Miracle-dz/UniFAR-FTUs huggingface dataset:
Oligo-Carrageenan Kappa-Induced Reducing Redox Status and Activation of TRR/TRX System Increase the Level of Indole-3-acetic Acid, Gibberellin A3 and trans-Zeatin in Eucalyptus globulus Trees

Eucalyptus globulus trees treated with oligo-carrageenan (OC) kappa showed an increase in NADPH, ascorbate and glutathione levels and activation of the thioredoxin reductase (TRR)/thioredoxin (TRX) system which enhance photosynthesis, basal metabolism and growth. In order to analyze whether the reducing redox status and the activation of thioredoxin reductase (TRR)/thioredoxin (TRX) increased the level of growth-promoting hormones, trees were treated with water (control), with OC kappa, or with inhibitors of ascorbate synthesis, lycorine, glutathione synthesis, buthionine sulfoximine (BSO), NADPH synthesis, CHS-828, and thioredoxin reductase activity, auranofine, and with OC kappa, and cultivated for four additional months. Eucalyptus trees treated with OC kappa showed an increase in the levels of the auxin indole 3-acetic acid (IAA), gibberellin A3 (GA3) and the cytokinin trans-zeatin (t-Z) as well as a decrease in the level of the brassinosteroid epi-brassinolide (EB). In addition, treatment with lycorine, BSO, CHS-828 and auranofine inhibited the increase in IAA, GA3 and t-Z as well as the decrease in EB levels. Thus, the reducing redox status and the activation of TRR/TRX system induced by OC kappa increased the levels of IAA, GA3 and t-Z levels determining, at least in part, the stimulation of growth in Eucalyptus trees.
Deep Surveys and Cosmology

Surveys with ISO (Kessler et al 1996), in particular with the CAM (Cesarsky et al 1996) and PHOT (Lemke et al 1996) instruments, will greatly extend our understanding of extra-galactic populations and their cosmological evolution. The main advantages that ISO surveys have over e.g IRAS are increased sensitivity/depth and wavelength coverage. Within the Guaranteed and Open Time programmes there are many field surveys which will efficiently map the limits in these parameters. In this talk I will briefly overview those surveys before concentrating in more detail on one survey in particular, the ISO survey of the Hubble Deep Field (HDF), to illustrate the kind of results that can be expected.
Placement and routing for 3D-FPGAs using reinforcement learning and support vector machines

The primary advantage of using 3D-FPGA over 2D-FPGA is that the vertical stacking of active layers reduce the Manhattan distance between the components in 3D-FPGA than when placed on 2D-FPGA. This results in a considerable reduction in total interconnect length. Reduced wire length eventually leads to reduction in delay and hence improved performance and speed. Design of an efficient placement and routing algorithm for 3D-FPGA that fully exploits the above mentioned advantage is a problem of deep research and commercial interest. In this paper, an efficient placement and routing algorithm is proposed for 3D-FPGAs which yields better results in terms of total interconnect length and channel-width. The proposed algorithm employs two important techniques, namely, reinforcement learning (RL) and support vector machines (SVMs), to perform the placement. The proposed algorithm is implemented and tested on standard benchmark circuits and the results obtained are encouraging. This is one of the very few instances where reinforcement learning is used for solving a problem in the area of VLSI.
An optimal scheduling policy for a two-flow priority queue with alternate paths

We consider a path-scheduling problem at a resource constrained node A that transmits two types of flows to a given destination through alternate paths. Type-1 flow is assumed to have a higher priority than type-2 flow thus, it is never rejected upon arrival. Type-2 flow, on the other hand, may be denied admission to the queue. Once accepted to the system, a packet joins queue 1 and is guaranteed service independent of its type. Instead of being rejected from service, packets have the option to be served at a slower server behind a second queue (queue 2) at node A. The slow server is intended mostly to serve low priority packets, therefore, type-1 packets are charged a switching cost in the event they are sent to queue 2. Transmitted packets receive a reward depending on which queue they were served at. The reward represents the resources saved for making that decision. A good path-scheduling policy at node A can reduce resource consumption at node A, extend the life of the efficient path, maximizes the service of both flows and guarantees the service of at least the high priority flow to the full extent. We propose and solve the path-scheduling problem for node A, which maximizes the average reward of successfully transmitting flows to a given sink, by dynamically assigning packets to one of the queues based on the packet type, the instantaneous queue lengths and the average reward for the associated path. We formulated the path-scheduling problem as a Markov decision process and show that the optimal policy is threshold-type.
Estimating Null Values in Database Using CBR and Supervised Learning Classification

