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The construction of an energy distribution network can improve the system's ability to absorb new energy, and its stable and efficient operation has become more and more important. The security and stability analysis of a distribution network needs accurate distribution network model parameters as support. At present, the installation of PMU equipment in China's distribution network synchronous phase angle measurement unit is limited, which brings challenges to the parameter correction of the distribution network. In this paper, an automatic correction algorithm of distribution network parameters based on the CIM model and measurement data is proposed for the distribution network system without PMU. Firstly, the distribution network topology construction technology based on XML files and key fields of the distribution network is proposed, and the non/small impedance devices (such as switches) are merged and reduced. The breadth-first traversal algorithm is used to verify the connectivity of the constructed topology. Then, based on the topology construction and the least squares method, an iterative parameter correction technique is constructed. Finally, the accuracy and effectiveness of the proposed algorithm are verified in a standard IEEE 33-bus system distribution network and an example of the China Southern Power Grid. The topology connections constructed based on the CIM model have significantly enhanced the efficiency of parameter correction. [ABSTRACT FROM AUTHOR]

Water, energy, and food (WEF) are critical resources to sustain urban development, which requires a sustainable structure of the urban WEF nexus to address trade-offs and achieve synergies. Although interactions in the WEF nexus are widely explored, its sustainable structure has largely been ignored. This study constructs a framework of WEF nexus sustainability factors. Based on a literature review and expert opinions, 21 factors influencing urban WEF nexus sustainability were extracted and their interrelationships determined. We used social network analysis (SNA) and interpretive structural modeling (ISM) to analyze the structure of the urban WEF network. The results indicate that technological investment and industrial added-value energy consumption are the most critical and fundamental factors for promoting the sustainable development of the urban WEF nexus. Additionally, the balance of water supply and demand and the comprehensive management of waste pollutants are also driving and supporting factors for the sustainability of the urban WEF nexus. The results of this study complement the interaction mechanism research of the urban WEF nexus and provide practical references for sustainable decision-making in urban WEF nexus practices. [ABSTRACT FROM AUTHOR]

Recognizing the importance of incorporating different risk measures in the portfolio management model, this paper examines the dynamic mean-risk portfolio optimization problem using both variance and value at risk (VaR) as risk measures. By employing the martingale approach and integrating the quantile optimization technique, we provide a solution framework for this problem. We demonstrate that, under a general market setting, the optimal terminal wealth may exhibit different patterns. When the market parameters are deterministic, we derive the closed-form solution for this problem. Examples are provided to illustrate the solution procedure of our method and demonstrate the benefits of our dynamic portfolio model compared to its static counterpart. [ABSTRACT FROM AUTHOR]

In recent years, the exercise behavior of Chinese adolescents has been on the decline, which is extremely detrimental to their physical and mental health development. However, few studies have explored the mechanisms by which exercise cognition influences Chinese adolescents' exercise behavior. The present study aimed to investigate the relationship between exercise cognition and exercise behavior among Chinese adolescents and the mediating role of satisfying basic psychological needs for exercise. The study consisted of 996 adolescents (44.6% males, 55.4% females) between the ages of 12 and 15 (M = 13.34, SD = 1.059). Participants' exercise behaviors and the satisfaction of basic psychological needs for exercise data were collected via surveys. Structure equation modeling (SEM) was performed to examine the direct and indirect effects. The results were as follows: (1) adolescents' perceptions of exercise were significantly associated with exercise behavior and (2) the mediation model suggests that the satisfaction of basic psychological needs for exercise is an important mechanism by which exercise cognition influences the occurrence of exercise behavior. Therefore, it is crucial to help adolescents form good exercise cognition. Schools, families, and society should take responsibility for adolescents' formation of good exercise cognition and satisfy adolescents' basic psychological needs for exercise so as to enhance adolescents' exercise behaviors and thereby develop good exercise habits. [ABSTRACT FROM AUTHOR]

The hydrogen cycle system, one of the main systems used for hydrogen fuel cells, has many advantages. It can improve the efficiency, the water capacity, and the management of thermal fuel cells. It can also enhance the safety of the system. Therefore, it is widely used in hydrogen fuel cell vehicles. We introduce the structure and principles of hydrogen cycle pumps, ejectors, and steam separators and analyze and summarize the advantages of the components, as well as reviewing the latest research progress and industrialization status of hydrogen cycle pumps and ejectors. The technical challenges in hydrogen circulation systems and the development direction of key technologies in the future are discussed. This paper aims to provide a reference for research concerning hydrogen energy storage application technology in hydrogen fuel cell systems. [ABSTRACT FROM AUTHOR]

Simple Summary: Spirometra mansoni is a neglected human-infective tapeworm. Its motile larva can invade humans, causing a parasitic zoonosis known as sparganosis. Cestoda parasites live in an oxygen-deprived environment in the gastrointestinal tract of their hosts; they mainly depend on energy production from glucose to lactate catalyzed by a series of enzymes under anaerobic conditions. Meanwhile, lactate dehydrogenase (LDH) is a complicated multi-gene family and plays key roles in oxidative production capacity and detoxification pathways in organisms. The purpose of this study was to investigate the gene diversity, phylogenetic patterns and molecular characteristics of the S. mansoni lactate dehydrogenase (SmLDH) protein family to explore the potential important roles of SmLDH in the growth and development of S. mansoni. The plerocercoid of Spirometra mansoni can parasitize both human and animals, resulting in sparganosis. Lactate dehydrogenase (LDH) is an important enzyme in parasites. However, our knowledge of the LDH family in S. mansoni is still inadequate. This work identified 19 new LDH members in S. mansoni. Clustering analysis demonstrated that all SmLDHs were divided into two main groups, which is consistent with the patterns of conserved motif organization. According to RT-qPCR, 2 LDHs were highly expressed in the plerocercoid stage and 17 LDHs were highly expressed in the adult stage. The evolutionary tree showed a high level of diversity of both cestode and trematode LDHs. SmLDHs contained both conserved family members and members in the process of further diversification. rSmLDH has a NAD-binding domain and a substrate-binding domain. The protein was immunolocalized in the epidermis of the pleroceroid and in the tegument, uterus and egg shell of adult worms. The optimum activity for rSmLDH in the pyruvate reduction reaction was found to be pH 4.5 and 37 °C. In the oxidation reaction, optimal values for pH and temperature were 9.0 and 30 °C, respectively. Gossypol was found to be the most powerful inhibitor in both reduction and oxidation reactions. The results provide a basis for the further study of the biological roles of LDHs in S. mansoni and other LDH-containing taxa. [ABSTRACT FROM AUTHOR]

