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This study introduces RTEEMF (Real-Time Evaluation Electromagnetic Field)-PhoneAnts, a novel Deep Learning (DL) framework for the efficient evaluation of mobile phone antenna performance, addressing the time-consuming nature of traditional full-wave numerical simulations. The DL model, built on convolutional neural networks, uses the Near-field Electromagnetic Field (NEMF) distribution of a mobile phone antenna in free space to predict the Effective Isotropic Radiated Power (EIRP), Total Radiated Power (TRP), and Specific Absorption Rate (SAR) across various configurations. By converting antenna features and internal mobile phone components into near-field EMF distributions within a Huygens' box, the model simplifies its input. A dataset of 7000 mobile phone models was used for training and evaluation. The model's accuracy is validated using the Wilcoxon Signed Rank Test (WSR) for SAR and TRP, and the Feature Selection Validation Method (FSV) for EIRP. The proposed model achieves remarkable computational efficiency, approximately 2000-fold faster than full-wave simulations, and demonstrates generalization capabilities for different antenna types, various frequencies, and antenna positions. This makes it a valuable tool for practical research and development (R&D), offering a promising alternative to traditional electromagnetic field simulations. The study is publicly available on GitHub for further development and customization. Engineers can customize the model using their own datasets.

As a convenient and natural way of human-computer interaction, gesture recognition technology has broad research and application prospects in many fields, such as intelligent perception and virtual reality. This paper summarized the relevant literature on gesture recognition using Frequency Modulated Continuous Wave (FMCW) millimeter-wave radar from January 2015 to June 2023. In the manuscript, the widely used methods involved in data acquisition, data processing, and classification in gesture recognition were systematically investigated. This paper counts the information related to FMCW millimeter wave radar, gestures, data sets, and the methods and results in feature extraction and classification. Based on the statistical data, we provided analysis and recommendations for other researchers. Key issues in the studies of current gesture recognition, including feature fusion, classification algorithms, and generalization, were summarized and discussed. Finally, this paper discussed the incapability of the current gesture recognition technologies in complex practical scenes and their real-time performance for future development.

Circulating genetically abnormal cells (CACs) constitute an important biomarker for cancer diagnosis and prognosis. This biomarker offers high safety, low cost, and high repeatability, which can serve as a key reference in clinical diagnosis. These cells are identified by counting fluorescence signals using 4-color fluorescence in situ hybridization (FISH) technology, which has a high level of stability, sensitivity, and specificity. However, there are some challenges in CACs identification, due to the difference in the morphology and intensity of staining signals. In this concern, we developed a deep learning network (FISH-Net) based on 4-color FISH image for CACs identification. Firstly, a lightweight object detection network based on the statistical information of signal size was designed to improve the clinical detection rate. Secondly, the rotated Gaussian heatmap with a covariance matrix was defined to standardize the staining signals with different morphologies. Then, the heatmap refinement model was proposed to solve the fluorescent noise interference of 4-color FISH image. Finally, an online repetitive training strategy was used to improve the model's feature extraction ability for hard samples (i.e., fracture signal, weak signal, and adjacent signals). The results showed that the precision was superior to 96%, and the sensitivity was higher than 98%, for fluorescent signal detection. Additionally, validation was performed using the clinical samples of 853 patients from 10 centers. The sensitivity was 97.18% (CI 96.72-97.64%) for CACs identification. The number of parameters of FISH-Net was 2.24 M, compared to 36.9 M for the popularly used lightweight network (YOLO-V7s). The detection speed was about 800 times greater than that of a pathologist. In summary, the proposed network was lightweight and robust for CACs identification. It could greatly increase the review accuracy, enhance the efficiency of reviewers, and reduce the review turnaround time during CACs identification., (© 2023. The Author(s) under exclusive licence to Society for Imaging Informatics in Medicine.)

Background: With the advancement of computer and medical imaging technologies, a number of high-resolution, voxel-based, full-body human anatomical models have been developed for medical education, industrial design, and physics simulation studies. However, these models are limited in many applications because they are often only in an upstanding posture., Objective: To quickly develop multi-pose human models for different applications. A semi-automatic framework for voxel deformation is proposed in the study., Methods: This paper describes a framework for human pose deformation based on three-dimensional (3D) medical images. The voxel model is first converted into a surface model using a surface reconstruction algorithm. Second, a deformation skeleton based on human bones is defined, and the surface model is bound to the skeleton. The bone Glow algorithm is used to assign weights to the surface vertices. Then, the model is deformed to the target posture by using the Smoothed Rotation Enhanced As-Rigid-As-Possible (SR-ARAP) algorithm. Finally, the volume-filling algorithm is applied to refill the tissues into the deformed surface model., Results: The proposed framework is used to deform two standing human models, and the sitting and running models are developed. The results show that the framework can successfully develop the target pose. When compared to the results of the As-Rigid-As-Possible algorithm, SR-ARAP preserves local tissues better., Conclusion: The study proposes a frame for voxel human model deformation and improves the local tissue integrity during deformation., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Recent studies have suggested that circulating tumor cells with abnormalities in gene copy numbers in mononuclear cell-enriched peripheral blood samples, such as circulating genetically abnormal cells (CACs), can be used as a non-invasive tool to detect patients with benign pulmonary nodules. These cells are identified through fluorescence signals counting by using 4-color fluorescence in situ hybridization (FISH) technology that exhibits high stability, sensitivity, and specificity. When FISH data are analyzed, the overlapping cells and fluorescence noise is a great challenge for identifying of CACs, thereby seriously affecting the efficiency of clinical diagnosis. To address this problem, in this study, we proposed an end-to-end FISH-based method (CACNET) for CAC identification. CACNET achieved nuclear segmentation and counted 4-color staining signals through improved Mask region-based convolutional neural network (R-CNN), followed by cell category (normal cell, deletion cell, gain cell, or CAC) according to pathological criteria. Firstly, the segmentation accuracy of overlapping nuclei was improved by adding an edge constraint head during training. Then, the interference of fluorescence noise was reduced by fusing non-local module to reconstruct the feature extraction network of Mask R-CNN. We trained and tested the proposed model on a dataset comprising 700 frames with 58,083 nuclei. The Accuracy, Sensitivity, and Specificity (overall performance metric for the algorithm) of CAC identification with CACNET were 94.06%, 92.1%, and 99.8%, respectively. Moreover, the developed method exhibited approximately identification speed of approximately 0.22 s per frames. The results showed that the proposed method outperformed the existing CAC identification methods, making it a promising approach for early screening of lung cancer., (© 2022 International Society for Advancement of Cytometry.)

