Some management practices, such as maintaining birds under high group density, used in the poultry industry may cause birds stress, leading to injurious behaviors, such as injurious pecking, aggression, and cannibalism. In addition, some management practices used to prevent severe injuries in birds may cause pain. Beak trimming (BT), removal of 1/3 to 1/2 of a beak, is a routine husbandry procedure practiced in laying hens to prevent or reduce injurious behaviors. However, BT causes tissue damage, which may increase somatosensory sensitization of the damaged nerve tissues, resulting in pain (acute, chronic or both) in the treated birds because the beak is a complex, functional organ with an extensive nerve supply. BT has already been heavily regulated or prohibited in several European countries and, in time, this trend will impact the practice used in the United States poultry industry. With the growing public concern for poultry welfare there is a pressing need to identify and develop alternatives to BT. Probiotics defined “as a source of live (viable) naturally occurring microorganisms (direct-fed microbials)” have been used as dietary supplements or functional foods to target gut microbiota (microbiome) for prevention or therapeutic treatment of mental diseases including social stress-induced psychiatric disorders in humans and various experimental animals. In our studies, chickens were used as an animal model to assess if dietary supplementation of probiotic, Bacillus subtilis, reduces injurious behaviors following social challenge. Hens of Dekalb XL strain, an aggressive line, were used in the studies. Our results indicate that dietary supplementation of the Bacillus subtilis based probiotic reduces aggressive behaviors in chickens. These results suggest dietary probiotics could be a suitable strategy for increasing hosts’ health status and welfare conditions.

The fluorine-less noble-gas containing anions OBONgO- and OCNNgO-have been studied by correlated electronic structure calculation and density functional theory. The obtained energetics indicates that for Ng = Kr and Xe, these anions should be kinetically stable at low temperature. The molecular structures and electron density distribution suggests that these anions are stabilized by ion-induced dipole interactions with charges concentrated on the electronegative OBO and OCN groups. The current study shows that in additional to the fluoride ion, polyatomic groups with strong electronic affinities can also form stable noble-gas containing anions of the type X-...NgO.

Aluminum wire is a common material for wire bonding due to its resistance to oxidation and low price. It does not melt when becoming a free air ball (FAB) during the electronic flame-off (EFO) process with wettability, and is applied by wedge bonding. This study used 20μm Zn-Coated Al-0.5wt.%Si (ZAS) wires to improve the FAB shape after the EFO process, while maintaining stability of the mechanical properties, including the interface bonding strength and hardness. In order to test circuit stability after ball bonding, the current-tensile test was performed. During the experiment, it was found that 80nm ZAS with wire bonding has lower resistance and higher fusing current. For the bias tensile test, the thicker Zn film diffused into the Al-Si matrix easily, after which the strength was reduced. The ball-bond interfaces had no change in their condition before and after the bias. Accordingly, ZAS could be a promising candidate for ball bonding in the future.

The black hole (BH) phenomenon is an intraluminal restenotic lesion. It was identified by intravascular ultrasound (IVUS) and optical coherence tomography (OCT) after intracoronary brachytherapy and drug-eluting stent implantation. Despite the similarity in the mode of action of brachytherapy and drug-eluting stent implantation, the BH phenomenon appears to be uncommon after drug-eluting stent implantation. Specifically, the BH phenomenon is better identified by OCT than by IVUS. Herein, we present a case of in-stent restenosis with suspected BH phenomenon on IVUS confirmed by OCT.

Scaffoldings play a critical role as temporary structures in supporting construction processes. Accidents at construction sites frequently stem from issues related to scaffoldings, including insufficient support caused by deviations from the construction design, insecure rod connections, or absence of cross bracing, which result in uneven loading and potential collapse, leading to casualties. In this study, we introduce a deep-learning-based, augmented reality (AR)-enabled system called scaffolding assembly deficiency detection system (SADDS) to assist field inspectors in identifying deficiencies in scaffolding assemblies. Inspectors have the flexibility to utilize SADDS through various devices, such as video cameras, mobile phones, or AR goggles (i.e., Microsoft HoloLens 2), for automated detection of deficiencies in scaffolding assemblies. The training test yielded satisfactory results, with a mean average precision of 0.89 and individual precision values of 0.96, 0.82, 0.90, and 0.89 for “qualified” frames and frames with the “missing cross-tie rod,” “missing lower-tie rod,” and “missing footboard” deficiencies, respectively. Field tests conducted at two construction sites demonstrated improved system performance compared to that in the training test. However, these field tests also revealed certain limitations of the SADDS system.

The Anderson insulating states in Au nanoparticle assembly are identified and studied under the application of magnetic fields and gate voltages. When the inter-nanoparticle tunneling resistance is smaller than the quantum resistance, the system showing zero Mott gap can be insulating at very low temperature. In contrast to Mott insulators, Anderson insulators exhibit great negative magnetoresistance, inferring charge de-localization in a strong magnetic field. When probed by the electrodes spaced by ~200 nm, they also exhibit interesting gate-modulated current similar to the multi-dot single electron transistors. These results reveal the formation of charge puddles due to interplay of disorder and quantum interference at low temperatures.

Continuous greenhouse gas emissions are causing global warming and impacting the habitats of many animals. Researchers in the field of electric power are making efforts to mitigate this situation. Operating and maintaining the power grid in an economic, low-carbon, and stable is challenging. To address the issue, we propose a grid dispatching technique that combines prediction technology, reinforcement learning, and optimization technology. Prediction technology can forecast future power demand and solar power generation, while reinforcement learning and optimization technology can make charging and discharging decisions for energy storage devices based on current and future grid conditions. In the power system, the aggregation of distributed energy resources increases uncertainty, particularly due to the fluctuating generation of renewable energy. This requires the use of advanced predictive control techniques to ensure long-term economic and decarbonization goals. In this paper, we present a real-time dispatching framework that integrates deep learning-based prediction, reinforcement learning-based decision-making, and stochastic optimization techniques. The framework can rapidly adapt to target uncertainty caused by various factors in real-time data distribution and control processes. The proposed framework achieved global Champion in the NeurIPS Challenge 2022 competition and demonstrated its effectiveness in practical scenarios of intelligent building energy management.

A novel five-surface phosphor-in-ceramic (FS-PiC) for high illumination and excellent color uniformity in larger-scale LEDs for sensor light source application is demonstrated. YAG phosphor (Y3Al5O12:Ce3+) was uniformly mixed with ceramic and sintered at 680°C to form a phosphor wafer. A sophisticated laser engraving was employed on the phosphor wafer to form a saddle-shaped large-scale FS-PiC LEDs. The performance of the FS-PiC LEDs exhibited the illumination of 401lm, average color temperature (CCT) of 5488K±110K, and color coordinates (CIE) of (0.3179±0.003, 0.3352±0.003). In contrast to convention single-surface phosphor-in-ceramic (SS-PiC) LEDs, the performance exhibited the illumination of 380lm, average CCT of 5830K±758K, and CIE of (0.3083±0.07, 0.3172±0.07). These indicated that the performance of the FS-PiC LEDs was higher than the SS-PiC LEDs for illumination, CCT, and CIE of 1.1, 7, and 23 times, respectively. Furthermore, the FS-PiC LEDs demonstrate lower lumen loss of 2% and less chromaticity shift of 5.4x10-3 under accelerated aging at 350°C for 1008 hours, owing to the high ceramic melting temperature of up to 510°C. In this study, the proposed FS-PiC larger-scale LEDs having excellent optical performance and high reliability may be the promising candidates to replace the convention phosphor-in-organic silicone material used in high-power LEDs for the next generation of sensor light sources, display, and headlight applications.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

Cloud Manufacturing (CMfg) has attracted lots of attention from scholars and practitioners. The purpose of quality of service (QoS)-aware manufacturing cloud service composition (MCSC), as one of the key issues in CMfg, is to combine different available manufacturing cloud services(MCSs) to generate an optimized MCSC that can meet diverse requirements of customers. However, many available MCS, deployed in the CMfg platform, have same function but different QoS attributes. It is a great challenge to achieve optimal MCSC with high QoS. In order to obtain better optimization results efficiently for the QoS-MCSC problems, a whale optimization algorithm(WOA) with adaptive weight, Lévy flight, and adaptive crossover strategies (ASWOA) is proposed. In the proposed ASWOA, the adaptive crossover inspired by the genetic algorithm is developed to balance the exploration and exploitation. The Lévy flight is designed to expand the search space of WOA and accelerate the convergence of WOA with adaptive crossover. The adaptive weight is developed to extend the search scale of the exploitation. Simulation and comparison experiments are conducted on different scale QoS-MCSC problems. The experimental results demonstrate that the proposed ASWOA outperforms other compared cutting-edge algorithms.

