Precision Era Research Articles

Refining radiative decay studies in singly heavy baryons

In this work, we systematically study the radiative decays of singly heavy baryons, a crucial aspect of their spectroscopic behavior. To enhance the accuracy of our calculations, we utilize numerical spatial wave functions for the singly heavy baryons obtained through the Gaussian expansion method, which also yields their mass spectrum. As hadron spectroscopy enters an era of high precision, we believe our study of the radiative decays of singly heavy baryons will provide valuable insights for further exploration of these particles. Published by the American Physical Society 2024

Artificial intelligence in dental imaging: A new era of precision and predictive diagnosis

Artificial intelligence in dental imaging: A new era of precision and predictive diagnosis

Fast and accurate algorithm for calculating long-baseline neutrino oscillation probabilities with matter effects

Neutrino oscillation experiments will be entering the precision era in the next decade with the advent of high statistics experiments like DUNE, HK, and JUNO. Correctly estimating the confidence intervals from data for the oscillation parameters requires very large Monte Carlo datasets involving calculating the oscillation probabilities in matter many, many times. In this paper, we leverage past work to present a new, fast, precise technique for calculating neutrino oscillation probabilities in matter optimized for long-baseline neutrino oscillations in the Earth’s crust including both accelerator and reactor experiments. For ease of use by theorists and experimentalists, we provide fast ++ and codes . Published by the American Physical Society 2024

Diagnosis and management of multiple primary lung cancer.

Multiple primary lung cancer (MPLC), can be categorized as synchronous multiple primary lung cancer (sMPLC) and metachronous multiple primary lung cancer (mMPLC), which are becoming increasingly common in clinical practice. A precise differential diagnosis between MPLC and intrapulmonary metastases (IPM) is essential for determining the appropriate management strategy. MPLC is primarily diagnosed through histology, imaging, and molecular methods. Imaging serves as an essential foundation for preoperative diagnosis, while histology is a critical tool for establishing a definitive diagnosis. As molecular biology advances, the diagnosis of MPLC has stepped into the era of molecular precision. Surgery is the preferred treatment approach, with stereotactic radiotherapy and ablation being viable options for unresectable lesions. Targeted therapy and immunotherapy can be considered for specific patients. A multidisciplinary team approach to evaluation and the application of combination therapy can benefit more patients. Looking ahead, the development of more authoritative guidelines will be instrumental in streamlining the diagnosis and management of MPLC.

Advent of machine learning in autonomous vehicles

The advent of Machine Learning has significantly transformed the landscape of automation, heralding a new era of efficiency, precision, and innovation. This literature review explores the pivotal role of machine learning in advancing automation across various industries. By examining the evolution of machine learning algorithms and their integration into automated systems, the paper highlights key developments and breakthroughs that have enabled machines to perform complex tasks with minimal human intervention. The review delves into case studies from manufacturing, healthcare, finance, and driver-less vehicles, illustrating how machine learning-driven automation has improved productivity, enhanced decision-making, and reduced operational costs. Furthermore, the paper discusses the challenges and ethical considerations associated with the widespread adoption of machine learning in automation, such as data privacy, job displacement, and algorithmic bias. By synthesizing findings from recent research, this review provides a thorough study of the current state and future potential of machine learning in automation. The insights gained underscore the huge impact of machine learning technologies, along with the need for continuous innovation and regulation to harness their full potential while mitigating associated risks. This paper serves as a valuable resource for academics, industry professionals, and policymakers aiming to navigate and contribute to the rapidly evolving field of machine learning in automation.

The emerging role of minimally invasive extracorporeal circulation in totally endoscopic and robotic-assisted cardiac surgery procedures.

Background: This review explores the potential benefits of combining totally endoscopic and robotic-assisted cardiac surgery with minimally invasive extracorporeal circulation (MiECC). Robotic techniques herald a new era of surgical precision, leveraging advanced instrumentation and enhanced visualization to navigate cardiac anatomy with unprecedented accuracy. Purpose: Concurrently, MiECC systems provide tailored physiological support during cardiopulmonary bypass, meticulously managing perfusion parameters to safeguard vital organs' function. Results: The convergence of these cutting-edge technologies marks a paradigmatic shift in cardiac surgical practice, with potential mitigation of invasiveness, attenuation of perioperative complications, and expedite postoperative recovery. Conclusions: This review also addresses prevailing challenges and limitations, including technological complexities and procedural intricacies, while elucidating the strategic imperatives for optimizing their collaborative utilization.

