Facial Process Research Articles

Synthesis of porous ZnxCo3-xO4 hollow nanoboxes derived from metal-organic frameworks for lithium and sodium storage

A facial and efficient process for the synthesis of porous ZnxCo3-xO4 hollow nanoboxes using zeolitic imidazolate frameworks as precursors has been demonstrated in this study, the as-prepared electrodes are applied for both LIBs and SIBs. The porous structure and hollow interspace can not only provide valuable channels and voids for lithium/sodium ion transfer and storage, but also buffer the stress/strain caused by volume changes. Besides, the enhanced electrical conductivity can effectively improve the reaction kinetics by synergistic effect of the binary metal oxides, as studied by density functional theory (DFT) calculations and storage mechanism studies. For lithium-ion batteries, the electrode exhibits an ultrahigh reversible capacity of 1141.7 mAh g−1, with an initial coulombic efficiency of 95.6%, and an ultralong life up to 800 cycles at 500 mA g−1. Even at a high current of 3.0 A g−1, a superior capacity of 484 mAh g−1 can be achieved. When using for sodium-ion battery anode, the reversible capacity is remained at 310 mAh g−1 after 100 cycles at 200 mA g−1, with a capacity retention of 90.4%. The electrode materials show long-term cycle stability and excellent rate capability, which gives a bright prospect for energy storage devices.

Nose width and mouth width predictions in a Thai population using cone-beam computed tomography data

ABSTRACT Nose width and mouth width are the distances needed to be estimated in facial reconstruction process. The previous prediction guidelines for them were mainly based on European samples, whereas Asian samples used in their studies were limit. Our study, therefore, intended to formulate the prediction guidelines for the nose and mouth width, using the infraorbital foramen and canine in a Thai population. The measurements were performed in 3D images generated from cone-beam computed tomography (CBCT) scans of the heads of 108 Thai subjects with normal BMI and ages ranging from 21.0–50.9 years. The ratio between the infraorbital and intercanine widths to the nose and mouth widths were calculated. The lateral distance between the infraorbital foramen and canine to the alare and cheilion were also assessed. The results suggested that nose width and mouth width predictions could be achieved with low variation using the infraorbital foramen and canine (the standard deviation of less than 2.0 mm and the coefficient of variation of less than 1.1 mm). Our results will give useful information for facial reconstruction in Thai samples.

LAMSTAR: For IoT‐based face recognition system to manage the safety factor in smart cities

AbstractDigital transformation played a vital role in smart cities because of its ability to process the different data to providing sustainability, connectivity, and mobility to data effectively. According to the diver operational productivity, preserving public safety government law enforcement integrated that face recognition is more important in smart cities. Traditional face recognition system fails to predict the exact facial features that leads to reduce the facial recognition accuracy. The false facial point detection process maximizes the computation complexity. Therefore, in this work, effective and artificial intelligence internet of things–based facial expression detection system is implemented to predict and match the face from the database. Initially, the facial images are captured from the internet of things sensor device, which is processed by applying the Perona‐Malik diffusion algorithm. Then, face location is cropped from the image, geometric face shape model is created for predicting the exact face from the template face image. From the face shape, different facial features are extracted from various region using Fisher linear discriminant analysis. The derived features are trained with the help of convolution network and the face recognition process is done by using the adaboost large memory storage and retrieval neural network. The network successfully recognizes the face from the template, which is used to eliminate the safety related risk in smart cities.

Studies of polypropylene surface modified with novel beta-thiopropionate-based zwitterionic polymeric brush: synthesis, surface characterization, and significantly reduced fouling characteristics evaluation

Creating a surface with anti- or reduced fouling characteristics can lead to a reduction in nonspecific protein adsorption as well as the bacterial adhesion and platelet adhesion/activation that occur as follows. A zwitterionic polymer that consists of both cationic and anionic functionalities have been reported as an effective material to achieve these goals, likely resulted from the strongly-adsorbed hydration layer after being immersed in the physiological environment. In this investigation, a novel beta-thiopropionate-based zwitterionic monomer, 2-ammonio-3-((3-(2-hydroxy-3-(methacryloyloxy)propoxy)-3-oxopropyl)thio)-3-methylbutanoate (DPAMA), was synthesized through a facial process. And then the hydrophobic polypropylene was surface modified with this novel zwitterionic polymer through the surface-initiated atom transfer radical polymerization technique. Surface characterization analyses have been employed to investigate the modified surface properties in each reaction stage. In vitro protein adsorption, bacterial adhesion, and platelet compatibility evaluations have shown the polyDPAMA-modified polypropylene surface has significantly reduced fouling characteristics and good hemocompatibility. Henceforth, this novel zwitterionic polyDPAMA grafting PP and the associated grafting reaction scheme have great potential for future clinical applications.

