The aim of this study was to adapt a treadmill-developed method for determination of inner-cycle parameters in cross-country roller ski skating for a field application. The method is based on detecting initial and final ground-contact of poles and skis during cyclic movements. Eleven athletes skied four laps of 2.5 km at low and high endurance-intensity, using two types of skis with different rolling coefficients. Participants were equipped with inertial measurement units (IMUs) attached to their wrists and skis, while insoles with pressure sensors and poles with force measurements were used as reference systems. The method based on IMUs was able to detect more than 97% of the temporal events compared to the reference system. The inner-cycle temporal parameters had a precision ranging from 49 to 59 ms, corresponding to 3.9% to 13.7% of the corresponding inner-cycle duration. Overall, this study showed good reliability of using IMUs on athlete’s wrists and skis to determine temporal events, inner-cycle parameters and the performed sub-techniques in cross-country roller ski skating in field-conditions.

Within the field of movement sensing and sound interaction research, multi-user systems have gradually gained interest as a means to facilitate an expressive non-verbal dialogue. When tied with studies grounded in psychology and choreographic theory, we consider the qualities of interaction that foster an elevated sense of social connectedness, non-contingent to occupying one’s personal space. In reflection of the newly adopted social distancing concept, we orchestrate a technological intervention, starting with interpersonal distance and sound at the core of interaction. Materialised as a set of sensory face-masks, a novel wearable system was developed and tested in the context of a live public performance from which we obtain the user’s individual perspectives and correlate this with patterns identified in the recorded data. We identify and discuss traits of the user’s behaviour that were accredited to the system’s influence and construct 4 fundamental design considerations for physically distanced sound interaction. The study concludes with essential technical reflections, accompanied by an adaptation for a pervasive sensory intervention that’s finally deployed in an open public space.

In recent years, several Ultrawideband (UWB) localization systems have already been proposed and evaluated for accurate position estimation of pedestrians. However, most of them are evaluated for a particular wearable sensor position; hence the accuracy obtained is subject to a given wearable sensor position. In this paper, we study the effects of body wearable sensor positions i.e., chest, arm, ankle, wrist, thigh, fore-head, hand, on the localization accuracy. The conclusion drawn is that the fore-head is the best, and the chest is the worst body sensor location for tracking a pedestrian. While the fore-head position is able to set an error lower than 0.35 m (90th percentile), the chest is able to set 4 m. The reason for such a contrast in the performance lies in the fact that in NLOS situations, the chest as an obstacle is larger in size and thickness than any other part of the human body, which the UWB signal needs to overcome to reach the target wearable sensor. And so, the large errors arise due to the signal arriving at the target wearable sensor from reflections of a nearby object or a wall in the environment.

Functional mobility assessments (i.e., Timed Up and Go) are commonly used clinical tools for mobility and fall risk screening in the aging population. In this work, we proposed a new Mixed Reality (MR)-based assessment that utilized a Microsoft HoloLens^TM headset to automatically lead and track the performance of functional mobility tests, and subsequently evaluated its validity in comparison with reference inertial sensors. Twenty-two healthy adults (10 older, 12 young) participated in this study. An automated functional mobility assessment app was developed based on the HoloLens platform. Mobility performance was recorded with the headset built-in sensor and validated with reference inertial sensor (Opal, APDM) taped on the headset and lower back. Results indicate vertical kinematic measures by HoloLens was in good agreement with the reference sensor (Normalized RMSE ~ 10%). Additionally, the HoloLens-based test completion time was in perfect agreement with clinical standard stopwatch measure. Overall, our preliminary investigation indicates that it is possible to use an MR headset to automatically guide users to complete common mobility tests with good measurement accuracy, thus it has great potential to provide objective and efficient sensor-based mobility assessment.

Research on fall and movement detection with wearable devices has witnessed promising growth. However, there are few publicly available datasets, all recorded with smartphones, that prevent authors to evenly compare their new proposals. Here, we present a dataset of falls and activities of daily living (ADL) acquired with a self-developed device composed of two types of accelerometer and one gyroscope. It consists of 19 ADL and 15 fall types performed by 23 young adults, 15 ADL types performed by 14 healthy and independent participants over 62 years old, and data from one participant of 60 years old that performed all ADL and falls. These activities were selected based on a survey and a literature analysis. We test the dataset with widely used feature extraction and a simple to implement threshold based classification, achieving up to 96~\% of accuracy in fall detection. An individual activity analysis demonstrates that most errors coincide in a few number of activities where algorithms could be focused on. Finally, validation tests with elderly people significantly reduced the fall detection performance of the tested features. This validates findings of other authors and encourages to develop new strategies with this new dataset as benchmark.

In recent years, long periods of drought and heat waves have become increasingly frequent, causing forest dieback phenomena that make stands more sensitive to biotic stressors. How trees may respond to extreme climatic events and which metabolites are involved under stress conditions is still not clear. In this study, we analysed by SPME how dieback (D) and non-dieback (ND) Hungarian oak trees from the San Paolo Albanese site respond to these climatic dynamics, in terms of volatile organic compounds (VOCs). For each group of trees, three wood samples were taken, each divided into four sub-samples with 5 growth rings, subjected to SPME and increase in basal area (BAI) analysis of the last 20 years. Dieback trees had a lower amount of leaves, and this condition may translate into less photosynthesis, less organic matter production and lower reserves of carbohydrates available for growth. Indeed, D trees showed lower radial increases and a lower content of aldehydes, terpenes, and fatty acids than ND trees, indicating a better health of ND trees compared to D trees. While D trees showed a reduction in terpenes, such as α-pinene, γ-eudesmol, and cyperene (with significant insecticidal activity), a reduction in aromatic aldehydes, such as furfural and 5-methylfurfural, and an increase in silanols (with antimicrobial function). Considering the different compounds’ contents between D and ND trees, our study could be useful for detecting bio-indicators to identify an early warning signal of dieback phenomena.

The interface of a structural system in the soil is usually unsaturated. A decrease in the shear strength of the soil-structure interface can degrade the structure, especially under humid conditions. Studying the shear characteristics of the silt-concrete interface using a shear apparatus. Suction-controlled ring shear tests were carried out on the silt-concrete interface for three interface roughness values. The influence of the matric suction (s) and interface roughness (R) on the shear strength index of the silt-concrete interface was analyzed. The test results showed that high values of s and R improved the shear strength of the interface, but the result was affected by the net normal stress (NNS). High values of NNS and R improved the strain-hardening characteristics. NNS, s, and R significantly affected the interface shear shrinkage. The internal friction angle of the saturated interface was smaller than that of saturated silt, whereas the opposite occurred in the unsaturated state. The cohesion and internal friction angle of the interface rose with an increase in R, and they were larger than that of silt. A shear strength model of the silt and interface was established.

A millimeter-wave microstrip leaky-wave antenna array based on the substrate-integrated waveguide (SIW) and the complementary split-ring resonator (CSRR) is proposed in this paper. The slow wave characteristics of the SIW are enhanced by etching two rows of symmetrical CSRR-type slots on the surface of the SIW layer. The magnetic coupling between the CSRR-SIW layer and equally spaced circular patches array on the upper layer realizes the radiation of electromagnetic energy. In the 23~30 GHz (relative bandwidth 26.4%) operating frequency band, the horizontal polarization radiation beam scanning from -62° to -2° is realized, with a peak gain of 9.6~11.7 dBi, and the cross-polarization ratio is more than 43.8 dB.

Collision tumors, even uncommon, characterized by two distinctive (morphological, as well immunohistochemical) and spatially independent tumor components in the same location, are always puzzling for clinicians, pathologists and patients because they don’t fit in usual approaching schemes, neither diagnostic, nor therapeutic. Reviewing the specialized literature, until now, collision tumors have been reported in multiple locations such as the skin, esophagus, stomach, liver, kidney, bladder, adrenal gland or thyroid. We report a case of coexistence on the same site of a malignant tumor of ascending colon and a benign one emerging from peritoneal lining, thought initially by the surgeon to be right sided serosal carcinomatosis. But the histopatological examination reveals that those multiple serosal nodules were benign granular cell tumors collided with highly aggressive transparietal signet-ring colon carcinoma. These results put the patient's prognosis and therapeutic strategy in a different light than the clinical-imaging and intraoperative assessment.

Self-compacting concrete is essential for vertical structures due to high reinforcement and usage of pumps for transporting the concrete at the working site. SCC is mainly influenced by self-curing for arid areas. To explore the SCC (Self-Compacting Concrete) mixture and condition influencing the self-curing condition were determined using the experimental procedure. Determination of various parameters was done using T50 slump flow, V-funnel, L-box-box, J ring test, compressive strength, splitting tensile strength, and flexural strength test. After the experimental investigation, it shows that if the dose if the dosage of superplasticizer (SNF%) increases, it will improve the concrete mixture's different properties, such as flowability and ability to pass. Higher water-to-cement ratios (w/c) generally result in enhanced flowability and stability. Mixture 9 (SNF 0.35, w/c 0.5) demonstrates favourable results across all parameters, indicating excellent flowability and stability. Mixture 9 (SNF 0.35, w/c 0.5) also shows favourable flowability and stability characteristics. Lower concentrations, such as 0.5%, may have a positive effect up to a certain point but might not provide sustained improvement over the curing period. On the other hand, concentrations of 1% and 2% demonstrated consistent and significant enhancement in strength throughout the 28 days. It is found that the higher concentrations of PEG 4000 may be more effective in improving the material strength.

This short paper demonstrates that the galactic spiral equations developed from ROTASE model can be used to morphologically simulate the phyllotactic spiral-ring patterns of plants. It is also noticed during this project that although the numbers in the Fibonacci sequence dominate the phyllotactic numbers, there are still significant phyllotactic numbers are not in the Fibonacci sequence, however, most of those numbers are well fit into a Fibonacci sibling sequence starting with numbers 0 and 2. Many plants show the phyllotactic number pairs of 10-16, 16-26 and 26-42 from the Fibonacci sibling sequence, which is the second dominated sequence in the phyllotaxis.

We measured the ring collection coefficient of bromide anion oxidation products in a neutral and slightly alkaline medium on a rotating ring-disk electrode (glassy carbon disk, platinum ring) varying the following parameters: disk electrode rotation velocity, sodium bromide concentration, pH of the medium (in the range of 6 – 12), anode current on the disk and the electroreduction potential of the bromide anion oxidation products on the ring. The data obtained is presented via dependences of the cathode ring current to the disk current ratio vs the ring electrode potential. The analysis of the results was carried out by comparing the experimental polarization curves of the ring electrode with the data of cyclic voltammetry in model solutions to determine the electrical activities of various bromine compounds in positive oxidation states. We claim that RRDE method could be used to obtain quantitative and qualitative data on the electrooxidation of bromide ion in neutral and alkaline solutions. For the most effective regeneration of the spent oxidizer the values of pH > 10 and moderate concentrations of NaBr should be used.

The evaporation of polymer solution droplet is an important in solution-based polymer film fabrications, such as inkjet print, spray coatings, and droplet casting etc. In this work, we investigated the effect of droplet size, solvent evaporation rate, and concentration on “coffee-ring” effect, crystal nucleation, polymorphism, and morphology of dried poly (vinylidene fluoride) (PVDF) solution droplets with atomic force microscopy (AFM) method. We found that the crystal structure, morphology and crystal distribution in the center and edge regions of dried PVDF droplets were different due to “coffee-ring” effect. The “coffee-ring” effect of dried PVDF droplets was mainly composited of accumulated crystals at the edge region of droplet, which was mainly made by crystallization of migrated chains. The interplay between migration of chains, crystallization and solidification of PVDF droplets significantly influenced the formation of “coffee-ring”. In addition, our results showed that the decrease of droplet size and controlling solvent evaporation rate were effective ways to improve the PVDF β-phase nucleation and decrease crystal size.

