Miracle-dz/UniFAR-FTUs huggingface dataset:
Epidemiology of Helicobacter Associated Diseases of Gastrointestinal Tract in Uzbekistan . The Local Treatment Protocols

DOI: 10.21276/sjpm.2018. 3.4. 6 Abstract: This paper devoted to the results of Helicobacter pylori infection spreading in Uzbekistan, its molecular-genetic characteristics, antibiotic resistance. It is shown that Uzbekistan belongs to the regions with a high degree of infection of the population of the HP. Pathogenic Cag positive bacterial strains were associated with chronic Helicobacter pylori associated gastritis. The resistance of HP to clarithromycin in the region was 13.3%. The effectiveness of the 7-day eradication triple therapy was 65%. Prolongation of the period of eradication therapy to 14 days and the inclusion of a complex of therapies of bismuth preparations allowed increasing the effectiveness of therapy to 95%.
THE INTERNATIONAL COMPARATIVE SOCIAL ENTERPRISE MODELS – ICSEM PROJECT-SOLIDARITY ECONOMY ENTERPRISES IN BRAZIL: An overview from the second national mapping

This paper constitutes an input from the Solidarity Economy and Co-operative Economics Research Group at Unisinos (Universidade do Vale do Rio dos Sinos, an university in southern Brazil) to the theoretical debate promoted in the scope of the ICSEM Project, a broad research project whose main purpose is to compare social enterprise models and their respective institutionalisation processes across the world. The ICSEM Project relies on the participation of a large number of researchers from all regions, who contribute by providing country-specific or field-specific analysis of social enterprise models. The field of analysis is delineated as made of organisations that combine an entrepreneurial dynamics to provide services or goods with the primacy of their social aims. This definition stresses specific governance models, often found in social enterprises, rather than the profile of social entrepreneurs. A democratic control or a participatory involvement of stakeholders and citizens reflects a quest for more economic democracy inside the organisation, in the line of the tradition of cooperatives and, more recently, of the Social and Solidarity Economy.
STUDIES ON THE CHANGES OF PROTEIN SECONDARY STRUCTURE AND CARBOHYDRATE CONTENTS IN SEEDLING-STAGE OF ABRUS CANTONIENSIS HANCE IN DROUGHT STRESS BASED ON FTIR AND CHEMOMETRICS

To study the response mechanism of seedling-stage Abrus cantoniensis to drought stress from the level of infiltration conditions, this research uses Fourier infrared spectroscopy based on such mathematical approaches as Fourier selfdeconvolution and Gaussian curve-fitting to analyze the broad characteristic absorption bands of the protein secondary structure and carbohydrates in the root, stem and leaf of seedling-stage under four drought stress treatments. The results show that the relative absorption of every type of secondary structure (namely, α-helix, β-sheet and β-turn), the α-helix/βsheet ratio and the relative contents of starch, soluble sugars and cellulose show significant differences in the different parts of seedling-stage A. cantoniensis under different drought treatments. These differences provide a theoretical basis for investigating the response mechanisms of seedling-stage A. cantoniensis to drought stress and for advancing rational cultivation measures for this species. A new method that is fast, efficient and sensitive is presented for the study of the response mechanism of seedling-stage A. cantoniensis to drought stress.
Probabilistic and Nondeterministic Systems

