The Merits of Bilateral Application of Middle Ear Implants in Patients With Bilateral Conductive and/or Mixed Hearing Loss.

This study investigated sound localization abilities in patients with bilateral conductive and/or mixed hearing loss (BCHL) when listening with either one or two middle ear implants (MEIs). Sound localization was measured by asking patients to point as quickly and accurately as possible with a head-mounted LED in the perceived sound direction. Loudspeakers, positioned around the listener within a range of +73°/-73° in the horizontal plane, were not visible to the patients. Broadband (500 Hz-20 kHz) noise bursts (150 ms), roved over a 20-dB range in 10 dB steps was presented. MEIs stimulate the ipsilateral cochlea only and therefore the localization response was not affected by crosstalk. Sound localization was better with bilateral MEIs compared with the unilateral left and unilateral right conditions. Good sound localization performance was found in the bilaterally aided hearing condition in four patients. In two patients, localization abilities equaled normal hearing performance. Interestingly, in the unaided condition, when both devices were turned off, subjects could still localize the stimuli presented at the highest sound level. Comparison with data of patients implanted bilaterally with bone-conduction devices, demonstrated that localization abilities with MEIs were superior. The measurements demonstrate that patients with BCHL, using remnant binaural cues in the unaided condition, are able to process binaural cues when listening with bilateral MEIs. We conclude that implantation with two MEIs, each stimulating only the ipsilateral cochlea, without crosstalk to the contralateral cochlea, can result in good sound localization abilities, and that this topic needs further investigation.

Phytotoxic responses of acrocarpous moss Campylopus schmidii as bioindicators in copper and cadmium contaminated environments: A comprehensive assessment.

Mosses play a vital role in environmental research as reliable biomonitoring tools. This study aims to understand the accumulation and distribution patterns of Cu and Cd in the acrocarpous moss [Campylopus schmidii (Müll. Hal.) A. Jaeger] (C.schmidii). In controlled in vitro experiments, C.schmidii cultures were exposed to varying concentrations of copper (Cu) and cadmium (Cd) stress (0, 10, 25, 50 µmol/L) in aquatic media. The study systematically evaluated the moss's response, including observing appearance features, oxidative traits, and accumulation characteristics. Scanning electron microscopy with energy-dispersive X-ray spectroscopy analyses were employed. They aimed to characterize and determine the distribution of metal particles in different parts of the mosses under high concentration treatments (50 µmol/L Cd, 50 µmol/L Cu, 50 µmol/L Cu and Cd). Results indicated that C.schmidii exhibited greater tolerance to Cu compared to Cd, as evidenced by significantly higher soluble protein content and lipid peroxidation with increasing concentrations. However, Cd stress induced severe damage, including widespread chlorosis, reduced chlorophyll content, and surface fragmentation. Both Cu and Cd were found to stimulate antioxidant levels by increasing the activity of hydrogen peroxide and peroxidase, thus reducing the accumulation of free radicals in C.schmidii. Additionally, the results revealed differential metal distribution. Higher Cu (2.23%) and lower Cd (0.54%) accumulation were observed at the bottom of gametophores, with Cd content 180.46% higher than Cu at the top. This study provides valuable insights into the potential application of acrocarpous mosses for biomonitoring and phytoremediation. It suggests specific strategies for metal deposition and absorption, such as utilizing upper, younger parts for Cd absorption and lower parts for Cu remediation in soil.

Robotic-assisted CT-guided percutaneous pulmonary nodules localization by hook-wire needles: a retrospective observational study.

