k-Same-Siamese-GAN: k-Same Algorithm with Generative Adversarial Network for Facial Image De-identification with Hyperparameter Tuning and Mixed Precision Training

For a data holder, such as a hospital or a government entity, who has a privately held collection of personal data, in which the revealing and/or processing of the personal identifiable data is restricted and prohibited by law. Then, "how can we ensure the data holder does conceal the identity of each individual in the imagery of personal data while still preserving certain useful aspects of the data after de-identification?" becomes a challenge issue. In this work, we propose an approach towards high-resolution facial image de-identification, called k-Same-Siamese-GAN, which leverages the k-Same-Anonymity mechanism, the Generative Adversarial Network, and the hyperparameter tuning methods. Moreover, to speed up model training and reduce memory consumption, the mixed precision training technique is also applied to make kSS-GAN provide guarantees regarding privacy protection on close-form identities and be trained much more efficiently as well. Finally, to validate its applicability, the proposed work has been applied to actual datasets - RafD and CelebA for performance testing. Besides protecting privacy of high-resolution facial images, the proposed system is also justified for its ability in automating parameter tuning and breaking through the limitation of the number of adjustable parameters

Single-crystalline δ-Ni2Si nanowires with excellent physical properties

[[abstract]]In this article, we report the synthesis of single-crystalline nickel silicide nanowires (NWs) via chemical vapor deposition method using NiCl2·6H2O as a single-source precursor. Various morphologies of δ-Ni2Si NWs were successfully acquired by controlling the growth conditions. The growth mechanism of the δ-Ni2Si NWs was thoroughly discussed and identified with microscopy studies. Field emission measurements show a low turn-on field (4.12 V/μm), and magnetic property measurements show a classic ferromagnetic characteristic, which demonstrates promising potential applications for field emitters, magnetic storage, and biological cell separation.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]電子版[[booktype]]紙

A Classification and Prediction Hybrid Model Construction with the IQPSO-SVM Algorithm for Atrial Fibrillation Arrhythmia

Atrial fibrillation (AF) is the most common cardiovascular disease (CVD); and most existing algorithms are usually designed for the diagnosis (i.e.; feature classification) or prediction of AF. Artificial intelligence (AI) algorithms integrate the diagnosis of AF electrocardiogram (ECG) and predict the possibility that AF will occur in the future. In this paper; we utilized the MIT-BIH AF Database (AFDB); which is composed of data from normal people and patients with AF and onset characteristics; and the AFPDB database (i.e.; PAF Prediction Challenge Database); which consists of data from patients with Paroxysmal AF (PAF; the records contain the ECG preceding an episode of PAF); and subjects who do not have documented AF. We extracted the respective characteristics of the databases and used them in modeling diagnosis and prediction. In the aspect of model construction; we regarded diagnosis and prediction as two classification problems; adopted the traditional support vector machine (SVM) algorithm; and combined them. The improved quantum particle swarm optimization support vector machine (IQPSO-SVM) algorithm was used to speed the training time. During the verification process; the clinical FZU-FPH database created by Fuzhou University and Fujian Provincial Hospital was used for hybrid model testing. The data were obtained from the Holter monitor of the hospital and encrypted. We proposed an algorithm for transforming the PDF ECG waveform images of hospital examination reports into digital data. For the diagnosis model and prediction model trained using the training set of the AFDB and AFPDB databases; the sensitivity; specificity; and accuracy measures were 99.2% and 99.2%; 99.2% and 93.3%; and 91.7% and 92.5% for the test set of the AFDB and AFPDB databases; respectively. Moreover; the sensitivity; specificity; and accuracy were 94.2%; 79.7%; and 87.0%; respectively; when tested using the FZU-FPH database with 138 samples of the ECG composed of two labels. The composite classification and prediction model using a new water-fall ensemble method had a total accuracy of approximately 91% for the test set of the FZU-FPH database with 80 samples with 120 segments of ECG with three labels

Quantification and recognition of parkinsonian gait from monocular video imaging using kernel-based principal component analysis

