Disparities in prevalence and treatment of diabetes, cardiovascular and chronic kidney diseases - Recommendations from the taskforce of the guideline workshop.

There is a mounting clinical, psychosocial, and socioeconomic burden worldwide as the prevalence of diabetes, cardiovascular disease (CVD), and chronic kidney disease (CKD) continues to rise. Despite the introduction of therapeutic interventions with demonstrated efficacy to prevent the development or progression of these common chronic diseases, many individuals have limited access to these innovations due to their race/ethnicity, and/or socioeconomic status (SES). However, practical guidance to providers and healthcare systems for addressing these disparities is often lacking. In this article, we review the prevalence and impact of healthcare disparities derived from the above-mentioned chronic conditions and present broad-based recommendations for improving access to quality care and health outcomes within the most vulnerable populations.

Folic Acid Functionalized AQ4N/Gd@PDA Nanoplatform with Real-Time Monitoring of Hypoxia Relief and Enhanced Synergistic Chemo/Photothermal Therapy in Glioma.

Purpose: Hypoxia is often associated with glioma chemoresistance, and alleviating hypoxia is also crucial for improving treatment efficacy. However, although there are already some methods that can improve efficacy by alleviating hypoxia, real-time monitoring that can truly achieve hypoxia relief and efficacy feedback still needs to be explored. Methods: AQ4N/Gd@PDA-FA nanoparticles (AGPF NPs) were synthesized using a one-pot method and were characterized. The effects of AGPF NPs on cell viability, cellular uptake, and apoptosis were investigated using the U87 cell line. Moreover, the effectiveness of AGPF NPs in alleviating hypoxia was explored in tumor-bearing mice through photoacoustic imaging. In addition, the diagnosis and treatment effect of AGPF NPs were evaluated by magnetic resonance imaging (MRI) and bioluminescent imaging (BLI) on orthotopic glioma mice respectively. Results: In vitro experiments showed that AGPF NPs had good dispersion, stability, and controlled release. AGPF NPs were internalized by cells through endocytosis, and could significantly reduce the survival rate of U87 cells and increase apoptosis under irradiation. In addition, we monitored blood oxygen saturation at the tumor site in real-time through photoacoustic imaging (PAI), and the results showed that synergistic mild-photothermal therapy/chemotherapy effectively alleviated tumor hypoxia. Finally, in vivo anti-tumor experiments have shown that synergistic therapy can effectively alleviate hypoxia and inhibit the growth of orthotopic gliomas. Conclusion: This work not only provides an effective means for real-time monitoring of the dynamic feedback between tumor hypoxia relief and therapeutic efficacy, but also offers a potential approach for the clinical treatment of gliomas.

Comparative evaluation of three real-time polymerase chain reaction assays to detect Myxobolus cerebralis.

OBJECTIVE: We sought to evaluate accurate and reproducible detection of Myxobolus cerebralis (Mc), the causative agent of whirling disease, by using nested polymerase chain reaction (nPCR) and three previously established real-time quantitative PCR (qPCR) assays: K18S (Kelley 18S), C18S (Cavender 18S), and Hsp70 (heat shock protein 70). We used a "fit for purpose" approach combined with intra- and interlaboratory testing to identify a molecular testing method that would be equivalent to the currently accepted nPCR procedure for Mc. METHODS: Assay performance was compared using a combination of intra- and interlaboratory testing that used synthetic gBlocks along with naturally and experimentally infected fish tissue. North American isolates representing geographically distinct locations were also tested using all three assays. RESULT: The K18S and C18S assays exhibited high assay sensitivity, intra- and interlaboratory repeatability of sample replicates, and reproducible identification of all test samples across multiple laboratories. In contrast, the Hsp70 assay failed to detect several positive samples at low DNA concentrations during intra- and interlaboratory testing. The K18S assay was the only procedure that demonstrated perfect detection accuracy when testing geographically distinct Mc isolates. Results demonstrated the K18S assay is robust under variable test conditions, is more accurate than the C18S and Hsp70 assays, and provides detection capabilities equivalent to those of the currently accepted nPCR confirmation assay "gold standard" that is described in the American Fisheries Society-Fish Health Section (AFS-FHS) Blue Book. CONCLUSION: The "fit for purpose" approach and preliminary completion of the World Organization for Animal Health validation pathway demonstrate that the K18S assay provides an alternate method for Mc testing. This work provides the foundation for acceptance of the K18S assay into the AFS-FHS Blue Book as a standardized test procedure for Mc.