Background: Preoperative computed tomography (CT)-guided localization of small pulmonary nodules (SPNs) is the major approach for accurate intraoperative visualization in video-assisted thoracoscopic surgery (VATS). However, this interventional procedure has certain risks and may challenge to less experienced junior doctors. This study aims to evaluate the feasibility and efficacy of robotic-assisted CT-guided preoperative pulmonary nodules localization with the modified hook-wire needles before VATS. Methods: A total of 599 patients with 654 SPNs who preoperatively accepted robotic-assisted CT-guided percutaneous pulmonary localization were respectively enrolled and compared to 90 patients with 94 SPNs who underwent the conventional CT-guided manual localization. The clinical and imaging data including patients' basic information, pulmonary nodule features, location procedure findings, and operation time were analyzed. Results: The localization success rate was 96.64% (632/654). The mean time required for marking was 22.85±10.27 min. Anchor of dislodgement occurred in 2 cases (0.31%). Localization-related complications included pneumothorax in 163 cases (27.21%), parenchymal hemorrhage in 222 cases (33.94%), pleural reaction in 3 cases (0.50%), and intercostal vascular hemorrhage in 5 cases (0.83%). Localization and VATS were performed within 24 hours. All devices were successfully retrieved in VATS. Histopathological examination revealed 166 (25.38%) benign nodules and 488 (74.62%) malignant nodules. For patients who received localizations, VATS spent a significantly shorter time, especially the segmentectomy group (93.61±35.72 vs. 167.50±40.70 min, P<0.001). The proportion of pneumothorax in the robotic-assisted group significantly decreased compared with the conventional manual group (27.21% vs. 43.33%, P=0.002). Conclusions: Robotic-assisted CT-guided percutaneous pulmonary nodules hook-wire localization could be effectively helpful for junior less experienced interventional physicians to master the procedure and potentially increase precision.

Efficacy, safety and patient satisfaction of two-stage versus single-stage computed tomography guided localization and resection of pulmonary nodules.

Background: Low-dose computed tomography (CT) has been increasingly utilized for lung cancer screening. Localization of solitary pulmonary nodules (SPN) is crucial for resection. Two-stage localization method involves dye injection by radiologists prior to the operation. The significant interval between localization and resection is associated with a higher risk of marker failure, psychological distress and procedural complications. Single-stage localization and resection procedure under general anesthesia poses unique challenges. The aim of the study is to compare the safety, efficacy and patient satisfaction between the two methods. Methods: This is a retrospective study comparing outcomes between two-stage and single-stage pre-operative localization of SPN. The primary study outcome was total operating time. Secondary outcomes included successful lesion localization, complication rate, 30-day readmission, mortality, patient satisfaction, and pain level. Results: A total of 26 and 56 patients were included for the single and two-stage group respectively. Total operative time was significantly longer in the single-stage arm (mean: 188 min) than that of the two-stage arm (mean: 172 min, P<0.001) due to the additional time needed for intra-operative localization. Mean satisfaction score was significantly higher in the single-stage group than that of the two-stage group (92 vs. 52.69, P=0.004). Pain level assessed by numerical rating scales was better in the single-stage arm compared to the two-stage arm (mean: 8.8 vs. 4.85, P=0.007). Conclusions: Single-stage localization and resection resulted in a minor increase in total operative time, higher patient satisfaction and less pain with comparable safety and efficacy to conventional two-stage approach.

Wireless sensor localization based on distance optimization and assistance by mobile anchor nodes: a novel algorithm.

Wireless sensor networks (WSNs) have wide applications in healthcare, environmental monitoring, and target tracking, relying on sensor nodes that are joined cooperatively. The research investigates localization algorithms for both target and node in WSNs to enhance accuracy. An innovative localization algorithm characterized as an asynchronous time-of-arrival (TOA) target is proposed by implementing a differential evolution algorithm. Unlike available approaches, the proposed algorithm employs the least squares criterion to represent signal-sending time as a function of the target position. The target node's coordinates are estimated by utilizing a differential evolution algorithm with reverse learning and adaptive redirection. A hybrid received signal strength (RSS)-TOA target localization algorithm is introduced, addressing the challenge of unknown transmission parameters. This algorithm simultaneously estimates transmitted power, path loss index, and target position by employing the RSS and TOA measurements. These proposed algorithms improve the accuracy and efficiency of wireless sensor localization, boosting performance in various WSN applications.

Automated crack identification in structures using acoustic waveforms and deep learning.

Structural elements undergo multiple levels of damage at various locations due to environments and critical loading conditions. The level of damage and its location can be predicted using acoustic emission (AE) waveforms that are captured from the generation of inherent microcracks. Existing AE methods are reliant on the feature selection of the captured waveforms and may be subjective in nature. To automate this process, this paper proposes a deep-learning model to predict the damage severity and its expected location using AE waveforms. The model is based on a densely connected convolutional neural network (CNN) that offers superior feature extraction and minimal training data requirements. Time-domain AE waveforms are used as inputs of the proposed model to automate the process of predicting the severity of damage and identifying the expected location of the damage in structural elements. The proposed approach is validated using AE data collected from a concrete beam and a wooden beam and plate. The results show the capability of the proposed method for predicting the level of damage with an accuracy range of 92-95% and identifying the approximate location of damage with 90-100% accuracy. Thus, the proposed method serves as a robust technique for damage severity prediction and localization in civil structures.