Dispersive solid-phase extraction adsorbent of methamphetamine using in-situ synthesized carbon-based conductive polypyrrole nanocomposite: focus on clinical applications in human urine.

Determination of methamphetamine is of great importance in clinical and forensic laboratories because there are low dosages of drugs in the biological media and social problems created due to the methamphetamine consumption. Polymeric carbon based-nano composites are reasonable candidates for dispersive solid phase extraction method due to facial and affordable synthesis process and high selectivity and sensitivity. Nano graphene oxide polypyrolle composite was synthesized and employed as dispersive solid-phase extraction adsorbent for methamphetamine extraction from complex urine matrix. Full characterization of the prepared nano graphene oxide polypyrolle composite was completed and the influential extraction parameters were investigated through one-parameter-at-a-time method. High-performance liquid chromatography detectors were applied as detection and quantification instrument. The optimized extraction parameters included 300 µL of methanol, 10min of extraction and desorption time, 6000 stirring rate, urine pH value of 10, 60mg of adsorbent, and 6mL of urine volume. After outlining the calibration curve, the linear range of the method was considered as 30-800ng/mL. The detection limit for the suggested method was 9ng/mL. The analysis of addicted subjects with the proposed method confirmed the utility of the method in different analytical and clinical laboratories.

The catalytic performance enhancement of Ni2P electrocatalysts for hydrogen evolution reaction by carbon-based substrates

Combination of catalytic active components with substrates is deemed to be a promising approach to pursue high active and stable catalysts. Wherein, carbon-based materials as a kind of frequently-used substrates are well developed, and thus the different effects of them on catalytic active components deserve investigating and contrasting. In this work, well dispersive and ultrafine Ni2P nanoparticles supported on N-doped reduced graphene oxide (N-RGO) were synthesized through a facial hydrothermal process and subsequent phosphorization. The prepared Ni2P/N-RGO demonstrates a superior electrocatalytic activity towards hydrogen evolution reaction (HER) in 0.5 M H2SO4 solution with a low onset overpotential (80 mV) and small Tafel slope (93.1 mV dec−1). Additionally, as compared with other representative carbon materials (carbon black (C) and carbon nanotubes (CNTs)) in the perspective of specific surface area (SSA), conductivity and electronic interaction in particular, N-RGO demonstrates a preeminent promotional effect as a substrate of Ni2P.

Disentangled representation learning and residual GAN for age-invariant face verification

One of the challenges in cross-age face recognition and verification is to effectively model the facial aging process. Despite the rapid advances in face-related areas, it is still very difficult for existing methods to simultaneously achieve accurate facial feature preservation and reliable aging during aging modeling. Aiming to address this issue, we introduce a Disentangled Representation learning and Residual Generative Adversarial Network (DR-RGAN) that represents the facial features without age interference, which is achieved by explicitly disentangling the facial features and age variation. An encoder-decoder structured generator produces aging images from unstructured facial representations by using the age characteristics provided separately. It can thus take the disentangled representation to preserve personal identity for face verification. Considering that pixel-based errors may cause a loss of detail, a VGG based content loss is further equipped to preferably preserve facial features. The discriminator is trained to distinguish the real from generated faces, carry out identification prediction, and leverage an age estimator to boost the aging accuracy. It is beneficial for obtaining more photorealistic and desirable aging effects, as well as more consistent face verification results. Extensive experiments on the CACD and LFW datasets demonstrate that our DR-RGAN generates pleasing aging imageries and achieves a high accuracy of face verification.

