Miracle-dz/UniFAR-FTUs huggingface dataset:
Privacy-Preserving Face Recognition in the Frequency Domain

Some applications may require performing face recognition (FR) on third-party servers, which could be accessed by attackers with malicious intents to compromise the privacy of users’ face information. This paper advocates a practical privacy-preserving FR scheme without key management realized in the frequency domain. The new scheme first collects the components of the same frequency from different blocks of a face image to form component channels. Only part of the channels are retained and fed into the analysis network that performs an interpretable privacy-accuracy trade-off analysis to identify channels important for face image visualization but not crucial for maintaining high FR accuracy. For this purpose, the loss function of the analysis network consists of the empirical FR error loss and a face visualization penalty term, and the network is trained in an end-to-end manner. We find that with the developed analysis network, more than 94% of the image energy can be dropped while the face recognition accuracy stays almost undegraded. In order to further protect the remaining frequency components, we propose a fast masking method. Effectiveness of the new scheme in removing the visual information of face images while maintaining their distinguishability is validated over several large face datasets. Results show that the proposed scheme achieves a recognition performance and inference time comparable to ArcFace operating on original face images directly.
A Wideband Endfire Dual Circularly Polarized Antenna for 5G Millimeter-Wave Applications

In this letter, an all-metallized wideband dual circularly polarized antenna with endfire radiation is proposed for fifth-generation (5G) millimeter-wave applications. By introducing two rectangular notches on the side walls of open-ended waveguide, the vertical components are increased and close to the horizontal components in the broadband range so that the axial ratio (AR) bandwidth is enhanced. The simulated results show that the proposed antenna excited by wave port has 63.9% operation bandwidth (22.7–44.0 GHz), where reflection coefficients less than −10 dB, isolations greater than 20 dB, and AR less than 3 dB are achieved. To verify the design, the proposed antenna excited by coaxial connectors is fabricated and measured. Based on the measurement results, the reflection coefficients less than −10 dB, isolations greater than 20 dB, and AR less than 3 dB are achieved from 23.0–40.0 GHz, the endfire gain varies from 5.1 to 8.5 dBic at the frequencies mentioned above.
Pan-Sharpening with Customized Transformer and Invertible Neural Network

In remote sensing imaging systems, pan-sharpening is an important technique to obtain high-resolution multispectral images from a high-resolution panchromatic image and its corresponding low-resolution multispectral image. Owing to the powerful learning capability of convolution neural network (CNN), CNN-based methods have dominated this field. However, due to the limitation of the convolution operator, long-range spatial features are often not accurately obtained, thus limiting the overall performance. To this end, we propose a novel and effective method by exploiting a customized transformer architecture and information-lossless invertible neural module for long-range dependencies modeling and effective feature fusion in this paper. Specifically, the customized transformer formulates the PAN and MS features as queries and keys to encourage joint feature learning across two modalities while the designed invertible neural module enables effective feature fusion to generate the expected pan-sharpened results. To the best of our knowledge, this is the first attempt to introduce transformer and invertible neural network into pan-sharpening field. Extensive experiments over different kinds of satellite datasets demonstrate that our method outperforms state-of-the-art algorithms both visually and quantitatively with fewer parameters and flops. Further, the ablation experiments also prove the effectiveness of the proposed customized long-range transformer and effective invertible neural feature fusion module for pan-sharpening.
The neural mechanisms of explicit and implicit processing of Chinese emotion-label and emotion-laden words: evidence from emotional categorisation and emotional Stroop tasks

ABSTRACT This study set out to examine the valence effect on the explicit and implicit processing of Chinese emotion-label and emotion-laden words with emotional categorisation task (ECT) and emotional Stroop task (EST). Behaviourally, the dissociation between emotion-label and emotion-laden words was only observed in the ECT and was modulated by valence. Neurophysiologically, a negative bias was found in the early perceptual processing stage (N170). In the second processing stage, the dissociation between emotion-label and emotion-laden words was modulated by valence (P2 and EPN). In the elaborate processing stage, the neural dissociation between emotion-label and emotion-laden words was modulated by the processing level (frontal N400 and early LPC). Valence interacted with processing level (late LPC). This study verifies the three-stage model of emotional word processing and extends it by adding two factors—processing level and emotional word type—into the model.
FlashMAC: A Time-Frequency Hybrid MAC Architecture With Variable Latency-Aware Scheduling for TinyML Systems

