Miracle-dz/UniFAR-FTUs huggingface dataset:
Real-time automated modeling and control of self-assembling systems

We present the M3 framework, a formal and generic computational framework for modeling and controlling stochastic distributed systems of purely reactive robots in an automated and real-time fashion. Based on the trajectories of the robots, the framework builds up an internal microscopic representation of the system, which then serves as a blueprint of models at higher abstraction levels. These models are then calibrated using a Maximum Likelihood Estimation (MLE) algorithm. We illustrate the structure and performance of the framework by performing the online optimization of a bang-bang controller for the stochastic self-assembly of water-floating, magnetically latching, passive modules. The experimental results demonstrate that the generated models can successfully optimize the assembly of desired structures.
Analysis of co-occurrence relationship between named entity in Web page

In order to analyze the closeness of named entities in massive web pages, the word co-occurrence algorithm FDC(frequency, term distance, co-collection ratio) is employed to evaluate the co-occurrence relationships between the named entities by their co-occurrence frequency, relative position and the ratio of co-occurrence among a document. And by employing the proper value of named entities' co-occurrence frequency and the relative distances between the two named entities, the FDC algorithm is improved. Experiments show that the improved FDC algorithm has better performance.
The Role of Implants in Orthodontics

In this article, a review of the development of implants inorthodontic treatment and use of dental implants is done. Theuse of implants has greatly increased over the last threedecades, largely as a consequence of their successful longtermosseointegration. This has led to increased orthodonticuse with appropriate modifications in the design, when required.
A Laminin G-EGF-Laminin G Module in Neurexin IV Is Essential for the Apico-Lateral Localization of Contactin and Organization of Septate Junctions

Septate junctions (SJs) display a unique ultrastructural morphology with ladder-like electron densities that are conserved through evolution. Genetic and molecular analyses have identified a highly conserved core complex of SJ proteins consisting of three cell adhesion molecules Neurexin IV, Contactin, and Neuroglian, which interact with the cytoskeletal FERM domain protein Coracle. How these individual proteins interact to form the septal arrays that create the paracellular barrier is poorly understood. Here, we show that point mutations that map to specific domains of neurexin IV lead to formation of fewer septae and disorganization of SJs. Consistent with these observations, our in vivo domain deletion analyses identified the first Laminin G-EGF-Laminin G module in the extracellular region of Neurexin IV as necessary for the localization of and association with Contactin. Neurexin IV protein that is devoid of its cytoplasmic region is able to create septae, but fails to form a full complement of SJs. These data provide the first in vivo evidence that specific domains in Neurexin IV are required for protein-protein interactions and organization of SJs. Given the molecular conservation of SJ proteins across species, our studies may provide insights into how vertebrate axo-glial SJs are organized in myelinated axons.
Astaxanthin Inhibits Proliferation and Induces Apoptosis and Cell Cycle Arrest of Mice H22 Hepatoma Cells

Background It is widely recognized that astaxanthin (ASX), a member of the carotenoid family, has strong biological activities including antioxidant, anti-inflammation, and immune-modulation activities. Previous studies have confirmed that ASX can effectively inhibit hepatoma cells in vitro. Material/Methods MTT was used to assay proliferation of mice H22 cells, and flow cytometry was used to determine apoptosis and cell cycle arrest of H22 cells in vitro and in vivo. Moreover, anti-tumor activity of ASX was observed in mice. Results ASX inhibited the proliferation of H22 cells, promoted cell necrosis, and induced cell cycle arrest in G2 phase in vitro and in vivo. Conclusions This study indicated that ASX can inhibit proliferation and induce apoptosis and cell cycle arrest in mice H22 hepatoma cells in vitro and in vivo.
Efficiency study of coaxial contactless power transmission for electric railway

