Consistency,availability, and partition tolerance in blockchain: a survey on the consensus mechanism over peer-to-peer networking

Annals of Telecommunications - Blockchain is a disruptive technology that relies on the distributed nature of the peer-to-peer network while performing an agreement, or consensus, a mechanism to...     

Development of low-alcohol isotonic beer by interrupted fermentation

Alcohol-free beer with isotonic properties is getting more popular and its production can be carried out by different production strategies; however, interrupted fermentation is still a challenge. Therefore, the objective of this study was to develop a low-alcohol isotonic beer (<0.5% v/v) by interrupted fermentation. Moreover, the major objective is to compare the developed product to commercial beverages (sports drinks, ‘Pilsen' regular beer, alcohol-free beers and low-alcohol isotonic beer). The beverages were evaluated based on pH, alcohol content (% v/v), total titratable acidity (mEq L⁻¹), osmolality (mOsmol kg⁻¹), bitterness International Bitterness Units, colour European Brewery Convention, total phenolic compounds (mg L⁻¹ gallic acid), reducing and total sugars (%) and Na and K contents (mg L⁻¹). The developed low-alcohol isotonic beer presented characteristics similar to sports drinks, with the advantage of being richer in phenolic compounds and suitable osmolality. Despite salts were added in its formulation, the grades attributed to all beers employed in the sensory evaluation, as well as the purchase intention did not present significant differences.     

Securing light clients in blockchain with DLCP

In blockchain, full nodes (FNs) are peers that store and verify entire chains of transactions. In contrast, light clients (LCs) are those with limited resources, and for this reason, they request only block headers from FNs for transaction verification—using protocols like Simple Payment Verification (SPV). In an approach to prevent FN tampering on transaction verification (byzantine fault), LCs request block headers from multiple FNs and compare received responses. One problem with this approach is that an LC must connect to each FN and perform the same cryptographic operations with each one repeatedly, which leads to client‐side complexity and slower response. We propose an alternate approach to tackle this issue, in which LCs can encrypt a request for block headers only once, and send that request to a predetermined set of FNs to access, process, and reply back in a single response. Our approach, called Distributed Lightweight Client Protocol (DLCP), enables LCs to verify with little effort if FNs have agreed on a response. From an experimental evaluation, we observed that DLCP provided lower latency and reduced computing and communication overhead in comparison with the existing conventional approach.     

Porous Silicon Nanoneedles Modulate Endocytosis to Deliver Biological Payloads

Owing to their ability to efficiently deliver biological cargo and sense the intracellular milieu, vertical arrays of high aspect ratio nanostructures, known as nanoneedles, are being developed as minimally invasive tools for cell manipulation. However, little is known of the mechanisms of cargo transfer across the cell membrane‐nanoneedle interface. In particular, the contributions of membrane piercing, modulation of membrane permeability and endocytosis to cargo transfer remain largely unexplored. Here, combining state‐of‐the‐art electron and scanning ion conductance microscopy with molecular biology techniques, it is shown that porous silicon nanoneedle arrays concurrently stimulate independent endocytic pathways which contribute to enhanced biomolecule delivery into human mesenchymal stem cells. Electron microscopy of the cell membrane at nanoneedle sites shows an intact lipid bilayer, accompanied by an accumulation of clathrin‐coated pits and caveolae. Nanoneedles enhance the internalization of biomolecular markers of endocytosis, highlighting the concurrent activation of caveolae‐ and clathrin‐mediated endocytosis, alongside macropinocytosis. These events contribute to the nanoneedle‐mediated delivery (nanoinjection) of nucleic acids into human stem cells, which distribute across the cytosol and the endolysosomal system. This data extends the understanding of how nanoneedles modulate biological processes to mediate interaction with the intracellular space, providing indications for the rational design of improved cell‐manipulation technologies.     