Robust three-dimensional porous rGO aerogel anchored with ultra-fine α-Fe2O3 nanoparticles exhibit dominated pseudocapacitance behavior for superior lithium storage

Based on the ultra-fast faradaic surface induced reversible redox reactions, pseudocapacitance behavior with rapid electrochemical kinetics can boost the high power density of lithium ion battery. In this work, a three-dimensional (3D) interconnected porous reduced graphene oxide network incorporated with homogeneously dispersed ultra-fine α-Fe2O3 nanoparticles (denoted α-Fe2O3@3DrGO) is subtly synthesised through a facial hydrothermal self-assembly process. Such desirable hierarchical structure delivers an ever-increasing pseudocapacitance storage as anode, achieving an unprecedented rate capacity (921.6, and 812.4 mA h g−1 at 1 and 5 A g−1) and a superior cycle performance with ultra-high capacity (1198.6 mA h g−1 at 1 A g−1 over 200 cycles), which is almost the best result reported so far. Even at a high current density of 5 A g−1, it still maintains the excellent cycle stability with a capacity of 396.6 mA h g−1 after 2000 cycles. Such outstanding electrochemical performance may be ascribed to the synergy of the robust structure, porous surface morphology as well as accompanying dominated pseudocapacitance behavior. We hope this work can provide a novel strategy for realizing high rate and stable cycle performances in lithium storage.

Facial recognition techniques using SVM: A comparative analysis

This paper presents a literary review of facial recognition in 2D, which plays an important role in the life of the human being in terms of safety, work activity, etc. The focus is on the results obtained by some researchers with the application of feature extraction techniques, pattern classifiers, databases and their respective percentage of efficiency obtained. The objective is to determine efficient techniques that allow an optimal 2D facial recognition process, based on the quality of databases, feature extractors and pattern classifiers.

Effects of Facial Threading on Female Skin Texture: A Prospective Trial with Physiological Parameters and Sense Assessment.

Background Facial threading is a common tradition in Taiwan, Southeast Asia (called “Bande Abru”), Middle East (called “Khite”), and Egypt (called “Fatlah”). In addition to the ability to remove facial vellus hairs, facial threading can make the skin fairer and shinier. However, there has been a lack of hard evidence regarding the effects of facial threading on the skin. Objective To examine the effects of facial threading on skin physiology as well as visual and touch senses by using scientific instruments. Methods A total of 80 participants were allocated to receive facial threading, application of powder only, exfoliation, and shaving. Prior to and following the assigned treatment, a noninvasive skin condition detection device was used to measure skin coarseness, hydration, melanin, and erythema index. Sense assessment and image analysis were also performed. Results This study showed that facial threading was found to improve the facial skin roughness indices with significant decreases by 30.4%, 35.9%, and 16.7%, respectively, for the participants' forehead, cheek, and mouth corner skin. No significant adverse changes in moisture levels and skin pigment indices were detected. In addition, there was improvement in subjects' touch sense of their skin and feelings about skin color. Conclusions Traditional facial threading can remove facial vellus hairs and lower skin roughness levels, thereby improving the skin texture. However, pricking sensation appeared during the facial threading process, which might cause concerns about irritation.

Preparation of bioactive hydroxyapatite@halloysite and its effect on MC3T3-E1 osteogenic differentiation of chitosan film.

Halloysite nanotubes (HNTs) are widely used in biomedical field due to their special tubular structure and high reinforcing ability, while hydroxyapatite (HAP) is generally used in tissue engineering owing to its excellent biocompatibility and biological activity. In this work, hydroxyapatite@halloysite nanotubes(HAP@HNTs) hybrid was synthesized via a facial hydrothermal reaction process. The morphology, particle size, specific surface area, and chemical composition of the hybrid were thoroughly characterized by different techniques. Rod-like HAP nanoparticles can be anchored on the outer surface of the clay tubes, which lead to a maximum increase of 4.7 m2/g in the specific surface area of HAP@HNTs over that of HNTs. HAP nanoparticles have little effect on the pores of HNTs, but diffraction peak strength of HNTs is covered by the HAP crystals. HAP@HNTs exhibit improved cytocompatibility and possess osteogenic differentiation ability towards MC3T3-E1 preosteoblasts. Chitosan/HAP@HNTs composite films were then prepared by doping of HAP@HNTs into chitosan by solution mixing. HAP@HNTs can serve as a functional phase which enhances mechanical properties of chitosan films and osteogenic differentiation of MC3T3-E1 cells. This work provides a facial synthesis routine of bioactive HAP@HNTs, which combines the osteogenic activity of HAP and the good mechanical properties of HNTs. HAP@HNTs can be used a novel bone regeneration biomaterial as local delivery systems with improved osteoinductive properties.