To study the contribution of moisture from different straw-treated and irrigated soil layers to the water consumption of winter wheat in dry farming, a 2-year straw treatment and regulated deficit irrigation experiment was implemented. The field experiment was carried out with 0% (S0), 1% (S1), and 2% (S2) straw returning amounts, and 75 mm (V3), 60 mm (V2), and 45 mm (V1) irrigation volumes. This experiment involved nine treatments, used to quantitatively analyze the ratio and variation of soil water use from different soil layers via the direct contrast method (DCM) and the multiple linear mixed model (MLMM). The results show the following: (1) The distribution of precipitation isotope compositions displayed a repeated trend of first decreasing and then increasing during the study period. Regression analysis showed that the local meteoric water line (LMWL): δD = 6.37δ18O − 3.77 (R2 = 0.832). (2) With increasing soil depth, the δ18O value decreased gradually, and the maximum δ18O value of the soil water within each growth period was distributed at 10 cm. (3) Under the same irrigation amount, δ 18O increased with increasing straw return at 0–20 cm and decreased with increasing straw return at 20–80 cm. (4) The comparison results of the DCM and MLMM were consistent. During the jointing and flowering stages, 0–30 cm soil water was the main source of water for winter wheat. The contribution of soil water below 30 cm had a decreasing trend from the jointing stage to the flowering stage. The average contribution rates of the 0–30 cm soil layer during the jointing and flowering stages were 23.07% and 23.15%, respectively. These findings have important implications for studying the soil water cycle in the context of farming. [ABSTRACT FROM AUTHOR]

The wireless power transmission (WPT) system, which eliminates the limitation of physical connection and improves the convenience of power transmission, has gradually become a research focus in recent years. However, in the current three-coil WPT system, the power repeater is composed of a coupling coil and a compensation capacitor, and its tuning conditions will affect the power transmission ability of the WPT system. However, the exact impact of compensation capacitor is not clear, which leads to the design of power repeaters being based on experience or trial and error methods, making it difficult to achieve the optimization of the WPT system. Therefore, this paper takes transmission power and transmission efficiency as optimization objectives and obtains the optimal relay coil compensation capacitor model of the three-coil WPT system. The result found that the transmission efficiency of the three-coil WPT system after optimizing the compensation capacitor is 3% higher than before, and the anti-migration ability is enhanced. Meanwhile, in view of the dynamic changes in load and mutual inductance that may occur during the use of the three-coil WPT system, a compensation capacitor design and a relay coil compensation capacitor circuit are proposed, respectively, and the parameter setting scheme of the circuit is proposed. The innovative scheme proposed in this paper can effectively improve the transmission efficiency and stability of the three-coil WPT system. [ABSTRACT FROM AUTHOR]

Simple Summary: In two cohorts of vaccinated cancer patients and healthcare workers, 5% had COVID-19 infection after vaccination. These infections occurred more frequently in younger cancer patients with gastrointestinal cancer, gynecological or breast cancer, or a localized cancer and in patients receiving chemotherapy or targeted therapy when vaccinated. In both cohorts, these breakthrough infections occurred early after initiation of vaccination (Alpha SARS-CoV-2 variant) or several months after the end of vaccination (Omicron SARS-CoV-2 variant). In both cohorts these COVID-19 cases in vaccinated individuals were not severe, with only four cancer patients requiring oxygen therapy. In a multicenter prospective cohort of cancer patients (CP; n = 840) and healthcare workers (HCWs; n = 935) vaccinated against COVID-19, we noticed the following: i/after vaccination, 4.4% of HCWs and 5.8% of CP were infected; ii/no characteristic was associated with post-vaccine COVID-19 infections among HCWs; iii/CP who developed infections were younger, more frequently women (NS), more frequently had gastrointestinal, gynecological, or breast cancer and a localized cancer stage; iv/CP vaccinated while receiving chemotherapy or targeted therapy had (NS) more breakthrough infections after vaccination than those vaccinated after these treatments; the opposite was noted with radiotherapy, immunotherapy, or hormonotherapy; v/most COVID-19 infections occurred either during the Alpha wave (11/41 HCW, 20/49 CP), early after the first vaccination campaign started, or during the Omicron wave (21/41 HCW, 20/49 CP), more than 3 months after the second dose; vi/risk of infection was not associated with values of antibody titers; vii/the outcome of these COVID-19 infections after vaccination was not severe in all cases. To conclude, around 5% of our CPs or HCWs developed a COVID-19 infection despite previous vaccination. The outcome of these infections was not severe. [ABSTRACT FROM AUTHOR]

Air pollution is becoming more and more serious as the number of vehicles increases. To address such problems, many cities have implemented many measures, including the circular economy mode, in which used cars with low carbon emission are becoming important in the sustainable transportation and carbon abatement. Considering multi-attribute demand, this study designed combinatorial auction mechanism for the bidders of automobile enterprises on an online used-car platform to achieve social welfare maximization. Two kinds of attributes were considered, namely, price attribute and non-price attributes; the latter particularly included the pro-environment attribute based on an analysis of complementarity and substitutability. Moreover, the mechanism was proved to satisfy individual rational condition and incentive compatibility condition. Numerical application showed that preference for the pro-environment attribute can better realize social welfare and respond to national energy conservation and emission reduction targets. As a result, from the social welfare perspective, the multi-attribute combinatorial auction can provide a reference for more fair and effective allocation of used cars to bidders and can promote both buyer's utility and seller's income. [ABSTRACT FROM AUTHOR]

