Miracle-dz/UniFAR-FTUs huggingface dataset:
The Skeletal Muscle as an Active Player Against Cancer Cachexia

The management of cancer patients is frequently complicated by the occurrence of cachexia. This is a complex syndrome that markedly impacts on quality of life as well as on tolerance and response to anticancer treatments. Loss of body weight, wasting of both adipose tissue and skeletal muscle and reduced survival rates are among the main features of cachexia. Skeletal muscle wasting has been shown to depend, mainly at least, on the induction of protein degradation rates above physiological levels. Such hypercatabolic pattern is driven by overactivation of different intracellular proteolytic systems, among which those dependent on ubiquitin-proteasome and autophagy. Selective rather than bulk degradation of altered proteins and organelles was also proposed to occur. Within the picture described above, the muscle is frequently considered a sort of by-stander tissue where external stimuli, directly or indirectly, can poise protein metabolism toward a catabolic setting. By contrast, several observations suggest that the muscle reacts to the wasting drive imposed by cancer growth by activating different compensatory strategies that include anabolic capacity, the activation of autophagy and myogenesis. Even if muscle response is eventually ill-fated, its occurrence supports the idea that in the presence of appropriate treatments the development of cancer-induced wasting might not be an ineluctable event in tumor hosts.
Busing: A Review of "the Evidence.".

David Armor's "The Evidence on Busing" presented a distorted and incomplete review of this politically charged topic. We respect Armor's right to publish his views against "mandatory busing. " But we challenge his claim that these views are supported by scientific evidence. A full discussion of our reading of the relevant research would be too lengthy and technical for the non-specialist. We must limit ourselves to outlining% and discussing briefly our principal disagreements with Armor, which center on four major points. First, his article begins by establishing unrealistically high standards by which to judge the success of school desegregation. Second, the article presents selected findings from selected studies as "the evidence on busing. " The bias is twofold. The few studies mentioned constitute an incomplete list and are selectively negative in results. Only cursory descriptions are provided of the few investigations that are reviewed. Third, the paper's anti-busing conclusions rest.primarily on the findings from one short-term study conducted by Armor himself: an evaluation of-a voluntary busing program in metropolitan Boston. This study is probably the weakest reported in the paper. Fourth, objections must be raised to the basic assumptions about racial change that undergird the entire article. The whole national context of individual and institutional racism is conveniently ignored. [For David Armor's reply, see UD 013 499. ] (Author/JM) PERMISSION TO REPRODUCE 1 H15 Col= RIGHTED MATERIAL HAS BEEN GRANTED
UvA-DARE ( Digital Academic Repository ) A Comparison Between Alignment and Integral Based Kernels for Vessel Trajectories

In this paper we present a comparison between two important types of similarity measures for moving object trajectories for machine learning from vessel movement data. These similarities are compared in the tasks of clustering, classification and outlier detection. The first similarity type are alignment measures, such as dynamic time warping and edit distance. The second type are based on the integral over time between two trajectories. Following earlier work we define these measures in the context of kernel methods, which provide state-of-the-art, robust algorithms for the tasks studied. Furthermore, we include the influence of applying piecewise linear segmentation as preprocessing to the vessel trajectories when computing alignment measures, since this has been shown to give a positive effect in computation time and performance. In our experiments the alignment based measures show the best performance. Regular versions of edit distance give the best performance in clustering and classification, whereas the softmax variant of dynamic time warping works best in outlier detection. Moreover, piecewise linear segmentation has a positive effect on alignments, which seems to be due to the fact salient points in a trajectory, especially important in clustering and outlier detection, are highlighted by the segmentation and have a large influence in the alignments. SNE technical report SNE-UVA-2014-01 http://www.science. uva.nl/research/sne/reports/
University of Groningen Mauritius since the last glacial

A 10m long peat core from the Kanaka Crater (208 250 S, 578 310 E), located at 560m elevation in Mauritius, was analyzed for microfossils. Eight radiocarbon ages show the pollen record reflects environmental and climatic change of the last ca. 38 cal ka BP. The record shows that the island was continuously covered by forest with Erica heath (Philippia) in the uplands. Cyperaceous reedswamp with Pandanus trees was abundant in the coastal lowlands as well as locally in the waterlogged crater. The record shows changes in climatic humidity (wet from 38.0 to 22.7 cal ka BP, drier from 22.7 to 10.6 cal ka BP, andwetter again from 10.6 cal ka BP to recent) as themain response to climate change. A high turnover in montane forest species is evidenced at 22.7 cal ka BP and at the start of the Holocene. The limited altitudinal ranges in the mountains of Mauritius (maximum altitude 828m), and changing humidity being more important than changing temperature, suggests that in response to climate change a reassortment in taxonomic composition of montane forests might be equally important as displacement of forest types to new altitudinal intervals. We found weak impact of the latitudinal migration of the Intertropical Convergence Zone and data suggest that the Indian Ocean Dipole is a more important driver for climatic change in the southwest Indian Ocean. Copyright # 2011 John Wiley & Sons, Ltd.
Profitability analysis of urban mass transport lines using activity-based costing method: An evidence from the Czech Republic

