Wireless Powered Communication Networks (WPCN), which has attracted much attention of researchers, also been recently recommended in 5^th generation (5G) wireless networks. With the help of the WPCN, the reliability and battery life of wireless low-power devices can be improved. In this paper, we investigate throughput and ergodic capacity in WPCN-assisted amplify-and-forward (AF) relaying system, considering two transmission modes including delay-tolerant and delay-limited. As important achievement, we propose symmetric energy harvesting protocol, namely time power switching relaying (TPSR) in order to find maximal throughput. In particular, both time switching and power switching coefficients in this schemes are considered. Unlike most of the previous works, we further focus on impact of outdated channel state information (CSI) in this WPCN. In order to evaluate information processing efficiency, the performance can be substantially improved by optimally harvesting time and power coefficients of the received signal at relay node for energy and information extraction, and by deploying several scenarios. By deploying Monte Carlo simulation, it is confirmed that the system performance is more sensitive to CSI estimation error, noise variance, signal-to-noise ratio (SNR) and resulting in other reasonable computations of TPSR need be deployed to obtain QoS requirement.

Carotid atherosclerotic lesions are a major cause of cerebrovascular disease (CVD). Identification and quantification of carotid plaques are important for categorizing the vulnerability of plaques for rupture and assessing the impact of treatments. The irregularity of plaque surface is associated with previous plaque rupture and plays an important role in the risk of stroke. Thus, the aim of this study is to develop and validate novel vulnerability biomarkers from three-dimensional ultrasound (3DUS) images by analyzing the surface morphological characterization of carotid plaque using fractal geometry features. 3D box-counting and 3D blanket are the two types of 3D fractal dimension that were employed to describe the smoothness of plaques. This fractal dimension analysis tool was used to evaluate the effect of atorvastatin using 3DUS carotid images, which were acquired from 6 patients treated with atorvastatin with 80 mg daily and 5 patients with placebo. The Student's T Test results showed that those two fractal features were effective for detecting the statin-related changes in carotid atherosclerosis with p<0.0068 and p<0.015 respectively, suggesting that 3D fractal dimension measurements can be used effectively to analyze the surface characteristics of carotid plaques, especially for evaluating the impact of the treatment.

Abstract: Background. The newer wireless portable scanners seem to permit a quicker bedside ultrasound (US) assessment, shortening the transfer times of the portable US unit and without the hindering of connection cables. However, no substantial evidence is currently available regarding of the clinical effectiveness of such new generation devices. Objective. The aim of the current study was to evaluate the efficacy of a wireless US system with respect to a high-end US unit in a cohort of consecutive respiratory patients. Materials and Methods. This prospective observational study included a total of 72 respiratory patients admitted in the department of Internal Medicine. The US examination were independently performed by two experienced blinded examiners with a high-end Esaote MyLab-Twice scanner and a wireless double-head linear and convex probe OTE-L/C501CD. The findings resulting from the high-end US assessment and the wireless US examination were then compared each other. All the patients had a confirmation chest CT scan. Results. The high-end US machine identified 64 positive cases for pleuro-pulmonary alterations, in comparison to which the wireless US unit resulted in 13 false negative results. The respective overall sensitivity and specificity for the portable wireless US unit were of 79.69% and 100.00%, respectively. The resolution of the portable wireless US device was judged as good in 22 (31%) cases, affected by minor diagnostic limitations in 26 (36%) cases and affected by major diagnostic limitations in 24 (33%). The main diagnostic strength of the wireless probe was in the detection of pleural effusion (sensitivity 100%). The diagnostic sensitivity of the wireless probe in assessing abnormalities of the pleural line (67%), pulmonary subpleural consolidations (65%), pleural lesions (33%) and pericardial effusion (0%) was reduced. Conclusions. The newer wireless US probes may have clinical roles for the detection and management of pleural effusion when used by experienced examiners. However, sensitivity in detecting other pleuro-pulmonary pathologies is not comparable to high-end ultrasound machines.

(1) Background: The purpose of this study is to evaluate the full arch scan accuracy (precision and trueness) of nine digital intra-oral scanners and four lab scanners. Previous studies have compared the accuracy of some intra-oral scanners, but as this is a field of quickly developing technologies, a more up-to-date study was needed to assess the capabilities of currently available models.; (2) Methods: The present in vitro study compared nine different intraoral scanners (Omnicam 4.6; Omnicam 5.1; Primescan; CS 3600; Trios 3; Trios 4; Runyes; i500 and DL206) as well as four lab light scanners (Einscan SE; 300e; E2 and Ineos X5) to investigate the accuracy of each scanner by examining the overall trueness and precision. Ten aligned and cut scans from each of the intra-oral and lab scanners in the in vitro study were brought into CloudCompare. A comparison was made with the master STL using the CloudCompare 3D analysis best-fit algorithm. The results were recorded along with individual standard deviation and a colorimetric map of the deviation across the surface of the STL mesh; a comparison was made to the master STL, quantified at specific points. ; (3) Results: In the present study, the Primescan had the best overall trueness (17.3 ± 4.9). Followed by (in order of increasing deviation) the Trios 4 (20.8 ± 6.2), i500 (25.2 ± 7.3), CS3600 (26.9 ± 15.9), Trios 3 (27.7 ± 6.8), Runyes (47.2 ± 5.4), Omnicam 5.1 (55.1 ± 9.5), Omnicam 4.6 (57.5 ± 3.2) and Launca DL206 (58.5 ± 22.0). Regarding the lab light scanners, the Ineos X5 had the best overall trueness with (0.0 ± 1.9). Followed by (in order of increasing deviation) the 3Shape E2 (3.6 ± 2.2), Up3D 300E (12.8 ± 2.7), and Einscan SE (14.9 ± 9.5); (4) Conclusions: This study confirms that all current generations of intra-oral digital scanners can capture a reliable, reproducible full arch scan in dentate patients. Out of the intra-oral scanners tested, no scanner produced results significantly similar in trueness to the Ineos X5. However, the Primescan was the only one to be statistically of a similar level of trueness to the 3Shape E2 lab scanner. All scanners in the study had mean trueness of under 60-micron deviation. While this study can compare the scanning accuracy of this sample in a dentate arch, the scanning of a fully edentulous arch is more challenging. The accuracy of these scanners in edentulous cases should be examined in further studies.

Lignocellulosic biomass, an abundant and renewable resource, serves as a crucial raw material for the production of biofuels, biochemicals, and various value-added products. This paper aims to develop and optimize a mild alkaline treatment of sawdust assisted by ultrasound, along with enzymatic hydrolysis of the pretreated material. The sonochemical pretreatment with alkali emerged as the optimal approach to enhance the susceptibility of cellulose to subsequent enzymatic hydrolysis, thereby increasing the yield of reducing sugars. A comparative study was performed using various ultrasonic applicators (horn and bath) and conventional assisted alkaline pretreatment. The ultrasonic assisted pretreatment revealed a higher delignification as 68% (horn) and 57% (bath) comparing with conventional pretreatment. Processes were optimized using a statistical analysis based on a 23 factorial design. The ratio between sawdust and alkanine solution (RSL = 0.5–1.5 g/100 mL), US amplitude (A = 20–60%), and working temperature (t = 30–50 °C) were selected as process factors. The optimal operating conditions to maximize the reducing sugar yield (138.15 mg GE /gsubstrate) were found as following: solid/liquid ratio RSL,opt = 1.25 g/100 mL, US amplitude Aopt = 60%, and and pretreatment temperature topt = 50 °C. The overall outcomes clearly confirmed the intensification of delignification by ultrasound assisted alkaline pretreatment

The urgent need to improve performance in the construction industry has led to the adoption of many innovative technologies. 3D laser scanners are amongst the leading technologies being used to capture and process assets or construction project data for use in various applications. Due to its nascent nature, many questions are still unanswered about 3D laser scanning, which in turn contribute to the slow adaptation of the technology. Some of these include the role of 3D laser scanners in capturing and processing raw construction project data. How accurate is the 3D laser scanner or point cloud data? How does laser scanning fit with other wider emerging technologies such as Building Information Modelling (BIM)? This study adopts a proof-of-concept approach, which in addition to answering the afore-mentioned questions, illustrates the application of the technology in practice. The study finds that the quality of the data, commonly referred to as point cloud data is still a major issue as it depends on the distance between the target object and 3D laser scanner’s station. Additionally, the quality of the data is still very dependent on data file sizes and the computational power of the processing machine. Lastly, the connection between laser scanning and BIM approaches is still weak as what can be done with a point cloud data model in a BIM environment is still very limited. The aforementioned findings reinforce existing views on the use of 3D laser scanners in capturing and processing construction project data.

This paper investigates an Energy Neutral System using Micro Energy Harvesters for a Health Monitoring Wireless Sensor Node (HM-WSN). We have implemented HM-WSN consisting of a solar cell energy harvester, a Power Management Unit (PMU) and the ucontroller, sensor and transmitter acting as load. A battery extender and a switching logic circuit for sensor node is designed to evaluate the efficiency of the proposed system. The HM-WSN senses body temperature with improvement in lifetime of coincell. The HM-WSN is built using commercially available off the shelf (COTS components and consumes 47.2uW for data being updated every 134s. It can be operated for approximately 1.32 years only on a coincell. Furthermore, the HM-WSN can be operated with solar energy at 200lux, achieving 96.36 years with a combination of a coincell with an additional capacitor of 2.2mF. It attains 4.07 years to 16.87 years lifetime with the load capacitor varying from 1mF to 1.5mF at 350lux lighting condition. With the same ambient condition and a 2mF load capacitor, HM-WSN attains complete energy autonomy.

For 80 years high-intensity focused ultrasound (HIFU) has been a significant area for medical research. It is a non-invasive procedure which causes cell death in a highly localised area at a defined distance from the transducer. Since 2000, the clinical indications have broadened considerable as the technology has improved. This review looks back at the history of HIFU and the current clinical indications.

With the integrated development of the Internet, wireless sensor technology, cloud computing, and mobile Internet, there has been a lot of attention given to research about and applications of the Internet of Things. A Wireless Sensor Network (WSN) is one of the important information technologies in the Internet of Things; it integrates multi-technology to detect and gather information in a network environment by mutual cooperation, using a variety of methods to process and analyze data, implement awareness, and perform tests. This paper mainly researches the localization algorithm of sensor nodes in a wireless sensor network. Firstly, a multi-granularity region partition is proposed to divide the location region. In the range-based method, the RSSI (Received Signal Strength indicator, RSSI) is used to estimate distance. The optimal RSSI value is computed by the Gaussian fitting method. Furthermore, a Voronoi diagram is characterized by the use of dividing region. Rach anchor node is regarded as the center of each region; the whole position region is divided into several regions and the sub-region of neighboring nodes is combined into triangles while the unknown node is locked in the ultimate area. Secondly, the multi-granularity regional division and Lagrange multiplier method are used to calculate the final coordinates. Because nodes are influenced by many factors in the practical application, two kinds of positioning methods are designed: the unknown node is in the positioning unit or not. When the unknown node is on the side of the positioning unit, we use the method of vector similarity. Moreover, we use the centroid algorithm to calculate the ultimate coordinates of unknown node. When the unknown node is not on the side of the positioning unit, we establish a Lagrange equation containing the constraint condition to calculate the first coordinates. Furthermore, we use the Taylor expansion formula to correct the coordinates of the unknown node. In addition, this localization method has been validated by establishing the real environment.

When a limb suffers a fracture, rupture, or dislocation, it is traditionally immobilized with plaster. This may induce discomfort in the patient, excessive itching and sweating, which creates the growth of bacteria, leading to an unhygienic and difficulty to keep clean from treatment. Furthermore, if the plaster remains for a long period, it may cause lesions in the joints and ligaments. To overcome all these disadvantages, orthoses have emerged as important medical devices to help patients in rehabilitation, as well as for self-care of deficiencies in clinics and daily life. Traditionally, these devices are produced manually, which becomes time-consuming and error prone. From another point-of-view, it is possible to use imageology (X-ray or computed tomography) to scan the human body; a process that may help orthoses manufacturing but induces radiation to the patient. To overcome this great disadvantage, several types of 3D scanners, without any kind of radiation have emerged. This article describes the use of various types of scanners capable of digitizing the human body, to produce custom orthoses. Studies have shown that photogrammetry is the most used and most suitable 3D scanner for the acquisition of the human body in 3D. With this evolution of technology, it is possible to decrease the scanning time and it will be possible to introduce this technology in clinical environment.

This study evaluates audiogenic epilepsy in Krushinsky-Molodkina rats using a wireless EEG system to overcome the limitations of traditional methods that restrict animal movement. Nine male KM rats, prone to audiogenic seizures, were implanted with electrodes in areas critical for seizure activity (inferior colliculus, ventrolateral periaqueductal gray, dorsal area of the secondary auditory cortex, and motor cortex). This setup allowed for the observation of seizures without movement restriction. Results showed that targeted neural intervention via electrode implantation reduced the intensity of convulsive seizures in half of the subjects, suggesting a potential therapeutic approach. The severity of seizures was influenced by the pre-phonostimulation EEG background activity in specific brain regions, identifying them as key in the genesis and generalization of seizures. Observations of dual generalized seizure waves and induced hyperkinesis challenge conventional epilepsy models and suggest new directions for research and therapy development.