Detection of pathogenic Vibrio spp. in foods: polymerase chain reaction-based screening strategy to rapidly detect pathogenic Vibrio parahaemolyticus, Vibrio cholerae, and Vibrio vulnificus in bivalve mollusks and preliminary results.

The majority of human diseases attributed to seafood are caused by Vibrio spp., and the most commonly reported species are Vibrio parahaemolyticus, Vibrio vulnificus, and Vibrio cholerae. The conventional methods for the detection of Vibrio species involve the use of selective media, which are inexpensive and simple but time-consuming. The present work aimed to develop a rapid method based on the use of multiplex real-time polymerase chain reaction (PCR) to detect V. parahaemolyticus, V. vulnificus, and V. cholerae in bivalve mollusks. 30 aliquots of bivalve mollusks (Mytilus galloprovincialis) were experimentally inoculated with two levels of V. parahaemolyticus, V. vulnificus, and V. cholerae. ISO 21872-1:2017 was used in parallel for qualitative analysis. The limit of detection of 50% was 7.67 CFU/g for V. cholerae, 0.024 CFU/g for V. vulnificus, and 1.36 CFU/g for V. parahaemolyticus. For V. vulnificus and V. cholerae, the real-time PCR protocol was demonstrated to amplify the pathogens in samples seeded with the lowest and highest levels. The molecular method evaluated showed a concordance rate of 100% with the reference microbiological method. V. parahaemolyticus was never detected in samples contaminated with the lowest level, and it was detected in 14 samples (93.33%) seeded with the highest concentration. In conclusion, the developed multiplex real-time PCR proved to be reliable for V. vulnificus and V. cholerae. Results for V. parahaemolyticus are promising, but further analysis is needed. The proposed method could represent a quick monitoring tool and, if used, would allow the implementation of food safety.

Development and application of one-step multiplex Real-Time PCR for detection of three main pathogens associated with bovine neonatal diarrhea.

Introduction: Neonatal calf diarrhea (NCD) is one of the most common diseases in calves, causing huge economic and productivity losses to the bovine industry worldwide. The main pathogens include bovine rotavirus (BRV), bovine coronavirus (BCoV), and Enterotoxigenic Escherichia coli (ETEC) K99. Since multiple infectious agents can be involved in calf diarrhea, detecting each causative agent by traditional methods is laborious and expensive. Methods: In this study, we developed a one-step multiplex Real-Time PCR assay to simultaneously detect BRV, BCoV, and E. coli K99+. The assay performance on field samples was evaluated on 1100 rectal swabs of diseased cattle with diarrhea symptoms and compared with the conventional gel-based RT-PCR assay detect BRV, BCoV, and E. coli K99+. Results: The established assay could specifically detect the target pathogens without cross-reactivity with other pathogens. A single real-time PCR can detect ~1 copy/µL for each pathogen, and multiplex real-time PCR has a detection limit of 10 copies/µL. Reproducibility as measured by standard deviation and coefficient of variation were desirable. The triple real-time PCR method established in this study was compared with gel-based PT-PCR. Both methods are reasonably consistent, while the real-time PCR assay was more sensitive and could rapidly distinguish these three pathogens in one tube. Analysis of surveillance data showed that BRV and BCoV are major enteric viral pathogens accounting for calves' diarrhea in China. Discussion: The established assay has excellent specificity and sensitivity and was suitable for clinical application. The robustness and high-throughput performance of the developed assay make it a powerful tool in diagnostic applications and calf diarrhea research. ​.

Exploiting the potential of a novel "in-situ latent heat recovery" in hollow-fiber vacuum membrane distillation process for simultaneously improved water production and energy efficiency.

Thermal driven membrane distillation (MD) technology is a promising method for purifying & recovering various salty (especially high salty) or contaminated wastewaters with low-grade heat sources. However, the drawbacks of "high energy consumption" and "high cooling water consumption" pose special challenges for the future development of this technology. In this article, we report an innovative strategy called "in-situ heat transfer", which is based on the jacketed structure composed of hollow fiber membranes and capillary heat exchange tubes, to simplify the migration steps of condensation latent heat in MD heat recovery process. The results indicate that the novel heat recovery strategy exhibits higher growth rates both in the flux and gained output ratio (47.4 % and 173.1 %, respectively), and further reduces the system's dependence on cooling water. In sum, under the control of the "in-situ heat transfer" mechanism, the functional coupling of "vapor condensation (exothermic)" and "feed evaporation (endothermic)" in limited-domain space is an attractive alternative solution, because it eliminates the disadvantages of the imbalance between heat supply and demand in traditional heat recovery methods. Our research may facilitate the development of MD heat recovery modules for industrial applications, which will help to further achieve the goal of energy saving and emission reduction.

