Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of testosterone supplementation on skeletal muscle fiber hypertrophy and satellite cells in community-dwelling older men.

OBJECTIVE In this study, we determined the effects of graded doses of testosterone on muscle fiber cross-sectional area (CSA) and satellite cell number and replication in older men. PARTICIPANTS Healthy men, 60-75 yr old, received a long-acting GnRH agonist to suppress endogenous testosterone production and 25, 50, 125, 300, or 600 mg testosterone enanthate im weekly for 20 wk. METHODS Immunohistochemistry, light and confocal microscopy, and electron microscopy were used to perform fiber typing and quantitate myonuclear and satellite cell number in vastus lateralis biopsies, obtained before and after 20 wk of treatment. RESULTS Testosterone administration in older men was associated with dose-dependent increases in CSA of both types I and II fibers. Satellite cell number increased dose dependently at the three highest doses (3% at baseline vs. 6.2, 9.2, and 13.0% at 125, 300, and 600 mg doses, P < 0.05). Testosterone administration was associated with an increase in the number of proliferating cell nuclear antigen+ satellite cells (1.8% at baseline vs. 3.9, 7.5, and 13% at 125, 300, and 600 mg doses, P < 0.005). The expression of activated Notch, examined only in the 300-mg group (baseline, 2.3 vs. 9.0% after treatment, P < 0.005), increased in satellite cells after testosterone treatment. The expression of myogenin (baseline, 6.2 vs. 20.7% after treatment, P < 0.005), examined only in the 300-mg group, increased significantly in muscle fiber nuclei after testosterone treatment, but Numb expression did not change. CONCLUSIONS Older men respond to graded doses of testosterone with a dose-dependent increase in muscle fiber CSA and satellite cell number. Testosterone-induced skeletal muscle hypertrophy in older men is associated with increased satellite cell replication and activation.
The Stepwise Dimensionality Increasing (SDI) Index for High-Dimensional Data

Similarity search is a powerful paradigm for image and multimedia databases, time series databases, and DNA and protein sequence databases. Objects are represented by high-dimensional feature vectors based on color, texture, and shape, in the case of images, for example object similarity is usually implemented via k-nearest neighbor (k-NN) queries, determined by the distance of the endpoints of the feature vectors. The cost of processing k-NN queries via a sequential scan increases with the number of objects and the number of dimensions. Multi-dimensional indexing structures can be used to improve the efficiency of k-NN query processing, but lose their effectiveness as the dimensionality increases. The curse of dimensionality manifests itself in the form of increased overlap among the nodes of the index, so that a high fraction of index pages are touched in processing k-NN queries. The increased dimensionality results in a reduced fanout and an increased index height. We propose a stepwise dimensionality increasing (SDI)-tree index, which aims at reducing the number of disk accesses and CPU processing cost. The index is built using feature vectors transformed via principal component analysis. Dimensions are retained in non-increasing order of their variance according to a parameter p, which specifies the incremental fraction of variance at each level of the index. The optimal value for p is determined experimentally. Experiments on three datasets have shown that SDI-trees access fewer disk pages and incur less CPU time than SR-trees, VAMSR-trees, vector approximation (VA)-Files and the recently proposed iDistance method. In CPU time SDI outperforms the sequential scan and OMNI methods.
Progress on phoneme recognition with a continuous-state HMM

Recent advances in automatic speech recognition have used large corpora and powerful computational resources to train complex statistical models from high-dimensional features, to attempt to capture all the variability found in natural speech. Such models are difficult to interpret and may be fragile, and contradict or ignore knowledge of human speech production and perception. We report progress towards phoneme recognition using a model of speech which employs very few parameters and which is more faithful to the dynamics and model of human speech production. Using features generated from a neural network bottleneck layer, we obtain recognition accuracy on TIMIT which compares favourably with traditional models of similar power. We discuss the implications of these results for recognition using natural features such as vocal tract resonances and spectral energies.
Remote sensing image classification and recognition based on KFCM