The increasingly affordable price point of terrestrial laser scanners has led to a democratization of instrument availability, but the most common low-cost instruments have yet to be compared in terms of the consistency to measure forest structural attributes. Here, we compared two low-cost terrestrial laser scanners (TLS): the Leica BLK360 and the Faro Focus 120 3D. We evaluate the instruments in terms of point cloud quality, forest inventory estimates, tree-model reconstruction, and foliage profile reconstruction. Our direct comparison of the point clouds showed reduced noise in filtered Leica data. Tree diameter and height were consistent across instruments (4.4% and 1.4% error, respectively). Volumetric tree models were less consistent across instruments, with ~29% bias, depending on model reconstruction quality. In the process of comparing foliage profiles, we conducted a sensitivity analysis of factors affecting foliage profile estimates, showing a minimal effect from instrument maximum range (for forests less than ~50 m in height) and surprisingly little impact from degraded scan resolution. Filtered unstructured TLS point clouds must be artificially re-gridded to provide accurate foliage profiles. The factors evaluated in this comparison point towards necessary considerations for future low-cost laser scanner development and application in detecting forest structural parameters.

Accurate expression of bracket prescription is important for successful orthodontic treatment. The aim of this study was to evaluate the accuracy of digital scan images of brackets produced by four different intraoral scanners (IOSs) in terms of the height, position, and angle of the bracket slot when scanning the surface of dental model attached with bracket materials made from different composition of materials. Brackets made from stainless steel, polycrystalline alumina, composite and composite/stainless steel slot were considered, which have been scanned from 4 different IOSs (Primescan, Trios, CS3600 and i500). SEM images were used as references. Each bracket axis was set in the reference scan image, and the axis was set identically by superimposing with the IOS image, and then only the brackets were divided and analyzed. The difference between the manufacturer's nominal torque and bracket slot base angle was 0.39 in SEM, 1.96 in Primescan, 2.04 in Trios, and 5.21 in CS3600 (P <0.001). The parallelism, which is the difference between the upper and lower angles of the slot wall, was 0.55 in SEM, 7.55 in Primescan, 6.74 in Trios3, 6.59 in CS3600, and 24.95 in i500 (p <0.001). This study evaluated the accuracy of the bracket only and it must be admitted that there is some error in recognizing slots through scanning in general

Idiopathic acute pancreatitis (IAP) presents a diagnostic challenge and refers to cases where the cause of acute pancreatitis remains uncertain despite a comprehensive diagnostic evalua-tion. Endoscopic ultrasound (EUS) has emerged as a valuable tool in the diagnostic workup of IAP. This review explores the pivotal role of EUS in detecting the actual cause of IAP, as-sessing its accuracy, timing, safety, and future technological improvement. Following PRISMA guidelines, 60 pertinent studies were selected and analysed. EUS emerges as a cru-cial diagnostic tool, particularly when conventional imaging fails. It can offer intricate visu-alization of the pancreas, biliary system, and adjacent structures. High accuracy of EUS is evident in detecting the actual causes of IAP such as microlithiasis, small bile duct stones, pancreas divisum, and small pancreatic tumors. Optimal timing for EUS is post-resolution of the acute phase of the disease. EUS, when conducted by experienced endoscopists, it boasts minimal safety concerns, and is crucial to prevent complications. EUS-guided interventions, including fine-needle aspiration, collection drainage, and biopsies, aid in cytological analy-sis. With high diagnostic accuracy, safety, and therapeutic potential, EUS is able to improve patient outcomes when managing IAP. Further refinement of EUS techniques and cost-effectiveness assessment of EUS-guided approaches need to be explored in multicenter prospective studies. This review underscores EUS as a transformative tool in unraveling IAP's enigma and advancing diagnostic and therapeutic strategies.

Herbal Coffee is getting more popular due to its unique flavor and higher concentration of bioactive compounds, mainly polyphenols. Rosemary is a unique herb with potent antioxidant properties. A green technique called ultrasound aids in releasing bioactive substances from the plant cell wall. In this context, ultrasound-assisted herbal coffee prepared and their anti-diabetic, anti-Alzheimer, and antioxidant activities were measured while the LC/MS was used to determine the bioactive components from the herbal coffee infusion. A total of 95 secondary metabolites were putatively reported, including alkaloids, phenolic acids, and flavonoids, which we identified in the herbal coffee infusion. The total phenolic content (61.5 ± 5.1 mg GAE/g), total flavonoid content (19.3 ± 0.9 mg QE/g), and total condensed tannin (7.6 ± 0.7 mg CE/g) of herbal coffee infusion were observed to be highest of the two remaining samples. The herbal coffee extracts were used to determine all samples' antioxidant, anti-diabetic, and anti-Alzheimer activities. Using LC-MS/MS, we semi-quantified 19 phenolic metabolites. The results show numerous bioactive components in herbal coffee infusion with more potent antioxidant, antidiabetic, and anti-Alzheimer potential. Moreover, more studies must be conducted to confirm how the metabolomic profile of herbal coffee affects its flavor profile.

A space charge density wireless measurement system based on the idea of distributed measurement is proposed for collecting and monitoring the space charge density in an ultra-high-voltage direct-current (UHVDC) environment. The proposed system architecture is composed of a number of wireless nodes connected with space charge density sensors and a base station. The space charge density sensor based on atmospheric ion counter method is elaborated and developed, and the ARM microprocessor and Zigbee radio frequency module are applied. The wireless network communication quality and the relationship between energy consumption and transmission distance in the complicated electromagnetic environment is tested. Based on the experimental results, the proposed measurement system demonstrates that it can adapt to the complex electromagnetic environment under the UHVDC transmission lines and can accurately measure the space charge density.

In recent years, unmanned aerial vehicles (UAVs) have become a valuable platform for many applications, including communication networks. UAV-enabled wireless communication faces challenges in complex urban and dynamic environments. UAVs can suffer from power limitations and path losses caused by non-line-of-sight connections, which may hamper better communication performance. To address these issues, reconfigurable intelligent surfaces (RIS) have been proposed as a helpful tool to enhance UAV communication networks. However, due to the high mobility of UAV, complex channel environments, and dynamic RIS configurations, it is challenging to estimate the link quality of ground users. In this paper, we propose a link quality estimation model using a gated recurrent unit (GRU) to assess the link quality of ground users for a multi-user RIS-assisted UAV-enabled wireless communication system. Our proposed framework uses a time series of user channel data and RIS phase shift information to estimate the quality of the link for each ground user. Simulation results showed that the proposed GRU model effectively and accurately estimates the link quality of the ground users in the RIS-assisted UAV-enabled wireless communication network.

Magnetomotive ultrasound (MMUS) is a promising imaging modality for detecting magnetic nanoparticles. In MMUS, an external oscillating magnetic field induces motion of the injected magnetic nanoparticles within tissue, and phase-based tracking algorithms are used to detect the motion. However, the subwavelength scale of theses displacements (often a few micrometers) makes direct visualization on conventional ultrasound B-mode images impossible. In this work, we adapt the Eulerian motion magnification technique to create a novel ultrasound display mode for identifying the nanoparticle locations, eliminating the need for displacement tracking algorithms. Phantom and in-vivo experiments demonstrate that our technique successfully magnifies magnetomotion and the associated shear wave propagation in ultrasound B-mode imaging and pinpoints the nanoparticle vibration source, even in low-concentration scenarios. Additionally, motion magnification magnified the displacement of nanoparticles, having the potential to improve the localization accuracy of displacement tracking algorithms in MMUS.

We are introducing a highly efficient 48-channel ultrasound beamforming system ideal for ultrasound endoscopy applications. The system includes a transmitter and a receiver, which allow for low-area, high-resolution imaging acquisition. The transmitter uses a charge redistribution HV (high voltage) scheme to generate three-level pulses that actuate the transducer, implemented with the standard CMOS process for optimal cost and power savings. Meanwhile, the receiver features a sub-array structure and a delay generator that reduces area usage. To achieve high-resolution ultrasound imaging acquisition with low computational power, we developed the Shift Coherence Factor (SCF) algorithm, which is hardware-friendly. This approach delivers a lateral resolution over 20% better than the conventional delay and sum (DAS) algorithm, with a contrast ratio of over 30 dB. The system was implemented in a 180 nm standard CMOS process with an area of 24.98 mm2, power consumption of 8.23 mW per channel, achieving a delay resolution of 8.33 ns, and a low-area implementation of 0.52 mm2 per channel. The system offers high-quality imaging acquisition with minimal additional area and power consumption, which has great potential for 3D imaging or catheterized ultrasound systems.

A machine learning method for classifying Lung UltraSound is here proposed to pro- vide a point of care tool for supporting a safe, fast and accurate diagnosis, that can also be useful during a pandemic like as SARS-CoV-2. Given the advantages (e.g. safety, rapidity, portability, cost-effectiveness) provided by the ultrasound technology over other methods (e.g. X-ray, computer tomography, magnetic resonance imaging), our method was validated on the largest LUS public dataset. Focusing on both accuracy and efficiency, our solution is based on an efficient adaptive ensembling of two EfficientNet-b0 models reaching 100% of accuracy, which, to our knowledge, outperforms the previous state-of-the-art. The complexity of this solution keeps the number of parameters in the same order as an EfficientNet-b0 by adopting specific design choices that are adaptive ensembling with a combination layer, ensembling performed on the deep features, minimal ensemble only two weak models. Moreover, a visual analysis of the saliency maps on sample images of all the classes of the dataset reveals where the focus is on an inaccurate weak model versus an accurate model.

The COVID-19 pandemic has affected millions of people globally, with respiratory organs being strongly affected in individuals with comorbidities. Medical imaging-based diagnosis and prognosis have become increasingly popular in clinical settings to detect COVID-19 lung infections. Among various medical imaging modalities, ultrasound stands out as low-cost, mobile, and radiation-safe imaging technology. In this comprehensive review, we focus on ultrasound-based AI studies for COVID-19 detection that use public or private lung ultrasound datasets. We surveyed articles that used publicly available lung ultrasound datasets for COVID-19 and reviewed publicly available datasets and organize ultrasound-based AI studies per dataset. We analyzed and tabulated studies in several dimensions, such as data preprocessing, AI models, cross-validation, and evaluation criteria. In total, we reviewed 42 articles, where 28 articles used public datasets, and the rest used private data. Our findings suggest that ultrasound-based AI studies for the detection of COVID-19 have great potential for clinical use, especially for children and pregnant women. Our review also provides a useful summary for future researchers and clinicians who may be interested in the field.

Communication between devices has transitioned from wired to unwired. Wireless networks have been in use widely around the globe since the advent of smartphones, IoT devices and other technologies that are compatible with wireless mode of communication. At the same time security issues have also increased in such communication methods. The aim of this paper is to propose security and privacy issues of the wireless networks and present them through comprehensive surveys. In context of security issues, there are 2 typical DDoS attacks - HTTP flood and SYN flood. Other than DDoS attacks, there are several other threats to wireless networks. One of the most prevalent include security issues in Internet of Things. In terms of privacy issues in a wireless network, location-based applications, individual data, cellular network and V2G (Vehicle to Grid) network are surveyed. The survey is hosted using questionnaire and responses of 70 participants is recorded. It is observed from the survey results that many groups of people lack the knowledge of security and privacy of wireless technologies and networks despite their increased use, however, students are relatively more aware and have strong knowledge of those issues. It is concluded from the results that an effective solution to these problems can be hosting campaigns for spreading the security and privacy laws to help the groups of people who are lagging behind in this domain of knowledge become more aware. A unique solution is also presented to overcome the security issues which include implementation of detection and mitigation techniques, implementing Blockchain in the IoT devices and implementing fog computing solutions. The unique solutions to overcome the privacy issues are proposed in the form of a privacy approach from the LBS server between pairs of users to increase the implementation of DSPM and blockchain as a solution.

One of the most critical aspects in introral impression is the detection of the finish line, in particular in case of subgingival preparations. The aim of these in vitro study was to evaluate the accuracy among four different IntraOral Scanners (IOSs) in scanning a subgingival vertical margins preparation (VP). A reference maxillary typodont (MT) was fabricated with a VP for full crown on #16 and #21. The MT was scanned with a laboratory scanner (Aadva lab scanner, GC, Tokyo, Japan) to obtain a digital MT (dMT) in .stl format file. A group of 40 digital casts (dIOC) were obtained by scanning the MT 10 times with four different IOSs (Trios 3, 3Shape A/S), ( I700, Medit), (Vivascan, Ivoclar), (Experimental IOS, GC). All the obtained dIOCs were imported into an inspection software program (Geomagic Control X; 3D SYSTEMS) to be superimposed to the dMT, to calculate trueness. Therefore, in order to calculate precision all the scans of the same scanner group were superimposed onto the cast that obtained the best result of trueness. Results were collected as root mean square value (RMS) on #16 and #21 abutment surfaces and on a marginal area positioned 1 mm above and below the gingival margin. A nonparametric analysis Kruskal-Wallis test was performed to compare the RMS values obtained in the different iOS groups for trueness and precision. Statistically significance was set at 0.05. The trueness on #16 abutment, did not statistically differ in between the IOS, while on #21 abutment, Vivascan (56.0 ±12.1) and Experimental IOS, GC (59.2±2.7) performed statistically better than the others. Regarding precision Experimental IOS, GC and Trios 3 were significantly better than I700 and Vivascan both in the #16 (10.7±2,1; 15.8 ± 2,7) and in the #21 area (16.9±13.8 ; 18.0±2.7). At marginal level for both #16 and #21 all the IOS reported reduced accuracy compared to clinical acceptance.

