Residential security through the Home Assistant Platform

The etymology of the word safety means: lack of danger; feeling of peace and confidence; shelter from any danger; feeling of security. A security system of goods, values and protection of people can be implemented through an automated platform, under the name of Home Assistant. This server software application can communicate with an easy control system for fast and two-way access, which can be mounted to a restricted main entrance. The automatic opening of the access door is controlled both by stand-alone RFID (Radio-Frequency Identification) modules, which act on an electric closing mechanism, and by an automation system configured in the Home Assistant application. The ultimate goal is the security of the premises through a system that can operate both locally and online via internet connection. The research methodology was based on the study of intelligent applications for residential access, described in the literature, aiming at integration into the open-source HA platform, by developing new code sequences. I come with this paper in support of those who want to bring an improvement in the existing automation system, respectively to encourage those who want an automated residence at a higher level.

Automated platform for consistent part realization with regenerative hybrid additive manufacturing workflow

Nowadays, the role of hybridization within the wider manufacturing ecosystem gains significant momentum with multiple commercial solutions already available on the market. Despite the very promising benefits of combining and selectively exploiting the advantages of additive and subtractive technologies on the same machine, hybrid additive manufacturing is far from reaching its full potential. One of the central limitations of existing hybrid process chains is the lack of a harmonized, structured and automated workflows to support an adaptive manufacturing strategy. This work is motivated by the need to bridge this gap and to capture the logic behind an adaptive hybrid process chain with the aim to support the achievement of enhanced product quality and improved operational efficiency in hybrid additive manufacturing. The paper discusses the implementation of a hybrid CAx platform and the underlying methodology aiming at the dynamic reduction of variabilities associated with the laser metal deposition process. The hybrid workflow identifies the most adapted sequence and planning of additive and subtractive operations while considering part inspection as an in-envelope functionality to quantify the geometrical and dimensional part deviations and to trigger the regenerative mechanism. The methodology is demonstrated on a hybrid machine by deploying laser ablation for the in situ removal of build deviations and an adapted deposition operation as part of a regenerative strategy leading to higher part confidence.

Reducing Cyber Incident Response to Protect CNI from Cyber Attacks using an N-SIEM Integration with an ICTI-CNI

The rapid evolution of technology has increased the role of cybersecurity and put it at the center of nationalcritical infrastructure. This role supports and guarantees the vital services of (CNI) while provides the proper functionalities for running operations between the public and private sectors. This evolution has hadthe same impact on cyberattack tools, methods, techniques used to gain unauthorized access to these computer systems that contain confidential and high-value information in the digital data sales market or asit called "darkweb". As a result, it has become necessary to monitor all events of the National Critical Infrastructure (CNI) computer systems. This proposed system uses a centralized National SIEM (N-SIEM) specializing in the correlation of security events caused by cyber attacks, collected by CNIs systems while integrating with anInternational Cyber Threat Intelligence system (ICTI-CNI). In addition, this conceptual model collects security breach events of CNIs systems, analyzes only cyber attacks, and correlates these security events in real-time with an intelligent automated platform while reducing the response time of security analysts.

Automated High-Throughput System Combining Small-Scale Synthesis with Bioassays and Reaction Screening

The Purdue Make It system is a unique automated platform capable of small-scale in situ synthesis, screening small-molecule reactions, and performing direct label-free bioassays. The platform is based on desorption electrospray ionization (DESI), an ambient ionization method that allows for minimal sample workup and is capable of accelerating reactions in secondary droplets, thus conferring unique advantages compared with other high-throughput screening technologies. By combining DESI with liquid handling robotics, the system achieves throughputs of more than 1 sample/s, handling up to 6144 samples in a single run. As little as 100 fmol/spot of analyte is required to perform both initial analysis by mass spectrometry (MS) and further MSn structural characterization. The data obtained are processed using custom software so that results are easily visualized as interactive heatmaps of reaction plates based on the peak intensities of m/ z values of interest. In this paper, we review the system’s capabilities as described in previous publications and demonstrate its utilization in two new high-throughput campaigns: (1) the screening of 188 unique combinatorial reactions (24 reaction types, 188 unique reaction mixtures) to determine reactivity trends and (2) label-free studies of the nicotinamide N-methyltransferase enzyme directly from the bioassay buffer. The system’s versatility holds promise for several future directions, including the collection of secondary droplets containing the products from successful reaction screening measurements, the development of machine learning algorithms using data collected from compound library screening, and the adaption of a variety of relevant bioassays to high-throughput MS.

CROPSR: An Automated Platform for Complex Genome-Wide CRISPR gRNA Design and Validation

Background: CRISPR/Cas9 technology has become an important tool to generate targeted, highly specific genome mutations. The technology has great potential for crop improvement, as crop genomes are tailored to optimize specific traits over generations of breeding. Many crops have highly complex and polyploid genomes, particularly those used for bioenergy or bioproducts. The majority of tools currently available for designing and evaluating gRNAs for CRISPR experiments were developed based on mammalian genomes that do not share the characteristics or design criteria for crop genomes. Results: We have developed the first open source tool for genome-wide design and evaluation of gRNA sequences for CRISPR experiments, CROPSR. The genome-wide approach provides a significant decrease in the time required to design a CRISPR experiment, including validation through PCR, at the expense of an overhead compute time required once per genome, at the first run. To better cater to the needs of crop geneticists, restrictions imposed by other packages on design and evaluation of gRNA sequences were lifted. A new machine learning model was developed to provide scores while avoiding situations in which the currently available tools sometimes failed to provide guides for repetitive, A/T-rich genomic regions. We show that our gRNA scoring model provides a significant increase in prediction accuracy over existing tools, even in non-crop genomes. Conclusions: CROPSR provides the scientific community with new methods and a new workflow for performing CRISPR/Cas9 knockout experiments. CROPSR reduces the challenges of working in crops, and helps speed gRNA sequence design, evaluation and validation. We hope that the new software will accelerate discovery and reduce the number of failed experiments.