As the technology for 3D photography has developed rapidly in recent years, an enormous amount of 3D images has been produced, one of the directions of research for which is face recognition. Improving the accuracy of a number of data is crucial in 3D face recognition problems. Traditional machine learning methods can be used to recognize 3D faces, but the face recognition rate has declined rapidly with the increasing number of 3D images. As a result, classifying large amounts of 3D image data is time-consuming, expensive, and inefficient. The deep learning methods have become the focus of attention in the 3D face recognition research. In our experiment, the end-to-end face recognition system based on 3D face texture is proposed, combining the geometric invariants, histogram of oriented gradients and the fine-tuned residual neural networks. The research shows that when the performance is evaluated by the FRGC-v2 dataset, as the fine-tuned ResNet deep neural network layers are increased, the best Top-1 accuracy is up to 98.26% and the Top-2 accuracy is 99.40%. The framework proposed costs less iterations than traditional methods. The analysis suggests that a large number of 3D face data by the proposed recognition framework could significantly improve recognition decisions in realistic 3D face scenarios.
Gestational diabetes (hyperglycaemia) is an elevated blood sugar level diagnosed during the period of pregnancy and affects the baby's health. Hyperglycaemia has been found within the gestational weeks between 24 and 28, and the foetus has also the possibility of getting out prior to this test frame; it causes excessive birth weight, early birth, low-blood sugar level, respiratory distress syndrome, and type-2 diabetes to the mother. It creates a mandatory situation to identify the hyperglycaemia at least during the pregnancy weeks from 18 to 20. Further, a continuous monitoring of the level of glucose is necessary for the proper delivery. In this work, a method is introduced for glucose detection at 0.06 mg/mL, assisted by gold nanorod (GNR)-conjugated glucose oxidase (GOx) on interdigitated electrode sensor. In the absence of GNR, GOx shows the limit of glucose detection to be 0.25 mg/mL. Moreover, with GOx-GNR the reactions of all the glucose concentrations have recorded higher levels of the current from the baseline. With the specificity analysis, it was found that the glucose only reacts with GOx-GNR and discriminates other sugars efficiently. This method of detection is useful to diagnose and continuously monitor the glucose level during the pregnancy period.
Microplastic fibers from textiles have been known to significantly contribute to marine microplastic pollution. However, little is known about the microfiber formation and discharge during textile production. In this study, we have quantified microfiber emissions from one large and representative textile factory during different stages, spanning seven different materials, including cotton, polyester, and blended fabrics, to further guide control strategies. Wet-processing steps released up to 25 times more microfibers than home laundering, with dyeing contributing to 95.0% of the total emissions. Microfiber release could be reduced by using white coloring, a lower dyeing temperature, and a shorter dyeing duration. Thinner, denser yarns increased microfiber pollution, whereas using tightly twisted fibers mitigated release. Globally, wet textile processing potentially produced 6.4 kt of microfibers in 2020, with China, India, and the US as significant contributors. The study underlined the environmental impact of textile production and the need for mitigation strategies, particularly in dyeing processes and fiber choice. In addition, no significant difference was observed between the virgin polyesters and the used ones. Replacing virgin fibers with recycled fibers in polyester fabrics, due to their increasing consumption, might offer another potential solution. The findings highlighted the substantial impact of textile production on microfiber released into the environment, and optimization of material selection, knitting technologies, production processing, and recycled materials could be effective mitigation strategies.
OBJECTIVE: Since the publication of the first Asia Pacific Consensus on Colorectal Cancer (CRC) in 2008, there are substantial advancements in the science and experience of implementing CRC screening. The Asia Pacific Working Group aimed to provide an updated set of consensus recommendations.
DESIGN: Members from 14 Asian regions gathered to seek consensus using other national and international guidelines, and recent relevant literature published from 2008 to 2013. A modified Delphi process was adopted to develop the statements.
RESULTS: Age range for CRC screening is defined as 50-75 years. Advancing age, male, family history of CRC, smoking and obesity are confirmed risk factors for CRC and advanced neoplasia. A risk-stratified scoring system is recommended for selecting high-risk patients for colonoscopy. Quantitative faecal immunochemical test (FIT) instead of guaiac-based faecal occult blood test (gFOBT) is preferred for average-risk subjects. Ancillary methods in colonoscopy, with the exception of chromoendoscopy, have not proven to be superior to high-definition white light endoscopy in identifying adenoma. Quality of colonoscopy should be upheld and quality assurance programme should be in place to audit every aspects of CRC screening. Serrated adenoma is recognised as a risk for interval cancer. There is no consensus on the recruitment of trained endoscopy nurses for CRC screening.
CONCLUSIONS: Based on recent data on CRC screening, an updated list of recommendations on CRC screening is prepared. These consensus statements will further enhance the implementation of CRC screening in the Asia Pacific region.
Worldwide, some 240 million people have chronic hepatitis B virus (HBV), with the highest rates of infection in Africa and Asia. Our understanding of the natural history of HBV infection and the potential for therapy of the resultant disease is continuously improving. New data have become available since the previous APASL guidelines for management of HBV infection were published in 2012. The objective of this manuscript is to update the recommendations for the optimal management of chronic HBV infection. The 2015 guidelines were developed by a panel of Asian experts chosen by the APASL. The clinical practice guidelines are based on evidence from existing publications or, if evidence was unavailable, on the experts' personal experience and opinion after deliberations. Manuscripts and abstracts of important meetings published through January 2015 have been evaluated. This guideline covers the full spectrum of care of patients infected with hepatitis B, including new terminology, natural history, screening, vaccination, counseling, diagnosis, assessment of the stage of liver disease, the indications, timing, choice and duration of single or combination of antiviral drugs, screening for HCC, management in special situations like childhood, pregnancy, coinfections, renal impairment and pre- and post-liver transplant, and policy guidelines. However, areas of uncertainty still exist, and clinicians, patients, and public health authorities must therefore continue to make choices on the basis of the evolving evidence. The final clinical practice guidelines and recommendations are presented here, along with the relevant background information.
In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.