Miracle-dz/UniFAR-FTUs huggingface dataset:
Complex Treatment of Multiple Sclerosis Patients by Use of Fetal StemCells

Objective: Refinement for all existing methods of treatment for the multiple sclerosis patients by means of combined method including conventional therapy and administration of fetal stem cells (FSCs)-suspensions containing stem cells derived from human fetal liver and brain. Materials and methods: 51 patients diagnosed with MS participated in the study including 27 men and 24 women aged 27 to 56 years. Average age range for men was 34.2 ± 1.2 years, for women it constituted 31.7 ± 1.3 years. 33 patients were allocated in the Main Group (MG) including 20 men (mean age 29.8 ± 2.2 years) and 13 women (average age 31.3 ± 2.1 years). The Control Group (CG) was composed of 18 patients diagnosed with MSincluding 10 men (mean age of 30.5 ± 1.2 years) and 8 women (average age 31.4 ± 1.4 years). Simultaneously, the scale of MMSE was applied for objective study of cognitive functions among our patients. State Trait Anxiety Inventory was effective for emotional-anxiety disturbances. In addition, we assessed depression in patients by means of Beck Depression Inventory. Results: Authors proved efficacy and safety of FSCs suspensions for MS patients. We emphasized a significant improvement of neurology deficit in the MG already over 6 months after fetal stem cells transplantation (FSCT), whereas the CG patients revealed such advantages over 12 months. Improvement of cognitive functions was characteristic for the MG starting from 6 months after FSCT. Anxiety and depression significantly decreased and these results were observed over 6 months after FSCT in the MG. In the CG, the same values which significantly decreased over 12 months after treatment and were recorded. Conclusion: FSCs use in complex treatment of patients with MS stabilizes disease compensation, improves cognitive functions as well as psycho-emotional state of the patients.
Robust adaptive dynamic surface control for nonlinear systems with output unmodeled dynamics

This paper presents a robust adaptive output-feedback dynamic surface control for a class of nonlinear systems with output unmodeled dynamics. A new relation ship between the output and the state of the output unmodeled dynamics is established while the unmodeled dynamics is input-to-state practically stable. With such relationship, it is shown that all the signals of the closed-loop system are bounded and the tracking error can be made arbitrarily small. Simulation results are presented to demonstate the efficiency of the proposed scheme.
Robust range estimation using acoustic and multimodal sensing

Many applications of robotics and embedded sensor technology can benefit from fine-grained localization. Fine-grained localization can simplify multi-robot collaboration, enable energy efficient multi-hop routing for low-power radio networks, and enable automatic calibration of distributed sensing systems. We focus on range estimation, a critical prerequisite for fine-grained localization. While many mechanisms for range estimation exist, any individual mode of sensing can be blocked or confused by the environment. We present and analyze an acoustic ranging system that performs well in the presence of many types of interference, but can return incorrect measurements in non-line-of-sight conditions. We then suggest how evidence from an orthogonal sensory channel might be used to detect and eliminate these measurements. The work illustrates the more general research theme of combining multiple modalities to obtain robust results.
Real-time face detection with self-adaptive cost-sensitive AdaBoost

In this paper, two main improvements are achieved in AdaBoost according to practical requirements of face detection. One is that a self-adaptive cost-sensitive coefficient related with cascade classifier is introduced to treat the classification status of positive and negative examples differently. The other is that the weights are normalized separately for positive and negative examples after their weights updating steps in each boosting circulation. Experiments demonstrate that in face detection, the self-adaptive cost-sensitive AdaBoost shows higher detection rates and lower false positive rates. Moreover, the training time is less than that of the naive one.
Study on the ionospheric weather and radio propagation in CRIRP

In this paper, we summarize the progress in ionopsheric weather and radio propagation in China Research Institute of Radiowave Propagation, including the ionospheric observations, the studies of ionospheric physics, ionospheric mapping, ionospheric modelling and artificial ionospheric modification, the ionospheric radio propagation studies, and ionospheric services.
Control of bi-directional DC-DC converter using batteries for wind power generation

The wind turbines and storage batteries are considered one of the main components of distribution systems. The paper describes in details the design and control of one of the bi-directional DC-DC converter topologies. It is bi-directional Dual Active Bridge. A control strategy, using PI controllers, for the storage batteries is developed based on constant wind turbine speed. With normal wind power generation, the batteries are set in a charging mode. When wind power generation fluctuates due to large wind speed variation, the developed control strategy allows batteries to mitigate these power fluctuations and avoids severe voltage transients on congested power systems. An actual wind speed data are used to simulate the impact of wind penetration during a 24-hour period. The simulations are carried out for wind without and with power fluctuation.
GOMES: A group-aware multi-view fusion approach towards real-world image clustering