<p>Abstract</p> <p>Background</p> <p>The computer-aided identification of specific gait patterns is an important issue in the assessment of Parkinson's disease (PD). In this study, a computer vision-based gait analysis approach is developed to assist the clinical assessments of PD with kernel-based principal component analysis (KPCA).</p> <p>Method</p> <p>Twelve PD patients and twelve healthy adults with no neurological history or motor disorders within the past six months were recruited and separated according to their "Non-PD", "Drug-On", and "Drug-Off" states. The participants were asked to wear light-colored clothing and perform three walking trials through a corridor decorated with a navy curtain at their natural pace. The participants' gait performance during the steady-state walking period was captured by a digital camera for gait analysis. The collected walking image frames were then transformed into binary silhouettes for noise reduction and compression. Using the developed KPCA-based method, the features within the binary silhouettes can be extracted to quantitatively determine the gait cycle time, stride length, walking velocity, and cadence.</p> <p>Results and Discussion</p> <p>The KPCA-based method uses a feature-extraction approach, which was verified to be more effective than traditional image area and principal component analysis (PCA) approaches in classifying "Non-PD" controls and "Drug-Off/On" PD patients. Encouragingly, this method has a high accuracy rate, 80.51%, for recognizing different gaits. Quantitative gait parameters are obtained, and the power spectrums of the patients' gaits are analyzed. We show that that the slow and irregular actions of PD patients during walking tend to transfer some of the power from the main lobe frequency to a lower frequency band. Our results indicate the feasibility of using gait performance to evaluate the motor function of patients with PD.</p> <p>Conclusion</p> <p>This KPCA-based method requires only a digital camera and a decorated corridor setup. The ease of use and installation of the current method provides clinicians and researchers a low cost solution to monitor the progression of and the treatment to PD. In summary, the proposed method provides an alternative to perform gait analysis for patients with PD.</p

Prevalence of Concurrent Functional Vision and Hearing Impairment and Association With Dementia in Community-Dwelling Medicare Beneficiaries.

IMPORTANCE: Impairments in vision or hearing are common and have been independently linked to higher risk of dementia in older adults. There is a limited understanding of the prevalence of concurrent functional vision and hearing impairment (dual sensory impairment) and its contribution to dementia risk. OBJECTIVE: To examine the age-specific prevalence of functional dual sensory impairment among older adults, and to investigate the cross-sectional and 7-year longitudinal associations between functional dual sensory impairment and dementia. DESIGN, SETTING, AND PARTICIPANTS: This cohort study of 7562 older adults used data from the US National Health and Aging Trends Study (NHATS), a nationally representative cohort study of community-dwelling, Medicare beneficiaries aged 65 years and older in the US. Participants in the study with complete data on hearing, vision, and dementia were included in analysis. Data were collected between 2011 and 2018, and between March 2018 and May 2020. EXPOSURES: Self-reported functional sensory impairments (ie, no sensory impairment, functional vision impairment only, functional hearing impairment only, and functional dual sensory impairment). MAIN OUTCOMES AND MEASURES: Age-specific prevalence of functional sensory impairments was calculated. Generalized linear regression with a complementary log-log link and a discrete time proportional hazards model with a complementary log-log link were used to assess the cross-sectional and 7-year longitudinal hazard of dementia. RESULTS: Of 7562 participants, 3073 (40.7%) were ages 80 years or older and 4411 (58.3%) were women. Overall, 5.4% (95% CI, 4.7%-6.1%) of participants reported functional vision impairment only, 18.9% (95% CI, 18.9%-17.8%) reported functional hearing impairment only, and 3.1% (95% CI, 2.7%-3.5%) reported functional dual sensory impairment (prevalence estimates are weighted). Participants reporting sensory impairments were older (no impairment: age ≥90 years, 2.12% [95% CI, 1.79%-2.46%] vs functional dual sensory impairment: age ≥90 years, 20.06% [95% CI, 16.02%-24.10%]), had lower education (no impairment: <high school, 19.05% [95% CI, 17.27%-20.83%] vs functional dual sensory impairment: <high school, 46.15% [95% CI, 38.38%-53.92%]), and greater disease burden (eg, heart disease: no impairment, 15.30% [95% CI, 14.04%-16.55%] vs functional dual sensory impairment, 25.49% [95% CI, 19.96%-31.02%]). Compared with no impairment, functional vision impairment (adjusted hazard ratio [aHR], 1.89; 95% CI, 1.57-2.28), functional hearing impairment (aHR, 1.14; 95% CI, 1.00-1.31), and functional dual sensory impairment (aHR, 2.00; 95% CI, 1.57-2.53) were associated with a higher cross-sectional hazard of dementia. Over 7 years, functional vision impairment (aHR, 1.40; 95% CI, 1.12-1.74), functional hearing impairment (aHR, 1.09; 95% CI, 0.95-1.24), and functional dual sensory impairment (aHR, 1.50; 95% CI, 1.12-2.02) were associated with a higher hazard of incident dementia compared with no impairment. CONCLUSIONS AND RELEVANCE: In this cohort study of US Medicare beneficiaries, dual sensory impairment was prevalent in older adults and associated with increased risk of dementia. These findings suggest that sensory rehabilitative interventions for multiple impairments may be an additional resource in efforts to reduce dementia risk

