Miracle-dz/UniFAR-FTUs huggingface dataset:
Power/Energy Estimator for Designing WSN Nodes with Ambient Energy Harvesting Feature

Wireless Sensor Networks (WSNs) consist of spatially distributed autonomous sensors to cooperatively monitor physical conditions. Thus, the node battery autonomy is critical. To outperform it, most WSNs rely on the harvesting capability. As nodes can recharge whenever energy is available, the problem is to determine at design time the node autonomy. For our project, we solve it by creating a power/energy estimator that simulates business scenarios to predict node autonomy; the estimation concerns both power and energy features. Based on node architecture configuration, its Dynamic Power Management (DPM) policy, and environmental conditions, we present a simulator that helps identify power consumption hot spots and make critical choices during the system design. It also helps to scale the energy storage system as well as the energy harvesters correctly. The hardware part is modelled using the FLPA methodology to develop different node component models with a variable accuracy. For the logical part, we developped a specific DPM by integrating meteorology and weather forecast behaviours. The novelty comes from the ability to simulate the WSN harvesting capability and to estimate at runtime the remaining duration of each service.
Measuring Poverty Dynamics and Inequality in Transition Economies: Disentangling Real Events from Noisy Data

The author uses instrumental variable methods, and the decomposition of income into transitory and persistent components to distinguish underlying income inequality and changes in poverty from the effects attributable to measurement error or transitory shocks. He applies this methodology to household-level panel data for Russia and Poland in the mid-1990s. The author finds that: 1) Accounting for noise in the data reduces inequality (as measured by the Gini coefficient) by 10-45 percent. 2) Individuals in both countries face much economic insecurity. The median absolute annual change in income or spending is about fifty percent in Russia, and about 20 percent in Poland. But roughly half of these fluctuations reflect measurement error or transitory shocks, so underlying levels of income, and spending are much more stable than the data suggest. 3) The apparent high levels of economic mobility are driven largely by transitory events and noisy data. After transitory shocks are accounted for, about eighty percent of the poor in both Russia and Poland remain in poverty for at least one year. So there is a real risk of an entrenched underclass emerging in these transition economies.
Webcrawling Using Sketches

The current breed of WWW search engines are systems which use agents to find and download text based information from the distributed multimedia database known as the World Wide Web. These search engines are well developed with respect to text, but typically ignore image and video content. In this paper we discuss a system which uses agents to search distributed multimedia databases over the world wide web. Operational goals of the system include the following: accessibility by anyone with a World Wide Web connection; low Response time; and usable by non-artists. Toward these ends, we developed the ImageScape system (http://ind134a.wi.leidenuniv.nl:2001) which includes MPEG based methods for compressing large image databases, optimal agents for analysis and downloading based on utility of the site information, and information theoretic techniques for sketch and representative image icon matching.
Hopfield Network as Associative Memory with Multiple Reference Points

Hopfield model of associative memory is studied in this work. In particular, two main problems that it possesses: the apparition of spurious patterns in the learning phase, implying the well-known effect of storing the opposite pattern, and the problem of its reduced capacity, meaning that it is not possible to store a great amount of patterns without increasing the error probability in the retrieving phase. In this paper, a method to avoid spurious patterns is presented and studied, and an explanation of the previously mentioned effect is given. Another technique to increase the capacity of a network is proposed here, based on the idea of using several reference points when storing patterns. It is studied in depth, and an explicit formula for the capacity of the network with this technique is provided.
A CONTROLLED STUDY OF ADENOVIRAL-VECTOR–MEDIATED GENE TRANSFER IN THE NASAL EPITHELIUM OF PATIENTS WITH CYSTIC FIBROSIS