Poly-ether-ether ketone (PEEK) is a great potential thermoplastic in industry and medical treatment and health. In this work, the PEEK/GO and PEEK/MoS2 composites were prepared by a novel hot isostatic pressing method. The addition of GO alters the tribological behaviours mechanism, fatigue wear mechanism is predominant to PEEK/GO composites. However, the combination of abrasive and adhesive wear mechanisms is observed for PEEK/MoS2 composites and PEEK. The reason is the hardness and tensile strength of composites are increased with the appropriate addition of GO. The response time to stable friction state of PEEK/GO and PEEK/MoS2 composites reduces in compared with PEEK, which conduce to shorten running-in time, reduce energy consumption and improve the tribological performances of composites. The addition of GO and MoS2 can effectively decrease the friction coefficient and wear rate, and the optimal content of GO and MoS2 was 0.7 wt.% and 15 wt.%, respectively. The results indicate that PEEK/GO and PEEK/MoS2 are impressive composites that possess super tribological properties.

A large amount of accurate river cross-section data is indispensable for predicting river stages. However, the measured river cross-section data are usually sparse in the transverse direction at each cross-section as well as in the longitudinal direction along the river channel. This study presents three algorithms to resample the river cross-section data points in both the transverse and longitudinal directions from the original data. The resampled cross-section data based on the linear interpolation satisfactorily maintains the topographic and morphological features of the river channel, especially in the meandering river segment. A two-dimensional (2D) high-resolution unstructured-grid hydrodynamic model was used to assess the performance of the original and resampled cross-section data on a simulated river stage under low flow and high flow conditions. The simulated river stages are significantly improved using the resampled cross-section data based on the linear interpolation in the tidal river and non-tidal river segments. Furthermore, the performance of the 2D and three-dimensional (3D) models on the simulated river stage was also evaluated using the resampled cross-section data. The results indicate that the 2D and 3D models reproduce similar river stages in both tidal and non-tidal river segments under the low flow condition. However, the 2D model overestimates the river stages in both the tidal and non-tidal river segments compared to the 3D model under the high flow condition. The model sensitivity was implemented to investigate the influence of bottom drag coefficient and vertical eddy viscosity on river stage. The results reveal that bottom drag coefficient has a minor impact on river stage, but the vertical eddy viscosity is insensitive to river stage.

This study aimed to compare the differences in durability and prestress loss between normal-weight concrete (NC) and lightweight aggregate concrete (LWC) prestressed box girders, which were constructed at the same time in the same area, so as to verify the superiority of using synthetic lightweight aggregate (LWA) made from reservoir sediments in prestressed bridges. For the NCs and LWCs used in prestressed box girders, the basic mechanical properties were tested on the one hand, and the durability properties were tested on the other hand. Then, through the prestress monitoring system, the prestress loss of the two groups of the prestressed box girders was tracked. The results of the durability test confirmed that LWC can inhibit the penetration of air, water, and chloride ions by strengthening the interfacial transition zone between the aggregate and the cement paste, thereby improving its durability. Moreover, the magnetic flux prestress loss of the NC prestressed box girder reached 8.1%. In contrast, the magnetic flux prestress losses on both sides of the LWC prestressed box girder were 4.6% and 4.9%, respectively. This verified that, under the same environmental conditions, the use of LWC produced less of a prestress loss than the use of NC.

An automated discharge imaging system (ADIS), a non-intrusive and safe approach, was developed for measuring river flows during flash flood events. ADIS consists of dual cameras to capture complete surface images in the near and far fields. Surface velocities are accurately measured using the Large Scale Particle Image Velocimetry (LSPIV) technique. The stream discharges are then obtained from the depth-averaged velocity (based upon an empirical velocity-index relationship) and cross-section area. The ADIS was deployed at the Yu-Feng gauging station in Shimen Reservoir upper catchment, northern Taiwan. For a rigorous validation, surface velocity measurements were conducted using ADIS/LSPIV and other instruments. In terms of the averaged surface velocity, all measured results were in good agreement with small differences, i.e., 0.004 to 0.39 m/s and 0.023 to 0.345 m/s when compared to those from acoustic Doppler current profiler (ADCP) and surface velocity radar (SVR), respectively. The ADIS/LSPIV was further applied to measure surface velocities and discharges during typhoon events (i.e., Chan-Hom, Soudelor, Goni, and Dujuan) in 2015. The measured water level and surface velocity both showed rapid increases due to flash floods. The estimated discharges from ADIS/LSPIV and ADCP were compared, presenting good consistency with correlation coefficient R = 0.996 and normalized root mean square error NRMSE = 7.96%. The results of sensitivity analysis indicate that components till (τ) and roll (θ) of the camera are most sensitive parameter to affect the surface velocity using ADIS/LSPIV. Overall, the ADIS based upon LSPIV technique effectively measures surface velocities for reliable estimations of river discharges during typhoon events.

In a global context, the story of the Jesuit compound in Shanghai, since its establishment by French Jesuits in 1847, reflected not only conflicts between rival powers in Europe but also the fight for their interests in the Eastern world. The Pope, who was stuck without legal status in the Vatican after 1861, was also seeking the chance to save the authority of the Church in the face of questions regarding the extent of his temporal power and the status of Rome in the context of Italian unification. As in the Reformation, a break-through in the east seemed to offer a solution for losses in Europe. However, the Jesuits to the East in the late 19th century were not only troops working and fighting on behalf of the Pope; their identities under the French Protectorate added complexity to an already complicated story involving not just the Church, but the course of world history.The female Catholic orders at the east bank of Zi-ka-wei compound became a unique window to approach the complexity.

Ganoderic Acid (GA), a major bioactive compound isolated from an oriental medicinal mushroom, i.e. Ganoderma tsugae, has traditionally been found to have significant medicinal properties. As a result of GA's poor solubility in water, formulation poses several challenges. Additionally, the traditional method of administering it via alcohol always results in unfavorable patient side effects. In order to overcome these problems, Ganoderma Tsugae extracts obtained by ethanol extraction were encapsulated in nanodispersions by ultrasonic cavitation and solvent evaporation to maximise bioavailability. Resultant nanodispersions contained Ganoderic acid in a hydrophobic core with a mean particle size of no more than 200 nm and a very narrow particle distribution. An analysis of the interactions between the control variables and the process optimisation was conducted using the Response Surface Methodology (RSM). Based on the results of the experiment, it was found that the particle size of nanodispersions was influenced by the Hydrophilic-Lipophilic Balance (HLB) number and the evaporation temperature. Moreover, the physical stability of micellar systems is generally determined by the organic phase within them. Regarding formulation stability, the zeta average of the nanodispersions remained virtually unchanged in solutions with different pH levels and short-term storage (14 days) at room temperature. Overall, it has been demonstrated that Ganoderic acid nanodispersions can be efficiently generated by combining ultrasound cavitation and solvent evaporation.

A typhoon-induced storm surge is considered one of the most severe coastal disasters in Taiwan. However, the combination of the storm surge and the astronomical tide called the storm tide can actually cause extreme flooding in coastal areas. This study implemented a two-dimensional hydrodynamic model to account for the interaction between tides and storm surges on the coast of Taiwan. The model was validated with observed water levels at Sauo Fish Port, Hualien Port, and Chenggong Fish Port under different historical typhoon events. The model results are in reasonable agreement with the measured data. The validated model was then used to evaluate the effects of the typhoon's intensity, bathymetric change, and the combination of the typhoon’s intensity and bathymetric change on the maximum storm tide and its distribution along the east coast of Taiwan. The results indicated that the maximum storm tide rises to 1.92 m under a typhoon with an intensity of a 100-year return period. The maximum storm tide increased from a baseline of 1.26 m to 2.63 m for a 90% bathymetric rise at Sauo Fish Port under the conditions of Typhoon Jangmi (2008). The combination of the intensity of a typhoon with a 100-year return period and a 90% bathymetric rise will result in a maximum storm tide exceeding 4 m, 2 m, and 3 m at Sauo Fish Port, Hualien Port, and Chenggong Fish Port, respectively. We also found that the distribution of the maximum storm tide on the east coast of Taiwan can expand significantly subject to the bathymetric rise.

