Feasibility, Tolerability, Safety and Efficacy of a Pantothenic Acid Based Dietary Supplement in Subjects with Mild to Moderate Facial Acne Blemishes

Objective: It has been suggested that pantothenic acid may have antibacterial and skin softening activity. The aim of this study was to explore the feasibility, tolerability, safety and preliminary efficacy of oral administration of a dietary supplement containing pantothenic acid in healthy human males and females with mild to moderate facial acne vulgaris. Methods: An open-label, single arm study of healthy adults who had been previously diagnosed with mild to moderate acne vulgaris was performed. Subjects were asked to take the study agent, a dietary supplement containing pantothenic acid, for eight weeks. The primary endpoint of the study was to assess the feasibility of oral administration of the study agent in subjects over an eight week period. Safety and tolerability were measured utilizing the assessment of adverse events by the National Cancer Institute’s Common Criteria for Adverse Event Reporting. Secondary endpoints measuring the efficacy of an oral panthothetic acid dietary supplement for the treatment of mild to moderate facial acne utilized changes in the extent of global facial skin blemishes, assessment of quality of life utilizing the Dermatology Life Quality Index (DLQI) and analysis of questions about the subject's beliefs and attitudes towards skin care and lifestyle. Results: Eleven subjects were enrolled and ten completed the study (90.9%). There were no reported adverse events. Of the 10 evaluable subjects, the average age (mean ± SD) was 31.8 ± 8. Analysis of the global number of skin blemishes demonstrated a significant mean reduction in lesion count following the use of the study agent at week 8 (endpoint) (11.18 ± 6.38, p = 0.02) compared to the average number of baseline blemishes (20.45 ± 10.44). DLQI scores were significantly lower at week 8 vs. baseline (p = 0.0194). Conclusions: The results from this study indicated that the administration of a pantothenic based dietary supplement in healthy human adults with mild to moderate acne vulgaris is feasible, safe and well tolerated. Secondary analysis shows that administration of the study agent significantly reduced global facial blemishes. Further randomized, placebo-controlled trials are warranted.

Tamanu Oil in Acne Management: Potential Anti-Inflammatory and Wound-Healing Properties for Scar Reduction

Tamanu oil, derived from the nuts of Calophyllum inophyllum, has gained increasing attention for its potential in acne management due to its purported anti-inflammatory and wound-healing properties. This analysis evaluates the efficacy of tamanu oil in acne treatment with a specific focus on its impact on inflammation and scar reduction. The novelty of this research lies in its comprehensive analysis of tamanu oil’s dual mechanism of action: reducing acne-related inflammation and promoting the healing of acne scars. Clinical trials and laboratory analyses were conducted to assess the oil’s effectiveness in diminishing erythema, swelling, and post-acne scarring compared to conventional treatments. Preliminary findings demonstrate that tamanu oil significantly reduces inflammation and accelerates wound healing, potentially offering a promising adjunct or alternative to standard acne therapies. Future research should aim to optimize formulation and application protocols, long-term effects, and comparative therapeutic efficacy with other anti-inflammatory agents. Tamanu oil offers a novel and effective approach to acne management, with potential advantages that go beyond inflammation reduction to include enhanced scar reduction, making it a subject that warrants further investigation.

Automatic Facial Spots and Acnes Detection System

Recently medical cosmetic has attracted significant business opportunity. Micro cosmetic surgery usually involves invasive cosmetic procedures such as non-ablative laser procedure for skin rejuvenation. However, to select an appropriate treatment for skin relies on accurate preoperative evaluations. In this paper, an automatic facial skin defects detection and recognition method is proposed. The system first locates the facial region from the input image. Then, the shapes of faces were recognized using a contour descriptor. The facial features are extracted to define regions of interest and an image segment method is used to extract potential defect. A support-vector-machine-based classifier is then used to classify the potential defects into spots, acnes and normal skin. Experimental results demonstrate effectiveness of the proposed method.