With the widespread of deep neural networks (DNNs) in diverse applications, tiny platforms such as Internet-of-Things devices are starting to adopt DNNs. Due to their extreme energy and form factor constraints, conventional digital-only implementations of multiply-and-accumulate (MAC) acceleration faced fundamental limitations. To that end, the investigation into mixed-signal computing architectures is growing rapidly. Motivated by the flash ADC, this article proposes FlashMAC architecture that can natively support multibit multiplication. In addition, through fusing time- and frequency-domain computing methods without power-hungry oscillators, it enables low latency accumulation with low power consumption. As a result, the proposed time-frequency hybrid architecture achieves high energy efficiency with the support for complex DNN models requiring higher precision. To enhance the robustness of PVT variation of the mixed-signal architecture, a frequency calibration loop is integrated. In addition, motivated by the data-dependent performance of the FlashMAC architecture, variable latency-aware scheduling is proposed. The FlashMAC does not skip MAC operations as zero-skipping architectures do, but the latency of the operation can be lower when operands are smaller in magnitude. Tackling the issue through software and hardware co-optimization, loose synchronization architecture and magnitude-aware weight reordering increase the DNN benchmark performance by achieving higher utilization of the parallel FlashMAC array. The proposed features are integrated into a test chip which is fabricated in 65-nm logic CMOS technology. The silicon chip achieves 56.52 TOPS/W peak energy efficiency and a peak operating frequency of 90 MHz. Tested with the VGG16 benchmark trained on the Imagenet dataset, it achieved 17.04-ms latency while showing 11.15 TOPS/W energy efficiency. As a result, compared to the previous state-of-the-art, the proposed FlashMAC achieved 3.15 $\times $ higher normalized energy efficiency.
Análise dos dispositivos de saúde mental em municípios do Vale do Paraíba

Estudo que teve como objetivo identificar e analisar a relacao entre a populacao quanto a quantidade e modalidade de dispositivos de saude mental existentes. Tratou-se de pesquisa descritivo-exploratoria realizada nos 27 municipios da Regional da Saude XVII do Estado de Sao Paulo. Dos municipios participantes, sete possuiam algum dispositivo de saude mental, totalizando 12 em cinco diferentes modalidades: dois Centros de Atencao Psicossocial tipo I; dois do tipo II; um hospital dia; 12 leitos em hospital geral; quatro ambulatorios e sete leitos em unidades de emergencia. Elevado numero de pessoas residentes nos municipios participantes encontra-se sem cobertura assistencial.
Impact of Chitosan Coatings Enriched with Clove Essential Oil on Quality of Minimally Processed Strawberries

: The work aimed to evaluate the effects of applying chitosan edible coating with the addition of different concentrations of clove essential oil in minimally processed strawberries. The strawberries were selected and sanitized, had their leaves removed, and were submerged in the coatings. Three treatments were obtained: T1 - control (uncoated strawberries); T2
Energy-Guided Multitarget Detection and Localization for Distributed MIMO Radar: Analysis and Solution

This article investigates the multitarget detection and localization problem for distributed multiple-input multiple-output radar. We first derive the optimal approach of this issue in the high-dimensional space according to the generalized likelihood ratio test (GLRT) and the maximum likelihood estimation. Moreover, the theoretical multitarget localization accuracy under the considered discrete time signal model is analyzed by invoking the Cram$\acute{\text{e}}$r–Rao lower bound and the sampling lower bound. To deal with the high complexity problem of the optimal solution, an energy-guided framework including two modules is proposed to detect and locate multiple targets. In the first module, the energy accumulation approach based on the GLRT is employed for multitarget detection, and a fast energy accumulation strategy in terms of the far-field case is developed to improve the computational efficiency. In the second module, an innovative iterative similarity evaluation method is designed to determine the positions of multiple targets by exploiting the relationship between the energy accumulation characteristics and the multitarget existence conditions. The effectiveness of the proposed framework is verified via extensive simulations in both far-field and near-field cases.
Effects of lifestyle and genetic factors on the levels of serum adiponectin, a novel marker of the metabolic syndrome, in Finnish servicemen

