Miracle-dz/UniFAR-FTUs huggingface dataset:
Common genetic risk factors for psychiatric and simatic disorders

There is increasing knowledge about considerable comorbidity between psychiatric and somatic diseases, questioning whether variations in genes could be predisposing factors for both conditions. With respect to the multiple interactions between brain and body investigations have centered on variants in several candidate genes for proteins that mediate these interactions and therefore also have implications in psychiatric disorders. The available data, although still preliminary and rare, indicate the importance of polymorphic variants in genes coding for the serotonin (5-hydroxytryptamine, 5-HT) transporter (5-HTT), the 5-HT2A receptor, proinflammatory cytokines, and the angiotensin-converting enzyme (ACE) in migraine, fibromyalgia, cardiovascular disorders, and psychiatric conditions. The role played by these various polymorphisms remains to be determined, as does whether they are indicative of common pathophysiological mechanisms or identify a subgroup of patients with somatic disorders that are more closely related to psychiatric symptoms. Nevertheless, they do at least illustrate the potential influence of genetic differences on illness course and treatment outcome, and might be a rational approach to drug development and treatment paradigms.
Effects of Variable Viscosity and Thermal Conductivity on Micropolar Fluid Flow Due to a Stretching Cylinder in Presence of Magnetic Field

In the presence of magnetic field, steady flow of a micropolar fluid due to a stretching cylinder is studied. Viscosity and thermal conductivity are assumed to be inverse linear functions of temperature. The governing partial differential equations are converted into ordinary differential equations using suitable similarity transformations and then solved by fourth order Runge-Kutta shooting method and developing Matlab programme. The graphs show the effects of different parameters and the skin friction coefficient and Nusselt numbers are shown in tabular form.
The relationship of multimodal executive function measurement and associated neuroanatomical factors in preschoolers born very low birth weight and full term

Objective: The current study investigated executive function (EF) in preschoolers born very low birth weight (VLBW) and full term by examining the dimensionality of EF and the relationship between multimodal measures of EF. Additionally, we investigated the neuroanatomical factors that may relate to EF in this population. Participants and Methods: The sample included 101 preschoolers: 61 VLBW and 40 full term (mean=45.98 months (SD=5.05). EF measures included: Bear Dragon, Gift Touch, Gift Peek, Progressive Executive Categorization Battery, parent rated EF (BRIEF-P), and Child Compliance observational coding. Magnetic resonance imaging (MRI) data were analyzed through voxel-based morphometry (VBM) for a subset of preschoolers Results: As expected, full term preschoolers were found to have higher EF scores than
Of sound, mind, and body: neural explanations for non-categorical phonology

Of sound, mind, and body: Neural explanations for non-categorical phonology by Benjamin Koppel Bergen B.A. (University of California, Berkeley) 1996 M.A. (University of California, Berkeley) 1997 A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Linguistics in the GRADUATE DIVISION of the UNIVERSITY OF CALIFORNIA, BERKELEY Committee in charge: Professor George P. Lakoff, Chair Professor Sharon Inkelas Professor Jerome A. Feldman Fall 2001
The Experiences of White Male Counsellors Who Work with First Nations Clients

This paper describes a qualitative study that investigated the experiences of White male counsellors who work with First Nations clients. Five experienced counsellors participated in individual, tape-recorded interviews, during which they described their experiences, yielding written protocols that were thematically analyzed. Results from this study revealed five predominant themes that included the following: (a) encountering difference, (b) establishing relationships, (c) a willingness to learn, (d) evolving professional identities, and (e) impact on self-awareness. Findings and implications for White counsellors and counsellor educators are included.
Load Shedding: A New Proposal

During overloads in the mains, the load curtailment applied to interruptible loads is often the only solution to keep the network in operation. Normally, in contingencies, the difference between the power absorbed and the power produced is very low, often less than 1% of the latter. Therefore if all the loads participated in the load shedding program, the discomfort would be minimal, considering its usually short duration. According to this point of view, we present a new approach to the load shedding program to guarantee the correct electrical system operation by increasing the number of participants. This new load control strategy is named Distributed Interruptible Load Shedding (DILS). Indeed, it is possible to split every user's load into interruptible and uninterruptible parts, and to operate on the interruptible part only. The optimal load reduction request is found by minimizing the expected value of an appropriate cost function, thus taking the uncertainty about the power absorbed by each customer into account. Presently, several users such as hospitals, data centres, supermarkets, universities, industries, etc. might be very interested in typical shedding programs as a way to spare money in their electrical account. However, in the future, when the domotic power plants are likely to be used widely, the distributors could interest the end users in participating in DILS programs for either economic or social reasons. By adopting the DILS program, the distributors can resort to the interruptible loads not only in case of emergency conditions but also during normal and alert operations.
ARCHON : A DISTRIBUTED ARTIFICIAL INTELLIGENCE SYSTEM FOR INDUSTRIAL APPLICATIONS