Background: DICER1, cancer predisposition syndrome (CPS), seems to escape timely diagnosis in pediatric patients. Case report 1: A 16-year-old female patient was referred to the endocrinology ward due to a large goiter. Her medical history indicated normal sexual maturation, with menarche occurring at 13.5 years. Over the past 2.5 years, she developed pronounced androgenic symptoms, including a deepened male voice, facial, back and neckline acne, hirsutism, and menstrual irregularities leading to secondary amenorrhoea. A thyroid ultrasound identified a multinodular goiter with cystic-solid lesions containing calcifi-cations. An abdominal ultrasound identified a 5.7x6.9 cm solid mass in the right adnexal region, displacing the uterus to the left. Histopathological examination confirmed a Sertoli-Leydig cell tumor. The patient was subjected to total thyroidectomy. Histopathology revealed benign follicular cell-derived neoplasms. Thyroid follicular nodular disease was diagnosed bilaterally. DNA analysis using NGS, confirmed by the Sanger method, revealed a pathogenic heterozygotic variant c.2953>T [p.Gln985*] in exon 18 of DICER1 gene. Case report 2: A 12-year-old male patient was admitted to the pediatric surgery unit due to a 33 ml goiter. A month prior to admission, the patient discovered a palpable nodule in his neck, accompanied by hoarseness. An ultrasound revealed a multinodular goiter. Molecular analysis revealed a pathogenic heterozygotic variant c.2782C>T [p.Gln928Ter] in exon 17 of DICER1 gene. Subsequently, a total thyroidectomy was performed, and histopathological examination revealed thyroid follicular nodu-lar disease bilaterally. Conclusion: Multinodular goiter, although rare in pediatric population, when accompanied by characteristic ultrasound and histopathological features, and by additional features such as androgen excess, warrants exclusion of DICER1 syndrome.

(1) Background: adnexal masses during pregnancy detection are increased due to the use of first trimester screening and to advanced maternal age. Although the low risk of malignancy, other risks are associated: torsion, rupture or labour obstruction. Correct diagnosis and management are fundamental to guarantee both maternal and fetal safety. Adnexal masses may be troublesome to classify during pregnancy due to the increase in the uterus volume and to pregnancy-related hormonal changes. Management should be based on ultrasound examination to provide the best treatment. (2) Methods: the aim was to describe the ultrasound features of ovarian masses detected during pregnancy. We evaluated patient’s management, perinatal outcomes and follow-up. (3) Results: our study demonstrated that the management should be guided by an accurate ultrasound examination performed by an expert operator according to standardized techniques. Secondly, our results confirm the data present in the literature: the masses are most frequently benign, ultrasound follow-up is the best management strategy and obstetric outcome is not considerably affected. (4) Conclusions: the management of patients with ovarian masses detected during pregnancy should be based on ultrasound examination and a centralization in referral centers for ovarian masses should be considered.

Endobronchial Ultrasound has been widely used in the lymph node staging of lung tumors and the diagnosis of mediastinal diseases. In the last decades this procedure has evolved in several technical aspects, with new tools available to optimize the tissue sampling and to increase the diagnostic yield, like elastography, different types of needles and, most recently, miniforceps and cryobiopsy. Then, also the indications for EBUS have extended beyond the thoracic boundaries to sample lesions of the liver, left adrenal gland and retroperitoneal lymph nodes via the gastroesophageal tract. In this review we will analyze the actual indication of EBUS, even the more unusual, to underline the multiple use of EBUS in clinical practise.

Since the advent of the Internet, there has been a significant shift from wired to wireless communication between devices. The volume of data transmitted has surged, primarily driven by the exponential growth of network services, Internet of Things (IoT) devices, and online users. This trend became especially pronounced with the onset of the COVID-19 pandemic, as the Internet's role and significance expanded dramatically. People began to spend more time online, engaging in activities like e-learning, remote work, and online shopping. Concurrently, concerns about the security of wireless communication channels have escalated. As more data is stored and transmitted over the Internet, cybercriminals are actively seeking unauthorized access to it to further their malicious objectives. Through a comprehensive literature review in the realm of wireless network security and privacy, it has become evident that several factors render these networks susceptible to vulnerabilities. The aim of this paper is to shed light on the major and common security and privacy challenges faced by existing wireless networks. Additionally, it seeks to demonstrate the array of techniques available to mitigate these issues. Ultimately, this paper will culminate in an in-depth analysis of cybersecurity measures to address the issues in wireless networks.

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.

Embryological development of pancreas is a complex phenomenon and therefore, it can have multiple developmental aberrations. Fortunately, majority of these pancreatic ductal anomalies are asymptomatic with no clinical relevance and are incidentally detected during diagnostic cross sectional imaging or endoscopic retrograde cholangiopancreatography (ERCP) or autopsy. Occasionally, pancreatic duct anomalies can result in symptoms like abdominal pain or recurrent pancreatitis. Also, accurate pre-operative diagnosis of ductal anomalies can prevent inadvertent duct injury during surgery. Conventionally, ERCP had been used for accurate diagnosis of pancreatic duct anomalies. However, because of being invasive and associated with risk of pancreatitis, it has been replaced with magnetic resonance cholangiopancreatography (MRCP). MRCP has demonstrated high sensitivity and specificity for diagnosis of ductal anomalies which can be further improved with use of secretin enhanced MRCP. Endoscopic ultrasound (EUS) is a new diagnostic and interventional tool in the armamentarium of endoscopists and has demonstrated promising results in detection of pancreatic duct variations and anomalies. In this article, we will focus on the role of EUS in diagnosis of various pancreatic duct anomalies.

Background: Hashimoto’s thyroiditis (HT) is an autoimmune disease that progressively leads to thyroid gland destruction and hypothyroidism. Patients produce antibodies against two thyroid-specific antigens: thyroglobulin and thyroid peroxidase. As a result of the abnormal amount of thyroid hormone produced and its autoimmune etiology, patients with HT display a higher frequency of either autoimmune or non-autoimmune dermatological disorders. On ultrasound examination, HT can be detected by observing an enlarged thyroid gland with hypoechoic parenchymal regions or by observing a small gland indicating atrophy and diffusely heterogeneous parenchyma. Changes in the parenchymal vascularity can be observed as decreased or increased levels of vascularization. Objective: This study aimed to analyze the role of clinical data and ultrasound evaluation of patients with HT in suggesting an association with dermatological disorders. Patients and methods: Complete dermatological and endocrinological assessments as well as ultrasonography of the thyroid and lymphnodes were performed in HT patients. Results: The data obtained showed that a family history of thyroid disease, increased diameter of the inferior thyroid artery, and the presence of cervical lymphadenopathy were more frequent in the group of patients with dermatological diseases. Taken together, our results suggest the usefulness of ultrasound in determining a possible association between HT and dermatological disorders.

In recent years, wireless networks have undoubtedly become a convenient way to connect to the Internet and provide connection to everyone in any corner of the world. In fact, in this era, people are connected to the internet almost everyday and wireless networks give us this privilege in a seamless manner. A wireless network normally consists of access points and nodes where the access points are responsible to amplify the wireless signals, while the nodes are the gadgets that are receiving these signals. However, with such great convenience provided, many challenges are also faced by the users and stakeholders. With no physical connection to devices, wireless networks are evidently more vulnerable to invisible cyber attacks. In this research paper, it the security issues that cause issues in the wireless networks are discussed. Furthermore, an analytical review of privacy challenges found in these networks is performed; these challenges are segregated into security issues and privacy issues. The paper will then present the methods used in conducting a survey and gathering the research results along with further discussion on the results obtained through this study. Finally, a suitable solution is proposed to prevent and overcome the intrusions faced in terms of security and privacy in wireless network scenarios through detection and response mechanism for mitigation of the problems.

The rapid growth of network services, Internet of Things devices and online users on the Internet have led to an increase in the amount of data transmitted daily. As more and more information is stored and transmitted on the Internet, cybercriminals are trying to gain access to the information to achieve their goals, whether it is to sell it on the dark web or for other malicious intent. Through thorough literature study relating to the causes and issues that are brought from the security and privacy segment of wireless networks, it is observed that there are various factors that can cause the networks to be an insecure; especially factors that revolve around cybercriminals with their growing expertise and the lack of preparation and efforts to combat them by relevant bodies. The aim of this paper is to showcase major and frequent security as well as privacy issues in wireless networks along with specialized solutions that can assist the related organizations or the public to fathom how great of an impact these challenges can bring if every related stakeholder took a step in reducing them. Through this paper it is discovered that there are many ways these challenges can be mitigated, however, the lack of implementation of privacy and security solutions is still largely present due to the absence of practical application of these solutions by responsible parties in real world scenarios.

Applications for Wireless Sensor Networks (WSNs) range from monitoring the environment to automating factories. However, sustained and effective functioning is made more difficult by Sensor Nodes (SNs) limited energy supplies in which optimization is the main issue. So with the aim of increasing the lifespan by decreasing the energy consumption of WSN, Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol with Deep Learning (DL) algorithm is analyzed in this paper. LEACH is a hierarchical mechanism that elects Cluster Heads (CHs) and regularly rotates their positions in order to allocate energy use effectively by using the same amount of energy. However, Deep Learning (DL) method is used to further improve energy optimization. In many applications, the types of Deep Learning methods like Artificial Neural Networks (ANNs) have shown to be very useful. Using this method, WSNs may make more efficient decisions that reduce energy consumption. Data aggregation, duty cycling, and transmission protocols may all be optimized by Deep Learning model's ability to recognize patterns and forecast network behavior. This results in lower energy consumption, a longer lifespan for the network, and better overall performance.

Network Simulators (NS) is typically used to study services and applications in complex scenarios due to the infeasibility of deploying real testbeds. This is the case of Mobile Ad hoc Networks (MANETs) which can be extensively used in emergency situations or to gather information without infraestructure. An important factor to get realiable results in the MANETs’ simulations is the wireless channel module of NSs. In this report, we explain how thw wireless channel is implemented in NS-3 and it can be configured.

Wireless Sensor Networks (WSN) is designed to collect information across a large number of limited battery sensor nodes. Therefore, it is important to minimize the energy consumption of each node, which leads to the extension of the network life. Our goal is to design an intelligent WSN that collects as much information as possible to process it intelligently. To achieve this goal, an agent has been migrated to each node in order to process the information and to cooperate with these neighboring nodes while Mobile Agents (MA) can be used to reduce information between nodes and send those to the base station (Sink). This work proposes to use communication architecture for wireless sensor networks based on the Multi Agent System (MAS) to ensure optimal information collection. The collaboration of these agents generates a simple message that summarizes the important information in order to transmit it by a mobile agent. To reduce the size of the MA, the nodes of the network have been grouped into sector. As for each MA, we have established an optimal itinerary, consuming a minimum amount of energy with the data aggregation efficiency in a minimum time. Successive simulations in large scale wireless sensor networks through the SINALGO simulator show the performance of our proposal, in terms of energy consumption and package delivery rate.

Imaging of the ocular vasculature can provide new insights into the pathophysiology of ocular diseases. This study proposes a novel high-frequency super-resolution ultrasound localization microscopy (SRULM) technique and evaluates its ability to measure in vivo perfusion changes in the rat eye at elevated intraocular pressure (IOP). A 38.4 MHz center frequency linear array transducer on a VisualSonics Vevo F2 imaging platform was used to collect high frame rate (1 kHz) radiofrequency data of the posterior rat eye following systemic microbubble contrast injection. Following clutter and spatiotemporal non-local means filtering, individual microbubbles were localized and tracked. The microbubble tracks were accumulated over 10,000 frames to generate vascular images quantifying perfusion velocity and direction. Experiments were performed using physiologic relevant controlled flow states for algorithm validation and subsequently performed in vivo on the rat eye at 10 mm Hg IOP increments from 10 to 60 mm Hg. The posterior vasculature of the rat eye, including the ophthalmic artery, long posterior ciliary arteries and their branches, central retinal artery and retinal arterioles and venules were successfully visualized, and velocities quantified at each IOP level. Significant reductions in arterial flow were measured as IOP was elevated. High-frequency SRULM can be used to visualize and quantify perfusion velocity of the rat eye in both the retrobulbar and intraocular vasculature simultaneously. The ability to detect ocular perfusion changes throughout the depth of the eye may help elucidate the role ischemia has in the pathophysiology of ocular diseases such as glaucoma.

Background: clubfoot is a common congenital deformity. The Ponseti technique, involving early corrective manipulations followed by the application of long leg casts and Achilles tenotomy, is widely accepted as the preferred treatment. Rapid healing of the tendon after surgery has been documented, but the aspect regarding tendon structure and properties is not known. Three cases of Achilles tendon rupture in adolescent previously treated for clubfoot have been described in the literature. Since rupture is a rare event in this age group a possible correlation with previous surgery has been hypothesized. The primary aim of the study was to compare the ultrasound findings of the Achilles tendon, in patients treated for clubfoot, between patients treated with casting alone and the ones who underwent surgery (percutaneous tenotomy or Z-plasty lengthening). Methods: 22 asymptomatic patients, (34 feet) median age 12 years, previously treated for clubfoot, were recruited for this study; the patients underwent an Achilles tendon ultrasound examination during a follow-up outpatient visit. Results: a greater thickness and structural alterations with presence of hypoechoic areas of the operated tendons compared to those treated with plaster alone were observed (p value: 0.0498 and

Ultrasound (US) has become a widely used imaging modality in clinical practice, characterized by its rapidly evolving technology, advantages, and unique challenges such as low imaging quality and high variability. There is a critical need to develop advanced automatic US image analysis methods to enhance diagnostic accuracy and objectivity. Vision transformer, a recent innovation in machine learning, has demonstrated significant potential in various research fields, including general image analysis and computer vision, due to its capacity to process large datasets and learn complex patterns. Its suitability for automatic US image analysis tasks, such as classification, detection, and segmentation, has been recognized. This review provides an introduction to vision transformer and discusses its applications in specific US image analysis tasks, while also addressing the open challenges and potential future trends in its application in medical US image analysis. Vision transformer has shown promise in enhancing the accuracy and efficiency of ultrasound image analysis and is expected to play an increasingly important role in the diagnosis and treatment of medical conditions using ultrasound imaging as technology progresses.