Establishment and application of a quadruplex real-time RT-qPCR assay for differentiation of TGEV, PEDV, PDCoV, and PoRVA.

Porcine viral diarrhea is a common ailment in clinical settings, causing significant economic losses to the swine industry. Notable culprits behind porcine viral diarrhea encompass transmissible gastroenteritis virus (TGEV), porcine epidemic diarrhea virus (PEDV), porcine deltacoronavirus (PDCoV), and porcine rotavirus-A (PoRVA). Co-infections involving the viruses are a common occurrence in clinical settings, thereby amplifying the complexities associated with differential diagnosis. As a consequence, it is therefore necessary to develop a method that can detect and differentiate all four porcine diarrhea viruses (TGEV, PEDV, PDCoV, and PoRVA) with a high sensitivity and specificity. Presently, polymerase chain reaction (PCR) is the go-to method for pathogen detection. In comparison to conventional PCR, TaqMan real-time PCR offers heightened sensitivity, superior specificity, and enhanced accuracy. This study aimed to develop a quadruplex real-time RT-qPCR assay, utilizing TaqMan probes, for the distinctive detection of TGEV, PEDV, PDCoV, and PoRVA. The quadruplex real-time RT-qPCR assay, as devised in this study, exhibited the capacity to avoid the detection of unrelated pathogens and demonstrated commendable specificity, sensitivity, repeatability, and reproducibility, boasting a limit of detection (LOD) of 27 copies/µL. In a comparative analysis involving 5483 clinical samples, the results from the commercial RT-qPCR kit and the quadruplex RT-qPCR for TGEV, PEDV, PDCoV, and PoRVA detection were entirely consistent. Following sample collection from October to March in Guangxi Zhuang Autonomous Region, we assessed the prevalence of TGEV, PEDV, PDCoV, and PoRVA in piglet diarrhea samples, revealing positive detection rates of 0.2% (11/5483), 8.82% (485/5483), 1.22% (67/5483), and 4.94% (271/5483), respectively. The co-infection rates of PEDV/PoRVA, PEDV/PDCoV, TGEV/PED/PoRVA, and PDCoV/PoRVA were 0.39%, 0.11%, 0.01%, and 0.03%, respectively, with no detection of other co-infections, as determined by the quadruplex real-time RT-qPCR. This research not only established a valuable tool for the simultaneous differentiation of TGEV, PEDV, PDCoV, and PoRVA in practical applications but also provided crucial insights into the prevalence of these viral pathogens causing diarrhea in Guangxi.

One-step and Rapid Identification of SARS-CoV-2 using Real-Time Reverse Transcription Loop-Mediated Isothermal Amplification (RT-LAMP).

Background: SARS-CoV-2 as the cause of novel coronavirus disease (COVID-19) is a member of the family Coronaviridea that has generated an emerging global health concern. Controlling and preventing the spread of the disease requires a simple, portable, and rapid diagnostic method. Today, a standard method for detecting SARS-CoV-2 is quantitative real-time reverse transcription PCR, which is time-consuming and needs an advanced device. The aim of this study was to evaluate a faster and more cost-effective field-based testing method at the point of risk. We utilized a one-step RT-LAMP assay and developed, for the first time, a simple and rapid screening detection assay targeting the Envelope (E) gene, using specific primers. Methods: For this, the total RNA was extracted from respiratory samples of COVID-19 infected patients and applied to one-step a RT-LAMP reaction. The LAMP products were visualized using green fluorescence (SYBR Green I). Sensitivity testing was conducted using different concentrations of the designed recombinant plasmid (TA-E) as positive control constructs. Additionally, selectivity testing was performed using the influenza H1N1 genome. Finally, the results were compared using with conventional real time RT-PCR. Results: It was shown that the RT-LAMP assay has a sensitivity of approximately 15 ng for the E gene of SARS-CoV-2 when using extracted total RNA. Additionally, a sensitivity of 112 pg was achieved when using an artificially prepared TA-E plasmid. Accordingly, for the detection of SARS-CoV-2 infection, the RT-LAMP had high sensitivity and specificity and also could be an alternative method for real-time RT-PCR. Conclusion: Overall, this method can be used as a portable, rapid, and easy method for detecting SARS-CoV-2 in the field and clinical laboratories.