Introduction: Winter wheat plays a crucial role in ensuring food security and sustainable agriculture. Accurate identification and recognition of winter wheat in remote sensing images are essential for monitoring crop growth and yield estimation. In recent years, attention-based convolutional neural networks have shown promising results in various image recognition tasks. Therefore, this study aims to explore the application of attention-based convolutional neural networks for winter wheat identification on GF-2 high-resolution images and propose improvements to enhance recognition accuracy. Method: This study built a multi-band winter wheat sample dataset based on GF-2 images. In order to highlight the characteristics of winter wheat, this study added two bands, NDVI and NDVIincrease, to the dataset and proposed a SUNet network model. In this study, the batch normalization layer was added to the basic structure of the UNet convolutional network to speed up network convergence and improve accuracy. In the jump phase, shuffle attention was added to the shallow features extracted from the coding structure for feature optimization and spliced with the deep features extracted by upsampling. The SUNet made the network pay more attention to the important features to improve winter wheat recognition accuracy. In order to overcome the sample imbalance problem, this study used the focus loss function instead of the traditional cross-entropy loss function. Result: The experimental data show that its mean intersection over union, overall classification accuracy, recall, F1 score and kappa coefficient are 0.9514, 0.9781, 0.9707, 0.9663 and 0.9501, respectively. The results of these evaluation indicators are better than those of other comparison methods. Compared with the UNet, the evaluation indicators have increased by 0.0253, 0.0118, 0.021, 0.0185, and 0.0272, respectively. Conclusion: The SUNet network can effectively improve winter wheat recognition accuracy in multi-band GF-2 images. Furthermore, with the support of a cloud platform, it can provide data guarantee and computing support for winter wheat information extraction. [ABSTRACT FROM AUTHOR]

The soil-water characteristic curve is the basic constitutive relation to express the water-holding characteristics of ion-absorbed rare earth. The simulated solution mining test and pressure plate apparatus tests were carried out, the relationship between matric suction and water content under different leaching actions was obtained. Using the Fredlund and Xing four-parameter model, the soil-water characteristic curves of ion-absorbed rare earth under different leaching actions were obtained, and the changing trend of each parameter was analyzed, and the influence of different leaching methods on the water-holding characteristic of soil was obtained. For different types of leaching solutions, the water-holding capacity of the soil varies from strong to weak for pure water, the 3% magnesium sulfate solution, and the 3% ammonium sulfate solution; as the concentration of the leaching solution increases, the water-holding capacity of the sample gradually decreases, and it decreases most significantly from 0% to 2%. Moreover, the saliency of the "hysteresis effect" of the soil-water characteristic curve was from high to low for pure water, the 3% magnesium sulfate solution, and the 3% ammonium sulfate solution, and the "hysteresis effect" showed a decreasing trend with the increase in the concentration. [ABSTRACT FROM AUTHOR]

Two series of pleuromutilin derivatives were designed and synthesized as inhibitors against Staphylococcus aureus (S. aureus). 6-chloro-4-amino-1-R-1H-pyrazolo[3,4-d]pyrimidine or 4-(6-chloro-1-R-1H-pyrazolo[3,4-d]pyrimidine-4-yl)amino-phenylthiol were connected to pleuromutilin. A diverse array of substituents was introduced at the N-1 position of the pyrazole ring. The in vitro antibacterial activities of these semisynthetic derivatives were evaluated against two standard strains, Methicillin-resistant Staphylococcus aureus (MRSA) ATCC 43300, Staphylococcus aureus (S. aureus), ATCC 29213 and two clinical S. aureus strains (144, AD3) using the broth dilution method. Compounds 12c, 19c and 22c (MIC = 0.25 μg/mL) manifested good in vitro antibacterial ability against MRSA which was similar to that of tiamulin (MIC = 0.5 μg/mL). Among them, compound 22c killed MRSA in a time-dependent manner and performed faster bactericidal kinetics than tiamulin in time–kill curves. In addition, compound 22c exhibited longer PAE than tiamulin, and showed no significant inhibition on the cell viability of RAW 264.7, Caco-2 and 16-HBE cells at high doses (≤8 μg/mL). The neutropenic murine thigh infection model study revealed that compound 22c displayed more effective in vivo bactericidal activity than tiamulin in reducing MRSA load. The molecular docking studies indicated that compound 22c was successfully localized inside the binding pocket of 50S ribosomal, and four hydrogen bonds played important roles in the binding of them. [ABSTRACT FROM AUTHOR]

Some recent studies use a convolutional neural network (CNN) or long short-term memory (LSTM) to extract gait features, but the methods based on the CNN and LSTM have a high loss rate of time-series and spatial information, respectively. Since gait has obvious time-series characteristics, while CNN only collects waveform characteristics, and only uses CNN for gait recognition, this leads to a certain lack of time-series characteristics. LSTM can collect time-series characteristics, but LSTM results in performance degradation when processing long sequences. However, using CNN can compress the length of feature vectors. In this paper, a sequential convolution LSTM network for gait recognition using multimodal wearable inertial sensors is proposed, which is called SConvLSTM. Based on 1D-CNN and a bidirectional LSTM network, the method can automatically extract features from the raw acceleration and gyroscope signals without a manual feature design. 1D-CNN is first used to extract the high-dimensional features of the inertial sensor signals. While retaining the time-series features of the data, the dimension of the features is expanded, and the length of the feature vectors is compressed. Then, the bidirectional LSTM network is used to extract the time-series features of the data. The proposed method uses fixed-length data frames as the input and does not require gait cycle detection, which avoids the impact of cycle detection errors on the recognition accuracy. We performed experiments on three public benchmark datasets: UCI-HAR, HuGaDB, and WISDM. The results show that SConvLSTM performs better than most of those reporting the best performance methods, at present, on the three datasets. [ABSTRACT FROM AUTHOR]

The ability to track the changes of the surrounding environment is critical for humans and animals to adapt their behaviors. In high-dimensional environments, the interactions between each dimension need to be estimated for better perception and decision making, for example in volatile or social cognition tasks. We develop a hierarchical Bayesian model for inferring and decision making in multi-dimensional volatile environments. The hierarchical Bayesian model is composed of a hierarchical perceptual model and a response model. Using the variational Bayes method, we derived closed-form update rules. These update rules also constitute a complete predictive coding scheme. To validate the effectiveness of the model in multi-dimensional volatile environments, we defined a probabilistic gambling task modified from a two-armed bandit. Simulation results demonstrated that an agent endowed with the proposed hierarchical Bayesian model is able to infer and to update its internal belief on the tendency and volatility of the sensory inputs. Based on the internal belief of the sensory inputs, the agent yielded near-optimal behavior following its response model. Our results pointed this model a viable framework to explain the temporal dynamics of human decision behavior in complex and high dimensional environments. [ABSTRACT FROM AUTHOR]