A Robust Method of Bipolar Mental Illness Detection from Facial Micro Expressions Using Machine Learning Methods

Bipolar disorder is a serious mental condition that may be caused by any kind of stress or emotional upset experienced by the patient.It affects a large percentage of people globally,who fluctuate between depression and mania,or vice versa.A pleasant or unpleasant mood is more than a reflection of a state of mind.Normally,it is a difficult task to analyze through physical examination due to a large patient-psychiatrist ratio,so automated procedures are the best options to diagnose and verify the severity of bipolar.In this research work,facial microexpressions have been used for bipolar detection using the proposed Convolutional Neural Network(CNN)-based model.Facial Action Coding System(FACS)is used to extract micro-expressions called Action Units(AUs)connected with sad,happy,and angry emotions.Experiments have been conducted on a dataset collected from Bahawal Victoria Hospital,Bahawalpur,Pakistan,Using the Patient Health Questionnaire-15(PHQ-15)to infer a patient’s mental state.The experimental results showed a validation accuracy of 98.99%for the proposed CNN modelwhile classification through extracted featuresUsing SupportVectorMachines(SVM),K-NearestNeighbour(KNN),and Decision Tree(DT)obtained 99.9%,98.7%,and 98.9%accuracy,respectively.Overall,the outcomes demonstrated the stated method’s superiority over the current best practices.

Pulse rate estimation based on facial videos:an evaluation and optimization of the classical methods using both self-constructed and public datasets

Pulse rate is one of the important characteristics of traditional Chinese medicine pulse diagnosis,and it is of great significance for determining the nature of cold and heat in diseases.The prediction of pulse rate based on facial video is an exciting research field for getting palpation information by observation diagnosis.However,most studies focus on optimizing the algorithm based on a small sample of participants without systematically investigating multiple influencing factors.A total of 209 participants and 2,435 facial videos,based on our self-constructed Multi-Scene Sign Dataset and the public datasets,were used to perform a multi-level and multi-factor comprehensive comparison.The effects of different datasets,blood volume pulse signal extraction algorithms,region of interests,time windows,color spaces,pulse rate calculation methods,and video recording scenes were analyzed.Furthermore,we proposed a blood volume pulse signal quality optimization strategy based on the inverse Fourier transform and an improvement strategy for pulse rate estimation based on signal-to-noise ratio threshold sliding.We found that the effects of video estimation of pulse rate in the Multi-Scene Sign Dataset and Pulse Rate Detection Dataset were better than in other datasets.Compared with Fast independent component analysis and Single Channel algorithms,chrominance-based method and plane-orthogonal-to-skin algorithms have a more vital anti-interference ability and higher robustness.The performances of the five-organs fusion area and the full-face area were better than that of single sub-regions,and the fewer motion artifacts and better lighting can improve the precision of pulse rate estimation.

Faster Region Convolutional Neural Network(FRCNN)Based Facial Emotion Recognition

Facial emotion recognition(FER)has become a focal point of research due to its widespread applications,ranging from human-computer interaction to affective computing.While traditional FER techniques have relied on handcrafted features and classification models trained on image or video datasets,recent strides in artificial intelligence and deep learning(DL)have ushered in more sophisticated approaches.The research aims to develop a FER system using a Faster Region Convolutional Neural Network(FRCNN)and design a specialized FRCNN architecture tailored for facial emotion recognition,leveraging its ability to capture spatial hierarchies within localized regions of facial features.The proposed work enhances the accuracy and efficiency of facial emotion recognition.The proposed work comprises twomajor key components:Inception V3-based feature extraction and FRCNN-based emotion categorization.Extensive experimentation on Kaggle datasets validates the effectiveness of the proposed strategy,showcasing the FRCNN approach’s resilience and accuracy in identifying and categorizing facial expressions.The model’s overall performance metrics are compelling,with an accuracy of 98.4%,precision of 97.2%,and recall of 96.31%.This work introduces a perceptive deep learning-based FER method,contributing to the evolving landscape of emotion recognition technologies.The high accuracy and resilience demonstrated by the FRCNN approach underscore its potential for real-world applications.This research advances the field of FER and presents a compelling case for the practicality and efficacy of deep learning models in automating the understanding of facial emotions.