Breast cancer localization by iodine seed 125I vs. wire- -guided localization - retrospective case-control study.

INTRODUCTION: For many years, the gold standard in the localization of non-palpable malignant breast tumors has been the use of wire-guided method. However, this has recently been replaced by more modern localization techniques in many institutions. METHODS: This is a retrospective case-control study comparing two localization techniques (iodine seed 125I and wire-guided localization) for localizing non-palpable tumors in patients with histologically verified breast carcinoma. RESULTS: The study included 62 patients - 31 with localization of malignant breast tumor by iodine seed (subgroup 125I) and 31 by wire-guided localization (subgroup FV). The average volume of the resected tissue in subgroup 125I (46.2 cm3) was statistically significantly smaller compared to subgroup FV (83.7 cm3; P = 0.0063). R0 resection was achieved in 29 cases (93.5%) in subgroup 125I and in 24 cases (77.4%) in subgroup FV (P = 0.0714). In subgroup 125I, re-resection was not indicated in any case, while in subgroup FV, re-resection due to tumor reaching the margin was indicated in 6 cases (19.4%; P = 0.01). CONCLUSION: Our initial experience show that the use of iodine seeds for localizing non-palpable breast tumors is associated with the removal of a smaller volume of resected tissue compared to wire-guided localization, with a trend towards more frequent achievement of R0 resection. In the subgroup of patients localized with iodine seeds, there was a smaller proportion of re-resections due to inadequate safety margins.

A Multimodal Point Cloud-Based Method for Tumor Localization in Robotic Ultrasound-Guided Radiotherapy.

Objectives: Part of the tumor localization methods in radiotherapy have poor real-time performance and may generate additional radiation. We propose a multimodal point cloud-based method for tumor localization in robotic ultrasound-guided radiotherapy, which only irradiates computed tomography (CT) during radiotherapy planning to avoid additional radiation. Methods: The tumor position was determined using the CT point cloud, and the red green blue depth (RGBD) point cloud was used to determine body surface scanning location corresponding to the tumor location. The relationship between the CT point cloud and RGBD point cloud was established through multi-modal point cloud registration. The point cloud was then used for robot tumor localization through coordinate transformation between camera and robot. Results: The maximum mean absolute error of the tumor location in the X, Y, and Z directions of the robot coordinate system were 0.781, 1.334, and 1.490 mm, respectively. The average point-to-point translation mean absolute error between the actual and predicted positions of the localization points was 1.847 mm. The maximum error in the random positioning experiment was 1.77 mm. Conclusion: The proposed method is radiation free and has real-time performance, with tumor localization accuracy that meets the requirements of radiotherapy. The proposed method, which potentially reduces the risks associated with radiation exposure while ensuring efficient and accurate tumor localization, represents a promising advancement in the field of radiotherapy.

Mismatch negativity between discriminating and undiscriminating participants on the front-back sound localization.

Sound localization in the front-back dimension is reported to be challenging, with individual differences. We investigated whether auditory discrimination processing in the brain differs based on front-back sound localization ability. This study conducted an auditory oddball task using speakers in front of and behind the participants. We used event-related brain potentials to examine the deviance detection process between groups that could and could not discriminate front-back sound localization. The results indicated that mismatch negativity (MMN) occurred during the deviance detection process, and P2 amplitude differed between standard and deviant locations in both groups. However, the latency of MMN was shorter in the group that could discriminate front-back sounds than in the group that could not. Additionally, N1 amplitude increased for deviant locations compared to standard ones only in the discriminating group. In conclusion, the sensory memories matching process based on traces of previously presented stimuli (MMN, P2) occurred regardless of discrimination ability. However, the response to changes in the physical properties of sounds (MMN latency, N1 amplitude) differed depending on the ability to discriminate front-back sounds. Our findings suggest that the brain may have different processing strategies for the two directions even without subjective recognition of the front-back direction of incoming sounds.

Successful Use of a Cadaver Model to Teach Ultrasound-Guided Breast Procedures to Surgical Trainees.