ARCHONTM (ARchitecture for Cooperative Heterogeneous ON-line systems) is Europe’s largest project in the area of Distributed Artificial Intelligence (DAI). It has devised a general-purpose architecture, software framework and methodology which has been used to support the development of DAI systems in a number of industrial domains. Some examples of the applications to which it has been successfully applied include: electricity distribution and supply, electricity transmission and distribution, control of a cement kiln complex, control of a particle accelerator, and control of a robotics application. The type of cooperating community that it supports has a decentralised control regime and individual problem solving agents which are large grain, loosely coupled, and semi-autonomous. This paper tackles a broad range of issues related to the application of ARCHON technology to industrial applications. Firstly, it gives the rationale for a DAI approach to industrial applications and highlights the characteristics which typify this important domain. Secondly, the ARCHON framework is detailed with a special emphasis being placed upon the functional and implementation architectures. Thirdly, a preliminary methodology for developing ARCHON communities is sketched. Finally, the application of the software framework and the methodology is illustrated through the development of a DAI system in the electricity distribution domain.
Identification of Potentially Cross-Reactive Peanut-Lupine Proteins by Computer-Assisted Search for Amino Acid Sequence Homology

Background: Allergic cross-reactions are an issue of major concern because of implications for public health. The molecular basis of cross-allergy is the similarity of epitopes belonging to proteins of different organisms. Lupine is an emerging cause of food allergy, which has become a ‘hot topic’ because of recent large-scale introduction into processed foods and frequent cross-reactions with other members of the legume family. However, no lupine allergen has been characterized thus far. Prompted by a recently reported case of peanut-lupine cross-allergy, we wished to identify the possible cross-reactive allergen(s) between the two vegetal species. Methods: We used computer-aided amino acid sequence comparison, a well-established technique for the study of protein homology, and followed the FAO/WHO guidelines for the identification of potential allergens. We also performed a three-dimensional modeling of the suspected cross-reactive proteins to compare their molecular surfaces. Results: We found a highly significant sequence homology and molecular similarity between allergen Ara h 8 of peanut and pathogenesis-related protein PR-10 of white lupine. Another protein of lupine, the β-conglutin precursor, was found to be significantly homologous to the Ara h 1 allergen of peanut. The molecular surfaces of Ara h 8 and PR-10 were remarkably similar. Conclusions: Our in silico data allow to predict the allergenicity of PR-10 and β-conglutin precursor of white lupine according to FAO/WHO guidelines. Amino acid sequence homology also suggests that these proteins could be responsible, at least in part, for some of the allergic cross-reactions between peanut and lupine reported in the literature.
Alkaloid-modified sodium channels from lobster walking leg nerves in planar lipid bilayers

Alkaloid-modified, voltage-dependent sodium channels from lobster walking leg nerves were studied in planar neutral lipid bilayers. In symmetrical 0.5 M NaCl the single channel conductance of veratridine (VTD) (10 pS) was less than that of batrachotoxin (BTX) (16 pS) modified channels. At positive potentials, VTD- but not BTX-modified channels remained open at a flickery substate. VTD-modified channels underwent closures on the order of milliseconds (fast process), seconds (slow process), and minutes. The channel fractional open time (f(o)) due to the fast process, the slow process, and all channel closures (overall f(o)) increased with depolarization. The fast process had a midpoint potential (V(a)) of -122 mV and an apparent gating charge (z(a)) of 2.9, and the slow process had a V(a) of -95 mV and a z(a) of 1.6. The overall f(o) was predominantly determined by closures on the order of minutes, and had a V(a) of about -24 mV and a shallow voltage dependence (z(a) approximately 0.7). Augmenting the VTD concentration increased the overall f(o) without changing the number of detectable channels. However, the occurrence of closures on the order of minutes persisted even at super-saturating concentrations of VTD. The occurrence of these long closures was nonrandom and the level of nonrandomness was usually unaffected by the number of channels, suggesting that channel behavior was nonindependent. BTX-modified channels also underwent closures on the order of milliseconds, seconds, and minutes. Their characterization, however, was complicated by the apparent low BTX binding affinity and by an apparent high binding reversibility (channel disappearance) of BTX to these channels. VTD- but not BTX-modified channels inactivated slowly at high positive potentials (greater than +30 mV). Single channel conductance versus NaCl concentrations saturated at high NaCl concentrations and was non- Langmuirian at low NaCl concentrations. At all NaCl concentrations the conductance of VTD-modified channels was lower than that of BTX- modified channels. However, this difference in conductance decreased as NaCl concentrations neared zero, approaching the same limiting value. The permeability ratio of sodium over potassium obtained under mixed ionic conditions was similar for VTD (2.46)- and BTX (2.48)-modified channels, whereas that obtained under bi-ionic conditions was lower for VTD (1.83)- than for BTX (2.70)-modified channels. Tetrodotoxin blocked these alkaloid-modified channels with an apparent binding affinity in the nanomolar range.
Omega-3 Fatty Acids: Anti-Arrhythmic, Pro-Arrhythmic, or Both?

