Multiple IoT based Network Attacks Discrimination by Multilayer Feedforward Neural Networks

In this paper a new neural model for detection of multiple network IoT-based attacks, such as DDoS TCP, UDP, and HHTP flood, is presented. It consists of feedforward multilayer network with back propagation. A general algorithm for its optimization during training is proposed, leading to proper number of neurons in the hidden layers. The Scaled Gradient Descent algorithm and the Adam optimization are studied with better classification results, obtained by the developed classifiers, using the latter. Tangent hyperbolic function appears to be proper selection for the hidden neurons. Two sets of features, gathered from aggregated records of the network traffic, are tested, containing 8 and 10 components. While more accurate results are obtained for the 10-feature set, the 8-feature set offers twice lower training time and seems applicable for real-world applications. The detection rate for 7 of 10 different network attacks, primarily various types of floods, is higher than 90% and for 3 of them – mainly reconnaissance and keylogging activities with low intensity of the generated traffic, deviates between 57% and 68%. The classifier is considered applicable for industrial implementation.

A New Approach for a Safe and Reproducible Seeds Positioning for Diffusing Alpha-Emitters Radiation Therapy of Squamous Cell Skin Cancer: A Feasibility Study

The purpose of this study is to discuss how to use an external radio-opaque template in the Diffusing Alpha-emitters Radiation Therapy (DaRT) technique’s pre-planning and treatment stages. This device would help to determine the proper number of sources for tumour coverage, accounting for subcutaneous invasion and augmenting DaRT safety. The procedure will be carried out in a first phase on a phantom and then applied to a clinical case. A typical DaRT procedure workflow comprises steps like tumour measurements and delineation, source number assessment, and therapy administration. As a first step, an adhesive fiberglass mesh (spaced by 2 mm) tape was applied on the skin of the patient and employed as frame of reference. A physician contoured the lesion and marked the entrance points for the needles with a radio opaque ink marker. According to the radio opaque marks and metabolic uptake the clinical target volume was defined, and with a commercial brachytherapy treatment planning system (TPS) it was possible to simulate and adjust the spatial seeds distribution. After the implant procedure a CT was again performed to check the agreement between simulations and seeds positions. With the procedure described above it was possible to simulate a DaRT procedure on a phantom in order to train physicians and subsequently apply the novel approach on patients, outlining the major issues involved in the technique. The present work innovates and supports DaRT technique for the treatment of cutaneous cancers, improving its efficacy and safety.

Control of G2 phase duration by CDC25B modulates the switch from direct to indirect neurogenesis in the neocortex

During development, cortical neurons are produced in a temporally regulated sequence from apical progenitors, directly, or indirectly through the production of intermediate basal progenitors. The balance between these major progenitors types is determinant for the production of the proper number and types of neurons and it is thus important to decipher the cellular and molecular cues controlling this equilibrium. Here we address the role of a cell cycle regulator, the CDC25B phosphatase, in this process. We show that deleting CDC25B in apical progenitors leads to a transient increase of the production of TBR1+ neurons at the expense of TBR2+ basal progenitors in mouse neocortex. This phenotype is associated with lengthening of the G2 phase of the cell cycle, the total cell cycle length being unaffected. Using in utero electroporation and cortical slice cultures, we demonstrate that the defect in TBR2+ basal progenitor production requires interaction with CDK1 and is due to the G2 phase lengthening in CDC25B mutants. Altogether, this study identifies a new role for CDC25B and the length of the G2 phase in direct versus indirect neurogenesis at early stages of the cortical development.

Direct Fabrication of Micron-Thickness PVA-CNT Patterned Films by Integrating Micro-Pen Writing of PVA Films and Drop-on-Demand Printing of CNT Micropatterns

The direct fabrication of micron-thickness patterned electronics consisting of patterned PVA films and CNT micropatterns still faces considerable challenges. Here, we demonstrated the integrated fabrication of PVA films of micron-thickness and CNT-based patterns by utilising micro-pen writing and drop-on-demand printing in sequence. Patterned PVA films of 1–5 μm in thickness were written first using proper micro-pen writing parameters, including the writing gap, the substrate moving velocity, and the working pressure. Then, CNT droplets were printed on PVA films that were cured at 55–65 °C for 3–15 min, resulting in neat CNT patterns. In addition, an inertia-pseudopartial wetting spreading model was established to release the dynamics of the droplet spreading process over thin viscoelastic films. Uniform and dense CNT lines with a porosity of 2.2% were printed on PVA substrates that were preprocessed at 55 °C for 9 min using a staggered overwriting method with the proper number of layers. Finally, we demonstrated the feasibility of this hybrid printing method by printing a patterned PVA-CNT film and a micro-ribbon. This study provides a valid method for directly fabricating micron-thickness PVA-CNT electronics. The proposed method can also provide guidance on the direct writing of other high-molecular polymer materials and printing inks of other nanosuspensions.

Meiotic Crossover Patterning

Proper number and placement of meiotic crossovers is vital to chromosome segregation, with failures in normal crossover distribution often resulting in aneuploidy and infertility. Meiotic crossovers are formed via homologous repair of programmed double-strand breaks (DSBs). Although DSBs occur throughout the genome, crossover placement is intricately patterned, as observed first in early genetic studies by Muller and Sturtevant. Three types of patterning events have been identified. Interference, first described by Sturtevant in 1915, is a phenomenon in which crossovers on the same chromosome do not occur near one another. Assurance, initially identified by Owen in 1949, describes the phenomenon in which a minimum of one crossover is formed per chromosome pair. Suppression, first observed by Beadle in 1932, dictates that crossovers do not occur in regions surrounding the centromere and telomeres. The mechanisms behind crossover patterning remain largely unknown, and key players appear to act at all scales, from the DNA level to inter-chromosome interactions. There is also considerable overlap between the known players that drive each patterning phenomenon. In this review we discuss the history of studies of crossover patterning, developments in methods used in the field, and our current understanding of the interplay between patterning phenomena.

