Miracle-dz/UniFAR-FTUs huggingface dataset:
Peroxisomes and Disease - An Overview

Peroxisomes are indispensable for human health and development. They represent ubiquitous subcellular organelles which compartmentalize enzymes responsible for several crucial metabolic processes such as β-oxidation of specific fatty acids, biosynthesis of ether phospholipids and metabolism of reactive oxygen species. Peroxisomes are highly flexible organelles that rapidly assemble, multiply and degrade in response to metabolic needs. Basic research on the biogenesis of peroxisomes and their metabolic functions have improved our knowledge about their crucial role in several inherited disorders and in other pathophysiological conditions. The goal of this review is to give a comprehensive overview of the role of peroxisomes in disease. Besides the genetic peroxisomal disorders in humans, the role of peroxisomes in carcinogenesis and in situations related to oxidative stress such as inflammation, ischemia-reperfusion, and diabetes will be addressed.
Wide area and wide band spectrum monitoring system based on sensor networks

With the increasing importance of radio spectrum in the national economy and safety, this paper develops a wide area and wide band radio spectrum monitoring system which uses sensor networks. The significant contribution of the paper is introducing wireless sensor networks into the design of the spectrum monitoring system. A spectrum monitoring oriented private network architecture is designed to realize the networked spectrum monitoring, and make the multi-node cooperation possible. So far, our system has covered the old and new campus of Xidian University, the forth telecom science institute, and other test regions, and continuously operated for two years. Under the monitoring band with 20MHz-8GHz, the system can achieve integrated comprehensive signal processing and intelligent analysis including signal detection, modulation recognition and location-tracking. The system solves the problems of spectrum monitoring and signal processing, which can be applied to spectrum monitoring in the complex electromagnetic environment.
Spatially resolved near-infrared spectroscopy of the massive star-forming region IRAS 19410+2336

Aims. IRAS 19410+2336 is a young massive star forming region with an intense outflow activity. Outflows are frequently studied in the near-infrared (NIR) since the H 2 emission in this wavelength range often traces the shocked molecular gas. However, the mechanisms behind the H 2 emission detected in IRAS 19410+2336 have not been clarified yet. We present here spatially resolved NIR spectroscopy which allows us to verify whether the H 2 emission originates from thermal emission in shock fronts or from fluorescence excitation by non-ionizing UV photons. Moreover, NIR spectroscopy also offers the possibility of studying the characteristics of the putative driving source(s) of the H 2 emission by the detection of photospheric and circumstellar spectral features, and of the environmental conditions (e.g. extinction). Methods. We obtained long-slit, intermediate-resolution, NIR spectra of IRAS 19410+2336 using LIRIS, the NIR imager/spectrographer mounted on the 4.2 m William Herschel Telescope. As a complement, we also obtained J, H and K s images with the Las Campanas 2.5 m Du Pont Telescope, and archival mid-infrared (MIR) Spitzer images at 3.6, 4.5, 5.8 and 8.0 μm. Results. We confirm the shocked nature of the H 2 emission, with an excitation temperature of about 2000 K, based on the analysis of relevant H 2 line ratios, ortho-to-para ratios and excitation diagrams. We have also identified objects with very different properties and evolutionary stages in IRAS 19410+2336. The most massive source at millimeter wavelengths, mml, with a mass of a few tens of solar masses, has a bright NIR (and MIR) counterpart. This suggests that emission - probably coming through a cavity created by one of the outflows present in the region, or from the outflow cavity itself - is leaking at these wavelengths. The second most massive millimeter source, mm2, is only detected at A ≥ 6 μm, suggesting that it could be a high-mass protostar still in its main accretion phase. The NIR spectra of some neighboring sources show CO first-overtone bandhead emission which is associated with neutral material located in the inner regions of the circumstellar environment of YSOs.
An efficient data structure for storing network intrusion detection dataset

Network based intrusion detection (NID) involves collection of raw packets from network and analyzing them for anomalous content. This deals with careful collection of required features from the header and payloads of packet. Data mining is one of the most popular technique to mine NID database. Most of the mining algorithms require multiple scans of database which increases the I/O operations and thus consume time. To cater this, data abstraction is used which reduces the memory requirement and scan time of database. In this paper we propose a novel data structure called Prefix Runlength tree (PR-Tree) for efficiently storing NID dataset. We used KDD 99 evaluation dataset for our experimentation and results are promising.
Systematic review of severe fever with thrombocytopenia syndrome:virology, epidemiology, and clinical characteristics