Graphene/silicon (Si) heterojunction photodetectors are widely studied in detecting of optical signals from near-infrared to visible light. However, performance of the graphene/Si photodetectors is limited by defects created in the growth process and surface recombination at the interface. Herein, a remote plasma-enhanced chemical vapor deposition is introduced to directly grow graphene nanowalls (GNWs) at a low power, which can effectively improve the growth rate and reduce defects. Moreover, hafnium oxide (HfO2) grown by atomic layer deposition has been employed as an interfacial layer for the GNWs/Si heterojunction photodetector. It is shown that the high-k dielectric layer of HfO₂ acts as an electron blocking and hole transport layer, which minimizes the recombination and reduces dark current. By optimizing the thickness of HfO₂, an extremely low dark current of 3.85×10^(-10) A with a responsivity of 0.19 AW^(-1), as well as a specific detectivity of 1.38×10^12 Jones at zero bias can be obtained for the fabricated GNWs/HfO₂/Si photodetector. This work demonstrates a universal strategy to fabricate high-performance graphene/Si photodetectors.

In prostate cancer, p53 maximizes apoptosis in response to severe DNA damage, not DNA replication stress. Here, we examined the apoptotic response of two glioblastoma cells, p53-wild type U87 and a p53-mutated T98G cell, for the same stresses. We ascertained that p53 intensified apoptosis in response to severe DNA damage, not DNA replication stress in glioblastoma. We further asked if p53-mediated apoptosis can be induced by cellular stress other than severe DNA damage. We analyzed two compounds, bortezomib and vorinostat, respective inhibitors of 26S proteasome and histone deacetylase, to evaluate their capacity to activate p53-mediated apoptosis. The cellular stress incited by bortezomib, not vorinostat, activated p53-mediated apoptosis. Next, we asked if the cellular stress generated by combining the two compounds had a synergistic effect on apoptosis. Our results demonstrated that doxorubicin with bortezomib or CFS-1686, or bortezomib with vorinostat have a significant synergistic effect on apoptosis only in p53-wild type cell. Under high stress, p53 translocates from cytosol into the nucleus to cause apoptosis possibly. Together, p53 maximizes apoptosis for cellular stress caused by severe DNA damage, disruption of protein turnover, and for the stress induced by drug combination including doxorubicin with bortezomib or CFS-1686, and bortezomib with vorinostat.

Two-dimensional (2D) bismuth oxyhalides (BiOX) have attracted much attention as potential optoelectronic materials. Expecting for their application diversity, we herewith systematically investigate the tunable properties of 2D BiOX by using first principles calculations. Their electronic and optical properties can be modulated by changing the number of monolayers, applying strain, and/or varying the halogen composition. The bandgap shrinks monotonically and approaches the bulk value, the optical absorption coefficient increases, and the absorption spectrum redshifts, as the layer number of 2D BiOX increases. Carrier transport property can be improved by applying tensile strain, and the ability of photocatalytic hydrogen evolution can be obtained by applying compressive strain. General strain engineering will be effective in linearly tune the bandgap of BiOX in a wide strain range. Strain together with halogen composition variation can tune the optical absorption spectrum to be on demand in the range from visible to ultraviolet. It suggests that that 2D BiOX materials have potential serving as tunable novel photodetectors, can be used to improve clean energy techniques, and are prospective in the field of flexible optoelectronics.

The digital orthophoto is an image with geometric accuracy and no distortion. It is acquired through a top view of the scene and finds widespread applications in map creation, planning, and related fields.This paper classifies the algorithms for digital orthophoto generation into two groups: explicit methods and implicit methods. Explicit methods rely on traditional geometric methods, obtaining geometric structure presented by explicit parameters with Multi-View Stereo (MVS) theories, as seen in our proposed Top view constrained Dense Matching (TDM). Implicit methods rely on neural rendering, obtaining implicit neural representation of scenes through the training of neural networks, as exemplified by Neural Radiance Fields (NeRF). Both of them obtain digital orthophoto by rendering from a top view perspective. In addition, this paper conducts an in-depth comparative study between explicit and implicit methods. The experiments demonstrate that both algorithms meet the measurement accuracy requirements and exhibit a similar level of quality in terms of generated results. Importantly, the explicit method shows a significant advantage in terms of efficiency, with a time consumption reduction of two orders of magnitude under our latest CUDA version TDM algorithm. Although explicit and implicit methods differ significantly in their representation forms, they share commonalities in the implementation across algorithmic stages. These findings highlight the potential advantages of explicit methods in orthophoto generation, while also providing beneficial references and practical guidance for the fast digital orthophoto generation using implicit methods.

Multimodal remote sensing data classification can enhance the model’s ability to distinguish land features through multimodal data fusion. In this context, how to help models understand the relationship between multimodal data and target tasks is the focus of researchers. Inspired by human feedback learning mechanisms, causal reasoning mechanisms, and knowledge induction mechanisms, this paper integrates causal learning, reinforcement learning, and meta learning into a unified remote sensing data classification framework and proposed the causal meta-reinforcement learning (CMRL). First, based on feedback learning mechanisms, we have overcome the limitations of traditional implicit optimization of fusion features and customized a reinforcement learning environment for multimodal remote sensing data classification tasks. Through feedback interactive learning between agents and the environment, we help them understand the complex relationships between multimodal data and labels, thereby achieving full mining of multimodal complementary information. Second, based on the causal inference mechanism we designed causal distribution prediction action, classification reward, and causal intervention reward, capturing pure causal factors in multimodal data and cutting off false statistical associations between non-causal factors and class labels. Finally, based on the knowledge induction mechanism, we designed a bi-layer optimization mechanism based on meta-learning. By constructing a meta training task and meta validation task simulation model in the generalization scenario of unseen data, we helped the model induce cross-task shared knowledge, thereby improving its generalization ability for unseen multimodal data. The experimental results on multiple sets of multimodal datasets show that the proposed method achieved state-of-the-art performance in multimodal remote sensing data classification tasks.

The nature abundant sodium metal is proposed as ideal anode materials for advanced batteries due to its high specific capacity of 1166mAh g-1 and low redox potential of -2.71V. However, the uncontrollable dendritic Na formation and low coulombic efficiency are still major obstacles for applications. Notably, the unstable and inhomogeneous solid electrolyte interphase (SEI) is recognized to be the root cause. As SEI layer plays a critical role in regulating uniform Na deposition and improving cycling stability, researches on SEI modification, especially the artificial SEI modifications has been extensively investigated recently. In this regard, we discussed the advances on artificial interface engineering from the aspects of inorganic, organic and hybrid inorganic/organic protective layers. Finally, we also highlighted the conclusions and key prospects for further investigations. We hope this review can provide a new insight for sodium metal protection.

Electrospinning polymer fibers for is a well-understood process, primarily resulting in random mats or single strands. More recent systems and methods have allowed for the production of nanofiber yarns (NFY) for ease of use in textiles. This paper presents a method of NFY manufacture using a simplified dry electrospinning system to produce self-assembling functional NFY capable of conducting electrical charge. The polymer is a mixture of cellulose nanocrystals (CNC), polyvinyl acrylate (PVA) and poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS). When treated with Ethylene Glycol (EG) to enhance conductivity, fibers touching the collector plate align to the applied electrostatic field and grow, twisting together as additional nanofiber polymer is added by the jet. The longer the electrospinning continues, the longer and more uniformly twisted the NFY becomes. This process has the added benefit of reducing the electric field required for NFY production from >2.43 kV cm-1 to 1.875 kV cm-1.