Treating nasolabial folds with dermal fillers: a holistic approach

There are multiple surgical and non-surgical ways to treat the nasolabial fold. Traditionally, the non-surgical way of treating nasolabial folds was through careful placement of hyaluronic acid fillers directly to the fold. Our understanding of the facial ageing process and facial anatomy has enabled us to evolve our technique so that nasolabial fold treatments are safer for patients and deliver better clinical outcomes. By treating nasolabial folds indirectly, by addressing the changes that occur through aging, the aesthetic practitioner can achieve more natural and effective reduction in the fold. Indirect treatment of the nasolabial fold requires addressing the bony resorption, deep fat and superficial fat volume loss. Through better understanding of the facial aging process, we are entering an era where more practitioners are treating the cause of a particular line than treating it directly. This has the benefit of creating a more balanced and natural result with longer lasting rejuvenation.

3D facial expression modeling based on facial landmarks in single image

Facial expression modeling is important for many applications such as human emotional analysis and facial animation. Generally, facial expression modeling from single 2D facial image is difficult. Different head poses and scales of facial data in images affect the accuracy of the modeling results. We propose a new 3D facial expression modeling method which is based on facial landmarks from single image. Using the facial landmarks, expression modeling can be processed in Kendall shape space. The Kendall shape space is mathematic space, the facial expression modeling process in Kendall shape space can be regarded as a geodesic path search between different faces. The modeling result is more accurate. The 3D facial expression modeling result is convenient to obtain from 2D facial image with different head poses. In experiments, we show the 3D facial expression modeling performance by our method, which include expression editing and evaluation in public facial database: JAFFE, LFW, Helen and RAF-DB.

Application of Cell Therapy for Anti-Aging Facial Skin.

The human skin undergoes the complex process of aging which is prompted by the interplay of intrinsic mechanisms and extrinsic influences. Aging is unavoidable but can be somewhat delayed. Numerous approaches have been developed to slow down facial skin aging process as it is of interest to stake holders in the beauty and fashion world as well as to plastic surgeons. Adipose-derived stem cell [ADSC] and mesenchymal stem cell [MSC] as potential anti-aging agents to some extent have provided a promising and effective alternative in managing skin and facial skin aging. Furthermore, bone marrow-derived mesenchymal stem cells [BMMSC] have exhibited similar ability to rejuvenate aged skin. This review is aimed at giving a comprehensive account of the application of stem cells especially ADSCs and MSCs to reduce or slow down the rate of facial skin aging process.

Comparison of facial expression recognition performance according to the use of depth information of structured-light type RGB-D camera

In this paper, we investigate the efficiency of depth information in facial expression classification through structured-light type RGB-D camera. In the experiment for verification, we compare the performance of binary classification for happy, surprise, and neutral facial expressions. Face images of 49,500 sets with pose variations for two-dimensional (2D) and three-dimensional (3D) images were acquired and the geometric feature points were extracted. Classification results of 10 geometric points around the eyes and mouth showed about 90.87% classification accuracy when depth information was not used. On the other hand, when depth information was used, the classification accuracy was about 86.24%. As a result, it was confirmed that the 2D image based method has higher classification performance than the 3D depth information based method. The reason is the compensation process of the horizontally accumulated depth error due to the characteristics of the vertical structured-light pattern for the depth measurement of the structured-light type RGB-D camera. Also, when the distance from the camera was 50cm, it was confirmed that a depth noise of 1 mm maximum occurred. As a result, it is suggested that unconditional trust in depth information may be adversely affected in facial expression recognition process through structured-light type RGB-D camera.

MnO2 based sandwich structure electrode for supercapacitor with large voltage window and high mass loading

The need for developing energy storage devices with high energy and power densities has motivated tremendous effort in the research of supercapacitors. Major challenges still exist in improving the working voltage window and specific capacitance of the devices. Here, we report a systematic effort in achieving remarkable supercapacitor performance. Firstly, a flexible CNT film/double side carbon tape/CNT film@MnO2 (CDC@MnO2) positive electrode with a large voltage window of 0–1.2 V was fabricated via a facial one-step water bath process. The large interfacial area created by the CDC sandwich structure enabled a high MnO2 mass loading up to 6.6 mg cm−2, resulting in a high area capacitance of 1.1 F cm−2 at a current density of 1 mA cm−2. Secondly, inspired by the superior electrochemical performance of the CDC@MnO2 positive electrode, a CDC@Fe2O3 film with area capacitance up to 339.1 mF cm−2 was fabricated as the negative electrode. Thirdly, a flexible asymmetric supercapacitor was successfully assembled which possesses a large voltage window of 0–2.1 V, a high volume capacitance of 6.8 F cm−3, and a high energy density of 4.1 mWh cm−3 at the power density of 22.3 mW cm−3.