Based on fuzzy C-means method and the characteristics of kernel-based method, the algorithm of kernel-based fuzzy clustering is presented, in which the objective function of fuzzy C-means is substituted by Gaussian kernel objective function. The approach of kernel-based fuzzy C-means clustering is used in the classification and recognition of remote sensing images, and the result shows that it can effectively improve the classification accuracy of remote sensing images compared with the traditional fuzzy C-means clustering.
Estimating roughness parameters of an object's surface from real images

Reflectance of an object’s surface plays an important role in image synthesis. Several reflection models have been proposed to realize realistic object representation, but the reflectance parameters are difficult to determine appropriately. Sato et al. [Sato et al. 1997] proposed a method to measure reflectance properties of real objects using the shape information and captured images. For more realistic image generation, it is necessary to measure the roughness parameters of an object’s surface from real images. Previous work has been done to obtain bump maps from real images [Rushmeier et al. 1997; Lefebvre and Poulin 2000]. In this paper, we propose a method to model roughness as bump parameters using distribution functions.
Fibrosis without an Antitumor Effect in Nude Mice 1 Induces Cachexia and Systemic β Transforming Growth Factor

While stimulating the growth of fibroblasts, transforming growth factor ,) I ( U.I ,n ) inhibits the growth of various normal and malignant cell lines in vitro. We studied the effects of TGF-/31 in vivo. The level of TGF-01 in serum was maximally elevated 2 h after injecting 1 fid of I25I-TGF-/31into the peritoneal cavity of nude mice. Five h after the Â¡. p. administration of 10 ng of unlabeled TGF-/31, 20 ng/ml of TGF-/J-like material in serum were detected by a radioreceptor assay on A549 lung carcinoma cells. Trichloroacetic acid-precipitable '"I-TGF-/31 was taken up by liver, spleen, lungs, kidneys, and tumor tissue but not by the brain. At doses exceeding 2 jig/day, TGF-,01 induced a generalized interstitial fibrosis and a cachexia, which was not mediated by elevated serum levels of tumor necrosis factor a as determined by Western blot analysis and enzyme-linked immunosorbent assay. A total of 200,000 cells of the estrogen receptor-negative human breast cancer line MDA-MB-231, which had been shown to be maximally growth inhibited in vitro by 40 pM TGF-/31 and to have high-affinity receptors (9, 11, 12), were injected into the mammary fat pad of each nude mouse. The duration of treatment was 16 days with ten animals in the control group and five animals in the treated groups. The dose ranged from 1 to 4 ^g per animal daily. The treatment was started 24 h after the injection of the tumor cells. Tumor growth was not significantly affected at either nontoxic or toxic doses of TGF-/91. Thus, we have demonstrated that TGF-/31, apart from being a local growth factor, has systemic effects, such as cachexia and multiple fibrosis. Its role as an antitumor agent may be limited.
Timing properties analysis of real-time embedded systems with AADL model using model checking

A novel approach to analyze timing properties of real-time embedded systems based on the model-driven architecture is proposed in this paper. The scheduling model which describes components of software and hardware as well as the interacting and binding relations of components is abstracted from an AADL model. The task deadline at the component lever and the end-to-end latency at the system lever are analyzed by specifying the scheduling model with the satisfiability modulo theories. An analysis tool is developed to work with the AADL developing environment to analyze the timing properties of the AADL model. The experiment results demonstrate the running performance of the proposed approach.
Development of a design methodology for warehousing systems : hierarchical framework

We will present a progress report on our effort to develop a science-based design methodology for warehousing systems. In particular, we will discuss the hierarchical structure of our design procedure. This includes the decisions and parameters used in the master model, the various sub-models, and the decision and data interaction between the various levels in the hierarchy. We will present several sub-models that are specific for a particular function or material handling equipment. Computational results of the application of the sub-model for modular storage drawers will also be shared.
Sentence segmentation for speech processing