This study aimed to estimate the distribution of the whole-body averaged specific absorption rate (WBSAR) using several measurable physique parameters for Chinese adult population exposed to environmental electromagnetic fields (EMFs) of current wireless communication frequencies, and to discuss the effects of these physique parameters in the frequency-dependent dosimetric results. The physique distribution of Chinese adults was obtained from the National Physical Fitness and Health Database comprising 81,490 adult samples. The number of physique parameters used to construct the surrogate model was reduced to three via mutual information analysis. A stochastic method with 40 deterministic simulations was used to generate frequency-dependent and gender-specific surrogate models for WBSAR via polynomial chaos expansion. In the simulations, we constructed anatomically correct models conforming to the targeted physique parameters via deformable human modelling technique, which was based on deep learning from the image database including 767 Chinese adults. Thereafter, we analysed the sensitivity of the physique parameters to WBSAR by covariance-based Sobol decomposition. The results indicated that the generated models were consistent with the targeted physique parameters. The estimated dosimetric results were validated using finite-difference time-domain simulations (the error was < 6% across all the investigated frequencies for WBSAR). The novelty of the study included that it demonstrated the feasibility of estimating the individual WBSAR using a limited number of physique parameters with the aid of surrogate modelling. In addition, the population-based distribution of the WBSAR in Chinese adults was firstly presented in the manuscript. The results also indicated that the different combinations of physique parameter, dependent on genders and frequencies, significantly influenced the WBSAR, although the general conservativeness of the guidelines of the International Commission on Non-Ionizing Radiation and Protection can be confirmed in the surveyed population., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Objective: We aimed to reduce the complexity of the 52-channel functional near-infrared spectroscopy (fNIRS) system to facilitate its usage in discriminating schizophrenia during a verbal fluency task (VFT)., Methods: Oxygenated hemoglobin signals obtained using 52-channel fNIRS from 100 patients with schizophrenia and 100 healthy controls during a VFT were collected and processed. Three features frequently used in the analysis of fNIRS signals, namely time average, functional connectivity, and wavelet, were extracted and optimized using various metaheuristic operators, i.e., genetic algorithm (GA), particle swarm optimization (PSO), and their parallel and serial hybrid algorithms. Support vector machine (SVM) was used as the classifier, and the performance was evaluated by ten-fold cross-validation., Results: GA and GA-dominant algorithms achieved higher accuracy compared to PSO and PSO-dominant algorithms. An optimal accuracy of 87.00% using 16 channels was obtained by GA and wavelet analysis. A parallel hybrid algorithm (the best 50% individuals assigned to GA) achieved an accuracy of 86.50% with 8 channels on the time-domain feature, comparable to the reported accuracy obtained using 52 channels., Conclusion: The fNIRS system can be greatly simplified while retaining accuracy comparable to that of the 52-channel system, thus promoting its applications in the diagnosis of schizophrenia in low-resource environments. Evolutionary algorithm-dominant optimization of time-domain features is promising in this regard., (Copyright © 2022 Xia, Quan and Wu.)

Background: Bone age assessment (BAA) is a crucial research topic in pediatric radiology. Interest in the development of automated methods for BAA is increasing. The current BAA algorithms based on deep learning have displayed the following deficiencies: (I) most methods involve end-to-end prediction, lacking integration with clinically interpretable methods; (II) BAA methods exhibit racial and geographical differences., Methods: A novel, automatic skeletal maturity assessment (SMA) method with clinically interpretable methods was proposed based on a multi-region ensemble of convolutional neural networks (CNNs). This method predicted skeletal maturity scores and thus assessed bone age by utilizing left-hand radiographs and key regional patches of clinical concern., Results: Experiments included 4,861 left-hand radiographs from the database of Beijing Jishuitan Hospital and revealed that the mean absolute error (MAE) was 31.4±0.19 points (skeletal maturity scores) and 0.45±0.13 years (bone age) for the carpal bones-series and 29.9±0.21 points and 0.43±0.17 years, respectively, for the radius, ulna, and short (RUS) bones series based on the Tanner-Whitehouse 3 (TW3) method., Conclusions: The proposed automatic SMA method, which was without racial and geographical influence, is a novel, automatic method for assessing childhood bone development by utilizing skeletal maturity. Furthermore, it provides a comparable performance to endocrinologists, with greater stability and efficiency., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-21-1158/coif). The authors have no conflicts of interest to declare., (2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Background: Circulating tumor cells (CTCs) acting as "liquid biopsy" of cancer are cells that have been shed from the primary tumor, which cause the development of a secondary tumor in a distant organ site, leading to cancer metastasis. Recent research suggests that CTCs with abnormalities in gene copy numbers in mononuclear cell-enriched peripheral blood samples, namely circulating genetically abnormal cells (CACs), could be used as a non-invasive decision tool to detect patients with benign pulmonary nodules. Such cells are identified by counting the fluorescence signals of fluorescence in situ hybridization (FISH). However, owing to the rarity of CACs in the blood, identification of CACs using this technique is time-consuming and is a drawback of this method., Methods: This study has proposed an efficient and automatic FISH-based CACs identification approach which is based on a combination of the high accuracy of You Only Look Once (YOLO)-V4 and the lightweight and rapidness of MobileNet-V3. The backbone of YOLO-V4 was replaced with MobileNet-V3 to improve the detection efficiency and prevent overfitting, and the architecture of YOLO-V4 was optimized by utilizing a new feature map with a larger scale to enable the enhanced detection ability for small targets., Results: We trained and tested the proposed model using a dataset containing more than 7,000 cells based on five-fold cross-validation. All the images in the dataset were 2,448×2,048 (pixels) in size. The number of cells in each image was >70. The accuracy of four-color fluorescence signals detection for our proposed model were all approximately 98%, and the mean average precision (mAP) were close to 100%. The final outcome of the developed method was the type of cells, i.e., normal cells, CACs, gaining cells or deletion cells. The method had a CACs identification accuracy of 93.86% (similar to an expert pathologist), and a detection speed that was about 500 times greater than that of a pathologist., Conclusions: The developed method could greatly increase the review accuracy, enhance the efficiency of reviewers, and reduce the review turnaround time during CACs identification., Competing Interests: Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-21-909/coif). XF, XL and XY are employees of Zhuhai Sanmed Biotech Ltd. The other authors have no conflicts of interest to declare., (2022 Quantitative Imaging in Medicine and Surgery. All rights reserved.)