The goal of this paper is to fabricate innovative diaphragm headphones using graphene oxide paper (GOP) and GOP/epoxy nanocomposites (GOPC). Initially, graphene oxide suspension is fabricated, and the vacuum filtration method is adopted to make GOP. Then vacuum bag molding is used to fabricate GOPC from GOP. Hot pressing and associated molds are adopted to fabricate line-indented (GOPC-L) or curve-indented patterns (GOPC-C) on the GOPC. The performance of one kind of GOP and three kinds of GOPC diaphragm headphones is analyzed based on their sound pressure level (SPL) curves achieved by the Soundcheck measurement system. There are four important processing parameters that will influence the performance of the diaphragm, including material type GOP versus GOPC, indented pattern type, sonication time on suspension, and graphene weight fraction in suspension. Compliances of various diaphragms are measured by the Klippel LPM laser measurement system. The results indicate that effects of sonication time and graphene weight fraction on SPL of GOP and GOPC headphones are in reverse, and this is associated with their difference on compliance (modulus), mass, damping ratio, and microstructure uniformity. Either GOPC-L or GOPC-C seems to improve the microstructure of the GOPC, and leads to better SPL performance. The correlation between the previous four factors and SPLs of four kinds of diaphragm headphones is proposed by using scanning electron microscope (SEM) to examine the microstructure of these diaphragms.

In this paper, fiber sensor based on Vernier effect for simultaneous measurement of relative humidity (RH) and temperature is proposed. The sensor is fabricated by coating two kinds of ultraviolet (UV) glue with different refractive indexes (RI) and thicknesses on the end face of a fiber patch cord. Vernier effect is formed by the inner lower-RI polymer cavity and the cavity composed of both polymer films. By calibrating the RH and temperature response of two peaks on the envelope of the reflection spectrum, simultaneous measurement of RH and temperature is realized by solving a set of quadratic equations. Experimental results show that the highest RH and temperature sensitivities of the sensor are 387.3 pm/%RH (in 20%RH to 90%RH) and -533.0 pm/°C (in 15°C to 40°C), respectively. The sensor has merits of low cost, simple fabrication, and high sensitivity, which makes it very attractive for applications that need to simultaneously monitor these two parameters.

The kinetics and efficacy profiles of photoinitiated polymerization are theoretically presented. For the same dose, lower light intensity achieves a higher steady-state-efficacy (SSE) in type-I; in contrast, type-II has an equal SSE. Higher light intensity has a faster rising efficacy, due to faster depletion of photoinitiator (PS) concentration. However, type-II process is also affected by the available oxygen. Higher light intensity produces more efficient singlet oxygen, resulting a higher transient efficacy, in which all intensities reach the same SSE when oxygen is completely depleted. With external oxygen, type-II efficacy increases with time, otherwise, it is governed only by the light dose, i.e., same dose achieves same efficacy. Moreover, type-II has an efficacy follows Bunsen Roscoe law (BRL), whereas type-I follows non-BRL. The measured type-I efficacy and gelation profile are analyzed by our analytic formulas. Schematics of the photocrosslinking stage defined by the availability of oxygen is developed, where both type-I and –II coexist until the oxygen is depleted. The overall efficacy may be enhanced by resupply of PS or oxygen during the light exposure. The roles of light dose and PS concentration on the efficacy of photoinitiated polymerization should be are governed a new concept of a volume efficacy (Ve), defined by the product of the crosslink (or gelation) depth (CD) and local [efficacy].

Initial water content significantly affects the efficiency of soil stabilization. In this study, the effects of initial water content on the compressibility, strength, microstructure and composition of a lean clay soil stabilized by compound calcium-based stabilizer were investigated by static compaction test, unconfined compression test, optical microscope observations, environment scanning electron microscopy, energy dispersive X-ray spectroscopy and X-ray diffraction spectroscopy. The results indicate that as the initial water content increases in the range studied, both the compaction energy and the maximum compaction force decrease linearly and there are less soil aggregates or agglomerations, and smaller proportion of large pores in the compacted mixture structure. In addition, for specimens cured with or without external water supply and under different compaction degrees, the variation law of the unconfined compressive strength with initial water content is different and the highest strength value is obtained at various initial water contents. With the increase of initial water content, the percentage of oxygen element tends to increase in the reaction products of the calcium-based stabilizer, whereas the crystalline mineral of the soil did not change obviously.

Optimal conditions for maximum efficacy of photoinitiated polymerization are theoretically presented. Analytic formulas are shown for the crosslink time, crosslink depth and efficacy function. The roles of photoinitiator (PI) concentration, diffusion depth and light intensity on the polymerization spatial and temporal profiles, for both uniform and non-uniform cases, are presented. For optimal efficacy, a strategy via controlled PI concentration is proposed, where re-supply of PI in high light intensity may achieve a combined-efficacy similar to low light intensity, but has a much faster procedure. A new criterion of efficacy based on the polymerization (crosslink) [strength] and [depth] is introduced. Experimental data are analyzed for the role of PI concentration and light intensity on the gelation time and efficacy.

The kinetics and modeling of dual-wavelength controlled photopolymerization confinement (PC) are presented and measured data are analyzed by analytic formulas and numerical data. The UV-light initiated inhibition effect is strongly monomer-dependent and different monomers have different C=C bond rate constants and conversion efficacy. Without the UV-light, for a given blue-light intensity, higher initiator concentration (C₁₀) and rate constant (k’) lead to higher conversion, as also predicted by analytic formulas, in which the total conversion rate (R_T) is an increasing function of k’R, which is proportional to k[gB₁C₁]^0.5. However, the coupling factor b₁ plays a different role that higher b₁ leads to higher conversion only in the transient regime; whereas higher b₁ leads lower steady-state conversion. For a fixed initiator concentration C₁₀, higher inhibitor concentration (C₂₀) leads to lower conversion due to stronger inhibition effect. However, same conversion reduction was found for the same H-factor of H₀ = [b₁C₁₀ - b₂C₂₀]. Conversion of blue-only are much higher than that of UV-only and UV-blue combined, in which high C₂₀ results a strong reduction of blue-only-conversion, such that the UV-light serves as the turn-off (trigger) mechanism for the purpose of spatial confirmation within the overlap area of UV and blue light. For example, UV-light controlled methacrylate conversion of a glycidyl dimethacrylate resin formulated with a tertiary amine co-initiator, and butyl nitrite, subject to a continuous exposure of a blue light, but an on-off exposure of a UV-light. Finally, we developed a theoretical new finding for the criterion of a good material/candidate governed by a double ratio of light-intensity and concentration, [I₂₀C₂₀.]/[I₁₀C₁₀].

Due to the advantages of low latency, low power consumption and high flexibility of FPGA-based acceleration technology, it has been more and more widely studied and applied in the field of computer vision in recent years. An FPGA-based feature extraction and tracking accelerator for real-time visual odometry (VO) and visual simultaneous localization and mapping (V-SLAM) is proposed, which can realize the complete acceleration processing capability of the image front-end and directly output the feature point ID and coordinates to the backend. The accelerator consists of image preprocessing, pyramid processing, optical flow processing, and feature extraction and tracking modules. For the first time, it implements a hardware solution that combines features from accelerated segment test (FAST) corners with Gunnar Farneback (GF) dense optical flow, to achieve better feature tracking performance and provide more flexible technical route selection. In order to solve the scale invariance and rotation invariance lacking problem of FAST features, an efficient pyramid module with a five-layer thumbnail structure is designed and implemented. The accelerator is implemented on a modern Xilinx Zynq FPGA. The evaluation result shows that the accelerator can achieve stable tracking of features of violently shaking images, and is consistent with the results of MATLAB code running on PC. When operating at 100MHz, the accelerator can process 108 frames per second for 720P images and 48 frames per second for 1080P images. Compared to PC CPUs that consume seconds of time, the processing latency is greatly reduced to the order of milliseconds, making GF dense optical flow an efficient and practical technical solution on the edge side.

In large-capacity energy storage systems, instructions are decomposed typically using an equalized power distribution strategy, where clusters/modules operate at the same power and durations. When dispatching shifts from stable single conditions to intricate coupled conditions, this distribution strategy inevitably results in increased inconsistency and hastened system aging. This paper presents a novel differentiated power distribution strategy comprising three control variables: the rotation status, the operating boundaries for both Depth of Discharge (DOD) and C-rates (C) within a control period. The proposed strategy integrates an aging cost prediction model developed to express the mapping relationship between these control variables and aging costs. Additionally, it incorporates the multi-colony particle swarm optimization (Mc-PSO) algorithm into the optimization model to minimize aging costs. The aging cost prediction model consists of three functions: predicting health features (HFs) based on the cumulative charge/discharge throughput quantity and operating boundaries, characterizing HFs as comprehensive scores, and calculating aging costs using both comprehensive scores and residual equipment value. Further, we elaborated on the engineering application process for the proposed control strategy. In the simulation scenarios, this strategy prolonged the service life by 14.62%, reduced the overall aging cost by 6.61%, and improved module consistency by 21.98%, compared with the traditional equalized distribution strategy. In summary, the proposed strategy proves effective in elongating service life, reducing overall aging costs, and increasing the benefit of energy storage systems in particular application scenarios.