D. , . D. , . D. , Abstract Background. Cystic ﬁbrosis is a monogen- ic disease that deranges multiple systems of ion transport in the airways, culminating in chronic infection and destruction of the lung. The introduction of a normal copy of the cystic ﬁbrosis transmembrane conduct- ance regulator ( CFTR ) gene into the airway epithelium through gene transfer is an attractive approach to cor- recting the underlying defects in patients with cystic ﬁbrosis. We tested the feasibility of gene therapy using adenoviral vectors in the nasal epithelium of such patients. Methods. An adenoviral vector containing the normal CFTR complementary DNA in four logarithmically in- creasing doses (estimated multiplicity of infection, 1, 10, 100, and 1000), or vehicle alone, was administered in a randomized, blinded fashion to the nasal epithelium of 12 patients with cystic ﬁbrosis. Gene transfer was quantitat- ed by molecular techniques that detected the expression of CFTR messenger RNA and by
Success and Failure of Adaptation-Diffusion Algorithms With Decaying Step Size in Multiagent Networks

This paper investigates the problem of distributed stochastic approximation in multiagent systems. The algorithm under study consists of two steps: A local stochastic approximation step and a diffusion step, which drives the network to a consensus. The diffusion step uses row-stochastic matrices to weight the network exchanges. As opposed to previous works, exchange matrices are not supposed to be doubly stochastic, and may also depend on the past estimate. We prove that nondoubly stochastic matrices generally influence the limit points of the algorithm. Nevertheless, the limit points are not affected by the choice of the matrices provided that the latter are doubly stochastic in expectation. This conclusion legitimates the use of broadcast-like diffusion protocols, which are easier to implement. Next, by means of a central limit theorem, we prove that doubly stochastic protocols perform asymptotically as well as centralized algorithms and we quantify the degradation caused by the use of nondoubly stochastic matrices. Throughout this paper, a special emphasis is put on the special case of distributed nonconvex optimization as an illustration of our results.
Spatiotemporal Dynamics of Microcystin Variants and Relationships with Environmental Parameters in Lake Taihu, China

Excessive anthropogenically-caused nutrient loading from both external and internal sources has promoted the growth of cyanobacteria in Lake Taihu from 2005 to 2014, suggesting increased production and release of cyanotoxins. In order to explain the spatial distribution and temporal variation of microcystins (MCs), the intracellular concentrations of MCs (MC-LR, -RR and -YR, L, R and Y are abbreviations of leucine, arginine and tyrosine) were monitored monthly from July 2013 to June 2014. Three MC variants are present simultaneously in Lake Taihu; the MC-LR and -RR variants were dominant (accounting for 40% and 39% of the total), followed by MC-YR (21%). However, MC-YR accounted for a higher proportion in colder months, especially in March. The highest concentrations of intracellular MCs were found in July and October when cyanobacteria cell density also reached the maximum. The average concentrations of MC-LR, -RR and -YR in July were 4.69, 4.23 and 2.01 μg/L, respectively. In terms of the entire lake, toxin concentrations in northern parts were significantly higher than the eastern part in summer, when MC concentrations were several times higher than the guideline value by WHO throughout much of Lake Taihu. Results from correlation and redundancy analysis (RDA) showed that total MCs, including all variants, were strongly and positively correlated with cyanobacteria cell density, water temperature, total phosphorus (TP) and pH, whereas each variant had different correlation coefficients with each of the considered environmental variables. MC-RR showed a stronger relationship with temperature, in contrast to MC-YR and -LR. Dissolved inorganic carbon (DIC) showed a negative relationship with each variant, suggesting that rising DIC concentrations may inhibit cyanobacterial growth and thereby reduce MC production in the future.
Leading the Blind: Guidance of Neuronal and Vascular Growth