SONI, ARVIND. Probabilistic and Nondeterministic Systems . (Under the direction of Professor Dr. S. Purushothaman Iyer). Probabilistic and nondeterministic systems are important to model systems such as distributed network protocols, concurrent systems and randomized algorithms, where nondeterminism is inherently present along with probabilistic choices. Probabilistic transition systems without any nondeterminism have been explored over the past decade. Several logics have been proposed to express the probabilistic behavior of systems. Nondeterministic systems differ from their probabilistic counterparts in that there behavior needs a notion of scheduler which resolves the nondeterministic choices. The probability space of observations of such systems is dependent on the choice of scheduler. In the absence of unique probability space the system properties can only be measured in intervals. The methods proposed in literature for quantitative analysis of nondeterministic systems use approximations for conjunction and disjunction to avoid the nonlinearity in the equations for measures. The contribution of this thesis is three fold. In the initial part we present a model checking method for quantitative analysis of nondeterministic systems. We generate a set of constraints and compute the minimum and maximum measure for the property without using any approximations. Secondly, we present an abstraction and probabilistic bisimulation based approach to model and analyze randomized token stabilization protocol. In the end we present a method for compositional verification of PNS where in we describe weak predicate transformers which can be used to generate sub-specification for the unknown systems from the specification of the composite system. Probabilistic and Nondeterministic Systems by Arvind Soni A thesis submitted to the Graduate Faculty of North Carolina State University in partial satisfaction of the requirements for the Degree of Master of Science Department of Computer Science Raleigh 2004
PyPLT: Python Preference Learning Toolbox

There is growing evidence suggesting that subjective values such as emotions are intrinsically relative and that an ordinal approach is beneficial to their annotation and analysis. Ordinal data processing yields more reliable, valid and general predictive models, and preference learning algorithms have shown a strong advantage in deriving computational models from such data. To enable the extensive use of ordinal data processing and preference learning, this paper introduces the Python Preference Learning Toolbox. The toolbox is open source, features popular preference learning algorithms and methods, and is designed to be accessible to a wide audience of researchers and practitioners. The toolbox is evaluated with regards to both the accuracy of its predictive models across two affective datasets and its usability via a user study. Our key findings suggest that the implemented algorithms yield accurate models of affect while its graphical user interface is suitable for both novice and experienced users.
Context Resolution Strategies for Automatic Wikipedia Linking

Automatically linking Wikipedia pages is done mostly by two strategies: (i) a content based strategy based on word similarities or (ii) a structural similarity exploiting link characteristics. In our approach we focus on a content based strategy by finding anchors using the title of candidate Wikipedia pages and resolving matching links by taking the context of the link anchor, i.e. its surrounding text, into account. Bestentry-points are estimated on a combination of title and content based similarity. Our goal was to evaluate syntactic title matching properties and the influence of the context around anchors for disambiguation and best-entry-point detection. Results show, that the whole Wikipedia page provides the best context for resolving links and that simple inverse document frequency based scoring of anchor texts is also capable of achieving high accuracy.
Preparation of various morphologies of ZnO nanostructure through wet chemical methods

Hydrothermal route and solution reaction method are adopted for the synthesis of zinc oxide (ZnO) nanopowders having four different morphologies such as nanoparticle, mirorod, nanoplate and nanotubule. Zinc nitrate hexahydrate Zn(NO3)2.6H2O was used as precursor for ZnO nanostructures. ZnO nanorods and nanoplates were synthesized by a hydrothermal approach using KOH as reaction chemical. ZnO nanotubes were obtained by a chemical reaction of Zn(NO3)2 and NH4OH. And ZnO nanoparticles were prepared by precipitation method from zinc nitrate and ammonium carbonate (NH4)2CO3 in aqueous solution. The structures, morphology, and element components of these ZnO products fabricated by the above-mentioned methods were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and transmission electron microscopy (TEM). These experimental results demonstrated that the as-prepared ZnO nanoparticles have average diameter of 30-60 nm; rod-like ZnO has average diameter of about 350 nm and the length of 3.5 μm; plate-like ZnO has average thickness of about 40 nm and lateral size of 200 × 400 nm; ZnO nanotubules have outer diameter of about 400 nm and inner diameter of about 300 nm, the length of about 4 μm. The XRD results indicated that four morphologies of ZnO are all wurtzite structure. It is found that the wet chemical technique is very promising for fabricating ZnO nanocrystallines with various morphologies. *Correspondence to: Nguyen Dac Dien, Vietnam Trade Union University, 169 Tay Son, Quang Trung, Dong Da, Hanoi, Vietnam, Tel: 0975528087; E-mail: diennd@dhcd.edu. vn
Nanostructured composite materials based on carbon nanotubes and 3-D photonic crystals

