An Energy-conscious Transport Protocol for Multi-hop Wireless Networks

We present a transport protocol whose goal is to reduce power consumption without compromising delivery requirements of applications. To meet its goal of energy efficiency, our transport protocol (1) contains mechanisms to balance end-to-end vs. local retransmissions; (2) minimizes acknowledgment traffic using receiver regulated rate-based flow control combined with selected acknowledgements and in-network caching of packets; and (3) aggressively seeks to avoid any congestion-based packet loss. Within a recently developed ultra low-power multi-hop wireless network system, extensive simulations and experimental results demonstrate that our transport protocol meets its goal of preserving the energy efficiency of the underlying network.Defense Advanced Research Projects Agency (NBCHC050053

A Two-step Statistical Approach for Inferring Network Traffic Demands (Revises Technical Report BUCS-2003-003)

Accurate knowledge of traffic demands in a communication network enables or enhances a variety of traffic engineering and network management tasks of paramount importance for operational networks. Directly measuring a complete set of these demands is prohibitively expensive because of the huge amounts of data that must be collected and the performance impact that such measurements would impose on the regular behavior of the network. As a consequence, we must rely on statistical techniques to produce estimates of actual traffic demands from partial information. The performance of such techniques is however limited due to their reliance on limited information and the high amount of computations they incur, which limits their convergence behavior. In this paper we study a two-step approach for inferring network traffic demands. First we elaborate and evaluate a modeling approach for generating good starting points to be fed to iterative statistical inference techniques. We call these starting points informed priors since they are obtained using actual network information such as packet traces and SNMP link counts. Second we provide a very fast variant of the EM algorithm which extends its computation range, increasing its accuracy and decreasing its dependence on the quality of the starting point. Finally, we evaluate and compare alternative mechanisms for generating starting points and the convergence characteristics of our EM algorithm against a recently proposed Weighted Least Squares approach.National Science Foundation (ANI-0095988, EIA-0202067, ITR ANI-0205294

Green Gateways: A concept for decisions in Circular-Oriented Economies

Industrial technologies have evolved towards circular-oriented manufacturing. New approaches in the management of production systems are needed to guarantee the success of such a circular approach. This paper identifies three research questions related to the complexities of decision-making within CEs and defines the concept of Green Gateways in the circular economy. A Green Gateway is a type of decision that supports to realizing the full potential of products and materials. Indeed, the potential value of products and materials must be assessed and leveraged and the concept of Green Gateway will be useful to identify common decisions and to define a common framework in the future. The integration of digital information and digital twins of products, processes, and circular value and supply chains emerges as a key factor in guiding decision-makers effectively, especially for Green Gateways where adequate information, tools and methods must be used to manage value retention options, product flows, production and pricing decisions jointly with the multiple objectives of profitability and sustainability. Additionally, this paper explores specific examples of circular economy use cases, drawing attention to their similarities and highlighting key insights

Common challenges for circular manufacturing industries in recycling

Over the past two decades, the concept of the circular economy has undergone significant development. Notably, research efforts have been centered on key elements essential for the shift towards circularity, specifically the Value Retention Options (ROs), aimed at optimizing resource retention throughout product life cycles. Given the diverse application fields, these ROs have been conceptualized in various ways. Recycling is considered one of the key ROs impacting the end-of-life of products to reduce landfills. An analysis is presented focusing on recycling activities to highlight key challenges encountered by manufacturing industries and their transition towards circularity. Examples of application fields involved are used to support the analysis. The considered research helps bridge the gap between research priorities and industrial requirements, as it highlights the shared challenges confronted by application fields engaged in the longest loops of a circular economy

Effects of heavy metals on seed protein fractions in chickpea, Cicer arietinum (L.)

Worldwide, different abiotic stresses, such as drought, salinity, and heavy metals, harm crop productivity. Legumes, compared to cereals, are more susceptible to these stresses. The current work aimed to provide more insights into the effects of Cd and Pb on various seed protein characteristics of two cultivars of chickpea (Cicer arietinum), HC1 and HC5. At the highest concentrations of Cd, the total seed proteins decreased from 25.2% (control) to 7.1% (30 mg/kg soil), while in the case of the maximum concentration of Pb, 300 mg/kg soil, the protein content decreased to 16.1% from 25.2%. The content of each of the four seed protein fractions viz. albumins, globulins, glutelins and prolamins decreased with an increase in the concentration levels of both heavy metals. The dominating protein fraction, globulins, was reduced by 21.7% in HC1 under Cd stress, while it was reduced by 11.9% in Pb-treated genotype HC5. Electrophoretic analysis of four seed protein fractions on SDS-gels showed only quantitative changes in the polypeptide patterns under varying concentrations of Pb with few qualitative alterations under Cd treatment. The contents of the amino acids tryptophan, cysteine and methionine also decreased with increasing concentrations of heavy metals. Compared to Pb, Cd was found to be more detrimental concerning its influence on seed protein quality. Thus, our analysis revealed how heavy metals impact the quality of chickpea seed proteins by decreasing the content of essential amino acids

Deep Learning Frameworks for Cardiovascular Arrhythmia Classification

Arrhythmia classification is a prominent research problem due to the computational complexities of learning the morphology of various ECG patterns and its wide prevalence in the medical field, particularly during the COVID-19 pandemic. In this article, we used Empirical Mode Decomposition and Discrete Wavelet Transform for preprocessing and then the modified signal is classified using various classifiers such as Decision Tree, Logistic Regression, Gaussian Naïve Bayes, Random Forest, Linear  SVM, Polynomial SVM, RBF SVM, Sigmoid SVM and Convolutional Neural Networks. The proposed method classify the data into five classes N (Normal), S (Supraventricular premature) beat, (V) Premature ventricular contraction, F (Fusion of ventricular and normal), and Q, (Unclassifiable Beat) using softmax regressor at the end of the network. The proposed approach performs well in terms of classification accuracy when tested using ECG signals acquired from the MIT-BIH database. In comparison to existing classifiers, the Accuracy, Precision, Recall, and F1 score values of the proposed technique are 98.5%, 96.9%, 94.3%, and 91.32%, respectively.  &nbsp

Obtenção de camu-camu em pó com elevado teor de compostos bioativos.

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