Miracle-dz/UniFAR-FTUs huggingface dataset:
MedEthEx: A Prototype Medical Ethics Advisor

As part of a larger Machine Ethics Project, we are developing an ethical advisor that provides guidance to health care workers faced with ethical dilemmas. MedEthEx is an implementation of Beauchamp's and Childress' Principles of Biomedical Ethics that harnesses machine learning techniques to abstract decision principles from cases in a particular type of dilemma with conflicting prima facie duties and uses these principles to determine the correct course of action in similar and new cases. We believe that accomplishing this will be a useful first step towards creating machines that can interact with those in need of health care in a way that is sensitive to ethical issues that may arise.
Laser Antimissile System Strategy Optimization Based on Genetic Algorithm

The attacking sequence optimization of laser antimissile system plays an important role in the real-time application. When faced with multiple attacking targets, it is clearly important for the laser antimissile system to determine the sequence of the attacking targets to be intercepted so that the maximum attacking targets are destroyed. Conceptually, this laser antimissile problem can be seen as a dynamical traveling salesman problem, which is much harder than a pure traveling salesman problem. In fact, it is a dynamical shortest path problem. But there are many barriers for finding the global optimal solution, especially when the number of the targets is greater than six. The dynamical inversion algorithm includes the inner flip and the outer flip; it partially solves the premature convergence problem. Finally, taking eight targets as an example, the simulation results show that the convergence of the algorithm is very fast and this achievement can be used in the real application.
The Fallacy of the 50 % Concordance Rate for Schizophrenia in Identical Twins

The common practice of treating psychiatric conditions with medications is justified by the belief that mental illnesses are the result of underlying biological deficits. Genetic research is one avenue of research that is frequently cited as proof in support of this belief; and, in turn, one of the most commonly cited pieces of genetic evidence is the concordance rate for identical twins diagnosed with schizophrenia. When discussing schizophrenia twin studies psychiatrists often report a 45%-50% concordance rate for identical twins, compared to only a 15% concordance rate for fraternal twins. These numbers which are often cited in psychiatry textbooks, peer reviewed papers, magazine articles, speeches and even newspaper articles are generally considered the most important piece of evidence supporting the biological theory of schizophrenia—and even as evidence that mental illnesses in general are biologically based. Concerning the genetic theory of schizophrenia, the most recent edition of the neuroscience textbook Fundamental Neuroscience by Squire et al. (2003) states, “The most compelling evidence is the 50% concordance rate for monozygotic twins relative to the 15% concordance for dizygotic twins” (Rapp and Bachevalier, 2003, p. 1193). A new book The Gene Illusion, by Jay Joseph shatters the validity of this statement and leaves the most commonly mentioned statistic in psychiatry in tatters. Joseph’s book is an analysis of psychiatric genetic research and covers topics such as the heritability concept, the genetics of IQ, the genetics of criminality, the schizophrenia adoption studies—but his most devastating criticism is of the schizophrenia twin studies (Joseph, 2003). It is hard to find any defense of biological psychiatry that does not mention the schizophrenia twin research. As just one example, Steven Hyman, the former-chairman of NIMH, appeared before President George Bush’s Commission on Bioethics for the purpose of defending the meteoric rise in the use of Ritalin
Triptolide Preserves Cognitive Function and Reduces Neuropathology in a Mouse Model of Alzheimer's Disease

Triptolide, a major bioactive ingredient of a widely used herbal medicine, has been shown to possess multiple pharmacological functions, including potential neuroprotective effects pertinent to Alzheimer's disease (AD) in vitro. However, the therapeutic potential of triptolide for AD in vivo has not been thoroughly evaluated. In the present study, we investigated the impact of peripherally administered triptolide on AD-related behavior and neuropathology in APPswe/PS1ΔE9 (APP/PS1) mice, an established model of AD. Our results showed that two-month treatment with triptolide rescued cognitive function in APP/PS1 mice. Immunohistochemical analyses indicated that triptolide treatment led to a significant decrease in amyloid-β (Aβ) deposition and neuroinflammation in treated mice. In contrast to previous findings in vitro, biochemical analyses showed that triptolide treatment did not significantly affect the production pathway of Aβ in vivo. Intriguingly, further analyses revealed that triptolide treatment upregulated the level of insulin-degrading enzyme, a major Aβ-degrading enzyme in the brain, indicating that triptolide treatment reduced Aβ pathology by enhancing the proteolytic degradation of Aβ. Our findings demonstrate that triptolide treatment ameliorates key behavioral and neuropathological changes found in AD, suggesting that triptolide may serve as a potential therapeutic agent for AD.
Transient epileptic amnesia: a description of the clinical and neuropsychological features in 10 cases and a review of the literature