Summary Accurate neuronal and vascular growth during development is critical for an organism’s function and survival. Neurons, however, would not grow into a spinal cord, nor would endothelial cells form vascular tissue, if not for molecular guidance signals. These cells are blind to the fate of their growth. Two decades ago, my lab, with numerous collaborators, began the process of elucidating multiple chemotropic proteins expressed in mouse models of the developing nervous system. Their presence selectively attracts and repels axons to guide their growth. These chemotropic factors play dual roles depending on the receptor to which they bind and the interactions between these receptors. In tracking the unique growth pathway of commissural axons, we characterized the activity of five receptor-ligand complexes. We showed neuron attraction was mediated by DCC-Netrin and Rig-1-Slit complexes, and repulsion was mediated by Unc5-Netrin, Robo-Slit, and NeuropilinSemaphorin complexes. Additionally, we learned that classical morphogens, such as Wnt and Shh, also function as chemoattractants. Most recently, we have found that several of these chemotropic factors, such as Netrin and Semaphorin, play parallel roles in guiding vascular growth. My current research aims to expose the extent of this parallel and apply this knowledge to design therapies promoting neural regeneration after injury, as well as inhibiting tumor angiogenesis.
Caterpillar saliva interferes with induced Arabidopsis thaliana defence responses via the systemic acquired resistance pathway

Arabidopsis thaliana (L.) Heynh. genotypes limited in their ability to mount either octadecanoid-dependent induced resistance (IR–) or systemic acquired resistance (SAR–) were used to characterize the roles of these pathways in plant–herbivore interactions. Molecular and biochemical markers of IR were analysed in plants subject to herbivory by caterpillars of the beet armyworm, Spodoptera exigua Hübner, which had either intact or impaired salivary secretions since salivary enzymes, such as glucose oxidase, have been implicated in the ability of caterpillars to circumvent induced plant defences. Transcript expression of genes encoding laccase-like multicopper oxidase [AtLMCO4 (polyphenol oxidase)] and defensin (AtPDF1.2) showed salivary-specific patterns which were disrupted in the SAR– mutant plants. The activity of octadecanoid-associated anti-nutritive proteins, such as LMCO and trypsin inhibitor, showed similar patterns. Gene and protein changes parallel plant hormone levels where elevated jasmonic acid was observed in wild-type plants fed upon by caterpillars with impaired salivary secretions compared with plants subject to herbivory by normal caterpillars. This salivary-specific difference in jasmonic acid levels was alleviated in SAR– mutants. These results support the model that caterpillar saliva interferes with jasmonate-dependent plant defences by activating the SAR pathway.
GeoMob: A mobility-aware geocast scheme in metropolitans via taxicabs and buses

Geocast, delivering messages to a specific location, has become an important issue with the accelerated development of the location-based services in mobile networks. Geocast in the automotive domain is of particular interest, enabling many promising applications, such as geographic advertising, location-based traffic alerts, etc. Different from the conventional geocast algorithms focusing on the distance-based approaches, in this paper, we propose a mobility-aware geocast algorithm (GeoMob) for urban VANETs from the Delay-Tolerant Network (DTN) perspective to better deal with the high mobility and transient connectivity issues. Different levels and aspects of vehicle mobility information are employed, making GeoMob very simple, scalable and communication and compunction-effective. Practical issues are well considered by introducing real-world trace analysis, trace-driven simulation and efficient buffer management. Extensive performance comparisons with other protocols have been conducted to show the advantages of GeoMob.
Multi-Obstacle Avoidance Based on the Method of Fuzzy-Function for Mobile Robot

This paper presented a method of collision avoidance based on the fuzzy-function focus on the complex environment existing multi-obstacle for mobile robot. It constructs the curve of fuzzy-function by defining the function of degree of risk, and changes the problem of two-dimension into one-dimension for collision avoidance. The experiment of simulation verified its validity
Test Case Prioritization Using Extended Digraphs

