Miracle-dz/UniFAR-FTUs huggingface dataset:
Gene Regulation Systems for Gene Therapy Applications in the Central Nervous System

Substantial progress has been made in the development of novel gene therapy strategies for central nervous system (CNS) disorders in recent years. However, unregulated transgene expression is a significant issue limiting human applications due to the potential side effects from excessive levels of transgenic protein that indiscriminately affect both diseased and nondiseased cells. Gene regulation systems are a tool by which tight tissue-specific and temporal regulation of transgene expression may be achieved. This review covers the features of ideal regulatory systems and summarises the mechanics of current exogenous and endogenous gene regulation systems and their utility in the CNS.
Steps toward a Cognitive Vision System

An adequate natural language description of developments in a real-world scene can be taken as proof of "understanding what is going on. " An algorithmic system that generates natural language descriptions from video recordings of road traffic scenes can be said to "understand" its input to the extent that algorithmically generated text is acceptable to the humans judging it. A fuzzy metrictemporal Horn logic (FMTHL) provides a formalism for representing both schematic and instantiated conceptual knowledge about the depicted scene and its temporal development. The resulting conceptual representation mediates in a systematic manner between the spatiotemporal geometric descriptions extracted from video input and a module that generates natural language text. This article outlines a 30-year effort to create such a cognitive vision system, indicates its current status, summarizes lessons learned along the way, and discusses open problems against this background.
A Comparison Study of Nonlinear Kernels

In this paper, we compare 5 different nonlinear kernels: min-max, RBF, fRBF (folded RBF), acos, and acos-$\chi^2$, on a wide range of publicly available datasets. The proposed fRBF kernel performs very similarly to the RBF kernel. Both RBF and fRBF kernels require an important tuning parameter ($\gamma$). Interestingly, for a significant portion of the datasets, the min-max kernel outperforms the best-tuned RBF/fRBF kernels. The acos kernel and acos-$\chi^2$ kernel also perform well in general and in some datasets achieve the best accuracies. One crucial issue with the use of nonlinear kernels is the excessive computational and memory cost. These days, one increasingly popular strategy is to linearize the kernels through various randomization algorithms. In our study, the randomization method for the min-max kernel demonstrates excellent performance compared to the randomization methods for other types of nonlinear kernels, measured in terms of the number of nonzero terms in the transformed dataset. Our study provides evidence for supporting the use of the min-max kernel and the corresponding randomized linearization method (i.e., the so-called "0-bit CWS"). Furthermore, the results motivate at least two directions for future research: (i) To develop new (and linearizable) nonlinear kernels for better accuracies; and (ii) To develop better linearization algorithms for improving the current linearization methods for the RBF kernel, the acos kernel, and the acos-$\chi^2$ kernel. One attempt is to combine the min-max kernel with the acos kernel or the acos-$\chi^2$ kernel. The advantages of these two new and tuning-free nonlinear kernels are demonstrated vias our extensive experiments.
Trends in HIV incidence in homosexual men in developed countries.

OBJECTIVES To describe trends in HIV notifications and in other measures of HIV incidence in homosexual men in developed countries. METHODS A literature search was conducted using PubMed. In addition to the peer-reviewed literature, data on HIV surveillance trends were sought by searching websites of surveillance authorities in developed countries. RESULTS The availability of long-term HIV surveillance data varied considerably. However, in almost all jurisdictions in which such data were available, notifications of new HIV diagnoses among homosexual men have increased, mostly since the late 1990s. The magnitude of this increase varied, but was more than 50% in many countries. There were much fewer data available on trends in direct measures of HIV incidence in homosexual men, and increases in HIV testing rates may have contributed to the increases in HIV diagnoses in many countries. However, since the late 1990s, several clinic- and community-based cohort studies in Europe and North America reported increasing incidence. CONCLUSION There were increases in HIV notifications in homosexual men in almost all developed countries, starting in the late 1990s and continuing to 2006. Although increases in HIV testing probably contributed to the increases in some settings, limited cohort data do support the existence of a true increase in HIV incidence in European and North American countries. Improved monitoring of HIV incidence in homosexual men at the population level is required to allow more timely assessment of the drivers underlying such trends.
New Concept to Restore Normal Cell Responses in Osteoarthritic Knee Joint Cartilage

Prediction of osteoarthritis progression does not exist. Cartilage “health” and degeneration during osteoarthritis depend on the signals perceived by chondrocytes. We hypothesize that biomechanical responses of chondrocytes in osteoarthritic cartilage can be restored close to their normal state. We propose an approach to evaluate quantitatively these responses in human joints and demonstrate how they can return close to normal levels.
A Decentralized Anonymity-Preserving Reputation System with Constant-time Score Retrieval

