Miracle-dz/UniFAR-FTUs huggingface dataset:
Systems Responses to Progressive Water Stress in Durum Wheat

Durum wheat is susceptible to terminal drought which can greatly decrease grain yield. Breeding to improve crop yield is hampered by inadequate knowledge of how the physiological and metabolic changes caused by drought are related to gene expression. To gain better insight into mechanisms defining resistance to water stress we studied the physiological and transcriptome responses of three durum breeding lines varying for yield stability under drought. Parents of a mapping population (Lahn x Cham1) and a recombinant inbred line (RIL2219) showed lowered flag leaf relative water content, water potential and photosynthesis when subjected to controlled water stress time transient experiments over a six-day period. RIL2219 lost less water and showed constitutively higher stomatal conductance, photosynthesis, transpiration, abscisic acid content and enhanced osmotic adjustment at equivalent leaf water compared to parents, thus defining a physiological strategy for high yield stability under water stress. Parallel analysis of the flag leaf transcriptome under stress uncovered global trends of early changes in regulatory pathways, reconfiguration of primary and secondary metabolism and lowered expression of transcripts in photosynthesis in all three lines. Differences in the number of genes, magnitude and profile of their expression response were also established amongst the lines with a high number belonging to regulatory pathways. In addition, we documented a large number of genes showing constitutive differences in leaf transcript expression between the genotypes at control non-stress conditions. Principal Coordinates Analysis uncovered a high level of structure in the transcriptome response to water stress in each wheat line suggesting genome-wide co-ordination of transcription. Utilising a systems-based approach of analysing the integrated wheat’s response to water stress, in terms of biological robustness theory, the findings suggest that each durum line transcriptome responded to water stress in a genome-specific manner which contributes to an overall different strategy of resistance to water stress.
Application of the electromagnetic borehole flowmeter

This report describes the operation and application of the TVA prototype EM borehole flowmeters, including theory, design, calibration, basic field applications, data analysis, and potential effects of various well construction and development procedures on data. The majority of these results are also applicable to the commercial version of this meter and other vertical component borehole flowmeters, including heat pulse and impeller tools. Several case studies illustrating specific uses of these tools are also discussed.
Java bytecode specification and verification

We propose a framework for establishing the correctness of untrusted Java bytecode components w.r. t. to complex functional and/or security policies. To this end, we define a bytecode specification language (BCSL) and a weakest precondition calculus for sequential Java bytecode. BCSL and the calculus are expressive enough for verifying non-trivial properties of programs, and cover most of sequential Java bytecode, including exceptions, subroutines, references, object creation and method calls. Our approach does not require that bytecode components are provided with their source code. Nevertheless, we provide a means to compile JML annotations into BCSL annotations by defining a compiler from the Java Modeling Language (JML) to BCSL. Our compiler can be used in combination with most Java compilers to produce extended class files from JML-annotated Java source programs. All components, including the verification condition generator and the compiler are implemented and integrated in the Java Applet Correctness Kit (JACK).
Accurate person recognition on combining signature and fingerprint

This paper is addressing the combination of physiological and behavioral biometrics. In this we adopted multimodal approach on combining signature and fingerprint biometrics using feature level fusion with different normalization techniques to improve the performance of multimodal system. Texture features are extracted for fingerprint, pen pressure, azimuth, and altitude features are extracted for signature. Thus, classification is done using K-NN and SVM classifiers; from experimental results of two classifiers shows that multimodal approach performs well by adopting robust feature normalization technique with suitable distance measures and kernels of classifiers
Real-Time Speech Separation & Intelligibility Enhancement on a Field Programmable Gate Array Platform

In this paper, we present a real-time implementation of the ideal binary-mask algorithm, which is a promising approach for enhancing speech intelligibility. Our implementation is hardware efficient, making it suitable for embedded biomedical devices such as hearing aids and cochlear implants. We tested our algorithm implementation on an FPGA platform, and produced results that verify that it effectively performs speech enhancement in real time.
Uncertain Decision Making with Dempster-Shafer Theory

We develop a new approach for decision making with Dempster-Shafer theory of evidence by using uncertain information represented in the form of interval numbers. We suggest the use of different types of uncertain aggregation operators in the problem. Then, we obtain new aggregation operators such as the belief structure - uncertain ordered weighted averaging (BSUOWA) operator and the BS uncertain hybrid averaging (BS-UHA) operator, among others. Some of their main properties are studied such as the distinction between descending and ascending orders and the analysis of different particular cases.
Ghosts of bump attractors in stochastic neural fields: Bottlenecks and extinction