Different features describe different views of visual appearance, multi-view based methods can integrate the information contained in each view and improve the image clustering performance. Most of the existing methods assume that the importance of one type of feature is the same to all the data. However, the visual appearance of images are different, so the description abilities of different features vary with different images. To solve this problem, we propose a group-aware multi-view fusion approach. Images are partitioned into groups which consist of several images sharing similar visual appearance. We assign different weights to evaluate the pairwise similarity between different groups. Then the clustering results and the fusion weights are learned by an iterative optimization procedure. Experimental results indicate that our approach achieves promising clustering performance compared with the existing methods.
Reduction of seizures by transplantation of cortical GABAergic interneuron precursors into Kv1.1 mutant mice

Epilepsy, a disease characterized by abnormal brain activity, is a disabling and potentially life-threatening condition for nearly 1% of the world population. Unfortunately, modulation of brain excitability using available antiepileptic drugs can have serious side effects, especially in the developing brain, and some patients can only be improved by surgical removal of brain regions containing the seizure focus. Here, we show that bilateral transplantation of precursor cells from the embryonic medial ganglionic eminence (MGE) into early postnatal neocortex generates mature GABAergic interneurons in the host brain. In mice receiving MGE cell grafts, GABA-mediated synaptic and extrasynaptic inhibition onto host brain pyramidal neurons is significantly increased. Bilateral MGE cell grafts in epileptic mice lacking a Shaker-like potassium channel (a gene mutated in one form of human epilepsy) resulted in significant reductions in the duration and frequency of spontaneous electrographic seizures. Our findings suggest that MGE-derived interneurons could be used to ameliorate abnormal excitability and possibly act as an effective strategy in the treatment of epilepsy.
Nonmonotonic Consequences in Default Domain Theory 1

Default domain theory is a framework for representing and reasoning about commonsense knowledge. Although this theory is motivated by ideas in Reiter's work on default logic, it is in some sense a dual framework. We make Reiter's default extension operator into a constructive method of building models, not theories. Domain theory, which is a well established tool for representing partial information in the semantics of programming languages, is adopted as the basis for constructing partial models. This paper considers some of the laws of nonmonotonic consequence, due to Gabbay and to Kraus, Lehmann, and Magidor, in the light of default domain theory. We remark that in some cases Gabbay's law of cautious monotony is open to question. We consider an axiomatization of the nonmonotonic consequence relation on prime open sets in the Scott topology { the natural logic { of a domain, which omits this law. We prove a representation theorem showing that such relations are in one to one correspondence with the consequence relations determined by extensions in Scott domains augmented with default sets. This means that defaults are very expressive: they can, in a sense, represent any reasonable nonmonotonic entailment. Results about what kind of defaults determine cautious monotony are also discussed. In particular, we show that the property of unique extensions guarantees cautious monotony, and we give several classes of default structures which determine unique extensions.
Friction compensation in hybrid force/velocity control of industrial manipulators

This paper deals with the implementation of a hybrid force/velocity controller for the automatic edge following of two-dimensional unknown planar contours performed by an industrial robot manipulator. In particular, the authors address the problem of compensating the joint friction effects that have to be taken into account in the controller design in order to achieve a reasonable performance with regards to normal force and tangential velocity errors. For that reason, two model-based friction-compensation methods are compared: a static method, based on a previously identified model, and an adaptive method, where joint friction parameters are recursively updated. By means of an extensive experimental activity, it is shown that, in spite of its simplicity and despite the friction effects changing in time during the robot operations, the devised adaptive procedure obtains a high performance in different operating conditions.
Moving Target Detection Algorithm Based on Susan Edge Detection and Frame Difference

Through the analysis of common moving target detecting algorithms, this paper proposes a moving target detecting algorithm based on Susan edge detection and frame difference. It detects the edge information of current frame image by Susan operator, then taking a differential operation between the current frame and the next frame image to get the outline of moving target. Finally, it extracts the target by using an and operation with two parts of information. The experimental results show that this algorithm is simple and effective, making up for the deficiency of a single frame difference method.
Outage Probability of MIMO Relay Systems with Relay Selection under Co-Channel Interferences