Reputation systems are a major feature of every modern e-commerce website, helping buyers carefully choose their service providers and products. However, most websites use centralized reputation systems, where the security of the system rests entirely upon a single Trusted Third Party. Moreover, they often disclose the identities of the raters, which may discourage honest users from posting frank reviews due to the fear of retaliation from the ratees. We present a reputation system that is decentralized yet secure and efficient, and could therefore be applied in a practical context. In fact, users are able to retrieve the reputation score of a service provider directly from it in constant time, with assurance regarding the correctness of the information obtained. Additionally, the reputation system is anonymity-preserving, which ensures that users can submit feedback without their identities being associated to it. Despite this anonymity, the system still offers robustness against attacks such as ballot-stuffing and Sybil attacks.
Predictive Value of Cytokines and Immune Activation Biomarkers in AIDS-Related Non-Hodgkin Lymphoma Treated with Rituximab plus Infusional EPOCH (AMC-034 trial)

Purpose: The aims of this study were to determine whether pretreatment plasma levels of cytokines and immune activation-associated molecules changed following treatment for AIDS-NHL with rituximab plus infusional EPOCH, and to determine whether pretreatment levels of these molecules were associated with response to treatment and/or survival. Experimental Design: We quantified plasma levels of B-cell activation-associated molecules (sCD27, sCD30, and sCD23) and cytokines (IL6, IL10, and CXCL13) before and after the initiation of treatment in persons with AIDS-NHL (n = 69) in the AIDS Malignancies Consortium (AMC) 034 study, which evaluated treatment of AIDS-NHL with EPOCH chemotherapy and rituximab. Results: Treatment resulted in decreased plasma levels of some of these molecules (CXCL13, sCD27, and sCD30), with decreased levels persisting for one year following the completion of treatment. Lower levels of CXCL13 before treatment were associated with complete responses following lymphoma therapy. Elevated levels of IL6 pretreatment were associated with decreased overall survival, whereas higher IL10 levels were associated with shorter progression-free survival (PFS), in multivariate analyses. Furthermore, patients with CXCL13 or IL6 levels higher than the median levels for the NHL group, as well as those who had detectable IL10, had lower overall survival and PFS, in Kaplan–Meier analyses. Conclusions: These results indicate that CXCL13, IL6, and IL10 have significant potential as prognostic biomarkers for AIDS-NHL. Clin Cancer Res; 22(2); 328–36. ©2015 AACR.
Perceptron Learning with Discrete Weights

Perceptron learning bounds with real weights have been pre- sented by several authors. In the present paper we study the perceptron learning task when using integer weights in (�k,k) d+1 . We present a sam- ple complexity formula based on an exact counting result of the finite class of functions implemented by the perceptron, and show that this bound is less pessimistic than existing bounds for the discrete and, in certain con- ditions, also for the continuous weight cases.
Vascular endothelial growth factors and vascular permeability

Vascular endothelial growth factors (VEGFs) are key regulators of permeability. The principal evidence behind how they increase vascular permeability in vivo and in vitro and the consequences of that increase are addressed here. Detailed analysis of the published literature has shown that in vivo and in vitro VEGF-mediated permeability differs in its time course, but has common involvement of many specific signalling pathways, in particular VEGF receptor-2 activation, calcium influx through transient receptor potential channels, activation of phospholipase C gamma and downstream activation of nitric oxide synthase. Pathways downstream of endothelial nitric oxide synthase appear to involve the guanylyl cyclase-mediated activation of the Rho–Rac pathway and subsequent involvement of junctional signalling proteins such as vascular endothelial cadherin and the tight junctional proteins zona occludens and occludin linked to the actin cytoskeleton. The signalling appears to be co-ordinated through spatial organization of the cascade into a signalplex, and arguments for why this may be important are considered. Many proteins have been identified to be involved in the regulation of vascular permeability by VEGF, but still the mechanisms through which these are thought to interact to control permeability are dependent on the experimental system, and a synthesis of existing data reveals that in intact vessels the co-ordination of the pathways is still not understood.
Abdominal muscle activity in sleep apnea during continuous positive airway pressure titration.

STUDY OBJECTIVES The aim of this study was to investigate whether presence of expiratory abdominal muscle activity (EAMA) in obstructive sleep apnea syndrome (OSAS) patients during nasal continuous positive airway pressure (nCPAP) is due to either nCPAP overprescription or nCPAP underprescription. DESIGN Airflow, esophageal pressure (Pes), and gastric pressure (Pga) were routinely measured during polysomnography aimed at determining the optimal nCPAP level, and the magnitude of EAMA was evaluated in relation to the nCPAP level and to the conventional indexes of upper-airway obstruction used during nCPAP titration. PATIENTS The study was performed 12 patients with OSAS. RESULTS Six patients displayed sustained EAMA, ie, EAMA lasting > 3 min, and characterized by a decrease in abdominal diameter and a paradoxical rise in Pga during expiration. In all six patients, EAMA decreased gradually as nCPAP neared optimal levels, and then disappeared when the optimal nCPAP level was achieved. The decrease in EAMA as nCPAP increased was associated with an increase in minute ventilation, decreases in both inspiratory and expiratory resistance, a decrease in Pes swing, and the normalization of the inspiratory flow contour. CONCLUSIONS We conclude that the EAMA observed in some OSAS patients might be an indirect marker of upper-airway obstruction, and that the presence of EAMA during nCPAP titration might indicate a suboptimal nCPAP level rather than a deleterious effect of nCPAP.
A Novel Framework for Learning Geometry-Aware Kernels

