Miracle-dz/UniFAR-FTUs huggingface dataset:
Designing a Chemical Script Editor in Grid environment with DLTK

All chemistry software has its own language and provides its corresponding script editor. A complex chemical job running in Grid environment often requires different chemistry software’s collaboration. The chemist edits computational chemistry program locally, then submits them to the Grid environment. Therefore, chemists need to use appropriate chemical editors for syntax checking when modifying chemical scripts. This process would require installing several kinds of chemistry software locally, which would be time-consuming and inconsequence. This paper proposes a solution, a Chemical Script Editor supporting several chemical script languages, to deal with this issue. The Chemical Script Editor is not only multifunctional and multi-lingual but also simple and easy to install. What’s more, the Chemical Script Editor caters to the dynamic characteristics of Grid environment perfectly. This paper would use a new framework -DLTK- to generate the Chemical Script Editor as a PLUG-INS to Eclipse platform.
Refinement of statemachines using hierarchical states , choice points and joins

While refinement gives a formal underpinning to the development of dependable control systems, such models are difficult to communicate and reason about in a non-formal sense, particularly for validation by non-specialist industrial partners. Here we present a visualisation of event B refinement using a specialisation of UML statemachines. The specialisation will be incorporated into the UML-B notation that is being re-developed within the Rodin project to improve integration with the Event B platform, which is also being developed by the Rodin project.
Overexpression of AtCpNifS Enhances Selenium Tolerance and Accumulation in Arabidopsis1

Selenium (Se) is an essential element for many organisms but is toxic at higher levels. CpNifS is a chloroplastic NifS-like protein in Arabidopsis (Arabidopsis thaliana) that can catalyze the conversion of cysteine into alanine and elemental sulfur (S0) and of selenocysteine into alanine and elemental Se (Se0). We overexpressed CpNifS to investigate the effects on Se metabolism in plants. CpNifS overexpression significantly enhanced selenate tolerance (1.9-fold) and Se accumulation (2.2-fold). CpNifS overexpressors showed significantly reduced Se incorporation into protein, which may explain their higher Se tolerance. Also, sulfur accumulation was enhanced by approximately 30% in CpNifS overexpressors, both on media with and without selenate. Root transcriptome changes in response to selenate mimicked the effects observed under sulfur starvation. There were only a few transcriptome differences between CpNifS-overexpressing plants and wild type, besides the 25- to 40-fold increase in CpNifS levels. Judged from x-ray analysis of near edge spectrum, both CpNifS overexpressors and wild type accumulated mostly selenate (SeVI). In conclusion, overexpression of this plant NifS-like protein had a pronounced effect on plant Se metabolism. The observed enhanced Se accumulation and tolerance of CpNifS overexpressors show promise for use in phytoremediation.
Geophysical Signatures of Shear‐Induced Damage and Frictional Processes on Rock Joints

In this study, ultrasonic waves recorded during direct shear experiments on rock joints were employed to investigate the shear failure processes. Three types of wave attributes were systematically observed prior to the shear failure of the rock joints: (a) maximum in the amplitude of the transmitted wave, (b) maximum in the dominant frequency of the transmitted wave, and (c) maximum in the velocity of the wave. Different processes occurring during both frictional sliding and stick‐slip oscillations were identified in this study: (a) interseismic phase and (b) preseismic phase. The interseismic phase is associated with elastic loading, very small local slip rate, and increasing ultrasonic transmission along the contact surfaces. The rock joint is considered locked, and the increase in ultrasonic transmission represents an increase in the real (true) area of contact because of interlocking and contact aging. The start of the preseismic phase is marked by the onset of precursors for different regions of the rock joint. Following the interseismic and preseismic phases, coseismic phase occurs. The coseismic phase begins with the reduction in the applied shear stress and is associated with an abrupt increase in the local slip rate. The reductions in transmitted amplitude, wave velocity, and dominant frequency all indicate the preseismic phase when the asperity contacts begin to fail before macroscopic frictional sliding. The observation of the preseismic phase in both the loading phase leading to stable sliding and stick‐slip failure modes suggests that microphysical processes of fault weakening may share key features for these two failure modes.
Wormhole Attack Behaviour in Monte-Carlo Localization for Mobile Sensor Networks

Localization is the basic requirement for network management in Wireless Sensor Networks as it helps nodes find their absolute position coordinates and in gathering information relevant to their locations. A localization algorithm has to be dynamic, scalable and should not impose high computation or communication overhead. The localization systems are also prone to attacks. We target a localization scheme for mobile sensor networks called Monte-Carlo Localization, which study its behavior under the most dangerous attack on localization called Wormhole Attack, also known as Collusion Attack and propose a modified algorithm that can help the localization system retain its accuracy level even in the presence of attacks. Our algorithm has communication cost almost equal to that of original localization algorithm (in this case MCL) in the absence of attacks.
A Language-Independent Transliteration Schema Using Character Aligned Models at NEWS 2009