Copper-based nanoparticles were synthesized using the glycine–nitrate process (GNP) by using copper nitrate trihydrate [Cu(NO₃)₂‧3H₂O] as the main starting material and glycine [C₂H₅NO₂] as the complexing and incendiary agent. The as-prepared powders were characterized through X-ray diffraction (XRD), Brunauer–Emmett–Teller (BET) analysis, X-ray photoelectron spectroscopy, and scanning electron microscopy. Using Cu(NO₃)₂.3H₂O as the oxidizer (N) and glycine as fuel (G), we obtained CuO, mixed-valence copper oxides (CuO + Cu₂O, G/N = 0.3–0.5), and metallic Cu (G/N = 0.7). The XRD and BET results indicated that increasing the glycine concentration (G/N = 0.7) and reducing particle surface area increased the yield of metallic Cu. The effects of varying reaction parameters such as catalyst activity, catalyst dose, and H₂O₂ concentration on nonylphenol-9-polyethoxylate (NP9EO) degradation were assessed. With a copper‐based catalyst in a heterogeneous system, the NP9EO and total organic carbon removal efficiencies were 83.1% and 70.6%, respectively, under optimum operating conditions (pH, 6.0; catalyst dose, 0.3 g/L; H₂O₂ concentration, 0.05 mM). The results suggested that removal efficiency increased with an increase in H₂O₂ concentration but decreased when the H₂O₂ concentration exceeded 0.0.5 mM. Furthermore, the trend of photocatalytic activity was as follows: G/N = 0.5 > G/N = 0.7 > G/N = 0.3. The G/N = 0.5 catalysts showed the highest photocatalytic activity and resulted in 94.6% NP9EO degradation in 600 min.

The detrital compositions in sandstone are important recorders of sedimentary provenance and transport, both of which have significant implications for the lithology, age and tectonic evolution of provenance. Through detailed identification and analysis, a high content of volcanogenic compositions (27.6%) was discovered in Shanxi formation of Daniudi Gas Field, Ordos Basin, which is much higher than that of the previous study. The volcanogenic compositions include volcanogenic quartz, lava fragments (dominated by various kinds of rhyolite fragments), tuff fragments, and tuffaceous matrix. In addition, at least 2 volcanic ash layers were discovered. Although the metamorphic rocks of the Precambrian succession in the ancient land of Yin Mountain are usually considered the primary source of the Shanxi formation, it is most likely that the volcanogenic compositions were derived from intermediate-acidic volcanic materials that accumulated in the Daqingshan area during the Late Carboniferous to Early Permian. Those volcanogenic compositions are mainly transported by flowing water rather than by air from provenance to basin. And the accumulation of volcanic materials in the Daqingshan area was controlled by volcanic eruptions occurring solely in this area, rather than by the Inner Mongolia Orogenic Belt. Those volcanic eruptions related to the southward subduction of the Paleo-Asian Ocean Plate beneath the northern margin of the North China Plate in Late Carboniferous to Early Permian. The active continental margin related to the subduction of the Paleo-Asian Ocean Plate lasted until at least the Early Permian, and the closure of the Paleo-Asian Ocean must have occurred later than the Early Permian.

Digital twin, an innovative technology propelled by data and models, plays a seminal role in the digital transformation and intelligent upgrade of ships. This study introduces a digital twin methodology for real-time monitoring of ship structure deformation fields, based on finite discrete strain data, and a visualization tool framework is developed using virtual reality technology. First, the inverse Finite Element Method (iFEM) is employed to derive the deformation field of the ship structure in real time via sensor strain data. Secondly, the deformation field data obtained based on the iFEM algorithm is converted into general visualization data conducive to interpretation within VR applications. Lastly, a digital twin software tool is built to enable synchronous response and interaction between the virtual scene and the physical scene, directly superposing particular virtual objects (data acquired by sensors, CAD virtual models, and deformation field cloud images) onto the physical scene in real-time. The digital twin tool embodies a virtual reality visualization system framework integrating physical data measurement, reconstruction, analysis, expression, storage, rendering and interaction of deformation field data. Through practical application, the flexibility, effectiveness and compatibility of the developed prototype tool are verified. According to the results, the system can enhance the efficiency of scientific communication, model validation, and interdisciplinary sharing during the analysis and evaluation of mechanical properties of ship structures.

To deal with the uncertainties in modeling offshore wind turbines, we proposed a parameter inversion method for the pile-soil interaction model based on structural health monitoring results and the numerical model. The proposed parameter inversion method has a numerical model, an objective function selected using both the numerical and identified results, and an inverse optimization using a random search algorithm in the assumed parameter space. The parameter results in the minimum optimization objective function are identified as the in-situ parameter. The proposed method is confirmed to converge after some iterations, whatever the initial parameter values are. However, different initial parameter cases may converge to slightly different optimal parameters, implying the pile results are sensitive to geological parameters. Moreover, a comparison with the original design results shows design redundancy or risks. Though the proposed method has several flaws, it can shed some light on the influence of uncertainties in offshore wind turbines, such as soil parameters in geological surveys.

The point cloud is a form of three-dimensional data that comprises various detailed features at multiple scales. Due to this characteristic and its irregularity, point cloud analysis based on deep learning is challenging. While previous works utilize the sampling-grouping operation of PointNet++ for feature description and then explore geometry by means of sophisticated feature extractors or deep networks, such operations fail to describe multi-scale features effectively. Additionally, these techniques have led to performance saturation. And it is difficult for standard MLPs to directly "mine" point cloud. To address above problems, we propose the Detail Activation (DA) module, which encodes data based on Fourier transform after sampling and grouping. We activate the channels at different frequency levels from low to high in the DA module to gradually recover finer point cloud details. As training progresses, the proposed Point-MDA can uncover local and global geometries of point cloud progressively. Our experiments show that Point-MDA achieves superior classification accuracy, outperforming PointNet++ by 3.3% and 7.9% in terms of overall accuracy on the ModelNet40 and ScanObjectNN dataset, respectively. Furthermore, it accomplishes this without employing complicated operations, while exploring the full potential of PointNet++.

The spillover of a virus from an animal reservoir to humans requires both molecular and ecological risk factors to align. While extensive research both before and after the emergence of SARS-CoV-2 in 2019 implicates horseshoe bats as the significant animal reservoir for the new human coronavirus, it remains unclear why it emerged at this time. One massive disruption to animal-human contacts in 2019 is linked to the on-going African swine fever virus (ASFV) pandemic. Pork is the major meat source in the Chinese diet. We hypothesize that the dramatic shortage of pork following large-scale culling and restrictions of pig movement (resulting in marked price increases) led to alternative sources of meat and unusual animal and meat movements nationwide, e.g., involving wildlife, and thus greatly increased opportunities for human-sarbecovirus contacts. Pork prices were particularly high in southern provinces (Guangdong, Guangxi, Fujian, Jiangxi, Hunan, and Hubei), where wildlife is farmed and more frequently consumed. Major wildlife farming provinces are spread from Northern to Southern China, which overlaps with horseshoe bat host ranges, potential hosts of the proximal SARS-CoV-2 ancestor, and wildlife sourcing provinces of Wuhan Huanan market and possibly other markets. Trading of SARS-CoV-2 susceptible wildlife in these markets, such as minks, raccoon dogs, foxes and palm civets in Wuhan markets, could have increased the risk of SARS-CoV-2 from an intermediary host. Moreover, large quantities of animals raised for fur could have entered the human food chain undetected and significantly increased risks of animal-human contact. Performing retrospective testing of stored susceptible animals and their meat sold before December 2019 may be helpful in the next stage of tracing the animal origin of SARS-CoV-2 as spillover events are more likely to have taken place in 2019 when China was experiencing the worst effects of the ASFV pandemic.