A novel contactless power supply system for electric trains is discussed based on structure of an air gapped coaxial transformer. Theoretical analysis, simulation results and verification experiments were conducted and the results are shown in this paper. The 94.0% efficiency was observed with air gap coaxial structure. Moreover, the power factor corrector (PFC) circuit are introduced to increase sending power. However, the efficiency drops to 86.8% for the internal resistance (ESR) of inserted parallel capacitor Cp. In order to reduce the effect of ESR, parallelization of Cp are introduced. This method achieves power transmission efficiency of 88.0%.
Representing a Set of Reconciliations in a Compact Way

Comparative genomic studies are often conducted by reconciliation analyses comparing gene and species trees. One of the issues with reconciliation approaches is that an exponential number of optimal scenarios is possible. The resulting complexity is masked by the fact that a majority of reconciliation software pick up a random optimal solution that is returned to the end-user. However, the alternative solutions should not be ignored since they tell different stories that parsimony considers as viable as the output solution. In this paper, we describe a polynomial space and time algorithm to build a minimum reconciliation graph--a graph that summarizes the set of all most parsimonious reconciliations. Amongst numerous applications, it is shown how this graph allows counting the number of non-equivalent most parsimonious reconciliations.
The metallicity range of variables in M 3

The recently published spectroscopic metallicities of RR Lyrae stars in M 3 (Sandstrom et al. [CITE]) show a relatively wide range of the measured [Fe/H] values. As no dependence of the metallicities on either minimum temperature or period was found, they concluded that no real metallicity spread was detected. Comparing these spectroscopic metallicities with the [Fe/H] values calculated from the Fourier parameters of the light curves of the variables a correlation between the results of the two metallicity determinations emerges. As a consequence of the complete independence of the spectroscopic and photometric metallicities, this correlation points to a real metallicity spread in M 3. The absolute magnitudes of the variables follow a similar trend with both the spectroscopic and photometric metallicities as the general $M_V - {\rm [Fe/H]}$ relation predicts. This fact supports that the detected range in the metallicities of the variables is real.
Composing crosscutting concerns using composition filters

It has been demonstrated that certain design concerns, such as access control, synchronization, and object interactions cannot be expressed in current OO languages as a separate software module [4, 7]. These so-called crosscutting concerns generally result in implementations scattered over multiple operations. If a crosscutting concern cannot be treated as a single module, its adaptability and reusability are likely to be reduced. A number of programming techniques have been proposed to express crosscutting concerns, for example, adaptive programming [9], AspectJ [8], Hyperspaces [10], and Composition Filters [1]. Here, we present the Composition Filters (CF) model and illustrate how it addresses evolving crosscutting concerns.
Speech emotion recognition using a deep autoencoder

The main objective of the emotion recognition systems is to improve the humanmachine interaction, giving them a more natural behavior to attend different situations and user requirement. Several works on this domain use the prosodic features and the spectrum characteristics of speech signal with classifiers based on neural networks, Gaussian mixtures and other standards classifiers. In this paper a deep autoencoder based on a Multilayer perceptron was used as a classifier. Following the deep learning paradigm, an autoencoder training strategy layer by layer was implemented, which results in a stack of perceptrons with a set of “good” weights. A final fine-tune training was applied to the whole classifier. Many configurations were evaluated in order to predict six different emotions and neutral emotional state. Performance of the classifier was over 70%, promoting better results for this novel approach. Key words— Emotion Recognition, Deep Autoencoder, Multilayer Perceptron.
Milk versus medicine for the treatment of iron deficiency anaemia in hospitalised infants