Endoscopic ultrasound-guided gallbladder drainage (EUS-GBD) is an alternative to surgery for acute cholecystitis (AC) in poor operative candidates. However, the role of EUS-GBD in non-cholecystitis (NC) indications has not been well studied. We compared clinical outcomes of EUS-GBD for AC and NC indications. Consecutive patients undergoing EUS-GBD for all indications at a single center were retrospectively analyzed. Fifty-one patients underwent EUS-GBD during the study period. Thirty-nine (76%) patients had AC while 12 (24%) had NC indications. NC indications included malignant biliary obstruction (n = 8), symptomatic cholelithiasis (n = 1), gallstone pancreatitis (n = 1), choledocholithiasis (n = 1), and Mirizzi’s syndrome (n = 1). Technical success was noted in 92% (36/39) for AC and 92% (11/12) for NC (p &gt; 0.99). Clinical success rate was 94% and 100%, respectively (p &gt; 0.99). There were 4 adverse events in the AC group and 3 in the NC group (p = 0.62). Procedure duration (median 43 vs 45 minutes, p = 0.37), post-procedure length of stay (median 3 vs 3 days, p = 0.97), and total gallbladder related procedures (median 2 vs 2, p = 0.59) were similar. EUS-GBD for NC indications is similarly safe and effective as EUS-GBD in AC.

Metabolic-associated fatty liver disease (MASLD) is not only associated with traditional cardiovascular risk factors such as T2DM and obesity, but it is also an independent risk factor for the development of cardiovascular disease. MASLD has been shown to be independently related to endothelial dysfunction and atherosclerosis. MASLD is characterized by a chronic proinflammatory response that, in turn, may induce a prothrombotic state. Several mechanisms such as endothelial and platelet dysfunction, changes in the coagulation cascade, decreased fibrinolytic activity can contribute to induce the prothrombotic state. Platelets are players and addresses of metabolic dysregulation; obesity and insulin resistance are related to platelet hyperactivation. Furthermore, platelets can exert a direct effect on liver cells, particularly through the release of mediators from granules. Growing data in literature support the use of antiplatelet agent as a treatment for MASLD. The use of antiplatelets drugs seems to have potential clinical implication for the prevention of HCC patients with MASLD, since platelets contribute to fibrosis progression and cancer development. This review aims to summarize the main data on the role of platelets in the pathogenesis of MAFLD and its main complications such as cardiovascular events and the development of liver fibrosis. Furthermore, we will examine the role of antiplatelet therapy not only in the prevention and treatment of cardiovascular events but also as a possible anti-fibrotic and anti-tumor agent.

Propagation of electromagnetic (EM) waves inside and on the surface of the human body is the subject of active research in area of biomedical applications. This research area is the basis for wireless monitoring of biological object parameters and characteristics. Much attention has been paid to radio-frequency identification systems, which are intended for biomedical applications. Solutions to the following problems are crucial to achieve the stated goals in the area of wireless monitoring: EM wave propagation inside regular and multilayer biological media, through the interface between different media, and on-body surface wave propagation. The biological object monitoring is based on a consideration of the followingprocesses: a) propagation of the EM wave in a biological medium considered as the dielectric with a high dielectric permittivity and substantial conductivity; b) penetration of the EM wave through the biological medium–air interface (wave reflection and refraction); c) propagation of the EM wave in a multi-layer biological medium; d) propagation of the EM wave along the plane or curved surface of biological objects.

It is since long known, that SAW devices, resonators as well as delay lines, can be used as passive wireless sensors for physical quantities like temperature and pressure as well as gas sensors or ID-Tags. The sensors are robust, work passively without battery, can be applied at high temperatures and provide a high resolution. Nevertheless, if the devices should be readout wirelessly in an industrial environment, several constraints have to be taken into account, especially when more than one quantity or device needs to be measured at the same time. The paper addresses the challenges that have to be tackled when establishing multi-sensor-wireless-readout for industrial applications. Major issues here are the legal ISM-band regulations, as well as sampling time and costs, which impose severe restrictions to any system design. We describe several design approaches and their constraints. We have successfully designed sensors based on reflective delay lines that allow the parallel readout of four independent temperature sensors in the 2.45 GHz ISM-band. These devices have been fabricated, positively tested and demonstrate the applicability of SAW sensors for industrial applications.

This study describes the design and implementation of an electronic nose, which was applied to classify and identify hazardous gases generated in underground coal mines. For this purpose, an electrochemical sensor array was used to detect a set of toxic gases. This work illustrates the electronic components of a wireless multisensory system for the toxic gases detection on indoor environments (i.e., underground mines), which was performed with reduced size, low cost and low electrical consumption, in order to detect different compounds using the basic principle of operation of each component to be applied to the target gas. Furthermore, the sample collection, data communication and data processing in real time obtained an excellent performance for gas sensing and even to measure the concentration level of the chemical volatile compounds transmitted from different points of the detection zone. The results demonstrated that using a wireless electronic nose for toxic gases detection was possible to reach a success rate of discrimination of 97%, using principal components analysis (PCA) and Linear Discriminant Analysis (LDA).

Bisphenol-A (BPA) represents an important co-monomer for obtaining polycarbonate, epoxy resins, flame retardants, in paint, and other chemicals products. Products containing BPA are widely used, and thus, we can find it in the environment: in the air, in the soil, in natural surface water and in sediments, underground water in landfills, and in wastewater. BPA disturbs human and animals’ health. This influences the enzymatic, androgenic, neurological, liver and reproductive systems at different stages of human life: like in fetal stage, children and adults’ stages. Taking these inconveniences into account, it is very important to remove BPA from water. Ultrasonic technology can be considered a verry sustainable and efficient method to remove BPA from water. The advantages of this method is easy to implement on existing water treatment and purification facilities, it does not produce residual compounds that produce sludge, the time required for degradation is of the order of 1-2 hours and the level of degradation is very high. In this work, we presented the studies on the efficiency of ultrasonics under air atmosphere on the degradation of BPA. The influence of the frequency and of some additional compounds such as carbon tetrachloride, FeSO4 7H2O (FS), and ethyl anthraquinone (EAC) was studied. Three different frequencies were used: 1146 KHz, 864 KHz, 580 KHz, at a power of 50 W. It was identified the efficiency of BPA degradation over a period of 60 minutes, with sampling every 15 minutes. Using the LC-MS/MS technique, the degradation compounds were identified that result from the application of ultrasound processes. Pathways of BPA degradation were also proposed.

IoTs and WSNs utilize their connectivity to enable solutions supporting a spectrum of industries in different and volatile environments. To effectively enhance the security and quality of service of networks, empirical research should take into account a variety of factors and be structured in a replicable manner. This will not only ensure scalability but also enable verification of conclusions, leading to more constructive outcomes. Cooja offers limited performance analysis capabilities of simulations, which are often extracted and calculated manually. In this paper, we introduce a framework and a toolkit that enable researchers to conduct structured and conclusive experiments considering different factors and metrics, experiment design to results analysis. Besides, this tool summarizes multiple network metrics and allows multiple scenarios. As proof of concept, this paper studies the flooding attacks on IoT and illustrates their impact on the network, leveraging the proposed framework and tools.

Load balancing, energy efficiency and fault tolerance are among the most important data dissemination issues in Wireless Sensor Networks (WSNs). In order to successfully cope with the mentioned issues, two main approaches (namely, Data-centric Storage and Distributed Data Storage) have been proposed in the literature. Both approaches suffer from data loss due to memory and/or energy depletion in the storage nodes. Even though several techniques have been proposed so far to overcome the mentioned problems, the proposed solutions typically focus on one issue at a time. In this paper, we integrate the Data-centric Storage (DCS) features into Distributed Data Storage (DDS) mechanisms and present a novel approach, denoted as Collaborative Memory and Energy Management (CoMEM), to overcome both problems and bring memory and energy efficiency to the data loss mechanism of WSNs. We also propose analytical and simulation frameworks for performance evaluation. Our results show that the proposed method outperforms existing approaches in various WSN scenarios.

Wireless Sensor Networks (WSNs) are being increasingly adopted in critical applications, where verifying the correct operation of sensor nodes is a major concern. Undesired events may undermine the mission of the WSNs. Hence their effects need to be properly assessed before deployment to obtain a good level of expected performance and during the operation in order to avoid dangerous unexpected results. In this paper we propose a methodology to support design and deployment of dependable WSNs by means of an event-based formal verification technique. The methodology includes a process to guide designers towards the realization of a dependable WSN and a tool ("ADVISES") to simplify its adoption. The tool allows to generate automatically formal specifications used to check correctness properties and evaluate dependability metrics at design time and at runtime. During the runtime we can check the behavior of theWSN accordingly to the results obtained at design time and we can detect sudden and unexpected failures, in order to trigger recovery procedures. The effectiveness of the methodology is shown in the context of two case studies, aiming to illustrate how the tool is helpful to drive design choices and to check the correctness properties of theWSN at runtime

Background and Objectives: Ultrasound (US) is a non-invasive tool for the in-vivo detection of peripheral nerve alterations. Materials and Methods: In this study we applied nerve US to assist the discrimination between the spectrum of Amyotrophic Lateral Sclerosis (ALS, n=11), chronic inflammatory demyelinating polyradiculoneuropathy (CIDP, n=5) and genetically confirmed Charcot-Marie-Tooth disease (CMT, n=5). All participants and n=15 controls without neurological diseases underwent high-resolution US of the bilateral tibial nerve. Nerve cross-sectional area (CSA) and nerve microvascular blood flow were compared between the groups and related to cerebrospinal fluid (CSF) measures, clinical symptoms and nerve conduction studies. Analyses are part of a larger multimodal study on the comparison between US and 7 Tesla (T) magnetic resonance neurography (MRN). Results: Patients and controls were matched with respect to their demographical data. CMT had the longest disease duration, followed by CIDP and ALS. CSA was related to age, weight and disease duration. CSA was larger in CMT and CIDP compared to ALS and controls. Blood flow was greatest in CIDP, and higher than in CMT, ALS and controls. In ALS, greater CSA was correlated with greater CSF total protein and higher albumin quotient. US measures did not correlate with clinical scores or nerve conduction studies in any of the subgroups. Conclusion: Our results point towards the feasibility of CSA and blood flow to discriminate between ALS, CIDP and CMT, even in small sample sized groups. In ALS, larger CSA could indicate an inflammatory disease subtype characterized by reduced blood-nerve barrier integrity. Our upcoming analysis will focus on the additive value of 7T MRN in combination with US to disentangle the spectrum between more inflammatory or more degenerative disease variants along the disease groups.

The analysis of data produced by the MV20/20 sensor, tagged with quality outcomes, is presented with the aim of developing a predictor model for real-time anomaly detection and classification. Three types of inclusions, undesired particles that deteriorate the quality of production, are used to tag the quality data using results from the lab. We explore both unsupervised and supervised learning, which both offer advantages in monitoring and controlling the quality of production. It is discovered that the dataset can be clustered using techniques like K-Means and DBSCAN. Bounding the data within a 95% confidence interval ellipse ensures we can detect anomalous events in real time. For supervised learning, a two-stage classifier is explored, which classifies the outcome of a cast and secondly the inclusion responsible for the negative outcome. We explore models from logistic regression and support vector machines, to two neural networks, namely the multi-layer perceptron and the radial basis function network. While the cast outcome is adequately predicted by all the models, the multi-layer perceptron provides a boundary performance for the inclusion type. A more advanced technique for model optimisation, namely grid search, is applied in order to improve on the results. The outcome for the grid search is not much better, which indicates a global maximum in the learning capacity of the model. Recommendations include the addition of sensor systems and an audit of data collection variation.

The current Covid-19 pandemic has hugely disrupted the delivery of routine and established medical care. Patients can develop a wide range of clinical signs and symptoms from a cough and fever to severe respiratory failure. There is an ongoing argument on a concise investigative pathway to ensure the safety of all healthcare workers. The stethoscope can help with any clinical respiratory assessment but the risk of cross infection is high. Computer tomography should not be routinely performed. There is a potential place for lung ultrasound but outcomes are not yet determined.

