Comtech Telecommunications (United States)

Precision medicine demands a shift from static, single-analyte diagnostics toward dynamic, systems-level understanding of health and disease. This review explores how the convergence of systems biology, multiomics, and artificial intelligence (AI) redefines biomarker discovery to drive early disease detection and personalized intervention. We highlight pioneering efforts that use longitudinal, multimodal data to map individual health trajectories and uncover early disease signals. Advances in AI, including machine learning and contextualization using knowledge graphs and digital twins, are accelerating clinical translation by enabling predictive, context-aware analyses. Real-world applications, including omics-informed diagnostics and digital health monitoring, demonstrate the potential of this approach to transform health care from reactive treatment to proactive wellness. These technologies also inform the development of targeted therapeutics that intervene earlier, personalize treatment, and potentially halt or reverse disease progression. We outline challenges, emerging solutions, and future directions that position AI-driven systems biology at the center of next-generation precision health.

An all-fiber high-power erbium-doped fiber laser (EDFL) source generating optical pulses from 200 µs to 5 ms with a stable rectangular envelope for fractional photo-rejuvenation is proposed and experimentally demonstrated. A master oscillator power amplifier (MOPA) configuration composed of a master oscillator, an acousto-optic modulator (AOM), and a one-stage amplifier is designed and employed in the EDFL to serve as an efficient laser system with excellent output performance. To avoid multistage amplifiers, the master oscillator generates 1.5 W, and a Yb-free Er-doped large-mode-area (LMA) active fiber is used for a one-stage power amplifier. There are two benefits to this approach: first, modulation of both pump and seed pulses is used to achieve clear rectangular shaped pulses without amplified spontaneous emission (ASE) growth; and second, there are no power limitations in the amplifier and undesirable 1 µm ASE compared to Er/Yb systems. We have reached 28.6 W of peak power with 26% slope efficiency limited only by available pump power, so the system can be easily scaled for achieving a higher peak power.

Conducting transmission path analysis using unit modes with simple mode shapes, the vibration mechanism, which is generally difficult to grasp, can be clarified. This paper explains how to extract multiple unit modes in order of importance. In addition, an application example to a vehicle FE model is introduced, in which road noise is reduced by shifting the eigenvalues of unit modes and thereby changing the vibration path.

IntroductionCoronavirus disease 2019 (COVID‐19) is characterized by a high contagiousness requiring isolation measures. At this time, diagnosis is based on the positivity of specific RT‐PCR and/or chest computed tomography scan, which are time‐consuming and may delay diagnosis. Complete blood count (CBC) can potentially contribute to the diagnosis of COVID‐19. We studied whether the analysis of cellular population data (CPD), provided as part of CBC‐Diff analysis by the DxH 800 analyzers (Beckman Coulter), can help to identify SARS‐CoV‐2 infection.MethodsCellular population data of the different leukocyte subpopulations were analyzed in 137 controls, 322 patients with proven COVID‐19 (COVID+), and 285 patients for whom investigations were negative for SARS‐CoV‐2 infection (COVID−). When CPD of COVID+ were different from controls and COVID− patients, we used receiver operating characteristic analysis to test the discriminating capacity of the individual parameters. Using a random forest classifier, we developed the algorithm based on the combination of 4 monocyte CPD to discriminate COVID+ from COVID− patients. This algorithm was tested prospectively in a series of 222 patients referred to the emergency unit.ResultsAmong the 222 patients, 86 were diagnosed as COVID‐19 and 60.5% were correctly identified using the discriminating protocol. Among the 136 COVID− patients, 10.3% were misclassified (specificity 89.7%, sensitivity 60.5%). False negatives were observed mainly in patients with a low inflammatory state whereas false positives were mainly seen in patients with sepsis.ConclusionConsideration of CPD could constitute a first step and potentially aid in the early diagnosis of COVID‐19.