The natural adsorption material montmorillonite (MMT) was selected, and cellulose acetate (CA) was used as the loading substrate to design and prepare a kind of green and environment-friendly recyclable porous composite fiber membrane with good heavy metal ion adsorption performance. Acetic acid modified montmorillonite (HCl-MMT), sodium dodecyl sulfonate modified montmorillonite (SDS-MMT), and chitosan modified montmorillonite (CTS-MMT) were prepared by inorganic modification and organic modification, and the porous MMT/CA composite fiber membrane was constructed by centrifugal spinning equipment. The morphological and structural changes of MMT before and after modification and their effects on porous composite fiber membranes were investigated. The morphology, structure, and adsorption properties of the composite fibers were characterized by scanning electron microscopy (SEM) and atomic absorption spectrometry (ASS). The experimental results showed that the maximum adsorption capacity of Cu2+ on the prepared 5 wt% CTS-MMT composite fiber membrane was 60.272 mg/g after 10 h static adsorption. The adsorption of Cu2+ by a porous composite fiber membrane conforms to the quasi-second-order kinetic model and Langmuir isothermal adsorption model. The main factor of the Cu2+ adsorption rate is chemical adsorption, and the adsorption mechanism is mainly monolayer adsorption. [ABSTRACT FROM AUTHOR]

Spiral ganglion neurons (SGNs) are important for hearing, and their peripheral and central processes connect sensory cells of the Corti organ to the central nervous system. The resulting network forms a point-to-point auditory conduction. As a cardiac hormone, brain natriuretic peptide (BNP) binds to natriuretic peptide receptor type A leading to diuresis, vasodilatation, inhibition of renin and aldosterone production, and cardiac and vascular myocyte growth. This study primarily aimed to explore the expression and function of BNP in the rat's inner ear and elucidate its regulatory mechanism. We determined the expression and function of BNP and found that the vitamin D receptor (VDR) could upregulate the expression of BNP and enhance its function. In SGNs of the rat inner ear, BNP promotes neuron survival and prolongs neurite length through the cGMP-PKG signaling pathway, which could be regulated by VDR and provide a novel approach for neuronal regeneration therapy. To the best of our knowledge, this is the first study to report this potential transcriptional regulatory relationship and will act as a reference for research on neuronal regeneration therapy for SGNs injury. [ABSTRACT FROM AUTHOR]

The oleo-pneumatic shock absorber involves a complex two-phase flow in the working process. In this paper, a simple oleo-pneumatic shock absorber model was established, and the volume-of-fluid (VOF) two-phase flow model was adopted to accurately simulate the distribution of the two-phase flow field in the shock absorber through the commercial software FLUENT 2020 R2. The accuracy of the simulation model was verified by the method of engineering damping force estimation, and the error of the numerical simulation results compared with the engineering estimation results was 7–8%. By numerical simulation, the influence of different orifice lengths and diameters on the maximum pressure, temperature, velocity and oil damping force inside the shock absorber was studied. The results showed that with the increase of the orifice length, the maximum pressure, flow rate and oil damping force in the shock absorber decreased. The temperature decreased first and then increased, but the overall effect was small. However, according to the oil volume fraction contour, the gas–liquid distribution in the shock absorber with an orifice larger than 15 mm was more chaotic. Increasing the diameter of the orifice had a great impact on the shock absorber. The maximum pressure, flow rate and damping force of the oil inside the shock absorber were sharply reduced, and the temperature continued to rise. These research results can provide reference for the optimization design of oleo-pneumatic shock absorbers. [ABSTRACT FROM AUTHOR]

Trochoid milling can improve the quality of machining of difficult materials as well as the efficiency of machining. However, its complex tool trajectory makes it difficult to predict the instantaneous cutting forces during cutting. Therefore, in this paper, the transient cutting thickness model in the cycloidal milling process was established using numerical combined with analytical methods, and the semi-mechanical cutting force model was established. Experiments were designed to compare the differences between the cutting force coefficients extracted from the slot milling experiments and those extracted from the trochoid milling. Finally, experiments were designed to validate the established cutting force model. The results showed that there was an error of 5–23% between the tangential cutting force coefficients extracted from slot milling and the tangential cutting force coefficients extracted from trochoid milling, while there was an error of 21–35% in the radial cutting force coefficients, indicating that the cutting force coefficients extracted from slot milling cannot be used to predict the cutting force in the trochoid milling process. It was verified that the error of the established cutting force model in predicting the cutting force of trochoid milling was 12%, indicating that the established model has a high accuracy, which provides a theoretical basis for the selection of cutting parameters and parameter optimization in the future. [ABSTRACT FROM AUTHOR]

At present, silver nanowire transparent conductive films (AgNWs-TCFs) still have problems such as high resistance of AgNWs network nodes, uneven distribution of resistance and poor electrical performance stability, which restrict their commercial application. Different from chemical modification, in this paper, a method of modifying AgNWs-TCFs with metal oxide nanoparticles (MONPs) is proposed, that is, ZnO, SnO2, Al2O3 and TiO2 etc., four transparent metal oxides are used as targets respectively in a magnetron sputtering process, modifying the silver nanowire network wire–wire junctions and silver nanowire in AgNWs-TCFs using active MONPs generated by magnetron sputtering. A series of AgNWs@MONPs for the AgNWs@ZnO-TCFs, AgNWs@SnO2-TCFs, AgNWs@Al2O3-TCFs and AgNWs@TiO2-TCFs were obtained. A significant decrease in the resistance of AgNWs-TCFs through the modification of MONPs was shown. Respectively, the reduction of resistance was 75.6%, 70.4%, 53.2% and 59.8% for AgNWs@ZnO-TCFs, AgNWs@SnO2-TCFs, AgNWs@Al2O3-TCFs and AgNWs@TiO2-TCFs. Correspondingly, its non-uniformity of resistance distribution was 12.5% (18.2% before), 10.0% (17.1% before), 10.1% (24.3% before) and 10.6% (13.4% before), respectively, which markedly improved the uniformity of electrical property. Respectively, their failure voltages reach 16, 16, 15 and 16 (V), so accordingly, the electrical stability is considerably enhanced. In addition, the uniformity of temperature distribution was also significantly optimized with its temperature non-uniformity of 10.4%, 8.7%, 10.3% and 9.6%, respectively. Contrast that with AgNWs@MONPs, and the failure voltages and temperature non-uniformity of AgNWs-TCFs are 12 V and 40.6%. [ABSTRACT FROM AUTHOR]