Basic analysis of facial ageing: The relationship between the superficial musculoaponeurotic system and age.

The superficial musculoaponeurotic system (SMAS) is an anatomical structure involved in the facial ageing process. We aimed to evaluate the SMAS laxity using multi-detector row computed tomography (MDCT) as a diagnostic tool, and to analyse the relationship between SMAS laxity and age. Fifty-seven female subjects (aged 21-57years) were enrolled in the study. The subjects were divided into two age groups: one below the mean age (Group Y, 30 subjects) and one over it (Group O, 27 subjects). The Posture Change (PC)-induced SMAS Laxity Index was measured using reconstructed CT images, and the relationship between the PC-induced SMAS Laxity Index and age was analysed. The PC-induced SMAS Laxity Index was significantly larger in Group O than in Group Y. As well, a strong and significant positive correlation was detected between the PC-induced SMAS Laxity Index and age (r=0.72; P<0.001). The use of MDCT provides insight into the detailed changes associated with ageing that take place within the cheeks. This study objectively demonstrated that SMAS laxity and age are factors associated with facial ageing, as the SMAS laxity increased with age. Finally, the imaging features confirmed the dermatological and aesthetic knowledge gained from plastic surgery regarding the loss of the SMAS supporting force due to facial ageing.

Prussian blue coupling with zinc oxide as a protective layer: an efficient cathode for high-rate sodium-ion batteries

Prussian blue coupled with zinc oxide has been synthesized via a facial heat treatment process. As a cathode for sodium ion batteries, the PB coupled with ZnO delivers an excellent rate performance, retaining 86.2 mA h g-1 at 10 A g-1 and a high reversible capacity of 89.9 mA h g-1 at 0.2 A g-1 after 500 cycles.

Real Time Face Recognition based on Convolution Neural Network

: Face recognition is an active research area with many successful traditional and deep learning methods. In our research, we are introducing a Real Time Face Recognition based on Convolution Neural Network (CNN) method for face recognition and to maintain a high accuracy which is running in real time. Face represents multidimensional, complex, meaningful visualization and developing a real time face recognition computational model for face recognition is not easy. In present time, real time face recognition is a challenging problem. The main challenge of face recognition is that how to improve the image recognition performance of the system when it is affected by the variability of non-linear effects. In this paper, 3-layer CNN architecture is proposed for solving the face recognition problem, CNN gives a solution which is capable of solving the facial images related problems that contains varying illumination, poses, occlusions and facial expressions. The test on 115 subject of Essex University database achieve an accuracy of 98.5% which is similar range of performance as the best result of previous works. Meaningfully, our system of real time face recognition based on CNN completes the facial recognition process in less than 0.019 seconds.

Face Reconstruction Using Hybrid PCA, LDP and SVM Machine Learning

This paper aims to develop a platform that allows face features to be extracted faster using multiple algorithms for looking up people in a large database. We will be presenting an enhanced technique for human face recognition where we will be using an image-based approach (process of using two-dimensional images to create three-dimensional models) towards artificial intelligence by extracting features from face images by using Principle Component Analysis, Local Directional Pattern and SVM Machine Learning. Up until now, studies focusing on face recognition rely on the fusion of PCA (Principle Component Analysis) and LBP (Local Binary Pattern) for feature extraction, PCA and LBP were used for global feature extraction of the whole image and the features of the mouth area separately. Results show that this method was susceptible to random noise and resulted in a performance rate of 89.64% [1]. Also, recent studies have shown the fusion of PCA (Principle Component Analysis) and LDP (Local Directional Pattern) for feature extraction [2]. First, PCA is adopted to extract global features of facial images, then LDP operator is used to extract local texture features of eyes and mouth area and these areas are calculated by comparing the relative edge response value of a pixel in different directions. This fusion resulted in a performance rate of 91.61%. The results of PCA and LDP method show that it is more effective than adopting the fusion of PCA and LBP. It’s more robust to noise and improves the rate of facial recognition. However, both methods still suffer from changes in illumination, pose changes, random noise, and aging. In this paper, we propose using a set of trained images to make the facial recognition process faster and provide more accurate results.