Miracle-dz/UniFAR-FTUs huggingface dataset:
Contact Binaries with Additional Components. I. The Extant Data

We have attempted to establish observational evidence for the presence of distant companions that may have acquired and/or absorbed angular momentum during the evolution of multiple systems, thus facilitating or enabling the formation of contact binaries. In this preliminary investigation we use several techniques (some of them distance-independent) and mostly disregard the detection biases of individual techniques in an attempt to establish a lower limit to the frequency of triple systems. While the whole sample of 151 contact binary stars brighter than Vmax = 10 mag gives a firm lower limit of 42% ± 5%, the corresponding number for the much better observed northern-sky subsample is 59% ± 8%. These estimates indicate that most contact binary stars exist in multiple systems.
Role of transcription factors in inflammatory lung diseases

Acute and chronic alveolar and/or bronchial inflammation is thought to be central to the pathogenesis of many lung disorders such as asthma, chronic obstructive pulmonary disease (COPD), adult respiratory distress syndrome (ARDS), and idiopathic pulmonary fibrosis (IPF). The site and specific characteristics of the inflammatory responses may be different in each of these diseases, but all are characterised by the recruitment to the lungs and activation of immune and inflammatory cells. These activated cells produce cytokines, oxidants and many other mediators which are involved in inflammation.1 2 Recent data indicate that, in addition, airway epithelial cells are able to act as immune effector cells by secreting pro-inflammatory mediators, oxidants, and cytokines.3 Once triggered, an inappropriate chronic inflammatory response persists in these conditions and is presumed to result in lung injury. The intracellular molecular mechanisms in response to environmental signals, leading to increased gene expression and biosynthesis of proinflammatory mediators by airspace inflammatory and epithelial cells, are of considerable current interest. It is now recognised that there are gene specific factors which regulate the transcription of particular genes by affinity binding to specific recognition motifs, which are usually located in the upstream (5′) promoter region of the gene. These factors, which are usually located in the cytosol, can translocate to the cell nucleus and, by binding to specific consensus sites, can upregulate the rate of transcription of the gene and therefore increase the formation of messenger RNA (mRNA) and the protein of an inflammatory mediator. Some transcription factors are cell specific, but others are ubiquitous. Their activity can be modulated by environmental signals and they may play a key role in immune and inflammatory responses. The transcription factors about which there is most information in immune and inflammatory responses are nuclear factor-kappa (κ)B (NF-κB) and activator protein 1 (AP-1). …
Coral Reefs and Changing Seawater Carbonate Chemistry

Seawater carbonate chemistry of the mixed layer of the oceans is changing rapidly in response to increases in atmospheric CO2. The formation and dissolution of calcium carbonate is now known to be strongly affected by these changes, but many questions remain about other controls on biocalcification and inorganic cementation that confound our attempts to make accurate predictions about the effects on both coral reef organisms and reefs themselves. This chapter overviews the current knowledge of the relationship between seawater carbonate chemistry and coral reef calcification, identifies the hurdles in our understanding of the two, and presents a strategy for overcoming those hurdles.
Exponential Groups 2: Extensions of Centralizers and Tensor Completion of CSA-Groups

For a CSA group $G$ and a wide class of abelian groups $A$ we give an explicit construction for the tensor $A$-completion of $G$ using free products with amalgamations. We apply the obtained results to the study of basic properties of $A$-free groups. In particular, canonical and reduced forms of elements in $A$-free groups are introduced, and then commuting and conjugate elements are described.
Adaptive Jacobian Tracking Control of Robots based on Visual Task-space Information

Most research so far on trajectory tracking control of robot has assumed that the kinematics of the robot is known exactly. This paper extends our recent work on adaptive Jacobian tracking control by deriving a new algorithm for trajectory tracking of robots with uncertain kinematics and dynamics. The algorithm requires only to measure the end-effector position in visual space, besides the robot’s joint angles and joint velocities. Experimental results are presented to illustrate the performance of the proposed controllers. In the experiments, we demonstrate that the robot’s shadow can be used to control the robot.
Brain and Serum Androsterone Is Elevated in Response to Stress in Rats with Mild Traumatic Brain Injury