Database and database systems have been used widely in almost, all life activities. Sometimes missed data items are discovered as missed or null values in the database tables. The presented paper proposes a design for a supervised learning system to estimate missed values found in the university database. The values of estimated data items or data it items used in estimation are numeric and not computed. The system performs data classification based on Case-Based Reasoning (CBR) to estimate loosed marks of students. A data set is used in training the system under the supervision of an expert. After training the system to classify and estimate null values under expert supervision, it starts classification and estimation of null data by itself.
The SMART Data Analysis Package for the Infrared Spectrograph on the Spitzer Space Telescope

SMART is a software package written in IDL to reduce and analyze Spitzer data from all four modules of the Infrared Spectrograph, including the peak‐up arrays. The software is designed to make full use of the ancillary files generated in the Spitzer Science Center pipeline so that it can either remove or flag artifacts and corrupted data and maximize the signal‐to‐noise ratio in the extraction routines. It can be run in both interactive and batch modes. The software and users guide will be available for public release in 2004 December. We briefly describe some of the main features of SMART, including visualization tools for assessing data quality, basic arithmetic operations for either two‐dimensional images or one‐dimensional spectra, extraction of both point and extended sources, and a suite of spectral analysis tools.
Optimal Detection of IDMA Signals

In this paper the system model of an uncoded and fully synchronised interleave division multiple access (IDMA) scheme is transformed into an equivalent matrix model. This new model allows for additional alternative insights into the principles of IDMA and it is shown that the arising matrices are highly structured and very sparse. Furthermore the optimal detector for IDMA is derived and compared to the standard iterative decoder. The authors use exit charts and an empirical rank analysis to highlight that systems without an alternating signature mask always have a low rank and that parallel interference cancellation then fails.
Optimal Solution of Collision Avoidance Maneuver with Multiple Space Debris

In this paper, the authors introduced a new approach to find the optimal collision avoidance maneuver considering multi threatening objects within short period, while minimizing the fuel consumption and satisfying the acceptable collision probability. A preliminary effort in applying a genetic algorithm (GA) to those kinds of problems has also been demonstrated through a simulation study with a simple case problem. And then, GA is applied to the complex case problem including multi-threatening objects. Two distinct collision avoidance maneuvers are dealt with: the first is in-track direction of collision avoidance maneuver. The second considers radial, in-track, and cross-track direction maneuvers. The results show that the first case violates the collision probability threshold, while the second case does not violate the threshold with satisfaction of all conditions. And the second case is consumed fuel less than the first case in minimization problem of fuel consumption. Various factors for analyzing and planning the optimal collision avoidance maneuver are also presented.
IAServ: An Intelligent Home Care Web Services Platform in a Cloud for Aging-in-Place

As the elderly population has been rapidly expanding and the core tax-paying population has been shrinking, the need for adequate elderly health and housing services continues to grow while the resources to provide such services are becoming increasingly scarce. Thus, increasing the efficiency of the delivery of healthcare services through the use of modern technology is a pressing issue. The seamless integration of such enabling technologies as ontology, intelligent agents, web services, and cloud computing is transforming healthcare from hospital-based treatments to home-based self-care and preventive care. A ubiquitous healthcare platform based on this technological integration, which synergizes service providers with patients’ needs to be developed to provide personalized healthcare services at the right time, in the right place, and the right manner. This paper presents the development and overall architecture of IAServ (the Intelligent Aging-in-place Home care Web Services Platform) to provide personalized healthcare service ubiquitously in a cloud computing setting to support the most desirable and cost-efficient method of care for the aged-aging in place. The IAServ is expected to offer intelligent, pervasive, accurate and contextually-aware personal care services. Architecturally the implemented IAServ leverages web services and cloud computing to provide economic, scalable, and robust healthcare services over the Internet.
Stochastic Filtering with Networked Sensing