INTRODUCTION: In academic breast surgery, ultrasound use tends to be limited to radiology departments, thus formal surgical resident training in breast ultrasound is sparse. Building on residents' ultrasound skills in our general surgery training program, we developed a novel curriculum to teach ultrasound-guided breast procedures (UGBPs), including core needle biopsy (CNB) and wire localization (WL). We hypothesized that learning UGBPs on cadavers would be preferred to learning with a breast phantom model using chicken breasts. METHODS: Residents received a 1-h lecture on breast CNB and WL followed by a 1-h hands-on laboratory session. Olives stuffed with red pimentos were used to replicate breast masses and implanted in chicken breasts and the breasts of lightly embalmed and unembalmed female cadavers. All residents practiced UGBPs with a course instructor on both models. Residents completed anonymous prelaboratory and postlaboratory surveys utilizing five-point Likert scales. RESULTS: A total of 35 trainees participated in the didactics; all completed the prelaboratory survey and 28 completed the postlaboratory survey. Participant clinical year ranged from 1 to 6. Residents' confidence in describing and performing CNBs and WLs increased significantly on postlaboratory surveys, controlling for clinical year (P < 0.001). Eighty-point seven percent preferred learning UGBPs on cadavers over phantoms most commonly citing that the cadaver was more realistic. CONCLUSIONS: Following a novel 2-h UGBP training curriculum using phantom and cadaveric models, resident confidence in describing and performing UGBPs significantly improved. Most favored the cadaveric model and reported that the course prepared them for real-life procedures.

Is intraoperative parathyroid monitoring during minimally invasive parathyroidectomy still justified?

Introduction: Primary hyperparathyroidism (PHPT) is the third most common endocrine disease. With parathyroidectomy, a cure rate of over 95% at initial surgery is reported. Localization of the abnormal parathyroid gland is critical for the operation to be successful. The aim of this study is to analyze data of patients with single gland disease (SGD) and positive concordant localization imaging undergoing minimally invasive parathyroidectomy (MIP) and intraoperative parathyroid hormone monitoring (IOPTH) to evaluate if IOPTH is still justified in patients with localized SGD. Methods: A retrospective database analysis of all minimally invasive operations with IOPTH for PHPT and positive concordant localization in ultrasound (US) and 99mTc-sestamibi scintigraphy (MIBI) between 2016-2021. When both US and MIBI were negative, patients underwent either choline or methionine PET-CT. The patients were also analyzed a second time without applying IOPTH. Results: In total, 198 patients were included in the study. The sensitivity of US, MIBI and PET-CT was 96%, 94% and 100%, respectively. Positive predictive value was 88%, 89% and 94% with US, MIBI and PET-CT, respectively. IOPTH was true positive in 185 (93.4%) patients. In 13 (6.6%) patients, no adequate IOPTH decline was observed after localizing and extirpating the assumed enlarged parathyroid gland. Without IOPTH, the cure rate decreased from 195 (98.5%) to 182 (92%) patients and the rate of persisting disease increased from 2 (1.0%) to 15 (7.5%) patients. Conclusion: Discontinuing IOPTH significantly increases the persistence rate by a factor of 7.5 in patients with concordantly localized adenoma. Therefore, IOPTH appears to remain necessary even for this group of patients.

Impact of age at the second implantation, experience of amplification use, and long-term binaural experience on sound localization of children with bilateral cochlear implants.

OBJECTIVES: To assess the influence of three factors using retrospective chart review: age at which 2nd cochlear implant (CI) is implanted, prior hearing aid (HA) experience in the 2nd CI ear, and long-term experience with bilateral cochlear implants (BICIs) on sound localization in children with sequential BICIs. METHODS: Mean absolute error (MAE) in localizing speech noise of 60 children with sequential BICIs was compared across four age groups of the 2nd CI (1-5.0; 5.1-10.0; 10.1-14.0; & 14.1-19.0 years) and two extents of prior HA experience (more than and less than one year). MAE was also longitudinally analyzed after 4-6 years of experience with BICI involving 18 participants out of 60. RESULTS: Children who received 2nd CI before five years of age demonstrated significantly better localization than those who received it after ten years of age. More than one year of prior HA experience in the 2nd CI ear and extensive experience with sequential BICIs significantly enhanced localization performance. Inter-implant intervals and age at the 2nd CI showed a significant positive correlation with the MAE (poorer localization). CONCLUSION: The results indicate that age at 2nd CI is important in developing sound localization skills. Based on the results, obtaining 2nd CI within the first five years of life and no later than ten years old is recommended. The results also suggest that longer use of amplification before 2nd CI and prolonged BICI experience significantly fosters localization development.