OBJECTIVES To clarify the clinical and neuropsychological aspects of transient epileptic amnesia (TEA) based on 10 personally studied cases as well as review of 21 previously published cases; and to propose tentative diagnostic criteria for the diagnosis of TEA. METHODS All 10 patients and informants underwent a standardised clinical interview. The radiological and neurophysiological (EEG) data were also reviewed in all cases. The diagnosis of transient epileptic amnesia was made on the basis of the following criteria: (1) there was a history of recurrent witnessed episodes of transient amnesia; (2) cognitive functions other than memory were judged to be intact during typical episodes by a reliable witness; (3) there was evidence for a diagnosis of epilepsy. This evidence was provided by either (a) wake or sleep EEG, or (b) the co-occurrence of other seizure types (if their roughly concurrent onset or close association with episodes of transient amnesia suggested a connection), or (c) a clear cut response to anticonvulsant therapy, or by a combination of these three factors. In addition all patients were administered a comprehensive neuropsychological test battery designed to assess verbal and non-verbal anterograde memory and retrograde memory for famous personalities and personal events. Their results were compared with those of 25 age and IQ matched normal controls. RESULTS TEA usually begins in later life, with a mean age of 65 years in this series. Episodes are typically brief, lasting less than one hour, and recurrent, with a mean frequency of three a year. Attacks on waking are characteristic. Repetitive questioning occurs commonly during attacks. The anterograde amnesia during episodes is, however, often incomplete so that patients may later be able to “remember not being able to remember”. The extent of the retrograde amnesia during attacks varies from days to years. Most patients experience other seizure types compatible with an origin in the temporal lobes, but transient amnesia is the only manifestation of epilepsy in about one third of patients. Epileptiform abnormalities arising from the temporal lobes are most often detected on interictal sleep EEG. Despite normal performance on tests of anterograde memory, many patients complain of persistent interictal disturbance of autobiographical memory, involving a significant but variable loss of recall for salient personal episodes. The epochs affected may predate the onset of epilepsy by many years. CONCLUSIONS TEA is an identifiable syndrome and comprises episodic transient amnesia with an epileptic basis, without impairment of other aspects of cognitive function. Future studies should consider the question of whether TEA reflects ictal activity or a postictal state, and the mechanism of the persistent autobiographical amnesia. It is hypothesised that the latter may result in part from impairment of very long term memory consolidation as a result of epileptic activity in mesial temporal structures.
Minimum-Power Routing in Wireless Ad Hoc Networks 1 Introduction

One of the major concerns in ad hoc wireless networks is reducing node energy consumption. For the purpose of energy conservation, each node can (possibly dynamically) adjust its transmitting power, based on the distance to the receiving node and the background noise. In the most common power-attenuation model [10], the signal power falls as 1 dκ where d is the Euclidean distance from the transmitter antenna and κ is the pass-loss exponent of the wireless environment–a real constant typically between 2 and 5. Assume that all nodes have the same power threshold for signal detection, which is typically normalized to one. Then, the power required to cover a transmission range of radius d is dκ. To simplify the problem, we assume that all nodes have the same maximum transmission range R. We use V to denote the set of nodes, and G = (V,E, c) be the weighted graph such that for any pair of nodes u and v, uv ∈ E if and only if ‖uv‖ ≤ R, and the weight of an edge uv is c (uv) = ‖uv‖. We assume that the graph G is connected. We use − → G to denote the weighted directed graph which is directed version of G.
Real-time soft shadow mapping by backprojection

We present a new real-time soft shadow algorithm using a single shadow map per light source. Therefore, our algorithm is well suited to render both complex and dynamic scenes, and it handles all rasterizable geometries. The key idea of our method is to use the shadow map as a simple and uniform discretized represention of the scene, thus allowing us to generate realistic soft shadows in most cases. In particular it naturally handles occluder fusion. Also, our algorithm deals with rectangular light sources as well as textured light sources with high precision, and it maps well to programmable graphics hardware.
Smart Phone User Behaviour Characterization Based on Autoencoders and Self Organizing Maps