Automatic sentence segmentation of speech is a process of identifying the end of a sentence. It is used for improving the output after speech recognition and helps in making the recognition output more readable. It is generally a two-class problem which involves the identification of a boundary characterizing the sentence part and the non-sentence part. An Automatic Speech Recognition (ASR) system receives a stream of speech signal and produces a un-annotated stream of words. The regions of silences in the inter word boundaries of the output of ASR are detected. The prosodic features of the input speech signal that are given to the ASR are extracted for a particular duration of time which includes pause, rhyme, slope, minimum, maximum and mean features. Once the features are extracted, SVM classifier uses all the features and discriminates each word boundary as sentence or non-sentence boundary.
Nonlinear Stability of a Delayed Feedback Controlled Container Crane

A simplified model of a container crane subject to a delayed feedback is investigated. The conditions for a Hopf bifurcation to stable/unstable limit-cycle solutions are determined. It is shown that a subcritical Hopf bifurcation to unstable oscillations cannot be ruled out and the undesired coexistence of stable large amplitude oscillations and a stable equilibrium endangers the robustness of time-delay control strategies. The bifurcation is analyzed both analytically and numerically using a continuation method.
Colored Petri nets based modeling and simulation of mixed workload interaction in a nondedicated cluster

This work presents a colored Petri nets based modeling and performance evaluation of mixed (interactive and parallel) workloads in a nondedicated cluster environment. To control the interactions between the two types of workloads, we propose to constrain the scheduling of local interactive processes by a measure of the maximum response time expected by the workstation (WS) user. The measure is assumed obtained through empirical studies. We propose a scheduling scheme that within the max-response time cycle computes time quanta to satisfy both local interactive processes present in the system and the parallel task process. We proposed a colored Petri net (CPN) model of the scheduling scheme and simulations have shown the effectiveness of the proposed method in allowing the parallel task to ensure a minimum speedup even in heavy loaded situations and to maximize the speedup adoptively depending on the load conditions.
A 250 nm GaN N-Path Filter IC with +27 dBm Blocker Tolerance

A fully integrated 250 nm GaN bandpass N-path filter is presented for high blocker tolerance applications. Measurements from 200 MHz to 1.9 GHz of a 4-phase shunt architecture demonstrate a broadband tunable bandpass response with insertion loss less than 5 dB, out-of-band rejection of 18 dB, in-band blocker B1dB of +18 dBm, and out-of-band blocker B1dB of +27 dBm.
Information Propagation Analysis in a Social Network Site

One of the most interesting and still not completely understood phenomena happening in Social Network Sites is their ability to spread (or not) units of information which may aggregate to form large distributed conversations. In this paper we present the result of an empirical study on a Large Social Database (LSD) aimed at measuring the factors enabling information spreading in Social Network Sites.
The activating function for magnetic stimulation derived from a three-dimensional volume conductor model

A three-dimensional volume conductor model of magnetic stimulation is proposed that relates transmembrane potential of an axon to the induced electric field in a uniform volume conductor. This model validates assumptions used previously to derive a one-dimensional cable model of magnetic stimulation (B.J. Roth and P.J. Basser, ibid., vol.37, p.588-97, 1990) of unmyelinated axons. The three-dimensional volume conductor model reduces to this one-dimensional cable equation forced by the activating function, - delta E/sub A//sup z// delta /sub z/. <<ETX>>
Design of Ultra-Low-Voltage RF Frontends With Complementary Current-Reused Architectures