This paper presents an improved indoor localization system based on RF and ultrasonic signal which we named SNSH system. This system composes of a transmitter mounted in a mobile target, and a series of receiver nodes which are managed by a coordinator. By measuring Time Delay of Arrival (TDoA) of RF and ultrasonic signal from the transmitter, distance from target to receiver node is calculated and sent to the coordinator through CAN network, and all the information are gathered in PC to estimate 3D position of the target. Sine wave detector and dynamic threshold filter are applied to provide excellent accuracy of range measurement from TDoA result, and multilateration algorithms is realized to optimize coordinate determination accuracy. Specifically, Linear Least Square and Non-linear Least Square techniques are implemented to contrast their performances in target coordinate estimation. RF signal encoding/decoding time, time delay in CAN network and math calculating are carefully considered to ensure optimal system performance and get ready for field application. Experiments show that sine wave detector algorithm has greatly improved range measurement accuracy, with mean error at 2.2mm and maximum error at 6.7 mm, for distance below 5m. In addition, 3D position accuracy is greatly enhanced by multilateration methods, with mean error in position stay under 15mm, and 90% confident error values at 23mm for LLS, 20mm for NLS. Overall system update period has been verified in real system operation, with maximum rate at 25ms, and compared with other existing researches.

Next generation in-to-out-of body biomedical applications have adopted optical wireless communications (OWCs). However, by delving into the published literature, a gap is recognised in modeling the in-to-out-of channel, since most published contributions neglect the particularities of different type of tissues. Towards this direction, in this paper we present a novel pathloss and scattering models for in-to-out-of OWC links. Specifically, we derive extract analytical expressions that accurately describe the absorption of the five main tissues’ constituents, namely fat, water, melanin, oxygenated and de-oxygenated blood. Moreover, we formulate a model for the calculation of the absorption coefficient of any generic biological tissue. Next, by incorporating the impact of scattering in the aforementioned model we formulate the complete pathloss model. The developed theoretical framework is verified by means of comparisons between the estimated pathloss and experimental measurements from independent research works. Finally, we illustrate the accuracy of the theoretical framework in estimating the optical properties of any generic tissue based on its constitution. The extracted channel model is capable of boosting the design of optimized communication protocols for a plethora of biomedical applications.

With the widespread use of electric machines there is a growing need to extract information from the machines to optimize their control systems and maintenance management. The present work shows the development of an embedded system to perform the monitoring of an squirrel cage induction motor rotor physical variables. The system comprises: circuit to acquire desirable rotor variable(s) value(s) and send it to the computer; a rectifier and power storage circuit that besides converting an alternating current in continuous also store energy for a certain amount of time to wait the motor engine shutdown; and magnetic generator that harvest energy from rotating field to power the circuits mentioned above. The embedded system is set on the rotor, making it difficult to power the system because it is rotating, problem solved with the construction of the magnetic generator eliminating the need of using batteries or collector rings and send data to the computer using a wireless NRF24L01 module. For the proposed system validation a temperature sensor (DS18b20) was used, variable known as the most important when identifying the need for maintenance and control systems. Tests were made getting satisfactory results proving the viability of using sensors on the rotor.

Abstract Purpose: This study aims to evaluate the potential of multimodal ultrasound techniques in improving the visibility of liver lesions that are indistinct under conventional ultrasound. Specifically, we will explore the application of fusion imaging, contrast-enhanced ultrasound (CEUS), and high-frequency ultrasound in enhancing the visibility of liver masses. These techniques will be utilized to assist in visualizing liver lesions and to accurately localize them for the purpose of performing percutaneous tissue biopsy. Lastly, we will compare the biopsy results with the final diagnosis to assess whether multimodal techniques can enhance the success rate of percutaneous biopsy for liver masses that are not clearly visible under conventional ultrasound. Furthermore, the potential impact of these techniques on the development of personalized treatment strategies for patients was also discussed. Materials and Results: A retrospective analysis was conducted on 144 patients with liver masses who underwent conventional ultrasound examinations at our hospital from October 2018 to January 2024. These patients had poor visibility on conventional ultrasound, but the tumor location was visible on abdominal computerized tomography (CT) or magnetic resonance imaging (MRI) scans. We excluded 71 patients who did not undergo percutaneous liver tumor biopsy and 8 patients who remained non-visualized under multimodal ultrasound. Finally, 95 patients met the inclusion criteria and their clinical and radiological data were selected for analysis. Computerized tomography or magnetic resonance imaging-ultrasound (CT/MR-US) fusion imaging was performed in 55 patients, CEUS was conducted in 95 patients, and high-frequency ultrasound examination was performed in 21 patients. The visibility of the lesions using these three techniques was evaluated, and the consistency between the biopsy pathology and the final diagnosis was analyzed. Results: In the study, a total of 39 cases were identified as solitary liver lesions, 34 cases as multiple lesions, and an additional 23 cases as diffuse hepatocellular carcinoma. Among them, there were 13 cases (13.7%) of lesions located in the left lobe, 73 cases (76.8%) in the right lobe, and 9 cases (9.4%) at the junction of the left and right lobes. The average maximum diameter of the lesions was 2.7 cm (ranging from 0.7 cm to 10.0 cm). The detection rates of lesions using CT/MR-US fusion imaging, contrast-enhanced ultrasound (CEUS), and high-frequency ultrasound examination were 49.1%, 96.8%, and 76.2%, respectively. All patients in the entire cohort underwent percutaneous ultrasound-guided biopsy after confirming the target location of the lesions, including 9 patients underwent percutaneous microwave ablation. No severe complications were observed. The accuracy rate of the biopsies was 91.6%, and the positive concordance rate was 91.1%. The biopsy pathology included 39 cases of hepatocellular carcinoma (HCC), 16 cases of intrahepatic cholangiocarcinoma (ICC), 22 cases of metastatic adenocarcinoma, 3 cases of hepatic adenoma (HA), 1 case of vascular sarcoma, and 1 case of mixed HCC-ICC. Among the 13 patients with negative pathology findings after biopsy, 8 cases were considered false negatives (based on follow-up laboratory tests and imaging results consistent with malignant tumor characteristics), resulting in a false negative rate of 8.9%. Conclusions: The application of multimodal ultrasound technology can significantly improve the success rate of liver lesion biopsies that are difficult to visualize using conventional ultrasound. Furthermore, it will facilitate the guidance of microwave ablation therapy for lesions using multimodal ultrasound imaging, enabling collaborative precision treatment planning for patients with clinical physicians.

Background: Endoscopic Ultrasound (EUS) is widely used for the diagnosis of bilio-pancreatic and gastrointestinal (GI) tract diseases, for the evaluation of subepithelial lesions, and for sampling of lymph nodes and solid masses lo-cated next to the GI tract. The role of Artificial Intelligence in healthcare in growing. This review aimed to provide an overview of the current state of AI in EUS from imaging to pathological diagnosis and training. Methods: AI algorithms can assist in lesion detection and characterization in EUS by analysing EUS images and identifying suspicious areas that may require further clinical evaluation or biopsy sampling. Deep learning tech-niques, such as convolutional neural networks (CNNs), have shown great potential for tumour identification and subepithelial lesion (SEL) evaluation by extracting important features from EUS images and using them to classify or segment the images. Results: AI models with new features can increase the accuracy of diagnoses, provide faster diagnoses, identify subtle differences in disease presentation that may be missed by human eyes, and provide more information and in-sights into disease pathology. Conclusions: The integration of AI in EUS images and biopsies has the potential to improve the diagnostic accura-cy, leading to better patient outcomes and to a reduction of repeated procedures in case of non-diagnostic biopsies.

Ultrasound is a well-known tool to produce thermal and non-thermal effects on cells and tissues. These effects require a correct application of ultrasound in terms of localization and acoustic energy delivered. This article describes a new device that combines ultrasound and Dry Needling treatments. The ultrasound transducer can rotate in 3D space mechanically to align itself in the direction of the needle. The transducer electronically focuses the acoustic pressure automatically on the needle tip and its surroundings. A computer, using graphical interface software, controls the angulation of the array and the focus position.

The manuscript presents the use of three novel technologies for the implementation of wireless green battery-less sensors that can be used in agriculture. The three technologies, namely additive manufacturing, energy harvesting, and wireless power transfer from airborne transmitters carried from UAVs, are considered for smart agriculture applications. Additive manufacturing is exploited for the implementation of both RFID based sensors and passive sensors based on humidity sensitive materials. A number of energy-harvesting systems at UHF and ISM frequencies are presented which are in position to power platforms of wireless sensors, including humidity and temperature IC sensors used as agriculture sensors. Finally, in order to provide the wireless energy to the soil-based sensors with energy harvesting features, wireless power transfer (WPT) from UAV carried transmitters is utilized. The use of these novel technologies can facilitate the extensive use and exploitation of battery-less wireless sensors which are environmentally friendly and thus “green”. Additionally, it can potentially drive precision agriculture in the next era, through the implementation of a vast network of wireless green sensors which can collect and communicate data, to airborne readers so as to support with data the Artificial Intelligence and Machine Learning based, decision making platforms.

Extensive research has been conducted on printable antenna technologies, believed to be fast-growing due to their significant impact on wireless devices. It is necessary to study the progress of printable antenna technology as they are core devices for wireless technology today. This review work offers a comprehensive account of the previous and recent research achievements based on the principle of printable antenna, and parametric studies of several key design parameters, for future wireless network applications. The systems considered for evaluation include broadband techniques, large Bandwidth, high gain, dual/multi-band, or reconfigurable structure, low-profile, size-reduction, compact, linear, or circular polarization applications. It also highlights the fabrication procedures, and the numerous material characteristics affecting the antenna performance for various wireless applications with design considerations. Fully printed antennas on different substrates and conductive ink were investigated, including polyethylene terephthalate (PET), synthetic paper (Teslin), resin-coated photo paper, and Kapton polyimide substrates, among many others. The findings show that the fully inkjet-printed antenna made fabrication easy, improving the accuracy and conductivity of the printed patterns by concentrating on the inherently difficult problems and opportunities. Inkjet-printed antennas are believed to be the futuristic demand for sustainability and wireless solution in several ways.

The reliability of Underwater Wireless Sensor Networks (UWSNs) is measured in terms of energy consumption (EC), end-to-end delay(E2E) and packet delivery ratio (PDR). The adverse effects of channel may cause data loss. Reducing delay up to possible extend improves the reliability of the network, also increasing the number of nodes in a particular network increase reliability. Besides, increasing the number of nodes improve reliability but also increase power consumption. In order to overcome these shortcomings, the two routing protocols are proposed in this paper, namely Delay and Reliability Aware Routing (DRAR) protocol and Cooperative Delay and Reliability Aware Routing (Co-DRAR) protocol for UWSNs. In DRAR protocol, network is divided into two equal regions where two sink nodes(SNs) are positioned at upper region of the network and two SNs are placed at the mid region of the network. The protocol choose the relay node based on residual energy (RE), distance and Bit Error Rate (BER). These parameters protect the data packets from corruption and also provide stable path (where nodes remain active for longer period and do not die quickly). The protocol uses single link and may get worse sometimes while changing channel circumstances. To address this problem, cooperative routing scheme is added to DRAR protocol in order to developed its enhanced version known as Co-DRAR protocol. The protocol works by allowing the destination to receive multiple copies of data packets in order to decide the quality of packets. The proposed protocols DRAR and Co-DRAR perform routing irrespective to geographical position of sensors nodes conversely to the some of conventional routing protocols that's way our propose protocol better perform than the well-known protocol i.e. Depth base routing (DBR) in terms of EC, E2E, PDR, dead nodes, packet drop ratio and number of alive nodes (ANs).

Nowadays, information security is a challenge especially when transmitted or shared in public clouds. Many of researchers have been proposed technique which fails to provide data integrity, security, authentication and another issue related to sensitivity data. The most common techniques were used to protect data during transmission on public cloud are cryptography, steganography, and compression. The proposed scheme suggests an entirely new approach for data security on public cloud. Authors have suggested an entirely new approach that completely makes secret data invisible behind carrier object and it is not been detected with the image performance parameters like PSNR, MSE, entropy and others. The details of results are explain in result section of paper. Proposed technique have better outcome than any other existing technique as a security mechanism on a public cloud. Primary focus of suggested approach is to minimize integrity loss of public storage data due to unrestricted access rights by uses. To improve reusability of carrier even after data concealed is really a challenging task and achieved through suggested approach.

An effective battery management system (BMS) is indispensable for any lithium-ion battery (LIB) powered systems such as electric vehicles (EVs) and stationary grid-tied energy storage systems. Massive wire harness, scalability issue, physical failure of wiring, and high implementation cost and weight are some of the major issues in conventional wired-BMS. One of the promising solutions researchers have come up with is the wireless BMS (WBMS) architecture. Despite research and development on WBMS got momentum more than a decade ago, it is still in a preliminary stage. Significant further upgradation is still required towards developing an industry-ready WBMS, especially for high-power LIB packs. Therefore, an in-depth survey exclusively on WBMS architectures is presented in this article. The aim is to provide a summary of the existing developments as well as to present an informative guide to the research community for future development by highlighting the issues, emerging trends, and challenges. In-depth analysis of the existing WBMS topologies will not only help the researchers to understand the existing challenges and future research scopes clearly while at the same time enthuse them to focus their research inclination in the domain of WBMS.