Fetal development is vital in the human lifespan. Therefore, it is essential to characterize exposure by a series of typical environmental magnetic and electromagnetic fields. In particular, there has recently been a sharp increase in the twin birth rate. However, lack of appropriate models has prohibited dosimetric evaluation, restricting characterization of the impact of these environmental factors on twins. The present study developed two whole-body pregnant models of 31 and 32 weeks of gestation with twin fetuses and explored several typical exposure scenarios, including 50-Hz uniform magnetic field exposure, local 125-kHz magnetic field (MF), and 13.56-MHz electromagnetic field exposure, as well as wideband planewave radiofrequency (RF) exposure from 20 to 6000 MHz. Finally, dosimetric results were derived. Compared to the singleton pregnancy with similar weeks of gestation, twin fetuses were overexposed at 50-Hz uniform MF, but they were probably underexposed in the RF scenarios with frequencies for wireless communications. Furthermore, the twin fetuses manifested large dosimetric variability compared to the singleton, which was attributed to the incident direction and fetal position. Based on the analysis, the dosimetric results over the entire gestation period were estimated. The results can be helpful to estimate the risk of twin-fetal exposure to electromagnetic fields and examine the conservativeness of the international guidelines.© 2022 Bioelectromagnetics Society., (© 2022 Bioelectromagnetics Society.)

In pediatric magnetic resonance imaging (MRI), infants are exposed to rapid, time-varying gradient magnetic fields, leading to electric fields induced in the body of infants and potential safety risks (e.g. peripheral nerve stimulation). In this numerical study, the in situ electric fields in infants induced by small-sized gradient coils for a 1.5 T MRI scanner were evaluated. The gradient coil set was specially designed for the efficient imaging of infants within a small-bore (baby) scanner. The magnetic flux density and induced electric fields by the small x, y, z gradient coils in an infant model (8-week-old with a mass of 4.3 kg) were computed using the scalar potential finite differences method. The gradient coils were driven by a 1 kHz sinusoidal waveform and also a trapezoidal waveform with a 250 µs rise time. The model was placed at different scan positions, including the head area (position I), chest area (position II), and body center (position III). It was found that the induced electric fields in most tissues exceeded the basic restrictions of the ICNIRP 2010 guidelines for both waveforms. The electric fields were similar in the region of interest for all coil types and model positions but different outside the imaging region. The y-coil induced larger electric fields compared with the x- and z- coils. Bioelectromagnetics. 43:69-80, 2022. © 2021 Bioelectromagnetics Society., (© 2021 Bioelectromagnetics Society.)

Neurophysiological effect of human exposure to radiofrequency signals has attracted considerable attention, which was claimed to have an association with a series of clinical symptoms. A few investigations have been conducted on alteration of brain functions, yet no known research focused on intrinsic connectivity networks, an attribute that may relate to some behavioral functions. To investigate the exposure effect on functional connectivity between intrinsic connectivity networks, we conducted experiments with seventeen participants experiencing localized head exposure to real and sham time-division long-term evolution signal for 30 min. The resting-state functional magnetic resonance imaging data were collected before and after exposure, respectively. Group-level independent component analysis was used to decompose networks of interest. Three states were clustered, which can reflect different cognitive conditions. Dynamic connectivity as well as conventional connectivity between networks per state were computed and followed by paired sample t -tests. Results showed that there was no statistical difference in static or dynamic functional network connectivity in both real and sham exposure conditions, and pointed out that the impact of short-term electromagnetic exposure was undetected at the ICNs level. The specific brain parcellations and metrics used in the study may lead to different results on brain modulation., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Yang, Liu, Zhou, Wang, Wu and Chen.)

A steady increase in sleep problems has been observed along with the development of society. Overnight exposure to a static magnetic field has been found to improve sleep quality; however, such studies were mainly based on subjective evaluation. Thus, the presented data cannot be used to infer sleep architecture in detail. In this study, the subjects slept on a magneto-static mattress for four nights, and self-reported scales and electroencephalogram (EEG) were used to determine the effect of static magnetic field exposure (SMFE) on sleep. Machine learning operators, i.e., decision tree and supporting vector machine, were trained and optimized with the open access sleep EEG dataset to automatically discriminate the individual sleep stages, determined experimentally. SMEF was found to decrease light sleep duration (N2%) by 3.51%, and sleep onset latency (SOL) by 15.83%, while it increased deep sleep duration (N3%) by 8.43%, compared with the sham SMFE group. Further, the overall sleep efficiency (SE) was also enhanced by SMFE. It is the first study, to the best of our knowledge, where the change in sleep architecture was explored by SMFE. Our findings will be useful in developing a non-invasive sleep-facilitating instrument.

Human exposure to the electromagnetic field emitted by wireless communication systems has raised public concerns. There were claims of the potential association of some neurophysiological disorders with the exposure, but the mechanism is yet to be established. The wireless networks, recently, experience a transition from the 4th generation (4G) to 5th generation (5G), while 4G long-term evolution (LTE) is still the frequently used signal in wireless communication. In the study, exposure experiments were conducted using the LTE signal. The subjects were divided into sham and real exposure groups. Before and after the exposure experiments, they underwent functional magnetic resonance imaging. Within-session and between-session comparisons have been executed for functional connectivity and network properties. Individual specific absorption rate (SAR) was also calculated. The results indicated that acute LTE exposure beneath the safety limits modulated both the functional connection and graph-based properties. To characterize the effect of functional activity, SAR averaged over a certain tissue mass was not an appropriate metric. The potential neurophysiological effect of 5G exposure has also been discussed in the study.

Functional near-infrared spectroscopy (fNIRS) has been widely employed in the objective diagnosis of patients with schizophrenia during a verbal fluency task (VFT). Most of the available methods depended on the time-domain features extracted from the data of single or multiple channels. The present study proposed an alternative method based on the functional connectivity strength (FCS) derived from an individual channel. The data measured 100 patients with schizophrenia and 100 healthy controls, who were used to train the classifiers and to evaluate their performance. Different classifiers were evaluated, and support machine vector achieved the best performance. In order to reduce the dimensional complexity of the feature domain, principal component analysis (PCA) was applied. The classification results by using an individual channel, a combination of several channels, and 52 ensemble channels with and without the dimensional reduced technique were compared. It provided a new approach to identify schizophrenia, improving the objective diagnosis of this mental disorder. FCS from three channels on the medial prefrontal and left ventrolateral prefrontal cortices rendered accuracy as high as 84.67%, sensitivity at 92.00%, and specificity at 70%. The neurophysiological significance of the change at these regions was consistence with the major syndromes of schizophrenia., (Copyright © 2020 Yang, Ji, Quan, Liu, Wei and Wu.)