*Tomas Bata University in Zlin, Nam. T.G. Masaryka 5555, 76001 Zlin, Czech Republic; teodora@seattleu.edu The objective of this study is to present how could be Activity-Based Costing method used for the purpose of the profitability analysis of individual bus and trolleybus lines in an urban mass transport company which operates the land public transport inside the medium sized town in Czech Republic. Activity-Based Costing method had been used, in order to causal allocation of overhead costs to individual operations in order to measure the profitability of particular transport lines. The performed study showed the application process of the Activity-Based Costing and possible information outputs for an urban mass transport company as well as the limitations of the method use in the field of transportation services. The study also analyses the obstacles in effective data collection and processing which implementation team faced during the analysis. The primary limitation of the analysis, is similarly as in other studies, is the quality of the non-financial information which had to be obtained. Study discusses problems related with the fare system, which does not provide the information regarding the route taken by individual passenger. The study presents the how could be ABC method used for the decision making support in urban mass transport company and shows a real example of the ABC system information outputs.
The Impact of the Implementation of Business Intelligent to Support Decision-Making in the American Banking Industry: a Literature Review

In facing globalization era, companies need to have innovation to survive in business competition. A change is needed to make a successful inovation, when a company needs a leader who has a strong managerial ability. The application of technology, in this case is business intelligence (BI), is an innovation that can becarried out by the management leader to survive in the complex world competition by finding appropriate decisions to solve business problems. This article was a literature review that concerned to exploration of the role of leadership and managerial ability in the application of BI on First American Company (FAC). The authors retrieved articles from google scholar with keywords, such as: leadership, managerial ability, and business. The implementation of BI on FAC proves to be a successful innovation formulated by the managementwho manage to change the company's financial situation that loss into a profit and managed to become the market leaders. In addition, this article also presented some cases of successful BI implementation which helped resolving credit problems and segmentation
The Red-Black Physics Engine: A Parallel Framework for Interactive Soft Body Dynamics

The simulation of soft bodies has been an ongoing research problem for over 30 years. The desiderata for real-time applications are believable results, while maintaining interactivity. The most popular approach to achieve this has been to use iterative methods, that find an approximate solution to the underlying equation system rapidly. In recent years, efforts have been made to improve the performance of these methods by exploiting the computational capabilities of modern hardware architectures, such as the graphics processing unit. This thesis introduces a parallel iterative solver that utilizes a Red-Black Gauss- Seidel technique. The solver is implemented within the Projective Dynamics framework, using a quadrangular network of particles and constraints, to simulate soft bodies in real-time. The results show that in this particular case, the Red-Black Gauss-Seidel method outperforms other traditional iterative solvers in terms of convergence speed. The results were achieved by creating a physics engine prototype, using a Verlet numerical integration scheme, parallel collision handling and three different types of iterative solvers; sequential Gauss-Seidel, parallel Jacobi and parallel Red-Black Gauss-Seidel. These solvers were then compared to each other. The physics engine as a whole was also compared to other contributions in the field. The quadrangular structure of the soft bodies resulted in real-time performance, at the cost of a moderate loss in precision.
Secure and Efficient Data Transmission for Cluster Based Wireless Sensor Network Using Cryptography

Wireless Sensor Networks (WSN) plays vital role in research field. Due to its rapidly increasing application in monitoring various kinds of environment by sensing physical phenomenon. Clustering is an efficient and effective method to enhance performance of the WSNs system. In this project work, we study a secure transmission of data for cluster-based WSNs (CWSNs), where the clusters are formed dynamically and randomly. We propose two Secure and Efficient data Transmission (SET) protocols for CWSNs, called SET-IBS and SET-IBOOS, by using the Identity-Based digital Signature (IBS) scheme and the Identity-Based Online/Offline digital Signature (IBOOS) scheme, respectively. The cluster routing protocol LEACH (Low-Energy Adaptive Clustering Hierarchy) is considered and improved. In SET-IBS, security relies on the hardness of the Diffie-Hellman problem in the pairing area. SET-IBOOS additionally decreases the computational operating cost for protocol security, which is critical for WSNs, while its defense depends on the stability of the problem of discrete logarithm. We propose a clustering routing protocol named Enhanced LEACH, which extends LEACH protocol by balancing the energy consumption in the network. The simulation results show that Enhanced LEACH outperforms LEACH in terms of network system lifetime and reduce the energy consumption.
An Efficient Approach for Resource Allocations using Hybrid Scheduling and Optimization in Distributed System