Abstract Background: Analysis of different type of consolidation in dogs and cats relay on parenchymal and vascular criteria. Hypothesis: the vascular criteria of the consolidation it’s possible to perform in dogs and cats and vascularisation is different in shred, tissue, nodule, wedge sign and mass. Animals: 347 cats and 634 dogs with different types of consolidations. Methods: Retrospective study between 2018-2023. Lung ultrasound performed in dogs and cats with different types of consolidations. Characteristic of bronchogram: air dynamic and static bronchogram, fluid bronchogram or absence of bronchogram. Types of vascularisations in consolidation: tree like type, residual, chaotic vascularisation and penetrating from the chest wall to consolidation and “vascular sign”. Conclusion and Clinical Importance: Analysis of bronchogram and type of vascularisation in consolidation is possible to perform in dogs and cat. The analysis of mentioned criteria had an impact on subsequent diagnostic and therapeutic decisions

Model-based image reconstruction has brought improvements in terms of contrast and spatial resolution to imaging applications such as magnetic resonance imaging and emission computed tomography. However, their use for pulse-echo techniques like ultrasound imaging is limited by the fact that model-based algorithms assume a finite grid of possible locations of scatterers in a medium -- which does not reflect the continuous nature of real world objects and creates a problem known as off-grid deviation. To cope with this problem, we present a method of dictionary expansion and constrained reconstruction that approximates the continuous manifold of all possible scatterer locations within a region of interest. The expanded dictionary is created using a highly coherent sampling of the region of interest, followed by a rank reduction procedure based on a truncated singular value decomposition. We develop a greedy algorithm, based on the Orthogonal Matching Pursuit (OMP), that uses a correlation-based non-convex constraint set that allows for the division of the region of interest into cells of any size. To evaluate the performance of the method, we present results of 2-dimensional ultrasound image reconstructions with simulated data in a nondestructive testing application. Our method succeeds in the reconstructions of sparse images from noisy measurements, providing higher accuracy than previous approaches based on regular discrete models.

With the emergence of Advance Logistics, the logistics industry has witnessed significant advancements, leading to a greater reliance on intelligent technologies. These technologies play a crucial role in gathering and transmitting logistics data, but they also introduce security and privacy risks to logistics management systems. The sharing of customer-sensitive information among stakeholders for efficient operations becomes vulnerable to unauthorized access, thus compromising privacy. This, amongst others, is a critical problem that needs to be addressed. The unique features of a cryptographic hash function, including immutability, efficient verification, and anonymity, make it a transformative technology that has the potential to address the mentioned challenges in various sectors. This disruptive technology offers solutions by ensuring data integrity, enabling quick verification, and preserving privacy. The findings suggest that employing Cryptographic Hash Functions to share customer data among logistics partners offers robust protection against cyber-attacks. The proposed system guarantees asset security, and as demonstrated by the case study evaluation, exhibits strong resilience in safeguarding against various security and privacy threats. Although this study is significant, it does have limitations. One of these limitations is the considerable overlap between logistics research and supply chain management (SCM). While our focus was on logistics tasks, we did not extensively delve into the broader context of SCM

In the past few years, the possibility to transfer power wirelessly has experienced growing interest from the research community. Since the wireless channel is subject to a large number of random phenomena, a crucial aspect is the statistical characterization of the energy that can be harvested by a given device. For this characterization to be reliable, a powerful model of the propagation channel is necessary. The recently proposed Generalized-K model has proven to be very useful, as it encompasses the effects of path-loss, shadowing and fast fading for a broad set of wireless scenarios, and it is analytically tractable. Accordingly, the purpose of this paper is to characterize, from a statistical point of view, the energy harvested by a static device from an unmodulated carrier signal generated by a dedicated source, assuming that the wireless channel obeys the Generalized-K propagation model. Specifically, using simulation-validated analytical methods, this paper provides exact closed-form expressions for the average and variance of the energy harvested over an arbitrary time period. The derived formulation can be used to determine a power transfer plan that allows multiple or even massive numbers of low-power devices to operate continuously, as expected from future network scenarios such as IoT or 5G/6G.

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations (ABSs) has been considered to be a feasible solution to provide network coverage in scenarios where the conventional terrestrial network is overloaded or inaccessible due to an emergency situation. This article studies the problem of optimal placement of the UAVs as ABSs to enable network connectivity to the users in a coverage free zone. The main contributions of this work include two approaches to position the UAVs and to assign user equipment (UE) to each UAV, such that the sum-rate and the coverage probability of the network is maximized. An approach can be selected depending on the prevailing scenario. The first approach uses clustering algorithm to determine the 2D positioning of the UAV and a matching algorithm is used for UE assignment by considering the characteristics of the air-to-ground propagation channels as well as the impact of co-channel interference from ABSs. Then it uses exhaustive search on different altitudes to find the optimal altitude. In the second approach, 2D positioning and UE assignment are done similarly to the first approach. However, the sub-optimal altitude is estimated using particle swarm optimization (PSO). The first approach is suitable for a system which has computational resource constraints or lower probability of line of sight (LoS) links. In contrast, the second approach is suitable for data rate greedy systems or a higher probability of LoS links.

This paper proposes a hybrid medium access control (MAC) protocol for wireless sensor network (WSN) data gathering, employing unmanned aerial vehicles (UAV). The UAV sends a beacon frame periodically to inform sensor nodes regarding its presence. Afterward, each sensor node which receives beacon frame contends to send registration frame to the UAV. The UAV will transmit the second beacon frame to the registered nodes to notify their transmission schedule. The time-slot scheme is used for the transmission schedule. The transmission schedule of each sensor is determined based on their priority. Specifically, the priority of each sensor is determined during the registration process. Furthermore, the architecture of UAV-WSN data gathering system is introduced in this paper. Simulations are performed, showing that the proposed MAC protocol achieves fairness while enhancing network performance.

Compressive sensing originates in the field of signal processing and has recently become a topic of energy-efficient data gathering in wireless sensor networks. In this paper, we propose an energy efficient distributed compressive sensing solution for sensor networks. Proposed solution utilizes sparsity distribution of signals to group sensor nodes into several coalitions and then implements localized compressive sensing inside coalitions. This solution improves data-gathering performance in terms of both data accuracy and energy consumption. The approach curbs both data-transmission costs and number of measurements. Coalition-based data gathering cuts transmission cost, and the number of measurements is reduced by scheduling sensor nodes and adjusting their sampling frequency. Our simulation showed that our approach enhances network performance by minimizing energy cost and improving data accuracy.

Wireless sensor networks (WSN) are widely used in various fields such as military, industrial and transportation for real-time monitoring, sensing and data collection of different environments or objects. However, the development of WSN is hindered by several limitations, including energy, storage space, computing power and data transmission rate. Among these, the availability of power energy plays a crucial role as it directly determines the lifespan of WSN. To extend the life cycle of WSN, two key approaches are power supply improvement and energy conservation. Therefor, we proposed an energy harvesting system and a low energy consumption mechanism for WSN. Firstly, we delved into the energy harvesting technology of WSN, explored the utilization of solar energy and mechanical vibration energy to ensure a continuous and dependable power supply to the sensor nodes, and analyzed the voltage output characteristics of bistable piezoelectric cantilever. Secondly, we proposed a neighbor discovery mechanism that utilizes a separation beacon, is based on reply to ACK, and can facilitate the identification of neighboring nodes. This mechanism operates at a certain duty cycle ratio, significantly reduces idle listening time and results in substantial energy savings. In comparison to the Disco and U-connect protocols, our proposed mechanism achieves a remarkable reduction of 66.67% and 75% in the worst discovery delay, respectively. Furthermore, we introduced a data fusion mechanism based on integer wavelet transform. This mechanism effectively eliminates data redundancy caused by spatio-temporal correlation, results in a data compression rate of 5.42. Additionally, it significantly reduces energy consumption associated with data transmission by the nodes.

The sensor nodes have limited computation, sensing, communication capabilities and generally operated by batteries in a harsh atmosphere with non-replenish able power sources. These limitations force the sensor network subject to failure because most of the energy is spent on sensing, computing and data transmission. This paper introduces an Energy Efficient Clustering and Shortest-Path Routing Protocol (EECSRP) to assist Wireless Sensor Networks (WSNs) by (a) extending the lifespan of the network (b) effectively using the battery power (c) decreasing the network overhead and (d) ensuring a high packet transmission ratio with minimal delay. The delay time-based Cluster Head (CH) is elected based on the node degree, residual energy and Received Signal Strength (RSS) to accomplish the goal. Additionally, the RSS-based network partitioning is implemented to evaluate the gradient based on demand routing between source (sensing node) and destination (BS). Whenever the current CH residual energy goes under the threshold level, the proposed protocol performs the clustering process, reducing the exchange of control packets. However, the BS periodically gathers the data from every single CH which helps to reduce the collision and Medium Access Control (MAC) layer conflict. From the simulation results, it is the evident that the proposed protocol performance in terms of average end-to-end latency, packet delivery ratio, average energy consumption and control overhead is better than the well-known current protocols.

A new circuit model of the self-powered device for heart rate measurement is presented in this paper. This device consists of piezoelectric energy harvester (PEH), power management circuit (PMC) with energy storage, microcontroller, Photoplethysmography (PPG) sensor, and Wi-Fi module. The PEH is placed under the insole to harvest the pressure energy from human foot-step to generate ac power. In our model, a PEH is represented by sine voltage source, where its parameters were taken from experiments with 20 volunteers. The PMC is simplified by a switch with gain δ placed in series with the main circuit. The model of the main circuit is RC elements in parallel, where C is the capacitance of the storage device, and R is the equivalent parallel resistance of the microcontroller, PPG sensor, and Wi-Fi modules, respectively. The value of R depends on the power and current absorbed by those modules during sleep, deep sleep, sense, and transmit modes which collected from the datasheet. Finally, the proposed circuit model of the self-powered device was built and simulated in SPICE. The simulation results were compared with the laboratory experiment using commercial devices. Based on the results, the proposed model had small gaps compared to the real self-powered devices in terms of average current, voltage, power and efficiency.

Cervical cancer remains a major public health problem. Despite the screening programs, cervical cancer is the second most commonly diagnosed cancer. Most of the cases occur in less developed countries, and it is the third leading cause of cancer death among females. In 2000–2007, the five-year relative survival rate for European women diagnosed with cervical cancer was 62%.[1] Standard treatment for locally advanced cervical cancer reveals external beam radiotherapy (EBRT) with concurrent chemotherapy followed by image-guided adaptive brachytherapy (IGABT) boost [2, 3]. In the last years, the Gynaecological (GYN) working group composed of Group Européen de Curiethérapie-European Society for Therapeutic Radiology and Oncology (GEC-ESTRO) has developed new recommendations for the treatment of cervical cancer based on IGABT. The treatment plan includes 3-dimensional (3D) imaging based on magnetic resonance imaging (MRI) or computed tomography (CT), adaptive to the target volume and organ at risk [4–6]. The brachytherapy insertion is made under anaesthesia. At the time of the application insertion, the ultrasound is used to guide the dilatation of the uterine canal and assess the depth of the uterine cavity. In this paper, we review the data available in international literature about the use of ultrasound (US) in brachytherapy treatment of cervical cancer.

Ultrasound based haptic feedback is a potential technology for human-computer interaction (HCI) with the advantages of low cost, low power consumption and controlled force. In this paper, the phase optimization for multipoint haptic feedback based on ultrasound array is investigated and the corresponding experimental verification is provided. A mathematical model of acoustic pressure is established for the ultrasound array and then a phase optimization model for an ultrasound transducer is constructed. We propose a pseudo-inverse (PINV) algorithm to accurately determine the phase contribution of each transducer in the ultrasound array. By controlling the phase difference of the ultrasound array, the multipoint focusing forces are formed leading to various shapes such as geometries and letters that can be visualized. Because the unconstrained PINV solution results in unequal amplitudes for each transducer, a weighted amplitude iterative optimization is deployed to further optimize the phase solution, by which the uniform amplitude distributions of each transducer are obtained. For the purpose of experimental verifications, a platform of ultrasound haptic feedback consisting of a Field Programmable Gate Array (FPGA), an electrical circuit and an ultrasound transducer array is prototyped. The haptic performances of single point, multiple points and dynamic trajectory were verified by controlling the ultrasound force exerted on the liquid surface. The experimental results demonstrate that the proposed phase optimization model and theoretical results are effective and feasible, and the acoustic pressure distribution is consistent with the simulation results.

This paper discusses the computer-aided (CAD) classification between Hepatocellular Carcinoma (HCC), i.e., the most common type of liver cancer, and Liver Abscess, based on ultrasound image texture features and Support Vector Machine (SVM) classifier. Among 79 cases of liver diseases, with 44 cases of HCC and 35 cases of liver abscess, this research extracts 96 features of Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Run-Length Matrix (GLRLM) from the region of interests (ROIs) in ultrasound images. Three feature selection models, i) Sequential Forward Selection, ii) Sequential Backward Selection, and iii) F-score, are adopted to determine the identification of these liver diseases. Finally, the developed system can classify HCC and liver abscess by SVM with the accuracy of 88.875%. The proposed methods can provide diagnostic assistance while distinguishing two kinds of liver diseases by using a CAD system.

The black hole (BH) phenomenon is an intraluminal restenotic lesion. It was identified by intravascular ultrasound (IVUS) and optical coherence tomography (OCT) after intracoronary brachytherapy and drug-eluting stent implantation. Despite the similarity in the mode of action of brachytherapy and drug-eluting stent implantation, the BH phenomenon appears to be uncommon after drug-eluting stent implantation. Specifically, the BH phenomenon is better identified by OCT than by IVUS. Herein, we present a case of in-stent restenosis with suspected BH phenomenon on IVUS confirmed by OCT.