A series of polycaprolactones (PCLs) with molecular weights of 950–10,100 g mol−1 and Ð of 1.10–1.87 have been synthesized via one-pot, solvent-free ring-opening polymerization (ROP) of ε-caprolactone (CL) using a heterogeneous double metal cyanide (DMC) catalyst. Various initiators such as polypropylene glycol, ethylene glycol, propylene glycol, glycerol, and sorbitol are employed to tune the number of hydroxyl end groups and properties of the resultant PCLs. Kinetic studies indicate that the DMC-catalyzed ROP of CL proceeds via a coordination mechanism. Branched PCLs copolymers are also synthesized via the DMC-catalyzed copolymerization of CL with glycidol. The α,ω-hydroxyl functionalized PCLs were successfully used as telechelic polymers to produce thermoplastic poly(ester-ester) and poly(ester-urethane) elastomers with well-balanced stress and strain properties.

Let N = N₀+ N₁+ N₂ be a Z₃-graded Novikov algebra. The main goal of the paper is to prove that over a field of characteristic not equal to 3 the algebra N is solvable if N₀ is solvable. We also show that a $Z_2$-graded Novikov algebra N=N₀+ N₂ over a field of characteristic not equal to 2 is solvable if N₀ is solvable. This implies that for every n of the form n=2^k3^l, any Z_n-graded Novikov algebra N over a field of characteristic not equal to 2,3 is solvable if N₀ is solvable.

Dendroclimatology has gained relevance during the XXI century. We analyze the state of-the-art of dendroclimatology in Latin America during the past 28 years (1990 to 2019), identifying the current state and recent advances in the application of dendroclimatology in this region. We carried out a systematic review in ScienceDirect, Web of Science, and Scopus databases using Boolean operators to logically connect the keywords “dendrochronology,” “dendroclimatology,” “trend,” “climatic variability,” and “climatic variability trend”, for each country. Dendroclimatological research conducted in the region focused on climatic reconstruction and the evaluation of new tree species with dendrochronological potential, which increase in 2010, then there was a gap between 1995 and 1996, later increase to present. Dendroclimatological studies in Latin America have been mainly developed in temperate climate zones (82.4 %) followed by tropical or subtropical areas (17.6 %). Dendroclimatological research in Latin America has provided advances in the study of climate variability by defining response functions of tree rings to climate. The generated information allows for a better understanding of the spatial and temporal dynamics of climatic variability and about its effects on ecosystems and society. We also call for increased dendroclimatological research based on subtropical and tropical forests limited studied until today.

Despite the ecological importance of forest tree species, our study was motivated by scarce data on dendrochronology studies limited to the northwestern part of Tajikistan due to lack of access to such a part of the country which is difficult to access. Current studies on Junipers in the northwestern part of Tajikistan identified that tree ring-based climate reconstruction is possible. Cores of Juniperus Turkestanica from Taboshar area, Sogd province were developed into 176-year tree-ring width chronology. In the current study a summer (June-September) minimum temperature reconstruction spanning AD 1840–2016 was developed, which can explain 30.0% of the instrumental variableness for the period of 1940–2015. Five warmest (1856–1866, 1869–1871, 1907–1916, 1923–1935, 1988–2016) and four coldest time periods (1840–1855, 1872–1906, 1917–1922, 1940–1984) were identified. The developed reconstruction coincides with cold and warm periods with prior investigations from tree-rings in China, Mongolia, Kyrgyzstan, Kazakhstan and Tajikistan. Spatial correlation analysis with the gridded minimum temperature data shows that the temperature reconstruction covers geographical representation over High Asia. Significant correlation was found between temperature reconstruction with summer SST, which suggests strong linkages of regional temperature variability with Indian-Ocean climate system. The obtained spectral peaks from the spectral analysis of the summer temperature reconstruction were significantly at 84.7-year (90%), 2.9-year (99%), 2.6-year (99%), 2.5-year (99%), 2.4-year (99%) and 2.2-year (99%).

The recent development of Wearable Exoskeletons has stressed their effectiveness in assisting humans for rehabilitation and augmentation purposes. These devices interact with the user, therefore their actuators and power transmission mechanisms are fundamental for improving physical Human-Robot Interaction (pHRI). The enhanced advancement of 3D-printing technology as a valuable approach for creating light and efficient gearboxes allows for exploring multiple reducers’ designs. However, to the authors’ knowledge, only sporadic implementations with relatively low reduction ratios are reported, and the respective experimental validations usually differ from each other, preventing a comprehensive evaluation of different design and implementation choices. In this paper, we design, develop, and examine experimentally multiple 3D-printed gearboxes conceived for wearable assistive devices. Two relevant transmission ratios (1:30 and 1:80) and multiple designs, that include single and double-stage compact cam cycloidal drives, compound planetary gearboxes, and the series of cycloidal and planetary architectures have been compared to assess the worth of 3D-printed reducers in Human-Robot Interaction applications. The resulting prototypes were examined by evaluating their weight, cost, back-driveability, friction, regularity of the reduction ratio, gear play, and stiffness. The results show that the developed gearboxes represent valuable alternatives for actuating wearable exoskeletons in multiple applications.

3D printing technology has made significant strides in smart textiles—fabrics embedded with electronics like conductive fibers and sensors—now widely applied in areas such as health con-dition monitoring, wearable energy-harvesting devices, and interactive textiles that respond to environmental conditions and color changes. Different 3D printing methods, such as Fused Deposition Modeling (FDM), Selective Laser Sintering (SLS), Direct Ink Writing (DIW), and PolyJet printing, are used in the fabrication of smart textiles. This study provides a detailed, applica-tion-specific overview of 3D printing technologies—such as FDM, SLS, DIW, and PolyJet print-ing—and their use in smart textiles across various sectors, including wearable technology, medical textiles, and smart fashion design. We gathered articles and reports from Scopus and Google Scholar, providing a concise assessment of 3D printing materials for smart textiles to give readers a quick understanding of the field. The timeline of 3D printing’s use in smart textiles, from 2016 to 2023, highlights significant advancements in various additive manufacturing techniques applied to smart textiles. The review emphasizes the importance of understanding 3D printing techniques such as FDM, SLS, DIW, and PolyJet, as their applicability for selecting the best approach to in-corporating advanced functionalities into smart textiles.

The recent growth of wearable medical device technology in the form of fitness trackers, smart watches, smartphone apps, and patient monitoring systems has created people-generated health data (PGHD) that may benefit medical science with large amounts of continuous real-world data. The prevalence of these devices speaks to their broad popularity and user-friendliness and may lead us one day to a more fully “connected healthcare system.” Meanwhile, data security, confidentiality, and privacy issues have emerged in these hackable systems. Despite the promise of anonymized data, data can sometimes be re-identified, but even without that step, data breaches may reveal information (name, address, date of birth, social security number, and so on) sufficient for identity theft. Clinicians are often asked about the utility and value of wearable devices or monitors, but most are unaware that data from these systems may be transmitted, stored, and even sold without the user’s specific knowledge. Despite the confidentiality of medical information, cybersecurity surrounding wearables and monitors remains relatively lax, making them comparatively easy targets for cyber-villains. It is also important that efforts be taken to make PGHD more secure, since medical data may have great value to telehealth applications and AI-physician assistants. Clinicians should take an active role in informing patients about both risks and benefits of wearables and similar devices.

Keywords: Energy harvesting, Hybrid, Medical Wearable Sensor Nodes, Health Monitoring, Power Management

Electroencephalography (EEG) enabled earbuds represent a promising frontier in evaluating brain activity beyond traditional laboratory settings. However, these devices need more comprehensive characterization before widespread health related usage. A toolbox was developed to facilitate and expand the assessment of ear-EEG devices. The first component of this toolbox is a desktop application (“EaR-P Lab”) that integrates EEG validation paradigms. This application is designed to be used with EEG amplifiers compatible with the Lab Streaming Layer (LSL) protocol. The second element of the toolbox introduces an adaptation of the phantom testing concept, to the domain of ear-EEG by using 3D ear scans of the tested individuals, allowing controlled assessment of ear-EEG devices. The EEG paradigms were validated for scalp acquisitions and applied on ear-EEG measurements, under wet ear electrode conditions. The ear-EEG phantom was successful in measuring useful metrics in EEG system characterization, highlighting performance differences within the electrodes on the tested earpieces. This knowledge was factored in to select an optimal electrode reference which resulted in increased response power on the auditory steady-state response (ASSR). Through this work, an ear-EEG evaluation toolkit is made available with the intention to enable future and systematic assessment of novel ear-EEG devices from the hardware to the neural signals.

Background: Accurate estimation of dietary intake is challenging. But whilst some progress has been made in high-income countries, low- and middle-income countries (LMICs) remain behind, contributing to critical nutritional data gaps. This study aimed to validate an objective, passive image-based dietary intake assessment method against weighed food records in London, UK for onward deployment to LMICs. Methods: Wearable camera devices were used to capture food intake of eating occasions in 18 adults and 17 children of Ghanaian and Kenyan origin living in London. Participants were provided pre-weighed meals of Ghanaian and Kenyan cuisine and camera devices to automatically capture images of the eating occasions. Food images were assessed for portion size, energy, and nutrient intake, and relative validity of the method compared to the weighed food records. Results: Pearson and Intra-class correlation coefficient of estimates of intakes of food, energy and 19 nutrients ranged from 0.60 to 0.95 and 0.67 to 0.90, respectively. Bland-Altman analysis showed good agreement between the image-based method and weighed food record. Under-estimation of dietary intake by the image-based method ranged from 4 to 23%. Conclusions: Passive food image capture and analysis provides an objective assessment of dietary intake comparable to weighed food records.

This paper presents a framework to recognize the affective state of children with Autism Spectrum Disorder (ASD) in an in-the-wild setting using Heart Rate (HR) information. Our algorithm classifies a child’s emotion into positive, negative, or neutral states by analyzing the heart rate signal. The HR signal is obtained from a smartwatch in real-time using our smartwatch application. The heart rate data is acquired when the child learns to code a robot while interacting with an avatar that assists the child in communications skills and programming the robot. In this paper, we also present a comparison of using HR data for the classification of emotions with classification based on features extracted from HR signals using Discrete Wavelet Transform (DWT). Our experimental results show that the proposed method produces a comparable performance with the state-of-the-art HR-based emotion recognition techniques, despite the fact that our experiments are performed in an uncontrolled setting as opposed to a lab environment. This work contributes to real-world affect analysis of children with ASD using HR information.

In the last decades, the automatic recognition and interpretation of brain waves acquired by electroencephalographic (EEG) technologies have undergone remarkable growth, leading to a consequent rapid development of Brain Computer Interfaces (BCIs). EEG-based BCIs are non-invasive systems that allow communication between a human being and an external device interpreting brain activity directly. Thanks to the advances in neurotechnologies, and especially in the field of wearable devices, BCIs are now also employed outside medical and clinical applications. Within this context, this paper proposes a systematic review of EEG-based BCIs, focusing on one of the most promising paradigms based on Motor Imagery (MI) and limiting the analysis to applications that adopt wearable devices. This review aims to evaluate the maturity levels of these systems, both from the technological and computational points of view. The selection of papers has been performed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA), leading to 84 publications considered in the last ten years (from 2012 to 2022). Besides technological and computational aspects, this review also aims at systematically list experimental paradigms and available datasets in order to identify benchmarks and guidelines for the development of new applications and computational models.

Consumer rhythm-monitoring devices, such as the Apple Watch, are becoming more readily available. Irregular pulses can be detected using an optical sensor built into the wearable device. The Apple Watch (Apple Inc., Cupertino, CA, USA) is a class II medical device with pulse rate and electrocardiography (ECG) monitoring capabilities. Here we report a case in which an arrhythmia that was conventionally perceived but undiagnosed was identified as atrial fibrillation by self-acquisition of ECG data using an Apple Watch.

The monitoring of maternal and child health, using wearable devices made with wireless sensor technologies, is expected to reduce maternal and child death rates. Wireless sensor technologies have been used in wireless sensor networks to enable the acquisition of data for monitoring machines, smart cities, transportation, asset tracking, and tracking of human activity. Applications based on wireless body area network (WBAN) have been used in healthcare for measuring and monitoring of patient health and activity through integration with wearable devices. Wireless sensors used in WBAN can be cost-effective, enable remote availability, and can be integrated with electronic health record (EHR) management systems. Interoperability of WBAN sensor data with other linked data has the potential to improve health for all, including maternal and child health through the improvement of data access, data quality and healthcare access. This paper presents a survey of the state-of-the-art techniques for managing WBAN sensor data interoperability. The findings in this study will provide reliable support to enable policymakers and health care providers to take action to enhance the use of e-health to improve maternal-child health and reduce the mortality rates of women and children.