Cyber security is a topic on every organisation's radar. It was only very recently that we heard about the catastrophic Dixons Carphone data breach, which involved 5.9 million card payments and the personal data records of 1.9 million people. 1 And who can forget the infamous TalkTalk hack from 2015, in which the personal details of 157,000 customers were compromised? 2 As a result of this breach, the company was hit with a record £400,000 fine. One persistent cyber security myth is that cyber attacks only ever involve attackers exploiting system vulnerabilities and stealing personal data. In fact, telecoms systems are equally susceptible to coming under attack. And as telephony is the beating heart of any business, it is essential that all businesses employ secure encryption as a part of their telecoms set-up. And there are three elements to this – awareness, education and action, argues Nick Claxson of Comtec.

This article describes the Information Process Maturity Model, which was modeled after the software industry's Capability Maturity Model, to guide managers of information-development groups in assessing and improving the work of their organizations. The model describes five levels of maturity: ad-hoc, rudimentary, organized and repeatable, managed and sustainable, and optimizing. The model currently explores ten characteristics of organizations to determine their level: organizational structure, quality assurance, planning, estimating and scheduling, hiring and training, information design, cost control, quality management, change management, and collaboration. The article looks forward to how the model is evolving in response to changes in technology and practice. The model is managed and updated by The Center for Information Development Management, CIDM, an organization for managers of information development.

Genetic interactions illuminate the functional organization and underlying mechanisms of biological systems, and often complement the biochemical analysis of signaling and metabolic networks. With the recent advent of efficient targeted gene disruption and control via CRISPR-Cas9 technologies, and high throughput genetic interaction screens in model systems and human cells, comes the need to precisely and consistently classify information about large numbers of genetic interactions in a variety of organisms. Due to historical reasons, existing nomenclature for genetic interactions is diverse, unsystematic, and at times ambiguous. An interoperable framework that can be implemented across biological databases is needed in order to enable reliable cross-species and cross-database comparisons of genetic interaction data. Here we propose the Genetic Interactions Structured Terminology (GIST), a systematic, flexible and modular method for naming and cataloging all forms of genetic interaction data. The GIST is designed for facile adoption by authors and biological curators alike to establish a common standard for annotation, interpretation and dissemination of genetic interaction data. Critically, the GIST separates structured descriptors of genetic interactions from phenotype, and when possible the GIST has been aligned with previous nomenclature conventions. The GIST system was developed by members of the WormBase and BioGRID databases and is supported by a number of biological databases including the Human Proteome Organization Proteomics Standards Initiative - Molecular Interactions working group (HUPO PSI-MI), Saccharomyces Genetics Database (SGD), Candida Genome Database (CGD), PomBase, FlyBase, the Zebrafish Model Organism Database (ZFIN), and The Arabidopsis Information Resource (TAIR). The widespread implementation of the GIST will enable researchers and biocurators to record and unambiguously describe genetic interactions from diverse sources, and thereby unify the investigations of the genetic basis for all phenotypes of living organisms.

Abstract Not Provided

Instrumentation is essentially information conveyance. It is important to understand the underlying principles of instrumentation so that the control system can optimize the application of existing technology and employ new technology as it becomes commercially available. This chapter begins by discussing the common characteristics and electrical design considerations, and talks about the three types of sensor or transmitter output signals used in most control systems. The next two sections deal with the measurement and transmission of pressure and temperature. Another section discusses the flow measurement devices commonly encountered in aeration systems. Most of the analytic instruments are complex—involving multiple parameters and sophisticated algorithms for determining the process variable. Heat is the principal enemy of electric motors. Motor monitoring is principally concerned with detecting excessive temperature in the motor or preventing damage by detecting high currents from overloads that will cause excess temperature.

There are several control platforms available for implementing the aeration control system. Computer control, distributed control systems (DCSs), and programmable logic controllers (PLCs) have all been used successfully. The PLC was originally developed to meet the requirements of the discrete component manufacturing processes associated with the automotive industry. It is important to determine the options in PLC selection while evaluating system cost during the design process. The DCS is generally optimized for process control and PID algorithms. There are two broad categories of human machine interfaces (HMIs) used in most aeration control systems. One is the local control panel interface communicating with a single PLC and displaying data for a single piece of equipment or a small group of process equipment. The other HMI category is the supervisory control and data acquisition (SCADA) system. Some of the common control panel design considerations are discussed in this chapter.