Severe fever with thrombocytopenia syndrome (SFTS) was firstly discovered in China in 2010, followed by several reports from many other countries worldwide. SFTS virus (SFTSV) has been identified as the causative agent of the disease and has been recognized as a public health threat. This novel Bunyavirus belongs to the Phlebovirus genus in the family Bunyaviridae. This review also describes the different aspects of virology, pathogenesis, epidemiology, and clinical symptoms on the basis of the published article surveillance data and phylogenetic analyses of viral sequences of large, medium, and small segments retrieved from database using mega 5.05, simplot 3.5. 1, network 4.611, and epi information system 3.5. 3 software. SFTS presents with fever, thrombocytopenia, leukocytopenia, and considerable changes in several serum biomarkers. The disease has 10 ~ 15% mortality rate, commonly because of multiorgan dysfunction. SFTSV is mainly reported in the rural areas of Central and North‐Eastern China, with seasonal occurrence from May to September, mainly targeting those of ≥50 years of age. A wide range of domesticated animals, including sheep, goats, cattle, pigs, dogs, and chickens have been proven seropositive for SFTSV. Ticks, especially Haemaphysalis longicornis, are suspected to be the potential vector, which have a broad animal host range in the world. More studies are needed to elucidate the vector–animal–human ecological cycle, the pathogenic mechanisms in high level animal models and vaccine development. © 2013 The Authors. Reviews in Medical Virology published by John Wiley & Sons, Ltd.
Extracting data records from web using suffix tree

There are many automatic methods that can extract lists of objects from the Web, but they often fail to handle multi-type pages automatically. This paper introduces a new method for record extraction using suffix tree which can find the repeated sub-string. Our method transfers a distinct group of tag paths appearing repeatedly in the DOM tree of the Web document to a sequence of integers firstly, and then builds a suffix tree by using this sequence. Four refining filter rules are defined. After the refining processes we can capture the useful data region patterns which can be used to extract data records. Experiments on real data show that this method is applicable for various web pages and can achieve higher accuracy and better robustness than previous methods.
Content-Based Social Network User Interest Tag Extraction

As a typical social network media, microblog has attracted a lot of users and quantities of information. More and more researchers and scholars are keen to explore useful information contained in microblog data and discover features of user interest for personalized recommendation. According to the unique feature of microblog text, this paper adjusts the traditional processes of Chinese word segmentation and tag extraction. Aiming to establish microblog user interest model, this paper combines clustering and classification algorithm to extract user interest tags. Experimenting upon Sina Weibo text dataset, the conclusion is reached that the method proposed in this paper is more effective and accurate to discover user features and the tags extracted are more in line with the user interest.
The Proposed GSD Model to Solve Coordination and Communication Problems

Global Software Development (GSD) is the most recent and major trend in software engineering domain. It provides many benefits but also faces various challenges in control, communication and coordination due to socio-cultural, geographical and temporal distance. Scrum is increasingly being applied in GSD as it supports teamwork between developers and customers. Scrum method offers a distinctive feature to mitigate the effects of socio-cultural and geographical but not temporal distance on coordination in GSD projects. This paper explains how Scrum helps to mitigate the effects of temporal distance that includes increased coordination costs in GSD projects.
Sustainable Leadership Practices Driving Financial Performance: Empirical Evidence from Thai SMEs

Many managers and researchers alike are asking: What does an enterprise need to do to generate a proper balance between economic, social, and ecological objectives while gaining superior corporate financial performance, resilience, and sustainability? Several leadership concepts for enhancing organizational sustainability have emerged in recent years, but none provides an integrative approach, with the exception of Sustainable Leadership (SL). However, empirical research examining the effects of various SL practices on financial performance and other business outcomes is lacking. This article addresses this gap by empirically investigating the relationships between 23 SL practices and financial performance. Using a cross-sectional survey, data stem from 439 managers in small and medium-sized enterprises (SMEs) in Thailand. Of the 23 SL practices in SL, 16 were significantly associated with corporate financial performance. Four SL practices, in particular—amicable labor relations, valuing employees, social responsibility, plus strong and shared vision—were significant drivers, and positive predictors, of enhanced long-term firm performance. Lastly, implications, limitations, and future directions are discussed.
Discovering Personal Action Contexts with SQL Server Integration and Analysis Services

Evidence of multitasking at work can be observed through several case studies. Moreover, task interleaving is constantly increasing due to the improvement of information and communication technologies. However, despite the availability of several personal information and task management tools, an appropriate support for multitasking is still lacking. Some reported limitations of current tools are: (1) overhead posed on users, (2) lack of automatic means for associating user actions with task or project contexts and enabling automatic switching between these contexts and (3) exclusion of interpersonal elements. Another important limitation is the design of current tools, which organizes actions and interactions according to single pre-defined schemas (e.g. tasks, projects or resources). We argue that this inflexibility is caused by the lack of an underlying theoretical model of multitasking. To overcome these limitations, this paper proposes a systems architecture that combines models of human multitasking and personal contexts. With the proposed architecture we aim at enabling semi-automatic discovery, display, switching, analysis and management of personal action contexts. This architecture is currently being implemented in a prototype with Visual Studio . net 2005 and SQL Server. In this paper, we report results on the automatic discovery of personal action contexts with SQL Server Integration and Analysis Services. These results are compared with results obtained through manual means.
On the query of video database