Dermal interstitial fluid (ISF) is a novel source of biomarkers that can be considered as an alternative to blood sampling for disease diagnosis and treatment. Nevertheless, in vivo extraction and analysis of ISF are challenging. On the other hand, microneedle (MN) technology can address most of the challenges associated with dermal ISF extraction and is well-suited for long-term, continuous ISF monitoring as well as in situ detection. In this review, we first briefly summarise the different dermal ISF collection methods and compare them with MN methods. Next, we elaborate on the design considerations and biocompatibility of MNs. Subsequently, the fabrication technologies of various MNs used for dermal ISF extraction, including solid MNs, hollow MNs, porous MNs and hydrogel MNs, are thoroughly explained. In addition, different sensing mechanisms of ISF detection will be discussed in detail. Subsequently, we identify the challenges and propose the possible solutions associated with ISF extraction. A detailed investigation is provided for the transport and sampling mechanism of ISF in vivo. Also, the current in vitro skin model integrated with the MN arrays will be discussed. Finally, future directions to develop a point-of-care (POC) device to sample ISF are proposed.

Stress has been identified as one of the major causes of automobile crashes which then lead to high rates of fatalities and injuries each year. Stress can be measured via physiological measurements and in this study the focus will be based on the features that can be extracted by common wearable devices. Hence the study will be mainly focusing on the heart rate variability (HRV). This study is aimed to develop a good predictive model that can accurately classify stress levels from ECG-derived HRV features, obtained from automobile drivers, testing different machine learning methodologies such as K-Nearest Neighbor (KNN), Support Vector Machines (SVM), Multilayer Perceptron (MLP), Random Forest (RF) and Gradient Boosting (GB). Moreover, the models obtained with highest predictive power will be used as reference for the development of a machine learning model that would be used to classify stress from HRV features derived from HRV measurements obtained from wearable devices. We demonstrate that MLP was the ideal stress classifier by achieving a Recall of 80%. The proposed method can be also used on all applications in which is important to monitor the stress level e. g. in physical rehabilitation, anxiety relief or mental wellbeing.

Regular exercise can reduce depression. However, the uptake of exercise is limited in patients with end-stage renal disease undergoing hemodialysis. To address the gap, we designed a gamified non-weight-bearing exercise program (Exergame), which can be executed during hemodialysis treatment. The Exergame is virtually supervised based on its interactive feedback via wearable sensors attached on lower extremities. We examined the effectiveness of this program to reduce depression symptom compared to supervised exercise in 73 hemodialysis patients (age=64.5±8.7years, BMI=31.6±7.6kg/m2). Participants were randomized into an Exergame group (EG) or a Supervised-exercise group (SG). Both groups received similar exercise tasks for 4-week, 3-session per week, 30-min per session, during hemodialysis treatment. Depression symptom was assessed at baseline and 4-week using Center for Epidemiologic Studies Depression (CES-D). Both groups showed significant reduction in depression score (37%, p<0.001, Cohen’s effect size d=0.69 in EG vs. 41%, p<0.001, d=0.65 in SG) with no between-group difference for the observed effect (p>0.050). The EG expressed a positive exercise experience including fun, safety, and helpfulness of sensor-feedback. Together, results suggested that the virtually-supervised low-intensity Exergame is feasible during routine hemodialysis treatment. It is as effective as supervised-exercise to reduce depression symptom, while reducing burden of administrating exercise in dialysis clinics.

As the rapid development of communication industry, especially the 5G communication and IOT, there will be plenty of electromagnetic (EM) waves in the free space, which carry lots of energies. However, some of these energies are wasted in free space. To reuse these wasted energies, significantly growing interests are towards to the energy harvesting antennas. This paper is aimed to investigate a wearable antenna which can transfer RF energy from ambient sources to direct current by a soft and portable textile antenna. Among the numerous signals in mobile network, the GSM 1800, 3G, WiFi and 4G/5G will be chosen due to the city signal intensity distribution. Hence, a corresponding triple bands antenna has been designed to cover those frequency bands. The CST STUDIO SUITE is used in whole process of antenna design and simulation. The proposed antenna is a hooked dipole antenna with tuning bar (HATB) whose ends have small folded part in each side for better bandwidth performance. The presented antenna provides a wide operating band from 1.8 GHz to 2.5 GHz below -10 dB in return loss. And methods to overcome interference between antennas is found. Furthermore, using the corresponding rectifier to achieve the RF/DC conversion. The overall efficiency of whole rectifier is about 56.8 %, and output power level of the antenna system is 45.92nW. The experimental results could indicate that my textile hooked antenna harvester is a good choice for the charging system of personal wearable attachment, which could achieve low power absorbing for long distance anytime and anywhere.

Vascular rings are a rare congenital anomaly of the aortic arch in which a ring-shaped structure forms surrounding the trachea and/or esophagus, potentially causing compression. We describe the case of a 14-month-old female patient with failure to thrive secondary to dysphagia, and a vascular ring formed by a right aortic arch, an aberrant left subclavian artery, and a left liga-mentum arteriosum. Surgical repair involved ligamentum arteriosum division, Kommerell’s di-verticulum obliteration, and left subclavian artery re-implantation into the left carotid artery. Endoscopy and EndoFLIPTM evaluated intraoperative improvement in esophageal narrowing and impedance, respectively. Postoperative period was uneventful and follow-up visits demonstrated dysphagia resolution and a patent re-implanted left subclavian artery.

Let a,b,c be positive integers such that a²+b²=c², 2|b,gcd(a,b)=1. In 1956, Jesmanowicz conjectured that for any positive integer w, the only solution of (aw)^x+(bw)^y=(cw)^z in positive integers is (x, y, z) = (2, 2, 2). In this paper, based on Gaussian integer ring, we show that Je$\acute{s}$manowicz' conjecture is true for any positive integer

Abstract Background Context Pelvic ring fractures are becoming more common in the aging population and can prove to be fatal, having mortality rates between 10% and 16%. Stabilization of these fractures is challenging and often require immediate internal fixation. Therefore, it is necessary to have a biomechanical understanding of the different fixation techniques for pelvic ring fractures. Methods A previously validated three-dimensional finite element model of the lumbar spine, pelvis, and femur was used for this study. A unilateral pelvic ring fracture was simulated by resecting the left side of the sacrum and pelvis. Five different fixation techniques were used to stabilize the fracture. A compressive follower load and pure moment was applied to compare different biomechanical parameters including range of motion (contralateral sacroiliac joint, L1-S1 segment, L5-S1 segment), and stresses (L5-S1 nucleus stresses, instrument stresses) between different fixation techniques. Results Transiliac -trans sacral screw fixation at S1 and S2 showed the highest stabilization for horizontal and vertical displacement at the sacral fracture site and reduction of contralateral sacroiliac joint for bending and flexion range of motion by 165% and 121%, respectively. DTSF (Double transiliac rod and screw fixation) model showed highest stabilization in horizontal displacement at the pubic rami fracture site, while the L5_PF_W_CC (L5-Ilium posterior screw fixation with cross connectors) and L5_PF_WO_CC ( L5-Ilium posterior screw fixation without cross connectors) showed higher rod stresses, reduced L1-S1 (approximately 28%), and L5-S1 (approximately 90%) range of motion. Conclusions Longer sacral screw fixations were superior in stabilizing sacral and contralateral sacroiliac joint range of motion. Lumbopelvic fixations displayed a higher degree of stabilization in the horizontal displacement compared to vertical displacement of pubic rami fracture, while also indicating the highest rod stresses. When determining the surgical approach for pelvic ring fractures, patient-specific factors should be accounted for to weigh the advantages and disadvantages for each technique.

Throughout this paper, we will establish a comprehensive theoretical foundation and rigorously develop the methodology to investigate the structure of quotient ring S/P under the influence of symmetric generalized n-derivations, where S represents an arbitrary ring, and P signifies a prime ideal of S satisfying certain algebraic identities acting on prime ideal P without relying on the assumption of primeness or semi-primeness of the ring.

Large aluminum alloy ring forgings are the core components of heavy-duty rocket fuel storage tanks, and the large residual stress inside the rings leads to poor shape accuracy of large thin-walled parts. The initial stress of the 2219 aluminum alloy ring blank was tested using the drilling method, and the creep constitutive coefficient of the 2219 aluminum alloy was determined through stress relaxation tests. The numerical simulation processes of thermal stress relief (TSR), vibration stress relief (VSR), and thermal-vibration stress relief (TVSR) were compared and established. Through the correlation analysis between the actual measurement results of residual stress and the simulation results, it can be seen that the strong correlation in three directions at each measurement point accounts for over 37.5%, and the moderate correlation accounts for over 62.5%. This indicates that the numerical simulation model of 2219 aluminum alloy ring containing initial residual stress can accurately reflect the size and distribution of residual stress inside the actual ring. The simulation results show that the derived constitutive model can describe the stress relaxation process of TVSR by combining a single thermal time effect stress relaxation constitutive theory with a VSR plastic deformation material model. The simulation models established above were used to calculate the residual stress homogenization ability of three types of aging. The results showed that VSR, TSR, and TVSR can homogenize and reduce the residual stress field inside the ring, improve the distribution of residual stress inside the ring, and have a better overall homogenization ability of TVSR. The VSR control has a certain effect on reducing and homogenizing residual stress, but compared with TSR and TVSR, the reduction and homogenization ability of residual stress control is limited. The homogenization control effect TVSR>TSR>VSR, and the maximum equivalent stress homogenization rates of VSR, TSR, and TVSR are 52.8%, 80.6%, and 82.2%, respectively. Then, numerical simulation technology is used to study how the initial residual stress in the blank will cause the deformation of the ring during the thin-walled machining process. The roundness error theory of the minimum containment area method is applied to evaluate the deformation degree during the thin-walled numerical machining process, and the TVSR method is used for stress regulation. The deformation law of the thin-walled machining of the ring under different aging parameters is studied.

The development of antimicrobial resistance to conventional antibiotics is a major global health challenge. Infections caused by multidrug-resistant gram-negative bacteria have been named one of the most urgent global health threats. Considerable efforts are devoted to developing new antibiotic drugs and investigating the mechanism of antibiotic resistance. Recently, Anti-Microbial Peptides (AMPs) have emerged as a new platform for the target and design of novel drug resistant anti-microbial agents promising a new therapeutic strategy. AMPs are rapid, potent, possess an unusually broad spectrum of activity, and have shown efficacy as topical agents. Unlike traditional therapeutics that interfere with essential bacterial enzymes, AMPs interact with microbial membranes through electrostatic interactions and physically damage cell integrity. However, naturally occurring AMPs have limited selectivity and modest efficacy. Therefore, recent efforts have focused on the development of synthetic AMP analogs as suitable drug targets. This work explores the development of novel antimicrobial agents which mimic the structure of graft-copolymers and mirror the mode of action of an AMP. Chitosan-graft-polypeptide side chains are synthesized by the ring-opening polymerization of N-carboxyanhydrides of L-lysine and L-leucine initiated from the functional groups of chitosan. The derivatives with random- and block-copolymer side chains are explored as drug targets. These graft copolymer systems exhibit activity against clinically significant pathogens and disrupt biofilm formation. This work highlights the potential of chitosan-graft-polypeptide structures in biomedical applications.

In this note we, first, recall that the sets of all representatives of some special ordinary residue classes become $\left( m,n\right) $-rings. Second, we introduce a possible $p$-adic analog of the residue class modulo a $p$-adic integer. Then, we find the relations which determine, when the representatives form a $\left( m,n\right) $-ring. At the very short spacetime scales such rings could lead to new symmetries of modern particle models.