Background: Schizophrenia is one of the most serious mental disorders. Currently, the diagnosis of schizophrenia mainly relies on scales and doctors' experience. Recently, functional near infrared spectroscopy (fNIRS) has been used to distinguish schizophrenia from other mental disorders. The conventional classification methods utilized time-course features from single or multiple fNIRS channels., New Method: The fNIRS data were obtained from 52 channels covering the frontotemporal cortices in 200 patients with schizophrenia and 100 healthy subjects during a Chinese verbal fluency task. The channels with significant between-group differences were selected as the seeds. Functional connectivity (FC) was calculated for each seed, and FCs with significant between-group differences were selected as the features for classification., Results: The proposed method reduced the number of channels to 26 while achieving overall classification accuracy, sensitivity and specificity values as high as 89.67%, 93.00% and 86.00%, respectively, outperforming most of the reported results. The superior performance was attributed to the cross-scale neurological changes related to schizophrenia, which were employed by the classification method. In addition, the method provided multiple classification criteria with similar accuracy, consequently increasing the flexibility and reliability of the results., Comparison With Existing Methods: This is the first fNIRS study to classify schizophrenia based on FCs. This method integrated information from regional modulation, segregation and integration. The classification performance outperformed most of the classification methods described in previous studies., Conclusions: Our findings suggest a reliable method with a high level of accuracy and a low level of instrumental complexity to identify patients with schizophrenia., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Purpose: In this study, we used magnetic resonance imaging (MRI) to investigate the anatomical alterations of cerebral cortex in children with Tourette syndrome (TS) and explore whether such deficits were related with their clinical symptoms., Methods: All subjects were scanned in a 3.0T MRI scanner with three-dimensional T1-weighted images (3DT1WI). Then, some surface-based features were extracted by using the FreeSurfer software. After that, the between-group differences of those features were assessed., Results: Sixty TS patients and 52 age- and gender-matched healthy control were included in this study. Surface-based analyses revealed altered cortical thickness, cortical sulcus, cortical curvature and local gyrification index (LGI) in TS group compared with healthy controls. The brain regions with significant-group differences in cortical thickness included postcentral gyrus, superiorparietal gyrus, rostral anterior cingulate cortex in the left hemisphere and frontal pole, lateral occipital gyrus, inferior temporal gyrus in the right hemisphere. In addition, the superior temporal gyrus, medial orbitofrontal gyrus, supramarginal gyrus, medial orbitofrontal gyrus, superiorparietal gyrus and lateral occipital gyrus showed significant between-group differences for cortical sulcus. Moreover, the brain regions with significant between-group differences in cortical curvature were located in caudal anterior cingulate cortex, supramarginal gyrus, inferior parietal gyrus and lateral occipital gyrus. The alteration of LGI were most prominent in the inferior temporal gyrus and insula. Additionally, there was no statistical difference in brain surface area for TS children compared with controls., Conclusion: The results of this study revealed that cortical thickness, sulcus, cortical curvature and LGI were changed in multiple brain regions for children with TS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Amblyopia is a common developmental disorder in adolescents and children. Stereoscopic loss is a symptom of amblyopia that can seriously affect the quality of patient's life. Recent studies have shown that the push-pull perceptual learning protocol had a positive effect on stereoscopic recovery. In this study, we developed a stereoscopic training method using a polarized visualization system according to the push-pull protocol. Dichoptic stimulation for 36 anisometropic and amblyopic subjects and 33 children with normal visual acuity (VA) has been conducted. Electroencephalogram (EEG) was used to evaluate the neurophysiological changes before, during, and after stimulation. For the anisometropic and amblyopic subjects, the statistical analysis demonstrated significant differences ( p < 0.01) in the beta rhythm at the middle temporal and occipital lobes, while the EEG from the normal VA subjects indicated no significant changes when comparing the results before and after training. We concluded that the dichoptic training in our study can activate the middle temporal visual area and visual cortex. The EEG changes can be used to evaluate the training effects. This study also found that the beta band EEG acquired during visual stimulation at the dorsal visual stream can be potentially used for predicting acute training effect. The results facilitated the optimization of the individual training plan., Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper., (Copyright © 2020 Wei Shi et al.)

The distribution of the induced electric field (E-field) during transcranial magnetic stimulation (TMS) depends on the individual anatomical structure of the brain as well as coil positioning. Inappropriate stimulation may degrade the efficacy of TMS or even induce adverse effects. Therefore, optimizing the E-field according to individual anatomy and clinical need has become a research focus. In this paper, particle swarm optimization (PSO) was applied for the first time to the positioning of TMS coils with anatomical head models. We discuss the parameters of the PSO algorithm, which were optimized to achieve a reasonable convergence time suitable for in-time treatment planning. The optimizer improved the distribution of the induced E-field strength at the dedicated cortical region, with a mean value of 48.31% compared with that from the conventional treatment position. The optimization terminated after 4-11 iterations for 13 head models. The applicability and performance of the optimizer for a large population are discussed in terms of cortical complexity. This study could benefit not only clinics but also research on brain modulation., Competing Interests: The authors report no conflicts of interest in this work. None of the authors have any personal or financial involvement with organizations that have a financial interest in its content., (Copyright © 2019 Congsheng Li et al.)

Extremely low frequency (ELF) magnetic field (MF) exposure in electric vehicles (EVs) has raised public concern for human health. There have been many studies evaluating magnetic field values in these vehicles. However, there has been no report on the temporal variation of the magnetic field in the cabin . This is the first study on the long-term monitoring of actual MFs in EVs. In the study, we measured the magnetic flux density (B) in three shared vehicles over a period of two years. The measurements were performed at the front and rear seats during acceleration and constant-speed driving modes. We found that the B amplitudes and the spectral components could be modified by replacing the components and the hubs, while regular checks or maintenance did not influence the B values in the vehicle. This observation highlights the necessity of regularly monitoring ELF MF in EVs, especially after major repairs or accidents, to protect car users from potentially excessive ELF MF exposure. These results should be considered in updates of the measurement standards. The ELF MF effect should also be taken into consideration in relevant epidemiological studies., Competing Interests: The authors declare no conflict of interest.