NANOSTRUCTURED COMPOSITE MATERIALS BASED ON CARBON NANOTUBES AND 3-D PHOTONIC CRYSTALS by Jing Chen Carbon nanotubes (CNT) and in particular, single-wall carbon nanotubes (SWCNT) have been extensively studied, in large part, due to their unique one-dimensional crystalline structures and related electronic and optical properties. Various polymeric composite materials, which were based on carbon nanotubes, have been also developed in an attempt to combine the properties of polymer and CNT in a single film. Such composites were mainly formed by mixing carbon nanotubes within the polymer without special emphasis on the structure and thereby, the nanoscopic properties of the resultant material. Photonic crystals belong to a class of man-made structures aimed at manipulating the propagation of electromagnetic waves at sub-wavelength dimensions in the visible range. The objective of this research work was to fabricate optical nano-composites from the bottom up: by incorporating carbon nanotubes within nano-structured templates we attempted to achieve novel composites with unique optical properties. Three-dimensional photonic crystals were made by self-assembly using monodisperse suspension of silicon dioxide colloids. Upon sedimentation, this highly ordered crystal, also known as opal, serves as a template for polymeric and polymer/CNT composites. For example, by infiltrating of the templates voids with a desired polymeric solution followed by etching of the silica template away, a three-dimensional inverse polymeric structure is obtained. Single-wall carbon nanotubes (SWCNT) have been directly grown into the template voids (in the range of 20 — 70 nm) by catalytic Chemical Vapor Deposition (CVD) technique with carbon monoxide as the carbon feedstock. The resultant SWCNTs were mostly semiconductive (p-doped). Control over the growth of SWCNT has been obtained by changing the catalyst concentration and the template's void-size. Various techniques were used to characterize the SWCNT and its composites: Scanning Electron Microscope (SEM) has been used to identify the morphology of structures; interactions between polymer and nanotubes have been characterized by Raman spectroscopy; optical properties were studied by linear and nonlinear optical transmission and optical activity measurements; electrical properties were studied using thermoelectric and photoconductivity measurements. These data suggest that selforganized nano-scale templates are a promising route for realizing novel optical composite materials. NANOSTRUCTURED COMPOSITE MATERIALS BASED ON CARBON NANOTUBES AND 3-D PHOTONIC CRYSTALS
Ecology of bivalves in the intertidal area of Gili Ketapang Island , East Java , Indonesia

Bivalves provide a range of ecosystem services such as turbidity reduction, denitrification induction, and habitat complexity provision. This study aimed to assess the diversity and the community structure of bivalves in the intertidal areas of Gili Ketapang Island, East Java, Indonesia, as well as analyze the environmental parameters that might influence their biological community. Three (15-m long) transects with five 1x1-m quadrant plots in each transect line of each research station were established seawards perpendicular to the coast line. The bivalves were composed of 5 families, 8 genera and 10 species of which Gafrarium tumidum had the highest density and distribution. On average, the Shannon’s diversity index (H’) and the Simpson dominance index (D) were moderate with the values of 1.12 and 3.13 respectively. The Evenness Index (J’) was high with value of 0.90, which indicated that the bivalve communities possessed ecological stability. Moreover, physico-chemical parameters of water and sediment were still in the range of the tolerant level to sustain bivalves life.
Design of a non-contact head-control mouse emulator for use by a quadriplegic operator

A non-invasive scanning mechanism has been designed which is microprocessor controlled to locate and follow head movement in a defined zone about a persons head. The resulting head movements may then be mapped onto a computer screen and can further be used to control the cursor, thus replacing the necessity of using a standard PC mouse. To demonstrate the concept, a Graphic User Interface (GUI) of a push button telephone has been designed, and a procedure is outlined below by which one may select and highlight a digit or group of digits, and in turn dial the chosen number.
An Encryption Scheme to Secure Data using Block Division and Predicate Encryption Algorithm