Re-evaluating the necessity of routine laboratory monitoring during isotretinoin therapy for acne

In this letter,we discuss the topic of necessity of routine laboratory monitoring during isotretinoin treatment for acne.According to Park and colleagues,it is advisable to monitor the levels of triglycerides,alanine aminotransferase,and aspartate aminotransferase every 5 to 6 months.Additionally,the levels of total cholesterol and low-density lipoprotein should be checked within the first two months of treatment.Isotretinoin is a commonly prescribed agent mainly used to treat acne.Despite its high effectiveness,it necessitates regular monitoring of laboratory parameters due to its side effect profile.Currently,there remains a lack of consensus on the appropriate frequency for monitoring these parameters during treatment with isotretinoin.This letter will provide insight into this complex and controversial topic.Based on existing literature,we concluded that the incidence of changes in lipid and liver aminotransferase levels during isotretinoin treatment for acne was low and likely clinically insignificant.For generally healthy people,we recommend testing lipid and liver profiles once at baseline and a second time at the peak dosage.However,frequent testing might still be beneficial in certain populations of patients.

Ocular surface changes in moderate-to-severe acne vulgaris

AIM:To investigate ocular surface disorders and tear function changes in patients with acne vulgaris and explore the potential relationship between acne vulgaris and dry eye.METHODS:This cross-sectional study included right eyes of 53 patients with acne vulgaris and 54 healthy controls.The participants completed the Ocular Surface Disease Index(OSDI)questionnaire.The following ocular surface-related parameters were measured:tear meniscus height(TMH),noninvasive tear breakup time(NIBUT),Schirmer I test(SIT),lipid layer thickness(LLT)score of the tear film,meibum score,meibomian gland orifice obstruction score,the ratio of meibomian gland loss,conjunctival hyperemia score,and corneal fluorescein staining(CFS)score.RESULTS:The stability of the tear film decreased in acne vulgaris patients.In the acne group,the TMH and NIBUT were lower,whereas the OSDI,meibum score,meibomian gland orifice obstruction score,ratio of meibomian gland loss,and conjunctival hyperemia score were higher compared with controls(P<0.05).There were no significant differences in the CFS score,SIT,or LLT score between the groups(P>0.05).In two dry eye groups,the TMH,NIBUT,and LLT score were lower in the acne with dry eye(acne-DE)group,and the meibum score,meibomian gland orifice obstruction score,ratio of meibomian gland loss and conjunctival hyperemia score in the acne-DE group were higher(P<0.05).There were no significant differences between OSDI,SIT,and CFS score(P>0.05).CONCLUSION:Patients with moderate-to-severe acne vulgaris are more likely to experience dry eye than those without acne vulgaris.Reduced tear film stability and meibomian gland structure dysfunction are more pronounced in patients with moderate-to-severe acne and dry eye.

Evaluation of Ear and Facial Indices of Ibibio and Efik Female Children of Akwa Ibom and Cross River States, Nigeria