Unleashing the power of EFT in neutrino-nucleus scattering

Neutrino physics is advancing into a precision era with the construction of new experiments, particularly in the few GeV energy range. Within this energy range, neutrinos exhibit diverse interactions with nucleons and nuclei. This study delves in particular into neutrino-nucleus quasi-elastic cross sections, taking into account both standard and, for the first time, non-standard interactions, all within the framework of effective field theory (EFT). The main uncertainties in these cross sections stem from uncertainties in the nucleon-level form factors, and from the approximations necessary to solve the nuclear many-body problem. We explore how these uncertainties influence the potential of neutrino experiments to probe new physics introduced by left-handed, right-handed, scalar, pseudoscalar, and tensor interactions. For some of these interactions the cross section is enhanced, making long-baseline experiments an excellent place to search for them. Our results, including tabulated cross sections for all interaction types and all neutrino flavors, can serve as the foundation for such searches.

Transforming Agriculture with Drones: Applications, Challenges and Implementation Strategies

The integration of drone technology, or Unmanned Aerial Vehicles (UAVs), has revolutionized the agricultural sector, offering a new era of precision and efficiency. This paper examines the diverse applications of drones in agriculture, including crop health assessment, precision crop spraying, soil analysis, irrigation management, and livestock monitoring. Equipped with advanced sensors and cameras, drones provide real-time data collection and analysis, enabling farmers to make informed decisions, optimize resource use, and swiftly respond to environmental changes. This technological advancement enhances productivity, conserves resources, and promotes sustainable farming practices. However, the adoption of drones in agriculture faces challenges such as high costs, regulatory uncertainties, and the need for specialized skills, along with concerns over privacy and weather dependency. Despite these obstacles, the potential benefits like improved resource utilization and reduced environmental impact underscore the importance of drones in meeting the growing global food demand. This paper aims to provide an extensive overview of the role and potential of drone technology in reshaping the future of agriculture, empowering farmers to optimize yields, conserve resources and embrace a more sustainable approach in the face of global challenges

(Invited) Analog Computing with High Precision and Programmability Enabled by Memristors

While digital computing dominates the technological landscape, analog computing distinguishes itself with superior energy efficiency and high throughput. However, its historical limitation in precision and programmability has confined its application to specific and low-precision domains, notably in neural networks. The escalating challenge posed by the analog data deluge calls for versatile analog platforms. These platforms must not only exhibit exceptional efficiency but also boast reconfigurability and precision.Recent breakthroughs in analog devices, such as memristors, have laid the groundwork for unparalleled analog computing capabilities. Leveraging the multifaceted role of memristors, we introduce memristive field-programmable analog arrays (FPAAs), mirroring the functionality of their digital counterparts, field-programmable digital arrays (FPGAs). To elevate precision, we delve into the origins of reading noise, successfully mitigating it and achieving an unparalleled 2048 conductance levels in individual memristors—equivalent to 11 bits per cell, setting a record precision among diverse memory types. Acknowledging the persistent demand for single or double precision in various applications, we propose and develop a circuit architecture and programming protocol. This innovation enables analog memories to attain arbitrarily high precision with minimal circuit overhead. Our experimental validation involves a memristor System-on-Chip fabricated in a standard foundry, demonstrating significantly improved precision and power efficiency compared to traditional digital systems.The co-design approach presented empowers low-precision analog devices to perform high-precision computing within a programmable platform. This demonstration underscores the transformative potential of analog computing, transcending historical limitations and ushering in a new era of precision and efficiency.

Correlation between tooth decay and insulin resistance in normal weight males prompts a role for myo-inositol as a regenerative factor in dentistry and oral surgery: a feasibility study.