Genome-wide identification of Glycyrrhiza uralensis Fisch. MAPK gene family and expression analysis under salt stress relieved by Bacillus subtilis.

Introduction: Research on Glycyrrhiza uralensis, a nonhalophyte that thrives in saline-alkaline soil and a traditional Chinese medicinal component, is focused on improving its ability to tolerate salt stress to increase its productivity and preserve its "Dao-di" characteristics. Furthermore, the inoculation of bioagents such as Bacillus subtilis to increase plant responses to abiotic stressors is currently a mainstream strategy. Mitogen-activated protein kinase (MAPK), a highly conserved protein kinase, plays a significant role in plant responses to various abiotic stress pathways. Methods: This investigation involved the identification of 21 members of the GuMAPK family from the genome of G. uralensis, with an analysis of their protein conserved domains, gene structures, evolutionary relationships, and phosphorylation sites using bioinformatics tools. Results: Systematic evolutionary analysis of the 21 GuMAPKs classified them into four distinct subgroups, revealing significant differences in gene structure and exon numbers. Collinearity analysis highlighted the crucial role of segmental duplication in expanding the GuMAPK gene family, which is particularly evident in G. uralensis and shows a close phylogenetic relationship with Arabidopsis thaliana, tomato, and cucumber. Additionally, the identification of phosphorylation sites suggests a strong correlation between GuMAPK and various physiological processes, including hormonal responses, stress resistance, and growth and development. Protein interaction analysis further supported the role of GuMAPK proteins in regulating essential downstream genes. Through examination of transcriptome expression patterns, GuMAPK16-2 emerged as a prospective pivotal regulatory factor in the context of salt stress and B. subtilis inoculation, a finding supported by its subcellular localization within the nucleus. Discussion: These discoveries offer compelling evidence for the involvement of GuMAPK in the salt stress response and for the exploration of the mechanisms underlying B. subtilis' enhancement of salt tolerance in G. uralensis.

JrPPO1/2 play distinct roles in regulating walnut fruit browning by different spatiotemporal expression and enzymatic characteristics.

Polyphenol oxidase (PPO) activity drives walnut fruit browning, but the roles of its only two-family genes, JrPPO1 and JrPPO2, remain unclear. This study explores the spatiotemporal expression and enzymatic characteristics of JrPPO1 and JrPPO2 in walnut. Treatment with the PPO activator CuSO4 and H2O2 accelerated fruit browning and up-regulated JrPPO1/2 expression, whereas treatment with the PPO inhibitor ascorbic acid delayed browning, down-regulating JrPPO1 and up-regulating JrPPO2 expression. Compared to mJrPPO1, mJrPPO2 can exhibited better enzyme activity at higher temperatures (47 °C) and in more acidic environments (pH 4.25). mJrPPO2 exhibited a higher substrate specificity over mJrPPO1, and the preferred substrates are catechol, chlorogenic acid, and epicatechin. Additionally, mJrPPO2 adapted better to low concentration of oxygen (as low as 1.0% O2) and slightly elevated CO2 levels compared to mJrPPO1. Subcellular localization and spatiotemporal expression patterns showed that JrPPO1 is only expressed in green tissues and located in chloroplasts, while JrPPO2 is also located in chloroplasts, partly associated with membranes, and is expressed in both green and non-green tissues. Silencing JrPPO1/2 with virus-induced gene silencing (VIGS) reduced fruit browning, maintained higher total phenols, and decreased MDA production. Notably, silencing JrPPO1 had a greater impact on browning than JrPPO2, indicating JrPPO1's greater contribution to PPO activity and fruit browning in walnut fruits. Consequently, JrPPO1 can be effectively regulated both at the molecular level and by manipulating environmental conditions, to achieve the objective of controlling fruit browning.

Node Localization Method in Wireless Sensor Networks Using Combined Crow Search and the Weighted Centroid Method.