(1) Background: Patella and achilles tendon injuries have become increasingly prevalent due to an increasingly active population. These injuries can cause significant dysfunction which is especially true for elite athletes. Standard B-Mode ultrasound has been useful in the diagnosis of these injuries, however, only to a limited extent. Shear wave elastography (SWE) can aid in evaluation by objectively measuring tissue stiffness. Prior studies have proven shear wave values can be used to evaluate tendon tissue noting differences in healthy versus pathologic tendons. One main limitation remains a lack of normative data for specific tendon tissues which we aim to address in this study; (2) Methods: A cross-sectional study of healthy volunteers aged 18-65 without lower extremity injury was evaluated using A Samsung RS85 Prestige ultrasound machine with a 14L-2 MHz transducer. Shear wave values were collected in a standardized manner for the patellar tendon at one location, as well as the achilles tendon at the midportion and insertional areas; (3) Results: Data for 54 healthy adult patellar and achilles tendons was collected bilaterally. The mean SWE average of the patellar tendon (P1-P3) for all subjects was 96.3 +/- 10.9 kPA. A higher BMI was correlated with a decrease in patella tendon kPA and the mean PT1 was higher for males compared to females (adjusted mean 96.4 kPA for males and 88.5 kPA for females, mean difference = 7.9 kPA; P = 0.009). The mean SWE average of the insertional Achilles (AT1-AT3) for all subjects was 101.7 +/-16.2 kPA and for the midportion achilles (MTP1-MTP5) was 145.6 +/- 18.8 kPA. There was a decrease in kPA for insertional Achilles measurements in those with a higher BMI, but this did not reach statistical significance (p=.12); (4) Conclusion: This study provides normative SWE values for the patella and achilles tendon using the Samsung RS85. These values can be used for comparison to pathological tissue by means of the same examination protocol to better understand tendon degeneration. Further studies are warranted as to how SWE can be applied to the diagnosis of tendinopathy, partial and full-thickness tears, and response to treatment.

Ultrasonography is a relevant diagnostic tool extensively used andrology of human and do-mestic animals, including dogs. The present review aimed to describe all the technologies based on ultrasound, starting with the basic B-Mode ultrasonography to the recent contrast-enhanced ultrasonography (CEUS) and the ultrasound elastography, available to assess the testicle of the dog. The principles of the different technologies and the relevant findings in normal and ab-normal testicular conditions were described and discussed. B-mode ultrasonography aims at the examination of the testis detecting focal lesions but lacks objectivization. Other technologies, such as Doppler ultrasonography, B-Flow, and CEUS allow the definition of vascular patterns, that could be measured with specific applications, such as spectral Doppler or quantitative CEUS. Finally, ultrasound elastography allows the estimation of parenchyma stiffness, in both qualitatively and quantitatively manner. Ultrasound-based technologies assist the andrology in the evaluation of the testicular function and integrity, offering valuable information to define pathological conditions that could have an impact on the health and life quality of the male dog.

This paper develops the study of the effect of powerful ultrasound on the laser breakdown of liquids and a comparative study of the possibilities of acoustic and optical diagnostics of breakdown. The method of laser-induced breakdown spectroscopy (LIBS) for elemental analysis of liquids, along with high efficiency, continues to be less sensitive compared to traditional chemical methods. The paper develops a method of using additional ultrasound irradiation of the laser breakdown area in order to increase the efficiency of LIBS. Using the developed technique, spectral lines of chemical elements such as potassium, manganese, sodium, calcium, etc. were obtained for the first time depending on the frequency and power of ultrasound. It is shown that a sharp increase in the intensity of spectral lines of elements in water during laser breakdown is observed in the field of high-power ultrasound. It indicates an increase in the sensitivity of the combined method of ultrasonic LIBS. Along with the optical spectrum, the spectral and energy characteristics of acoustic emission were studied. An automated complex for hydrophysical and spectral studies is described, which was tested in the Sea of Japan during the voyage No. 81 of the research vessel RV "Professor Gagarinsky" in August 2022.

Ultrasound has become widely used as a mean to measure the rectus femoris muscle in the acute and chronic phase of critical illness. Despite its noninvasiveness and accessibility, its accuracy highly depends on the skills of the technician. However, few ultrasound phantoms for the confirmation of its accuracy or to improve technical skills exist. In this study, we created a novel phantom model and used it for investigating the accuracy of measurements and for training. Study 1 investigated how various conditions affect ultrasound measurements such as thickness, cross-sectional area, and echogenicity. Study 2 investigated if the phantom can be used for training of various health care providers in vitro and vivo. Study 1 showed that thickness, cross-sectional area, and echogenicity were affected by probe compression strength, probe angle, phantom compression, and varying equipment. Study 2 in vitro showed that using the phantom for training improved the accuracy of the measurements taken within phantom, and Study 2 in vivo showed the phantom training had a short-term effect on improving the measurement accuracy in a human volunteer. The new ultrasound phantom model revealed that various conditions affected ultrasound measurements, and phantom training improved the measurement accuracy.

Nerve hydrodissection (HD), a technique used when treating nerve entrapments, involves using an anesthetic or solution such as saline or 5% dextrose solution to separate the nerve from the surrounding tissue, fascia, or adjacent structures. This technique aims to treat neuropathic pain, or pain caused by the nerve. Ultrasound-guided HD of peripheral nerves has gained significant attention in the medical profession and pain management fields in recent years. This is due to a number of high impact publications of randomized control trials demonstrating the efficacy and safety of this technique for the treatment of carpal tunnel syndrome. Even the 20th edition of Harrison’s Principles of Internal Medicine textbook lists injection of 5% dextrose as an alternative local treatment that does not have the side effects of corticosteroids. At present, there is no review of the current literature on this technique. This manuscript will summarize and discuss the following: 1) the different approaches to doing ultrasound-guided HD of nervous structures, 2) its usages in different clinical situations, 3) its clinical pearls, 4) the solution used, and 5) the postulated mechanisms of action.

Virtual Histology- Intravascular Ultrasound (VH-IVUS) image is an available method for visualizing plaque component to detect thin cap fibroatheroma. Nevertheless, this imaging modality has considerable limitations to extract the plaque component features and identifying the TCFA plaque. The aim of this paper is to improve the identification of TCFA using fusion of IVUS and VH-IVUS images. In order to generate the automatic technique for reducing the human interaction, a new method namely Active Contour based Plaque Border Detection (ACPB) is proposed. In order to perform the pixel wise classification, hybrid of K-means algorithm with Particle Swarm Optimization and Plaque based Minimum Euclidean Distance (KMPSO-PMED) method is presented to classify the plaque region as well. Moreover, to obtain more significant information of imaging modalities, fusion of two different images consisting of VH-IVUS and IVUS is performed. Therefore, geometric features are extracted from the plaque region and combine with IVUS features. Furthermore, different group of plaque features are divided by means of the histopathological studies. SVM classifiers is applied to detect the TCFA and non-TCFA plaques. The proposed method is applied on 566 in-vivo IVUS and their matching VH-IVUS images obtained from 9 patients. The best result of SVM illustrates the accuracy rates of 99.41% for classification of TCFA plaque. The results prove that the highest accuracy is achieved by integrated features of IVUS and VH-IVUS images.

Relationship between the results of penile duplex doppler ultrasound (PDDU) and response to vardenafil was investigated in patients diagnosed with erectile dysfunction (ED). Data of 148 patients with ED were analysed retrospectively. Patients who did not respond to therapy were classified as Group I (n = 32), those responded partially were classified as Group II (n = 40) and complete responders were classified as Group III (n = 76). Age, comorbid diseases, vascular and penile pathology were compared among the three groups. While diabetes mellitus (DM) and dyslipedimia positivity adversely affect the response to treatment, the presence of hypertension (HT), peyronie's disease and priapism increase the therapeutic response to the treatment (p < 0.05). Arterial insufficiency was present in 20(30.3%), 25(37,9%) and 21(31.8%) of the patients in Group I, Group II and Group III, respectively (p = 0.001). Venous insufficiency was observed in 3(14.3%) patients in Group I and in 8(85.7%) patients in Group III (p = 0.001). Arterial/venous insufficiency was seen in 9(30%), 14(46.7%) and 7(23.3%) of the patients in Group I, Group II and Group III, respectively (p = 0.001). Response rate to treatment was highest in normal patients according to PDDU, followed by patients with venous insuffiency. Besides, it was found that DM decreased the response to treatment, whereas response was increased in cases with HT, priapism and Peyronie’s disease.

The next-generation communication systems demand integration of sensing, communication, and power transfer (PT) capabilities, requiring high spectral efficiency, energy efficiency, and low cost, while also necessitating robustness in high-speed scenarios. Integrated sensing and communication systems (ISACS) exhibit the ability to simultaneously perform communication and sensing tasks using a single RF signal, while simultaneous wireless information and power transfer (SWIPT) systems can handle simultaneous information and energy transmission, and orthogonal time frequency space (OTFS) signals are adept at handling high Doppler scenarios. Combining the advantages of these three technologies, a novel cyclic prefix (CP) OTFS based integrated simultaneous wireless sensing, communication, and power transfer system (ISWSCPTS) framework is proposed in this work. Within the ISWSCPTS, the CP-OTFS matched filter (MF) based target detection and parameters estimation (MF-TDaPE) algorithm is proposed to endow the system with sensing capabilities. To enhance the system’s sensing capability, a waveform design algorithm based on CP-OTFS ambiguity function shaping (AFS) is proposed, which is solved by iteratively method. Furthermore, to maximize the system’s sensing performance under communication and PT Quality of Service (QoS) constraints, a semidefinite relaxation (SDR) beamforming design (SDR-BD) algorithm is proposed, solved using through SDR technique. Simulation results demonstrate that the ISWSCPTS exhibits stronger parameter estimation performance in high-speed scenarios compared to orthogonal frequency division multiplexing (OFDM), waveform designed by CP-OTFS AFS demonstrates superior interference resilience, and beamforming designed by SDR-BD strikes a balance in the overall performance of the ISWSCPTS.

This study aims to precisely characterize the use of magnetoelectric nanoparticles (MENPs) for stimulating peripheral nerves. Numerical methods were employed to quantify the interaction between MENPs and nervous tissue. The influence of MENPs orientation, concentration and distance was assessed in terms of the external potential distribution exerted by the MENPs, the amplification of the exerted MENPs stimulation required to excite the neural fibers and the current injected into the intracellular space. The results highlight the significance of MENPs concentration for stimulation accuracy and efficiency, the impact of MENPs orientation on the electric potential distribution sensed by the nervous tissue, as well as the importance of the MENPs distance over the fibers’ recruitment. Given the considerable variability in the interaction between MENPs and nerves, our research provides a crucial step towards understanding this interaction, offering quantitative support for the application of MENPs in nervous tissue stimulation.

As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory towards 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts towards super convergence, non-IP-based networking protocols, and information-centric net-works, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into the core of 6G, we articulate a systematic exploration of the key technologies earmarked to revolutionize wireless communication including terahertz (THz) waves, optical wireless technology, and dynamic spectrum management,while elucidating the intricate tradeoffs necessitated by the integration of such innovations. This paper not only lays out a comprehensive 6G vision accentuated by high security, affordability, and intelligence but also charts the course for addressing the pivotal challenges of spectrum efficiency, energy consumption, and the seamless integration of emerging technologies. In this study, our goal is to enrich the existing discussions and research efforts by providing comprehen-sive insights into the development of 6G technology, ultimately supporting the creation of a thoroughly connected future world that meets evolving demands.

A new power receiving unit (PRU) is proposed in this paper for the resonant wireless power transfer (WPT), which is characterized by the capability of attracting high power from the power transmitting unit (PTU). The resonant WPT is designed for delivering the electrical power to the PRU attached on an electrical vehicle (EV) chassis 50cm away from a PTU installed on the ground. The proposed PRU uses only the passive elements such as inductors, diodes and the capacitors, which needs no initial power from the EV. It is then applicable for charging a battery to several hundred volts for even a first-time charging battery. At a switching frequency of the resonant WPT in the experiment being 4MHz, the proposed PRU behaves itself as a negative impedance converter (NIC) in the subharmonics of 4MHz. The NIC effect plus the subharmonic oscillation causes an instability current charging the battery connected to the PRU. In this paper, we simulated the PRU and performed the experiment. The experiment demonstrates a battery charging of 150W from 50cm away using three D-mode GaN HEMT transistors via the instability current ramp. The power transfer efficiency (PTE) improved as the power delivered to load (PDL) goes higher. The best power transfer efficiency (PTE) is 65% in the present findings. The simulation analysis shows that the circuit allows itself be used to much higher power transfer when it is implemented with more GaN HEMT transistors connected in parallel. The theoretical derivation of the PRU circuit is also used to support both the experimental and simulation results.

In underwater optical wireless communications (UOWC), scattering of the propagating light beam results in both intensity and phase variations, which limit the transmission link range and channel bandwidth, respectively. Scattering of photons while propagating through the channel is a random process, which results in the channel-dependent scattering noise. In this work, we introduce for the first time an analytical model for this noise and investigate its effect on the bit error rate performance of the UOWC system for three types of waters and a range of transmission link spans. We show that, for a short range of un-clear water or a longer range of clear water, the number of photons experiencing scattering is high, thus leading to the increased scattering noise.

In recent years, since the propagation channel characteristics have been effectively used for applications such as motion sensing, position detection, etc. A great deal of attention is attracted to channel sounding methods easy to utilize using low-cost devices. This paper presents a device-free indoor location estimation method using spatio-temporal features of radio propagation channels using the 2.4-GHz band 3-by-3 MIMO channel sounder developed using commodity wireless LANs. The measurement results demonstrated a reasonable performance of the proposed method with small number of antennas.

