Miracle-dz/UniFAR-FTUs huggingface dataset:
Loss of heterozygosity analysis: Practically and conceptually flawed?

The Knudson “two‐hit” hypothesis has provided the rationale for studies that aim to identify tumor‐suppressor genes by mapping regions of allelic loss (loss of heterozygosity, LOH). Although LOH has been found in practically all types of tumors, very few such projects have been successful in identifying their tumor‐suppressor targets. The prime explanation for this failure is probably that researchers have, in general, been too credulous about the two‐hit hypothesis, and too willing to ignore factors such as intratumor heterogeneity, contamination by normal cells, karyotypic complexity, homozygous deletions, gene dosage changes, and polymerase chain reaction artifacts. We suggest ways of minimizing these problems. Unfortunately, there is no guarantee that existing or newer methods, such as genomic microarrays and in situ single‐nucleotide polymorphism analysis, will solve the difficulties of LOH analysis. The future prospects for LOH studies are, as ever, uncertain. © 2002 Wiley‐Liss, Inc.
Long-term angiotensin-converting enzyme inhibition with fosinopril improves depressed responsiveness to Ca2+ in myocytes from aortic-banded rats.

BACKGROUND We have previously shown that long-term ACE inhibition with fosinopril prolongs survival and improves ventricular function despite persistent severe left ventricular pressure overload in ascending aortic-banded rats with left ventricular hypertrophy during the transition from compensation to failure. METHODS AND RESULTS To study the cellular mechanism of the effects of long-term ACE inhibition on the modification of the transition to failure in pressure-overload hypertrophy, we measured simultaneous intracellular Ca2+ transients and myocyte shortening in isolated left ventricular myocytes from fosinopril-treated aortic-banded rats (n = 9), untreated aortic-banded rats (n = 9), and normal age-matched control rats (n = 10). Fosinopril therapy was begun 6 weeks after banding and was continued until week 21 after banding, when the animals were killed. Collagenase-dissociated myocytes loaded with indo 1-AM were paced at 3 Hz at 36 degrees C and superfused at [Ca2+]o of 0.6, 1.2, and 3.0 mmol/L. In myocytes from untreated aortic-banded rats, peak systolic [Ca2+]i was higher than in control myocytes, and the relationship between myocyte shortening and [Ca2+]i was depressed relative to control myocytes, implicating impaired responsiveness to Ca2+. Long-term fosinopril treatment improved both myocyte shortening and the relationship of shortening to [Ca2+]i (P < .05 versus myocytes from untreated aortic-banded rats). Maximal Ca(2+)-activated force was depressed in chemically skinned left ventricular fibers from untreated aortic-banded hypertrophied rats relative to age-matched controls but not in the fosinopril-treated aortic-banded rats. CONCLUSIONS Long-term ACE inhibition improves responsiveness to Ca2+ in the presence of normalization of maximal Ca(2+)-activated force in aortic-banded rats subjected to persistent pressure overload. This may contribute to the favorable effects whereby ACE inhibition modifies the transition from compensated hypertrophy to failure.
A Study of Effects of Perceptual Cues on Presence for the Elderly in 3D Virtual Store

Virtual environments (VEs) technology applied in web shops provided a 3D perspective to customers for more real sense on goods and shopping environment. A sense of presence is one of the critical components required by any effective VEs. However, previous studies on cognitive aging have found that certain aspects of human information-processing abilities are negatively correlated with age. Therefore, when the quality of depth perceptual cues is good, whether the perceptual confliction for the elderly will be less to influence the feeling of presence or not? An experiment addressed presence, and performance of 3D virtual store in the elderly participation with auto-stereoscopic, stereoscopic and monocular display in good/poor depth perceptual cues. Results showed that 3D virtual store via auto-stereoscopic display with high quality depth perceptual cues will produce good sense and realism in stereopsis. However, the response time of objects-searching with 3D displays was longer than monocular display.
Transforming Growth Factor- b1 Induces Desmoplasia in an Experimental Model of Human Pancreatic Carcinoma

