Presently, the policies and support services related to the development and utilization of human resources for the elderly in China are not perfect, and the increasing aging situation affects the ...labor supply in the social market. In this paper, under the concept related to active aging, the active aging index is proposed, and the current situation is analyzed by studying active aging based on the human capital perspective, the labor supply profile of the elderly in China, and the impact of active aging on labor supply. With the advancement of population aging, the employed population of the elderly grows further, and the employment rate of the elderly population aged 60 and above in China is about 17%. The employment rate of the male elderly population is significantly higher than that of the female elderly population, with the employment rate of 60-year-old male elderly being about 32 percentage points higher than that of females of the same age. Among the employed older adults, nearly 85% or more have an educational attainment of only junior high school or below. Therefore, in the period of rapid population aging in China, it is of great practical significance to study active aging to optimize the structure of the elderly, achieve sustainable economic growth and build a harmonious society.
China has been the leading source of foreign students pursuing tertiary degrees in other countries. The incoming Chinese students in Hungary comprised the third highest number of foreign students in ...the country in 2016. This paper examines the Chinese students’ motivations for choosing the Hungarian education system, with the purpose of gaining a more comprehensive and accurate understanding of the flow of Chinese students to Hungary. In terms of methodology, this paper uses the systematic review protocol by retrieving relevant literatures. The author developed the main factors influencing Chinese students’ choice of the Hungarian education system, which are social class inequality and the modernization process from the Chinese perspective; meanwhile, the state policy perceptions, the institution, and community influence are encouraging from the Hungarian views. Moreover, individual motivation and the challenges of “invisible academic performance in the classroom” are explored with regard to Chinese students in Hungary. This article practically contributes to policy implications for Hungarian higher education in the international environment and inspires Chinese students who are from the lower socioeconomic classes.
The impact of the COVID-19 pandemic on the mental health of students in locked-down colleges remains obscure. This study aimed to explore influencing factors for the psychological impact of COVID-19 ...on Wuhan college students, post-traumatic stress symptoms in particular, so as to inform evidence-based strategy development to ameliorate such adverse impacts. An online survey was conducted from 26 to 29 April 2020, and 4355 students enrolled in Wuhan universities and colleges participated. Post-Traumatic Stress Disorder via the Impact of Event-Scale-Revised was assessed. COVID-19 disproportionately affected older male Master's and doctoral students living in Wuhan. The overall prevalence of PTSD was 16.3%. The three-level socio-interpersonal model of PTSD was empirically validated, and college students faced individual level risks such as infection with COVID-19, close relationship level risks such as family support (infection suspicion of family members, the loss of loved ones, and the family income decrease) and online course difficulties (little interaction, disturbing learning environment, and difficulty in adaption), and distant level risks such as excessive collection of personal information, estrangement of family relatives, and harassment and insult from strangers. The findings suggest the severity of the psychological impact of COVID-19. Mental health services reducing PTSD should be provided. Students who have lost loved ones and suffered family financial loss should be given particular care.
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•Among different water quality components, TC degradation by UV/NH2Cl process was most greatly affected by addition of HCO3−.•Reactive chlorine species played a major role on TC ...degradation by UV/NH2Cl process in pH range of 6.0–8.0.•TC degradation in UV/NH2Cl process involved the hydroxylation, demethylation, dehydration and chlorine substitution.•Compared with chloramination, UV/NH2Cl treatment increased the NDMA formation.•The observed acute toxicity in chloramination and UV/NH2Cl oxidation was higher than UV photolysis.