This paper presents a solution to the problem of target tracking within a sensor network. This is based on modeling the target dynamics as a Markov process, and is reformulated as nonlinear filtering. When the target motion is a diffusion process, the optimal filtering involves a resolution of the backward Kolmogorov equation. Since an explicit solution for this partial differential equation does not exist in general, we recover the filtering by an alternative Monte-Carlo approach.
Psychological Reactions to an MI: A Study of Attention and Avoidance to Cardiac Stimuli.

iii CHAPTER INTRODUCTION . 1 REVIEW OF LITERATURE . 4 Psychological Reactions to an MI . 4 Coping Reactions . 10 Information Processing Approach to Attention . 15 Thought Suppression . 22 Overview of Proposed Study . 35 METHODS . 41 Subj ects . 41 Measures . 42 Attentional Search Task . 46 Thought Suppression Manipulation . 47 Procedure . 49 RESULTS . 51 Proposed Analyses . 51 Exploratory Analyses . 69 DISCUSSION . 78 Summary of Main Findings . 78 Attention to Threat . 79 Influence of Suppression Instructions . 89 Conclusion and Future Directions . 92 REFERENCES . 100 APPENDIXES A DEMOGRAPHIC INFORMATION QUESTIONNAIRE. 107 B CONSENT FORM . 109 C STATE-TRAIT ANXIETY INVENTORY . Ill D MILLER BEHAVIORAL STYLE SCALE . 114 F CARDIAC CONCERN QUESTIONNAIRE . 117 G CENTER FOR EPIDEMIOLOGICAL STUDY DEPRESSION SCALE . 119 H WORDS USED IN ATTENTIONAL SEARCH TASK . 121 VITA . 123
On the complex scheduling formulation of virtual network functions over optical networks

Software-Defined Networking and Network Functions Virtualisation has brought a revolution within the telecom market landscape. Initial proof-of-concept prototypes for NFV-enabled solutions are being developed at the same time SDN models are identified as the futures solutions within the telecom realm. We provide in this article an overview of the SDN/NFV technologies over optical networks, as well as we provide the first formalisation model for the virtual network function complex scheduling problem. The article aims at being used as starting point in order to optimally solve the scheduling problem of virtual network functions that compose network services to be provisioned within the SDN paradigm.
37 Million Compilations: Investigating Novice Programming Mistakes in Large-Scale Student Data

Previous investigations of student errors have typically focused on samples of hundreds of students at individual institutions. This work uses a year's worth of compilation events from over 250,000 students all over the world, taken from the large Blackbox data set. We analyze the frequency, time-to-fix, and spread of errors among users, showing how these factors inter-relate, in addition to their development over the course of the year. These results can inform the design of courses, textbooks and also tools to target the most frequent (or hardest to fix) errors.
Inhibition of HMGB1-Induced Angiogenesis by Cilostazol via SIRT1 Activation in Synovial Fibroblasts from Rheumatoid Arthritis