In this paper, ultra-low-voltage circuit techniques are presented for CMOS RF frontends. By employing a complementary current-reused architecture, the RF building blocks including a low-noise amplifier (LNA) and a single-balanced down-conversion mixer can operate at a reduced supply voltage with microwatt power consumption while maintaining reasonable circuit performance at multigigahertz frequencies. Based on the MOSFET model in moderate and weak inversion, theoretical analysis and design considerations of the proposed circuit techniques are described in detail. Using a standard 0.18-mum CMOS process, prototype frontend circuits are implemented at the 5-GHz frequency band for demonstration. From the measurement results, the fully integrated LNA exhibits a gain of 9.2 dB and a noise figure of 4.5 dB at 5 GHz, while the mixer has a conversion gain of 3.2 dB and an IIP3 of -8 dBm. Operated at a supply voltage of 0.6 V, the power consumptions of the LNA and the mixer are 900 and 792 muW, respectively.
Towards Enhancing Earthquake Response Interpretation Using Sonification

In this paper, we select the application domain of earthquake engineering for utility of sonification, where signals are of random frequency and amplitude content. In particular, we focus on the response of structures to particular earthquake time histories. Given a random ground motion input, the resulting response signal will vary in the time and frequency domain, and show large variations in acceleration, velocity and displacement space. We illustrate the utility of different simple, yet robust sonification techniques to the study of the response of a variety of linear elastic single-degree-offreedom (SDOF) oscillators, with different natural periods Tn and associated damping ratios ζn, subjected to a pair of earthquake motions. In the system study, we augment the representation of the response results of these SDOF structures with both visual and aural cues.
A future location-prediction replacement strategy for mobile computing environments

While the traditional data shipping systems use physical information to organize data, a newer data caching technique maintains both associated answers (data items) of previous queries and their meaning (purpose). This form of information description is called semantic description, and it makes it possible to reason about and derive knowledge from the given description. In a distributed heterogeneous environment, such as the mobile environment, the semantic data caching paradigm is an important technique for improving the performance of wireless data dissemination systems. Data caching performance depends heavily on the replacement policy being used for the cache management. However, future location ambiguity, limited client resources and frequent client disconnections make cache management a challenge. This paper proposes a future location-aware cache replacement policy to manage a semantic cache. The proposed replacement policy uses the validity of the data fetched from the server and the neighboring locations to decide which of the cache entries is less likely to be needed in the future, and therefore, a good candidate to be evicted when cache space is needed. The replacement policy's preference for cached items to be evicted is modelled as a general function that declines with distance between the cell the candidate for replacement's cached item is bounded to and the query's bound cell. For better efficiency the overall replacement granularity is dynamically achieved along three levels: ring, cell and data item. Simulation study of the proposed approach shows that it outperforms both the least recently used (LRU) and furthest away replacement (FAR) schemes, where only temporal locality is considered. Moreover, the proposed scheme is easier to implement than the industry standard policies
Developing Neurons Form Transient Nanotubes Facilitating Electrical Coupling and Calcium Signaling with Distant Astrocytes

Despite the well-documented cooperation between neurons and astrocytes little is known as to how these interactions are initiated. We show here by differential interference contrast microscopy that immature hippocampal neurons generated short protrusions towards astrocytes resulting in tunneling nanotube (TNT) formation with an average lifetime of 15 minutes. Fluorescence microscopy revealed that all TNTs between the two cell types contained microtubules but 35% of them were F-actin negative. Immunolabeling against connexin 43 showed that this gap junction marker localized at the contact site of TNTs with astrocytes. Using optical membrane-potential measurements combined with mechanical stimulation, we observed that ∼35% of immature neurons were electrically coupled with distant astrocytes via TNTs up to 5 hours after co-culture but not after 24 hours. Connexin 43 was expressed by most neurons at 5 hours of co-culture but was not detected in neurons after 24 hours. We show that TNTs mediated the propagation of both depolarization and transient calcium signals from distant astrocytes to neurons. Our findings suggest that within a limited maturation period developing neurons establish electrical coupling and exchange of calcium signals with astrocytes via TNTs, which correlates with a high neuronal expression level of connexin 43. This novel cell-cell communication pathway between cells of the central nervous system provides new concepts in our understanding of neuronal migration and differentiation.
Benchmarks for dynamic multi-objective optimisation