Aims: To compare iron fortified follow-on milk (iron follow-on), iron fortified partially modified cows’ milk (iron milk), and iron medicine for the treatment of iron deficiency anaemia (IDA) in hospitalised infants. Methods: In a randomised controlled trial, infants aged 9–23 months with IDA and who were hospitalised with an acute illness received iron follow-on (12 mg/l ferrous iron), iron milk (12.9 mg/l ferrous iron), or iron medicine (ferrous gluconate at 3 mg/kg of elemental iron once daily). All interventions were given for three months. Changes in measures of iron status three months after hospital discharge were determined. Results: A total of 234 infants were randomised. Iron status was measured at follow up in 59 (70%) iron medicine, 49 (66%) iron follow-on, and 54 (70%) iron milk treated infants. There was a significant (mean, 95% CI) increase in haemoglobin (15 g/l, 13 to 16) and iron saturation (9%, 8 to 10) and decrease in ferritin (−53 μg/l, −74 to −31) in all three groups. Mean cell volume increased in iron follow-on (2 fl, 1 to 3) and iron milk (1 fl, 0.1 to 3) treated infants, but not in the iron medicine group (1 fl, −1 to 2). The proportion with IDA decreased in all three groups: iron medicine 93% to 7%, iron follow-on 83% to 8%, and iron milk 96% to 30%. Adverse effects, primarily gastrointestinal, occurred in 23% of the iron medicine, 14% of the iron follow-on, and 13% of the iron milk group. Conclusions: Iron fortified follow-on milk, iron fortified partially modified cows’ milk, and iron medicine all effectively treat IDA in infancy.
Performance Comparison of Daubechies, Biorthogonal and Haar Transform for Grayscale Image Compression

Image compression is process to remove the redundant information from the image so that only essential information are stored the storage size, transmission bandwidth and transmission time. In this paper comparative analysis of gray scale image compression is done by three different methods that are Daubechies Transform, Haar Transform and Biorthogonal Transform. Experimental results demonstrate that the Daubechies algorithm is more efficient for PSNR and MSE while Haar Wavelet Transform provides the better compression ratio.
Modelling and Analysis on Biomechanical Dynamic Characteristics of Knee Flexion Movement under Squatting

The model of three-dimensional (3D) geometric knee was built, which included femoral-tibial, patellofemoral articulations and the bone and soft tissues. Dynamic finite element (FE) model of knee was developed to simulate both the kinematics and the internal stresses during knee flexion. The biomechanical experimental system of knee was built to simulate knee squatting using cadaver knees. The flexion motion and dynamic contact characteristics of knee were analyzed, and verified by comparing with the data from in vitro experiment. The results showed that the established dynamic FE models of knee are capable of predicting kinematics and the contact stresses during flexion, and could be an efficient tool for the analysis of total knee replacement (TKR) and knee prosthesis design.
A Simple Nonlinear Adaptive-Fuzzy Passivity-Based Control of Power Systems

A new intelligent nonlinear control for power system stabilizers that improves the transient stability is proposed. To guarantee high performance with low complexity cost, new concepts on the passivity design under unknown disturbance inputs, as well as on the adaptive fuzzy logic rule extraction are introduced. This permits the most possible simple design implementation of an adaptive-fuzzy logic passivity-based controller which is developed on an equivalent model of the system obtained by a suitable use of the backstepping technique. The overall scheme is decentralized providing local output feedback controllers, supported by a very simple adaptive-fuzzy scheme of only three rules. A detailed analysis proves that the proposed control scheme ensures uniform ultimate boundedness of all the error variables in an arbitrarily small region around the origin. Extensive simulations on a two machine infinite bus power system on which a permanent serious fault occurs, confirm the theoretical results and verify an excellent system performance.
Stability issues in a Biological Model of Self and Non-self Immune Regulation

In this paper, we analyze the stability of a model for the self/non-self discrimination. The model simulates how the T helper cells (Th), namely lymphocytes developed in the thymus, learn which antigens are self and which ones are non-self. All antigen-responsive cells are born without effector activity and, in the initial stage, have two pathways open to them: inactivation and activation. The choice between these two paths depends on the presence or absence of effector T-helpers (eTh). Thus, the problem is to provide a model for the origin of the first eTh. A kinetic formulation can be modelled with 6 variables. To have a steady state, the system starts at particular levels of populations and has to stay at these levels as long as there is no external action. A stable steady state is reached when the net change of each population equals zero. We analyze the instability of the system in respect to the SI, the proportion of anti-self cells in the total number of repertoire (anti-self and anti-non self cells). In addition, we explore the spectrum of the control parameter SI and we discover a point where the stability changes its behavior
Human protein status modulates brain reward responses to food cues.