ANALYSIS OF MIXED DATA TO SELECT BANANAS CLONES (Musa SPP.) TO BE INCLUDED IN A GERMPLASM BANK

In an asexually reproducing hybrid such as banana (Musa spp.), the assessment of clones in the short term is limited because replications are frequently unavailable in the proper number. The aim of this work is to propose the Multiple Factor Analysis of Mixed Data (MFAmix) as a tool for establishing objective criteria to identify banana clones that preserve variability for qualitative and quantitative variables. In the long term, the aim is the development of a banana germplasm bank. MFAmix was applied on a population composed of 124 banana clones collected from different farmers’ fields and four controls. Two groups of variables related to the agronomic aptitude of the clones were evaluated, one composed of nine quantitative variables, and the other, composed of three dichotomous qualitative variables. A Selection Index (SI) was built from the MFAmix coordinates in order to rank the clones and select a subset that allows to preserve the existing genetic variability. The first two axes of MFAmix explained a 49.47% of the total data variability. The set of the banana clones was successfully characterized based on quantitative and qualitative variables. In the long term, the creation of a banana germplasm bank should consider the height and diameter of the plant, the rachis bunch weight and the hands weight, and the qualitative variable plant leafiness. Key words: asexual hybrid, collection of germplasm, multivariate analysis, Musaceae.

ANALYSIS OF MIXED DATA TO SELECT BANANAS CLONES (Musa SPP.) TO BE INCLUDED IN A GERMPLASM BANK

In an asexually reproducing hybrid such as banana (Musa spp.), the assessment of clones in the short term is limited because replications are frequently unavailable in the proper number. The aim of this work is to propose the Multiple Factor Analysis of Mixed Data (MFAmix) as a tool for establishing objective criteria to identify banana clones that preserve variability for qualitative and quantitative variables. In the long term, the aim is the development of a banana germplasm bank. MFAmix was applied on a population composed of 124 banana clones collected from different farmers’ fields and four controls. Two groups of variables related to the agronomic aptitude of the clones were evaluated, one composed of nine quantitative variables, and the other, composed of three dichotomous qualitative variables. A Selection Index (SI) was built from the MFAmix coordinates in order to rank the clones and select a subset that allows to preserve the existing genetic variability. The first two axes of MFAmix explained a 49.47% of the total data variability. The set of the banana clones was successfully characterized based on quantitative and qualitative variables. In the long term, the creation of a banana germplasm bank should consider the height and diameter of the plant, the rachis bunch weight and the hands weight, and the qualitative variable plant leafiness. Key words: asexual hybrid, collection of germplasm, multivariate analysis, Musaceae.

Molecular Perspectives of Mitophagy in Myocardial Stress: Pathophysiology and Therapeutic Targets

A variety of complex risk factors and pathological mechanisms contribute to myocardial stress, which ultimately promotes the development of cardiovascular diseases, including acute cardiac insufficiency, myocardial ischemia, myocardial infarction, high-glycemic myocardial injury, and acute alcoholic cardiotoxicity. Myocardial stress is characterized by abnormal metabolism, excessive reactive oxygen species production, an insufficient energy supply, endoplasmic reticulum stress, mitochondrial damage, and apoptosis. Mitochondria, the main organelles contributing to the energy supply of cardiomyocytes, are key determinants of cell survival and death. Mitophagy is important for cardiomyocyte function and metabolism because it removes damaged and aged mitochondria in a timely manner, thereby maintaining the proper number of normal mitochondria. In this review, we first introduce the general characteristics and regulatory mechanisms of mitophagy. We then describe the three classic mitophagy regulatory pathways and their involvement in myocardial stress. Finally, we discuss the two completely opposite effects of mitophagy on the fate of cardiomyocytes. Our summary of the molecular pathways underlying mitophagy in myocardial stress may provide therapeutic targets for myocardial protection interventions.

A Simple WiFi Harvester with a Switching-Based Power Management Scheme to Collect Energy from Ordinary Routers

This paper shows the design process of a simplified harvesting circuit for WiFi at the 2.4 GHz frequency band based on the analysis of the environment available signals. Those signals and their power level define an antenna design to maximize captured energy and select the proper number of stages for a voltage multiplier so that an impedance matching network is no longer required. With this, it is possible to maintain the harvester architecture simple without sacrificing performance. The use of supercapacitors is preferred over batteries due to their high-power capacity, the ability to deliver high peak currents, long-life cycle size, and low cost. Hence, supercapacitor availability allows to devise a novel switching scheme that employs two units that favor energy use and speed up the recharging process. The built harvester exhibits a power conversion efficiency greater than 50% under an incident signal of 0 dBm in the rectenna. The tests are carried out in an academic environment using a multi SSID router, collecting 494 mJ without requiring special modifications in the router used as an energy source.

An ANN Model for Predicting the Compressive Strength of Concrete

An artificial neural network (ANN) model for predicting the compressive strength of concrete is established in this study. The Back Propagation (BP) network with one hidden layer is chosen as the structure of the ANN. The database of real concrete mix proportioning listed in earlier research by another author is used for training and testing the ANN. The proper number of neurons in the hidden layer is determined by checking the features of over-fitting while the synaptic weights and the thresholds are finalized by checking the features of over-training. After that, we use experimental data from other papers to verify and validate our ANN model. The final result of the synaptic weights and the thresholds in the ANN are all listed. Therefore, with them, and using the formulae expressed in this article, anyone can predict the compressive strength of concrete according to the mix proportioning on his/her own.