When algorithms solve dynamic multi-objective optimisation problems (DMOOPs), benchmark functions should be used to determine whether the algorithm can overcome specific difficulties that can occur in real-world problems. However, for dynamic multi-objective optimisation (DMOO) there are no standard benchmark functions that are used. This article proposes characteristics of an ideal set of DMOO benchmark functions, as well as suggested DMOOPs for each characteristic. The limitations of current DMOOPs and studies of dynamic multi-objective optimisation algorithms (DMOAs) are highlighted. In addition, new DMOO benchmark functions with complicated Pareto-optimal sets (POSs) and approaches to develop DMOOPs with either an isolated or deceptive Pareto-optimal front (POF) are introduced to address identified limitations of current DMOOPs.
Comparison of Structural Architecture of HCV NS3 Genotype 1 versus Pakistani Genotype 3a

This study described the structural characterization of Pakistani HCV NS3 GT3a in parallel with genotypes 1a and 1b NS3. We investigated the role of amino acids and their interaction patterns in different HCV genotypes by crystallographic modeling. Different softwares were used to study the interaction pattern, for example, CLCBIO sequence viewer, MODELLER, NMRCLUST, ERRAT score, and MODELLER. Sixty models were produced and clustered into groups and the best model of PK-NCVI/Pk3a NS3 was selected and studied further to check the variability with other HCV NS3 genotypes. This study will help in future to understand the structural architecture of HCV genome variability and to further define the conserved targets for antiviral agents.
A New Approach Based on Benders Decomposition for Unit Commitment Problem

This study presents a new formulation based on generalized benders decomposition approach to solve thermal unit commitment problem. This new approach decomposes the problem into a master problem and a s ub-problem. The master problem is an integer program and sub-problem is a nonlinear program. The master problem applies the integer programming method to solve (Unit Commitment) UC and finds proper on/off states of the units. In the proposed approach, the sub-problem is modeled as a nonlinear problem and it uses the outputs of master problem to form appropriate cuts and adds them to the master problem for solving the next iteration of UC. Appropriate formulations of constraints for both parts of problem are presented. The results obtained, considering a commonly used system, show the efficiency of this approach in comparison with other methods.
Centroid Neural Network for Clustering of Line Segments

An approach for an efficient clustering of 3D line segments based on an unsupervised competitive neural network is applied to a set of high resolution satellite image data in this paper. The unsupervised competitive neural network, called centroid neural network for clustering 3D line segments (CNN-3D), utilizes the characteristics of 3D line segments. Successful application of CNN-3D can lead accurate extraction of rectangular boundaries for building rooftops from an 3-D edge image which is considered as challenging and difficult because 3-D line segments are often contaminated with various noises obtained during stereo matching process. Experiments and results show that the proposed CNN-3D algorithm can group 3D line segments and the resulting 3D line groups can be successfully utilized for detecting rectangular boundaries for building detection.
A realisation of ethical concerns with smartphone personal health monitoring apps

The pervasiveness of smartphones has facilitated a new way in which owners of devices can monitor their health using applications (apps) that are installed on their smartphones. Smartphone personal health monitoring (SPHM) collects and stores health related data of the user either locally or in a third party storing mechanism. They are also capable of giving feedback to the user of the app in response to conditions that are provided to the app therefore empowering the user to actively make decisions to adjust their lifestyle. Regardless of the benefits that this new innovative technology offers to its users, there are some ethical concerns to the user of SPHM apps. These ethical concerns are in some way connected to the features of SPHM apps. From a literature survey, this paper attempts to recognize ethical issues with personal health monitoring apps on smartphones, viewed in light of general ethics of ubiquitous computing. The paper argues that there are ethical concerns with the use of SPHM apps regardless of the benefits that the technology offers to users due to SPHM apps' ubiquity leaving them open to known and emerging ethical concerns. The paper then propose a need for further empirical research to validate the claim.