Node localization is critical for accessing diverse nodes that provide services in remote places. Single-anchor localization techniques suffer co-linearity, performing poorly. The reliable multiple anchor node selection method is computationally intensive and requires a lot of processing power and time to identify suitable anchor nodes. Node localization in wireless sensor networks (WSNs) is challenging due to the number and placement of anchors, as well as their communication capabilities. These senor nodes possess limited energy resources, which is a big concern in localization. In addition to convention optimization in WSNs, researchers have employed nature-inspired algorithms to localize unknown nodes in WSN. However, these methods take longer, require lots of processing power, and have higher localization error, with a greater number of beacon nodes and sensitivity to parameter selection affecting localization. This research employed a nature-inspired crow search algorithm (an improvement over other nature-inspired algorithms) for selecting the suitable number of anchor nodes from the population, reducing errors in localizing unknown nodes. Additionally, the weighted centroid method was proposed for identifying the exact location of an unknown node. This made the crow search weighted centroid localization (CS-WCL) algorithm a more trustworthy and efficient method for node localization in WSNs, with reduced average localization error (ALE) and energy consumption. CS-WCL outperformed WCL and distance vector (DV)-Hop, with a reduced ALE of 15% (from 32%) and varying communication radii from 20 m to 45 m. Also, the ALE against scalability was validated for CS-WCL against WCL and DV-Hop for a varying number of beacon nodes (from 3 to 2), reducing ALE to 2.59% (from 28.75%). Lastly, CS-WCL resulted in reduced energy consumption (from 120 mJ to 45 mJ) for varying network nodes from 30 to 300 against WCL and DV-Hop. Thus, CS-WCL outperformed other nature-inspired algorithms in node localization. These have been validated using MATLAB 2022b.

Peer-to-Peer Ultra-Wideband Localization for Hands-Free Control of a Human-Guided Smart Stroller.

We propose a hands-free control system for a human-guided smart stroller. The proposed method uses real-time peer-to-peer localization technology of the human and stroller to realize an intuitive hands-free control system based on the relative position between the human and the stroller. The control method is also based on functional and mechanical safety to ensure the safety of the stroller's occupant (child) and the pilot (parent) during locomotion. In this paper, first, we present a preliminary investigation of the humans' preference for the relative position in the context of hands-free guided strollers. Then, we present the control method and a prototype implemented with an electric wheelchair and UWB sensors for localization. We present an experimental evaluation of the proposed method with 14 persons walking with the developed prototype to investigate the usability and soundness of the proposed method compared to a remote joystick and manual operation. The evaluation experiments were conducted in an indoor environment and revealed that the proposed method matches the performance of joystick control but does not perform as well as manual operation. Notably, for female participants, the proposed method significantly surpasses joystick performance and achieves parity with manual operation, which shows its efficacy and potential for a smart stroller. Also, the results revealed that the proposed method significantly decreased the user's physical load compared to the manual operation. We present discussions on the controllability, usability, task load, and safety features of the proposed method, and conclude this work with a summary assessment.

Spatial Localization of Transformer Inspection Robot Based on Adaptive Denoising and SCOT-ß Generalized Cross-Correlation.

In the detection process of the internal defects of large oil-immersed transformers, due to the huge size of large transformers and metal-enclosed structures, the positional localization of miniature inspection robots inside the transformer faces great difficulties. To address this problem, this paper proposes a three-dimensional positional localization method based on adaptive denoising and the SCOT weighting function with the addition of the exponent ß (SCOT-ß) generalized cross-correlation for L-type ultrasonic arrays of transformer internal inspection robots. Aiming at the strong noise interference in the field, the original signal is decomposed by an improved Empirical Mode Decomposition (EMD) method, and the optimal center frequency and bandwidth of each mode are adaptively searched. By extracting the modes in the frequency band of the positional localization signal, suppressing the modes in the noise frequency band, and reconstructing the Intrinsic Mode Function (IMF) of the independently selected superior modal components, a signal with a high signal-to-noise ratio is obtained. In addition, for the traditional mutual correlation algorithm with a large delay estimation error at a low signal-to-noise ratio, this paper adopts an improved generalized joint weighting function, SCOT-ß, which improves the anti-jamming ability of the generalized mutual correlation method at a low signal-to-noise ratio by adding an exponential function to the denominator term of the SCOT weighting function's generalized cross-correlation. Finally, the accurate positional localization of the transformer internal inspection robot is realized based on the quadratic L-array and search-based maximum likelihood estimation method. Simulation and experimental results show the following: the improved EMD denoising method better improves the signal-to-noise ratio of the positional localization signal with a lower distortion rate; in the transformer test tank, which is 120 cm in length, 100 cm in width, and 100 cm in height, based on the positional localization method in this paper, the average relative positional localization error of the transformer internal inspection robot in three-dimensional space is 2.27%, and the maximum positional localization error is less than 2 cm, which meets the requirements of engineering positional localization.