We study the effects of additive noise on stationary bump solutions to spatially extended neural fields near a saddle-node bifurcation. The integral terms of these evolution equations have a weight kernel describing synaptic interactions between neurons at different locations of the network. Excited regions of the neural field correspond to parts of the domain whose fraction of active neurons exceeds a sharp threshold of a firing rate nonlinearity. For sufficiently low firing threshold, a stable bump coexists with an unstable bump and a homogeneous quiescent state. As the threshold is increased, the stable and unstable branch of bump solutions annihilate in a saddle node bifurcation. Near this criticality, we derive a quadratic amplitude equation that describes the slow evolution of the even mode (bump contractions) as it depends on the distance from the bifurcation. Beyond the bifurcation, bumps eventually become extinct, and the time it takes for this to occur increases for systems nearer the bifurcation. When noise is incorporated, a stochastic amplitude equation for the even mode can be derived, which can be analyzed to reveal bump extinction time both below and above the saddle-node.
An Interval-Valued Fuzzy Analytical Hierarchy Process Approach and Its Application

Project evaluation and selection is a complex multi-attribute decision-making problem. With the information uncertainty and inaccuracy considered, a new model for project evaluation and selection is proposed, which combines the fuzzy analytic hierarchy process (AHP) and technique for order performance by similarity to ideal solution (TOPSIS). The hybrid method is based on interval-valued triangular fuzzy numbers. An index system for selecting the optimal project is established. The weights of criteria and sub-criteria are derived by fuzzy AHP. The relative closeness is drawn from the calculation of the distance between the alternatives and positive ideal solutions or negative ones. Also, the ranking of alternatives can be based on their relative closeness. Finally, a case study is given adopting the proposed method.
Fast Linear Model Predictive Control Via Custom Integrated Circuit Architecture

This paper addresses the implementation of linear model predictive control (MPC) at millisecond range, or faster, sampling rates. This is achieved by designing a custom integrated circuit architecture that is specifically targeted to the MPC problem. As opposed to the more usual approach using a generic serial architecture processor, the design here is implemented using a field-programmable gate array and employs parallelism, pipelining, and specialized numerical formats. The performance of this approach is profiled via the control of a 14th-order resonant structure with 12 sample prediction horizon at 200-μs sampling rate. The results indicate that no more than 30 μs are required to compute the control action. A feasibility study indicates that the design can also be implemented in 130 nm CMOS technology, with a core area of 2.5 mm2. These results illustrate the feasibility of MPC for reasonably complex systems, using relatively cheap, small, and low-power computing hardware.
Antecedents of trust in the sharing economy : A systematic review

Users and potential users of the sharing economy need to place a considerable amount of trust in both the person and the platform with which they are dealing. The consequences of transaction partners’ opportunism may be severe, for example damage to goods or endangered personal safety. Trust is, therefore, a key factor in overcoming uncertainty and mitigating risk. However, there is no thorough overview of how trust is developed in this context. To understand how the trust of users in the sharing economy is influenced, we performed a systematic literature review. After screening, 45 articles were included in a qualitative synthesis in which the results were grouped according to a well-established trust typology. The results show various antecedents of trust in the sharing economy (e.g. reputation, trust in the platform, and interaction experience) related to multiple entities (i.e. seller, buyer, platform, interpersonal, and transaction). Trust in this economy is often reduced to the use of reputation systems alone. However, our study suggests that trust is much more complex than that and extends beyond reputation. Furthermore, our review clearly shows that research on trust in the sharing economy is still scarce and thus more research is needed to understand how trust is established in this context. Our review is the first that brings together antecedents of trust in online peer-to-peer transactions and integrates these findings within an existing framework. Additionally, the study suggests directions for future research in order to advance the understanding of trust in the sharing economy.
EFFECTS OF PAHS ON MICROBIAL ACTIVITY AND DIVERSITY IN FRESHLY CONTAMINATED AND WEATHERED SOILS