The data from real world usually have nonlinear geometric structure, which are often assumed to lie on or close to a low-dimensional manifold in a high-dimensional space. How to detect this nonlinear geometric structure of the data is important for the learning algorithms. Recently, there has been a surge of interest in utilizing kernels1 to exploit the manifold structure of the data. Such kernels are called geometry-aware kernels and are widely used in the machine learning algorithms. The performance of these algorithms critically relies on the choice of the geometry-aware kernels. Intuitively, a good geometryaware kernel should utilize additional information other than the geometric information. In many applications, it is required to compute the out-of-sample data directly. However, most of the geometry-aware kernel methods are restricted to the available data given beforehand, with no straightforward extension for out-of-sample data. In this paper, we propose a framework for more general geometry-aware kernel learning. The proposed framework integrates multiple sources of information and enables us to develop flexible and effective kernel matrices. Then, we theoretically show how the learned kernel matrices are extended to the corresponding kernel functions, in which the out-of-sample data can be computed directly. Under our framework, a novel family of geometry-aware kernels is developed. Especially, some existing geometry-aware kernels can be viewed as instances of our framework. The performance of the kernels is evaluated on dimensionality reduction, classification, and clustering tasks. The empirical results show that our kernels significantly improve the performance.
Bicycle-sharing systems expansion: station re-deployment through crowd planning

Bicycle-sharing systems (BSSs) which provide short-term shared bike usage services for the public are becoming very popular in many large cities. The accelerating bike traveling demands from the public have driven several significant expansions of many BSSs to place additional bikes and stations in their extended service regions. Meanwhile, to capture individuals' traveling needs more precisely, in the expansion, many BSSs have set up online websites to receive station location suggestions from the public. In this paper, we will study the bike station re-deployment problem in the BSSs expansion. Besides the historical bike usage and construction cost information, the crowd suggestions are also incorporated in the problem. The station re-deployment problem is very challenging to solve, and it covers two sub-tasks simultaneously: (1) bike station locations identification, and (2) bike dock assignment (to the deployed stations). To address the problem, a novel bike station re-deployment framework, CrowdPlanning, is introduced in this paper. In both station deployment and capacity assignment tasks, CrowdPlanning fuses different categories of spatial information including the crowd suggestions, individuals' historical bike usage and the construction costs simultaneously. By formulating these two tasks as two optimization problems, the optimal expansion strategies can be identified by CrowdPlanning. for the BSSs. Extensive experiments are conducted on the real-world BSSs and crowd suggestion dataset to demonstrate the effectiveness of framework CrowdPlanning.
A Logical Approach to High-Level Robot Programming A Progress Report*

This paper describes a novel approach to high-level robot programming based on a highly developed logica] theory of action. The user provides a specification of the robot’s basic actions (their preconditions and effects on the environment) as well as of relevant aspects of the environment, in an extended version of the situation calculus. He can then specify robot behaviors in terms of these actions in a programming language that allows references to world conditions (e.g. if 3c(PoP-CAN(c) A ON_TABLE(c)) then PICK_UP(c)). The programs can be executed to drive the robot. The interpreter automatically maintains the world model required to execute programs based on the specification. The theoretical framework includes a solution to the frame problem and is very general -- it handles dynamic and incompletely known worlds, as well as perception actions. Given this kind of domain specification, it is Mso possible to support more sophisticated reasoning, such as task planning at run-time. The specification can also be used to prove the robot control programs correct. A simple mall delivery application is used to present the approach. Ongoing work on implementing the approach and handling outstanding problems, such as modeling noisy sensors, is also described.
Colchicine suppresses the release of fibroblast growth factors from alveolar macrophages in vitro. The basis of a possible therapeutic approach ot the fibrotic disorders.