Promoting a Patient-Centered Understanding of Safety in Acute Mental Health Wards: A User-Centered Design Approach to Develop a Real-Time Digital Monitoring Tool.

BACKGROUND: Acute mental health services report high levels of safety incidents that involve both patients and staff. The potential for patients to be involved in interventions to improve safety within a mental health setting is acknowledged, and there is a need for interventions that proactively seek the patient perspective of safety. Digital technologies may offer opportunities to address this need. OBJECTIVE: This research sought to design and develop a digital real-time monitoring tool (WardSonar) to collect and collate daily information from patients in acute mental health wards about their perceptions of safety. We present the design and development process and underpinning logic model and programme theory. METHODS: The first stage involved a synthesis of the findings from a systematic review and evidence scan, interviews with patients (n=8) and health professionals (n=17), and stakeholder engagement. Cycles of design activities and discussion followed with patients, staff, and stakeholder groups, to design and develop the prototype tool. RESULTS: We drew on patient safety theory and the concepts of contagion and milieu. The data synthesis, design, and development process resulted in three prototype components of the digital monitoring tool (WardSonar): (1) a patient recording interface that asks patients to input their perceptions into a tablet computer, to assess how the ward feels and whether the direction is changing, that is, "getting worse" or "getting better"; (2) a staff dashboard and functionality to interrogate the data at different levels; and (3) a public-facing ward interface. The technology is available as open-source code. CONCLUSIONS: Recent patient safety policy and research priorities encourage innovative approaches to measuring and monitoring safety. We developed a digital real-time monitoring tool to collect information from patients in acute mental health wards about perceived safety, to support staff to respond and intervene to changes in the clinical environment more proactively.

Establishment and application of TaqMan real-time PCR method for detection of Theileria annulata resistant to buparvaquone.

Tropical theileriosis is a tick-borne disease that caused by Theileria annulata, and leads to substantial economic impact in endemic area. Distinguishes to other piroplasms, Theileria is the only eukaryotic parasite could transform mammalian leukocytes. At present, buparvaquone is the most effective drug used for treatment of Theileria infection. However, frequently reported of failure treatment with buparvaquone for some T. annulata isolates. Mutation of TaPIN1 was reported to be the direct reason for failure of buparvaquone treatment. Through in vitro culture, a T. annulata isolate with a TaPIN1 mutation that is similar to the reported strain was recently identified in China. In order to understand the distribution of Theileria with mutation of TaPIN1 in China, here we developed a TaqMan probe-based real-time PCR technology to detect the mutated TaPIN1 gene. The specificity, sensitivity and reproducibility of the established TaqMan Real-time PCR method were evaluated, and field cattle blood samples collected from Xinjiang Uyghur Autonomous Region were used to test its application. Among 1683 samples, 335 samples were confirmed positive for T. annulata by traditional PCR method and 34 samples were positive for buparvaquone-resistant. The TaPIN1 gene of those 34 samples was sequenced and analyzed with the published gene sequences from NCBI database. The results showed that the sequence obtained from the present study has good consistency with those published sequences. In conclusion, the TaqMan probe-based real-time PCR targeting T. annulata mutated TaPIN1 gene was successfully established and can be used to detect clinical samples to investigation of buparvaquone-resistant parasites in Xinjiang region quickly and accurately, which will be useful for guiding clinical medicine application.

Yak IGFBP3 promotes hepatocyte proliferation through PI3K-Akt signaling pathway.