Simple Summary: Vaccination against COVID-19 was a major weapon against current epidemics. In a multicenter cohort study conducted in cancer patients (CP) and health care workers (HCW) we demonstrated that: (i) vaccination was well accepted in both cohorts; (ii) the seropositivity rate was high after the first and second injections among HCW and among CP this was only after the second injection; (iii) similar patterns in antibody response followed the second dose; in both groups, antibody levels waned 3 months after the second dose. Overall, two-dose COVID-19 vaccination was effective in both populations studied, but could not totally prevent a few vaccine breakthrough infections, owing to the continuously emerging novel variants. In this prospective, real-life cohort study, we followed 523 cancer patients (CP) and 579 healthcare workers (HCW) from two cancer centers to evaluate the biological and clinical results of the COVID-19 vaccination campaign. Seventy percent of the CP and 90% of the HCW received an mRNA vaccine or the AZD1222 vaccine. Seropositivity was high after the first vaccine among HCW and poor among CP. The second dose resulted in almost 100% seropositivity in both cohorts. Antibody response was higher after the second injection than the first in both populations. Despite at least two doses, 8 CP (1.5%) and 14 HCW (2.4%) were infected, corresponding either to a weak level of antibody or a new strain of virus (particularly the Omicron variant of concern). Sixteen CP and three HCW were hospitalized but none of them died from COVID-19. To conclude, this study showed that two doses of COVID-19 vaccines were crucially necessary to attain sufficient seropositivity. However, the post-vaccination antibody level declines in individuals from the two cohorts and could not totally prevent new SARS-CoV-2 infections. [ABSTRACT FROM AUTHOR]

Resilience describes individuals' and organizations' recovery from crises and adaptation to disturbances and adversities. Emerging research shows the deterioration of the population's mental health and well-being during the multiple waves of the COVID-19 pandemic, suggesting that the resilience developed is insufficient to address the system's persistent shocks. Drawing on the findings on mental health and well-being during the COVID-19 pandemic and the psychological and organizational resilience theories, we developed a system dynamics theory model exploring how the presence of multiple shocks to the system challenges the population's health and well-being. We initiated the model with three shocks with the same intensities and durations, and then experimented with scenarios in which the strength of multiple shocks (duration and intensity) was attenuated and amplified. The model showed that temporary environmental adjustments with limited long-term stabilized solutions and a lack of health service provision can increase the accumulative risks of health and well-being deterioration. We highlight the role of essential health service sectors' resilience and individuals' and organizations' tolerance of adversities and disturbances in providing sustainable resilience. We conclude by discussing critical factors in organizational and psychological resilience development in crises with multiple shocks to the system. [ABSTRACT FROM AUTHOR]

Background: The presence of the blood–brain barrier (BBB) uniquely distinguishes the brain from other organs, and various brain pathologies, including cancer, can disrupt or breach the BBB. The specific implications of BBB alterations in glioma have not been sufficiently clarified. Methods: In this study, statistical analysis of the TCGA pan-glioma dataset and four other validation cohorts was used to investigate the infiltration of BBB constituent cells (endothelial cells, pericytes and astrocytes) in the glioma tumor microenvironment (TME). Results: We found that the infiltration proportions of the three BBB constituent cell types were highly collinear, which implied alteration of the BBB. Hence, we developed an index, the BBB score, which is calculated based on the infiltration proportion of BBB constituent cells. Furthermore, we observed that patients with higher BBB scores were more likely to be diagnosed with more malignant entities in the TCGA database according to significant molecular features, such as IDH mutation status and 1p/19q deletion. The BBB score was also strikingly positively correlated with WHO grade in other cohorts. More importantly, a higher BBB score correlated with shorter survival time and unfavorable prognosis in glioma patients. Finally, we showed that TME-related pathways may regulate BBB alterations and that coinhibitory immune checkpoints were enriched in samples with higher BBB scores. Conclusions: We showed that TME-related pathways may regulate BBB alterations and that coinhibitory immune checkpoints were enriched in samples with higher BBB scores. Assessing BBB alterations may help elucidate the complex role of the glioma TME and suggest new combination treatment strategies. [ABSTRACT FROM AUTHOR]

Hashing has been widely used for large-scale remote sensing image retrieval due to its outstanding advantages in storage and search speed. Recently, deep hashing methods, which produce discriminative hash codes by building end-to-end deep convolutional networks, have shown promising results. However, training these networks requires numerous labeled images, which are scarce and expensive in remote sensing datasets. In order to solve this problem, we propose a deep unsupervised hashing method, namely deep contrastive self-supervised hashing (DCSH), which uses only unlabeled images to learn accurate hash codes. It eliminates the need for label annotation by maximizing the consistency of different views generated from the same image. More specifically, we assume that the hash codes generated from different views of the same image are similar, and those generated from different images are dissimilar. On the basis of the hypothesis, we can develop a novel loss function containing the temperature-scaled cross-entropy loss and the quantization loss to train the developed deep network end-to-end, resulting in hash codes with semantic similarity preserved. Our proposed network contains four parts. First, each image is transformed into two different views using data augmentation. After that, they are fed into an encoder with the same shared parameters to obtain deep discriminate features. Following this, a hash layer converts the high-dimensional image representations into compact binary codes. Lastly, a novel hash function is introduced to train the proposed network end-to-end and thus guide generated hash codes with semantic similarity. Extensive experiments on two popular benchmark datasets of the UC Merced Land Use Database and the Aerial Image Dataset have demonstrated that our DCSH has significant superiority in remote sensing image retrieval compared with state-of-the-art unsupervised hashing methods. [ABSTRACT FROM AUTHOR]