— Information plays a important role in today’s world where business, organizations, military operations, at every aspect there is lots of information . Information in the wrong hands can lead to loss of business or catastrophic results. To secure such communication, a business or any organization can use cryptology to cipher information . Cryptology involves transforming information into non human readable format and we in this paper are proposing a new encryption scheme which generates a block cipher. The scheme applies a block division on data blocks which separately stores the data into groups and remainder data. Later on the remainder data we apply predicate encryption scheme on the data to be stored( remainder data) in which the keys correspond to predicates and cipher texts are associated with attributes. The public key PK with an attribute ‘x’ is used to encrypt the text and the secret key SKf corresponding to predicate f can be used to decrypt a cipher text with attribute ‘x’ if and only if f(x)=1.
Optimal and General Out-of-Order Sliding-Window Aggregation

Sliding-window aggregation derives a user-defined summary of the most-recent portion of a data stream. For in-order streams, each window change can be handled in O (1) time even when the aggregation operator is not invertible. But streaming data often arrive inherently out-of-order, e.g., due to clock drifts and communication delays. For such streams, prior work resorted to latency-prone buffering or spent O (log n ) time for every window change, where n is the instantaneous window size. This paper presents FiBA, a novel real-time sliding window aggregation algorithm that optimally handles streams of varying degrees of out-of-orderness. FiBA is as general as the state-of-the-art and supports variable-sized windows. An insert or evict takes amortized O (log d ) time, where d is the distance of the change to the window's boundary. This means O (1) time for in-order arrivals and nearly O (1) time for slightly out-of-order arrivals, tending to O (log n ) time for the most severely out-of-order arrivals. We also prove a matching lower bound, showing optimality. At its heart, the algorithm combines and extends finger searching, lazy rebalancing, and position-aware partial aggregates. Further, FiBA can answer range queries that aggregate subwindows for window sharing. Finally, our experiments show that FiBA performs well in practice and conforms to the theoretical findings, with significantly higher throughput than O (log n ) algorithms.
A Naïve Bayes Model using Semi-Supervised Parameters for Enhancing the Performance of Text Analytics

------------------------------------------------------------------- ABSTRACT --------------------------------------------------------------- Sentiment mining is an emerging area that utilizes the feedback of the users to make intelligent decisions in marketing. Consumer reviews helps the user to convert oral conversations to digital versions to be used in marketing analytics. Since e-commerce takes intrinsic forms in present day business, the need to get positive reviews for specific products is vital on an organization perspective. Both sentiment mining and TF-IDF (Term Frequency-Inverse Document Frequency) are text mining tasks but have their unique applications and characteristics. Sentiment mining classifies the documents into positive, negative or neutral opinions that are used to derive intelligent decisions. TF-IDF classifies the documents into sub-categories within the documents itself. Utilizing the TF-IDF as a feature for sentiment mining improves the performance of classification. In this research work a strategy is applied for feature preprocessing to evaluate the consumer ’ s sentiments accurately. This strategy makes use of the semi-supervised parameter estimation Naïve Bayes Model. The experimental results demonstrate that TF-IDF tuning approach results in better optimized results.
Preparation and Adsorption Properties of Biochar/g-C3N4 Composites for Methylene Blue in Aqueous Solution

Using straw and urea as raw materials, biochar (BC) and g-C3N4 were prepared by oxygen-free pyrolysis at 300°C and 550°C. BC/g-C3N4 was prepared by loading different amounts of g-C3N4 onto the surface of biochar and characterized by SEM and FT-IR. The adsorption effect on methylene blue (MB) was investigated from the aspects of dosage and pH. The studies of adsorption equilibrium isotherms and the kinetic and the thermodynamic parameters on the BC/g-C3N4 adsorbents are discussed. The results showed that BC/g-C3N4 0.16 g/L with a doping ratio of 1 : 3 was added to the MB solution with an initial concentration of 50 mg/L and pH=11. The adsorption rate and adsorption amount were 96.72% and 302.25 mg/g, respectively. The adsorption process included surface adsorption and intraparticle diffusion, which conformed to the pseudo-second-order kinetic model and Langmuir-Freundlich model. Thermodynamic parameters (ΔG0<0, ΔH0>0, and ΔS0>0) showed that the adsorption reaction is spontaneous, which positively correlated with temperature.
Analysis of the interactions between GMF and Arp 2 / 3 complex in two binding sites by molecular dynamics simulation