Metabolic syndrome (MetS) is a combination of disorders that increase one's risk for type 2 diabetes (DM2) and cardiovascular disease (CVD). Both lifestyle and genetic factors have been established to be involved in the aetiology of MetS. Improving our knowledge about the pathophysiology of MetS could provide more effective therapeutic approaches and reduce the risk of developing DM2 and CVD. Lower levels of adiponectin, an adipose-derived protein, has been shown to be associated with the components of MetS. Common variants in a number of candidate genes related to MetS have been shown to be associated with changes in the serum adiponectin level. This study was designed to evaluate the putative effects of military lifestyle, as well as common polymorphisms of the peroxisome proliferator activated receptor gamma 2 (PPARγ2), insulin receptor substrate-1 (IRS-1) and adiponectin (APM1) genes on serum adiponectin level in a cohort of Finnish servicemen. Results of this study have showed that serum adiponectin significantly decreased during the sixmonth follow up in military service compared to baseline levels. This decrease was even shown in subjects that experienced a 5-10 % weight loss after six-months. Subjects with the Ala12Ala genotype of PPARγ2 had significantly higher levels of serum adiponectin compared with subjects with the Pro12Ala and Pro12Pro genotypes. Subjects having the X12Ala genotype of PPARγ2 with > 10% weight reduction showed a significant increase in serum adiponectin compared to other groups during the follow up. Those having the Ala12Ala genotype of PPARγ2 + Gly972Gly genotype of IRS-1 combination had significantly higher adiponectin compared with subjects with the Pro12Pro + Gly972Gly and Pro12Ala + Gly972Gly genotype combinations. Adiponectin levels were significantly higher in men with the T276T genotype compared with subjects with the G276T or G276G genotypes of SNP+276 of the APM1 gene. In conclusion, this study shows a possible impact of a military lifestyle as well as, candidate gene variations, and their interactions upon the regulation of serum adiponectin levels as a marker of MetS. This study could serve as a pilot for the further extensive studies with longer follow up periods as well as more accurate information on specific lifestyle factors.
Differential Distribution and Activity Profile of Acylpeptide Hydrolase in the Rat Seminiferous Epithelium

Acylpeptide hydrolase (APEH) is a serine protease involved in amino acid recycling from acylated peptides (exopeptidase activity) and degradation of oxidized proteins (endoproteinase activity). This enzyme is inhibited by dichlorvos (DDVP), an organophosphate compound used as an insecticide. The role of APEH in spermatogenesis has not been established; therefore, the aim of this study was to characterize the distribution and activity profile of APEH during this process. For this purpose, cryosections of male reproductive tissues (testis and epididymis) and isolated cells (Sertoli cells, germ cells, and spermatozoa) were obtained from adult rats in order to analyze the intracellular localization of APEH by indirect immunofluorescence. In addition, the catalytic activity profiles of APEH in the different male reproductive tissues and isolated cells were quantified. Our results show that APEH is homogeneously distributed in Sertoli cells and early germ cells (spermatocytes and round spermatids), but this pattern changes during spermiogenesis. Specifically, in elongated spermatids and spermatozoa, APEH was localized in the acrosome and the principal piece. The exopeptidase activity was higher in the germ cell pool, compared to sperm and Sertoli cells, while the endoproteinase activity in epididymal homogenates was higher compared to testis homogenates at 24 h of incubation. In isolated cells, this activity was increased in Sertoli and germ cell pools, compared to spermatozoa. Taken together, these results indicate that APEH is differentially distributed in the testicular epithelium and undergoes re-localization during spermiogenesis. A possible role of APEH as a component of a protection system against oxidative stress and during sperm capacitation is discussed.
Unsupervised Domain Adaptation using Maximum Mean Covariance Discrepancy and Variational Autoencoder