The combination of UV and monochloramine (UV/NH2Cl) was investigated to eliminate tetracycline (TC) in water. The results indicated that TC degradation by UV/NH2Cl oxidation far exceeded that by UV photolysis and dark chloramination and these processes well fitted pseudo-first-order kinetics. With the increase of NH2Cl dosage, the pseudo-first-order rate constant (kobs) value increased linearly during TC chloramination, while the growth rate of kobs presented a gradual downward trend in UV/NH2Cl process. TC degradation by UV photolysis, dark chloramination and UV/NH2Cl oxidation displayed highly pH-dependent. As solution pH increased from 5.0 to 9.0, the TC removal increased during UV photolysis, while decreased during dark chloramination. For UV/NH2Cl process, the TC degradation showed a decreasing trend with increasing pH from 5.0 to 7.0, but further increasing pH to 9.0 presented an increasing trend. Reactive chlorine species acted as the major contributors to TC degradation in pH range of 6.0–8.0. TC degradation was not apparently affected after the introduction of HA and chloride, but was substantially accelerated in the presence of HCO3−. The proposed degradation pathways involved the hydroxylation, demethylation, dehydration and chlorine substitution processes. Compared with dark chloramination, the N-Nitrosodimethylamine (NDMA) generation was enhanced during TC oxidation by UV/NH2Cl process. The NDMA concentration increased with increasing solution pH from 6.0 to 8.0 and also elevated in the presences of humic acid (HA), nitrite, nitrate and ammonium during TC oxidation by chloramination and UV/NH2Cl. The results of acute toxicity test demonstrated that the toxicity of the reacted solution exhibited similar trends during dark chloramination and UV/NH2Cl treatment and was found to be obviously higher than UV photolysis.
Highlights • The multi-channel fully convolutional networks is designed. • We segment liver tumors from multiphase contrast-enhanced CT images. • We train one network for each phase of CT images and ...fuse their high-layer features together. • This method can make full use of the characteristics of different enhancement phases of CT images. • The results showed our model provided greater accuracy and robustness than previous methods.
In this paper, a reinforcement learning-based sleep scheduling for coverage (RLSSC) algorithm is proposed for sustainable time-slotted operation in rechargeable sensor networks. RLSSC is a two-stage ...sleep scheduling algorithm. It includes the precedence operator-based group formation algorithm and the Q learning-based active node selection algorithm. First, a precedence operator is designed in the group formation algorithm to ensure the desired area coverage. All the nodes are formed into groups. Then, Q learning algorithm is expanded into a multi-sensor cooperation Q learning group model. The learning and action selection strategy are designed in a group to direct nodes in collaborative learning of working modes selection while adapting to the dynamic environment. Through the role changes of active nodes, the algorithm accomplishes the entire team learning of sleep scheduling while scheduling others into sleep modes. Experiments of RLSSC on a solar-powered wireless sensor network for area surveillance tasks are presented. Compared with LEACH and a random algorithm, the results show that RLSSC can effectively adjust the working modes of nodes in a group by perceiving the environment. In addition, it achieves the energy consumption balance between nodes so as to prolong the network lifetime while maintaining the desired coverage.
To effectively detect motion sickness induced by virtual reality environments, we developed a classification model specifically designed for visually induced motion sickness, employing a phase-locked ...value (PLV) functional connectivity matrix and a CNN-LSTM architecture. This model addresses the shortcomings of traditional machine learning algorithms, particularly their limited capability in handling nonlinear data. We constructed PLV-based functional connectivity matrices and network topology maps across six different frequency bands using EEG data from 25 participants. Our analysis indicated that visually induced motion sickness significantly alters the synchronization patterns in the EEG, especially affecting the frontal and temporal lobes. The functional connectivity matrix served as the input for our CNN-LSTM model, which was used to classify states of visually induced motion sickness. The model demonstrated superior performance over other methods, achieving the highest classification accuracy in the gamma frequency band. Specifically, it reached a maximum average accuracy of 99.56% in binary classification and 86.94% in ternary classification. These results underscore the model’s enhanced classification effectiveness and stability, making it a valuable tool for aiding in the diagnosis of motion sickness.