The aim of this work is to propose two different and complementary sensors for the structural health monitoring of concrete beams. In particular, a diffused sensing element and a split ring resonator network are presented. The first sensor is able to detect the variation of the dielectric properties of the concrete along the whole beam length, for a diffuse monitoring both during the important concrete curing phase and also for the entire life cycle of the concrete beams. The resonators instead work punctually, in their surroundings, allowing an accurate evaluation of the permittivity both during the drying phase and after. This allows the continuous monitoring of any presence of water both inside the concrete beam and in points that can be critical, in the case of beams in dams, bridges or in any case subject to a strong presence of water which could lead to deterioration, or worse, cause serious accidents. Moreover, the punctual sensors are able to detect the presence of cracks in the structure and to localize them.

In this work, generalized geometry of second-order tangent groups and affine configuration complexes is proposed. Initially, geometry for higher weights n=4 and weights n=5 is presented through some interesting and suitable homomorphisms, finally, this geometry is extended and generalized for any weight n.

Biomedical sensors have revolutionized healthcare by offering advanced tools for real-time disease diagnosis, continuous monitoring, and effective treatment. These sensors encompass various technologies, including biosensors, nanotechnology-based sensors, flexible and wearable devices, and more, all of which have played a pivotal role in modernizing medical practices. This review delves into the evolution, types, and technological advancements, along with their broad applications in healthcare, such as in molecular informatics, genomics, proteomics, and personalized medicine. The primary objective of this review is to provide a comprehensive overview of the current landscape, highlighting the latest technological innovations, diverse applications, and potential future trends. The review seeks to demonstrate the critical role these sensors play in enhancing diagnostic accuracy, treatment efficacy, and overall patient care. This review methodically examines various biomedical sensor technologies, focusing on advancements such as microfabrication techniques, nanotechnology, and the development of biocompatible materials. The analysis also covers the miniaturization of sensors, their portability, and the integration of these devices with the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) to improve healthcare outcomes. These sensors are widely used in wearable and implantable devices for continuous monitoring of vital signs, disease diagnosis, and therapeutic interventions. Notable applications include diabetes management, cardiovascular monitoring, and cancer detection. Emerging trends are set to further enhance the capabilities and applications of these sensors. Despite challenges such as biocompatibility, data privacy, and regulatory hurdles, ongoing research and innovation will likely overcome these barriers, ensuring that biomedical sensors, improve patient outcomes, and facilitate more personalized medical interventions.

Recent developments in flexible printed heaters (FPH) for wearable thermal applications, driven by the advancement of printed electronics, show great promise in revolutionizing patient care through the development of wearable flexible heaters for medical applications. Wearable heaters with high thermal stability, heat uniformity, safety, flexibility, comfort, biocompatibility, and power efficiency are desirable for stand-alone medical thermotherapy applications. This paper reviews recent advancements in the design of FPHs for wearable thermal applications. Materials for FPHs, fabrication methods, designs, temperature control mechanisms, medical applications, and performance analysis of specific FPHs are all thoroughly discussed. Materials for FPHs, such as conductive and substrate materials, have received special attention, along with the heater design parameters. Finally, the challenges and future directions for developing FPHs for wearable medical applications are addressed.

(1) Background: Heart rate variability (HRV) has emerged as a potential prognostic tool in cardiovascular diseases, offering individualized insights into autonomic nervous system activity. However, real-time HRV data during the acute phase of STEMI, particularly during percutaneous coronary intervention (PCI), was not previously explored. (2) Methods: This single-center, observational cohort study included 104 STEMI patients undergoing primary percutaneous coronary intervention (PCI). HRV parameters were measured using a wearable device (CE marked) during PCI, capturing dynamic responses. The association between HRV parameters and adverse outcomes, including in-hospital mortality and major adverse cardiovascular events (MACE), were assessed. (3) Results: HRV parameters significantly decreased after myocardial revascularization, particularly SDNN, RMSSD, pNN50, HF, SD1, and SD2/SD1 ratio. Significant associations were found between reduced SD2/SD1 ratio, approximate entropy, and adverse outcomes, including increased in-hospital mortality and MACE. The SD2/SD1 ratio was significantly lower in patients who died during the hospital stay (p = 0.008) compared to survivors. Approximate entropy was also significantly lower in deceased patients (p = 0.019). (4) Conclusions: Real-time HRV monitoring using wearable technology offers valuable data regarding dynamic physiological changes during primary PCI. The integration of HRV into routine clinical practice, facilitated by wearable devices, could improve the risk stratification and event prediction in STEMI patients.

The graphene based highly conductive and flexible devices has received momentous attraction and growth in recent years for potential multifunctional uses. The development of flexible and washable textile sensors, actuators, energy storage and energy harvesting systems. Textile fabrics coated with graphene and conductive polymers have been used for wearable self-powered e-textiles, such as tribo-electric, piezoelectric, and Thermoelectric. Herein this research, 100% woven cotton fabric is Fictionalized with graphene oxide (GO) using industrial-scale cold pad batch dyeing technique for the development of low-grade body heat into self-powered wearable e-textiles. The conductive polymer PEDOT: PSS was coated using layer by layer approach. The study demonstrates that the resultant textile electrodes showed reduced electrical sheet resistance from 2.5 MΩ to 15KΩ, with a reduced graphene oxide and further reduced to (2.5 -12.5 Ω) for conductive polymer. The sheet resistance was decreased with the number of dyeing cycles (10-15) and increased with 20 washing cycles vice versa. The study demonstrates that the sensor response and performance were improved with increasing the content percent of rGO and PEDOT: PSS. The tensile strength of as coated fabric electrodes was improved from (25.0-85.5 mPa) and fabric thickness was increased to (26-38µm) without compromising or influencing the air permeability. The resultant textile electrodes may potentially be used in smart textiles for self-powered flexible wearable generators, sensors, and energy storage. The study demonstrates that the cold pad batch dyeing method is a suitable and effective method for the fabrication of graphene-based textiles.

Previous studies to recognize negative emotions (e.g. disgust, fear, sadness) for mental health care have used heavy equipment directly attaching electroencephalogram (EEG) electrodes to the head, making it difficult to use in daily life, and they have proposed binary classification methods to determine whether negative emotion or not. To tackle this problem, we propose a negative emotion recognition system to collect multimodal biosignal data such as five EEG signals in an EEG headset and heart rate, galvanic skin response, and skin temperature in a smart band for classifying multiple negative emotions. It consists of android Internet of Things (IoT) application, an oneM2M-compliant IoT server, and a machine learning server. The android IoT application upload the biosignal data to the IoT server. By using the biosignal data stored in the IoT server, the machine learning server recognizes the negative emotions of disgust, fear, and sadness using a multi-class support vector machine (SVM) model with a radial basis function kernel (RBF). The experimental results showed that the multi-class SVM model achieved 93% accuracy when considering all the multimodal biosignal data. Moreover, when considering only data in the smart band, it could achieve 98% accuracy by optimizing the hyper-parameter of the RBF kernel.

Nowadays, fostered by technological progress and contextual circumstances such as economic crisis and pandemic restrictions, remote education is living a growing deployment. However, this growth generated widespread doubts about the actual effectiveness of remote/online compared to face-to-face education. The present study aimed at comparing face-to-face and remote education through a multimodal neurophysiological approach. It involved forty students at a driving school, during a real classroom, experiencing both the modalities. Wearable devices to measure brain, ocular, heart and sweating activities were employed in order to analyse the students’ neurophysiological signals to obtain insights about their cognitive dimension. In particular, four parameters were considered, the Eye Blink Rate, the Heart Rate and its Variability and the Skin Conductance Level. Also, the students filled a questionnaire at the end to obtain an explicit measure of their learning performance. Data analysis showed a higher cognitive activity, in terms of attention and mental engagement, in presence with respect to remote modality. On the other hand, students by remote felt more stressed, in particular during the first part of the lesson. Analysis of questionnaires demonstrated worst performance by remote, thus suggesting a common “disengaging” behaviour when attending remote courses, thus undermining their effectiveness. In conclusion, neuroscientific tools could help to obtain insights about mental concerns, often «blind», such as attentional decreasing and stress increasing, as well as their dynamics during the lesson itself, so allowing to define proper countermeasures to emerging issues when introducing new practices into daily life.

This study aims to explore the effect of real-time visual feedback (VF) information of the pres-sure of center (COP) provided by intelligent insoles on balance training in a one leg stance (OLS) and tandem stance (TS) posture. Thirty healthy female college students were randomly assigned to the visual feedback balance training group (VFT), non-visual feedback balance training group (NVFT), and control group (CG). The balance training includes: OLS, tandem Stance (dominant leg behind, TSDL), tandem stance (non-dominant leg behind, TSNDL). The training lasted 4 weeks, the training lasts 30 minutes at an interval of 1 days. There was a sig-nificant difference in the interaction effect between Groups*Times of the COP parameters (p<0.05) for OLS. There was no significant difference in the interaction effect between Groups*Times of the COP parameters (p>0.05) for TS. The main effect of the COP parameters was a significant difference in Times (p<0.05). The COP displacement, velocity, radius, and area in VFT significantly decreased after training (p < 0.05). Therefore, the visual feedback technology of intelligent auxiliary equipment during balance training can enhance the benefit of training. The use of smart wearable devices in OLS balance training may improve the visual and physical balance integration ability.

The consequences of a fall on an elderly person can be reduced if the accident is attended by medical personnel within the first hour. Independent elderly people use to stay alone for long periods of time, being in more risk if they suffer a fall. The literature offers several approaches for detecting falls with embedded devices or smartphones using a triaxial accelerometer. Most of these approaches were not tested with the target population, or are not feasible to be implemented in real-life conditions. In this work, we propose a fall detection methodology based on a non-linear classification feature and a Kalman filter with a periodicity detector to reduce the false positive rate. This methodology requires a sampling rate of only 25 Hz; it does not require large computations or memory and it is robust among devices. We test our approach with the SisFall dataset achieving 99.4% of accuracy. Then, we validate it with a new round of simulated activities with young adults and an elderly person. Finally, we give the devices to three elderly persons for full-day validations. They continued with their normal life and the devices behaved as expected.

The dynamic beam equations provide an analytical model and a generic solution for continuous systems. The constants for amplitudes and frequencies are given by the boundary conditions, which are here considered looped, in order to represent a closed element, by topological closure. This type of model is applied to the representation of a semicircular canal. This approach addresses the deformability of this anatomical element, both in Lagrangian solid parts (bone, membranes, intermediate materials) and in fluids (Eulerian pressure waves). The model is proposed for both physiological representation and pathology modeling. The latter is represented by a passive or retroactive singularity. An original analytical approach is thus developed for each segment, representing physiological modes – nodes and bellies - and possible disturbances. The damping entropy is also the subject of a special segmented treatment, to take account of fluid-solid interactions, providing a coherent model. The result is a simplified but robust model that both reproduces the vibro-acoustic modes of the semicircular canal and anticipates the effects of a singular pathology, such as a third window or neuritis. Mathematically, this model opens the way to structural analytical models of the inner ear, and to possible dynamic couplings between equilibration and acoustics.

We hypothesize that the first ancestral "ante-cell" molecular structures, i.e., first RNAs and peptides which gradually transformed into real cells once the Earth had cooled sufficiently for organic molecules to appear there, have leaved traces in RNAs and genes of present cells. We propose a circular RNA which could have been one of these ancestral structures whose vestigial pentameric subsequences would mark the evolution from this key moment when the ante-cells have begun to join the living organisms. In particular, we propose that in present RNAs (ribosomal or messenger) playing an important role in the metabolism of current cells, we look for traces of the proposed primitive structure in the form of pentamers (or longer fragments) belonging to their nucleotide sequence. The result obtained can be summarized in the existence of a gradient of occurrence of such pentamers, with a high frequency for the most vital functions (protein synthesis, nucleic synthesis, cell respiration, etc.). This gradient is also visible between organisms, from the oldest (Archaea) to the most recent (Eukaryotes) in evolution of species.