This review focuses on developments after 2008, when the topic was last reviewed by the author. Pertinent publications were found by medline searches and in the author’s personal data base. Prevention of atrial fibrillation (AF) was investigated in a number of trials, sparked by one positive report on the effects of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), considerations of upstream therapy, data from electrophysiologic laboratories and animal experiments. If EPA + DHA prevent postoperative AF, the effect is probably smaller than initially expected. The same is probably true for maintenance of sinus rhythm after cardioversion and for new-onset AF. Larger trials are currently ongoing. Prevention of ventricular arrhythmias was studied in carriers of an implanted cardioverter-defibrillator, with no clear results. This might have been due to a broad definition of the primary endpoint, including any ventricular arrhythmia and any action of the device. Epidemiologic studies support the contention that high levels of EPA + DHA prevent sudden cardiac death (SCD). However, since SCD is a rare occurrence, it is difficult to conduct an adequately powered trial. In patients with congestive heart failure, EPA + DHA reduced total mortality and rehospitalizations, but not SCD or presumed arrhythmic death. Of three trials in patients after a myocardial infarction, two were inadequately powered, and in one, the dose might have been too low. Taken together, while epidemiologic studies support an inverse relation between EPA + DHA and occurrence of SCD or arrhythmic death, demonstrating this effect in intervention trials remained elusive so far. A pro-arrhythmic effect of EPA + DHA has not been seen in intervention studies, and results of epidemiologic and animal studies also rather argue against such an effect. A different, and probably more productive, perspective is provided by a standardized analytical assessment of a person’s status in EPA + DHA by use of the omega-3 index, EPA + DHA in red cell fatty acids. In populations with a high omega-3 index, SCD is rare. Intervention trials can become more effective by including a low omega-3 index into the inclusion criteria, thus creating a study population more likely to demonstrate an effect of EPA + DHA. This is especially relevant in case of rare endpoints, like new-onset AF or SCD.
A reverse-engineering approach to subsystem structure identification

Reverse-engineering is the process of extracting system abstractions and design information out of existing software systems. This process involves the identification of software artefacts in a particular subject system, the exploration of how these artefacts interact with one another, and their aggregation to form more abstract system representations that facilitate program understanding. This paper describes our approach to creating higher-level abstract representations of a subject system, which involves the identification of related components and dependencies, the construction of layered subsystem structures, and the computation of exact interfaces among subsystems. We show how top-down decompositions of a subject system can be (re)constructed via bottom-up subsystem composition. This process involves identifying groups of building blocks (e.g., variables, procedures, modules, and subsystems) using composition operations based on software engineering principles such as low coupling and high cohesion. The result is an architecture of layered subsystem structures. The structures are manipulated and recorded using the Rigi system, which consists of a distributed graph editor and a parsing system with a central repository. The editor provides graph filters and clustering operations to build and explore subsystem hierarchies interactively. The paper concludes with a detailed, step-by-step analysis of a 30-module software system using Rigi.
Embryonic Stem Cell-Derived Glial Precursors as a Vehicle for Sulfamidase Production in the MPS-IIIA Mouse Brain

Pluripotent stem cells, including human embryonic stem cells and induced pluripotent stem cells, have generated much excitement about their prospects for use in cell transplantation therapies. This is largely attributable to their virtually unlimited growth potential, their ability to be precisely genetically altered in culture, and their utility for forming differentiated cell populations with potential clinical applications. Lysosomal storage diseases such as Sanfilippo syndrome (MPS-IIIA) represent ideal candidate diseases for the evaluation of cell therapies in the central nervous system (CNS). These diseases exhibit widespread pathology yet result from a single gene deficiency, in the case of Sanfilippo syndrome the lysosomal enzyme sulfamidase. The aim of this study was to investigate mouse embryonic stem (ES) cell-derived glial precursor cells as a vehicle for sulfamidase delivery in the MPS-IIIA mouse brain. In this study we have created a mouse ES cell line genetically modified to stably express and secrete high levels of human sulfamidase and a protocol for the in vitro derivation of large numbers glial precursors from ES cells. Differentiation of sulfamidase-expressing ES cells resulted in cell populations with sustained secretion of high levels of sulfamidase, comprised primarily of glial precursor cells with minor contaminants of other neural cell phenotypes but not residual pluripotent cells. CNS implantation studies demonstrated that ES cell-derived glial precursor cells formed using this differentiation method were able to engraft and survive for at least 12 weeks following implantation. The percentage of engraftment was quantified in different regions of the brain in 2-, 4-, and 8-week-old normal and MPS-IIIA mice. No teratomas were observed in any of the cell-transplanted animals. The results of this study support the further investigation of sulfamidase-expressing glial precursor cells as a vehicle for delivery of deficient enzyme into the CNS of MPS-IIIA mice.
Optimised analysis and visualisation of metabolic data using graph theoretical approaches