Proliferation of fibrotic tissue (desmoplasia) is one of the hallmarks of several epithelial tumors including pancreatic adenocarcinoma. This tissue reaction may be deleterious or advantageous to the host or tumor. In a systematic analysis, we identified two growth factors expressed by human pancreatic carcinoma cells that are positively correlated with the ability to induce fibroblast proliferation both in vitro and in vivo, i.e., transforming growth factor (TGF)b1 and fibroblast growth factor-2. Here we demonstrate that the overexpression of TGFb1 induced upregulation of matrix proteins and growth factors in the TGFb1-transfected pancreatic tumor cells. Furthermore, transfection of PANC-1 cells induces the same change in fibroblasts in either cocultivation experiments or when they are grown in conditioned medium from TGF-b1-transfected PANC-1 cells. TGF-b1-transfected pancreatic tumor cells induced a rich stroma after orthotopical transplantation in the nude mouse pancreas. The transfer of a single growth factor, TGF-b1, conveys the ability to induce a fibroblast response similar to that seen in desmoplasia in human pancreatic adenocarcinoma. This effect cannot only be attributed to direct effects of TGF-b1 but also results from the up-regulation of several other factors including collagen type I, connective tissue growth factor, and platelet-derived growth factor.
The influence of computer-assisted instruction on acquiring early skills in intraoral radiography.

The purpose of this study was to determine if there was a significant difference in the diagnostic quality of the initial full-mouth series (FMS) exposed by first-year dental students after viewing a Computer Assisted Instruction (CAI) module on radiographic technique as compared to those who did not and to determine if students who used the CAI module expressed a preference to using it and would recommend its use prior to exposure. Fifty-nine first-year dental students were randomly selected and assigned to two groups (students who did not view a CAI CD and students who did) before exposing their initial FMS on a Dental X-ray Training and Teaching Replica (DXTTR). For each radiographic series, a radiology faculty member determined the total number of error points based on performance criteria. The Wilcoxon Rank Sum Test was used to determine significance between the two groups, p = . 05. After exposing the FMS, students in the second group completed a questionnaire to assess their preference for using the CAI CD. The Sign Rank Test was used to determine preference, p = . 05. No significant difference in error points were found to exist between the two groups. Dental students who reviewed the CAI preferred using it and would recommend it to others before exposing their FMS.
Enhancement of Low-Voltage Ride Through Capability of an offshore wind turbine

This paper proposes an effective control strategy to enhance the Low Voltage Ride-Through (LVRT) capability of an offshore wind turbine connected to the grid. A new nonlinear control method based on differential flatness property of systems is applied to control the wind turbines in where, the system control is carried out by planning the appropriate trajectories on components of the output variables vector of the system. Also, the reactive power of variable speed wind turbine is managed in this work in order to respect the grid code requirements during voltage dips as well as to reduce their impacts on the grid. Simulation of the system model is carried out in Matlab/SimPowerSystems. The simulation results are presented to demonstrate the effectiveness and robustness of the Flatness-Based Control (FBC) to enhance LVRT of the offshore wind turbine.
Comparison of total energy expenditure assessed by two devices in controlled and free-living conditions