In an era of precision and stratified medicine, homogeneity in population-based cohorts, stringent causative entry, and pattern analysis of datasets are key elements to investigate medical treatments. Adhering to these principles, we collected in vivo and in vitro data pointing to an insulin-sensitizing/insulin-mimetic effect of myo-inositol (MYO) relevant to cell regeneration in dentistry and oral surgery. Confirmation of this possibility was obtained by in silico analysis of the relation between in vivo and in vitro results (the so-called bed-to-benchside reverse translational approach). Fourteen subjects over the 266 screened were young adult, normal weight, euglycemic, sedentary males having normal appetite, free diet, with a regular three-times-a-day eating schedule, standard dental hygiene, and negligible malocclusion/enamel defects. Occlusal caries were detected by fluorescence videoscanning, whereas body composition and energy balance were estimated with plicometry, predictive equations, and handgrip. Statistically significant correlations (Pearson r coefficient) were found between the number of occlusal caries and anthropometric indexes predicting insulin resistance (IR) in relation to the abdominal/visceral fat mass, fat-free mass, muscular strength, and energy expenditure adjusted to the fat and muscle stores. This indicated a role for IR in affecting dentin reparative processes. Consistently, in vitro administration of MYO to HUVEC and Swiss NIH3T3 cells in concentrations corresponding to those administered in vivo to reduce IR resulted in statistically significant cell replication (ANOVA/Turkey tests), suggesting that MYO has the potential to counteract inhibitory effects of IR on dental vascular and stromal cells turnover. Finally, in in silico experiments, quantitative evaluation (WOE and information value) of a bioinformatic Clinical Outcome Pathway confirmed that in vitro trophic effects of MYO could be transferred in vivo with high predictability, providing robust credence of its efficacy for oral health. Our reverse bed-to-benchside data indicate that MYO might antagonize the detrimental effects of IR on tooth decay. This provides feasibility for clinical studies on MYO as a regenerative factor in dentistry and oral surgery, including dysmetabolic/aging conditions, bone reconstruction in oral destructive/necrotic disorders, dental implants, and for empowering the efficacy of a number of tissue engineering methodologies in dentistry and oral surgery.

Abstract B014: Unveiling the future: Exploring cutting-edge technologies for synthetic lethality discovery

Abstract Synthetic lethality discovery is an emerging field of research that aims to reshape the landscape of cancer treatment, offering new hope and possibilities for patients faced with challenging diagnoses. In this article, we explored the cutting-edge technologies shaping the future of synthetic lathality research. Artificial intelligence and machine learning are not just buzzwords but indispensable tools that are shaping the field of precision medicine and personalized cancer treatment. By leveraging the power of computational tools, scientists can accelerate the identification of synthetic lethal interactions and pave the way for the development of more effective targeted cancer therapies. Through case studies, researchers can uncover the functional genomics of complex diseases and identify novel drug targets for cancer therapy. The integration of multi-omics approaches not only enhances the depth of analysis but also offers a more nuanced understanding of the molecular mechanisms driving synthetic lethal interactions, paving the way to unlock novel therapeutics and personalized treatment strategies. In addition, the integration of high-throughput screening techniques, such as CRISPR-Cas9 gene editing, opens up new avenues for identifying new drug targets and therapeutic strategies, ultimately paving a new era where personalized and targeted therapies redefine the way we approach cancer care, ushering in a novel era of precision and efficacy in medicine. Citation Format: Peter Oloche David. Unveiling the future: Exploring cutting-edge technologies for synthetic lethality discovery [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr B014.

SMART TEMPERATURE SENSORS FOR TEMPERATURE CONTROL SYSTEMS

Temperature control systems are pivotal in various applications, ranging from industrial processes and environmental monitoring to everyday comfort and safety. Smart temperature sensors represent a significant advancement in this field, enabling precise, efficient, and intelligent temperature regulation. This article provides an overview of the latest developments in smart temperature sensors and their integration into temperature control systems. The paper begins by discussing the fundamental importance of temperature control systems in maintaining optimal conditions in diverse settings. It highlights the growing need for sensors that offer improved accuracy, reliability, and adaptability, all of which smart temperature sensors are designed to provide. Subsequently, the article delves into the key features and capabilities of smart temperature sensors. These sensors incorporate advanced technologies such as microelectromechanical systems (MEMS), integrated digital signal processing, and wireless connectivity, enabling them to collect and transmit data with unprecedented precision and efficiency. Moreover, smart temperature sensors often offer real-time data monitoring, remote access, and the capacity for data analytics, making them invaluable tools for enhancing temperature control. The discussion then shifts to the various applications of smart temperature sensors. Whether it be optimizing energy consumption in HVAC systems, ensuring compliance with safety standards in industrial processes, or monitoring temperature-sensitive goods during transport and storage, these sensors have the potential to revolutionize temperature control across numerous domains. Additionally, the article addresses the challenges and considerations in implementing smart temperature sensors, including calibration, data security, and power efficiency. The integration of artificial intelligence and machine learning algorithms for predictive temperature control is explored, as they promise to further enhance the adaptability and responsiveness of temperature control systems. In conclusion, smart temperature sensors are at the forefront of temperature control system innovation. Their ability to provide real-time, highly accurate data, alongside intelligent features, positions them as key components in achieving optimal temperature conditions in a wide range of applications. As technology continues to evolve, the adoption of smart temperature sensors is expected to grow, ushering in a new era of temperature control efficiency and precision. Keywords: Smart temperature sensors, Precision temperature monitoring, Digital signal processing, Safety, Industrial processes.