The usefulness of a video database depends on whether the video of interest can be easily located. In this paper, we propose a video retrieval algorithm based on a new representation of video shot. In contrast to key-frame based representation of shot, our approach analyzes all frames within a shot to fully exploit the spatio-temporal information contained in video. A compact shot representation is obtained by integrating the color and spatial features of individual frame. In the video matching step, a shot similarity measure is defined to locate the occurrence of similar video clips in the database. Experimental results indicate that the proposed approach is effective and feasible in retrieving and ranking similar video clips.
Learnability and discriminability of melodic medical equipment alarms *

Melodic alarms proposed in the IEC 60601‐1‐8 standard for medical electrical equipment were tested for learnability and discriminability. Thirty‐three non‐anaesthetist participants learned the alarms over two sessions of practice, with or without mnemonics suggested in the standard. Fewer than 30% of participants could identify the alarms with 100% accuracy at the end of practice. Confusions persisted between pairs of alarms, especially if mnemonics were used during learning (p = 0.011). Participants responded faster (p < 0.00001) and more accurately (p = 0.002) to medium priority alarms than to high priority alarms, even though they rated the high priority alarms as sounding more urgent (p < 0.00001). Participants with at least 1 year of formal musical training identified the alarms more accurately (p = 0.0002) than musically untrained participants, and found the task easier overall (p < 0.00001). More intensive studies of the IEC 60601‐1‐8 alarms are needed for their effectiveness to be determined.
Orthogonal snake model

Based on parametric snake model, this paper presents orthogonal snake model which retains some of the attractive features of existing methods and overcomes some of their limitations. The basic idea of orthogonal snake model is that any curve can be approximated by a polygon. Its key improvement is establishing the intrinsic relationship between the contour evolution and the intensity variation by computing the relative or absolute changes of intensity along orthogonal line of each side of polygon. Its information processing phase is a closed state. The algorithm is implemented with dynamic programming. The efficacy of this model is demonstrated with several experiments
A study and implementation of VGA multi-resolution on Android platform

At present, Android system can only support fixed resolution. This paper discusses a universal and concise solution to solve this problem, and the realization of Android VGA multi-resolution is described in detail. In order to solve the problem efficiently, we present a method with presetting resolution and reboot-confirmation strategy. This method involves multiple layers of the Android system architecture. We conducted a study on the Android system framework and graphics system architecture. Combined with Framebuffer driver technology of the Linux Kernel, the study applies the presetting resolution and reboot-confirmation method by using the existed framework. According to experiment result, the design achieved the expected goal, and it ensured the stable operation of the system. This solution is universal for all Android systems. In a way, it has reference value and practical value for making Android system support multi-resolution.
Towards Text Processing System for Emergency Event Detection in the Arctic Zone

We present the ongoing work on text processing system for detection and analysis of events related to emergencies in the Arctic zone. The peculiarity of the task consists in data sparseness and scarceness of tools / language resources for processing such specific texts. The system performs focused crawling of documents related to emergencies in the Arctic region, text parsing including named entity recognition and geotagging, and indexing texts with their metadata for faceted search. The system aims at processing both English and Russian text messages and documents. We report the preliminary results of the experimental evaluation of the system components on Twitter data.
Interactive Planarization and Optimization of 3D Meshes

Constraining 3D meshes to restricted classes is necessary in architectural and industrial design, but it can be very challenging to manipulate meshes while staying within these classes. Specifically, polyhedral meshes—those having planar faces—are very important, but also notoriously difficult to generate and manipulate efficiently. We describe an interactive method for computing, optimizing and editing polyhedral meshes. Efficiency is achieved thanks to a numerical procedure combining an alternating least‐squares approach with the penalty method. This approach is generalized to manipulate other subsets of polyhedral meshes, as defined by a variety of other constraints.
Named Entity Recognition and Classification for texts in Basque 1

This paper presents a system for Named Entity (NE) recognition in written Basque to be used in a CLIR application. Being an agglutinative language, Basque has highly inflected forms, so a previous linguistic preprocess is required. The tool we present relies on a combined method that carries out the identification and recognition of entity names in two subsequent steps. First, a grammar based on morphological information is applied in order to extract the entity names of the text, and then, the identified entities are classified by applying a heuristic that combines contextual information and gazetteers.
Explorer MATHsAiD : A Mathematical Theorem Discovery Tool