The explosive emergence of wireless technologies and standards, covering licensed and unlicensed spectrum bands has triggered the appearance of a huge amount of wireless technologies, with many of them coexisting in the same band. Unfortunately, the wireless spectrum is a scarce resource, and the available frequency bands will not scale with the foreseen demand for new capacity. Certain parts of the spectrum, in particular the license-free ISM bands, are overcrowded, while other parts, mostly licensed bands, may be significantly underutilized. As such, there is a need to introduce more advanced techniques to access and share the wireless medium, either to improve the coordination within a given band, or to explore the possibilities of intelligently using unused spectrum in underutilized (e.g., licensed) bands. Therefore, in this paper, we present an open source SDR-based framework that can be employed to devise disruptive techniques to optimize the sub-optimal use of radio spectrum that exists today. Additionally, we describe three use cases where the proposed framework can be employed along with intelligent algorithms to achieve improved spectrum utilization.

In this paper, we investigate an animal-human cohabitation problem with the help of machine learning and fiber-wireless (FiWi) access networks integrating cloud and edge (fog) computing. We propose an early warning system which detects wild animals nearby road/rail with the help of wireless sensor networks and alerts passing vehicles of possible animal crossing. Additionally, we show that animals' detection at the earliest and the related processing, if possible, at sensors would reduce the energy consumption of edge devices and the end-to-end delay in notifying vehicles, as compared to the scenarios where raw sensed data needs to be transferred up the base stations or the cloud. At the same time, machine learning helps in classification of captured images at edge devices, and in predicting different time-varying traffic profiles-- distinguished by latency and bandwidth requirements-- at base stations, including animal appearance events at sensors, and allocating bandwidth in FiWi access networks accordingly. We compare three scenarios of processing data at sensor nodes, base stations and a hybrid case of processing sensed data at either sensors or at base stations, and showed that dynamic allocation of bandwidth in FiWi access networks and processing data at its origin leads to lowering the congestion of network traffic at base stations and reducing the average end-to-end delay.

This literature review offers a comprehensive analysis of the design and optimization of microstrip patch antennas for wireless communication systems, drawing insights from a variety of research papers. It examines diverse approaches aimed at enhancing antenna performance and functionality. Key topics explored include optimization of resonant frequency, design of antenna arrays, and bandwidth enhancement. Noteworthy optimization techniques, such as genetic algorithms and artificial neural networks, are discussed, highlighting their effectiveness in achieving superior antenna performance. Application-specific solutions tailored to areas such as military communication and RFID systems are emphasized. The review underscores the significant role played by optimization techniques in achieving desired performance metrics and identifies future research directions, including multi-objective optimization, investigation of robustness and reliability, and integration with advanced technologies. Overall, this literature review provides valuable insights into the state-of-the-art in microstrip patch antenna design and optimization, guiding future research endeavors in this dynamic and rapidly evolving field.

Wireless energy harvesting (EH) communication has long been considered a sustainable networking solution. However, it has been limited in efficiency, which has been a major obstacle. Recently, strategies such as energy relaying and borrowing have been explored to overcome these difficulties and provide long-range wireless sensor connectivity. In this article, we examine the reliability of the wireless-powered communication network by maximizing the net bit rate. To accomplish our goal, we focus on enhancing the performance of hybrid access points and information sources by optimizing their transmit power. Additionally, we aim to maximize the use of harvested energy by energy-harvesting relays for both information transmission and energy relaying. However, this optimization problem is complex as it involves non-convex variables and requires combinatorial relay selection indicators optimization for decode and forward (DF) relaying. To simplify this problem, we utilize the Markov decision process and deep reinforcement learning framework based on the deep deterministic policy gradient algorithm. This approach enables us to tackle this non-tractable problem, which conventional convex optimisation techniques would be difficult to solve in complex problem environments. The proposed algorithm significantly improves the end-to-end net bit rate of the smart energy borrowing and relaying EH system by 13.22%,27.57%, and 14.12% compared to the benchmark algorithm based on borrowing energy with an adaptive reward for Quadrature Phase Shift Keying, 8-PSK, and 16-Quadrature amplitude modulation schemes, respectively.

Due to the renewed variation in government and political systems inside and outside countries, and with the high tariffs at borders, the latter have become an outlet for terrorism and smugglers. Therefore, each country seeks to develop its own protection system, and the technologies used in these systems vary according to the severity and the importance of the installations to be protected, it is found that some of them are expensive and unnecessary, but other have good and variable levels of efficiency. Consequently, the idea of designing a surveillance system that can monitor and control access becomes indispensable. In the same context, this work is of crucial strategic and geopolitical importance. It combines pre-existing alarm and monitoring methods and revolutionary Internet of Things (IoT) application products, of which Wireless Sensor Networks (WSN) and Optical Fiber Sensors (OFS) are part of this application. This article presents the distribution of wireless radar nodes accompanying with a Bragg fiber sensor to identify each rolling intruder incoming the zone to be monitored, from the determination of its speed, weight and wheelbase distance.

Wireless Sensor Networks (WSNs) has the characteristics of large-scale deployment, flexible networking, and wide application. It is an important part of the wireless communication networks. However, due to limited energy supply, the development of WSN is greatly restricted. Wireless Rechargeable Sensor Networks (WRSNs) transform the distributed energy around the environment into usable electricity through energy collection technology. In this work, a joint optimization strategy is proposed to improve the energy management efficiency for WRSNs. The joint optimization strategy is divided into two phases. In the first phase, we design an Annulus Virtual Force based Particle Swarm Optimization (AVFPSO) algorithm for area coverage planing. It adopts the multi-parameter joint optimization method to improve the efficiency of the algorithm. In the second phase, a Queuing Game-based Energy Supply (QGES) algorithm is designed for energy scheduling. It converts energy supply and consumption into network service. By solving the game equilibrium of the model, the optimal energy distribution strategy can be obtained. The simulation results show that our scheme improves the efficiency of coverage and energy, and extends the lifetime of WSN.

Water covers a greater part of the earth's surface. Even though we know very little about the underwater world as most parts of it remain unexplored. Oceans including other water bodies hold huge natural resources and also the aquatic lives. These are mostly unexplored and very few of those are known due to unsuited and hazardous environments for the human to explore. This vast underwater world can be monitored remotely from a distant location with much ease and less risk. To monitor water-bodies remotely in real-time, sensor networking has been playing a great role. It is needed to deploy a wireless sensor network over the volume which we want to surveil. For vast water bodies like oceans, rivers and large lakes, data is collected from the different heights of the water level which is sent to the surface sink. Unlike terrestrial communication, radio waves and other conventional mediums can't serve the purpose of underwater communication as they pose high attenuation and very reduced transmission range. Rather an acoustic medium can transmit data more efficiently and reliably in comparison to other mediums. To transmit data reliably from the bottom of the sea to the sinks at the surface, multi-hop communication is needed which must involve a certain scheme. For seabed to surface sink communication, leading researchers have proposed different routing protocols. The goal of these routing protocols is to make underwater communication more reliable, energy-efficient and delay efficient thus to improve the performance of the overall communication. This paper surveys the advancement and applications of the routing protocols which eventually helps in finding the most efficient routing protocol for the Underwater Wireless Sensor Network (UWSN).

Background: According to EWGSOP2, the diagnosis of sarcopenia is confirmed when in addition to low muscle strength, low muscle quantity or quality is present. Echo intensity (EI) determined by muscle ultrasound (US) has been proposed as an efficient method for the assessment of muscle quality. The effect of changing various US parameter settings on EI remains unclear. Therefore, the aim of this study was to assess the differences between EI values obtained by adjusting parameter settings over their entire range in a sample of middle-aged healthy subjects. Methods: Thirty-two repeated US scans of rectus femoris (RF) and rectus abdominis (RA) muscles were taken in eight men and three women with a portable Mindray M7 premium US machine, working in an Extended field-of-view, B-Mode setup, equipped with a linear 5.0-10.0 MHz transducer. The following US parameters and settings were fixed: gain 60dB, depth 6.5cm, and frequency 10 MHz. Readily adjustable parameters were dynamic range (DR), gray map (GM), line density, persistence, and IClear. A default setting DR65 was chosen as the reference setting. For each of the parameters, the settings of one single parameter of interest was changed over its entire range following a standardized protocol. The EI values were calculated using the open-source software ImageJ. Repeated measures analyses were performed to evaluate the effect of parameter settings on EI. Linear interpolation was used to determine non-significant ranges across a given parameter. Results: For the RF muscle, the EI values were significantly different across DR (p<0.001), GM (p<0.001), and IClear (p<0.001). Post hoc analysis confirmed the differences within these three settings. Echo intensity values within the range of DR55 to DR80 were not significantly different. For the RA muscle, the EI values were significantly different across DR (p=0.004) and GM (p=0.030). Post hoc pairwise comparisons revealed no significant difference with the default setting, except for DR150 (p=0.042). Conclusion: We showed that EI values differ across the DR and GM range, especially in the RF. We suggest using a DR setting within its midrange to minimize the effect of machine setting-dependent factors on EI values. These findings reconfirm the need for standardization of ultrasound echo intensity settings when applied for diagnostic purposes of muscle quality.

Controlling the collective behavior of micro/nanomotors with ultrasound may enable new functionality in robotic, medicine and other engineering disciplines. Currently, various collective behaviors of nanomotors, such as assembly, reconfiguration and disassembly, have been explored by using acoustic fields with a fixed frequency, while regulating their collective behaviors by varying the ultrasound frequency still remains challenging. In this work, we design an ultrasound manipulation methodology allowing nanomotors to exhibit different collective behaviors by regulating the applied ultrasound frequency. This work has important implications for design of artificial actuated nanomotors and optimize their performances.

Although pancreatic neuroendocrine neoplasms (PNENs) are relatively rare tumors, their number is increasing with advances in diagnostic imaging modalities. Even small lesions that are difficult to detect using computed tomography or magnetic resonance imaging can be detected with endoscopic ultrasound (EUS). Contrast-enhanced EUS is useful, and not only diagnosis but also malignancy detection have become possible by evaluating the vascularity of tumors. Pathological diagnosis using EUS with fine-needle aspiration (EUS-FNA) is useful when diagnostic imaging is difficult. EUS-FNA can also evaluate the grade of malignancy. Pooling the data of the studies which compared the PNENs grading between EUS-FNA samples and surgical specimen, the concordance rate was 77.5% (κ-statistic: 0.65, 95% confidence interval = 0.59 - 0.71, P< 0.01). EUS is a particularly important modality for the treatment of PNENs.

This article aims to detect lung cavitations using lung ultrasound (LUS) in a cohort of patients with pulmonary tuberculosis (TB) and correlate the findings with chest computed tomography (CT) and chest x-ray (CXR) to obtain LUS diagnostic sensitivity. Patients with suspected TB were enrolled after being evaluated with CXR and chest CT. A blinded radiologist performed LUS within 3 days after the admission at the Infectious Diseases Department. Finally, 82 patients were enrolled in the study. BAL confirmed TB in 58/82 (71%). Chest CT showed pulmonary cavitations in 38/82 (43.6%; 32 TB patients and 6 non-TB ones), LUS in 15/82 (18.3%; 11 TB patients and 4 non-TB ones) and CXR in 27/82 (33%; 23 TB patients and 4 non-TB ones). Patients with multiple cavitations were 12 detected at CT and only 1 at LUS. LUS sensitivity was 39.5%, specificity 100%, PPV 100%, NPV 65.7%. CXR sensitivity was 68.4% and specificity 97.8%. No false positive cases were found. LUS sensitivity is rather low as many cavitated consolidations do not reach the pleural surface. Aerated cavitations could be detected with LUS with relative confidence, highlighting a thin air-crescent sign towards the pleural surface within a hypoechoic area of consolidation, easily distinguishable from dynamic or static air-bronchogram.

Background: Interstitial lung disease (ILD) is a frequent complication in systemic sclerosis (SSc). So, an increased awareness of this complication is a real need in the clinical setting, because it may affect the prognosis of patients. In particular, an accurate strategy is desirable in order to detect ILD in its stages. So, we investigate the validity of ultrasound (US) in detecting subclinical ILD in SSc, and to determine its potential in disease progression. Methods: 133 patients without respiratory symptoms and 133 healthy controls were included. Borg scale, Rodnan skin score (RSS), pulmonary auscultation, chest radiographs and respiratory function tests (RFT) were performed. An expert rheumatologist performed the lung US. High-resolution CT (HRCT) was also performed. After the baseline assessment, the patients were followed every 3 months for 12 months. Results: A total of 79 of 133 patients (59.4%) showed US signs of ILD in contrast to healthy controls (4.8%) (p=0.0001). The clinical and laboratory variables associated with ILD were anti-centromere antibodies (p=0.005) and RSS (p=0.004). A positive correlation was demonstrated between the US and HRCT findings (p=0.001). Sensitivity and specificity of US in detecting ILD was 91.2% and 88.6% respectively. A good inter-observer reliability was observed (k = 0.72). In the follow-up, a total of 30 patients out of 79 (37.9%) who demonstrated US signs of ILD at baseline, showed changes in the ILD score by US. Conclusions: US showed a high prevalence of subclinical ILD in SSc patients. It demonstrated to be a valid, reliable and feasible tool to detect ILD in SSc and to monitoring the disease progression.