The accurate estimation of patient's exposure to the radiofrequency (RF) electromagnetic field of magnetic resonance imaging (MRI) significantly depends on a precise individual anatomical model. In the study, we investigated the applicability of an efficient whole-body individual modelling method for the assessment of MRI RF exposure. The individual modelling method included a deformable human model and tissue simplification techniques. Besides its remarkable efficiency, this approach utilized only a low specific absorption rate (SAR) sequence or even no MRI scan to generate the whole-body individual model. Therefore, it substantially reduced the risk of RF exposure. The dosimetric difference of the individual modelling method was evaluated using the manually segmented human models. In addition, stochastic dosimetry using a surrogate model by polynomial chaos presented SAR variability due to body misalignment and tilt in the coil, which were frequently occurred in the practical scan. In conclusion, the dosimetric equivalence of the individual models was validated by both deterministic and stochastic dosimetry. The proposed individual modelling method allowed the physicians to quantify the patient-specific SAR while the statistical results enabled them to comprehensively weigh over the exposure risk and get the benefit of imaging enhancement by using the high-intensity scanners or the high-SAR sequences.

By now, the neurophysiological effect of electromagnetic field (EMF) exposure and its underlying regulating mechanisms are not well manifested. In this study, we aimed to investigate whether acute long-term evolution (LTE) EMF exposure could modulate brain functional connectivity using regional homogeneity (ReHo) method and seed-based analysis on resting-state functional magnetic resonance imaging (fMRI). We performed the LTE-EMF exposure experiment and acquired the resting-state brain activities before and after EMF exposure. Then we applied ReHo index to characterize the localized functional connectivity and seed-based method to evaluate the inter-regional functional connectivity. Statistical comparisons were conducted to identify the possible evidence of brain functional connectivity modulation induced by the acute LTE-EMF exposure. We found that the acute LTE-EMF exposure modulated localized intra-regional connectivity (p < 0.05, AlphaSim corrected, voxel size ≥ 18) and inter-regional connectivity in some brain regions (p < 0.05, AlphaSim corrected, voxel size ≥ 18). Our results may indicate that the approaches relying on network-level inferences could provide deeper insight into the acute effect on human functional activity induced by LTE-EMF exposure. Bioelectromagnetics. 40:42-51, 2019. © 2018 Wiley Periodicals, Inc., (© 2018 Wiley Periodicals, Inc.)

In the electric vehicles (EVs), children can sit on a safety seat installed in the rear seats. Owing to their smaller physical dimensions, their heads, generally, are closer to the underfloor electrical systems where the magnetic field (MF) exposure is the greatest. In this study, the magnetic flux density (B) was measured in the rear seats of 10 different EVs, for different driving sessions. We used the measurement results from different heights corresponding to the locations of the heads of an adult and an infant to calculate the induced electric field (E-field) strength using anatomical human models. The results revealed that measured B fields in the rear seats were far below the reference levels by the International Commission on Non-Ionizing Radiation Protection. Although small children may be exposed to higher MF strength, induced E-field strengths were much lower than that of adults due to their particular physical dimensions.

In recent years, there has been increasing demand for personalized anatomy modelling for medical and industrial applications, such as ergonomics device development, clinical radiological exposure simulation, biomechanics analysis, and 3D animation character design. In this study, we constructed deformable torso phantoms that can be deformed to match the personal anatomy of Chinese male and female adults. The phantoms were created based on a training set of 79 trunk computed tomography (CT) images (41 males and 38 females) from normal Chinese subjects. Major torso organs were segmented from the CT images, and the statistical shape model (SSM) approach was used to learn the inter-subject anatomical variations. To match the personal anatomy, the phantoms were registered to individual body surface scans or medical images using the active shape model method. The constructed SSM demonstrated anatomical variations in body height, fat quantity, respiratory status, organ geometry, male muscle size, and female breast size. The masses of the deformed phantom organs were consistent with Chinese population organ mass ranges. To validate the performance of personal anatomy modelling, the phantoms were registered to the body surface scan and CT images. The registration accuracy measured from 22 test CT images showed a median Dice coefficient over 0.85, a median volume recovery coefficient (RC vlm ) between 0.85 and 1.1, and a median averaged surface distance (ASD) < 1.5 mm. We hope these phantoms can serve as computational tools for personalized anatomy modelling for the research community., (© 2018 Anatomical Society.)

Long-term evolution (LTE) wireless telecommunication systems are widely used globally, which has raised a concern that exposure to electromagnetic fields (EMF) emitted from LTE devices can change human neural function. To date, few studies have been conducted on the effect of exposure to LTE EMF. Here, we evaluated the changes in electroencephalogram (EEG) due to LTE EMF exposure. An LTE EMF exposure system with a stable power emission, which was equivalent to the maximum emission from an LTE mobile phone, was used to radiate the subjects. Numerical simulations were conducted to ensure that the specific absorption rate in the subject's head was below the safety limits. Exposure to LTE EMF reduced the spectral power and the interhemispheric coherence in the alpha and beta bands of the frontal and temporal brain regions. No significant change was observed in the spectral power and the inter-hemispheric coherence in different timeslots during and after the exposure. These findings also corroborated those of our previous study using functional magnetic resonant imaging.

The physiological responses to human thermal stimulation have been widely investigated, but most of them are mainly concerned about the whole body thermal stimulation. In this study, we investigated the effects of stimulus mode and ambient temperature on cerebral responses during local thermal stimulation on hand. The left hands were stimulated by metal thermostat based and thermostatic water based stimulators at different stimulated temperatures (38°C, 40°C, 42°C and 44°C) and different ambient temperatures (25°C and 32°C). EEG data were recorded over the whole brain during the experiments. Then the statistical comparisons were conducted on the EEG relative power among different experimental sessions. We observed that EEG activities were alternated between thermal stimulated periods and the baseline in all four frequency bands. And there was a higher percentage of delta band power in the right temporal and parietal regions under the ambient temperature of 32°C while compared to 25°C. In addition, the theta band activity under the metal based stimulation showed significantly higher EEG relative power than that under the water based stimulation over the whole brain. Compared with the water based stimulation, there was a lower EEG relative power of the beta band activity during the metal based stimulation in the bilateral frontal and right temporal regions. The experimental results suggested that the neural physiological responses in different EEG frequency bands were sensitive to different influence factors during the local hand thermal stimulation., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Objective: C. elegans has been used as a biomonitor for microwave-induced stress. However, the RF (radiofrequency) fields that have been used in previous studies were weak (≤1.8W/kg), and the bio-effects on C. elegans were mostly negative or ambiguous. Therefore, this study used more intense RF fields (SAR = 3W/kg) and longer time course of exposure (60h at 25°C, L1 stage through adult stage) to investigate the biological consequences of 1750 MHz RF fields in wild-type worms., Methods: The growth rates and lifespans of RF-exposure group and the control group were carefully recorded. RNA samples were collected at L4 (35h) and gravid adult (50h) stages for further high-throughput sequencing, focusing on differences between the RF-exposure and the sham control groups., Results: The RF-exposed and sham control groups developed at almost the same rate and had similar longevity curves. In L4 stage worms, 94 up-regulated and 17 down-regulated genes were identified, while 186 up-regulated and 3 down-regulated genes were identified in adult stage worms. GO analysis showed that the differentially expressed genes at 35h were associated with growth, body morphogenesis and collagen and cuticle-based development. Genes that were linked to growth rate and reproductive development were differentially expressed at 50h. Some embryonic and larval development genes in the offspring were also differentially expressed at 50h. Ten genes were differentially expressed at both 35h and 50h, most of which were involved in both embryonic and larval developmental processes. Although prolonged RF fields did not induce significant temperature increase in RF exposure groups, the temperature inside worms during exposure was unknown., Conclusions: No harmful effects were observed in prolonged exposure to 1750 MHz RF fields at SAR of 3W/kg on development and longevity of C. elegans. Although some differentially expressed genes were found after prolonged RF exposure, these differences were ascribed to oscillating gene expression patterns in L4 and gravid adult worms. It was also difficult to rule out a weak thermal effect caused by prolonged RF exposure inside the worms.