Exposure to lateral fluid percussion (LFP) injury consistent with mild traumatic brain injury (mTBI) persistently attenuates acoustic startle responses (ASRs) in rats. Here, we examined whether the experience of head trauma affects stress reactivity. Male Sprague-Dawley rats were matched for ASRs and randomly assigned to receive mTBI through LFP or experience a sham surgery (SHAM). ASRs were measured post injury days (PIDs) 1, 3, 7, 14, 21, and 28. To assess neurosteroids, rats received a single 2.0 mA, 0.5 s foot shock on PID 34 (S34), PID 35 (S35), on both days (2S), or the experimental context (CON). Levels of the neurosteroids pregnenolone (PREG), allopregnanolone (ALLO), and androsterone (ANDRO) were determined for the prefrontal cortex, hippocampus, and cerebellum. For 2S rats, repeated blood samples were obtained at 15, 30, and 60 min post-stressor for determination of corticosterone (CORT) levels after stress or context on PID 34. Similar to earlier work, ASRs were severely attenuated in mTBI rats without remission for 28 days after injury. No differences were observed between mTBI and SHAM rats in basal CORT, peak CORT levels or its recovery. In serum and brain, ANDRO levels were the most stress-sensitive. Stress-induced ANDRO elevations were greater than those in mTBI rats. As a positive allosteric modulator of gamma-aminobutyric acid (GABAA) receptors, increased brain ANDRO levels are expected to be anxiolytic. The impact of brain ANDRO elevations in the aftermath of mTBI on coping warrants further elaboration.
A Quantitative Evaluation Model of Group User Experience

This paper explores the problem of user experience evaluation, in particular the quantitative evaluation of group user experience, in the ubiquitous computing environments. Firstly, the classification and definition of four different categories of user groups are proposed and the notion of group user experience is introduced. Secondly, we analyze the quantitative evaluation of group user experience for different user groups and establish a uniform evaluation model for group user experience. Particularly, we employ two quantitative metrics, user rating and user attention duration, as the main criteria for evaluating user experience. At the same time, the intercommunication and differences among group members in the capacity of information acquisition, the degree of correlation with other members and the weight of impact to the overall group user experience are taken into account to form a general quantitative evaluation model of group user experience for different user groups. Finally, we evaluate the effectiveness of the proposed model with preliminary experiments.
Energy efficient deployment of mobile node in wireless Sensor networks 

The wired environment encomprises with that of physical devices and interfaces of electrical equipments. Though the wireless trait has been emerged with its flexibility in information and communication technology, the wired atmosphere has the plugged in resource of fidelity and reliability providing armor to physical and logical data. The industrial field with the basement of control and instrumentation technology which makes the entire world automated. The hardware is ubiquitous with tangible outputs in robotics field also which further progress tremendously. This project deals with the robotic technique to control the various input parameters and puts the technical disorder in safe mode from electrical damage. Proposed i n fo r ma t io n a b o u t manage the power consumption in Wireless sensor network based o n e f f e c t i v e n o d e deployment by making the sensor communication in standby mode using a hardware model integrating multiple sensors in a single devices.ie, implementing various sensors in a single hardware unit. Also the recursive mechanism provides stability and infers the system in total power consumption which in turn gives the good performance. A wireless sensor networks(WSN) consists of spatically distributed autonomous sensing devices which cooperatively moniter physical or environmental conditions,such as temperature, sound, pressure, motion at different locations. A wireless sensor network is a collection of nodes organized into a cooperative network. Each node consists of processing capability (one or more microcontrollers, CPUs or DSP chips), may contain multiple types of memory (program, data and flash memories), have a RF transceiver (usually with a single Omni-directional antenna), have a power source (e.g. batteries and solar cells), and accommodate various sensors and actuators. The nodes communicate wirelessly and often self-organize after being deployed in an adhoc fashion. Recently there has been renewed interest in using mobile robots as sensor carring platforms in order to perform hazardous tasks [6]. One of the major activities of mobile robots is to move from one place to another. In order to reach the goal position, mobile robots are required to follow a predetermined route. Deploying large numbers of sensors has been receiving a lot of attention for detection of hazardous biological or chemical substances in public buildings,
Improvements on a Novel Hybrid Tracking System

Today's tracking systems typically require a fixed installation in a room in order to not drift quadratically with time like common inertia measurement units. This makes tracking a delicate task in ad-hoc VR installations. To overcome this problem, this paper describes a novel hybrid tracking system and shows further algorithmic improvements to increase tracking accuracy.
ACUAI framework for automatic composition of web services using gaming AI

In a domain SOA environment, multiple services exist to help in executing the users requests but manually handling each request is time wasting and very tiring thus the idea of automatic composition of web services emerged. This paper describes the ACUAI framework which is an AI automatic composer for web services with learning capabilities, since games have the most developed dynamic system adaptation to user action this framework uses two AI techniques which are used in games development they are decision trees and the finite state machines, the user request will be handled in the same way games react to user input then a decision is taken based on current state of the orchestration and then the algorithm changes the state of the orchestration according to the last decision taken to be able to guide the orchestration towards the goal and get a successful composition then each successful composition and its template request are saved to be used later on in enhancing the execution time.
Detecting unknown word senses using concept dictionary