Building applications that are cognizant of temporal and spatial changes in human behaviour under a one-class learning restriction represents a requirement for many user centric systems. We are particularly motivated to demonstrate the utility of algorithms for the self identification of smart phones. A framework is designed to quantify: (i) the dissimilarity in behaviours among any two users, (ii) the exclusivity of each user's behaviour (inclass) from the world (outclass). A central element of the proposed framework is to first identify a discriminating representation for each user. To this end, an autoencoder is employed in which the goal is to identify an encoding that rebuilds the original data with maximum accuracy/ least loss. The hypothesis of this work is that such an autoencoding step provides an effective mechanism for discovering good data representations prior to the application of a data description technique, such as clustering. Both the autoencoder and the clustering steps are performed relative to a single user. We construct a user specific behavioural model using the most frequently used applications, cell towers and websites. We demonstrate that relative to the most up-to-date publicly available smart phone data set, the resulting behavioural models are capable of uniquely identifying each user under a one-class learning constraint.
Projected Sequential Gaussian Processes : A C + + tool for interpolation of heterogeneous data sets

Within MUCM there might occasionally arise the need to use large training set sizes, or employ observations with non-Gaussian noise characteristics or non-linear sensor models in a calibration stage. This technical report deals with Gaussian process models in these non-Gaussian, and / or large data set size cases. Treating such data within Gaussian processes is most naturally accomplished using a Bayesian approach, however such methods generally scale rather badly with the size of data set, and require computationally expensive Monte Carlo based inference in non-Gaussian settings. Recently within the machine learning and spatial statistics communities many papers have explored the potential of reduced rank representations of the covariance matrix, often referred to as projected or fixed rank approaches. In such methods the covariance function of the posterior process is represented by a reduced rank approximation which is chosen such that there is minimal information loss. In this paper a sequential Bayesian framework for inference in such projected processes is presented. The observations are considered one at a time which avoids the need for high dimensional integrals typically required in a Bayesian approach. A C++ library, psgp, which is part of the INTAMAP web service, is introduced which implements projected, sequential estimation and adds several novel features. In particular the library includes the ability to use a generic observation operator, or sensor model, to permit data fusion. It is also possible to cope with a range of observation error characteristics, including non-Gaussian observation errors. Inference for the covariance parameters is explored, including the impact of the projected process approximation on likelihood profiles. We illustrate the projected sequential method in application to synthetic and real data sets. Limitations and extensions are discussed.
POSTER: trend of online flash XSS vulnerabilities

Flash objects are widely embedded in web pages, supporting Rich Internet Applications using ActionScript. However, according to our survey, many Flash objects are seriously exposed to Cross-site Scripting vulnerabilities as they are usually coded without proper sanitization of their inputs. This becomes a potential danger for cyber users. In this paper, we analyze XSS in online Flash and present an engine FXD (Flash XSS Detector) for automatically scrambling Flash files in web pages and checking whether or not they are vulnerable to XSS. We call vulnerable ActionScript functions "key functions" and divide them into four categories by its functionality. The usability of FXD is further evaluated by disposing it in real-world websites. Our results reveal that at least 48 Flash applications in 18% of Alexa top 100 sites on the web are vulnerable to XSS. Each of these vulnerable Flash objects has been verified and confirmed of their XSS flaws. Finally, we discuss a new trend of Flash XSS, nowadays it is mainly caused by combination of key functions in different categories.
Finite-Settling-Steps Direct Torque and Flux Control for Torque-Controlled Interior PM Motors at Voltage Limits

This paper proposes a voltage-limited finite-settling-step direct torque and flux control (FSS-DTFC) method with a constant switching frequency for torque-controlled interior permanent-magnet synchronous motors (IPMSMs). The proposed control law dynamically scales the voltage vectors on the hexagonal voltage boundary to ensure the maximum torque capabilities under the given operating conditions while simultaneously regulating the stator flux linkage magnitude under flux-weakening operation. Instead of relying on classical overmodulation methods at voltage limits, this paper developed two independent voltage truncation rules to facilitate the possible voltage vector choices. The analytical solution led to the dynamic voltage modification at each time step with respect to the available inverter voltage. The voltage-limited FSS-DTFC approach has potential advantages in achieving a fast transient torque trajectory and direct manipulation of the stator flux linkage while exploiting the maximum voltage excitation.
Learning Experiences and Perspective Transformation in Evangelical Faith-Based Adult Nonformal Education Programs

The study adapted an existing instrument to examine perspective transformation and its associated factors in participants of evangelical faith-based adult nonformal education in the Midwestern United States. Stratified random one-stage cluster sampling of 11 churches produced a nonprobability sample (N = 597) that was significantly (p < .05) different from the population of the geographical location of the study. An 86% majority self-reported a level of agreement or stronger of perceived transformation of perspectives, but differences predicted by gender were insignificant. The difference in perceived perspective transformations between respondents aged 40-59 that had the highest levels and respondents aged 60 and above that had the lowest levels was significant. The factors of influential individuals, personal reflection, and thought-provoking learning assignments significantly predicted all four factors of perspective transformation; the Writing Assignment factor was a significant negative predictor of only the Perception of Change factor, and a significant positive predictor of only the Future Benefits factor. The study recommended that additional research on faith-based frames of reference and age category differences. The study also recommended that faith-based practitioners consider emphasizing transformative learning experiences and personal reflection in their programs for
Software Process Improvement Framework Based on CMMI Continuous Model Using QFD