Wearable devices have been popularly used with people from different age groups. As a consequence, the concerns of their electromagnetic field (EMF) exposure to the human body and their electromagnetic interference (EMI) to the implanted medical devices have attracted many studies. The aim of this study was to evaluate the human exposure to the EMF of an active radiofrequency identification (RFID) armlet as well as its EMI to the cardiac pacemaker (CP). Different human models from various age groups were applied to assess the result variability. The scalar potential finite element method was utilized in the simulation. Local EMF exposure and the exposure to the central nerve system tissues were evaluated using different metrics. EMI to the CP was assessed in terms of the conducted voltage to the CP. The results from all the models revealed that the studied RFID armlet would not produce the EMF exposure exceeding the safety limits. The calculated interference voltage was highly dependent on the distance between the RFID armlet and the CP (i.e. the physical dimension of the individual model). The results proposed to evaluate the appropriateness of the current EMI measurement protocol for this kind of devices used by the infants.

A reverberation chamber (RC) is realized for the rodents' in vivo exposure to electromagnetic fields (EMFs) with various small-scale fading characteristics. Its performance is evaluated to ensure the exposure experiments from 0.85 to 2.60 GHz. By different configurations, line-of-sight and non-line-of-sight exposures can be established. The measured electric field in the RC is analyzed to determine its statistical distribution. We accordingly reconstruct the EMF environment by numerical methods. Simulations are carried to compare the dosimetric variability due to different small-scale fading characteristics. It demonstrates that the surveyed fading distribution will not change the specific absorption rate in the rats. The possibility to reproduce the realistic multi-reflective EMF environment by adjusting the structures of the RC is discussed. It is the first reported in vivo exposure system aiming to provide the EMF exposure with different small-scale fading distributions.

In this paper, we aimed to investigate the possible effects of acute radiofrequency electromagnetic fields (EMF) on the interhemispheric homotopic functional connectivity with resting state functional magnetic resonance imaging (fMRI) technique. We designed a controllable LTE-related EMF exposure environment at 2.573 GHz and performed the 30 min real/sham exposure experiments on human brain under the safety limits. The resting state fMRI signals were collected before and after EMF exposure. Then voxel-mirrored homotopic connectivity method was utilized to evaluate the acute effects of LTE EMF exposure on the homotopic functional connectivity between two human hemispheres. Based on our previous research, we further demonstrated that the 30 min short-term LTE EMF exposure would modulate the interhemispheric homotopic functional connectivity in resting state around the medial frontal gyrus and the paracentral lobule during the real exposure.

Near-infrared spectroscopy (NIRS) has been applied to examine the possible functional alternations during the performance of cognitive tasks in schizophrenia. With this technique, previous studies have observed that patients with schizophrenia are often associated with reduced brain activation in the prefrontal cortex during the verbal fluency task (VFT) of the English version or the Japanese version. However, it remains unclear whether there is a brain functional impairment in Chinese-speaking patients with schizophrenia. In this study, we designed a Chinese version of the VFT and performed a multichannel NIRS study in a large group of patients with schizophrenia and healthy controls. We investigated brain activation during the task period of the Chinese version of the VFT within a schizophrenia group and a healthy group, respectively, and compared the relative changes between the two groups. Our results confirmed that Chinese-speaking patients with schizophrenia had significantly lower brain activation in the prefrontal cortex and superior temporal cortex when compared with healthy controls. Such findings based on the NIRS data provided us reliable evidences about brain functional deficits in the Chinese-speaking patients with schizophrenia., (Copyright © 2014 Elsevier Inc. All rights reserved.)

The use of electronic article surveillance (EAS) systems has become popular in many public sites. As a consequence, concern has risen about infant exposure to magnetic fields (MFs) from this kind of device. To evaluate infant exposure to MFs of an EAS system (operating at 125 kHz and 13.56 MHz), we numerically compared dosimetric results among adult, child and infant models. Results revealed that postures insignificantly influenced dosimetric results if there was a similar cross-sectional area under exposure. Although safety limits are unlikely to be exceeded, the infant has higher SAR values for brain and central nervous system tissues compared with adult (1.5x at 125 kHz and 112x at 13.56 MHz), which deserve further investigation. Infant's specific anatomy (e.g., non-proportionally large head and high fat content) did not induce higher SAR values. The numerical models developed in the study (stroller and postured infant models) could be freely used for nonprofit academic research., (© 2015 Wiley Periodicals, Inc.)

Infant exposure to 50 Hz magnetic fields from power lines was numerically analyzed in this study. Dosimetric variability due to posture and skin-to-skin contact was evaluated using human anatomical models including a recently developed model of a 12-months-old infant. As proposed by the International Commission on Non-Ionizing Radiation Protection, the induced E-field strength (99th percentile value, E99 ) for the central nerve systems (E99&#95;CNS ) and peripheral nerve system (E99&#95;PNS ), were used as metrics. Results showed that the single (free of contact with others) infant model has lower E99 (E99&#95;CNS and E99&#95;PNS inclusive) compared with single adult and child models when exposed to the same power-frequency magnetic field. Also, studied postures of sitting, standing, or arm-up, would not change E99 &#95;PNS . However, skin-to-skin contact with other models could significantly raise induced E-field strength in the infant (e.g., contact on 0.93% of the infant's total surface increased E99&#95;PNS by 213%). Simulations with canonical models were conducted to assess different factors contributing to the E99 enhancement. Results indicated the importance of thoroughly investigating the conservativeness of current safety guidelines in the case of skin-to-skin contact, especially with infants., (© 2015 Wiley Periodicals, Inc.)