Background: The ear and face are indispensable and distinctive features for hearing and identification. Objectives: This study was designed to generate anthropometric data of the ear and facial indices of females of Efik and Ibibio children in Cross River and Akwa Ibom States, show morphological and aesthetic differences and ethnicity. Methods: A total of 600 female children (300 Efiks and 300 Ibibios) aged 2 to 10 years that met the inclusion criteria were chosen from selected primary schools in Calabar Municipality, Calabar South of Cross River State and from Uyo, Itu of Akwa Ibom State, Nigeria. Standardized measurements of face length, face width, ear length, and ear width were taken with a spreading caliper;the facial (proscopic) and ear (auricular) indices were determined. Results: Efik subjects presented a mean face length of 8.36 ± 0.06 cm, face width of 11.04 ± 0.04 cm, ear length of 4.92 ± 0.02 cm, and ear width of 3.06 ± 0.01 cm. Ibibio subjects had mean values for face length, face width, ear length, and ear width as 8.17 ± 0.05 cm, 10.75 ± 0.05 cm, 4.77 ± 0.03 cm, and 2.94 ± 0.02 cm respectively. The mean facial index and ear index for Efik subjects were 75.68 ± 0.31 and 62.16 ± 0.27 respectively;while the mean facial and ear indices for Ibibio subjects were 74.79 ± 0.36 and 61.80 ± 0.34 respectively. Statistical analysis demonstrated significant differences in face length, ear length, ear width and facial index, with the Efik subjects having higher values than Ibibio subjects (p Conclusion: The results showed hypereuryproscopic face as the prevalent face type among females of both ethnic groups, therefore can be of importance in sex, ethnic, and racial differentiation, and in clinical practice, aesthetics and forensic medicine.

Global-local combined features to detect pain intensity from facial expression images with attention mechanism

The estimation of pain intensity is critical for medical diagnosis and treatment of patients.With the development of image monitoring technology and artificial intelligence,automatic pain assessment based on facial expression and behavioral analysis shows a potential value in clinical applications.This paper reports a framework of convolutional neural network with global and local attention mechanism(GLA-CNN)for the effective detection of pain intensity at four-level thresholds using facial expression images.GLA-CNN includes two modules,namely global attention network(GANet)and local attention network(LANet).LANet is responsible for extracting representative local patch features of faces,while GANet extracts whole facial features to compensate for the ignored correlative features between patches.In the end,the global correlational and local subtle features are fused for the final estimation of pain intensity.Experiments under the UNBC-McMaster Shoulder Pain database demonstrate that GLA-CNN outperforms other state-of-the-art methods.Additionally,a visualization analysis is conducted to present the feature map of GLA-CNN,intuitively showing that it can extract not only local pain features but also global correlative facial ones.Our study demonstrates that pain assessment based on facial expression is a non-invasive and feasible method,and can be employed as an auxiliary pain assessment tool in clinical practice.

Epidemiological and Computed Tomography Aspects of Facial Trauma at Kira Hospital in Bujumbura

Background: Maxillofacial trauma affects young adults more. The injury assessment is difficult to establish in low-income countries because of the imaging means, particularly the scanner, which is poorly available and less financially accessible. The aim of this study is to describe the epidemiological profile and the various tomodensitometric aspects of traumatic lesions of the face in patients received in the Radiology department of Kira Hospital. Patients and methods: This is a descriptive retrospective study involving 104 patients of all ages over a period of 2 years from December 2018 to November 2019 in the medical imaging department of KIRA HOSPITAL. We included in our study any patient having undergone a CT scan of the head and presenting at least one lesion of the facial mass, whether associated with other cranioencephalic lesions. Results: Among the 384 patients received for head trauma, 104 patients (27.1% of cases) presented facial damage. The average age of our patients was 32.02 years with extremes of 8 months and 79 years. In our study, 87 of the patients (83.6%) were male. The road accident was the circumstance in which facial trauma occurred in 79 patients (76% of cases). These injuries were accompanied by at least one bone fracture in 97 patients (93.3%). Patients with fractures of more than 3 facial bones accounted for 40.2% of cases and those with fractures of 2 to 3 bones accounted for 44.6% of cases. The midface was the site of the fracture in 85 patients (87.6% of cases). Orbital wall fractures were noted in 57 patients (58.8% of cases) and the jawbone was the site of a fracture in 50 patients (51.5% of cases). In the vault, the fractures involved the extra-facial frontal bone (36.1% of cases) and temporal bone (18.6% of cases). Cerebral contusion was noted in 41.2% of patients and pneumoencephaly in 15.5% of patients. Extradural hematoma was present in 16 patients and subdural hematoma affected 13 patients. Conclusion: Computed tomography is a diagnostic tool of choice in facial trauma patients. Most of these young patients present with multiple fractures localizing to the mid-level of the face with concomitant involvement of the brain.