Non-alcoholic fatty liver disease (NAFLD), one of the most common types of chronic liver disease, is strongly correlated with obesity, insulin resistance, metabolic syndrome, and genetic components. The pathological progression of NAFLD, consisting of non-alcoholic fatty liver (NAFL), non-alcoholic steatohepatitis (NASH), and liver cirrhosis, is characterized by a broad spectrum of clinical phenotypes. Although patients with mild NAFL are considered to show no obvious clinical symptoms, patients with long-term NAFL may culminate in NASH and further liver fibrosis. Even though various drugs are able to improve NAFLD, there are no FDA-approved medications that directly treat NAFLD. In this paper, the pathogenesis of NAFLD, the potential therapeutic targets, and their underlying mechanisms of action were reviewed. [ABSTRACT FROM AUTHOR]

This study focuses on the shear serviceability of simple and continuous reinforced concrete deep beams. The test results of 81 simple deep beams (i.e., simply supported single-span deep beams) and 29 continuous deep beams, for which their diagonal tension cracking loads were reported, were collected from existing studies. On this basis, the diagonal tension cracking mechanism is discussed, and four existing models for diagonal tension cracking are evaluated. The evaluation results show the existing models fail to accurately reflect the influences of the main design parameters (including the shear span-to-effective depth ratio and main tensile reinforcement ratio) on the diagonal tension cracking strength. Therefore, a new equation for the diagonal tension cracking strength for simple and continuous deep beams is proposed. The proposed equation is verified to be superior to the existing models, showing an average value and a coefficient of variation for tested-to-predicted diagonal tension cracking strength ratios of 1.02 and 0.21, respectively. On the other hand, a probabilistic analysis is conducted to evaluate the diagonal tension cracking risk under service load, showing that 35% of deep beams exhibited a diagonal tension cracking load that is less than the service load, which indicated that diagonal cracks easily occur in RC deep beams under service loads. [ABSTRACT FROM AUTHOR]

For shear tests of reinforced concrete (RC) beams, a simply supported and symmetrical loading system is usually applied. In deterministic analysis, shear capacities of the paired shear spans of such beams are the same. However, considering the randomness of concrete strength, geometric dimension, and other factors, shear failure often occurs in the weaker one of the paired shear spans of a beam rather than occurring in the two shear spans simultaneously. Therefore, from the perspective of probability theory, the shear capacities of the paired shear spans of such simply supported and symmetrically loaded beams can be regarded as two random variables with the same distribution. The beam shear capacity, which is the minimum of the two random variables, is also a random variable. Hence, probabilistic differences exist between the shear capacities of shear spans and beams. In this paper, the transformation relationship between the stochasticities of shear span shear capacity and beam shear capacity is theoretically derived. By taking the RC beams without web reinforcement as an example, the shear capacity stochasticities of shear spans and beams, which are valuable for reliability-based design codes, are quantitatively analyzed based on three shear strength models in design codes and a reliable experimental database. Their probabilistic differences are identified and verified to have an impact on the model calibration in the reliability analysis. The results also show that there are obvious differences in the shear capacity stochasticities obtained by different models. It indicates that to obtain the real stochasticity of the shear capacity, it is not enough to consider the model uncertainty merely but to minimize it. Therefore, models based on a solid understanding of the shear mechanisms are urgently needed for practical design. [ABSTRACT FROM AUTHOR]

Rolling element bearings (REB) are widely used in all walks of life, and they play an important role in the health operation of all kinds of rotating machinery. Therefore, the fault diagnosis of REB has attracted substantial attention. Fault diagnosis methods based on time-frequency signal analysis and intelligent classification are widely used for REB because of their effectiveness. However, there still exist two shortcomings in these fault diagnosis methods: (1) A large amount of redundant information is difficult to identify and delete. (2) Aliasing patterns decrease the methods' classification accuracy. To overcome these problems, this paper puts forward an improved fault diagnosis method based on tree heuristic feature selection (THFS) and the dependent feature vector combined with rough sets (RS-DFV). In the RS-DFV method, the feature set was optimized through the dependent feature vector (DFV). Furthermore, the DFV revealed the essential difference among different REB faults and improved the accuracy of fault description. Moreover, the rough set was utilized to reasonably describe the aliasing patterns and overcome the problem of abnormal termination in DFV extraction. In addition, a tree heuristic feature selection method (THFS) was devised to delete the redundant information and construct the structure of RS-DFV. Finally, a simulation, four other feature vectors, three other feature selection methods and four other fault diagnosis methods were utilized for the REB fault diagnosis to demonstrate the effectiveness of the RS-DFV method. RS-DFV obtained an effective subset of five features from 100 features, and acquired a very good diagnostic accuracy (100%, 100%, 99.51%, 100%, 99.47%, 100%), which is much higher than all comparative tests. The results indicate that the RS-DFV method could select an appropriate feature set, deeply dig the effectiveness of the features and more exactly describe the aliasing patterns. Consequently, this method performs better in REB fault diagnosis than the original intelligent methods. [ABSTRACT FROM AUTHOR]

Background and Purpose: A majority studies on diagnosis of Alzheimer's Disease (AD) are based on an assumption: the training and testing data are drawn from the same distribution. However, in the diagnosis of AD and mild cognitive impairment (MCI), this identical-distribution assumption may not hold. To solve this problem, we utilize the transfer learning method into the diagnosis of AD. Methods: The MR (Magnetic Resonance) images were segmented using spm-Dartel toolbox and registrated with Automatic Anatomical Labeling (AAL) atlas, then the gray matter (GM) tissue volume of the anatomical region were computed as characteristic parameter. The information gain was introduced for feature selection. The TrAdaboost algorithm was used to classify AD, MCI, and normal controls (NC) data from Alzheimer's Disease Neuroimaging Initiative (ADNI) database, meanwhile, the "knowledge" learned from ADNI was transferred to AD samples from local hospital. The classification accuracy, sensitivity and specificity were calculated and compared with four classical algorithms. Results: In the experiment of transfer task: AD to MCI, 177 AD and 40NC subjects were grouped as training data; 245 MCI and 45 remaining NC subjects were combined as testing data, the highest accuracy achieved 85.4%, higher than the other four classical algorithms. Meanwhile, feature selection that is based on information gain reduced the features from 90 to 7, controlled the redundancy efficiently. In the experiment of transfer task: ADNI to local hospital data, the highest accuracy achieved 93.7%, and the specificity achieved 100%. Conclusions: The experimental results showed that our algorithm has a clear advantage over classic classification methods with higher accuracy and less fluctuation. [ABSTRACT FROM AUTHOR]