In this study, we successfully synthesized a novel branched polyamide 6 with ε-caprolactam(CPL) and α-Amino-ε-caprolactam(ACL) through hydrolytic ring-open co-polymerization. The NMR characterization and rheological test result proved the existence of branched chain structure additionally. The branched chain structure caused a remarkable enhancement in the rheological properties. The met index(MFR),zero shear rate viscosity and storage modulus at low frequency region had a remarkable increase.The shear thinning phenomenon became more obvious. The thermal properties test determined by differential scanning calorimetry(DSC) showed that the melting point and crystallinity of co-polymers decreased with the increase of ACL addition.However, the crystal structure of the samples remained unchanged. The appropriate addition amount of ACL can improve the tensile mechanical properties of the co-polymers. When the amount of ACL was 1%, the tensile strength and fracture elongation rate of the co-polymers had the most significant increase.

A review on planar printed structures that are based on Matryoshka-like geometries is presented. These structures use the well-known principle of Matryoshka dolls that are successively nested inside each other. The well-known advantages of the planar printed technology and of the meandered nested Matryoshka geometries are combined to generate miniaturized, multi-resonance and/or wideband configurations. Both metal and complementary slot structures are considered. Closed and open configurations are analyzed. The working principles are explored do get physical insight of their behavior. Low cost and single layer applications as frequency selective surfaces, filters, antennas, and sensors, in the microwave frequency region, are reviewed. Potential future research perspectives and new applications are discussed.

Banking sectors commit modern working frameworks and models smooth development based on decentralization with keeping money confront in unused ranges and differing activities. Consortium Blockchain Privacy becomes a major concern and the challenge of Most of banking sectors.Development without being hampered being a major concern it can store confirmed, Data privacy includes assuring protection for both insider ad outsider threats therefore access control of Ring signature could help to secure Privacy of inside and outside threats by secure process by RSBAC using CIA triad privacy Confidentiality, Availability, Integrity.This paper proposes a ring signature-based on access control mechanism for determining who a user is and then regulating that person's access to and use of a system's resources. In a nutshell, access control restricts who has access to a system. It also restricts access to system resources to users who have been identified as having the necessary privileges and permissions. The proposed paradigm satisfies the needs of both workflow and non-workflow systems in an enterprise setting. The traits of the conditional purposes, roles, responsibilities, and policies provide the foundation for it. It ensures that internal risks such as database administrators are protected.Finally, it provides the necessary protection in the event that the data is published.

In particle physics, spin is an intrinsic form of angular momentum carried by the elementary particles. It is believed that spin is a solely quantum-mechanical phenomenon, which does not have a counterpart in classical mechanics. We have derived the simplest equations of spin and magnetic moment of a charged elementary particle. These formulas enable us to understand the physical nature of the spin and the structure of elementary particles. It is shown that the electron and muon are in the shape of a thin ring with a circular cross section (torus), and the proton is in the form of a ring with a non-circular cross section (toroid). The connection between the photon’s spin of and the propagation of electromagnetic waves is considered.

Capacitor banks are widely used in current electrical transmission systems in order to improve power quality and increase efficiency. Utilizing high voltage components such as, shunt capacitors in the power grid imposes new challenges to the system which are required to be addressed. One of these challenges is corona discharges that can have negative impacts on capacitor banks such as power loss, insulator erosion followed by equipment failure, and radio interference. Although previous studies have almost exclusively focused on optimization of corona suppression rings for transformers and transmission lines, no specific studies have conducted regarding high voltage capacitor banks. This paper presents a novel study concerning verification and development of corona discharge suppression models on AC and DC capacitor banks with two different voltage levels. The employed method is based on the Maxwell’s equations and finite element method (FEM) which is implemented with the help of COMSOL Multiphysics© software. Results have verified the necessity of suppression methods as well as the efficiency of proposed solutions. Corona inception voltage levels are identified and effective factors on its appearance are reviewed. Analyses of proposed solutions have shown significant improvements in optimization of corona suppression methods as well as enhancement of maintenance maneuverability.

The absolute absorption cross section of the ethyl peroxy radical, C2H5O2, in the Ã←X ̃ electronic transition with the peak wavelength at 7596 cm-1, has been determined by the method of dual wavelengths time resolved continuous wave cavity ring down spectroscopy. C2H5O2 radicals were generated from pulsed 351 nm photolysis of C2H6/Cl2 mixture in presence of O2 and detected on one of the CRDS paths. Two methods have been applied for the determination of the C2H5O2 absorption cross section: (i) based on Cl-atoms being converted alternatively to either C2H5O2 by adding C2H6 or to hydro peroxy radicals, HO2, by adding CH3OH to the mixture, whereby HO2 was reliably quantified on the second CRDS path in the 21 vibrational overtone at 6638.2 cm-1 (ii) based on the reaction of C2H5O2 with HO2, measured under either excess HO2 or under excess C2H5O2 concentration. Both methods lead to the same peak absorption cross section of C2H5O2,7596 cm-1 = (1.0±0.2) × 10-20 cm2. The rate constant for the cross reaction between of C2H5O2 and HO2 has been measured to be (6.5±1.6) × 10-12 cm3 molecule-1 s-1.

This paper is a thorough review of innovative architectures of electro-hydraulic servovalves that exploit actuation systems based on piezo-electric materials. The use of commercially available piezo-electric actuators, namely, piezo-stacks, amplified piezo-stacks, rectangular benders and ring benders, is very promising for the actuation of the main stages and of the pilot stages of servovalves, given the fast response and low weight of piezoelectric materials. The use of these actuators can also allow novel designs to be developed, thus helping manufacturers to overcome the typical drawbacks of commercial servovalves, such as the high complexity and the high internal leakage of the pilot stages of two stage servovalves, as well as the large size and weight of direct drive servovalves. Firstly, the piezoelectric actuators that can be used for driving servovalves are presented in the paper and their characteristics are thoroughly discussed. Then, the main novel architectures present in the literature are explained and compared with the commercial ones, and their performance parameters are discussed to draw conclusions on the prospect that some of these architectures can be used by manufacturers as future designs.

The advancement of performance in the domain of flexible wearable strain sensors has become increasingly significant due to extensive research on laser-induced graphene (LIG). An innovative doping modification technique is required owing to the limited progress achieved by adjusting laser parameters to enhance LIG’s performance. By pre-treating with AgNO3, we successfully manufactured LIG with a uniform dispersion of silver nanoparticles across its surface. The experimental results for the flexible strain sensor exhibit exceptional characteristics, including low resistance (183.4 Ω), high sensitivity (426.8), a response time of approximately 150 ms, and a relaxation time of about 200 ms. Moreover, this sensor demonstrates excellent stability under various tensile strains and remarkable repeatability during cyclic tests lasting up to 8,000 s. Additionally, this technique yields favorable results in finger bending and hand back stretching experiments, holding significant reference value for preserving the inherent characteristics of LIG preparation in a single-step and in situ manner.

Currently, old-style personal medicare techniques rely mostly on traditional methods, such as cumbersome tools and complicated processes, which can be time-consuming and inconvenient in some circumstances. Furthermore, such old methods need the use of heavy equipment, blood draws, and traditional bench-top testing procedures. Invasive ways of acquiring test samples can potentially cause patients discomfort and anguish. Wearable sensors, on the other hand, may be attached to numerous body areas to capture diverse biochemical and physiological characteristics as a developing analytical tool. Physical, chemical, and biological data transferred via the skin is used to monitor health in various circumstances. Wearable sensors can assess the aberrant conditions of the physical or chemical components of the human body in real-time, exposing the body state in time, thanks to unintrusive sampling and high accuracy. Most commercially available wearable gadgets are mechanically hard components attached to bands and worn on the wrist, with form factors ultimately constrained by the size and weight of the batteries required for the power supply. Wearable gadgets with “skin-like” qualities are a new type of automation that is only starting to make its way out of research labs and into pre-commercial prototypes. In this paper, we studied the recent advancement in battery-powered wearable sensors established on optical phenomena and skin-like battery-free sensors which brings a breakthrough in wearable sensing automation.

Wearable cardiac sensors pave the way to advanced cardiac monitoring applications based on heart rate variability (HRV). In real-life settings, heart rate (HR) measurements are subject to mo-tion artifacts that can be timely removed from the recordings. This leads to frequent data loss in the HR signal, especially for commercial devices based on photoplethysmography (PPG). The cur-rent study had two main goals: (i) to provide a white-box quality index that estimates the amount of missing samples in any piece of HR signal; and (ii) to quantify the impact of data loss on feature extraction in a PPG-based HR signal. This was done by comparing real-life recordings from com-mercial sensors featuring both PPG (Empatica E4) and ECG (Zephyr BioHarness 3). After an out-lier rejection process, our quality index was used to isolate portions of ECG-based HR signal that could be used as benchmark, to validate the output of Empatica E4 at the signal level and at the feature level. Our results showed high accuracy for estimating the mean HR, poor accuracy for short-term HRV features and moderate accuracy for longer-term HRV features. Levels of error could be substantially reduced by using our quality index to identify time windows with few or no missing data.

Background: Limited research has been done to measure ambulatory respiratory behavior, in particular those associated with tobacco use, in the natural environment due to a lack of monitoring techniques. Respiratory topography parameters provide useful information for modelling particle deposition in the lung and assessing exposure risk and health effects associated with tobacco use. Commercially available Wearable Respiratory Monitors (WRM), such as the Hexoskin Smart Garment, have embedded sensors which measure chest motion and may be adapted for measuring ambulatory lung volume. Methods: Self-reported ‘everyday’ and ‘some days’ Hookah and Cigarette smokers were recruited for a 3-day natural environment observation study. Participants wore the Hexoskin shirt while using their preferred tobacco product. The shirt was calibrated on them prior to, during, and after the observation period. A novel method for calculating the calibration parameters is presented. Results: N=5 Hookah and N=3 Cigarette participants were enrolled. Calibration parameters were obtained and applied to the observed chest motion waveform from each participant to obtain their lung volume waveform. Respiratory topography parameters were derived from the lung volume waveform. Conclusion: The feasibility of using the Hexoskin for measuring ambulatory respiratory topography parameters in the natural environment is demonstrated..

The deterioration of gait can be used as a biomarker for ageing and neurological diseases. Continuous gait monitoring and analysis are essential for early deficit detection and personalized rehabilitation. The use of mobile and wearable inertial sensor systems for gait monitoring and analysis have been well explored with promising results in the literature. However, most of these studies focus on the technologies for gait characteristic assessment, few of them have considered the data acquisition bandwidth of the sensing system. Inadequate sampling frequency will sacrifice signal fidelity, thus leading to an inaccurate estimation especially for spatial gait parameters. In this work, we developed an inertial sensor based in-shoe gait analysis system for real-time gait monitoring and investigated the optimal sampling frequency to capture all the information on walking patterns. An exploratory validation study was performed using an optical motion capture system on four healthy adult subjects, where each person underwent five walking sessions, giving a total of 20 sessions. Percentage mean absolute errors (MAE%) obtained in stride time, stride length, stride velocity, and cadence while walking were 1.19%, 1.68%, 2.08%, and 1.23%, respectively. In addition, an eigen-analysis based graphical descriptor from raw gait cycle signals was proposed as a new gait metric that can be quantified by principal component analysis to differentiate gait patterns, which has great potential to be used as a powerful analytical tool for gait disorder diagnostics.

This paper presents a system developed for the assistance with a collaborative robot in hand-assisted laparoscopic surgery (HALS). The system includes a sensing glove with piezoresistive sensors which capture continuously the flexion degree of the surgeon's fingers. These data are analyzed using an algorithm that detects and recognize the selected movements. This information is sent as commands to the collaborative robot throughout the surgical operation. The bending patterns, speed and execution times of the movements are modelled in a pre-phase in which it will extract all the necessary information for later detection during the motion execution. The results obtained with 10 different volunteers show a high degree of accuracy and a low false discovery rate.

For engines operating with heavy fuel oil (HFO), the nozzle rings of the turbocharger turbines are prone to severe degradation in terms of contamination with unburned fuel deposits. This contamination may lead to increased excitation of blade resonances. A previous study provides technical guidelines on how to extract the relevant information from the pulsation spectra by means of a single probe installed away from the turbine trailing edge and some sound experimental proofs of integral mode turbine vibration detection. These theoretical discussions only allude to the effects of mistuning and interferences due to classical blade passing frequencies on sound radiation patterns emitted by integral blade vibration modes. In this paper, both effects are thoroughly discussed. Combining the knowledge of theoretical study and further experimental results, the application range of this blade vibration detection method can be remarkably extended.