Re-Distributing Facial Features for Engagement Prediction with ModernTCN

Automatically detecting learners’engagement levels helps to develop more effective online teaching and assessment programs,allowing teachers to provide timely feedback and make personalized adjustments based on students’needs to enhance teaching effectiveness.Traditional approaches mainly rely on single-frame multimodal facial spatial information,neglecting temporal emotional and behavioural features,with accuracy affected by significant pose variations.Additionally,convolutional padding can erode feature maps,affecting feature extraction’s representational capacity.To address these issues,we propose a hybrid neural network architecture,the redistributing facial features and temporal convolutional network(RefEIP).This network consists of three key components:first,utilizing the spatial attention mechanism large kernel attention(LKA)to automatically capture local patches and mitigate the effects of pose variations;second,employing the feature organization and weight distribution(FOWD)module to redistribute feature weights and eliminate the impact of white features and enhancing representation in facial feature maps.Finally,we analyse the temporal changes in video frames through the modern temporal convolutional network(ModernTCN)module to detect engagement levels.We constructed a near-infrared engagement video dataset(NEVD)to better validate the efficiency of the RefEIP network.Through extensive experiments and in-depth studies,we evaluated these methods on the NEVD and the Database for Affect in Situations of Elicitation(DAiSEE),achieving an accuracy of 90.8%on NEVD and 61.2%on DAiSEE in the fourclass classification task,indicating significant advantages in addressing engagement video analysis problems.

Research on the Nursing Effect of Glycolipids on Acne Skin

Glycolipids are lipid compounds,which are a type of amphiphilic molecules containing glycosyl ligands.This experiment studied the efficacy of glycolipids on acne skin care from the aspects of antibacterial,anti-inflammatory,anti-allergic,oil-control,soothing and repair.Research results show that glycolipids have excellent antibacterial properties against P.acnes;when the dosage of glycolipids reaches 10μg/mL,the inhibition rate of glycolipids on lipid synthesis in SZ95 cells can reach 20%;glycolipids can induce LPS induction RAW264.7 cells have the inhibitory effect on the release of inflammatory factors IL-6 and NO;when the glycolipids concentration is 15 mg/mL,the inhibition rate of glycolipids on hyaluronidase reaches 45.8%;when the glycolipids concentration is 25μg/mL,the inhibition rate on calcium ion concentration reaches 45.3%;glycolipids have a significant promoting effect on wound healing.Furthermore,human efficacy evaluation shows that glycolipids products have comprehensive care effects on acne skin.This study will help further promote the application of glycolipids in cosmetic products,especially in skin care products for acne skin.

Facial Image-Based Autism Detection:A Comparative Study of Deep Neural Network Classifiers

Autism Spectrum Disorder(ASD)is a neurodevelopmental condition characterized by significant challenges in social interaction,communication,and repetitive behaviors.Timely and precise ASD detection is crucial,particularly in regions with limited diagnostic resources like Pakistan.This study aims to conduct an extensive comparative analysis of various machine learning classifiers for ASD detection using facial images to identify an accurate and cost-effective solution tailored to the local context.The research involves experimentation with VGG16 and MobileNet models,exploring different batch sizes,optimizers,and learning rate schedulers.In addition,the“Orange”machine learning tool is employed to evaluate classifier performance and automated image processing capabilities are utilized within the tool.The findings unequivocally establish VGG16 as the most effective classifier with a 5-fold cross-validation approach.Specifically,VGG16,with a batch size of 2 and the Adam optimizer,trained for 100 epochs,achieves a remarkable validation accuracy of 99% and a testing accuracy of 87%.Furthermore,the model achieves an F1 score of 88%,precision of 85%,and recall of 90% on test images.To validate the practical applicability of the VGG16 model with 5-fold cross-validation,the study conducts further testing on a dataset sourced fromautism centers in Pakistan,resulting in an accuracy rate of 85%.This reaffirms the model’s suitability for real-world ASD detection.This research offers valuable insights into classifier performance,emphasizing the potential of machine learning to deliver precise and accessible ASD diagnoses via facial image analysis.