Sodium substitution Li1-xNaxMn2O4 cathodes were synthesized by a solid-state reaction method. The morphologies and crystal structures of Li1-xNaxMn2O4 were characterized by scanning electron microscopy (SEM) and X-ray diffraction (XRD), respectively. All Li1-xNaxMn2O4 samples exhibited a single phase LiMn2O4 spinel structure with good crystallinity. The effect of Na+ ions on the electrochemical performance of Li1-xNaxMn2O4 was investigated by galvanostatic charge-discharge test. The results showed that lithium substituted by sodium deteriorated its capacity retention but enhance its discharge capacity when it worked at large current densities. The initial discharge capacity was 114.2 mAh/g for Li0.94Na0.06Mn2O4, and 93.1 mAh/g remained after 300 cycles at a current density of 2220 mA/g in the voltage range 3.0–4.3 V at room temperature.

This paper presents an optimized feature-centered reflection symmetry axis detection and localization framework for object perception. The proposed framework is formed to obtain an improved reflection symmetry axis based on the salient symmetry feature. It starts with a refined Multi-scale Saliency Symmetry Model (MSSM), which is realized by applying isotropic symmetry operator on salient points in scale-space rather than all pixels. In each scale, salient points are initially extracted as local extremal from an image, and they are further refined by a multi-scale implementation for generating salient symmetry feature maps. A Symmetric Transformation Matrix is then computed using the optimal feature matching pairs, which can be explicitly used as an abstract representation of the constraint regions of symmetry objects in an image to optimize the performance of the potential symmetry axis detection. The framework has been investigated experimentally both on the classical dataset from a symmetry detection challenge and the latest dataset. It has shown that the framework can get a better or comparative result and also can be further adapted into terminated human--computer equipment for reflection symmetry object perception and tracking.

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban-rural transition affects PM2.5 are warranted within the framework of urban-rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban-rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban-rural transformation and PM2.5. The results are as follows: (1) Over time, there was a discernible upward tendency in the change in urban-rural areas. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban-rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted “N-shaped” curve of negative-positive-negative changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. Currently, an inverted "U-shaped" curve forms the left side of the impact of population transition (PT) on PM2.5. Land development (LT) has a "U-shaped" curve for its effect on PM2.5. This research provides a new perspective on the topic of PM2.5 and its connection to urban-rural integration, which is crucial to understanding the dynamics of this shift. To achieve its goal of high-quality development, it supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, it can provide a reference for decision-makers in the world’s densely populated areas that suffer from serious air pollution.

Aluminum (Al) toxicity is the most common factor limiting the growth of alfalfa in acidic soil conditions. Melatonin (MT), a significant pleiotropic molecule present in both plants and animals, has shown promise in mitigating Al toxicity in various plant species. This study aims to elucidate the underlying mechanism by which melatonin alleviates Al toxicity in alfalfa through a combined physiological and transcriptomic analysis. The results reveal that 5 μM MT significantly alleviates Al-induced growth inhibition and preserves the morphology of root tip cells. Moreover, MT application reduces Al accumulation in alfalfa roots and shoots by 28.6% and 27.6%, respectively. Additionally, MT plays a crucial role in scavenging Al-induced excess H2O2 by enhancing the activities of superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), consequently reducing malondialdehyde (MDA) levels. The RNA-seq results reveal that MT application significantly upregulates the expression of xyloglucan endotransglucosylase/hydrolase (XTH) and carbon metabolism-related genes, including those involved in the glycolysis process, as well as sucrose and starch metabolism, suggesting that MT application may mitigate Al toxicity by facilitating the binding of Al to the cell walls, thereby reducing intracellular Al accumulation, and by improving respiration and the content of sucrose and trehalose. Taken together, our study demonstrates that MT alleviates Al toxicity in alfalfa by restoring redox homeostasis, enhancing Al binding to the cell wall, and modulating carbon metabolism. This research advances our understanding of the mechanisms underlying MT's effectiveness in mitigating Al toxicity, offering potential strategies for reducing Al accumulation in alfalfa.

Taiwan developing offshore wind power to promote green energy and self-electricity production. In this study, a Light Detection and Ranging (Lidar) was set up at Chang-Hua development zone one on the sea and 10km away from the seashore. At Lidar location, WRF (3.33km & 2km grid lengths) model and WAsP were used to simulate the wind speed at various elevations. Three days mean wind speed of simulated results were compared with Lidar data. From the four wind data sets, developed five different comparisons to find an error% and R-Squared values. Comparison between WAsP and Floating Lidar was shown good consistency. Lukang meteorological station 10 years wind observations at 5m height were used for wind farm energy predictions. The yearly variation of energy predictions of traditional and TGC wind farm layouts are compared under purely neutral and stable condition. The one-year cycle average surface heat flux over the Taiwan Strait is negative (-72.5 (W/m2) and 157.13 STD), which represents stable condition. At stable condition TGC (92.39%) and 600(92.44%), wind farms were shown higher efficiency. The Fuhai met mast wind data was used to estimate roughness length and power law exponent. The average roughness lengths are very small and unstable atmosphere.

Underwater target detection is widely used in various applications such as underwater search and rescue, underwater environment monitoring, and Marine resources survey. However, the visibility of the underwater environment and the accuracy of target detection can be affected by complex underwater light changes and unpredictable background noise. To address these issues, we propose an improved underwater target detection algorithm based on YOLOv8n. Our algorithm focuses on three aspects. Firstly, we replace the original C2f module with Deformable Convnets v2 to enhance the adaptive ability of the target region in the convolution check feature map and extract the target region's features more accurately. Secondly, we introduce SimAm, a non-parametric attention mechanism, which can deduce and assign three-dimensional attention weights without adding network parameters. Lastly, we optimize the loss function by replacing the CIOU loss function with the Wise-IOU loss function. To conduct our experiments, we create our own dataset of underwater target detection for experimentation. Meanwhile, we also utilized the Pascal VOC dataset to evaluate our approach. The [email protected] and [email protected]:0.95 of the original YOLOv8n algorithm on the underwater target detection were 88.6% and 51.8%, respectively, and the improved algorithm [email protected] and [email protected]:0.95 can reach 91.8% and 55.9%. The original YOLOV8n algorithm was 62.2% and 45.9% [email protected] and [email protected]:0.95 on the Pascal VOC dataset, respectively. The improved YOLOV8n algorithm [email protected] and [email protected]:0.95 were 65.7% and 48.3%, respectively. The floating-point computation volume of the model is reduced by about 6%. The above experimental results prove the effectiveness of our method.

In the clock network design, the trade-off between power consumption and timing closure is an important and difficult issue. To achieve this target, a hybrid clock network architecture that combines both clock tree and clock mesh seems to be a promising solution. In this paper, we propose a novel clock mesh architecture – cross-mesh, with the average dispersion of the overall driving force, our methodology creates small non-zero skew clock trees. In addition, we integrate clock gating and register clustering techniques to further reduce dynamic power consumption. The proposed algorithms have four stages: cross-mesh planning, register clustering, mesh line connecting, and load balancing. Experimental results show that our methodology and algorithms get feasible solution effectively and improve both power consumption and clock skew simultaneously.

Edcraft, a recycling and upcycling event for Malaysian secondary school students, particularly in the Klang Valley area in 2020. The event's goal was to look into gamified solutions to encourage recycling and upcycling among the students’ age group. Lectures, talks, practical exercises and games were used to teach students about climate change and environmental preservation. According to a post-event survey, the percentage of participants who recycle has climbed significantly: 76% now recycle, compared to only 24% previously. The study discovered that gamification-based activities could effectively facilitate recycling and upcycling behaviours. Such solutions can be applied to encourage behavioural changes in different contexts. By interviewing 15 Edcraft students in a focus group study setting, researchers could better understand the motivations. Themes such as 'social connections are vital', 'convenience and rewards are significant motivators', 'gamified activities help attract and engage teens' and 'environmental knowledge is crucial to prolonging recycling' emerged from the thematic analysis. This manuscript proposes gamified activities to induce a behavioural change in upcycling, and the findings yield helpful insights to fuel pro-environmental behaviours.