Wearable Sensor Node for Safety Improvement in Workplaces: Technology Assessment in a Simulated Environment.

Personal protective equipment (PPE) has been universally recognized for its role in protecting workers from injuries and illnesses. Smart PPE integrates Internet of Things (IoT) technologies to enable continuous monitoring of workers and their surrounding environment, preventing undesirable events, facilitating rapid emergency response, and informing rescuers of potential hazards. This work presents a smart PPE system with a sensor node architecture designed to monitor workers and their surroundings. The sensor node is equipped with various sensors and communication capabilities, enabling the monitoring of specific gases (VOC, CO2, CO, O2), particulate matter (PM), temperature, humidity, positional information, audio signals, and body gestures. The system utilizes artificial intelligence algorithms to recognize patterns in worker activity that could lead to risky situations. Gas tests were conducted in a special chamber, positioning capabilities were tested indoors and outdoors, and the remaining sensors were tested in a simulated laboratory environment. This paper presents the sensor node architecture and the results of tests on target risky scenarios. The sensor node performed well in all situations, correctly signaling all cases that could lead to risky situations.

Concrete Defect Localization Based on Multilevel Convolutional Neural Networks.

Concrete structures frequently manifest diverse defects throughout their manufacturing and usage processes due to factors such as design, construction, environmental conditions and distress mechanisms. In this paper, a multilevel convolutional neural network (CNN) combined with array ultrasonic testing (AUT) is proposed for identifying the locations of hole defects in concrete structures. By refining the detection area layer by layer, AUT is used to collect ultrasonic signals containing hole defect information, and the original echo signal is input to CNN for the classification of hole locations. The advantage of the proposed method is that the corresponding defect location information can be obtained directly from the input ultrasonic signal without manual discrimination. It effectively addresses the issue of traditional methods being insufficiently accurate when dealing with complex structures or hidden defects. The analysis process is as follows. First, COMSOL-Multiphysics finite element software is utilized to simulate the AUT detection process and generate a large amount of ultrasonic echo data. Next, the extracted signal data are trained and learned using the proposed multilevel CNN approach to achieve progressive localization of internal structural defects. Afterwards, a comparative analysis is conducted between the proposed multilevel CNN method and traditional CNN approaches. The results show that the defect localization accuracy of the proposed multilevel CNN approach improved from 85.38% to 95.27% compared to traditional CNN methods. Furthermore, the computation time required for this process is reduced, indicating that the method not only achieves higher recognition precision but also operates with greater efficiency. Finally, a simple experimental verification is conducted; the results show that this method has strong robustness in recognizing noisy ultrasonic signals, provides effective solutions, and can be used as a reference for future defect detection.

Childhood Tumors around the Knee Revisited: Predilection Sites for Most Entities Confirmed.

Background: The diagnostic work-up of musculoskeletal tumors is a multifactorial process. During the early phase, differential diagnoses are made using basic radiological imaging. In this phase, part of the decision making is based on the patient's age, as well as the incidence and predilection sites of different entities. Unfortunately, this information is based on older and fragmented data. In this study, we retrospectively evaluated all soft-tissue and bone tumors around the knee in children treated at our tertiary center in the last 20 years, with the aim of verifying the data used today. Methods: In this retrospective study, the databank of our tertiary center was used to give an overview of treated tumors around the knee in children. Results: We were able to include 224 children with bone and soft-tissue tumors around the knee. The cohort consisted of 184 bone tumors, of which 144 were benign and 40 malignant. The 40 soft-tissue tumors comprised 30 benign and 10 malignant masses. The most common lesions were osteochondromas (88) in the bone and tenosynovial giant-cell tumors (12) in the soft tissue. Conclusions: With this original work, we were able to verify and supplement earlier studies, as well as deepen our insight into these very rare diseases.