Balancing Dermatological and Gynecological Considerations: Evaluating the Necessity of Pelvic Exams in OCP Prescriptions for Acne Management

Routine pelvic examinations in women prescribed oral contraceptive pills (OCPs) for acne management are scrutinized to assess their impact on dermatological outcomes versus gynecological health. A synthesis of clinical trials, patient surveys, and medical guidelines reveals that these routine exams do not significantly enhance the effectiveness of acne treatment with OCPs but are linked to increased patient discomfort and false-positive results. Evidence suggests that routine pelvic examinations do not significantly impact the effectiveness of acne management with OCPs but are associated with increased patient discomfort and higher rates of false-positive results. The analysis indicates that a more personalized approach, focusing on selective pelvic examinations based on individual risk factors and clinical symptoms, may offer a more practical and patient-centered alternative. The review advocates for a reexamination of existing guidelines to better align with a model of individualized care, emphasizing the need for further research to optimize best practices at the intersection of dermatological and gynecological care. Adopting a personalized approach to pelvic examinations could substantially improve patient care by minimizing unnecessary interventions and discomfort while maintaining the efficacy of acne treatment with oral contraceptive pills.

Recurrent herpes infection showing a new facial phenotype:A case report

BACKGROUND Facial herpes is a common form of the herpes simplex virus-1 infection and usually presents as vesicles near the mouth,nose,and periocular sites.In contrast,we observed a new facial symptom of herpes on the entire face without vesicles.CASE SUMMARY A 33-year-old woman with a history of varicella infection and shingles since an early age presented with sarcoidosis of the entire face and neuralgia without oral lesions.The patient was prescribed antiviral treatment with valacyclovir and acyclovir cream.One day after drug administration,facial skin lesions and neurological pain improved.Herpes simplex without oral blisters can easily be misdiagnosed as pimples upon visual examination in an outpatient clinic.CONCLUSION As acute herpes simplex is accompanied by neuralgia,prompt diagnosis and prescription are necessary,considering the pathological history and health conditions.

Peripheral Facial Paralysis in People Living with Human Immunodeficiency Virus (HIV)

Introduction: Peripheral facial palsy (PFP) is a frequent reason for ENT consultations. It is a common complication of human immunodeficiency virus (HIV) infection. The aim of this study was to describe the diagnostic and therapeutic aspects and to establish the correlation between PFP and HIV in our context. Patients and Method: This was a retrospective descriptive study conducted in the ENT and CFS department of the HIAOBO, covering the medical records of patients hospitalized for taking a PFP on HIV terrain from January 1, 2016 to December 31, 2020. Results: The study involved 17 patients, 10 men (59%) and 7 women (41%), a sex ratio of 1.4. The average age was 39 years with the extremes of 11 and 69 years. Shopkeepers reported 9 cases (53%). The reason for consultation was facial asymmetry in 11 cases (100%). The delay in consultation during the first week was 82.4%. Clinical signs were unilateral facial asymmetry, the opening of the palpebral fissure and lacrimation. All patients received medical treatment for PFP and HIV. Evolution was favorable, with complete recovery and no sequelae in 82.4% of cases. Surgery was performed in one case. Conclusion: PFPs are common in HIV infection. Diagnosis is clinical and management is multidisciplinary. Progression depends on the length of time taken to treat the disease.