In this paper, a decode-and-forward multiple-input multiple-output relay system with relay selection under unequal power co-channel interferences is considered. In the system, transmit beamforming is applied at each transmitter, and maximal ratio combining is applied at each receiver. The closed- form exact outage probability expression of the system over Rayleigh fading channels has been derived. The result is valid for arbitrary antenna number and interferer number. Numerical investigation shows that the theoretical result makes an exact match with the computer simulations.
Classification of localization algorithms for wireless sensor network: A survey

Localization is an active field of research in wireless sensor networks WSNs. The information of exact physical location of the sensor nodes in WSNs is useful for various application e.g. intrusion detection, target tracking, environmental monitoring and network services etc. In this paper we present the classification and comparative study of localization algorithms. The goal of our consideration is to analyze, how these localization algorithms work in order to increase the life span of network nodes in harsh environments like oil fields, gas fields, forests, chemical factories and underground mines etc. and how to find the position of mobile node with Distributed, Range-based and Beacon-based Localization technique in harsh environments. Furthermore this paper also highlights some issues experienced by these localization techniques.
A scalable lock-free stack algorithm

The literature describes two high performance concurrent stack algorithms based on combining funnels and elimination trees. Unfortunately, the funnels are linearizable but blocking, and the elimination trees are non-blocking but not linearizable. Neither is used in practice since they perform well only at exceptionally high loads. The literature also describes a simple lock-free linearizable stack algorithm that works at low loads but does not scale as the load increases. The question of designing a stack algorithm that is non-blocking, linearizable, and scales well throughout the concurrency range, has thus remained open.This paper presents such a concurrent stack algorithm. It is based on the following simple observation: that a single elimination array used as a backoff scheme for a simple lock-free stack is lock-free, linearizable, and scalable. As our empirical results show, the resulting elimination-backoff stack performs as well as the simple stack at low loads, and increasingly outperforms all other methods (lock-based and non-blocking) as concurrency increases. We believe its simplicity and scalability make it a viable practical alternative to existing constructions for implementing concurrent stacks.
USING NAÏVE BAYES CLASSIFIER

Privacy-preserving data mining is discovering accurate patterns and rules without precise access to the original data. In this paper, we propose a novel algorithm for privacy preserving data mining. The proposed algorithm is based on the integration of RSA public key cryptosystem and homomorphic encryption scheme. No data is shared between distributed parties except the final result. Data mining algorithm is performed locally for each party. The final result of all parties is compared to get the target value. Previous solution for privacy preserving data mining of Naive Bayes classifier is based on secure sum that may permit collusion between parties, which is not here in proposed solution. Theoretical analysis and experimental results show that the proposed algorithm can provide good capability of privacy preserving, accuracy and efficiency.
FDTD subcell models powering latest progress in computational antenna optimization

This article demonstrates the capability of using the finite-differences time-domain (FDTD) method as simulation tool for optimizing the design of an antenna. The FDTD simulation method is locally enhanced with subcell modeling techniques, which incorporates a-priori known field behavior in (1) curved material interfaces and (2) strong field gradients near sharp metal edges. Combining the FDTD subcell modeling technique with a FDTD simulation hardware acceleration card enables the efficient optimization of several parameters based on genetic algorithms. The ongoing work targets the improved optimization of commercial CAD based mobile phones.
Vision-Based Autonomous Security Robot Nitesh

The goal of this paper is to develop a computer vision system that enables a robot to navigate the hallways of buildings using a generic webcam as the only sensor. OpenCV2.0 programmed in C++ is the primary tool used to develop the vision system software. Three algorithms were developed to identify the center of the hallway and guide the robot in the correct direction. The first two algorithms use a generic filter (normal, median, or Gaussian) followed by edge detection and then corner detection on the edgedetected image. The first algorithm identifies the strongest vertical lines on an image. Averaging the horizontal coordinates of the vertical lines indicates the location of the center of the hallway relative to the robot. The second algorithm utilizes the trapezoidal shape of the hallway formed where the floor meets the walls, as seen from the perspective of the robot. The y-coordinates associated with the trapezoid‟s legs are then compared to estimate robot orientation with respect to the walls. The third algorithm uses color to segment the floor from the rest of the features in the image (walls, ceiling, and obstacles). Once again, the trapezoidal shape appears and the center of the hallway is determined based on the location of the highest y-valued pixels identified as floor pixels. Test data indicates that none of these algorithms is singularly sufficient; however, combining their results they can identify the direction a robot must turn to remain in the center of the hallway with 96.6% accuracy. Furthermore, leveraging the results of multiple algorithms produces more robust navigation, where one algorithm covers over the shortcomings of another. The vision system architecture is designed to execute algorithms in parallel. Such a structure enables the addition and removal of algorithms without adversely affecting the system as a whole. Further algorithms may be developed and easily added to improve navigation. Additionally, the system may intelligently ignore results from algorithms that are recognized as inappropriate for certain situations.
Interspecies interactions are an integral determinant of microbial community dynamics