Abstract The objective of this study was to evaluate the validity of total energy expenditure (TEE) provided by Actiheart® and Armband®. Normal-weight adult volunteers wore both devices either for 17 hours in a calorimetric chamber (CC, n = 49) or for 10 days in free-living conditions (FLC) outside the laboratory (n = 41). The two devices and indirect calorimetry or doubly labelled water, respectively, were used to estimate TEE in the CC group and FLC group. In the CC, the relative value of TEE error was not significant (p > 0.05) for Actiheart® but significantly different from zero for Armband®, showing TEE underestimation (−4.9%, p < 0.0001). However, the mean absolute values of errors were significantly different between Actiheart® and Armband®: 8.6% and 6.7%, respectively (p = 0.05). Armband® was more accurate for estimating TEE during sleeping, rest, recovery periods and sitting–standing. Actiheart® provided better estimation during step and walking. In FLC, no significant error in relative value was detected. Nevertheless, Armband® produced smaller errors in absolute value than Actiheart® (8.6% vs. 12.8%). The distributions of differences were more scattered around the means, suggesting a higher inter-individual variability in TEE estimated by Actiheart® than by Armband®. Our results show that both monitors are appropriate for estimating TEE. Armband® is more effective than Actiheart® at the individual level for daily light-intensity activities.
Anomaly based Intrusion Detection System using Genetic Algorithm and K-Centroid Clustering

Internet is being expanded because of the enhancement of today’s networks and with these expansion different types of unauthorized activities building up to make the network vulnerable. Many researchers are working around the world to protect the systems from any kind of unauthorized access. In this study we have implemented an Intrusion Detection System based on K-Centroid Clustering and Genetic Algorithm to achieve a better detection rate and false positive rate. In our system training set is classified into different clusters based on K-Centroid clustering and then GA is performed to check each connection of the test set and finally result has been obtained for every specific connection. We have used both Kdd99Cup and NSLKDD dataset to get the experiment result of our system. Finally analyzing with those data we have got a decent detection rate in our implemented system. General Terms Network Security
Palliative care nurses' recognition and assessment of delirium symptoms: A qualitative study using critical incident technique

Background: Delirium is prevalent in palliative care inpatient settings and management is often challenging. Despite nurses’ integral patient care role, little is known about palliative care nurses’ capacity to recognise, assess and respond to patients’ delirium symptoms. Objective: To explore the experiences, views and practices of inpatient palliative care nurses in delirium recognition and assessment. Settings and participants: 30 nurses from nine Australian specialist palliative care inpatient
Local Estimation of Orbital and Spin Angular Momentum Mode Numbers

At radio frequencies, previous works by Mohammadi et al. derived from quantum mechanics state that the spin angular momentum (SAM), orbital angular momentum (OAM), and their sum [the total angular momentum (TAM)] can be estimated locally without ambiguity. In this letter, we highlight an inconsistency in this method when adding an SAM with an OAM. The latter cannot be estimated for a nonzero SAM. From optical currents, we propose a more general method. It is based on the Poynting expansion into spin and orbital components to estimate the OAM regardless of the SAM value.
Mean Square Exponential Stability of Stochastic Cohen-Grossberg Neural Networks with Unbounded Distributed Delays

This paper addresses the issue of mean square exponential stability of stochastic Cohen-Grossberg neural networks (SCGNN), whose state variables are described by stochastic nonlinear integrodifferential equations. With the help of Lyapunov function, stochastic analysis technique, and inequality techniques, some novel sufficient conditions on mean square exponential stability for SCGNN are given. Furthermore, we also establish some sufficient conditions for checking exponential stability for Cohen-Grossberg neural networks with unbounded distributed delays.
Thermodynamics of Surface Growth with Application to Bone Remodeling