In this paper we present a statistical transliteration technique that is language independent. This technique uses statistical alignment models and Conditional Random Fields (CRF). Statistical alignment models maximizes the probability of the observed (source, target) word pairs using the expectation maximization algorithm and then the character level alignments are set to maximum posterior predictions of the model. CRF has efficient training and decoding processes which is conditioned on both source and target languages and produces globally optimal solution.
Improving the Performance of Wireless Ad Hoc Networks Through MAC Layer Design

In this paper, the performance of the ALOHA and CSMA MAC protocols are analyzed in spatially distributed wireless networks. The main system objective is correct reception of packets, and thus the analysis is performed in terms of outage probability. In our network model, packets belonging to specific transmitters arrive randomly in space and time according to a 3-D Poisson point process, and are then transmitted to their intended destinations using a fully-distributed MAC protocol. A packet transmission is considered successful if the received SINR is above a predefined threshold for the duration of the packet. Accurate bounds on the outage probabilities are derived as a function of the transmitter density, the number of backoffs and retransmissions, and in the case of CSMA, also the sensing threshold. The analytical expressions are validated with simulation results. For continuous-time transmissions, CSMA with receiver sensing (which involves adding a feedback channel to the conventional CSMA protocol) is shown to yield the best performance. Moreover, the sensing threshold of CSMA is optimized. It is shown that introducing sensing for lower densities (i.e., in sparse networks) is not beneficial, while for higher densities (i.e., in dense networks), using an optimized sensing threshold provides significant gain.
A Model of Interval Timing by Neural Integration

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.
Formulation and Physicochemical Characterization of Lycopene-Loaded Solid Lipid Nanoparticles.

PURPOSE Lycopene belongs to the carotenoids that shows good pharmacological properties including antioxidant, anti-inflammatory and anticancer. However, as a result of very low aqueous solubility, it has a limited systemic absorption, following oral administration. METHODS Here, we prepared a stable lycopene-loaded solid lipid nanoparticles using Precirol® ATO5, Compritol 888 ATO and myristic acid by hot homogenization method with some modification. The size and morphological characteristics of nanoparticles were evaluated using Scanning Electron Microscopy (SEM). Moreover, zeta potential and dispersity index (DI) were measured using zeta sizer. In addition, encapsulation efficiency (EE%), drug loading (DL) and cumulative drug release were quantified. RESULTS The results showed that the size and DI of particles was generally smaller in the case of SLNs prepared with precirol when compared to SLNs prepared with compritol. Scanning electron microscopy (SEM) and particle size analyses showed spherical SLNs (125 ± 3.89 nm), monodispersed distribution, and zeta potential of -10.06 ± 0.08 mV. High EE (98.4 ± 0.5 %) and DL (44.8 ± 0.46 mg/g) were achieved in the case of nanoparticles prepared by precirol. The stability study of the lycopene-SLNs in aqueous medium (4 °C) was showed that after 2 months there is no significant differences seen in size and DI compared with the fresh formulation. CONCLUSION Conclusively, in this investigation we prepared a stable lycopene-SLNs with good physicochemical characteristic which candidate it for the future in vivo trials in nutraceutical industries.
Optimal Investments for Robust Utility Functionals in Complete Market Models

This paper introduces a systematic approach to the problem of maximizing the robust utility of the terminal wealth of an admissible strategy in a general complete market model, where the robust utility functional is defined by a set Q of probability measures. Our main result shows that this problem can often be reduced to determining a "least favorable" measure Q0âQ, which is universal in the sense that it does not depend on the particular utility function. The robust problem is thus equivalent to a standard utility-maximization problem with respect to the "subjective" probability measure Q0. By using the Huber-Strassen theorem from robust statistics, it is shown that Q0 always exists if Q is the I-core of a 2-alternating capacity. Besides other examples, we also discuss the problem of robust utility maximization with uncertain drift in a Black-Scholes market and the case of "weak information. "
Key issues in the developing synergism between cardiovascular imaging and biomarkers.