—Face Recognition has progressed tremendously from its initial use of holistic learning models to using hand-crafted, shallow, and deep learning models. DeepFace, a nine- layer Deep Convolutional Neural Network (DCNN), reached near-human performance on unconstrained face recognition for the La- beled Faces in the Wild (LFW) dataset. These models performed very well on the benchmark datasets, but their performance sometimes deteriorated for real-world applications. The problem arose when there was a domain shift due to different distribution spaces of the training and testing models. Few researchers looked at Unsupervised Domain Adaptation (UDA) to ﬁnd the domain- invariant feature spaces. They tried to minimize the domain discrepancy using a static loss of maximum mean discrepancy (MMD). From MMD, the researchers delved into the higher-order statistics of maximum covariance discrepancy (MCD). MMD and MCD were combined to get maximum mean and covariance discrepancy (MMCD), which captured more information than MMD alone. We use a Variational Autoencoder (VAE) with joint mean and covariance discrepancy to offer a solution for domain adaptation. The proposed MMCD-VAE model uses VAE to measure the discrepancy in the spread of variance around the mean value and uses MMCD to measure the directional discrepancy in the variance. Analysis was done using the TinyFace benchmark dataset and the Bollywood Celebrities dataset. Three objective image quality parameters, namely SSIM, pieAPP, and SIFT feature matching, demonstrate the superiority of MMCD-VAE over the conventional KL-VAE model. MMCD-VAE shows an 18 % improvement in SSIM and a remarkable improvement in the perceptual quality of the image over the conventional KL- VAE model.
Incidence, prognostic factors and survival in bladder cancer patients: a population-based study

Background The aim of this study was to investigate the incidence, epidemiologic characteristics, prognostic factors and survival of patients with bladder cancer. Methods Bladder cancer patients diagnosed between 2010 and 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox proportional hazards regression analyses were used to identify the independent prognostic factors for overall survival. Kaplan-Meier survival analysis and nomogram analysis were constructed based on the identified independent prognostic factors. Results A total of 95,329 eligible bladder cancer patients were included in this study. Eight independent risk factors, including age, histologic type, race, tumor, node and metastasis (TNM) stage, American Joint Committee on Cancer (AJCC) stage, surgery, tumor metastasis and summary stage, were recognized by using multivariate logistic regression models. By comprising these factors, a predictive nomogram was constructed to predict the 1-, 3-, and 5-year overall survival possibilities. The concordance index and calibration curve showed that the nomogram had robust and accurate performance. Conclusions Bladder cancer is the most common cancer of the urinary system, but the overall incidence has been decreasing yearly since 1992. Our results demonstrate eight factors significantly associated with overall survival in bladder cancer patients. Based on these factors, we established and validated a nomogram, which has the potential to provide an individualized prediction of overall survival in patients with bladder cancer.
High Levels of Akkermansia muciniphilia Growth Associated With Spring Water Ingestion Prevents Obesity and Hyperglycemia in a High-fat Diet-Induced Mouse Model

Background: Type 2 diabetes may be alleviated by mineral water (MW) ingestion. We investigated whether spring water (SW) (a kind of mixed MW) ingestion influences metabolic parameters via alteration of the gut microbiota in high-fat diet (HFD)-fed mice. Method: We divided 32 C57/BL mice into 4 equal groups: normal diet with tap water (Control), high-fat diet with tap water (HFD), normal diet with SW (SW), and high-fat diet with SW (HFD + SW). During this experiment, we checked the body weight (BW) with fasting blood sugar (FBS) every week and all mice were sacrificed in the 17th week to observe serological markers, internal organs, and composition of gut microbiota. Results: The BW of HFD-fed mice was significantly higher than that of mice fed an HFD + SW diet in the early period of the experiment. Fasting blood glucose (FBG) in the HFD group showed a fluctuating pattern compared to the HFD + SW group, and the area under the curve (AUC) value of the oral glucose tolerance test (OGTT) was significantly greater in the HFD group than in the HFD + SW group. Serologic markers were not significantly different between the HFD and HFD + SW groups. Histologically, the most severe fatty changes in the liver were observed in the HFD group. Lastly, the gut levels of Akkermansia muciniphilia were 100-fold higher in the HFD + SW group than in the HFD mice. Conclusion: These findings indicate that SW ingestion, and the associated high levels of A muciniphilia growth in the gut, may improve the early stage of obesity and ameliorate HFD-induced hyperglycemia.
Global Disparities of Hypertension Prevalence and ControlClinical Perspective