Fibrosis is the accumulation of fibroblasts and the connective tissue products secreted by these cells, usually subsequent to tissue injury. While fibrosis can be useful in preserving the general structural integrity of a tissue, it often alters cell-cell and cell-connective tissue interactions, which leads to loss of tissue function. On the basis of the concept that mononuclear phagocytes can direct the development of fibrosis through the release of specific mediators that stimulate fibroblast proliferation, we propose a therapeutic strategy to prevent fibrosis by preventing the release of these specific mediators. The present study demonstrated that colchicine, a widely used and well-tolerated drug, can block alveolar macrophage release of 2 mediators associated with the development of fibrosis in interstitial lung diseases, fibronectin, and the alveolar-macrophage-derived growth factor (AMDGF). Colchicine blocked the spontaneous release of fibronectin by alveolar macrophages obtained from patients with fibrotic lung disease by 23 +/- 4% after 24 h and by greater than 90% after 72 h. AMDGF release was blocked by 68 +/- 10% after 4 h (p less than 0.01, all comparisons). The effect of colchicine was not due to nonspecific toxicity since [14C]proline tracer studies demonstrated that macrophages treated with colchicine were capable of de novo protein synthesis and the secretion of several protein products, despite the fact that fibronectin and AMDGF release were suppressed. The effect of colchicine on the spontaneous release of both fibronectin and AMDGF could be observed at concentrations less than 10 ng/ml, levels that can be achieved in vivo. (ABSTRACT TRUNCATED AT 250 WORDS)
Gender Differences in Attitudes towards Information Technology among Malaysian Student Teachers: A Case Study at Universiti Putra Malaysia

This article presents a quantitative study on gender differences in attitudes toward the usage of Information Technology (IT) related tools and applications. The study was conducted at Universiti Putra Malaysia, Malaysia, with 73 female and 29 male student teachers involved as participants. They were each presented with a questionnaire to relate their attitudes toward IT before and after undergoing a discrete IT course for the duration of one semester (14 weeks). The attitudes of the respondents were measured in terms of three dimensions, namely, usefulness, confidence and aversion. There were no significant differences between female and male student teachers when the pre- and post-test mean scores were compared. Both genders exhibited the same levels of attitudes before and after undergoing the comprehensive IT course. This suggests that the exposure to IT did not contribute to any significant gender disparity. The paired sample t-test results showed improved attitudes toward IT usage in both females and males after the exposure to IT. The biggest improvement for both females and males was in the aversion dimension which showed that their initial strong dislike toward IT was greatly reduced at the end of the course. In terms of confidence, female participants exhibited an enhanced confidence level after the course as opposed to the male participants. The results support the view that computer experience is gender-based as the increase in IT confidence over time assumed different patterns for females and males.
Absolute absorption cross-section and photolysis rate of I 2

Abstract. Following recent observations of molecular iodine (I2) in the coastal marine boundary layer (MBL) (Saiz-Lopez and Plane, 2004), it has become important to determine the absolute absorption cross-section of I2 at reasonably high resolution, and also to evaluate the rate of photolysis of the molecule in the lower atmosphere. The absolute absorption cross-section (σ) of gaseous I2 at room temperature and pressure (295K, 760Torr) was therefore measured between 182 and 750nm using a Fourier Transform spectrometer at a resolution of 4cm-1 (0.1nm at λ=500nm). The maximum absorption cross-section in the visible region was observed at λ=533.0nm to be σ=(4.24±0.50)x10-18cm2molecule-1. The spectrum is available as supplementary material accompanying this paper. The photo-dissociation rate constant (J) of gaseous I2 was also measured directly in a solar simulator, yielding J(I2)=0.12±0.03s-1 for the lower troposphere. This is in excellent agreement with the value of 0.12±0.015s-1 calculated using the measured absorption cross-section, terrestrial solar flux for clear sky conditions and assuming a photo-dissociation yield of unity. A two-stream radiation transfer model was then used to determine the variation in photolysis rate with solar zenith angle (SZA), from which an analytic expression is derived for use in atmospheric models. Photolysis appears to be the dominant loss process for I2 during daytime, and hence an important source of iodine atoms in the lower atmosphere.
A Wavelet Based Recognition System for Malayalam Vowels using Artificial Neural Networks

This work explores the use of a discrete wavelet transform, a feature extractor mechanism for speech recognition. Speech recognition is a fascinating application of digital signal processing offering unparalleled opportunities. The real-world applications deploying speech recognition and its implications can be varied across various fields. Speech recognition can automate many tasks that previously required hands-on human interaction. Accurate vowel recognition forms the backbone of most successful speech recognition systems. The vowel set of Malayalam, one of the South Indian languages, is used to create the database. A hybrid approach with discrete wavelet transforms and neural networks are used to form a system with improved performance. Daubechies wavelet is employed in this experiment. Features are extracted by using Discrete Wavelet Transforms (DWT). Training, testing and pattern recognition are performed using Artificial Neural Networks (ANN). The results show excellent overall recognition accuracy above 95%. The high accuracy obtained shows promising potentials of discrete wavelet transforms and neural networks in speech recognition.