Abstract Nowadays, what captures consumers' primary attention is how to purchase electric vehicles with long range and desirable price. Lightweight construction stands as one of the most effective ...approaches for prolonging range and lowering costs. As a consequence, it is particularly imperative to undertake lightweight design optimization for the battery bracket of new energy vehicles by applying 3D printing technology. To actualize this goal, Rhino software was initially employed for 3D modeling to design the battery bracket system for a pure electric vehicle in China. Subsequently, topology optimization design of the battery bracket was carried out by adopting Altair Inspire software. Last but not least, manufacturing and assembly inspection were completed using a 3D printer. The results show that the maximum displacement of the battery lower tray bracket after topology optimization is 3.20 mm, which is slightly higher than before, but still relatively small. The maximum Mises equivalent stress rose to 240.7 MPa post-optimization, but brought about a uniform stress distribution at the bottom of the bracket. In comparison, the minimum factor of safety met design requirements at 1. The mass was lessened to 0.348 kg, representing a 49.2% decrease in comparison with pre-optimization levels. The 3D-printed bracket was fabricated by employing a 3D printer, thereby achieving the aforementioned mass abatement. The battery pack parts exhibited a bright surface with low roughness and no discernible warping or deformation defects. As revealed by the assembly results, the components of the battery pack bracket are tightly coordinated with each other, with no evident assembly conflicts, revealing that the dimensional accuracy and fit of the completed parts meet production requirements. These findings lay solid groundwork for the mass production of high-performance battery pack brackets.
Mutant KRAS is a known driver oncogene in pancreatic cancer. However, this protein remains an “undruggable” therapeutic target. Inhibiting mutated KRAS expression at the mRNA level is a potentially ...effective strategy. Recently, a novel CRISPR-Cas effector, Cas13a has been reported to specifically knock down mRNA expression under the guidance of a single CRISPR-RNA in mammalian cells. Here we demonstrate that the CRISPR-Cas13a system can be engineered for targeted therapy of mutant KRAS in pancreatic cancer. In initial screening, we show that the bacterial Cas13a protein and crRNA significantly knock down mutant KRAS mRNA expression, identifying a CRISPR-Cas13a system that can induce up to a 94% knockdown efficiency. Introducing a single mismatch into the crRNA-target duplex enabled the CRISPR-Cas13a system to specifically recognize KRAS-G12D mRNA with no detectable effects on wild-type KRAS mRNA. More importantly, CRISPR-Cas13a-mediated KRAS-G12D mRNA knockdown potently induced apoptosis in vitro and elicited marked tumor shrinkage in mice. Our work describes an optimization strategy for the development of a CRISPR-Cas13a system to affect efficient and specific knockdown of the oncogenic mRNA, establishing the CRISPR-Cas13a system as a flexible, targeted therapeutic tool.
•An engineered CRISPR-Cas13a system can specially knock down mutant KRAS mRNA.•The Lw.Cas13a system can induce up to a 94% knockdown efficiency of KRAS-G12D mRNA.•Introducing a mismatch enabled the Lw.Cas13a system to specifically recognize KRAS-G12D.•Cas13a-mediated KRAS-G12D mRNA knockdown induced a dramatic cancer cell apoptosis.•Lw.Cas13a system can be used for the targeted therapy of other oncogenic mutations.
With the development of autonomous driving, augmented reality, and other fields, it is becoming increasingly important for machines to more accurately and comprehensively perceive their surrounding ...environment. LiDAR is one of the most important tools used by machines to obtain information about the surrounding environment. However, because of occlusion, the point cloud data obtained by LiDAR are not the complete shape of the object, and completing the incomplete point cloud shape is of great significance for further data analysis, such as classification and segmentation. In this study, we examined the completion of a 3D point cloud and improved upon the FoldingNet auto-encoder. Specifically, we used the encoder–decoder architecture to design our point cloud completion network. The encoder part uses the transformer module to enhance point cloud feature extraction, and the decoder part changes the 2D lattice used by the A network into a 3D lattice so that the network can better fit the shape of the 3D point cloud. We conducted experiments on point cloud datasets sampled from the ShapeNet car-category CAD models to verify the effectiveness of the various improvements made to the network.
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