Background: Hypertension is the leading preventable cause of premature death worldwide. We examined global disparities of hypertension prevalence, awareness, treatment, and control in 2010 and compared secular changes from 2000 to 2010. Methods: We searched MEDLINE from 1995 through 2014 and supplemented with manual searches of retrieved article references. We included 135 population-based studies of 968 419 adults from 90 countries. Sex- and age-specific hypertension prevalences from each country were applied to population data to calculate regional and global numbers of hypertensive adults. Proportions of awareness, treatment, and control from each country were applied to hypertensive populations to obtain regional and global estimates. Results: In 2010, 31.1% (95% confidence interval, 30.0%–32.2%) of the world’s adults had hypertension; 28.5% (27.3%–29.7%) in high-income countries and 31.5% (30.2%–32.9%) in low- and middle-income countries. An estimated 1.39 (1.34–1.44) billion people had hypertension in 2010: 349 (337–361) million in high-income countries and 1.04 (0.99–1.09) billion in low- and middle-income countries. From 2000 to 2010, the age-standardized prevalence of hypertension decreased by 2.6% in high-income countries, but increased by 7.7% in low- and middle-income countries. During the same period, the proportions of awareness (58.2% versus 67.0%), treatment (44.5% versus 55.6%), and control (17.9% versus 28.4%) increased substantially in high-income countries, whereas awareness (32.3% versus 37.9%) and treatment (24.9% versus 29.0%) increased less, and control (8.4% versus 7.7%) even slightly decreased in low- and middle-income countries. Conclusions: Global hypertension disparities are large and increasing. Collaborative efforts are urgently needed to combat the emerging hypertension burden in low- and middle-income countries. # Clinical Perspective {#article-title-35}
The First Approved COVID-19 Vaccines: The Road to Cancer Vaccines

In the past decade, mRNA vaccines have been highly discussed as a promising therapy for cancer. With the pandemic of COVID-19, some researchers redirected their studies to the development of a new vaccine for COVID-19 due to the urgent need. With the pandemic’s deceleration due to the vaccines’ success, the research and development of mRNA vaccines have turned to cancer again. Considering the new evidence and results generated by the vaccination of millions of people with mRNA vaccines, this article intends to provide a perspective on how the results from COVID-19 vaccination could now provide new insights for the development of an mRNA cancer vaccine. Many lessons were learned, and new evidence is available to re-focus and enhance the potential of the mRNA technology to cancer. Pfizer-BioNTech and Moderna’s mRNA technologies, and their significant advancements, allowed mRNA to overcome many of the challenges and blockers related to this platform in the past, now providing a new breadth of hope on using the mRNA technology to treat many diseases, namely cancer. This study also reports a better understanding of how it was possible to boost an accelerated development process of COVID-19 vaccines from a regulatory point of view. It is also relevant to consider other synergies and factors that contributed to gathering all the conditions ensuring the development of these vaccines in such a short period. Suppose the same efforts from all stakeholders could be applied to the development of new cancer vaccines, aligned now with the new scientific evidence generated from the current mRNA vaccines for COVID-19. In that case, mRNA cancer vaccines are near, and a new era for cancer treatment is about to begin.
Global Stabilization for Uncertain Nonlinear Time-Delay Systems With Saturated Input

In this article, global stabilization for a class of nonlinear uncertain time-delay systems with saturated input is considered. The saturated input is handled by a new auxiliary system with dynamic gain and the linear growth condition with unknown growth rates is removed. A novel adaptive observer-controller coupling design framework is put forward, under which the closed-loop system is globally bounded. Finally, a simulation shows that the proposed technique is effective.