High mobility group box chromosomal protein 1 (HMGB-1) released from injured cells plays an important role in the development of arthritis. This study investigated the anti-angiogenic effects of cilostazol in collagen-induced arthritis (CIA) of mice, and the underlying mechanisms involved. The expressions of HIF-1α, VEGF, NF-κB p65 and SIRT1 in synovial fibroblasts obtained from rheumatoid arthritis (RA) patients were assessed by Western blotting, and in vitro and in vivo angiogenesis were analyzed. Tube formations by human microvascular endothelial cells (HMVECs) were significantly increased by direct exposure to HMGB1 or to conditioned medium derived from HMGB1-stimulated RA fibroblasts, and these increases were attenuated by cilostazol, the latter of which was blocked by sirtinol. HMGB1 increased the expression of HIF-1α and VEGF and concomitantly increased nuclear NF-κB p65 and DNA binding activity, but these effects of HMGB1 were inhibited by cilostazol. SIRT1 protein expression was time-dependently decreased (3–24 hr) by HMGB1, which was recovered by pretreatment with cilostazol (1–30 µM) or resveratrol, accompanying with increased SIRT1 deacetylase activity. In the tibiotarsal joint tissues of CIA mice treated with vehicle, HIF-1α- and VEGF-positive spots and CD31 staining were markedly exaggerated, whereas SIRT1 immunofluorescence was diminished. These variables were wholly reversed in cilostazol (30 mg/kg/day)-treated mice. Furthermore, number of blood vessels stained by von Willebrand factor antibody was significantly lower in cilostazol-treated CIA mice. Summarizing, cilostazol activated SIRT1 and inhibited NF-κB-mediated transcription, thereby suppressing the expression of HIF-1α and VEGF. In addition, cilostazol caused HIF-1α deacetylation by enhancing SIRT1 activity and reduced VEGF production, thereby had an anti-angiogenic effect in vitro studies and in CIA murine model.
Tracking Food Materials with Changing Their Appearance in Food Preparing

This paper describes our work in computer vision to track food materials in the food preparation process. Tracking such food materials is difficult, because they are often hidden when moved by hand. Furthermore, their appearance may change in hand when they are cut or peeled. For tracking these objects in such situations, we propose a novel method that matches an object on a cooking table to one grasped in the past. We use the following three criteria to match the objects even when they are cut or peeled: the similarity in their appearance, the validity of their change in appearance, and the grasped order. We experimentally evaluated our method by applying it to the scenes of cutting and peeling food materials. As a result, we achieved an accuracy of 83.6% in matching the objects.
Developing highER-throughput zebrafish screens for in-vivo CNS drug discovery

The high prevalence of brain disorders and the lack of their efficient treatments necessitate improved in-vivo pre-clinical models and tests. The zebrafish (Danio rerio), a vertebrate species with high genetic and physiological homology to humans, is an excellent organism for innovative central nervous system (CNS) drug discovery and small molecule screening. Here, we outline new strategies for developing higher-throughput zebrafish screens to test neuroactive drugs and predict their pharmacological mechanisms. With the growing application of automated 3D phenotyping, machine learning algorithms, movement pattern- and behavior recognition, and multi-animal video-tracking, zebrafish screens are expected to markedly improve CNS drug discovery.
New cost calculation method for finding shortest path of Hybrid VANET protocol

A Vehicular Ad-Hoc Network (VANET) which enables vehicles to communicate one another has played an important role in the wireless network communication and in the Internet of Things (IoT). Many protocols and standards have been proposed in order to implement VANET. On the road, there are both buses and cars as vehicles. Some protocols uses only cars and some protocol uses only buses for packet forwarding. Hybrid-VANET protocol that uses both buses and cars was proposed However, there are still some challenge in cost calculation for finding the shortest paths from sources to destinations of packets. In this paper, we propose a new method of cost calculation for using in Hybrid-VANET protocol. Our proposed method is more effective in the term of packet losses and computing complication. We evaluate our proposed method by simulation. The experimental results show that our method improves the packet losses and packet delays over Hybrid-VANT and some other VANET protocols.
Generalized antisymmetric filters for edge detection

A large number of filters has been proposed to compute local gradients in grayscale images, usually having as goal the adequate characterization of edges. A significant portion of such filters are antisymmetric with respect to the origin. In this work we propose to generalize those filters by incorporating an explicit evaluation of the tonal difference. More specifically, we propose to apply restricted dissimilarity functions to appropriately measure the tonal differences. We present the mathematical developments, as well as quantitative experiments that indicate that our proposal offers a clear option to improve the performance of classical edge detection filters.
Konrad-zuse-zentrum F ¨ Ur Informationstechnik Berlin Self-organizing Maps Combined with Eigenmode Analysis for Automated Cluster Identification Self-organizing Maps Combined with Eigenmode Analysis for Automated Cluster Identification