Polycyclic aromatic hydrocarbon (PAH)-contaminated soils are of concern to the Environmental Protection Agency (EPA) due to their mutagenic and carcinogenic nature. Bioremediation of PAHs is aimed at increasing the overall rate of natural degradation. Microbial bioremediation promotes processes by which microorganisms can take up and/or degrade organic molecules and their metabolites. Microorganisms can use organic molecules for energy or convert them into cell biomass, ultimately releasing carbon dioxide and water to the environment. Changes in microbial biomass and CO2 evolved are used as indices of degradation rates. In situ bioremediation utilizes indigenous microorganisms and/or involves addition of specific microorganisms with enzymatic capabilities (such as enhanced oxidative functions) to establish conditions favorable to microbial degradative activities. The overall goal of this study was to assess the biodegradation of the target PAHs, pyrene and phenanthrene, in rhizosphere soils. Comparisons of microbial diversity and activities due to PAH contamination between a weathered loam and a clean sandy loam were made. Carbon substrate utilization was the estimate of microbial functional diversity used in this study. Functional diversity was evaluated using the Biologfi assay system. Results from the study show significant differences in substrate utilization and microbial diversity between the two soil types and various treatments.
Gesture based imitation learning for Human Robot Interaction

This paper describes a gesture based recognition system using Indian Sign Language (ISL) for performing Human Robot Interaction (HRI) in real time. It permits us to construct a convenient gesture based communication with humanoid robot HOAP-2. The classification process is carried out by extracting the features from ISL gestures. Orientation Histogram is considered as a feature vector for classification process. It is to be done by the two statistical approaches namely known as Hidden Markov Model (HMM) technique and Bhattacharyya Distance estimation in order to achieve satisfactory recognition accuracy. The major task involves by computing the recognition time taken by both the above methods and finally the suitable one participates for HRI applications. The classification result has been tested on the Webots simulation platform on Humanoid robot (HOAP2) to generate mimicry according to the recognized
Characterizing Responses of Translation-Invariant Neurons to Natural Stimuli: Maximally Informative Invariant Dimensions

The human visual system is capable of recognizing complex objects even when their appearances change drastically under various viewing conditions. Especially in the higher cortical areas, the sensory neurons reflect such functional capacity in their selectivity for complex visual features and invariance to certain object transformations, such as image translation. Due to the strong nonlinearities necessary to achieve both the selectivity and invariance, characterizing and predicting the response patterns of these neurons represents a formidable computational challenge. A related problem is that such neurons are poorly driven by randomized inputs, such as white noise, and respond strongly only to stimuli with complex high-order correlations, such as natural stimuli. Here we describe a novel two-step optimization technique that can characterize both the shape selectivity and the range and coarseness of position invariance from neural responses to natural stimuli. One step in the optimization is finding the template as the maximally informative dimension given the estimated spatial location where the response could have been triggered within each image. The estimates of the locations that triggered the response are updated in the next step. Under the assumption of a monotonic relationship between the firing rate and stimulus projections on the template at a given position, the most likely location is the one that has the largest projection on the estimate of the template. The algorithm shows quick convergence during optimization, and the estimation results are reliable even in the regime of small signal-to-noise ratios. When we apply the algorithm to responses of complex cells in the primary visual cortex (V1) to natural movies, we find that responses of the majority of cells were significantly better described by translation-invariant models based on one template compared with position-specific models with several relevant features.
Notions of Refinement for a Coordination Language for Gamma

Gamma has shown to be a powerful and expressive formalism that allows the basic computation of an algorithm to be expressed with a minimum of control. In a second stage of the design process, the highly nondeterministic behaviour of Gamma can be exploited to impose additional control using a separate coordination language. Separating computation from coordination facilitates correctness proofs of the computation component, because operational details need not be taken into account. In this respect it is important that the coordination component does not invalidate the established correctness of the program. In this paper we propose several notions of re nement that allow the coordination component of a Gamma program to be constructed through a correctness preserving derivation process. We show that the notions can be combined into a hybrid proof method that can be used to reason about di erent properties of the coordination component. A short version of this report appears as [6]
Reducing Fragmentation in Incremental Author Name Disambiguation

Author name ambiguity is a hard problem that occurs when several authors publish articles with the same name or when a same author publishes their articles under different names. Traditionally, automatic disambiguation methods process the author names of all citation records in a repository. Aiming efficiency, incremental methods disambiguate author names only when new citation records are inserted into the repository. As a side effect, several citation records of a same author may be associated with different authors, aka, the fragmentation problem. To diminish this problem, we propose a new merge-oriented incremental method capable of reducing such side effect, without the need to apply a traditional disambiguation method on the whole repository. Our experimental evaluation shows that our method produces significant improvements when compared to an incremental baseline and is very competitive with batch-mode methods.
Microvascular Complications in Adolescents with Type 1 Diabetes Mellitus