IGFBP3 (Insulin-like growth factor binding protein 3) constitutes a crucial constituent of the insulin-like growth factor (IGF), which are intimately associated with the organism's growth and development processes. Despite its significance, the precise function of IGFBP3 in yak liver development remains largely unexplored. In the present study, we systematically examined the expression profile of IGFBP3 in the liver tissues of yaks across various growth stages, elucidated its influence on the activity of yak hepatocytes, and probed its effects on murine liver development. A comparative analysis revealed that the expression of IGFBP3 was significantly higher in the liver tissue of 5-year-old yaks compared to their 15-month-old and 1-day-old counterparts (P < 0.01). To further validate its biological function, pET-28a-BgIGFBP3 prokaryotic expression vector was constructed. Upon exposing yak hepatocytes to varying concentrations of Bos grunniens (Bg) IGFBP3 protein, we observed augmented cellular activities and elevated colony formation rates. Moreover, our investigation revealed the upregulation of key genes within the PI3K-Akt signaling pathway, including ERBB2, IRS1, PIK3R1, AKT1, RAF1, MAP2K2, and MAPK3, in both yak hepatocyte cultures and murine models. These findings collectively indicate that BgIGFBP3 promotes the proliferation of yak hepatocytes and enhances murine liver development by modulating the PI3K-Akt signaling pathway. The functional relevance of BgIGFBP3 was substantiated through in vivo and in vitro experiments, thereby underscoring its potential as a regulatory factor in liver development processes.

Partnering With Technology: Advancing Laparoscopy With Artificial Intelligence and Machine Learning.

Artificial intelligence (AI) and machine learning (ML) have emerged as transformative technologies in optimizing laparoscopic surgery, offering innovative solutions to enhance surgical precision, efficiency, and safety. This editorial explores the potential role of AI/ML across the surgical continuum, including preoperative optimization, intraoperative assistance, and postoperative care. It outlines the benefits of laparoscopic surgery compared to traditional open procedures and identifies current challenges such as technical difficulty and human error. The editorial discusses how AI and ML technologies can address these challenges, including patient selection and risk stratification, surgical planning and simulation, and personalized medicine approaches. Moreover, it examines the role of AI/ML in intraoperative assistance, such as instrument tracking and guidance, real-time tissue analysis, and the detection of potential complications. Postoperative care and follow-up are also explored, highlighting the potential of AI/ML in monitoring patient recovery, predicting and preventing complications, and tailoring rehabilitation plans. Ethical concerns surrounding data privacy and security, the lack of transparency in decision-making, potential job displacement, and regulatory frameworks are discussed as challenges to the widespread adoption of AI/ML in laparoscopic surgery. Finally, potential areas for further research and exploration are outlined, emphasizing interdisciplinary collaboration and the need for transparent and accountable AI systems. Overall, this editorial provides insights into the challenges and opportunities in harnessing AI/ML technologies to optimize laparoscopic surgery and improve patient outcomes.

Reduction in Diabetes-Related Hospitalizations and Medical Costs After Dexcom G6 Continuous Glucose Monitor Initiation in People with Type 2 Diabetes Using Intensive Insulin Therapy.

INTRODUCTION: Some people with type 2 diabetes (T2D) require intensive insulin therapy to manage their diabetes. This can increase the risk of diabetes-related hospitalizations. We hypothesize that initiation of real-time continuous glucose monitoring (RT-CGM), which continuously measures a user's glucose values and provides threshold- and trend-based alerts, will reduce diabetes-related emergency department (ED) and inpatient hospitalizations and concomitant costs. METHODS: A retrospective analysis of US healthcare claims data using Optum's de-identified Clinformatics® Data Mart database was performed. The cohort consisted of commercially insured, CGM-naïve individuals with T2D who initiated Dexcom G6 RT-CGM system between August 1, 2018, and March 31, 2021. Twelve months of continuous health plan enrollment before and after RT-CGM initiation was required to capture baseline and follow-up rates of diabetes-related hospitalizations and associated healthcare resource utilization (HCRU) costs. Analyses were performed for claims with a diabetes-related diagnosis code in either (1) any position or (2) first or second position on the claim. RESULTS: A total of 790 individuals met the inclusion criteria. The average age was 52.8 (10.5) [mean (SD)], 53.3% were male, and 76.3% were white. For claims with a diabetes-related diagnosis code in any position, the number of individuals with ≥ 1 ED visit decreased by 30.0% (p = 0.01) and with ≥ 1 inpatient visit decreased by 41.5% (p < 0.0001). The number of diabetes-related visits and average number of visits per person similarly decreased by at least 31.4%. Larger relative decreases were observed for claims with a diabetes-related diagnosis code in the first or second position on the claim. Total diabetes-related costs expressed as per-person-per-month (PPPM) decreased by $341 PPPM for any position and $330 PPPM for first or second position. CONCLUSION: Initiation of Dexcom G6 among people with T2D using intensive insulin therapy was associated with a significant reduction in diabetes-related ED and inpatient visits and related HCRU costs. Expanded use of RT-CGM could augment these benefits and result in further cost reductions.