BACKGROUND Protein is indispensable in the human diet, and its intake appears tightly regulated. The role of sensory attributes of foods in protein intake regulation is far from clear. OBJECTIVE We investigated the effect of human protein status on neural responses to different food cues with the use of functional magnetic resonance imaging (fMRI). The food cues varied by taste category (sweet compared with savory) and protein content (low compared with high). In addition, food preferences and intakes were measured. DESIGN We used a randomized crossover design whereby 23 healthy women [mean ± SD age: 22 ± 2 y; mean ± SD body mass index (in kg/m(2)): 22.5 ± 1.8] followed two 16-d fully controlled dietary interventions involving consumption of either a low-protein diet (0.6 g protein · kg body weight(-1) · d(-1), ~7% of energy derived from protein, approximately half the normal protein intake) or a high-protein diet (2.2 g protein · kg body weight(-1) · d(-1), ~25% of energy, approximately twice the normal intake). On the last day of the interventions, blood oxygen level-dependent (BOLD) responses to odor and visual food cues were measured by using fMRI. The 2 interventions were followed by a 1-d ad libitum phase, during which a large array of food items was available and preference and intake were measured. RESULTS When exposed to food cues (relative to the control condition), the BOLD response was higher in reward-related areas (orbitofrontal cortex, striatum) in a low-protein state than in a high-protein state. Specifically, BOLD was higher in the inferior orbitofrontal cortex in response to savory food cues. In contrast, the protein content of the food cues did not modulate the BOLD response. A low protein state also increased preferences for savory food cues and increased protein intake in the ad libitum phase as compared with a high-protein state. CONCLUSIONS Protein status modulates brain responses in reward regions to savory food cues. These novel findings suggest that dietary protein status affects taste category preferences, which could play an important role in the regulation of protein intake in humans. This trial was registered at www.trialregister. nl/trialreg/admin/rctview.asp? TC=3288 as NTR3288.
Use of Spatial Information and Search Strategies in a Water Maze Analog in Drosophila melanogaster

Learning the spatial organization of the environment is crucial to fitness in most animal species. Understanding proximate and ultimate factors underpinning spatial memory is thus a major goal in the study of animal behavior. Despite considerable interest in various aspects of its behavior and biology, the model species Drosophila melanogaster lacks a standardized apparatus to investigate spatial learning and memory. We propose here a novel apparatus, the heat maze, conceptually based on the Morris water maze used in rodents. Using the heat maze, we demonstrate that D. melanogaster flies are able to use either proximal or distal visual cues to increase their performance in navigating to a safe zone. We also show that flies are actively using the orientation of distal visual cues when relevant in targeting the safe zone, i.e., Drosophila display spatial learning. Parameter-based classification of search strategies demonstrated the progressive use of spatially precise search strategies during learning. We discuss the opportunity to unravel the mechanistic and evolutionary bases of spatial learning in Drosophila using the heat maze.
Mechanisms of acid resistance in enterohemorrhagic Escherichia coli