A platform for P2P agent-based collaborative applications

The operational environment can be a valuable source of information about the behavior of software applications and their usage context. Although a single instance of an application has limited evidence of the range of the possible behaviors and situations that might be experienced in the field, the collective knowledge composed by the evidence gathered by the many instances of a same application running in several diverse user environments (eg, a browser) might be an invaluable source of information. This information can be exploited by applications able to autonomously analyze how they behave in the field and adjust their behavior accordingly. Augmenting applications with the capability to collaborate and directly share information about their behavior is challenging because it requires the definition of a fully decentralized and dependable networked infrastructure whose nodes are the user machines. The nodes of the infrastructure must be collaborative, to share information, and autonomous, to exploit the available information to change their behavior, for instance, to better accommodate the needs of the users to prevent known problems. This paper describes the initial results that we obtained with the design and the development of an infrastructure that can enable the execution of collaborative scenarios in a fully decentralized way. Our idea is to combine the agent-based paradigm, which is well suited to design collaborative and autonomous nodes, and the peer-to-peer paradigm, which is well suited to design distributed and dynamic network infrastructures. To demonstrate our idea, we augmented the popular JADE agent-based platform with a software layer that supports both the creation of a fully decentralized peer-to-peer network of JADE platforms and the execution of services within that network, thus enabling JADE multiagent systems (MASs) to behave as peer-to-peer networks. The resulting platform can be used to study the design of collaborative applications running in the field.     

Bulk nanocrystalline aluminum 5083 alloy fabricated by a novel technique: Cryomilling and spark plasma sintering

Dense, bulk nanocrystalline aluminum 5083 alloy was fabricatedvia a combined technique: cryomilling (mechanical milling at cryogenic temperature) to achieve the nanocrystalline Al 5083 powder and spark plasma sintering (SPS) to consolidate the cryomilled powder. The results of X-ray diffraction analysis indicate that the average grain size in the SPS consolidated material is 51 nm, one of the smallest grain sizes ever reported in bulk Al alloys produced by powder metallurgy derived methods. In contrast, transmission electron microscopy (TEM) analysis revealed a bimodal grain size distribution, with an average grain size of 47 nm in the fine-grained regions and approximately 300 nm in the coarse-grained regions. Nanoindentation was used to evaluate the mechanical properties and the uniformity of the consolidated nanocrystalline Al 5083. The hardness of the material is greatly improved over that of the conventional equivalent, due to the fine grain size. The mechanisms for spark plasma sintering and the microstructural evolution are discussed on the basis of the experimental findings.     

Tumor-Stroma Ratio and Programmed Cell Death Ligand 1 Expression in Preoperative Biopsy and Matched Laryngeal Carcinoma Surgical Specimen

Programmed cell death ligand 1 (PD-L1) seems to rely on close relations between neoplastic and immune cells in the tumor microenvironment. Tumor to stroma ratio (TSR) has been associated with prognosis in different malignancies. The aims of this exploratory investigation were to analyze for the first time the: (i) association between TSR, PD-L1 expression and other clinical–pathological features in laryngeal squamous cell carcinoma (LSCC) biopsies and paired surgical specimens; (ii) prognostic and predictive role of TSR and PD-L1. TSR, PD-L1 expression (in terms of combined positive score [CPS]), and other clinical–pathological features were analyzed in biopsies and surgical specimens of 43 consecutive LSCC cases. A CPS < 1 evaluated on surgical specimens was associated with a low TSR (stroma rich) on both biopsies and surgical specimens (p = 0.0143 and p = 0.0063). Low TSR showed a significant negative prognostic value when evaluated on both biopsies and surgical specimens (HR = 8.808, p = 0.0003 and HR = 11.207, p = 0.0002). CPS ≥ 1 appeared to be a favorable prognostic factor (HR = 0.100, p = 0.0265). The association between bioptic and surgical specimen TSR and PD-L1 expression should be further investigated for a potential impact on targeted treatments, also with regard to immunotherapeutic protocols.     

DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis

Emerging deep learning-based applications in precision medicine include computational histopathological analysis. However, there is a lack of the required training image datasets to generate classification and detection models. This phenomenon occurs mainly due to human factors that make it difficult to obtain well-annotated data. The present study provides a curated public collection of histopathological images (DeepHP) and a convolutional neural network model for diagnosing gastritis. Images from gastric biopsy histopathological exams were used to investigate the performance of the proposed model in detecting gastric mucosa with Helicobacter pylori infection. The DeepHP database comprises 394,926 histopathological images, of which 111 K were labeled as Helicobacter pylori positive and 283 K were Helicobacter pylori negative. We investigated the classification performance of three Convolutional Neural Network architectures. The models were tested and validated with two distinct image sets of 15% (59K patches) chosen randomly. The VGG16 architecture showed the best results with an Area Under the Curve of 0.998%. The results showed that CNN could be used to classify histopathological images from gastric mucosa with marked precision. Our model evidenced high potential and application in the computational pathology field.