In this paper, we present a method for detecting unknown word senses using a concept dictionary and newspaper articles. It is very important to detecting unknown word senses for document classiﬁcation, information retrieval, information extraction, etc. Although for extracting similar word pairs the methods which use similarity of case structure between two words are used, comparison between similarity of two words suffers word sparseness problem. Especially, it is necessary to solve this problem for detecting word senses of proper nouns which are not listed in the dictionary. The proposed method used hierarchical semantic features of a concept dictionary in order to deal with this problem. We performed some experiments in order to conﬁrm effectiveness of the method.
Curvature-Based Feature Extraction Method for 3D Model Retrieval

Curvature on the surface of 3D mesh model is an important discrete differential geometrical descriptor. It can show the curving degree very well for those models with curving pieces and the ones with extreme points or extension components. In this paper, we use mean curvature and corresponding coordinates of the vertexes on the surface as the feature descriptor of model. The descriptor we defined describes models accurately and keeps invariant for transformation and rotation. Additionally, we bring EMD (Earth Moving Distance) method into the similarity measure frame. This comparison way is very efficient and especially adapt to these conditions: different numbers of the two features, variant or indefinite dimension of the features. Thought several retrieval experiments, the results implied that this descriptor could be used to find the exact model from the PSB model library. Particularly for models which are made up of curving pieces and those models with extreme points or parts, the result showed much better than other feature descriptors.
Conditions on Ramsey non-equivalence

Given a graph H, a graph G is called a Ramsey graph of H if there is a monochromatic copy of H in every coloring of the edges of G with two colors. Two graphs G, H are called Ramsey equivalent if they have the same set of Ramsey graphs. Fox et al. [J. Combin. Theory Ser. B 109 (2014), 120--133] asked whether there are two non-isomorphic connected graphs that are Ramsey equivalent. They proved that a clique is not Ramsey equivalent to any other connected graph. Results of Nesetril et al. showed that any two graphs with different clique number [Combinatorica 1(2) (1981), 199--202] or different odd girth [Comment. Math. Univ. Carolin. 20(3) (1979), 565--582] are not Ramsey equivalent. These are the only structural graph parameters we know that "distinguish" two graphs in the above sense. This paper provides further supportive evidence for a negative answer to the question of Fox et al. by claiming that for wide classes of graphs, chromatic number is a distinguishing parameter. In addition, it is shown here that all stars and paths and all connected graphs on at most 5 vertices are not Ramsey equivalent to any other connected graph. Moreover two connected graphs are not Ramsey equivalent if they belong to a special class of trees or to classes of graphs with clique-reduction properties.
A comprehensive and practical model for HARQ in LTE system

This paper presents a HARQ model in LTE system level simulation capable of reliably predicting the block error ratio improvement. Our model is based on the Mutual Information Effective SINR Mapping (MIESM) which is usually used as the link-to-System (L2S) interface and both SISO and MIMO transmission mode are supported. In addition, taking the rate matching, soft combining into account, the model distinguishes between Chase Combining (CC) gains and Incremental Redundancy (IR) gains from retransmission packets. As a consequence, our model can not only avoid bit level operations so that to be used in system level simulation but also achieve good accuracy. The simulation results show that HARQ can reduce the block error rate (BLER), improve throughput, and perform better in low-speed scenario than in high-speed case.
Review of Mixed‐Integer Nonlinear and Generalized Disjunctive Programming Methods

This work presents a review of the main deterministic mixed-integer nonlinear programming (MINLP) solution methods for problems with convex and nonconvex functions. An overview for deriving MINLP formulations through generalized disjunctive programming (GDP), which is an alternative higher-level representation of MINLP problems, is also presented. A review of solution methods for GDP problems is provided. Some relevant applications of MINLP and GDP in process systems engineering are described in this work.
The High-Z Supernova Search: Measuring Cosmic Deceleration and Global Curvature of the Universe Using Type Ia Supernovae