Since the completion of the Human Genome Project in 2003, it has become increasingly apparent that while genomics has a major role to play in the understanding of human biology, information from other disciplines is necessary to explain the web of interacting signals that allow our bodies to function on a day to day basis and respond to rapid changes in our local environment. One such field, that of metabolomics, focuses on the study of the set of low molecular weight compounds (metabolites) involved in metabolism. Metabolomic studies aim to quantify the concentrations of each of these compounds within a subject under particular conditions, resulting in either information on the physiological effects of a disease or environmental factor (such as a toxin) on the organism, or the identification of metabolites or groups of metabolites that serve as biochemical markers for a state or illness. Whilst metabolite concentrations alone can give great insight into a chosen state, additional information can be obtained by considering the ways in which metabolites interact with each other as parts of a larger system. One method of tackling this problem, metabolic networks, is gaining popularity within the community as it offers a complementary approach to the traditional biological method for studying metabolism, the metabolic pathway. Construction methods are varied; ranging from the mapping of experimental data onto pathway diagrams, through the use of correlation-based techniques, to the analysis of time-series data of metabolic fluxes. However, while many attempts have been made to capture and visualise the complex web of reactions within an organism, few have yet succeeded in showing how they can be used to help identify the metabolites that are most significantly involved in the differences between groups of biological samples. This thesis discusses ways in which graphs may be used to aid researchers in both the visualisation and interpretation of metabolomic datasets, and provide a platform for more automated analysis techniques. To that end, it first presents the background to the relevant topics, metabolomics and graph theory, before moving on to show how metabolic correlation networks can be used to identify and visualise differences in metabolism between groups of subjects. It then introduces Linked Metabolites, a software package that has been developed to help researchers explain differences in metabolism by highlighting relationships between metabolites within the metabolic pathways, and to compile those relationships into directed metabolic graphs suitable for analysis using metrics from graph theory. Finally, the thesis explains how the directed metabolic graphs produced by Linked Metabolites could potentially be used to integrate data gathered from the same sample using different experimental techniques, refining the areas of the underlying biochemistry needing further investigation.
Blind assistive device — Smart Lazy Susan

This study designed a smart Lazy Susan as a daily life aid for the visually impaired people to improve their dining convenience and safety. This smart device was realized by combining a Lazy Susan, electric motor, gears, voice integrated circuit (IC) module, radio frequency identification (RFID), blue-tooth module, mobile application (APP), speaker, single-chip microcomputer, and a set of buttons with Braille. After a button is pressed, the proposed device turns automatically to move the corresponding dish to the front of the diner, while the introduction of the dish is played through the speaker to help the visually impaired diner with dish selection.
Real-time position and orientation measurement with occlusion handling for distributed optical large-scale metrology systems

Abstract. Occlusion is a major problem for real-time position and orientation measurement with distributed optical large-scale metrology systems. This paper presents two novel methods with occlusion handling to address this issue, which should be used in combination for practical applications. These two approaches are based on the constraints established by three control points and six control points, respectively, and then the position and orientation can be calculated through iterative optimization algorithms. In this paper, all the work is carried out by using the workspace measuring and positioning system as a verification platform. The experimental results show that the orientation accuracies of the three-point method and the six-point method are kept within 0.1 and 0.04 deg, respectively, and the position accuracy exceeds 0.15 and 0.08 mm.
Analysis on information spreading as recorded in twittersphere = 트위터 소셜 네트워크에서의 정보 전파 분석

Twitter is offering an unprecedented opportunity for the study of information spreading in human society as all actions and underlying social network can be recorded. In this thesis, we present empirical study of information spreading phenomena in Twitter. We collected 32 million photo URLs posted on Twitter via Twitpic and related 52 million tweets from April 2010 to June 2010. Twitpic links guarantee that the source of information is unique and a Twitter user. Thus, Twitpic links eliminate chance of having multiple source users who bring the same information to Twittersphere. We show analysis on information creation and spreading tracking Twitpic URL links. Microscopic characteristics of information diffusion at the individual information level are not well-explored yet. We analyze temporal and topological characteristics of microscopic information spreading characteristics with the reconstructed diffusion trees of Korean users. We discover that diffusion in Twitter is very fast making wide and shallow diffusion trees. We show information diffusion model which is an extension of Independent Cascade Model considering response time of users. We show that spreading probabilities are influenced by type of information and directness to the original source. To be best of our knowledge this work is the first study on characteristics of microscopic information diffusion in Twitter.