A new type of Janus cellulose acetate (CA) fiber membrane was used to separate oil–water emulsions, which was prepared with plasma gas phase grafting by polymerizing octamethylcyclotetrasiloxane (D4) onto a CA fiber membrane prepared by centrifugal spinning. The Janus–CA fiber membrane was described in terms of chemical structure using Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) analysis, energy dispersive X-ray spectroscopy (EDX) analysis and morphology by field emission scanning electron microscopy (FESEM). In this contribution, we examine the influence of spinning solution concentration, spinning speed and nozzle aperture on the centrifugal spinning process and the fiber morphology. Superhydrophobic/hydrophilic Janus–CA fiber membrane was used to separate water and 1,2-dibromoethane mixture and Toluene-in-water emulsion. Unidirectional water transfer Janus–CA fiber membrane was used to separate n-hexane and water mixture. The separation for the first-time interception rate was about 98.81%, 98.76% and 98.73%, respectively. Experimental results revealed that the Janus cellulose acetate (CA) fiber membrane gave a permeate flux of about 43.32, 331.72 and 275.27 L/(m2·h), respectively. The novel Janus–CA fiber membrane can potentially be used for sustainable W/O emulsion separation. We believe that this is a facile strategy for construction of filtration materials for practical oil–water separation. [ABSTRACT FROM AUTHOR]

Simple Summary: COVID-19 has some clinical manifestations that are similar to the side effects of cancer treatments such that cancer patients may fail to distinguish COVID-19 symptoms from those of their treatments. The PAPESCO-19 study investigated 13 COVID-19 symptoms and confirmed that in combination with anorexia, fever, headache, and rhinorrhea, anosmia has a strong association with COVID-19 for cancer patients while dysgeusia/ageusia does not. Background: Cancer patients may fail to distinguish COVID-19 symptoms such as anosmia, dysgeusia/ageusia, anorexia, headache, and fatigue, which are frequent after cancer treatments. We aimed to identify symptoms associated with COVID-19 and to assess the strength of their association in cancer and cancer-free populations. Methods: The multicenter cohort study PAPESCO-19 included 878 cancer patients and 940 healthcare workers (HCWs). At baseline and quarterly thereafter, they reported the presence or absence of 13 COVID-19 symptoms observed over 3 months and the results of routine screening RT-PCR, and they were systematically tested for SARS-CoV-2-specific antibodies. We identified the symptom combinations significantly associated with COVID-19. Results: Eight percent of cancer patients were COVID-19 positive, and 32% were symptomatic. Among the HCWs, these proportions were 9.5 and 52%, respectively. Anosmia, anorexia, fever, headache, and rhinorrhea together accurately discriminated (c-statistic = 0.7027) COVID-19 cases from cancer patients. Anosmia, dysgeusia/ageusia, muscle pain, intense fatigue, headache, and chest pain better discriminated (c-statistic = 0.8830) COVID-19 cases among the HCWs. Anosmia had the strongest association in both the cancer patients (OR = 7.48, 95% CI: 2.96–18.89) and HCWs (OR = 5.71, 95% CI: 2.21–14.75). Conclusions: COVID-19 symptoms and their diagnostic performance differ in the cancer patients and HCWs. Anosmia is associated with COVID-19 in cancer patients, while dysgeusia/ageusia is not. Cancer patients deserve tailored preventive measures due to their particular COVID-19 symptom pattern. [ABSTRACT FROM AUTHOR]

Cotton is one of the most important fiber and oil crops in the world. Chloroplast genomes harbor their own genetic materials and are considered to be highly conserved. Transfer RNAs (tRNAs) act as "bridges" in protein synthesis by carrying amino acids. Currently, the variation and evolutionary characteristics of tRNAs in the cotton chloroplast genome are poorly understood. Here, we analyzed the structural variation and evolution of chloroplast tRNA (cp tRNA) based on eight diploid and two allotetraploid cotton species. We also investigated the nucleotide evolution of chloroplast genomes in cotton species. We found that cp tRNAs in cotton encoded 36 or 37 tRNAs, and 28 or 29 anti-codon types with lengths ranging from 60 to 93 nucleotides. Cotton chloroplast tRNA sequences possessed specific conservation and, in particular, the Ψ-loop contained the conserved U-U-C-X3-U. The cp tRNAs of Gossypium L. contained introns, and cp tRNAIle contained the anti-codon (C-A-U), which was generally the anti-codon of tRNAMet. The transition and transversion analyses showed that cp tRNAs in cotton species were iso-acceptor specific and had undergone unequal rates of evolution. The intergenic region was more variable than coding regions, and non-synonymous mutations have been fixed in cotton cp genomes. On the other hand, phylogeny analyses indicated that cp tRNAs of cotton were derived from several inferred ancestors with greater gene duplications. This study provides new insights into the structural variation and evolution of chloroplast tRNAs in cotton plants. Our findings could contribute to understanding the detailed characteristics and evolutionary variation of the tRNA family. [ABSTRACT FROM AUTHOR]

Silver nanowire (AgNWs) transparent conductive film (TCF) is considered to be the most favorable material to replace indium tin oxide (ITO) as the next-generation transparent conductive film. However, the disadvantages of AgNWs, such as easy oxidation and high wire-wire junction resistance, dramatically limit its commercial application. In this paper, moisture treatment was adopted, and water was dripped on the surface of AgNWs film or breathed on the surface so that the surface was covered with a layer of water vapor. The morphology of silver nanowire mesh nodes is complex, and the curvature is large. According to the capillary condensation theory, water molecules preferentially condense near the geometric surface with significant curvature. The capillary force is generated, making the wire-wire junction of AgNWs mesh bond tightly, resulting in good ohmic contact. The experimental results show that AgNWs-TCF treated by moisture has better conductivity, with an average sheet resistance of 20 Ω/sq and more uniform electrical properties. The bending test and adhesion test showed that AgNWs-TCF treated by moisture still exhibited good mechanical bending resistance and environmental stability. [ABSTRACT FROM AUTHOR]