Layered two-dimensional (2D) graphene oxide (GO) films are integrated with micro-ring resonators (MRRs) to experimentally demonstrate enhanced nonlinear optics in the form of four-wave mixing (FWM). Both uniformly coated and patterned GO films are integrated on CMOS-compatible doped silica MRRs using a large-area, transfer-free, layer-by-layer GO coating method together with photolithography and lift-off processes, yielding precise control of the film thickness, placement, and coating length. The high Kerr nonlinearity and low loss of the GO films combined with the strong light-matter interaction within the MRRs results in a significant improvement in the FWM efficiency in the hybrid MRRs. Detailed FWM measurements are performed at different pump powers and resonant wavelengths for the uniformly coated MRRs with 1−5 layers of GO as well as the patterned devices with 10−50 layers of GO. The experimental results show good agreement with theory, achieving up to ~7.6-dB enhancement in the FWM conversion efficiency (CE) for an MRR uniformly coated with 1 layer of GO and ~10.3-dB for a patterned device with 50 layers of GO. By fitting the measured CE as a function of pump power for devices with different numbers of GO layers, we also extract the dependence of GO’s third-order nonlinearity on layer number and pump power, revealing interesting physical insights about the evolution of the layered GO films from 2D monolayers to quasi bulk-like behavior. These results confirm the high nonlinear optical performance of integrated photonic resonators incorporated with 2D layered GO films.

Globally, life expectancy has been increasing, with South Korea reaching an average of 85.6 years. Therethrough, ‘being healthy’ is essential for a high quality of life, and interest in health and disease prevention grew significantly after the COVID-19 pandemic. The pandemic boosted digital health technology adoption, and emphasizing the need for tailored health strategies based on age group. KIHASA conducted the study of digital confidence and health management methods involving the use of digital devices, and it examines differences in digital device use and confidence between 359 young adults (20–39Y) and 641 middle-aged adults (40–69Y). Respondents were asked about their use of digital health tools, such as wearable devices and mobile apps and confidence in using digital systems and managing health via digital tools was assessed using a five-point Likert scale. We an-alyzed the results, and it indicated that while young adults have lower rates of using digital devices for health care, they exhibit higher confidence in using such devices. In contrast, middle-aged adults, despite having lower confidence, report higher usage of digital devices for health care purposes. This study explored differences in digital confidence and health care usage between age group.

Wearable devices have a significant impact on society and recent advancements in modern sensor technologies are opening up new possibilities for healthcare applications. Continuous vital sign monitoring using IoT can be a crucial tool for emergency management, reducing risk in rescue operations and ensuring the safety of workers.The massive amounts of data, high network traffic, and computational demands of a typical IoT monitoring application can be challenging to manage with traditional infrastructure. Cloud computing provides a solution with its built-in resilience and elasticity capabilities.This article presents a cloud-based monitoring architecture for remote vital sign tracking of paramedics and medical workers through the use of a mobile wearable IoT device. It enables the management of ECG, breathing patterns, and other vital signs during work sessions, and sends real-time alarm events to a personnel management center. The platform was extensively used and tested in a large-scale monitoring application for tracking the activities of emergency room and ambulance workers, and the results of this testing are presented.

Reminding the courier through wearable artificial intelligence devices to prevent accidents is not only beneficial to the courier's safety but also will save a lot of insurance premiums for express companies, therefore, it is worth investigating what factors can influence the acceptance of wearable artificial intelligence devices by couriers. Push-pull-mooring (PPM) theory and affective event theory (AET) are integrated to test couriers’ adoption to wearable safety detection devices. Social influence, perceived security, personal innovativeness and affective event reaction are applied to research model. Questionnaires are distributed among several listed express companies and 263 valid questionnaires are used for empirical test. Empirical results indicated that social influence, perceived safety, personal innovativeness and affective event reaction are positively related to usage with coefficients 0.218, 0.301, 0.698 and 0.309. Personal innovativeness has positively moderating effects on relationships between affective event reaction, perceived security and usage with coefficients 0.145 and 0.106, whereas has no significant moderating effect on relationship between social influence and usage. The research aims to help support the proliferation and adoption of wearable artificial intelligence devices to optimize the current state of the express industry and improve the interaction between couriers and managers, creating an active management strategy that will allow express companies to thrive. This study can help express companies reduce insurance costs and therefore reduce the premium pricing of insurance companies for the courier industry.. This study also provides design suggestions for the application of wearable artificial intelligence devices based on chat GPT in various working conditions.

Problem:Palestinian demographic landscape is undergoing an increase in the elderly population like many regions across the world. The elderly Palestinians face a unique challenges and problems of limited access to traditional care due to restricted movement, checkpoints, and also for limited healthcare resources. Therefore, the need arose to develop a sensitive and adaptable smart health monitoring system for Palestinian elderly to provide accurate and timely health data to improve well-being and prevent complications. Method: The proposed system (SHMS) leverages the Internet of Things (IoT) with appropriate sensors to track vital signs like heart rate, blood oximeter, body temperature and signal from a patient heart. Advanced algorithms analyze the data, generating alerts for potential health risks, triggering timely interventions, and enabling remote consultations. Results: This system has the potential to contributes to SDG 3 to significantly improve the health and well-being of elderly Palestinians by providing an accurate, low-power, and low-cost system for remote health monitoring. The system, being wearable, reads vital signs in real-time, overcoming geographical barriers and facilitating remote monitoring, especially in areas with limited healthcare centers and suffered from barriers along the way. The Doctor can suggest the patient’s prescription needed based on the momentary condition of the elderly and on previous readings of the sensors, if necessary. Which will also be notified via messages. Moreover, the doctor can take immediate intervention in case of an emergency. By implementing the system, it will be unnecessary for more than 50\% of the elderly to visit health care, thus reducing the cost to 50\%.}

Wearable antennas are increasingly vital in modern healthcare, facilitating continuous monitoring and communication for medical purposes. These antennas are integrated into wearable devices, allowing for the transmission and reception of vital health data, such as heart rate, body temperature, and blood pressure, to medical professionals or monitoring systems in real time. This instantaneous data transmission enables timely interventions, thus improving the quality of healthcare services. This review aims to comprehensively synthesize recent research from reputable databases, focusing on the functionality and effectiveness of wearable antennas in medical applications. The primary objectives of each study were categorized, including antenna design and integration, the performance of medical wearable antenna technology, safety considerations in wearable antenna biomedicine, and the use of antennas in clinical applications and their impact. This synthesis provides valuable insights for researchers and practitioners aiming to develop and deploy wearable antennas in medical settings, ultimately enhancing healthcare delivery and patient outcomes.

We propose a new methodology for long-time biopotential recording based on MEMS multisensor integrated platform featuring a commercial electrostatic charge transfer sensor. That family of sensors was originally intended for presence tracking in automotive, so the existing setup has been engineered for the acquisition of electrocardiogram, electroencephalogram, electrooculogram and electromyography, designing a dedicated front-end and writing a proper firmware for the specific application. Systematic tests on controls and nocturnal acquisitions from patients in domestic environment will be discussed in detail. The excellent results candidate this technology to provide a low power, unexplored solution to biopotentials acquisition. The technology breakthrough is in that it enables adding this type of functionality to existing MEMS boards at near-zero additional power consumption. For these reasons, they open to additional possibilities for wearable sensing and strengthen the role of MEMS technology in medical wearable applications for long time synchronous acquisition of a wide range of signals.

Recently, cobalt iron boron (CoFeB) thin films have been widely investigated to apply to magnetic sensors, due to their high magnetic moment, anisotropy, and stability. However, most of these studies are conducted on rigid silicon substrates. For more diverse applications of magnetic sensors and angle sensors, it is important to explore the properties of ferromagnetic thin films grown on non-rigid deformable substrates. Here, using representative deformable substrates such as polyimide (PI), polyethylene naphthalate (PEN) and polydimethylsiloxane (PDMS) that can be bent or stretched, we report experimental comparison of in-plane magnetic field angle-dependent properties of the amorphous Ta/CoFeB/MgO/Ta thin film which is grown on those deformable substrates. We investigate effects of substrate roughness, tensile stress, characteristics of deformable substrates, and sputtering process on the change of magnetic properties like coercive field (Hc), remanence over saturation magnetization (Mr/Ms), and their biaxial characteristics. This work presents unconventional foundations for exploring deformable magnetic sensors capable of detecting magnetic field angle.

Emotions are indicators of affective states and play a significant role in human daily life, behavior, and interactions. Giving emotional intelligence to the machines could, for instance, facilitate early detection and prediction of (mental) diseases and symptoms. Electroencephalography (EEG) -based emotion recognition is being widely applied because it measures electrical correlates directly from the brain rather than the indirect measurement of other physiological responses initiated by the brain. The recent development of non-invasive and portable EEG sensors makes it possible to use them in real-time applications. Therefore, this paper presents a real-time emotion classification pipeline, which trains different binary classifiers for the dimensions of Valence and Arousal from an incoming EEG data stream. After achieving a 23.9% (Arousal) and 25.8% (Valence) higher f1-score on the state-of-art AMIGOS dataset, this pipeline was applied to the dataset achieved by an emotion elicitation experimental framework developed within the scope of this thesis. Following two different protocols, 15 participants were recorded using two different consumer-grade EEG devices while watching 16 short emotional videos in a controlled environment. For an immediate label setting, the mean f1-score of 87% and 82% were achieved for Arousal and Valence, respectively. In a live scenario, while continuously being updated on the incoming data stream with delayed labels, the pipeline proved to be fast enough to achieve predictions in real time. However, the significant discrepancy from the readily available labels on the classification scores leads to future work to include more data with frequent delayed labels in the live settings.

Although the relations between sleep and academic performance have been extensively examined, how sleep predicts future academic performance (e.g., 2 -3 years) remains to be further investigated. Using wearable smartwatches and a self-report questionnaire, we tracked sleep activities of 45 college students over a period of approximate half a month to see whether their sleep activities predicted their academic performance, which was estimated by grade point average (GPA). Results showed that both nighttime sleep awakening frequency and its consistency in the tracking period were not significantly correlated with the GPA for the courses taken in the semester during sleep tracking (current GPA). However, both nighttime sleep awakening frequency and its consistency inversely predicted the GPA for the rest of the courses taken after that semester (future GPA). Moreover, students with more difficulty staying awake throughout the day obtained lower current and future GPAs, and students with lower inconsistency of sleep quality obtained lower future GPA. Together, these findings highlight the importance of nighttime sleep awakening frequency and consistency in predicting future academic performance and emphasize the necessity of assessing the consistency of sleep measures in future studies.

One third of fatal car accidents and so much tragedies are due to alcohol abuse. These sad numbers could be mitigated if everyone had access to a breathalyzer anytime and anywhere. Having a breathalyzer built into a phone or a wearable could be the way to get around the reluctance to carry a separate device. Towards this goal, we propose an inexpensive breathalyzer that could be integrated in the screen of mobile devices. Our technology is based on the evaporation rate of the fog produced by the breath on the phone screen, which increases as a function of the breath alcohol content. The device simply uses a photodiode placed on the side of the screen to measure the signature of the scattered light intensity from the phone display that is guided through the stress layer of the Gorilla glass screen. A part of the display light is coupled to the stress layer via the evanescent field induced at the edge of the breath microdroplets. We demonstrate that the intensity signature measured at the detector can be linked to the blood alcohol content. We fabricated a prototype in a smartphone case powered by the phone’s battery, controlled by an application software installed in the smartphone and tested it in real-world environments. Limitations and future work toward a fully operational device are discussed.