The High-Z Supernova Search is an international collaboration to discover and monitor Type Ia supernovae (SNe Ia) at z > 0.2 with the aim of measuring cosmic deceleration and global curvature. Our collaboration has pursued a basic understanding of supernovae in the nearby universe, discovering and observing a large sample of objects and developing methods to measure accurate distances with SNe Ia. This paper describes the extension of this program to z ≥ 0.2, outlining our search techniques and follow-up program. We have devised high-throughput filters that provide accurate two-color rest frame B and V light curves of SNe Ia, enabling us to produce precise, extinction-corrected luminosity distances in the range 0.25 < z < 0.55. Sources of systematic error from K-corrections, extinction, selection effects, and evolution are investigated, and their effects estimated. We present photometric and spectral observations of SN 1995K, our program's first supernova (SN), and use the data to obtain a precise measurement of the luminosity distance to the z = 0.479 host galaxy. This object, when combined with a nearby sample of SNe, yields an estimate for the matter density of the universe of ΩM=-0.2−0.8+1.0 if ΩΛ = 0. For a spatially flat universe composed of normal matter and a cosmological constant, we find ΩM=0.4−0.4+0.5, Ω=0.6−0.5+0.4. We demonstrate that with a sample of ~30 objects, we should be able to determine relative luminosity distances over the range 0 < z < 0.5 with sufficient precision to measure ΩM with an uncertainty of ±0.2.
Stable isotopes in precipitation in the Asian monsoon region

[1] The influence of the Asian monsoon on the δ18O composition of precipitation is investigated on the basis of the ECHAM-4 Atmospheric General Circulation Model (AGCM), fitted with stable isotopic tracers. The model is forced with prescribed sea surface temperatures (SST) over the last few decades of the 20th century. The simulated climate and climate–stable isotope relationships are validated with observational data from the International Atomic Energy Agency–Global Network of Isotopes in Precipitation (IAEA-GNIP) and reanalysis data. The model shows deficiencies when simulating interannual variations of monsoon precipitation, but the associated monsoon circulation is quite accurately reproduced, in particular when run in a high-resolution (T106) version. The modeled stable isotope distribution is quite similar to observations, but the local climatic controls on δ18O are overestimated. The influence of the Asian monsoon on δ18O is analyzed on the basis of a vertical wind shear index M, indicative of variations in large-scale monsoon strength. The ECHAM model simulates a significant negative relationship between δ18O composition of precipitation and M over most monsoon-affected areas, consistent with the IAEA-GNIP data. Variations in the amount of precipitation provide a first-order explanation for this relationship. Distillation processes during transport and hence increased rainout and depletion of heavy isotopes upstream may also lead to a significant monsoon-δ18O relationship in areas where local precipitation is not affected by monsoon variability. The modern δ18O record from the Dasuopu ice core in the Himalayas is a good indicator of the large-scale monsoon circulation, a relationship that is correctly simulated by the T106 version of the ECHAM model. Our results suggest that δ18O variations in this region are sensitive to fluctuations in Asian monsoon intensity.
Measurement of retinal thickness for detection of Glaucoma

The thickness of retinal nerve fibre layer (RNFL) is one of the parameters for assessing the Glaucoma. It is second largest disease which causes blindness. Glaucoma is caused due to the increase of intra ocular pressure (IOP). Vision is lost before the patient becomes aware of glaucoma. Optical Coherence Tomography (OCT) provides enhanced depth and clarity of viewing tissues with high resolution compared with other medical imaging device such as fundus camera or intravascular imaging. This paper presents an automatic method to find the thickness of RNFL using OCT images. The proposed algorithm first extracts all the layers present in the retina using Sobel operator and an algorithm is then developed. The thickness measurement of RNFL is automatically displayed based on pixel calculation. The calculated thickness values are compared with the original values obtained from hospital. The result shows that the proposed algorithm is efficient in segmenting the region of interest without manual intervention. The effectiveness of the proposed method is proved statistically by the performance analysis.
Cost-Sensitive Support Vector Machine Based on Weighted Attribute

In practice it is existed a matter in classified problem. The problem can be described as that the different sort has different wrong classified cost. In this paper we propose a Cost-sensitive SVM approach based on weighted attribute. The approach first calculates the weightiness of feature attributes corresponded to the classification attribute, then calculates the corresponding weightiness of attribute for all sample. In the end the samples are used for Cost-sensitive SVM training and testing. The experimental results show that the approach can improve the classification precision of the cost sensitive samples, and also the use of feature attribute increases the integer classified capability of the classifier. The approach has important realistic significance of unbalanced wrong-classification cost in classified problem.
Design LSP Trajectory Model for Speech Recognition

Speech signal is the continuous signal which has the characteristics in its own. For recognizing the speech signal, the system must be able to classify and recognize the speech feature. Almost of this system is speaker-independent speech system. This paper presents statistical methods for speech recognition by extracting the features of the speech and analyzing their trajectory. The speech feature has been extracted to line spectral pairs (LSP) coefficients and then uses the statistic model to pattern the trajectory for recognizing the signal. The result shows that the using technique usually works well which the maximum accuracy of recognition is 99.67% at number 1 of male speech and the minimum accuracy of recognition is 82.33% at number 5 of female speech.