Traffic sign recognition in poor environments has always been a challenge in self-driving. Although a few works have achieved good results in the field of traffic sign recognition, there is currently a lack of traffic sign benchmarks containing many complex factors and a robust network. In this paper, we propose an ice environment traffic sign recognition benchmark (ITSRB) and detection benchmark (ITSDB), marked in the COCO2017 format. The benchmarks include 5806 images with 43,290 traffic sign instances with different climate, light, time, and occlusion conditions. Second, we tested the robustness of the Libra-RCNN and HRNetv2p on the ITSDB compared with Faster-RCNN. The Libra-RCNN performed well and proved that our ITSDB dataset did increase the challenge in this task. Third, we propose an attention network based on high-resolution traffic sign classification (PFANet), and conduct ablation research on the design parallel fusion attention module. Experiments show that our representation reached 93.57% accuracy in ITSRB, and performed as well as the newest and most effective networks in the German traffic sign recognition dataset (GTSRB). [ABSTRACT FROM AUTHOR]

The leading cause of heart failure is cardiomyopathy and damage to the cardiomyocytes. Adult mammalian cardiomyocytes have the ability to regenerate, but this cannot wholly compensate for myocardial cell loss after myocardial injury. Studies have shown that exercise has a regulatory role in the activation and promotion of regeneration of healthy and injured adult cardiomyocytes. However, current research on the effects of aerobic exercise in myocardial regeneration is not comprehensive. This review discusses the relationships between aerobic exercise and the regeneration of cardiomyocytes with respect to complex molecular and cellular mechanisms, paracrine factors, transcriptional factors, signaling pathways, and microRNAs that induce cardiac regeneration. The topics discussed herein provide a knowledge base for physical activity-induced cardiomyocyte regeneration, in which exercise enhances overall heart function and improves the efficacy of cardiac rehabilitation. [ABSTRACT FROM AUTHOR]

The morphology of the active layer plays a crucial role in determining device performance and stability for organic solar cells. All-polymer solar cells (All-PSCs), showing robust and stable morphologies, have been proven to give better thermal stability than their fullerene counterparts. However, outstanding thermal stability is not always the case for polymer blends, and the limiting factors responsible for the poor thermal stability in some All-PSCs, and how to obtain higher efficiency without losing stability, still remain unclear. By studying the morphology of poly [2,3-bis (3-octyloxyphenyl) quinoxaline-5,8-diyl-alt-thiophene-2,5-diyl](TQ1)/poly[4,8-bis[5-(2-ethylhexyl)-2-thienyl]benzo[1,2-b:4,5-b′]dithiophene-alt-(4-(2-ethylhexyl)-3-fluorothieno[3,4-b]thiophene-)-2-carboxylate-2-6-diyl]] (PCE10)/PNDI-T10 blend systems, we found that the rearranged molecular packing structure and phase separation were mainly responsible for the poor thermal stability in devices containing PCE10. The TQ1/PNDI-T10 devices exhibited an improved PCE with a decreased π–π stacking distance after thermal annealing; PCE10/PNDI-T10 devices showed a better pristine PCE, however, thermal annealing induced the increased π–π stacking distance and thus inferior hole conductivity, leading to a decreased PCE. Thus, a maximum PCE could be achieved in a TQ1/PCE10/PNDI-T10 (1/1/1) ternary system after thermal annealing resulting from their favorable molecular interaction and the trade-off of molecular packing structure variations between TQ1 and PCE10. This indicates that a route to efficient and thermal stable All-PSCs can be achieved in a ternary blend by using material with excellent pristine efficiency, combined with another material showing improved efficiency under thermal annealing. [ABSTRACT FROM AUTHOR]

Mobile Edge Computing (MEC) is an innovative technique, which can provide cloud-computing near mobile devices on the edge of networks. Based on the MEC architecture, this paper proposes an ARIMA-BP-based Selective Offloading (ABSO) strategy, which minimizes the energy consumption of mobile devices while meeting the delay requirements. In ABSO, we exploit an ARIMA-BP model for estimating computation capacity of the edge cloud, and then design a Selective Offloading Algorithm for obtaining offloading strategy. Simulation results reveal that the ABSO can apparently decrease the energy consumption of mobile devices in comparison with other offloading methods. [ABSTRACT FROM AUTHOR]

Copper(II) (Cu 2+ ) is essential for plant growth and development. However, high concentrations are extremely toxic to plants. We investigated the tolerance mechanism of cotton under Cu 2+ stress in a hybrid cotton variety (Zhongmian 63) and two parent lines with different Cu 2+ concentrations (0, 0.2, 50, and 100 μM). The stem height, root length, and leaf area of cotton seedlings had decreased growth rates in response to increasing Cu 2+ concentrations. Increasing Cu 2+ concentration promoted Cu 2+ accumulation in all three cotton genotypes' roots, stems, and leaves. However, compared with the parent lines, the roots of Zhongmian 63 were richer in Cu 2+ and had the least amount of Cu 2+ transported to the shoots. Moreover, excess Cu 2+ also induced changes in cellular redox homeostasis, causing accumulation of hydrogen peroxide (H 2 O 2 ) and malondialdehyde (MDA). Conversely, antioxidant enzyme activity increased, while photosynthetic pigment content decreased. Our findings indicated that the hybrid cotton variety fared well under Cu 2+ stress. This creates a theoretical foundation for the further analysis of the molecular mechanism of cotton resistance to copper and suggests the potential of the large-scale planting of Zhongmian 63 in copper-contaminated soils.

The leading cause of heart failure is cardiomyopathy and damage to the cardiomyocytes. Adult mammalian cardiomyocytes have the ability to regenerate, but this cannot wholly compensate for myocardial cell loss after myocardial injury. Studies have shown that exercise has a regulatory role in the activation and promotion of regeneration of healthy and injured adult cardiomyocytes. However, current research on the effects of aerobic exercise in myocardial regeneration is not comprehensive. This review discusses the relationships between aerobic exercise and the regeneration of cardiomyocytes with respect to complex molecular and cellular mechanisms, paracrine factors, transcriptional factors, signaling pathways, and microRNAs that induce cardiac regeneration. The topics discussed herein provide a knowledge base for physical activity-induced cardiomyocyte regeneration, in which exercise enhances overall heart function and improves the efficacy of cardiac rehabilitation.