Objective: Screening of complications is an important part of diabetes care. The aim of this study was to investigate diabetic complications and related risk factors in adolescents with type 1 diabetes mellitus (T1DM). Methods: This cross-sectional study was conducted on type 1 diabetics who were over 11 years of age or had a diabetes duration of 2 years and included 155 adolescents with T1DM (67 male, 88 female). The mean age of the patients was 14.4±2.1 years. Mean diabetes duration was 6.3±2.9 years. The patients were screened for diabetic nephropathy, retinopathy and peripheral neuropathy. Results: Mean glycosylated hemoglobin (HbA1c) level of the study group was 8.4%. The frequency of microalbuminuria and peripheral neuropathy were 16.1% and 0.6%, respectively. None of the patients had diabetic retinopathy. Dyslipidemia and hypertension rates were 30.3% and 12.3%, respectively. Risk factors associated with microalbuminuria were hypertension, higher HbA1c levels, longer diabetes duration and dyslipidemia. Conclusion: Early diagnosis and treatment of hypertension and dyslipidemia as well as achieving a better metabolic control are important in prevention or postponement of complications in patients with T1DM. Yearly screening for diabetic nephropathy should be started 2 years after the onset of the diabetes. Conflict of interest:None declared.
Empirical Features of Congested Traffic States and Their Implications for Traffic Modeling

We address the controversial issue of traffic flow modeling, whether first-order, second-order, or other traffic models are best supported by empirical facts and theoretical considerations. This is done by a critical discussion of the pros and cons of the different theoretical approaches and by the analysis of a large set of empirical data with new evaluation techniques. Specifically, we investigate characteristic properties of the congested traffic states on a 30-km-long stretch of the German freeway A5 near Frankfurt/Main. Among the approximately 245 breakdowns of traffic flow at several different bottlenecks in 165 days, we have identified five different kinds of spatiotemporal congestion patterns and their combinations. Based on an “adaptive smoothing method” for the visualization of detector data, we also discuss particular features of breakdowns, such as signs of unstable traffic flow and the “boomerang effect,” which often seems to be caused by overtaking maneuvers of trucks. Controversial issues such as “synchronized flow” or stop-and-go waves are addressed as well. Our empirical results are compared with the implications of different theoretical concepts such as first-order traffic models and the phase diagram of congested traffic states predicted by some second-order models and the nonlocal, gas-kinetic based traffic model (GKT model). For a correct understanding of empirical observations such as the “general pattern,” it is important to consider particularities such as the fact that off-ramps can act as bottlenecks, when activated by downstream on-ramp bottlenecks. As sequences of off-and on-ramps generate different congestion patterns than single on-ramps, they must be treated as interconnected bottlenecks. Furthermore, our empirical results question Kerner's three-phase theory.
Introducing tangerine: a tangible interactive natural environment

In this paper we describe TANGerINE, a tangible tabletop environment in which users can interact with digital contents manipulating tangible smart objects. Such objects provide continuous data about their status through the embedded wireless sensors, while an overhead computer vision module tracks their position and orientation. Merging sensing data, the system is able to detect a richer language of gestures and manipulations both on the tabletop and in its surroundings, enabling for a more expressive interaction language across different contexts.
POSTER: Performance Management in Application-controlled Software Deﬁned Networks

—Software Deﬁned Networking (SDN) is an emerging new paradigm that allows for an application-driven control of network resources. Traditional network management systems (NMS) can beneﬁt from an application-controlled SDN approach, which promises to drastically reduce OPEX by translating application requirements into network behavior without human intervention. However, delivering predictable performance for applications remains a challenge as it requires such systems to maintain and forecast the resource utilization and performance of the underlying network. Therefore, this paper proposes a new application-controlled NMS approach for SDN, considering the resource and performance characteristics of the underlying network. The goal is to model the network utilization and to forecast the usage proﬁles of applications to prevent resource shortages before they occur. The proposed concept focusses on OpenFlow due to its generic approach, well deﬁned resource requirements, and prevalence in scientiﬁc research.