In the field of automated reasoning, one of the most challenging (even if, perhaps, somewhat overlooked) problems thus far has been to develop a means of discerning, from amongst all the truths that can be discovered and proved, those which are either useful or interesting enough to be worth recording. As for human reasoning, mathematicians are well known for their predilection towards designating certain discoveries as theorems, lemmas, corollaries, etc., whilst relegating all others as relatively unimportant. However, precisely how mathematicians determine which results to keep, and which to discard, is perhaps not so well known. Nevertheless, this practice is an essential part of the mathematical process, as it allows mathematicians to manage what would otherwise be an overwhelming amount of knowledge. MATHsAiD is a system intended for use by research mathematicians, and is designed to produce high quality theorems, as recognised by mathematicians, within a given theory. The only input required is a set of axioms and definitions for each theory. In this paper we brie y describe some of the more important methods used by MATHsAiD, most of which are based primarily on the human mathematical process.
Execution and Verification of Imperative Programs

This paper studies the relation between execution and verification. A simple imperative language with execution and verification commands is introduced. A machine only executes execution commands of a program, while the compiler only performs the verification commands. Common commands in other languages can be defined as a combination of execution and verification commands. Design of verifiers then becomes program design using verification commands. It is shown that type checking, abstract interpretation, modeling checking and Hoare Logic are all special verification programs, so are many of their combinations.
Deliberation, Distraction, and the role of the unconscious in Multiple Cue Probability Learning

Many findings in cognitive psychology suggest that many decisions and judgments rely on processes that are unconscious, that these processes can be disrupted by conscious input, leading to poor decision making. A commonly paradigm has shown that decision makers who are distracted while deciding make better to make quick decisions . The distraction is thought to facilitate spontaneous unconscious processing, called the “deliberation without attention effect”, that lead to better decisions when the question is later revisited. This effect was tested in three studies on diagnostic judgments in a multiple cue probability learning paradigm. In three studies, the effect of rushed decision making, forced deliberation, and distraction were tested on probability judgments, and on choices and confidence judgments. Evidence suggested that subjects in the immediate decision were less accurate than the other conditions, in decisions and judgments, despite higher levels of confidence, but equaled performance in other conditions when given make-work tasks in between decisions, which may have primed more careful or more deliberate thinking. The results did not make any strong theoretical implications for the deliberation without attention effect.
Zeaxanthin Radical Cation Formation in Minor Light-harvesting Complexes of Higher Plant Antenna*

Previous work on intact thylakoid membranes showed that transient formation of a zeaxanthin radical cation was correlated with regulation of photosynthetic light-harvesting via energy-dependent quenching. A molecular mechanism for such quenching was proposed to involve charge transfer within a chlorophyll-zeaxanthin heterodimer. Using near infrared (880-1100 nm) transient absorption spectroscopy, we demonstrate that carotenoid (mainly zeaxanthin) radical cation generation occurs solely in isolated minor light-harvesting complexes that bind zeaxanthin, consistent with the engagement of charge transfer quenching therein. We estimated that less than 0.5% of the isolated minor complexes undergo charge transfer quenching in vitro, whereas the fraction of minor complexes estimated to be engaged in charge transfer quenching in isolated thylakoids was more than 80 times higher. We conclude that minor complexes which bind zeaxanthin are sites of charge transfer quenching in vivo and that they can assume Non-quenching and Quenching conformations, the equilibrium LHC(N) ⇆ LHC(Q) of which is modulated by the transthylakoid pH gradient, the PsbS protein, and protein-protein interactions.
Streamlining the Risk Analysis Process and Ensuring the Optimal Organizations for Food Safety: The case application to biotechnology of Fusarium species

Food safety and security may be improved by using technological innovation. However, hostile consumer reaction to scientific solutions is commonly accompanied. The case analysis of food and environmentally borne Fusarium mycotoxins and illnesses is examined to clarify a situation where the biotechnological tools could be utilized. Fusarium species cause serious economic hardships. The greatest concern is in diseases like Fusarium head blight (FHB) associated with deadly mycotoxins, as well as opportunistic species such as Fusarium solani can directly infect humans, causing serious illness. An evaluation of the risk analysis framework critiques and makes suggested solutions in order to effectively manage the use of biotechnology in sensitive situations, as in the case of Fusarium.
Construction of Lyapunov-Krasovskii functional for time-varying delay systems

This paper provides some new techniques to construct a Lyapunov-Krasovskii functional for time varying delay systems. The construction is based on a partitioning scheme of the time-varying delay leading to a new type of Lyapunov-Krasovskii functional. This functional is depending on an augmented state and also on an integral quadratic constraint added to reduce the conservatism of the proposed methodology. This approach is then extended to the robust case. Finally, some examples support our approach.