Background: Natural environment inhalation topography provides useful information for toxicant exposure, risk assessment and cardiopulmonary performance. Commercially available Wearable Respiratory Monitors (WRM), which are currently used to measure a variety of physiological parameters such as heart rate and breathing frequency, can be leveraged to obtain inhalation topography, yet little work has been done. This paper assesses the feasibility of adapting these WRMs for measuring inhalation topography. Methods: Commercially available WRMs were compiled and assessed for the ability to report chest motion, data analysis software features, ambulatory observation capabilities, participant acceptability, purchasing constraints and affordability. Results: The following WRMs were found: LifeShirt, Equivital EQ02 LifeMonitor, Smartex WWS, Hexoskin Smart Garment, Zephyr BioHarness, Nox T3&amp;A1, BioRadio, SleepSense Inductance Band, and ezRIP &amp; zRIP Durabelt. None of the WRMs satisfied all six assessment criteria in a manner enabling them to be used for inhalation topography without modification and development. Conclusion: The results indicate that there are WRMs with core technologies and characteristics that can be built upon for ambulatory inhalation topography measurement in the NE.

In this paper, we present the design of a wearable photoplethysmography (PPG) system, R-band for acquiring the PPG signals. PPG signals are influenced by the respiration or breathing process and hence can be used for estimation of respiration rate. R-Band detects the PPG signal that is routed to a Bluetooth low energy device such as a nearbyplaced smartphone via microprocessor. Further, we developed an algorithm based on Extreme Learning Machine (ELM) regression for the estimation of respiration rate. We proposed spectral kurtosis features that are fused with the state-ofthe-art respiratory-induced amplitude, intensity and frequency variations-based features for the estimation of respiration rate (in units of breaths per minute). In contrast to the neural network (NN), ELM does not require tuning of hidden layer parameter and thus drastically reduces the computational cost as compared to NN trained by the standard backpropagation algorithm. We evaluated the proposed algorithm on Capnobase data available in the public domain.

This paper focuses on examining a new type of n-additive maps called the symmetric reverse n-derivations. As implied by its name, it combines the ideas of n-additive maps and reverse derivations, with a 1-reverse derivation being the ordinary reverse derivation. We explore several findings that expand our knowledge of these maps, particularly their presence in semiprime rings and the way rings respond to specific functional identities involving elements of ideals. Also, we provide examples to help clarify the concept of symmetric reverse n-derivations. This study aims to deepen the understanding of these symmetric maps and their properties within mathematical structures.

This paper focuses on examining a new type of $n$-additive maps called the symmetric reverse $n$-derivations. As implied by its name, it combines the ideas of $n$-additive maps and reverse derivations, with a $1$-reverse derivation being the ordinary reverse derivation. We explore several findings that expand our knowledge of these maps, particularly their presence in semiprime rings and the way rings respond to specific functional identities involving elements of ideals. Also, we provide examples to help clarify the concept of symmetric reverse $n$-derivations. This study aims to deepen the understanding of these symmetric maps and their properties within mathematical structures.

This study investigates the stress corrosion cracking (SCC) behavior of type 316L stainless steel (SS316L) produced with sinter-based material extrusion additive manufacturing (AM). This technology has been shown to produce SS316L with microstructures and mechanical properties comparable to its wrought counterpart in the annealed condition. However, despite plenty of research on SCC of SS316L, little is known about SCC in sinter-based AM SS316L. This study focuses on the influence of sintered microstructures on susceptibility to SCC initiation and crack-branching. Custom-made C-rings were exposed to different stress levels in acidic chloride solutions at various temperatures. To better understand the SCC behavior of SS316L, solution-annealed (SA) and cold-drawn (CD) wrought SS316L were tested for comparison. Results showed that sinter-based AM SS316L was more susceptible to SCC initiation than SA wrought SS316L but more resistant than CD wrought SS316L. Moreover, sinter-based AM SS316L showed noticeably better resistance to crack-branching than both wrought SS316L counterparts. The investigation was supported by comprehensive pre- and post-test microanalysis using light optical microscopy (LOM), scanning electron microscopy (SEM), electron backscatter diffraction (EBSD), and micro-computed tomography (micro-CT)

Mode locked pulse generation has been reported using both active and passive mode locking schemes. Active mode locking technique has been proven to be an effective way to generate high-repetition-rate pulses by incorporating a modulator inside the laser cavity. Compared to actively mode locked lasers, passively mode locked lasers can generate pulse train at ultrashort pulse width but with relatively lower repetition rate. Thus, it is a brilliant idea to build a hybrid mode locked system combining both active and passive mode lockers. In this review, several hybrid mode locked fiber ring laser systems are discussed and summarized. Hybrid mode locking is a promising method to generate high speed ultrashort optical pulses for fiber-optic telecommunication system.

Stress is an inherent sensation of being unable to handle demands and occurrences. If not properly managed, stress can develop into a chronic condition, leading to the onset of additional chronic health issues like cardiovascular illnesses and diabetes. Various stress meters have been suggested in the past, along with diverse approaches for its estimate. However, in the case of more serious health issues such as hypertension and diabetes, the results can be significantly improved. This study presents the design and implementation of a distributed wearable sensor computing platform with multiple channels. The platform aims to estimate stress levels in diabetes patients by utilizing a fuzzy logic algorithm that is based on the assessment of several physiological indicators. Additionally, a mobile application was created to monitor users' stress levels and integrate data on their blood pressure and blood glucose levels. Validation experiments were performed on patients with chronic diabetes, and the initial findings are presented in the study.

The manuscript presents a novel approach to designing and fabricating a stretchable patch antenna designed for strain sensing and wireless communication of sensing data at the same time. The challenge lies in combining flexible and stretchable textile materials with different physical mor-phologies, which can hinder adhesion among multiple layers when stacked up, resisting the overall stretchability of the antenna. The proposed antenna design overcomes this challenge by incorpo-rating a lattice hinge pattern in the non-stretchable conductive e-textile, transforming it into a stretchable structure. The innovative design includes the longitudinal cuts inserted in both the patch and the ground plane of the antenna, allowing it to stretch along in the perpendicular direction. Implementing the lattice hinge pattern over the conductive layers of the proposed patch antenna in combination with a 2 mm thick Polydimethylsiloxane (PDMS) substrate achieves a maximum of 25% stretchability compared to its counterpart antenna without lattice hinge design. The stretchable textile antenna resonates around a frequency of 2.45 GHz and exhibits a linear resonant frequency shift when strained up to 25%. This characteristic makes it suitable for use as a strain sensor. Ad-ditionally, the lattice hinge design enhances the conformability and flexibility of the antenna compared to a solid patch antenna. The realized antenna gains in the E and H-plane were measured as 2.21 dBi and 2.34 dBi, respectively. Overall, the presented design offers a simple and effective solution for fabricating a stretchable textile patch antenna for normal use or as a sensing element, opening up possibilities for applications in communication and sensing fields.

Freezing of Gait (FOG) is an impairment that affects the majority of patients in the advanced stages of Parkinson’s Disease (PD). FOG can lead to sudden falls and injuries, negatively impacting the quality of life for the patients and their families. Rhythmic Auditory Stimulation (RAS) can be used to help patients recover from FOG and resume normal gait. RAS might be ineffective due to the latency between the start of a FOG event, it’s detection and initialization of RAS. We propose a system capable of both FOG prediction and detection using signals from tri-axial accelerometer sensors that will be useful in initializing RAS with minimal latency. We compared the performance of several time frequency analysis techniques, including moving windows extracted from the signals, handcrafted features, Recurrence Plots (RP), Short Time Fourier Transform (STFT), Discreet Wavelet Transform (DWT) and Pseudo Wigner Ville Distribution (PWVD) with Deep Learning (DL) based Long Short Term Memory (LSTM) and Convolutional Neural Networks (CNN). We also propose three Ensemble Network Architectures that combine all the time frequency representations and DL architectures. Experimental results show that our ensemble architectures significantly improve the performance compared with existing techniques. We also present the results of applying our method trained on publicly available dataset to data collected from patients using wearable sensors in collaboration with A.T. Still University.

(1) Background: New sensor technologies in wearables and other consumer health devices open up promising opportunities to collect real-world data. As cardiovascular diseases remain reason number one for disease and mortality worldwide, cardiology offers potent monitoring use-cases with patients in their out-of-hospital daily routine. Therefore, the aim of this systematic review is to investigate the status quo of studies monitoring patients with cardiovascular risks and patients suffering from cardiovascular diseases in a telemedical setting using not only a smartphone-based app, but also consumer health devices such as wearables and other sensor-based devices. (2) Methods: A literature search was conducted across five databases and the results were examined according to the study protocols, technical approaches and qualitative and quantitative parameters measured. (3) Results: Out of 166 articles, 8 studies were included in this systematic review. These cover interventional and observational monitoring approaches in the area of cardiovascular diseases, heart failure and atrial fibrillation using various app, wearable and health device combination. (4) Conclusions: Depending on the researcher’s motivation a fusion of apps, patient reported outcome measures and non-invasive sensors can be orchestrated in a meaningful way adding major contributions to monitoring concepts for both, individual patients and larger cohorts.

Detection of human movement requires lightweight, flexible systems to detect mechanical parameters (like strain and pressure) not interfering with user activity, and that he/she can wear comfortably. In this work we address such multifaceted challenge with the development of smart garments for lower limb motion detection, like a textile kneepad and anklet in which soft sensors and readout electronics are embedded for detecting movement of the specific joint. Stretchable capacitive sensors with a three-electrode configuration are built combining conductive textiles and elastomeric layers, and distributed at knee and ankle. They show an excellent behavior in the ~30% strain range, hence the correlation between their responses and the optically tracked Euler angles is allowed for basic lower limb movements. Bending during knee flexion/extension is detected, and it is discriminated from any external contact by implementing in real time a low computational algorithm. The smart anklet is designed to address joint motion detection in and off the sagittal plane. In this work, ankle dorsi/plantar flexion, adduction/abduction, and rotation are retrieved. Both smart garments show a high accuracy in movement detection, with a RMSE less than 4° in the worst case.

Herein, we have reported the synthesis and characterization [single crystal X-ray diffraction technique, spectroscopic etc.] of two new Ni(II) and Zn(II) coordination compounds viz. [Ni(2,6-PDC)2]2[Ni(en)2(H2O)2]2[Ni(en)(H2O)4]·4H2O (1) and [Zn(2,6-PDC)(Hdmpz)2] (2) (where, 2,6-PDC = 2,6-pyridinedicarboxylate, en = ethylene-1,2-diamine, Hdmpz = 3,5-dimethyl pyrazole). Compound 1 is found to crystallize as a multicomponent Ni(II) compound with five discrete complex moieties; whereas, compound 2 is a mononuclear compound of Zn(II). Deep analysis of the crystal structure of compound 1 unfolds unusual dual enclathration of guest complex cationic moieties within the supramolecular host cavity stabilized by anion‒π, π-stacking, N‒H⋯O, C‒H⋯O and O‒H⋯O hydrogen bonding interactions. Interestingly, further enclathration of a complex cationic moiety is observed within another supramolecular host cavity formed involving anionic complex moieties and lattice water molecules in 1. Again, the crystal structure of compound 2 is stabilized by the presence of unconventional C‒H⋯π(chelate ring) interactions along with C‒H⋯O, C‒H⋯N hydrogen bonding, π-stacking, C‒H⋯π(pyridyl) interactions. These non-covalent interactions have been further studied theoretically using density functional theory (DFT) calculations, molecular electrostatic potential (MEP) surfaces, non-covalent interaction (NCI) plot index and quantum theory of atoms in molecules (QTAIM) computational tools. The computational study displays that π-stacking or H-bonds greatly tune the directionality of compound 1 although non-directional electrostatic forces dominate energetically. For compound 2, combined QTAIM/NCI plot analysis confirms the presence of unconventional C‒H⋯π(chelate ring) interaction along with other weak interactions obtained from the crystal structure analysis. Further, the individual energy contributions of these weak yet significant non-covalent interactions have also been determined computationally.

A micro-ring resonator structure was fabricated via two-photon polymerization (2PP) technique directly on a single-mode fiber tip and tested for refractive index sensing application. The micro-ring structure was used to excite whispering gallery modes (WGMs) and observations of the changes in resonance spectrum introduced by changes in refractive index of the environment served as the sensing principle. The proposed structure has the advantages of a very simple design, allowing for measurements in reflection mode, relatively easy and fast fabrication and integration with a single tip of a standard single-mode fiber, which allowed for quick and convenient measurements in the optical setup. The performance of structure was characterized, resonant spectrum giving high potential for refractive index sensing was measured. Future perspectives of the research are discussed.