Enterohemorrhagic strains of Escherichia coli must pass through the acidic gastric barrier to cause gastrointestinal disease. Taking into account the apparent low infectious dose of enterohemorrhagic E. coli, 11 O157:H7 strains and 4 commensal strains of E. coli were tested for their abilities to survive extreme acid exposures (pH 3). Three previously characterized acid resistance systems were tested. These included an acid-induced oxidative system, an acid-induced arginine-dependent system, and a glutamate-dependent system. When challenged at pH 2.0, the arginine-dependent system provided more protection in the EHEC strains than in commensal strains. However, the glutamate-dependent system provided better protection than the arginine system and appeared equally effective in all strains. Because E. coli must also endure acid stress imposed by the presence of weak acids in intestinal contents at a pH less acidic than that of the stomach, the ability of specific acid resistance systems to protect against weak acids was examined. The arginine- and glutamate-dependent systems were both effective in protecting E. coli against the bactericidal effects of a variety of weak acids. The acids tested include benzoic acid (20 mM; pH 4.0) and a volatile fatty acid cocktail composed of acetic, propionic, and butyric acids at levels approximating those present in the intestine. The oxidative system was much less effective. Several genetic aspects of E. coli acid resistance were also characterized. The alternate sigma factor RpoS was shown to be required for oxidative acid resistance but was only partially involved with the arginine- and glutamate-dependent acid resistance systems. The arginine decarboxylase system (including adi and its regulators cysB and adiY) was responsible for arginine-dependent acid resistance. The results suggest that several acid resistance systems potentially contribute to the survival of pathogenic E. coli in the different acid stress environments of the stomach (pH 1 to 3) and the intestine (pH 4.5 to 7 with high concentrations of volatile fatty acids). Of particular importance to the food industry was the finding that once induced, the acid resistance systems will remain active for prolonged periods of cold storage at 4 degrees C.
Kernel based learning approach for satellite image classification using support vector machine

Machine learning is a scientific computing discipline to automatically learn to recognize complex patterns and make intelligent decisions based on the set of observed examples (training data). Support Vector Machine (SVM) is a supervised machine learning method used for classification. An SVM kernel based algorithm builds a model for transforming a low dimension feature space into high dimension feature space to find the maximum margin between the classes. In the field of geospatial data processing, there is a high degree of interest to find an optimal image classifier technique. Many image classification methods such as maximum likelihood, K-Nearest are being used for determining crop patterns, land use and mining other useful geospatial information. But SVM is now considered to be one of the powerful kernel based classifier that can be adopted for resolving classification problems. The objective of the study is to use SVM technique for classifying multi spectral satellite image dataset and compare the overall accuracy with the conventional image classification method. LISS-3 and AWIFS sensors data from Resourcesat-1, Indian Remote Sensing (IRS) platform were used for this analysis. In this study, some of the open source tools were used to find out whether SVM can be a potential classification technique for high performance satellite image classification.
Integrative Neuroscience Review Article Long-latency Reflexes Account for Limb Biomechanics through Several Supraspinal Pathways

Accurate control of body posture is enforced by a multitude of corrective actions operating over a range of time scales. The earliest correction is the short-latency reflex (SLR) which occurs between 20–45 ms following a sudden displacement of the limb and is generated entirely by spinal circuits. In contrast, voluntary reactions are generated by a highly distributed network but at a significantly longer delay after stimulus onset (greater than 100 ms). Between these two epochs is the long-latency reflex (LLR) (around 50–100 ms) which acts more rapidly than voluntary reactions but shares some supraspinal pathways and functional capabilities. In particular, the LLR accounts for the arm's biomechanical properties rather than only responding to local muscle stretch like the SLR. This paper will review how the LLR accounts for the arm's biomechanical properties and the supraspinal pathways supporting this ability. Relevant experimental paradigms include clinical studies, non-invasive brain stimulation, neural recordings in monkeys, and human behavioral studies. The sum of this effort indicates that primary motor cortex and reticular formation (RF) contribute to the LLR either by generating or scaling its structured response appropriate for the arm's biomechanics whereas the cerebellum scales the magnitude of the feedback response. Additional putative pathways are discussed as well as potential research lines.
Software metrics

Software metrics, an area of software engineering, is concerned with various measurements of computer software and its development. Software metrics, its importance, some current areas of investigation, and problems are described. An annotated bibliography of work in software metrics is included.I often say that when you can measure what you are speaking about, and express it in numbers, you know something about it; but when you cannot measure it, when you cannot express it in numbers, your knowledge is of a meagre and unsatisfactory kind: it may be the beginning of knowledge, but you have scarcely, in you thoughts, advanced to the stage of science, whatever the matter may be. ---Lord Kelvin, Popular Lectures and Addresses, volume 1, 1889