Background: Based on near-infrared spectroscopy (NIRS), recent converging evidence has been observed that patients with schizophrenia exhibit abnormal functional activities in the prefrontal cortex during a verbal fluency task (VFT). Therefore, some studies have attempted to employ NIRS measurements to differentiate schizophrenia patients from healthy controls with different classification methods. However, no systematic evaluation was conducted to compare their respective classification performances on the same study population., New Method: In this study, we evaluated the classification performance of four classification methods (including linear discriminant analysis, k-nearest neighbors, Gaussian process classifier, and support vector machines) on an NIRS-aided schizophrenia diagnosis. We recruited a large sample of 120 schizophrenia patients and 120 healthy controls and measured the hemoglobin response in the prefrontal cortex during the VFT using a multichannel NIRS system. Features for classification were extracted from three types of NIRS data in each channel. We subsequently performed a principal component analysis (PCA) for feature selection prior to comparison of the different classification methods., Results: We achieved a maximum accuracy of 85.83% and an overall mean accuracy of 83.37% using a PCA-based feature selection on oxygenated hemoglobin signals and support vector machine classifier., Comparison With Existing Methods: This is the first comprehensive evaluation of different classification methods for the diagnosis of schizophrenia based on different types of NIRS signals., Conclusions: Our results suggested that, using the appropriate classification method, NIRS has the potential capacity to be an effective objective biomarker for the diagnosis of schizophrenia., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Rats' exposure to electromagnetic pulses (EMPs) has been conducted using an EMP simulator for various biological endpoints. In contrast, information about the EMP energy distribution and its variability in rats is lacking. EMPs are signals with spectrum concentrating in several hundred MHz, leading to EM absorption patterns different from those obtained at high frequencies. In this study, two anatomical models of rats (a male and a female) were reconstructed from magnetic resonance imaging. The models had the same posture as in the exposure experiments. Realistic EMPs were acquired directly from the EMP simulator and applied to the simulations. The interaction of the EMP with the rat was analyzed through the finite-difference time-domain method. Two approaches were utilized to calculate the energy absorption at the tissue and whole-body levels. Dosimetric variability due to incident directions, polarizations, exposure signals simplification, and rat separation was evaluated in this study. The variability result differed substantially from that of the non-constrained rats' exposure experiments. The result sensitivity to frequency and amplitude was discussed as well. The work can be used as a basis to determine the uncertainty and to formulate a standard experimental protocol for this type of experiment.

Realistic anatomical modeling is essential in analyzing human exposure to electromagnetic fields. Infants have significant physical and anatomical differences compared with other age groups. However, few realistic infant models are available. In this work, we developed one 12-month-old male whole body model and one 17-month-old male head model from magnetic resonance images. The whole body and head models contained 28 and 30 tissues, respectively, at spatial resolution of 1 mm × 1 mm × 1 mm. Fewer identified tissues in the whole body model were a result of the low original image quality induced by the fast imaging sequence. The anatomical and physical parameters of the models were validated against findings in published literature (e.g., a maximum deviation as 18% in tissue mass was observed compared with the data from International Commission on Radiological Protection). Several typical exposure scenarios were realized for numerical simulation. Dosimetric comparison with various adult and child anatomical models was conducted. Significant differences in the physical and anatomical features between adult and child models demonstrated the importance of creating realistic infant models. Current safety guidelines for infant exposure to radiofrequency electromagnetic fields may not be conservative., (© 2014 Wiley Periodicals, Inc.)

This paper evaluates the variability of specific absorption rate (SAR) in the human eye. This variability results from changes in ocular axial length (OAL), which is common in many ophthalmologic and vision abnormalities, including myopia. A generic eye model was reconstructed according to published data. The feasibility of using the generic model in numerical research of electromagnetic fields (EMF) was demonstrated by means of comparative simulations with eye models reconstructed from magnetic resonance (MR) scans. Free-form deformation (FFD) was used to deform the OAL of the generic eye model. Thus, 64 deformed eyes were created and were categorized according to the OAL increase. The finite-difference time-domain (FDTD) method was applied in the simulations. The results revealed that changing the OAL does not increase EMF absorption in the eyes or the eye tissues. No additional induced temperature rise was produced by the changes of OAL. The results also indicated that the non-pathological increment of the OAL, which is inevitable during the childhood, does not increase the SAR in the eyes., (© 2014 Wiley Periodicals, Inc.)

A Chinese head phantom (CHP) is constructed for evaluating the specific absorption rate (SAR) by the wireless transceivers. The dimensions of the head phantom are within 4 % difference compared with the 95th percentile data from the China's standard. The shell's thickness and the configuration of the pinna are the same as those of the specific anthropomorphic mannequin (SAM). Three computable models for the mobile phones are generated and used in the SAR simulations with the SAM and the CHP. The results show that the simulated SAR from the SAM head is similar. Its morphological reason has been analysed. The authors discuss the conservativeness of the two head phantoms as well. The CHP can be used in the inter-laboratory evaluation for the SAR uncertainty. It can also provide the information for the SAR variability due to physical difference, which will benefit the maintenance and the harmonisation of the standards.

Objective: The motivation of this study is to evaluate the possible alteration of regional resting state brain activity induced by the acute radiofrequency electromagnetic field (RF-EMF) exposure (30min) of Long Term Evolution (LTE) signal., Methods: We designed a controllable near-field LTE RF-EMF exposure environment. Eighteen subjects participated in a double-blind, crossover, randomized and counterbalanced experiment including two sessions (real and sham exposure). The radiation source was close to the right ear. Then the resting state fMRI signals of human brain were collected before and after the exposure in both sessions. We measured the amplitude of low frequency fluctuation (ALFF) and fractional ALFF (fALFF) to characterize the spontaneous brain activity., Results: We found the decreased ALFF value around in left superior temporal gyrus, left middle temporal gyrus, right superior temporal gyrus, right medial frontal gyrus and right paracentral lobule after the real exposure. And the decreased fALFF value was also detected in right medial frontal gyrus and right paracentral lobule., Conclusions: The study provided the evidences that 30min LTE RF-EMF exposure modulated the spontaneous low frequency fluctuations in some brain regions., Significance: With resting state fMRI, we found the alteration of spontaneous low frequency fluctuations induced by the acute LTE RF-EMF exposure., (Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.)