BACKGROUND Sophisticated methods of cardiac imaging have the potential to revolutionize the care of patients with cardiovascular disease. The benefits of these state-of-the art imaging techniques can be enhanced by their use in combination with new cardiac biomarkers. This review addresses potentially useful interactions between imaging and biomarkers. CONTENT Areas were defined in which the combined use of novel imaging techniques and biomarkers would be most beneficial. This review addresses multiple cardiovascular conditions for which the useful aspects of imaging and biomarkers are likely to be positively synergistic, including acute and chronic ischemic heart disease, heart failure, myocarditis, hypertension, and atherosclerosis. CONCLUSIONS The synergistic use of imaging techniques and biomarkers will enhance the investigation of many key issues and questions and will be an important resource in the future.
Active learning using a low-rank classifier

The majority of learning algorithms work based on a training dataset. However, labeling the collected data is costly and time consuming. Active learning has gained high attention due to its ability to label a vast amount of unlabeled collected data. However, the performance of the current state-of-the-art methods declines when the number of training data is increasing. In this paper, we propose and study a variant of Support Vector Machine (SVM), namely low-rank classifier, which is regularized by the trace-norm of learning parameters in active learning scenario. We compare this algorithm with the standard SVM algorithms in depth and analyze its computational complexity and optimization solution. Our experimental results confirm, that the proposed method outperforms the other methods for an increasing amount of training data.
Arabic-Segmentation Combination Strategies for Statistical Machine Translation

Arabic segmentation was already applied successfully for the task of statistical machine translation (SMT). Yet, there is no consistent comparison of the effect of different techniques and methods over the final translation quality. In this work, we use existing tools and further re-implement and develop new methods for segmentation. We compare the resulting SMT systems based on the different segmentation methods over the small IWSLT 2010 BTEC and the large NIST 2009 Arabic-to-English translation tasks. Our results show that for both small and large training data, segmentation yields strong improvements, but, the differences between the top ranked segmenters are statistically insignificant. Due to the different methodologies that we apply for segmentation, we expect a complimentary variation in the results achieved by each method. As done in previous work, we combine several segmentation schemes of the same model but achieve modest improvements. Next, we try a different strategy, where we combine the different segmentation methods rather than the different segmentation schemes. In this case, we achieve stronger improvements over the best single system. Finally, combining schemes and methods has another slight gain over the best combination strategy.
Embedded System for Real-Time Digital Processing of Medical Ultrasound Doppler Signals

Ultrasound (US) Doppler systems are routinely used for the diagnosis of cardiovascular diseases. Depending on the application, either single tone bursts or more complex waveforms are periodically transmitted throughout a piezoelectric transducer towards the region of interest. Extraction of Doppler information from echoes backscattered from moving blood cells typically involves coherent demodulation and matched filtering of the received signal, followed by a suitable processing module. In this paper, we present an embedded Doppler US system which has been designed as open research platform, programmable according to a variety of strategies in both transmission and reception. By suitably sharing the processing tasks between a state-of-the-art FGPA and a DSP, the system can be used in several medical US applications. As reference examples, the detection of microemboli in cerebral circulation and the measurement of wall _distension_ in carotid arteries are finally presented.
Distribution Patterns of Picosized and Nanosized Phytoplankton Assemblages in the East China Sea and the Yellow Sea: Implications on the Impacts of Kuroshio Intrusion

Kuroshio, the strongest west boundary current of the Pacific Ocean, has significant impacts on the oceanographic conditions and ecological processes of the Pacific-Asian marginal seas through exchange of water, heat, and materials. In two cruises organized in the East China Sea (ECS) and the Yellow Sea in the spring 2014, observations of picosized and nanosized phytoplankton assemblages using flow cytometry reflected potential impacts of Kuroshio intrusion on phytoplankton communities, particularly in the ECS. The distribution pattern of Prochlorococcus in the ECS clearly depicts the intrusion route of Nearshore Kuroshio Branch Current from the main stream of Kuroshio northeast to Taiwan Island to the coastal waters adjacent to the Changjiang River estuary, an important red tide zone in the coastal waters of China. High abundance of photosynthetic nanoeukaryotes in the coastal waters adjacent to the Changjiang River estuary reflects the occurrence of diatom and dinoflagellate blooms during the investigation. The presence of Prochlorococcus in the coastal waters adjacent to the Changjiang River estuary offers a strong evidence that waters and materials associated with Nearshore Kuroshio Branch Current could be transported into the red tide zone adjacent to the Changjiang River estuary and will affect dynamics of harmful algal blooms in this region. Plain Language Summary Kuroshio is the strongest west Pacific boundary current. The oceanographic and ecological processes of Pacific Asian marginal seas are strongly affected by Kuroshio and its branches. During spring 2014, two cruises were conducted in the East China Sea and the Yellow Sea to find out how Kuroshio intrusion influence the environment and phytoplankton there. Four phytoplankton assemblages with different distribution patterns were detected by flow-cytometry. The assemblage with larger cell size (nanoeukaryotes) preferred to live in the coastal waters and reflected harmful algal blooms in the sea area adjacent to Changjiang River estuary. The abundance of the smallest photosynthetic organism Prochlorococcus was the highest where Kuroshio main stream flows by. The distribution pattern of Prochlorococcus in the East China Sea well depicted the route of a branch stretched from Kuroshio to the coastal waters adjacent to Changjiang River estuary (Nearshore Kuroshio Branch Current), and Prochlorococcus could be an indicator to reflect the influence Kuroshio intrusion has on phytoplankton. The results provide important aspect that open ocean could affect coastal ecological problems related to phytoplankton, such as harmful algal blooms.
Assessing the ecological and socioeconomic impacts of the lionfish invasion in the Wider Caribbean Region

