten and Goldman-Rakic, 1990; Murphy et al., 1994, 1996a,b, 1997). In particular, these studies have suggested that supranormal stimulation of D1 receptors may contribute to the detrimental actions of DA in the PFC (Murphy et al., 1994, 1996a). The current study directly tested this hypothesis by examining the effects of infusing a full D1 receptor agonist, SKF 81297, into the PFC of rats performing a spatial working memory task, delayed alternation. SKF 81297 produced a dose-related impairment in delayed-alternation performance. The impairment was reversed by pretreatment with a D1 receptor antagonist, SCH 23390, consistent with drug actions at D1 receptors. SCH 23390 by itself had no effect on performance, although slightly higher doses impaired performance (Murphy et al., 1994, 1996a). There was a significant relationship between infusion location and drug efficacy; animals with cannulae anterior to the PFC were not impaired by SKF 81297 infusions. Taken together, these results demonstrate that supranormal D1 receptor stimulation in the PFC is sufficient to impair PFC working memory function. These cognitive data are consistent with recent electrophysiological studies of D1 receptor mechanisms affecting the PFC (Williams and Goldman-Rakic, 1995; Yang and Seamans, 1996). Increased D1 receptor stimulation during stress may serve to take the PFC “off-line” to allow posterior cortical and subcortical structures to regulate behavior, but may contribute to the vulnerability of the PFC in many neuropsychiatric disorders.
Relations between implicit and explicit measures of personality - prospects of Implicit Association Test (IAT) in assessment of basic personality traits

Introduction. The core idea behind the Implicit Association Test (IAT) is to obtain information that are not the result of controlled processes. Therefore, it is considered a technique with the potential to overcome some disadvantages of explicit measures, such as socially desirable responding. IAT consists of a task of double categorization whereby the respondents have to sort the stimuli belonging to superordinated categories. Study objective. The main objective of the study was to investigate the convergent and discriminative validity of IAT in the assessment of basic personality traits. Method. To investigate the relations between the implicit and explicit measures, Implicit Association Tests, several self-report measures, ratings by close others, and measures of cognitive abilities were administered to a sample of 224 university students at Belgrade University. Ratings by experts and linguistic measures were collected from a subsample of 99 subjects. The respondents completed the personality IAT, NEO-PIR and DELTA10 (S and R form), a short scale of attributes (DOCEAN), a short questionnaire for the assessment of relevant moderator variables, KOG9 battery test for the assessment of intellectual abilities, and self-assessment of intellectual abilities. In addition, they were observed by experts in structured interviews, in which linguistic parameters were collected through an automatic text analysis (LIWC). Results. The correlations between the self-reported and IAT Neuroticism (0.17) and Extraversion (0.16) were found to be small but significant (p<0.05). However, none of the paths from the personality IAT to the corresponding latent traits in SEM Correlated-Traits-Correlated-Uniqueness-MTMM-Model was significant. The model had the excellent fit: c2=338.18, p=0.00; RMSEA=0.042 (90% CI RMSEA 0.031- 0.053), SRMR=0.066 and CFI=0.96. The MTMM analyses on a subsample of 99 respondents, from which behavioural measures were collected, demonstrated relations iv between IAT and the parameters collected with automatic text analysis (LIWC). Subsequent analyses demonstrated a strong divergence between implicit and explicit method factors. Conclusion. Study has shown that the personality IAT measures have little in common with personality traits measured by the traditional self-report inventories or rating scales. However, MTMM analysis provides evidence about the predictive validity of IAT in spontaneous verbal behaviour.
The Use of Dependenoy Relationships in the Control of Reasoning by

Several recent problem-solving programs have indicated improved methods for controlling program actions. Some of these methods operate by analyzing the time-independent antecedent-consequent dependency relationships between the components of knowledge about the problem for solution. This paper is a revised version of a thesis proposal which indicates how a general system of automatically maintained dependency relationships can be used to effect many forms of control on reasoning in an antecedent reasoning framework. *Fannie and John Hertz Foundation Graduate Fellow Research reported herein was conducted at the Artificial Intelligence Laboratory, a Massachusetts Institute of Technology research program supported in part by the Advanced Research Projects Agency of the Department of Defense and monitored by the Office of Naval Research under contract N00014-75-C-0643. Workitg Papers are tnformal papers tntended for tnternal use. Devendencies and Control Jon DoYle Section