In the rapid technological innovation and changes era, the key to the survival company is the continuous improvement of its process. In this paper, we introduce Software Process Improvement (SPI) and Quality Function Deployment (QFD); and for combining also the staged model and the continuous model in CMMI, the Software Process Improvement framework with CMMI has two parts: 1) Software Process Improvement framework with CMMI staged model based on QFD and 2) SPI framework for CMMI based on QFD continuous model. Finally, we also draw conclusions.
Acupoints Stimulation for Anxiety and Depression in Cancer Patients: A Quantitative Synthesis of Randomized Controlled Trials

This study aims at concluding the current evidence on the therapeutic effects of acupoints stimulation for cancer patients with anxiety and depression. Randomized controlled trials using acupoints stimulation for relieving anxiety and/or depression in cancer patients were searched, and 11 studies were finally included, of which eight trials compared acupoints stimulation with standard methods of treatment/care, and acupoints stimulation showed significantly better effects in improving depression than using standard methods of treatment/care. Four studies compared true acupoints stimulation with sham methods, and no significant differences can be found between groups for either depression or anxiety, although the pooled effects still favored true intervention. For the five studies that evaluated sleep quality, the results were conflicting, with three supporting the superiority of acupoints stimulation in improving sleep quality and two demonstrating no differences across groups. Acupoints stimulation seems to be an effective approach in relieving depression and anxiety in cancer patients, and placebo effects may partially contribute to the benefits. However, the evidence is not conclusive due to the limited number of included studies and the clinical heterogeneity identified among trials. More rigorous designed randomized, sham-controlled studies are necessary in future research.
Automated Planning for Self-Adaptive Systems

Self-adaptation has been proposed as a viable solution to alleviate the management burden that is induced by the dynamic nature and increasing complexity of computer systems. In this context, architectural-based self-adaptation has emerged as one of the most promising approaches to automatically manage such systems, resorting to a control loop that includes monitoring, analyzing, planning, and executing adequate actions. This work addresses the challenges of adaptation planning -the decision-making process for selecting an appropriate course of action- with a focus on the problem of provisioning automated mechanisms for assembling adaptation plans, as a means to enhance adaptive capabilities under uncertainty. To this purpose, adaptations are modeled in a hierarchical manner, defining primitive actions, guarded actions, and deliberate plans, which may guide the system towards a desired state.
VFC-BOX : A Multi-user System For Consistent File Sharing

Computer assisted collaborative work has been motivating the design and implementation of systems capable of e ciently sharing and storing data. This document provides an overview of the current state-of-the-art technologies to e ciently share and store data. Further, it focuses on the ability of systems to use the interest of collaborators over parts of the shared information in order to reduce the use of network resources and shrink the data's latency seen by users. Relevant systems are presented and discussed, indicating their main advantages and disadvantages. Finally, this document presents an overview of the preliminary VFC-BOX architecture. VFC-BOX is a multi-user consistent le sharing system, based on deduplication techniques and a consistency model that takes into account the interest management (or localityawareness) of a user. Through these techniques, this system may achieve higher performances w.r. t. data transfer/synchronization and storage.
SREM at the Age of Eight; The Distributed Computing Design System

SREM has been extended. Now a requirements-driven modelfor integrated software engineering environments, SREM has new tools to support its application, the Distributed Computing Design System. Since its development and initial presentation in 1976, Software Requirements Engineering Methodology, or SREM, technology has evolved in both application and research. ' The methodology and tools have matured to a point where they are being used on a variety of projects at a number of different locations; the research that led to SREM has been extended to address the problems of specifying system-level requirements and defining a distributed or uniprocessor design that satisfies requirements generated with SREM. This article overviews developments in these areas and summarizes their results. It also describes the origins of SREM, its basic model of requirements, and how the model is implemented in RSL, the Requirements Statement Language, and supporting software.
Turkish word segmentation using morphological analyzer

This paper describes an algorithm to segment an input Turkish string without any spaces, which may be an output of a speech-to-text application, into words by using morphological analyzer. It is quite possible to use the algorithm on other languages, which has a morphological analysis component, as well. Turkish morphological analyzer is designed and implemented as the linguistic engine of the algorithm. The construction of the analyzer proposes a technique that attempts to achieve group vise morpheme recognition instead of searching suffixes one by one in a word.