Precision Sports Science: What Is Next for Data Analytics for Athlete Performance and Well-Being Optimization?

In elite sports, athletic excellence demands meticulous performance preparation and a sound health status. This paper overviews the current propositions and applications of pervasive computing and data analytics and our vision on how they should be used in future frameworks to contribute to the optimal balance of athletes’ performance and health requirements. Two main areas will be discussed. The first area is Sports Performance Optimization, in which we consider interesting recent advancements in data analytics for performance improvement, equipment design, and team member recruitment and selection. We will also briefly discuss how the betting industry has been relaying and developing sports analytics. The second area is Athlete’s Wellness and Wellbeing, which will discuss how wearables and data analytics have been used to assess physical activity and sedentary behavior profiles, sleep and circadian rhythm, nutrition and eating behavior, menstrual cycles, and training/performance readiness. In the final part of this paper, we argue that a critical issue for managers to enhance their decision making is the standardization of acquired information and decision-making processes, while introducing an adaptable, personalized approach. Thus, we present and discuss new theoretical and practical approaches that could potentially address this problem and identify precision medicine as a recommended methodology. This conceptualization involves the integration of pervasive computing and data analytics by employing predictive models that are constantly updated with the outcomes from monitoring tools and athletes’ feedback interventions. This framework has the potential to revolutionize how athletes’ performance and well-being are monitored, assessed, and optimized, contributing to a new era of precision in sports science and medicine.

The Future of Marketing: The Transformative Power of Artificial Intelligence

This research offers a rich narrative explaining this multifaceted relationship by exploring the transformative impact of Artificial Intelligence (AI) on marketing by adopting a qualitative descriptive approach for in-depth exploration. The findings reveal profound implications for customer engagement, market strategy, and ethical considerations. The multifaceted integration of AI into marketing enables customer personalization and increases brand loyalty. Predictive analytics enable businesses to develop proactive strategies aligned with future market dynamics. Despite its advantages, ethical considerations surrounding data privacy and consumer consent require AI to be used responsibly and transparently. Integrated augmented reality, virtual reality, predictive customer journeys, and the Internet of Things that transform marketing dynamics must be harnessed to balance ethical concerns. A comprehensive resource for academic researchers and industry professionals, this work provides a clear roadmap for organizations to effectively leverage AI in their marketing operations in an environment of increasing reliance on digital platforms and expanding data availability.

Capacitive immunosensing at gold nanoparticle-decorated reduced graphene oxide electrodes fabricated by one-step laser nanostructuration

Nanostructured electrochemical biosensors have ushered in a new era of diagnostic precision, offering enhanced sensitivity and specificity for clinical biomarker detection. Among them, capacitive biosensing enables ultrasensitive label-free detection of multiple molecular targets. However, the complexity and cost associated with conventional fabrication methods of nanostructured platforms hinder the widespread adoption of these devices. This study introduces a capacitive biosensor that leverages laser-engraved reduced graphene oxide (rGO) electrodes decorated with gold nanoparticles (AuNPs). The fabrication involves laser-scribed GO-Au3+ films, yielding rGO-AuNP electrodes, seamlessly transferred onto a PET substrate via a press-stamping methodology. These electrodes have a remarkable affinity for biomolecular recognition after being functionalized with specific bioreceptors. For example, initial studies with human IgG antibodies confirm the detection capabilities of the biosensor using electrochemical capacitance spectroscopy. Furthermore, the biosensor can quantify CA-19-9 glycoprotein, a clinical cancer biomarker. The biosensor exhibits a dynamic range from 0 to 300 U mL−1, with a limit of detection of 8.9 U mL−1. Rigorous testing with known concentrations of a pretreated CA-19-9 antigen from human fluids confirmed their accuracy and reliability in detecting the glycoprotein. This study signifies notable progress in capacitive biosensing for clinical biomarkers, potentially leading to more accessible and cost-effective point-of-care solutions.

Saving Lives in Thoracic Surgery: Balancing Oncological Radicality and Functional Preservation, Transitioning from Standard Pneumonectomy to Targeted Sublobar Resection.