Molecular characterization and functional analysis of the ecdysone receptor isoform (EcR) from the oriental fruit moth Grapholita molesta (Lepidoptera: Tortricidae).

20-Hydroxyecdysone (20E) plays a vital role in a series of biological processes, via the nuclear receptors, EcR/USP by activating the ecdysone regulatory cascade. To clarify the role of EcR during the development of Grapholita molesta, the complementary DNA of ecdysone receptor isoform B1 (GmEcR-B1) was obtained from the transcriptome of G. molesta and verified by PCR. Alignment analysis revealed that the deduced protein sequence of GmEcR-B1 was highly homologous to EcR proteins identified in other lepidopteran species, especially the EcR-B1 isoform in Spodoptera litura. Quantitative real-time PCR showed that GmEcRs was expressed at all test developmental stages, and the expression level of GmEcRs was relatively higher during the period of the 3rd day of fifth instar larvae to 2nd of pupa than those in other stages. Moreover, the messenger RNA of GmEcRs was much more strongly expressed in the Malpighian tubule and epidermis than those in other tissues, which suggests that this gene may function in a tissue-specific manner during larval development. Silencing of GmEcRs could significantly downregulate the transcriptional level of ecdysone-inducible genes and result in increased mortality during metamorphosis and prolonged prepupal duration. Taken together, the present results indicate that GmEcRs may directly or indirectly affect the development of G. molesta.

CD99 Expression and Prognostic Impact in Glioblastoma: A Single-Center Cohort Study.

Glioblastoma is the most frequent and aggressive brain tumor in adults. This study aims to evaluate the expression and prognostic impact of CD99, a membrane glycoprotein involved in cellular migration and invasion. In a cohort of patients with glioblastoma treated with surgery, radiotherapy and temozolomide, we retrospectively analyzed tumor expression of CD99 by immunohistochemistry (IHC) and by quantitative real-time polymerase chain reaction (qRT-PCR) for both the wild type (CD99wt) and the truncated (CD99sh) isoforms. The impact on overall survival (OS) was assessed with the Kaplan-Meier method and log-rank test and by multivariable Cox regression. Forty-six patients with glioblastoma entered this study. Immunohistochemical expression of CD99 was present in 83%. Only the CD99wt isoform was detected by qRT-PCR and was significantly correlated with CD99 expression evaluated by IHC (rho = 0.309, p = 0.037). CD99 expression was not associated with OS, regardless of the assessment methodology used (p = 0.61 for qRT-PCR and p = 0.73 for IHC). In an exploratory analysis of The Cancer Genome Atlas, casuistry of glioblastomas CD99 expression was not associated with OS nor with progression-free survival. This study confirms a high expression of CD99 in glioblastoma but does not show any significant impact on survival. Further preclinical studies are needed to define its role as a therapeutic target in glioblastoma.

Development, Validation, and Comparison of a Novel Nociception/Anti-Nociception Monitor against Two Commercial Monitors in General Anesthesia.

In this paper, we present the development and the validation of a novel index of nociception/anti-nociception (N/AN) based on skin impedance measurement in time and frequency domain with our prototype AnspecPro device. The primary objective of the study was to compare the Anspec-PRO device with two other commercial devices (Medasense, Medstorm). This comparison was designed to be conducted under the same conditions for the three devices. This was carried out during total intravenous anesthesia (TIVA) by investigating its outcomes related to noxious stimulus. In a carefully designed clinical protocol during general anesthesia from induction until emergence, we extract data for estimating individualized causal dynamic models between drug infusion and their monitored effect variables. Specifically, these are Propofol hypnotic drug to Bispectral index of hypnosis level and Remifentanil opioid drug to each of the three aforementioned devices. When compared, statistical analysis of the regions before and during the standardized stimulus shows consistent difference between regions for all devices and for all indices. These results suggest that the proposed methodology for data extraction and processing for AnspecPro delivers the same information as the two commercial devices.

Real-Time Measurement and Uncertainty Evaluation of Optical Path Difference in Fiber Optic Interferometer Based on Auxiliary Interferometer.