Tau PET With 18F-THK-5351 Taiwan Patients With Familial Alzheimer's Disease With the APP p.D678H Mutation

Background: Brain 18F-AV-45 amyloid positron emission tomography (PET) in Taiwanese patients with familial Alzheimer's disease with the amyloid precursor protein (APP) p.D678H mutation tends to involve occipital and cerebellar cortical areas. However, tau pathology in patients with this specific Taiwan mutation remains unknown. In this study, we aimed to study the Tau PET images in these patients.Methods: Clinical features, brain magnetic resonance imaging/computed tomography (MRI/CT), and brain 18F-THK-5351 PET were recorded in five patients with the APP p.D678H mutation and correlated with brain 18F-AV-45 PET images. We also compared the tau deposition patterns among five patients with familial mild cognitive impairment (fMCI), six patients with sporadic amnestic mild cognitive impairment (sMCI), nine patients with mild to moderate dementia due to Alzheimer's disease (AD), and 12 healthy controls (HCs). All of the subjects also received brain 18F-AV-45 PET.Results: The nine patients with sAD and six patients with sMCI had a positive brain AV-45 PET scans, while the 12 HCs had negative brain AV-45 PET scans. All five patients with fMCI received a tau PET scan with the age at onset ranging from 46 to 53 years, in whom increased standard uptake value ratio (SUVR) of 18F-THK-5351 was noted in all seven brain cortical areas compared with the HCs. In addition, the SUVRs of 18F-THK-5351 were increased in the frontal, medial parietal, lateral parietal, lateral temporal, and occipital areas (P &lt; 0.001) in the patients with sAD compared with the HCs. The patients with fMCI had a significant higher SUVR of 18F-THK-5351 in the cerebellar cortex compared to the patients with sMCI. The correlations between regional SUVR and Mini-Mental State Examination score and between regional SUVR and clinical dementia rating (sum box) scores within volumes of interest of Braak stage were statistically significant.Conclusion: Tau deposition was increased in the patients with fMCI compared to the HCs. Increased regional SUVR in the cerebellar cortical area was a characteristic finding in the patients with fMCI. As compared between amyloid and tau PET, the amyloid deposition is diffuse, but tau deposition is limited to the temporal lobe in the patients with fMCI

Transcriptional regulation of miR-196b by ETS2 in gastric cancer cells

E26 transformation-specific sequence (ETS)-2 is a transcriptional modulator located on chromosome 21, alterations in its expression have been implicated with a reduced incidence of solid tumors in Down syndrome patients. MicroRNAs (miRNAs) are thought to participate in diverse biological functions; however, the regulation of miRNAs is not well characterized. Recently, we reported that miR-196b is highly expressed in gastric cancers. Herein, we demonstrate that miR-196b expression was significantly repressed by ETS2 during gastric cancer oncogenesis. We demonstrate that knockdown of endogenous ETS2 expression increases miR-196b expression. A genomic region between −751 and −824 bp upstream of the miR-196b transcriptional start site was found to be critical for the repression activity. This putative regulatory promoter region contains three potential ETS2-binding motifs. Mutations within the ETS2 binding sites blocked the repression activity of ETS2. Furthermore, knockdown of ETS2 or overexpression of miR-196b significantly induced migration and invasion in gastric cancer cells. In addition, alterations in ETS2 and miR-196b expression in gastric cancer cell lines affected the expression of epithelial–mesenchymal transition-related genes. The levels of vimentin, matrix metalloproteinase (MMP)-2 and MMP9 were drastically induced, but levels of E-cadherin were decreased in shETS2- or miR-196b-transfected cells. Our data indicate that ETS2 plays a key role in controlling the expression of miR-196b, and miR-196b may mediate the tumor suppressor effects of ETS2. We demonstrated that miR-196b was transcriptionally regulated by ETS2 and there was an inverse expression profile between miR-196b and ETS2 in clinical samples. This finding could be beneficial for the development of effective cancer diagnostic and alternative therapeutic strategies