In physics, surface growth classically refers to processes where material reorganize on the substrate onto which it is deposited (like epitaxial growth), but principally to phenomena associated to phase transition, whereby the evolution of the interface separating the phases produces a crystal (Kessler, 1990; Langer, 1980). From a biological perspective, surface growth refers to mechanisms tied to accretion and deposition occurring mostly in hard tissues, and is active in the formation of teeth, seashells, horns, nails, or bones (Thompson, 1992). A landmark in this field is Skalak (Skalak et al., 1982, 1997) who describe the growth or atrophy of part of a biological body by the accretion or resorption of biological tissue lying on the surface of the body. Surface growth of biological tissues is a widespread situation, with may be classified as either fixed growth surface (e.g. nails and horns) or moving growing surface (e.g. seashells, antlers). Models for the kinematics of surface growth have been developed in (Skalak et al., 1997), with a clear distinction between cases of fixed and moving growth surfaces, see (Ganghoffer et al., 2010a,b; Garikipati, 2009) for a recent exhaustive literature review. Following the pioneering mechanical treatments of elastic material surfaces and surface tension by (Gurtin and Murdoch, 1975; Mindlin, 1965), and considering that the boundary of a continuum displays a specific behavior (distinct from the bulk behavior), subsequent contributions in this direction have been developed in the literature (Gurtin and Struthers, 1990; Gurtin, 1995, Leo and Sekerka, 1989) for a thermodynamical approach of the surface stresses in crystals; configurational forces acting on interfaces have been considered e.g. in (Maugin, 1993; Maugin and Trimarco, 1995) – however not considering surface stress -, and (Gurtin, 1995; 2000) considering specific balance laws of configurational forces localized at interfaces. Biological evolution has entered into the realm of continuum mechanics in the 1990’s, with attempts to incorporate into a continuum description time-dependent phenomena, basically consisting of a variation of material properties, mass and shape of the solid body. One outstanding problem in developmental biology is indeed the understanding of the factors that may promote the generation of biological form, involving the processes of growth (change of mass), remodeling (change of properties), and morphogenesis (shape changes), a classification suggested by Taber (Taber, 1995). The main focus in this chapter is the setting up of a modeling platform relying on the thermodynamics of surfaces (Linford, 1973) and configurational mechanics (Maugin, 1993)
An Integrated Sensor Web Grid Cyberimplementation for Environmental Protection

Wireless Sensor Networks (WSNs) have been deployed for collecting the observed data across different areas. The continuous evolution of wireless networks and sensors emerges a new instrument concept which is called SensorWeb network. This type of network measures data related to geospatial information and can detect the conditions of remote places as a new instrument for environmental monitoring in the physical world. On the other hand the uninterrupted demand of the scientific community for computational and storage resources led us to the Grid Computing. Grid Computing is the combination of several distributed computational resources to a single problem at the same time, usually to a scientific or technical problem that requires a great number of computer processing cycles and a huge storage capability of data.
Connectivity Learning in Multi-Branch Networks

While much of the work in the design of convolutional networks over the last five years has revolved around the empirical investigation of the importance of depth, filter sizes, and number of feature channels, recent studies have shown that branching, i.e., splitting the computation along parallel but distinct threads and then aggregating their outputs, represents a new promising dimension for significant improvements in performance. To combat the complexity of design choices in multi-branch architectures, prior work has adopted simple strategies, such as a fixed branching factor, the same input being fed to all parallel branches, and an additive combination of the outputs produced by all branches at aggregation points. In this work we remove these predefined choices and propose an algorithm to learn the connections between branches in the network. Instead of being chosen a priori by the human designer, the multi-branch connectivity is learned simultaneously with the weights of the network by optimizing a single loss function defined with respect to the end task. We demonstrate our approach on the problem of multi-class image classification using three different datasets where it yields consistently higher accuracy compared to the state-of-the-art "ResNeXt" multi-branch network given the same learning capacity.
Utilisation de ressources externes dans un modèle Bayésien de Recherche d'Information. Application à la recherche d'information multilingue avec UMLS. (Use of external resources in a Bayesian model of Information Retrieval. Application to multilingual information retrieval with UMLS)

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Utilisation de ressources externes dans un modèle Bayésien de Recherche d’Information. Application à la recherche d’information multilingue avec UMLS. Thi Hoang Diem Le
A genome wide search for alcoholism susceptibility genes