This study investigated the factors that determine the dynamics of bacterial communities in a complex system using multidisciplinary methods. Since natural and engineered microbial ecosystems are too complex to study, six types of synthetic microbial ecosystems (SMEs) were constructed under chemostat conditions with phenol as the sole carbon and energy source. Two to four phenol-degrading, phylogenetically and physiologically different bacterial strains were used in each SME. Phylogeny was based on the nucleotide sequence of 16S rRNA genes, while physiologic traits were based on kinetic and growth parameters on phenol. Two indices, J parameter and “interspecies interaction,” were compared to predict which strain would become dominant in an SME. The J parameter was calculated from kinetic and growth parameters. On the other hand, “interspecies interaction,” a new index proposed in this study, was evaluated by measuring the specific growth activity, which was determined on the basis of relative growth of a strain with or without the supernatant prepared from other bacterial cultures. Population densities of strains used in SMEs were enumerated by real-time quantitative PCR (qPCR) targeting the gene encoding the large subunit of phenol hydroxylase and were compared to predictions made from J parameter and interspecies interaction calculations. In 4 of 6 SEMs tested the final dominant strain shown by real-time qPCR analyses coincided with the strain predicted by both the J parameter and the interspecies interaction. However, in SMEII-2 and SMEII-3 the final dominant Variovorax strains coincided with prediction of the interspecies interaction but not the J parameter. These results demonstrate that the effects of interspecies interactions within microbial communities contribute to determining the dynamics of the microbial ecosystem.
In-Network Caching vs. Redundancy Elimination

Network-level Redundancy Elimination (RE) techniques have been proposed to reduce the amount of traffic in the Internet. and the costs of the WAN access in the Internet. RE middleboxes are usually placed in the network access gateways and strip off the repeated data from the packets. More recently, generic network-level caching architectures have been proposed as alternative to reduce the redundant data traffic in the network, presenting benefits and drawbacks compared to RE. In this paper, we compare a generic in-network caching architecture against state-of-the-art redundancy elimination (RE) solutions on real network topologies, presenting the advantages of each technique. Our results show that in-network caching architectures outperform state-of-the-art RE solutions across a wide range of traffic characteristics and parameters.
Comparative study of vibration and acoustic noise between classical and mutually coupled switched reluctance motors

This paper presents a comparative study of magnetic force, vibration and acoustic noise of classical and mutually coupled switched reluctance motors (SRM) with 6-slot and 4-pole. Construction of 2D multi-physic models allows us to predict these two kinds of motor vibration and noise behavior which are mainly caused by radial magnetic force. With the same structure and same average output torque, the maximum radial force of mutually coupled SRM is found to be two times lower than that of classical SRM. The comparative results of vibration and acoustic noise are presented and analyzed both in time domain and frequency domain. It is found that the vibration and the noise are considerably reduced for mutually coupled SRM compared to the classical SRM.
Morphological analysis of male mating organ in the Drosophila virilis species group : a multivariate approach

The shape of the male mating organ differs among 11 closely related species of the Drosophila virilis species group. Multivariate analyses of variation of a suite of 35 morphological traits (indices) describing the phallus shape were carried out in order to characterize interspecies variability of the traits. An overwhelming majority of the traits displayed species-specific variability. The main result of the investigation was the revelation of the differences involved in the traits studied in the evolution of the D. virilis species group. The structure of species-specific variability of some traits was discovered to be in accordance with the generally accepted taxonomy of the species group, while that of other traits required isolation of D. virilis per se from lummei phylad (former virilis phylad), and confirmed separation of montana phylad into three subphylads: montana proper, littoralis and kanekoi. Several subsets of traits having separate variability were determined in different parts of the male mating organ which correspond to spots of evolutionarily significant variability.