Environmental changes of di erent scales and magnitudes are occurring at an alarming pace throughout the globe. As natural and human systems resist, cope, and/or adapt to global changes, new equilibrium states might be reached. To understand these changes we need to obtain information relevant to both biological and human systems and the interactions within and between them. My thesis combines approaches from ecology and socioeconomic to investigate the impacts of a specific stressor invasive Indo-Pacific lionfish on coral reef ecosystems. First, I explore how this invasion has changed trophic interactions and food web dynamics of coral reef fish communities. Second, I investigate how the impacts of an invasive predator can scale up to a ect and change socioeconomic systems associated with natural systems. I found that the trophic niche of lionfish has changed over time, concomitant with large changes in native fish prey abundance. I also found that lionfish predation is having impacts on energy flow through coral reef fish communities even in the absence of marked changes in fish community structure. Combined, these changes could a ect ecosystem function. I also present some of the first evidence of economic impacts of this invasion in regions that depend on reef-related tourism. I show that reductions in lionfish abundance through management actions should be beneficial to the reef tourism industry, and that tourist user fees are an acceptable means of financing such actions. As new management strategies are explored, the popularity of lionfish tournaments (derbies) has increased, premised on the idea that involving the public could help to tackle this invasion. However, my results show that such events are most likely to be successful only when lionfish densities are high and where there is a large pool of participants. This dissertation sheds light on the need to study and manage the impacts of biotic invasions from a multidisciplinary and integrated perspective since impacts will rarely be limited to the natural system a ected by invaders.
The Hamming metric in genetic algorithms and its application to two network problems

Lkng the Hamming metric to compute distances between chromosomes values as bits, we introduce two real-valued measures in genetic algorithms. These measurq gestetk drift and chtstering, give insight into the behavioral effects of mutation convergence and mating (using simple crossover) during generation cycles. The genetic driti and cltsstsring messttres will then be appfied to two cmtmton computes network problems: the optimaf placement of a multi-station access unit (Steiner Point variation problem) ad path loss (edge integrity of a graph). hstroduction and Definitions Genetic algorithms are a class of search algorithms baaed on the mechanics of naturtd biological selection [7]. A data structure is created which reprraertta en individual trial in the search space of all pssible feasible solutions. Each individual in the population has a fitness value which ia an evaluation of the worth of that individual as a solution. In one of our applications, we use chromosomes of bit strings for our population members to daermine phtce.men~ interconnectednesa, and the total length of connections in a multistation access uniL We reward poptdation members with the smaller total length of connectims by giving them a higher fitness vafue and select them for breeding more often. Offspring are created by applying (probabilistic) chromosomaf crossover to two members (parents) during a breeding (generation). Offspring from such a union may be further modficd by random mutations of bits. A common difficulty with genetic algorithms is fme tuning the algorithm to prevent premature convergence, that is, convergence to local minima or maxima without adequate exploration of the search apace. The art of fine tuning genetic algorithms in unique applications is explored m [3], while a fuller description of genetic algorithms CS! Sbe found in Goldberg’s book [7]. We assume that the genetic algorithm ppulatkn consists of individual chromasorsres (bitmaps} O = fak, 1 = true. We use the following parameters to tune our genetic algorithsrw Name * Popx size of the poptdatiorL number of chromosomes N uniform length of the chromosomes in the GA population HamDiat Hamrning distance betweest two chromosomes The Hamming dMsnce (HamDtat) between two individuala in such a population is the number of corresponding bit kations where they differ: HasuDi. 7t(P1, P2) = $ PI [k] xor Pa[k] where P][k] and P2[k] is the kth blt vafue of the first and second member (respectively) of the pair. Using the Hamrning metric, we define genetk drift as the avemge distance of all individuals in the currentgenerationfrom the beat (most fit) population member found to date, similar to that found in [4]. mHtunDfst(P,, 13est) Genetic Drift = Pepsi ze Clustering ia the average pair-wise dmtance of all individuals in the went generation.