In this paper, we aimed to investigate the possible interactions between human brain and radiofrequency electromagnetic fields (EMF) with electroencephalogram (EEG) technique. Unlike the previous studies which mainly focused on EMF effect on local brain activities, we attempted to evaluate whether the EMF emitted from Long Term Evolution (LTE) devices can modulate the functional connectivity of brain electrical activities. Ten subjects were recruited to participate in a crossover, double-blind exposure experiment which included two sessions (real and sham exposure). In each session, LTE EMF exposure (power on or off) lasted for 30 min and the EEG signals were collected with 32 channels throughout the experiment. Then we applied the synchronization likelihood method to quantify the neural synchronization over the whole brain in different frequency bands and in different EEG record periods. Our results illustrated that the short-term LTE EMF exposure would modulate the synchronization patterns of EEG activation across the whole brain.

Radiofrequency (RF) electromagnetic field (EMF) exposure from wireless telecommunication base station antennae can lead to debates, conflicts or litigations among the adjacent residents if inappropriately managed. This paper presents a measurement campaign for the GSM band EMF exposure in the vicinity of 827 base station sites (totally 6207 measurement points) in Guangxi, China. Measurement specifications are designed for risk communication with the residents who previously complained of over-exposure. The EMF power densities with the global positioning system coordinate at each measured point were recorded. Compliance with the International Commission on Non-Ionizing Radiation Protection guidelines and Chinese environmental EMF safety standards was studied. The results show that the GSM band EMF level near the base stations is very low. The measurement results and the EMF risk communication procedures positively influence public perception of the RF EMF exposure from the base stations and promote the exchange of EMF exposure-related knowledge.

Digital human models are frequently obtained from supine-postured medical images or cadaver slices, but many applications require standing models. This paper presents the work of reconstructing standing Chinese adult anatomical models from supine postured slices. Apart from the previous studies, the deformation works on 2-D segmented slices. The surface profile of the standing posture is adjusted by population measurement data. A non-uniform texture amplification approach is applied on the 2-D slices to recover the skin contour and to redistribute the internal tissues. Internal organ shift due to postures is taken into account. The feet are modified by matrix rotation. Then, the supine and standing models are utilised for the evaluation of electromagnetic field exposure over wide band frequency and different incident directions.

Standing Chinese adult anatomical models are obtained from supine-postured cadaver slices. This paper presents the dosimetric differences between the supine and the standing postures over wide band frequencies and various incident configurations. Both the body level and the tissue/organ level differences are reported for plane wave and the 3T magnetic resonance imaging radiofrequency electromagnetic field exposure. The influence of posture on the whole body specific absorption rate and tissue specified specific absorption rate values is discussed.

The digital human model is a key element in evaluating the electromagnetic field (EMF) exposure. This paper proposes the application of simplified segmented human models for EMF exposure compliance evaluation with the whole body and the localised limits. The method is based on the fact that most of the EMF power absorption is concentrated in several major tissues. Two kinds of human models were simply (the proposed method) and precisely segmented from two sets of whole body magnetic resonance imaging (MRI) scanned images. The whole body average-specific absorption rate (WBA-SAR) and the peak localised SAR averaging over 10 g tissues for the two kinds of models are calculated for various exposure configurations. The results confirmed the efficiency and the validity of the proposed method. The application as evaluating the MRI radiofrequency EMF exposure is also discussed in the paper.

An experimental approach was used to assess immunological biomarkers in the sera of young rats exposed in utero and postnatal to non-ionizing radiofrequency fields. Pregnant rats were exposed free-running, 2 h/day and 5 days/week to a 2.45 GHz Wi-Fi signal in a reverberation chamber at whole-body specific absorption rates (SAR) of 0, 0.08, 0.4, and 4 W/kg (with 10, 10, 12, and 9 rats, respectively), while cage control rats were kept in the animal facility (11 rats). Dams were exposed from days 6 to 21 of gestation and then three newborns per litter were further exposed from birth to day 35 postnatal. On day 35 after birth, all pups were sacrificed and sera collected. The screening of sera for antibodies directed against 15 different antigens related to damage and/or pathological markers was conducted using enzyme-linked immunosorbent assay (ELISA). No change in humoral response of young pups was observed, regardless of the types of biomarker and SAR levels. This study also provided some data on gestational outcome following in utero exposure to Wi-Fi signals. Mass evaluation of dams and pups and the number of pups per litter was monitored, and the genital tracts of young rats were observed for abnormalities by measuring anogenital distance. Under these experimental conditions, our observations suggest a lack of adverse effects of Wi-Fi exposure on delivery and general condition of the animals., (Copyright © 2012 Wiley Periodicals, Inc.)

This paper presents the work of constructing Chinese adult anatomical models and their application in evaluation of radio frequency (RF) electromagnetic field exposures. The original dataset was obtained from photos of the sliced frozen cadavers from the Chinese Visible Human Project. Details of preparing the cadaver for slicing procedures which may influence the anatomical structures are discussed. Segmentation and reconstruction were performed mainly manually by experienced anatomists. The reconstructed models represent the average Chinese in their twenties and thirties. The finest resolution for the models is 1 × 1 × 1 mm(3) with 90 identified tissues/organs for the female and 87 identified tissues/organs for the male. Tiny anatomical structures such as blood vessels with diameters of 1 mm, various glands and nerves were identified. Whole-body-averaged specific absorption rate (WBSAR) from 20 MHz to 5.8 GHz was calculated with the finite-difference time-domain method for different RF exposure configurations. The WBSAR results are consistent with those from other available models. Finally, some details about the anatomical models are discussed.

This paper presents the whole-body specific absorption rate (WBSAR) assessment of embryos and new-born rats' exposure in a reverberating chamber (RC) operating at 2.4 GHz (WiFi). The finite difference in time domain (FDTD) method often used in bio-electromagnetism is facing very slow convergence. A new simulation-measurement hybrid approach has been proposed to characterize the incident power related to the RC and the WBSAR in rats, which are linked by the mean squared electric field strength in the working volume. Peak localized SAR in the rat under exposure is not included in the content of the study. Detailed parameters of this approach are determined by simulations. Evolutions for the physical and physiological parameters of the small rats at different ages are discussed. Simulations have been made to analyse all the variability factors contributing to the global results. WBSAR information and the variability for rats at different ages are also discussed in the paper.