One of the important tasks in Data Mining is automated cluster analysis. Self-Organizing Maps (SOMs) introduced by Kohonen are, in principle , a powerful tool for this task. Up to now, however, its cluster identification part is still open to personal bias. The present paper suggests a new approach towards automated cluster identification based on a combination of SOMs with an eigenmode analysis that has recently been developed by Deuflhard et al. in the context of molecular conformational dynamics. Details of the algorithm are worked out. Numerical examples from Data Mining and Molecular Dynamics are included.
Diagnostic Method of Quality Degradation Segment from Sampled Packets

Recent diversification in applications has increased the number of services that are sensitive to network quality. For such services, degradation of network quality such as packet loss or delay is directly linked to the quality perceived by users. It is therefore important for network administrators to know these quality indicators for each session. However, the measurement of quality per session has become difficult due to the rapid increase of line speeds. Packet sampling techniques have been receiving much attention as a way to solve this problem, but there has been only a little discussion of packet loss in that research though it is very important. In order to determine whether quality degradations occur at particular sessions, we have proposed methods for estimating the end-to-end packet loss per session by packet sampling. In this paper, we then propose a method to determine whether the quality degradation occurs between the sending terminal and the measurement point (send segment) or between the measurement point and the receiving terminal (receive segment). The proposed method will estimate packet loss of receive segment to observe duplicate ACKs and the DATA packet with corresponding sequence number to ACK number of duplicate ACKs. Then, the packet loss of send segment can be estimated by subtraction packet loss of receive segment from end-to-end packet loss. This allows quality degradation segment to be estimated from only a 10% sample of the packet flow
Visualizing 2D Flows with Animated Arrow Plots

Flow fields are often represented by a set of static arrows to illustrate scientific vulgarization, documentary film, meteorology, etc. This simple schematic representation lets an observer intuitively interpret the main properties of a flow: its orientation and velocity magnitude. We propose to generate dynamic versions of such representations for 2D unsteady flow fields. Our algorithm smoothly animates arrows along the flow while controlling their density in the domain over time. Several strategies have been combined to lower the unavoidable popping artifacts arising when arrows appear and disappear and to achieve visually pleasing animations. Disturbing arrow rotations in low velocity regions are also handled by continuously morphing arrow glyphs to semi-transparent discs. To substantiate our method, we provide results for synthetic and real velocity field datasets.
ProPred: prediction of HLA-DR binding sites

UNLABELLED ProPred is a graphical web tool for predicting MHC class II binding regions in antigenic protein sequences. The server implement matrix based prediction algorithm, employing amino-acid/position coefficient table deduced from literature. The predicted binders can be visualized either as peaks in graphical interface or as colored residues in HTML interface. This server might be a useful tool in locating the promiscuous binding regions that can bind to several HLA-DR alleles. AVAILABILITY The server is available at http://www.imtech.res.in/raghava/propred/ CONTACT raghava@imtech.res.in SUPPLEMENTARY INFORMATION http://www.imtech.res.in/raghava/propred/page3.html
Improving the Performance of a Scalable Encryption Algorithm (SEA) using FPGA

The present symmetric encryption algorithms result from a Tradeoff between implementation cost and resulting performances. SEA is a scalable encryption algorithm targeted for small embedded applications. It was initially designed for software implementations in controllers, smart cards, or processors. In this Paper we proposed a system that investigates its performances in recent field-programmable gate array (FPGA) devices. The proposed system is applicable where there are limited processing resources and throughput requirements. For this purpose, we propose low-cost encryption routines (i.e. with small code size and memory) targeted for processors with a limited instruction set (i.e. AND, OR, XOR gates, word rotation and modular addition). The proposed design is parametric in the text, key and processor size, provably secure against linear or differential cryptanalysis, allows efficient combination of encryption/decryption and on-the-fly" key derivation. Beyond its low cost performances, a significant advantage of the proposed architecture is its full flexibility for any parameter of the scalable encryption algorithm, taking advantage of generic VHDL coding.