This review chronicles the evolution of thoracic surgical interventions, from the standardized pneumonectomy to the precise approach of sublobar resections. It discusses the emergence and acceptance of minimally invasive and robot-assisted surgical techniques, highlighting their impact on improving outcomes beyond cancer and their influence on the surgical management of early-stage lung cancer. Evaluating historical developments alongside present methodologies, this review underscores the critical need for meticulous surgical planning and execution to optimize both oncological radicality and functional preservation. This evolution portrayed not only technical advancements but also a shift in the clinical approach towards tailored, organ-preserving methodologies, culminating in a contemporary framework promoting sublobar resections as the standard for specific patient profiles, signifying a new era of precision in thoracic surgery.

Convergence properties of fine structure constant measurements using quasar absorption systems

ABSTRACT Searches for space–time variations of fundamental constants have entered an era of unprecedented precision. New, high-quality quasar spectra require increasingly refined analytical methods. In this paper, a continuation in a series to establish robust and unbiased methodologies, we explore how convergence criteria in non-linear least-squares optimization impact on quasar absorption system measurements of the fine structure constant α. Given previous claims for high-precision constraints, we critically examine the veracity of a so-called blinding approach, in which α is fixed at the terrestrial value during the model building process, releasing it as a free parameter only after the ‘final’ absorption system kinematic structure has been obtained. We show that this approach results in such small consecutive parameter steps during minimization that convergence is unlikely to be reached, even after as many as 1000 iterations. The fix is straightforward: α must be treated as a free parameter from the earliest possible stages of absorption system model building. The implication of the results presented here is that all previous measurements that have used initially fixed α should be reworked.

Experimental research of a structural health monitoring system concept based on fiber Bragg grating sensors on composite panels of an aircraft

In the dynamic realm of aviation, ensuring the structural integrity of aircraft stands as an imperative pillar of safety and operational efficiency. Amidst this landscape, the advent of Fiber Bragg Grating (FBG) sensing technology has propelled structural health monitoring (SHM) into a new era of precision and reliability. This paper embarks on an exploration of SHM in aviation, using the transformative capabilities of FBG sensing. The primary objective was to evaluate the sensitivity of FBG-based sensors to static and dynamic loads as well as the response to defects formed upon fracture. The study involves fifteen experiments with FBG setups on a composite panel. Using interrogators, the distortions in optical signals were obtained and recalculated to provide data on deformations. Based on the results, FBG sensing technology proved to be sensitive to the mentioned load types, outputting consistent data.

Cystic Fibrosis between “names” and “surnames”: the expression of Biopower in the era of precision

Resumo Na fibrose cística, a identificação da variabilidade genética (mutações) da CFTR - a qual difere quanto a síntese, tráfego, estabilidade e função da proteína e suas implicações na disfuncionalidade do gene - é a principal base para o desenvolvimento dos medicamentos moduladores e inovações na terapêutica. Tais inovações prometem um aumento da expectativa de vida com qualidade na era da biomedicina high tech. O argumento deste artigo se funda na ideia de que o poder-saber pelo conhecer da mutação fomenta a construção da identidade no “eu genético”. Metodologicamente, assume-se a Análise Crítica dos Discursos (ACD), interessada nas formações discursivas dos atores sociais, como uma comunidade de especialistas com vinculações diversas no campo da fibrose cística. Discute-se o quanto posições sócio-históricas e culturais, em correspondência com as práticas sociais, veiculam a centralidade do debate do direito à vida na era da medicina de precisão. A experiência compartilhada da FC, como uma condição de saúde rara, aponta para o (res)significar da cidadania em torno do bios.

Immune landscape of the kidney allograft in response to rejection.

Preventing kidney graft dysfunction and rejection is a critical step in addressing the nationwide organ shortage and improving patient outcomes. While kidney transplants (KT) are performed more frequently, the overall number of patients on the waitlist consistently exceeds organ availability. Despite improved short-term outcomes in KT, comparable progress in long-term allograft survival has not been achieved. Major cause of graft loss at 5 years post-KT is chronic allograft dysfunction (CAD) characterized by interstitial fibrosis and tubular atrophy (IFTA). Accordingly, proactive prevention of CAD requires a comprehensive understanding of the immune mechanisms associated with either further dysfunction or impaired repair. Allograft rejection is primed by innate immune cells and carried out by adaptive immune cells. The rejection process is primarily facilitated by antibody-mediated rejection (ABMR) and T cell-mediated rejection (TCMR). It is essential to better elucidate the actions of individual immune cell subclasses (e.g. B memory, Tregs, Macrophage type 1 and 2) throughout the rejection process, rather than limiting our understanding to broad classes of immune cells. Embracing multi-omic approaches may be the solution in acknowledging these intricacies and decoding these enigmatic pathways. A transition alongside advancing technology will better allow organ biology to find its place in this era of precision and personalized medicine.