Although many test case prioritization techniques exist, their performance is far from perfect. Hence, we propose a new fault-based test case prioritization technique to promote fault-revealing test cases in model-based testing (MBT) procedures. We seek to improve the fault detection rate—a measure of how fast a test suite is able to detect faults during testing—in scenarios such as regression testing. We propose an extended digraph model as the basis of this new technique. The model is realized using a novel reinforcement-learning (RL)- and hidden-Markov-model (HMM)-based technique which is able to prioritize test cases for regression testing objectives. We present a method to initialize and train an HMM based upon RL concepts applied to an application's digraph model. The model prioritizes test cases based upon forward probabilities, a new test case prioritization approach. In addition, we also propose an alternative approach to prioritizing test cases according to the amount of change they cause in applications. To evaluate the effectiveness of the proposed techniques, we perform experiments on graphical user interface (GUI)-based applications and compare the results with state-of-the-art test case prioritization approaches. The experimental results show that the proposed technique is able to detect faults early within test runs.
CHRNA7 Deletions are Enriched in Risperidone-Treated Children and Adolescents.

OBJECTIVE Aggression is among the most common indications for referral to child and adolescent mental health services and is often challenging to treat. Understanding the biological underpinnings of aggression could help optimize treatment efficacy. Neuronal nicotinic acetylcholine receptors (nAChRs), specifically the α7 nAChR, encoded by the gene CHRNA7, have been implicated in aggressive behaviors in animal models as well as humans. Copy number variants (CNVs) of CHRNA7 are found in individuals with neuropsychiatric disorders, often with comorbid aggression. In this study, we aimed to determine the prevalence of CHRNA7 CNVs among individuals treated with risperidone, predominantly for irritability and aggression. METHODS Risperidone-treated children and adolescents were assessed for CHRNA7 copy number state using droplet digital PCR and genomic quantitative PCR. Demographic, anthropometric, and clinical data, including the Child Behavior Checklist (CBCL), were collected and compared across individuals with and without the CHRNA7 deletion. RESULTS Of 218 individuals (90% males, mean age: 12.3 ± 2.3 years), 7 (3.2%) were found to carry a CHRNA7 deletion and one proband carried a CHRNA7 duplication (0.46%). T-scores for rule breaking, aggression, and externalizing behavior factors of the CBCL were higher in the deletion group, despite taking 58% higher dose of risperidone. CONCLUSIONS CHRNA7 loss may contribute to a phenotype of severe aggression. Given the high prevalence of the deletion among risperidone-treated youth, future studies should examine the therapeutic potential of α7 nAChR-targeting drugs to target aggression associated with CHRNA7 deletions.
Autonomous navigation of mobile robot based on DGPS/INS sensor fusion by EKF in semi-outdoor structured environment

Although GPS/DGPS become the dominant localization solution in the outdoor environment, it needs assistant sensors or algorithms for the covering the area not to get the position information from GPS. Especially, in the robot navigation, the sensor fusion algorithm is needed. In addition, it is hard to get the position information at the area surrounded the high buildings such as the downtown because GPS signals is so feeble. Therefore, this paper illustrates an efficient method for the outdoor localization incorporating DGPS, Encoder, and IMU sensor based on EKF. To show the localization performances of the proposed fusion algorithm, we have implemented the proposed algorithm and applied the advertising robot platform which is operating well during 80 days in the real semi-outdoor structured environment. The proposed sensor fusion algorithm and the experimental results showed the feasibility of our novel sensor fusion algorithm.
Optimal Control of Water Level Using Time-Delay system

This paper presents an optimal control problem using time-delay system based on the optimal control theory. The time-delay system includes two types of control, ordinary and delayed controls. On the problem of drainage basin, ordinary control denotes the control on which the water drains out into the drainage basin, and delayed control denotes the control on which the water returns to the river. Each control values are expressed as the same function form. In this paper, optimal control of water level is considered using a model of Tsurumi river. As the spatial discretization, the Galerkin method is applied. The bubble function element is used to the interpolation function. The Crank-Nicolson method is applied to the temporal discretization. As the minimization technique of the performance function, the Sakawa-Shindo method is utilized.
Ubiquitous Sensor Network System