A multi-decadal change analysis of the irrigation ponds in Taoyuan, Taiwan was conducted by using multi-source data including digitized ancient maps, declassified single-band CORONA satellite images, and multispectral SPOT images. Supervised LULC classifications were conducted using four textural features derived from the single-band CORONA images and spectral features derived from SPOT images. Post-classification analysis revealed that the number of irrigation ponds in the study area decreased during the post-World War II farmland consolidation period (1945 – 1965) and the subsequent industrialization period (1970 – 2000). However, efforts on restoration of irrigation ponds in recent years have resulted in gradual increases in the number (9%) and total area (12%) of irrigation ponds in the study area.

CdZnTe (CZT) is a new type of compound semiconductor that has emerged in recent years. Compared to other semiconductor materials, it possesses an ideal bandgap, high density, and high electron mobility, rendering it an excellent room-temperature composite semiconductor material for X-ray and γ-ray detectors. Due to the exceptional performance of CZT material, detectors manufactured using it exhibit high energy resolution, spatial resolution, and detection efficiency. They also have the advantage of operating at room temperature. CZT array detectors, furthermore, demonstrate outstanding spatial detection and three-dimensional imaging capabilities. Researchers worldwide have conducted extensive studies on this subject. This paper, building upon this foundation, provides a comprehensive analysis of CZT crystals and CZT array detectors, summarizes existing research to offer valuable insights for envisioning new detector methodologies.

To evaluate the efficacy of fish oil for protection against coronary heart disease (CHD), we conducted a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the use of fish oil for protection against CHD. We retrieved relevant articles published from January 1966 to January 2020 by searching the PubMed, EMBASE, Cochrane CENTRAL, and Web of Science databases. RCTs of fish oil in preventing CHD were selected. The study quality was evaluated using the Cochrane Risk of Bias tool with RevMan 5.3 software. The first selection involved 350 citations. After screening and evaluation of suitability, 19 RCTs adjusted for clustering were included in the meta-analysis. All selected manuscripts considered that fish oil was effective in preventing CHD, secondary outcome measures included angina, sepsis and death. Compared with the control group, fish oil may confer significant protection against CHD (odds ratio = 0.84; 95% confidence interval: 0.72–0.98). There was no significant difference in the incidence of secondary outcomes between the observation group and the control group (P > 0.05). The above results show that fish oil plays an important role in reducing CHD and cardiovascular events. However, because of the suboptimal quality of the studies included into the meta-analysis, these results do not justify adding fish oils systematically to the heavy pharmaceutical assortment already recommended in CHD patients.

Our previous retrospective observational study demonstrated the safety of laparoscopically assisted subtotal colectomy with ileorectal anastomosis and preservation of the superior rectal artery (SRA), without instances of leakage, in patients with slow-transit constipation (STC). Thus, we extended the enrollment period and enlarged the sample size to detect the differences in the post-operative complications, and surgical and functional outcomes between patients who underwent laparoscopically assisted subtotal colectomy with and without SRA preservation. We conducted a retrospective single-center analysis of patients with STC who underwent laparoscopically assisted subtotal colectomy between 2016 and 2020. The diagnosis of STC was based on the colonic transit and anal functional tests, and barium enema to exclude secondary causes. Patients were divided into group A that underwent surgery with SRA preservation, and group B that underwent ligation of the SRA during surgery. Outcome assessments for both groups included the incidence of anastomotic breakdown, intraoperative complications, length of hospital stay, estimated blood loss, time to first flatus, and complications. Propensity-score matching allocated 34 patients to groups A and B each. Postoperative bowel function, including time to first flatus, stool, and oral intake, recovered better in group A than that in group B. Anastomotic leakage, a significant postoperative complication, was less frequent in patients with SRA preservation. Preservation of the SRA in patients undergoing laparoscopically assisted subtotal colectomy with ileorectal anastomosis for STC is associated with favorable postoperative bowel function recovery and lower anastomotic leakage rates.

In response to injury, vascular smooth muscle cells (VSMCs) of the arterial wall dedifferentiate into a proliferative and migratory phenotype, leading to intimal hyperplasia. The ERK1/2 pathway participates in cellular proliferation and migration while dual-specificity phosphatase 6 (DUSP6, also named MKP3) can dephosphorylate activated ERK1/2. We showed that DUSP6 was expressed in low baseline levels in normal arteries; however, arterial injury significantly increased DUSP6 levels in the vessel wall. Compared with wild-type mice, Dusp6-deficient mice had smaller neointima. In vitro, IL-1β induced DUSP6 expression and increased VSMC proliferation and migration. Lack of DUSP6 diminished IL-1β-induced VSMC proliferation and migration. DUSP6 deficiency did not affect IL-1β-stimulated ERK1/2 activation. Instead, ERK1/2 inhibitor U0126 prevented DUSP6 induction by IL-1beta, indicating that ERK1/2 functions upstream of DUSP6 to regulate DUSP6 expression in VSMCs rather than downstream as a DUSP6 substrate. IL-1β decreased levels of cell cycle inhibitor p27 and cell-cell adhesion molecule N-cadherin in VSMCs whereas lack of DUSP6 prevented their downregulation, revealing novel functions of DUSP6 in regulating these two molecules. Taken together, our results indicate that lack of DUSP6 attenuated neointima formation following arterial injury by reducing VSMC proliferation and migration, which were likely mediated via maintaining p27 and N-cadherin levels.

Metamorphosis is a critical process for most anurans to transition from water to land. The appearance of air-breathing lungs occurs during the change in oxygen medium from water to air. Revealing the structural construction and molecular switches of lung organogenesis is essential to understand the realization of air-breathing function. In this study, histology and transcriptomics were combinedly conducted to explore these issues in Microhyla fissipes lungs during metamorphosis. During the pro-metamorphic phase, histological structure improving of the alveolar wall was accompanied by robust substrate metabolism and protein turnover. The lungs, at the metamorphic climax phase, are characterized by an increased number of cilia in the alveolar epithelial cells and collagenous fibers in the connective tissues, corresponding to the transcriptional upregulation of cilia and extracellular matrix-related genes. The post-metamorphic lungs strengthen the contracting function, as suggested by the thickened muscle layer and the upregulated expression of genes involved in muscle contraction. The blood–gas barrier is fully developed in adult lungs whose transcriptional features are tissue growth and differentiation regulation and immunity. Importantly, significant transcriptional switches of pulmonary surfactant protein and hemoglobin facilitate air-breathing. Our results illuminated four key steps of lung development for amphibians to transition from water to land.

M87 is the best available source for studying the AGN jet-launching region. To enrich our knowledge of this region, with quasi-simultaneous observations using VLBA at 22, 43 and 86~GHz, we capture the images of the radio jet in M87 on a scale within several thousand R_s. Based on the images, we analyze the transverse jet structure and obtain the spectral-index distribution in the jet. We find that the absorption is enhanced at the collimation regions and the interruption of the jet. The external medium, which may not be uniform, may have contributed a lot to the absorption in the jet-launching region. Additionally, the temporal morphology of the jet in its launching region may be largely affected by the local, short-lived kink instability growing in itself.

Detailed kinetics for a 3-wavelength photopolymerization confinement (PC) system is presented for both numerical solutions and analytic formulas. The dynamic profiles are simulated for oxygen, free radical, and conversion for various situations of: blue-light only, 2-light (red and UV), and 3-light (red, blue, UV). An effective PC requires two conditions: (i) a strong N-inhibition for uncured regime with a low conversion (triggered by the UV-light); and (ii) a weak S-inhibition (oxygen-induced) for high conversion under the blue-light or blue and red-light initiation. Good PC candidates are governed by collective factors of: (i) the double ratio of light-intensity and initiator-concentration, (ii) monomers rate-constant; and (iii) effective absorption constants at specific wavelength and initiators. A new reverse feature for the role of N-inhibition on the blue-conversion is found. Higher oxygen concentration leads to a lower conversion, which could be enhanced by reducing the S-inhibition via a red or blue-light pre-irradiation, having a pre-irradiation time TP=200 s for red-light only, and reduced to 150 s, when both red and blue-light. System under UV-only leads a conversion lower than that of blue-only. However, conversion could be improved by the dual-light (blue and UV), and further enhanced by the pre-irradiation of red-light. The two competing factors, N-inhibition and S-inhibition, could be independently and selectively tailored to achieve: (a) high conversion of blue-light (without UV-light), enhanced by red-light pre-irradiation for minimal S-inhibition; and (b) efficient PC initiated by UV-light produced N-inhibition for reduced confinement thickness and for high print speed.