Grid computing consists of achieving an effectual clustering of the valuable resources having dissimilar locations which will deal with real time scenarios. The grid follows the dispersed procedures having heavy workloads which can be in the form of the traffic files from different locations. Grid computing is related to the extraordinary performance systems like computer clustering or we can say nodes in the grid in such a manner that each set of the node performs different tasks and applications. Grid computers also deals with networks with topology variations and diverse geography which is not essentially to connect substantially to the cluster of computers. As the number of traffic increases day by day, is the challenging task to complete all the allocated processes in the limited time intervals. So this research deals with the efficient scheduling and optimization approach for the resource management using Ant colony optimization and round robin scheduling to obtain low execution intervals with less error rate probabilities. The whole simulation is done in MATLAB environment.
The Role of Iron in Friedreich’s Ataxia: Insights From Studies in Human Tissues and Cellular and Animal Models

Friedreich’s ataxia (FRDA) is a rare early-onset degenerative disease that affects both the central and peripheral nervous systems, and other extraneural tissues, mainly the heart and endocrine pancreas. This disorder progresses as a mixed sensory and cerebellar ataxia, primarily disturbing the proprioceptive pathways in the spinal cord, peripheral nerves and nuclei of the cerebellum. FRDA is an inherited disease with an autosomal recessive pattern caused by an insufficient amount of the nuclear-encoded mitochondrial protein frataxin, which is an essential and highly evolutionary conserved protein whose deficit results in iron metabolism dysregulation and mitochondrial dysfunction. The first experimental evidence connecting frataxin with iron homeostasis came from Saccharomyces cerevisiae; iron accumulates in the mitochondria of yeast with deletion of the frataxin ortholog gene. This finding was soon linked to previous observations of iron deposits in the hearts of FRDA patients and was later reported in animal models of the disease. Despite advances made in the understanding of FRDA pathophysiology, the role of iron in this disease has not yet been completely clarified. Some of the questions still unresolved include the molecular mechanisms responsible for the iron accumulation and iron-mediated toxicity. Here, we review the contribution of the cellular and animal models of FRDA and relevance of the studies using FRDA patient samples to gain knowledge about these issues. Mechanisms of mitochondrial iron overload are discussed considering the potential roles of frataxin in the major mitochondrial metabolic pathways that use iron. We also analyzed the effect of iron toxicity on neuronal degeneration in FRDA by reactive oxygen species (ROS)-dependent and ROS-independent mechanisms. Finally, therapeutic strategies based on the control of iron toxicity are considered.
Diversity of Yam ( Dioscorea spp .) Populations in South Western Region of Cameroon

Yams are Dioscoreaceae grown in the tropics and sub-tropics and used as food and for related pharmaceutical properties. The South Western Region of Cameroon is a major yam producing zone. This study which evaluates morphological variability between ten linguistically different yam types grown in South Western Cameroon will serve as a necessary step for subsequent genetic study of the species. The yams, collected from nine sites, were planted in a completely randomized design in four locations. Analysis of data on nine morphological vines traits reveals that, the yam types constituted five main clusters. Cluster 1 with 61.3% similarity consists of five accessions of D. rotundata - Ikom, Calabar, White, Agar and Igbo yams. This cluster has three sub-groups with 84.9% similarity. Cluster 2 consists of Yellow yam (D. cayenensis) with 48.5% similarity to members of Cluster 1. Ghana Water yam and Swệt yam constitute Cluster 3 with 83.4% similarity while Sugar yam and Water yam constitute the 4th and 5th clusters respectively. The ten yam types are actually five cultigens –rotundata, rotundata-cayenensis complex, cayenensis, dumetorum and alata; and the significant variability (P<0.05) observed with respect to the morphological characters evaluated may be the basis for the linguistic polymorphism noticed in the naming of the different yam types. Although genetic analysis is recommended to determine firm similarities, the establishment of clear links remains problematic because of the high hybridisation noticed among members of the Dioscoreaceae; and considering that yams types were introduced in the zone from different lands over many centuries.
BUSINESS STRATEGIES IN CREDIT RATING AND THE CONTROL OF MISCLASSIFICATION COSTS IN NEURAL NETWORK PREDICTIONS

This paper reports on an investigation into the control of misclassification costs in Artificial Neural Network (ANN) prediction. Given the availability of a small historical data set and without imposing any strong assumptions on the behavior of the underlying variables, this study investigates the enhancement of ANN prediction with a training set containing the replication of interested cases. With this replicated training set, the ANN will learn more about patterns of a particular category and then improve the accuracy in predicting the membership of this category. In a context of small business loan application, depending on the cost to the financial institution in the case of misclassification, one may consider replicating the accepted or rejected cases in the training set in an appropriate proportion. Consequently, one can achieve a more accurate ANN prediction on the interested category.
Numerical Modeling of Deposition of Inhaled Particles in Central Human Airways