A ubiquitous sensor network is a means for realizing the collection and utilization of real-time information any time and anywhere. Features include easy implementation and maintenance, as well as ample flexibility. In this paper, we introduce the elemental technologies of sensor network systems, as well as provide examples of solutions for the "facility status monitoring system," "quality control and instrumentation systems for the manufacturing and inspection processes," "temperature and humidity monitoring systems for warehouses," as well as "building management system".
Rapidity Gap Events for Squark Pair Production at the LHC

The exchange of electroweak gauginos in the $t-$ or $u-$channel allows squark pair production at hadron colliders without color exchange between the squarks. This can give rise to events where little or no energy is deposited in the detector between the squark decay products. We discuss the potential for detection of such rapidity gap events at the Large Hadron Collider (LHC). We present an analysis with full event simulation using PYTHIA as well as Herwig++, but without detector simulation. We analyze the transverse energy deposited between the jets from squark decay, as well as the probability of finding a third jet in between the two hardest jets. For the mSUGRA benchmark point SPS1a we find statistically significant evidence for a color singlet exchange contribution.
Cancer incidence among Finnish ferrochromium and stainless steel production workers in 1967–2011: a cohort study

Objectives The aim of the study was to assess the risk of cancer among workers employed in the Finnish ferrochromium and stainless steel industry since the beginning of production in 1967. Methods The study cohort was made up of all persons employed by the Finnish stainless steel production chain from chromite mining to cold rolling of stainless steel during the period 1967–2004, and it was divided into subcohorts by production units with specific exposure patterns of the subcohorts assessed in previous studies. Follow-up for cancer through the files of the Finnish Cancer Registry was performed using the personal identity code as key. Standardised incidence ratios (SIRs) were calculated as the ratios of observed numbers of cancer cases and numbers expected on the basis of incidence rates in the population of the same region. Results The overall cancer incidence was at the expected level. The lung cancer risk was decreased in the whole cohort (SIR 0.79; 95% CI 0.65 to 1.08). The incidence of prostate cancer was significantly increased (1.31; 1.05 to 1.61) and that for kidney cancer was significantly decreased (0.38; 0.14 to 0.82). None of the department-specific SIRs for lung cancer were significantly different from 1.0. No cancers of the nose and nasal sinuses were observed among workers in the ferrochromium smelter or the stainless steel melting shop. Conclusions It is not likely that the occupational exposures in the Finnish ferrochromium and stainless steel industry would have increased the risk of cancer.
Synchronous Dependency Insertion Grammars: A Grammar Formalism for Syntax Based Statistical MT

This paper introduces a grammar formalism specifically designed for syntax-based statistical machine translation. The synchronous grammar formalism we propose in this paper takes into consideration the pervasive structure divergence between languages, which many other synchronous grammars are unable to model. A Depend-ency Insertion Grammars (DIG) is a generative grammar formalism that captures word order phenomena within the dependency representation. Synchronous Depend-ency Insertion Grammars (SDIG) is the synchronous version of DIG which aims at capturing structural divergences across the languages. While both DIG and SDIG have comparatively simpler mathematical forms, we prove that DIG nevertheless has a generation capacity weakly equivalent to that of CFG. By making a comparison to TAG and Synchronous TAG, we show how such formalisms are linguistically motivated. We then introduce a probabilistic extension of SDIG. We finally evaluated our current implementation of a simplified version of SDIG for syntax based statistical machine translation.
The first Steps towards Assamese Named Entity Recognition

Named Entity Recognition (NER) is the process of identifying and classifying proper nouns in text documents into pre-defined classes such as person, location and organization. Although NER in Indian languages is a di cult and challenging task and su↵ers from scarcity of resources, such work has started to appear recently. In this paper we present an overview of NER, the di↵erent approaches to NER and its existing work in Indian language. Finally we describe the Assamese language and the issues faced by this language in NER and the rules of Assamese NER.