The Arp2/3 complex plays a key role in nucleating actin filaments branching. The glia maturation factor (GMF) competes with activators for interacting with the Arp2/3 complex and initiates the debranching of actin filaments. In this study, we performed a comparative analysis of interactions between GMF and the Arp2/3 complex and identified new amino acid residues involved in GMF binding to the Arp2/3 complex at two separate sites, revealed by X-ray and single particle EM techniques. Using molecular dynamics simulations we demonstrated the quantitative and qualitative changes in hydrogen bonds upon binding with GMF. We identified the specific amino acid residues in GMF and Arp2/3 complex that stabilize the interactions and estimated the mean force profile for the GMF using umbrella sampling. Phylogenetic and structural analyses of the recently defined GMF binding site on the Arp3 subunit indicate a new mechanism for Arp2/3 complex inactivation that involves interactions between the Arp2/3 complex and GMF at two binding sites. © 2018 Elsevier Inc. All rights reserved.
Mixed Neural and Feedback Controller for Apache Web Server

Overload control mechanism is used to protect a web server from excessive load during traffic peaks and involves techniques of predictive control with limited local information. Four main types of overload control can be identified: Load balancing, content adaptation, Scheduling and Admission control. This paper presents a Neural Model based Feedback control approach to keep the mean response time of a web server close to the service level specification. Implementing in a real server, we show that both neural network and feedback control leads better tracking of QoS specification than with feedback control only or neural model based feed forward control only.
Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants

A novel combination of the ant colony optimization algorithm (ACO)and computational fluid dynamics (CFD) data is proposed for modeling the multiphase chemical reactors. The proposed intelligent model presents a probabilistic computational strategy for predicting various levels of three-dimensional bubble column reactor (BCR) flow. The results prove an enhanced communication between ant colony prediction and CFD data in different sections of the BCR.
The Impact of Vilnius City on the Transformation Trends of the Sparsely Populated EU East Border Region

S U M M A R Y: This paper analyses the general trends of the socio-economic development of the multicultural Vilnius city region. It is located in South-East Lithuania, which stands out as the poorest area of Lithuania in terms of its socio-economic situation. Moreover, in a broader context, Vilnius city region is also located in the middle of the international Central European region, which is often perceived as one of the most “depressed” areas of the contemporary EU. Together with the systemic reforms of the early 1990s the profound economic and social changes have started, in which the Vilnius city region has been experiencing one of the most significant transformations throughout Lithuania. It is obvious that at present the main factor of the intense development of South-East Lithuania is the presence of Vilnius city. It has been growing very fast during the recent decades, thus a significant impact on the population structure and the economy of the surrounding areas has been made. The main questions of this paper are: what is the effect of Vilnius’ development on the surrounding region and how profound this impact is. The process of transformations of the rural area into the urban one, changes of the population structure, ethnic landscape and economic processes are of greatest concern in the given paper. The Vilnius city region is the area of very dynamic changes, where socio-economic tension of various kinds is almost inevitable, while the means of planning and sustainable development are quite limited.
Sampling-based Path Planning to Cartesian Goal Positions for a Mobile Manipulator Exploiting Kinematic Redundancy

A robot path planner is presented which integrates both collision-free path planning and finding an inverse kinematics solution in a single search stage. Thereby the degrees of freedom resulting from redundant robot kinematics with regard to goal positions specified in the Cartesian workspace are used to optimize the path length, whereas the usual two-stage approach of decoupled inverse kinematics computation and path planning in the configuration space fails to exploit this potential. In addition to sampling-based exploration of the configuration space, the proposed algorithm uses a computationally efficient gradient descent method for approaching the Cartesian goal pose. Furthermore, the planner is extended by the possibility to respect end-effector path orientation constraints. A detailed evaluation of the planning performance in comparison with a two-stage planner is presented.