This Paper intends to introduce the notion of prime ideals of Intuitionistic fuzzy normed Rings and to establish basic properties related to it. It investigates these notions and shown anew Result using intuinistic fuzzy points and non membership function incorparating with t-norm and s-norm to show aome results of fuzzy prime ideal.

This paper presents results on tribological characteristics for polymer blends made of polybutylene terephthalate (PBT) and polytetrafluoroethylene (PTFE). This blend is relatively new in research as PBT has restricted processability because of its processing temperature near the degradation one. Tests were done block-on-ring tribotester, in dry regime, the variables being the PTFE concentration (0%, 5%, 10% and 15%wt) and the sliding regime parameters (load: 1 N, 2.5 N and 5 N, the sliding speed: 0.25 m/s, 0.5 m/s and 0.75 m/s, and the sliding distance: 2500 m, 5000 m and 7500 m). Results are encouraging as PBT as neat polymer has very good tribological characteristics in terms of friction coefficient and wear rate. SEM investigation reveals a quite uniform dispersion of PTFE drops in the PBT matrix.

Noninvasive and portable diagnoses via angle-resolved coherent spectral data are presented. ACTIRS (Angle- resolved coherent tomographic IR spectroscopy) through angle-coherent return spectra from photonic quantum ring laser of whispering gallery modes, which is not photocurrent-converted after the cortical, vascular or muscular diffuse paths, can be a new method for brain/heart studies. Also it will be eligible for frequent do-it-yourself diagnoses of breast cancer before hospital visits. The unique angle-coherent multi-spectra will eventually lead to study ionic or protein contents of cranial, arterial or lactiferous ducts that have been obtained only from uncomfortable biopsy, NMR, CT or mammography. The spectral data can be spatially or temporally improved and correlated for extracting more meaningful diagnostic conclusions

Background: Regular moderate-vigorous intensity exercise is recommended for adults as it can improve longevity and reduce health risks associated with a sedentary lifestyle. However, there are barriers to achieving intense exercise that may be addressed using virtual reality (VR) as a tool to promote exercise intensity and adherence, particularly through visual feedback and competition. The purpose of this work is to compare visual feedback and competition within fully-immersive VR to enhance exercise intensity and user experience of exercise for young adults; and to describe and compare visual attention during each of the conditions. Methods: Young adults (21- 34 years old) bicycled in three 5-minute VR conditions (visual feedback, self-competition and competition against others). Exercise intensity (cycling cadence and % of maximum heart rate) and visual attention (derived from a wearable eye tracking sensor) were measured continuously. User experience was measured by an intrinsic motivation questionnaire, perceived effort and participant preference. A repeated measures ANOVA with paired t-test post-hoc tests was conducted to detect differences between conditions. Results: Participants exercised at a higher intensity and had higher intrinsic motivation in the two competitive conditions compared to visual feedback. Further, participants preferred the competitive conditions and only reached a vigorous exercise intensity during self-competition. Visual exploration was higher in visual feedback compared to self-competition. Conclusion: For young adults bicycling in VR, competition promoted higher exercise intensity and motivation compared to visual feedback.

Crowd accident surveys have shown that regardless of the initial triggering factors, pedestrian fall behaviour is the most critical factor causing and aggravating crowd accidents in public traffic areas (PTAs). Application of pedestrian fall behaviour detection methods in PTAs is significant. Once deployed, it would prevent many pedestrians from losing life in crowed traffic areas accidents. However, most existing methods is still focused on medical assistance for the elderly. Therefore, this paper conducted bibliometric and content analyses, combining fall detection-related keywords to retrieve from internationally recognized literature databases and benchmark pedestrian behaviour datasets. Based on the analysis of the state-of-the-art (SOTA) achievements in fall detection methods, the fall detection methods were classified into different categories according to the research approach. Among them, it undertakes a comprehensive analysis of five predominant methods, namely computer vision, Internet of Things, smartphone, kinematic, and wearable device-based methods. Furthermore, the benchmark datasets including fall scenarios were introduced and compared. Finally, it provides a detailed discussion of existing fall detection methods, and possible future directions are identified considering application requirements in PTAs. This overview may help researchers understand the SOTA fall detection methods and devise new methodologies by improving and synthesizing the highlighted issues in PTAs.

Despite soccer popularity, comparatively little scientific information is available concerning the assessment of youth players’ physiological characteristics. The use of medical software integrating wearable sensors to provide accurate and objective data is necessary. In the present study, the objective assessment of physical performance of 128 adolescent soccer players at two timepoints (pre-season and end-season) has been performed. Participants completed a comprehensive test battery including stability, countermovement jumps (CMJ), plyometric jumps (PJ), agility, and quick feet tests. A single Inertial Measurement Unit (IMU) sensor provided quantitative data on various performance metrics. Principal Component Analysis (PCA) reduced the dataset to four principal components (PCs) explaining over 80% of the variance: power (PC1), balance (PC2), speed/agility (PC3), and stiffness (PC4). Paired samples t-test between the two timepoints showed no significant differences in the PCs between the two timepoints, indicating that the training program did not significantly alter the assessed physical attributes. However, subtle individual changes may still inform personalized training adjustments. The study highlights the importance of continuous monitoring and individualized training strategies to optimize athlete performance and reduce injury risk.

The design of torsional springs for Series Elastic Actuators (SEAs) is challenging, especially when it comes to balancing good stiffness characteristics and efficient torque robustness. This study focuses on the design of a lightweight, low-cost, and compact torsional spring for use in rotary series elastic actuator (ES-RSEA) of lumbar support exoskeleton. The exoskeleton is used as an assistive device to prevent lower back injuries. The torsion spring was designed following design for manufacturability (DFM) principles, focusing on minimal space and weight. The design process consisted of determining the potential topology and optimizing the selected topology parameters through finite element method (FEM) to reduce equivalent stress. The prototype was made using a waterjet cutting process with low-cost material (AISI-4140-alloy) and tested using a custom-made test rig. The results showed that the torsion spring had a linear torque-displacement relationship with 99% linearity, and the deviation between FEM simulation and experimental measurements was less than 2%. The torsion spring has a maximum torque capacity of 45.7 Nm and a stiffness of 440 Nm/rad. The proposed torsion spring is a promising option for lumbar support exoskeletons and similar applications requiring high stiffness, low weight-to-torque ratio, and cost-effectiveness.

The Galvanic Skin Response (GSR, also widely known as electrodermal activity EDA) is one of the signals related to this emotional reaction. Given the sparsity of studies related to and the variety of devices, we experimented at the Human Health Activity Laboratory with 17 healthy subjects. The goal is to know the variability of detection changes in the electrodermal activity among a test group with heterogeneous respondents in response to valence and arousal stimuli, correlating GSR biosignals measured from different body sites. We experiment with the right and left wrist, left fingers, the right foot's inner side using Shimmer3GSR, and Empatica E4 sensors. Results indicate as the most promising homogeneous GSR measure place the left fingers and right foot. Results suggest that due to a significantly strong correlation among the inner side of the right foot and left fingers and moderate correlations with the right and left wrist, the foot is a good place to measure EDA. This paper also contributes knowledge about some wearable sensor technologies available in the market. Shimmer3GSR sensor may be better reliable to homogenous detecting electrodermal activity changes, as these have fewer anomalies among the respondents. However, we found some anomalies in signals from the Empatica E4 sensor, which we discuss in this work.

Motor functions are deteriorated by aging. Some conditions may magnify this deterioration. To examine whether hemodialysis (HD) process would negatively impact gait and balance beyond diabetes condition among mid-age adults (48-64 years) and older adults (65+ years). One hundred and ninety-six subjects (age=66.2±9.1 years, body-mass-index=30.1±6.4 kg/m², female=56%) in 5 groups were recruited: mid-age adults with diabetes undergoing HD (Mid-age HD+, n=38) and without HD (Mid-age HD-, n=40); older adults with diabetes undergoing HD (Older HD+, n=36) and without HD (Older HD-, n=37); and non-diabetic older adults (Older DM-, n=45). Gait parameters (stride velocity, stride length, gait cycle time, and double support) and balance parameters (ankle, hip, and center of mass sways) were quantified using validated wearable platforms. Groups with diabetes had overall poorer gait and balance compared to the non-diabetic group (p<0.050). Among people with diabetes, the HD+ had significantly worsened gait and balance when comparing to the HD- (Cohen’s effect size d=0.63-2.32, p<0.050). Between-group difference was more pronounced among older adults with the largest effect size observed for stride length (d=2.32, p<0.001). Results suggested that deterioration in gait speed among the HD+ was correlated with age (r=-0.440, p<0.001), while this correlation was diminished among the HD-. Interestingly, results also suggested that poor gait in the Older HD- related to poor balance, while no correlation was observed between poor balance and poor gait among the Older HD+. Using objective assessments, results confirmed that the presence of diabetes can deteriorate gait and balance, and this deterioration can be magnified by HD process. Among non-HD people with diabetes, poor static balance described poor gait. However, among people with diabetes undergoing HD, age was a dominate factor describing poor gait irrespective of static balance. Results also suggested feasibility of using wearable platforms to quantify motor performance during routine dialysis clinic visits. These objective assessments may assist in identifying early deterioration in motor function, which in turn may promote timely intervention.

The magnetic properties of 0.10 mm ultra-thin grain-oriented (UTGO) silicon steel and Fe-based amorphous (FBA) alloy under sinusoidal excitation were measured experimentally, and the magnetic field strength and iron loss of the two materials under different frequencies and magnetic densities were obtained. Based on the measured data, the magnetization and loss characteristics of the two materials were analyzed and compared. Furthermore, two Epstein square ring models of the same specification and different materials were designed, and the reliability of the models was verified. Then, the electromagnetic characteristics of the two Epstein square ring models at higher and lower frequencies were calculated by using the finite element method, and the iron loss was obtained and compared. The results show that the FBA alloy has good application characteristics at low frequency and low power, and the 0.10 mm UTGO silicon steel has good application characteristics at high frequency and high power. This research can provide important data basis to promote the application of these two materials in new energy equipment.

Microelectromechanical System (MEMS) vibrating gyroscope design considerations are always intriguing due to their microscale mechanical, electrical, and material behavior. MEMS vibrating ring gyroscopes have become important inertial sensors in inertial measurement units (IMU) for navigation and sensing applications. The design of a MEMS vibrating ring gyroscope incorporates an oscillating ring structure as a proof mass, reflecting unique design challenges and possibilities. This paper presents a comprehensive design analysis of the MEMS vibrating ring gyroscope from the mechanical, electrical, and damping perspectives. The mechanical design of the MEMS vibrating ring gyroscope investigates the various frame designs of the vibrating ring structure, as well as the various beam structures, including curved, rectangular, and semicircular beam structures, which are analyzed using mathematical models and finite element analysis (FEA) simulations that provide an in-depth analysis of the stiffness and deflection of the vibrating structures. The electrical designs of the MEMS vibrating ring gyroscope were analyzed using various electrode configurations, electrostatic actuation, and capacitive detection mechanisms, respectively. The design analysis of various forms of damping, including viscous, structural, thermoelastic, and anchor damping, has been discussed. The variety of design structures investigated for MEMS vibrating ring gyroscopes' mechanical, electrical, and damping performance.

The dependence of the width of annual rings of woody plants on the characteristics of the snow cover is analyzed in various natural zones of the West Siberian Plain and adjacent mountainous areas: the maximum thickness and water reserve for the entire winter period and for individual months, the dates of disappearing, establishment, and duration of the occurrence of a stable snow cover. It has been shown that the role of the thickness and water content of snow cover for the radial growth of trees is differentiated by geographical location. On the plain, it intensifies in the forest-tundra and dry steppe. The response of radial growth to snow cover in the upper and lower parts of the forest belt is often opposite. Dates of establishment of stable snow cover are more important for tree growth compared to dates of disappearance. Dates of disappearance of stable snow cover are more significant in the southern regions than in the northern ones. The value of the duration of the period with stable snow cover for tree growth is higher in the southern regions.