The objective of our research is to model physical and biological processes related to the development of adverse health effects, especially initiation of lung cancer in the central human airways following inhalation of aerosol particles. There is experimental evidence that bronchogenic carcinomas originate mainly at the dividing zone of large central airway bifurcations where primary hotspots of deposition have been found. However, current lung deposition models do not take into consideration the inhomogeneity of deposition within bronchial airways. The flow field within three-dimensional morphologically realistic geometries of airway generations 3–6 of the human tracheobronchial tree is computed by the FLUENT CFD (computational fluid dynamics) code for a wide range of flow rates during both inhalation and exhalation. A large number of particle trajectories has been simulated to determine the resulting deposition patterns, which were finally quantified by local deposition enhancement factors. Both the local airflow fields and deposition patterns strongly depend on the shape of the geometry, especially on the form of the carinal ridge. The computed enhancement factors indicate that local deposition densities may be two orders of magnitude higher than the average values for scanning on the surface by a 100 × 100 μm surface element, i.e. at approximately cellular dimensions.
Understanding Game Balance with Quantitative Methods

Game balancing is the fine-tuning phase in which a functioning game is adjusted to be deep, fair, and interesting. Balancing is difficult and time-consuming, as designers must repeatedly tweak parameters and run lengthy playtests to evaluate the effects of these changes. Only recently has computer science played a role in balancing, through quantitative balance analysis. Such methods take two forms: analytics for repositories of real gameplay, and the study of simulated players. In this work I rectify a deficiency of prior work: largely ignoring the players themselves. I argue that variety among players is the main source of depth in many games, and that analysis should be contextualized by the behavioral properties of players. Concretely, I present a formalization of diverse forms of game balance. This formulation, called 'restricted play', reveals the connection between balancing concerns, by effectively reducing them to the fairness of games with restricted players. Using restricted play as a foundation, I contribute four novel methods of quantitative balance analysis. I first show how game balance be estimated without players, using simulated agents under algorithmic restrictions. I then present a set of guidelines for using domain-specific models to guide data exploration, with a case study of my design work on a major competitive video game. I extend my work on this game with novel data visualization techniques, which overcome limitations of existing work by decomposing data in terms of player skill. I finally present an advanced formulation of fairness in games—the first to take into account a game's metagame, or player community. These contributions are supported by a detailed exploration of common understandings of game balance, a survey of prior work in quantitative balance analysis, a discussion of the social benefit of this work, and a vision of future games that quantitative balance analysis might one day make possible.
Legal Documents Clustering and Summarization using Hierarchical Latent Dirichlet Allocation

Received Jul 30, 2012 Revised Oct 27, 2012 Accepted Jan 07, 2013 In a common law system and in a country like India, decisions made by judges are significant sources of application and understanding of law. Online access to the Indian Legal Judgments in the digital form creates an opportunities and challenges to the both legal community and information technology researchers. This necessitates organizing, analyzing and presenting it in a useful manner to the legal community for quick understanding and for taking necessary decision pertaining to a present case. In this paper we propose an approach, to cluster legal judgments based on the topics obtained from hierarchical Latent Dirichlet Allocation (hLDA), using similarity measure between topics and documents and to find the summarry of each document using the same topics. The developed topic based model, is capable of grouping the legal judgments into different clusters and to generate summary of each legal judgment in the cluster, in effective manner compare to our previous approach [1]. Keyword:
The Study of Complex Adaptive System Theory and It's Application

Complex Adaptive System(CAS) is one of the common complex system. The bring forward of CAS theory has great guide meaning and application value on solving and interpreting the complex problem and phenomenon in complex system. In this paper, the author give an example of the application of CAS theory on economic system after the introducing of CAS theory and CAS character, showed the validity and meaning of this theory.
Handwritten Digit Recognition Technology Based on Multistage Classifying Device

On the basis of analyzing present Handwritten Numeral Recognition,a multistage classifying device is proposed and a multistage Classifying device system structure is given.Tow procedure are included:Preconditioning on Handwritten Digital samples;Drawing different classify characters in light of different subclassfying device.The identifying ratio increase by level number as the refuse identify samples of the last level are the input of the next level.Finally,a multistage classifying device experimental system is developed based on Visual C++ and Matlab.The result demonstrates that the identifying technology.Operates simply and has better performance as well.
Conditional functional dependencies for detecting data inconsistencies

Conditional Functional Dependencies (CFDs) are extension of Functional Dependencies (FDs) by importing semantic constraints.They can be made extensive use of data inconsistency repair and data cleaning.This paper discusses the semantic rules of CFDs,and mainly studies data inconsistencies detection based on CFDs.Particularly,it introduces confidence coefficients for improving detection rules,which have more advantages on the simplicity and the accurate standardization.