Sensory Evaluation of Freeze-Dried Facial Mask and Analysis of User Profile

To thoroughly understand market opportunity of freeze-dried facial mask and deeply get insight of consumers’usage behavior and needs,evaluate sensory feelings of 10 screened commercial freeze-dried facial mask products,group test products according to the differences of sensory attributions via Principal Component Analysis(PCA)and Agglomerative Hierarchical Clustering(AHC),pick up the representative products.Freeze-dried facial mask users evaluate satisfaction degree of picked up products and participate survey of usage behavior/cognition.Analyze consumer data by AHC to get consumer segmentations and their profile.The test results show that,sensory data and consumer data,which is from consumers test of screened representative products by performing PCA and AHC on sensory data,can be verified mutually.It is helpful to understand the needs of consumer segmentations and reason to buy by combining sensory data and consumer test.

Inhibition of Propionibacterium acnes by refined bamboo vinegar and preparation of the slow-release system with bamboo charcoal as the carrier

Background:Acne vulgaris is one of the most common skin diseases that can significantly impact a considerable proportion of individuals over their lifetime.Objective:This study focuses on the exploration of the application potential of bamboo vinegar in cosmetics.Materials and Methods:The stock solution of bamboo vinegar is subjected to reduced-pressure distillation at different temperatures to obtain refined bamboo vinegar.Then,inhibition of Propionibacterium acnes(P.acnes)by refined bamboo vinegar is observed.Moreover,the refined bamboo vinegar is adsorbed and released with activated bamboo charcoal as the carrier.In all,this study aims to probe into the mechanism of the controlledrelease system of bamboo vinegar.Results:The results shows that the harmful substances(tar)in bamboo vinegar distilled at 70℃decreased by 94.44%,which is a more notable decrease compared with that in the stock solution.The total organic acid content in bamboo vinegar after reduced-pressure distillation is 11.840%,reaching the national standard for refined bamboo vinegar(GB/T 31734–2015).Additionally,the minimum inhibitory concentration of refined bamboo vinegar against P.acnes using the punch method is 7.90 mg/mL.This indicates that refined bamboo vinegar has the potential as a prospective raw material for formulations in anti-acne cosmetic products.Furthermore,the release rate of bamboo charcoal/bamboo vinegar in water for 15 min reaches 70.57%,which then slows down to a plateau.The slow-release behavior is agreed with the Ritger-Peppas model and is beneficial to relieve the irritation of bamboo vinegar to the skin and lengthen its bacteriostatic duration.Conclusion:The foregoing conclusions can serve as the theoretical foundation for the application of bamboo vinegar in anti-acne cosmetics.

Artificially Generated Facial Images for Gender Classification Using Deep Learning

Given the current expansion of the computer visionfield,several appli-cations that rely on extracting biometric information like facial gender for access control,security or marketing purposes are becoming more common.A typical gender classifier requires many training samples to learn as many distinguishable features as possible.However,collecting facial images from individuals is usually a sensitive task,and it might violate either an individual's privacy or a specific data privacy law.In order to bridge the gap between privacy and the need for many facial images for deep learning training,an artificially generated dataset of facial images is proposed.We acquire a pre-trained Style-Generative Adversar-ial Networks(StyleGAN)generator and use it to create a dataset of facial images.We label the images according to the observed gender using a set of criteria that differentiate the facial features of males and females apart.We use this manually-labelled dataset to train three facial gender classifiers,a custom-designed network,and two pre-trained networks based on the Visual Geometry Group designs(VGG16)and(VGG19).We cross-validate these three classifiers on two separate datasets containing labelled images of actual subjects.For testing,we use the UTKFace and the Kaggle gender dataset.Our experimental results suggest that using a set of artificial images for training produces a comparable performance with accuracies similar to existing state-of-the-art methods,which uses actual images of individuals.The average classification accuracy of each classifier is between 94%and 95%,which is similar to existing proposed methods.