Optical interferometers are the main elements of interferometric sensing and measurement systems. Measuring their optical path difference (OPD) in real time and evaluating the measurement uncertainty are key to optimizing system noise and ensuring system consistency. With the continuous sinusoidal wavelength modulation of the laser, real-time OPD measurement of the main interferometer is achieved through phase comparison of the main and auxiliary interferometers. The measurement uncertainty of the main interferometer OPD is evaluated. It is the first evaluation of the impact of different auxiliary interferometer calibration methods on OPD measurements. A homodyne quadrature laser interferometer (HQLI) is used as the main interferometer, and a 3 × 3 interferometer is used as the auxiliary interferometer. The calibration of the auxiliary interferometer using optical spectrum analyzer scanning and ruler measurement is compared. The evaluation shows that the auxiliary interferometer is the most significant source of uncertainty and causes the total uncertainty to increase linearly with increasing OPD. It is proven that a high-precision calibration and large-OPD auxiliary interferometer can improve the real-time accuracy of OPD measurements based on the auxiliary interferometer. The scheme can determine the minimum uncertainty to optimize the system noise and consistency for vibration, hydroacoustic, and magnetic field measurements with OPDs of the ~m level.

Towards Automating Personal Exercise Assessment and Guidance with Affordable Mobile Technology.

Physical activity (PA) offers many benefits for human health. However, beginners often feel discouraged when introduced to basic exercise routines. Due to lack of experience and personal guidance, they might abandon efforts or experience musculoskeletal injuries. Additionally, due to phenomena such as pandemics and limited access to supervised exercise spaces, especially for the elderly, the need to develop personalized systems has become apparent. In this work, we develop a monitored physical exercise system that offers real-time guidance and recommendations during exercise, designed to assist users in their home environment. For this purpose, we used posture estimation interfaces that recognize body movement using a computer or smartphone camera. The chosen pose estimation model was BlazePose. Machine learning and signal processing techniques were used to identify the exercise currently being performed. The performances of three machine learning classifiers were evaluated for the exercise recognition task, achieving test-set accuracy between 94.76% and 100%. The research methodology included kinematic analysis (KA) of five selected exercises and statistical studies on performance and range of motion (ROM), which enabled the identification of deviations from the expected exercise execution to support guidance. To this end, data was collected from 57 volunteers, contributing to a comprehensive understanding of exercise performance. By leveraging the capabilities of the BlazePose model, an interactive tool for patients is proposed that could support rehabilitation programs remotely.

SmartLaundry: A Real-Time System for Public Laundry Allocation in Smart Cities.

Smart cities facilitate the comprehensive management and operation of urban data generated within a city, establishing the foundation for smart services and addressing diverse urban challenges. A smart system for public laundry management uses artificial intelligence-based solutions to solve the challenges of the inefficient utilization of public laundries, waiting times, overbooking or underutilization of machines, balancing of loads across machines, and implementation of energy-saving features. We propose SmartLaundry, a real-time system design for public laundry smart recommendations to better manage the loads across connected machines. Our system integrates the current status of the connected devices and data-driven forecasted usage to offer the end user connected via a mobile application a list of recommended machines that could be used. We forecast the daily usage of devices using traditional machine learning techniques and deep learning approaches, and we perform a comparative analysis of the results. As a proof of concept, we create a simulation of the interaction with our system.

Implementation of Lightweight Convolutional Neural Networks with an Early Exit Mechanism Utilizing 40 nm CMOS Process for Fire Detection in Unmanned Aerial Vehicles.

The advancement of unmanned aerial vehicles (UAVs) enables early detection of numerous disasters. Efforts have been made to automate the monitoring of data from UAVs, with machine learning methods recently attracting significant interest. These solutions often face challenges with high computational costs and energy usage. Conventionally, data from UAVs are processed using cloud computing, where they are sent to the cloud for analysis. However, this method might not meet the real-time needs of disaster relief scenarios. In contrast, edge computing provides real-time processing at the site but still struggles with computational and energy efficiency issues. To overcome these obstacles and enhance resource utilization, this paper presents a convolutional neural network (CNN) model with an early exit mechanism designed for fire detection in UAVs. This model is implemented using TSMC 40 nm CMOS technology, which aids in hardware acceleration. Notably, the neural network has a modest parameter count of 11.2 k. In the hardware computation part, the CNN circuit completes fire detection in approximately 230,000 cycles. Power-gating techniques are also used to turn off inactive memory, contributing to reduced power consumption. The experimental results show that this neural network reaches a maximum accuracy of 81.49% in the hardware implementation stage. After automatic layout and routing, the CNN hardware accelerator can operate at 300 MHz, consuming 117 mW of power.