Alcoholism is currently one of the most serious public health problems in the US. Lifetime prevalence rates are relatively high with one in five men and one in 12 women meeting criteria for this condition. Identification of genetic loci conferring an increased susceptibility to developing alcohol dependence could strengthen prevention efforts by informing individuals of their risk before abusive drinking ensues. Families identified through a double proband methodology have provided an exceptional opportunity for gene‐finding because of the increased recurrence risks seen in these sibships. A total of 360 markers for 22 autosomes were spaced at an average distance of 9.4 cM and genotyping performed for 330 members of these multiplex families. Extensive clinical data, personality variation, and event‐related potential characteristics were available for reducing heterogeneity and detecting robust linkage signals. Multipoint linkage analysis using different analytic strategies give strong support for loci on chromosomes 1, 2, 6, 7, 10, 12, 14, 16, and 17. © 2004 Wiley‐Liss, Inc.
Binocular openview system to perform estimations of aberrations and scattering in the human eye

We present a system that integrates a double-pass (DP) instrument and a Hartmann-Shack (HS) wavefront sensor to provide information not only on aberrations, but also on scattering occurring in the human eye. A binocular open-view design permits evaluations in normal viewing conditions. Furthermore, the system is able to compensate for both spherical and astigmatic refractive errors during measurements by using devices with configurable optical power. The DP and HS techniques provide comparable data after estimating wavefront slopes with respect to intersections of an ideal grid and compensating for residual errors provoked by optical defects of the measuring system. Once comparable data is obtained, it is possible to use this combined manner of assessment to provide information on scattering. Measurements in an artificial eye suggest that the characteristics of the ocular fundus may induce deviations of DP with respect to HS data. These differences were quantified in terms of the modulation transfer function in young healthy eyes measured in infrared light to demonstrate the potential use of the system in visual optics studies.
Optimal phase element for generating an elliptic perfect optical vortex

We study perfect optical vortices with an elliptic shape. Like the conventional circular perfect vortices, elliptic perfect optical vortices (EPOVs) have diameters that are independent on the topological charge. A pure-phase optical element is proposed for efficient generation of such EPOV. Intensity of EPOV generated by this element is order of magnitude higher than that of the EPOV generated by the Fraunhofer diffraction of an elliptic Bessel beam. We obtain exact analytical expressions for the orbital angular momentum (OAM) of the EPOV. These expressions show that the OAM of the EPOV can be fractional and it always exceeds the OAM of the conventional circular perfect optical vortex, which equals the topological charge. EPOVs can be used for movement of microscopic particles along an ellipse with acceleration, as well as for generation of OAM-entangled photons.
Tracking the underwater acoustic channel using two-dimensional frequency sampling

Rapidly fluctuating multipath arrivals along with unpredictable surface wave focusing events render the shallow water acoustic channel difficult to track using sparse or least-squared error (LSE) optimization techniques. This fundamental bottleneck is primarily due to the time-varying nature of the underlying distribution. In this work, we propose a complementary channel tracking technique that exploits the dual representation of the acoustic channel in the Fourier domain and employs two-dimensional frequency sampling using an application-inspired input dictionary. Specifically, we reformulate the time-varying channel tracking problem on a MIMO framework and design training symbols that sample the channel in its dual Fourier domain. Ground truths based on experimental field data are presented.
SVM-based loss differentiation mechanism in mobile ad hoc networks

In MANET (Mobile Ad hoc NETwork) packet loss at the receiver can be due to wireless random errors, the route change loss induced by node mobility and network congestion. While the traditional TCP-Friendly Rate Control protocol attributes all the packet losses to congestion, and in turn takes congestion control actions to reduce the sending rate, that causes the channel utilization of MANET network extremely low. This paper proposes an end-to-end machine learning algorithm to cognize the loss reasons. Through extracting the statistical characteristics of the lost packet the receiver can train a support vector machine (SVM) model, which can be used to discriminate the three major loss reasons: congestion, route change and wireless error. The unique merit of our solution is that it can cope with this puzzled problem intelligently without subjective or artificial thresholds to been determined. Extensive simulation results demonstrate that the differentiation scheme performs effectively under most scenarios.