The rapid development of multicopters has led to many security problems. In order to prevent multicopters from invading restricted areas or famous buildings, an Anti-UAV Defense System (AUDS) has been developed and become a research topic of interest. Topics under research in relation to this include electromagnetic interference guns for unmanned aerial vehicles (UAVs), high-energy laser guns, US military net warheads, and AUDSs with net guns. However, these AUDSs use either manual aiming or expensive radar to track UAVs. This paper proposes a dual-axis rotary platform with UAV automatic tracking. The tracking platform uses visual image processing technology to track and lock the dynamic displacement of a UAV. When a target UAV is locked, the system uses a nine-axis attitude meter and laser rangefinders to measure its flight altitude and calculates its longitude and latitude coordinates through sphere coordinates to provide UAV monitoring for further defense or attack missions. Tracking tests of UAV flights in the air were carried out using a DJI MAVIC UAV at a height of 30 meters to 100 meters. It was set up for UAV image capture and visual recognition for tracking under various weather conditions by a thermal imager and a full-color camera respectively. When there was no cloud during the daytime, the images captured by the thermal imager and full-color camera provide a high-quality image recognition result. However, under dark weather, black clouds will emit radiant energy and seriously affect the capture of images by a thermal imager. When there is no cloud at night, the thermal imager performs well in UAV image capture. When the UAV is tracked and locked, the system can effectively obtain the flight altitude and longitude and latitude coordinate values.

Photodynamic therapy has been applied endoscopically to treat early esophageal cancer. However, the long-term survival outcome of this treatment option is unknown in literature. Patients and Method: The patients of early esophageal cancer (clinical stage I) treated with photophrin based photodynamic therapy were analyzed for their long-term survival outcome and compared to those patients undergoing esophagectomy by a single surgeon for stage I disease. Results: There were 15 and 16 patients undergoing PDT and esophagectomy enrolled in the current study respectively. Complete response was achieved in 10 (66.7%) patients after PDT. After adjuvant chemoradiation (CCRT) complete response was achieved in 13 patients (86%). There is no mortality after PDT. Severe complication was detected in 3 patients including trachea-esophageal fistulae, esophageal stenosis and skin photosensitivity respectively. With a median follow-up duration of 110.2 months (+9.6 months) for the patients after PDT, there were 4 and 3 recurrence in the primary tumor site and regional lymph node respectively with 73.3% of successful local control rate of the primary tumor. There were 7 (46.7%) patients died during clinical follow-up of this cohort with 5 (33.3%) from disease progression of esophageal cancer and two from other diseases respectively. The five-year survival rate after PDT is 64.3%, whereas 70.9% of the patients after esophagectomy without significant difference of these two group of patients (P=0.72). Conclusion: Our preliminary results suggested that PDT might provide an equivalent long-term oncological outcome as compared to that done by esophagectomy for early esophageal cancer. A prospective randomized clinical trial comparing the results with esophagectomy and other endoscopic abrasive therapies is warrant in the future.

Strawberry root rot caused by Neopestalotiopsis clavispora is one of the main diseases of strawberry and significantly impacts the yield and quality of strawberry fruit. There are now no effective control techniques available except for fungicide sprays, which may directly impact consumers. Biological control is becoming an alternative method for the control of plant diseases to replace or decrease the application of traditional synthetic chemical fungicides. Trichoderma is widely used as a biological agent for controlling strawberry root rot. In order to provide resources for screening the highly effective biocontrol fungus for controlling strawberry root rot caused by Neopestalotiopsis clavispora, the biocontrol mechanism,the control effects of Trichoderma asperellum CMT10 against strawberry root rot and growth-promoting effects on strawberry seedlings were investigated by plate culture, microscopy observation and root drenching methods.The results showed that CMT10 had obvious competitive, antibiotic and hyperparasitism effects on Neopestalotiopsis clavispora CMGF3. The CMT10 could quickly occupy nutritional space, and the inhibition rates of CMT10 against CMGF3 in confrontation culture on 7 d was 65.49%. The inhibition rates of volatile metabolite and fermentation metabolite produced by CMT10 against CMGF3 were 79.67% and 69.84%, respectively. The mycelium of strain CMT10 can act as hyperparasites by making contacting, winding and penetrating hyphae of CMGF3. Pot experiment showed that the biocontrol efficacy of CMT10 on strawberry root rot caused by Neopestalotiopsis clavispora was 63.00%. CMT10 had obvious promotion effect on strawberry growth, the plant height, root length, total fresh weight, root fresh weight, stem fresh weight and root dry weight, with the promotion rates were 20.09%, 22.39%, 87.11%, 101.58%, 79.82% and 72.33%, respectively. Overall, this study showed the ability of Trichoderma asperellum CMT10 to control strawberry root rot and their potential to develop as novel biocontrol agents to replace chemical fungicides for eco-friendly, sustainable agriculture.

Variable cross-section arch is widely used in practical engineering because of its beautiful arc and excellent mechanical properties. However, there is still no systematic and comprehensive study on the out-plane buckling of variable cross-section arch. In view of this, this paper is concentrated on an elastic analytical research of out-plane buckling of arches with variable cross-section under a uniformly distributed radial local load. The pre-buckling and out-plane buckling behaviour of a variable cross-sectional arch under an external load is quite different from that of an arch with uniform cross-section. The Castigliano's second theorem is used to establish pre-buckling force method equilibrium equations for variable cross-sectional arches under a uniformly distributed radial local load, and corresponding analytical solutions of normal stress, axial compression and the bending moment are obtained. Based on the energy method and the Ritz method, analytical solutions of the critical load for the elastic out-plane buckling of arches with variable cross-section are derived. Comparisons with ANSYS results indicated that the analytical solutions are able to accurately predict the pre-buckling internal forces and critical out-plane buckling load of variable cross-section arches subjected to a uniformly distributed radial local load. It is found that the internal forces and the out-plane buckling load of an arch are significantly affected by the variation of cross-sectional height. With the ratio of cross-sectional height of the top to the end increase, the bending moment decreases and the axial force and critical out-plane buckling load increase. Analytical solutions of pre-buckling internal force and critical out-plane buckling load problems for arches with variable cross-section have a wider significance, since they can provide an effective explicit analytic method for the optimal design of arch structure.

The development requirements for reusable liquid rocket engines have set higher standards for the reliability design of turbopump structures. To address the issue of bearing failure in turbopumps under harsh conditions such as low temperature, high speed, heavy load, and repeated start-stop cycles, this paper proposes replacing ball bearings with thrust foil bearings. We used liquid nitrogen instead of liquid hydrogen and liquid oxygen to simulate the ultralow temperature and low viscosity operating environment of turbopumps, evaluating the potential feasibility of using thrust foil bearings in this context. The numerical calculations primarily include the formulation of the foil deformation equations based on the link-spring model for the wavy foil and the thin plate finite element model for the top foil. These equations are solved by coupling the Reynolds lubrication equation, the fluid film thickness equation, and the foil deformation equations using the finite difference method, Newton-Raphson method, and finite element method. A detailed analysis is conducted on the effects of rotational speed, fluid film thickness, thrust disk inclination angle, and wavy foil interface friction coefficient on the static and dynamic characteristics of thrust foil bearings. The research findings provide guidance for the application of thrust foil bearings in liquid rocket turbopumps.

The spatial distribution of elements can be regarded as a numerical field of concentration values with a continuous spatial coverage. An active area of research is to discover geologically meaningful relationships among elements from their spatial distribution. To solve this problem, we propose an association rule mining method based on clustered events of spatial auto-correlation and applied it to the polymetallic deposits of the Chahanwusu River area, Qinghai Province, China. The elemental data for stream sediments were first clustered into HH (high-high), LL (low-low), HL (high-low), and LH (low-high) groups by using local Moran’s I clustering map (LMIC). Then the Apriori algorithm was used to mine the association rules among different elements in these clusters. More than 86% of the mined rule points are located within 1000 m of faults and near known ore occurrences, and occur in the upper reaches of the stream and catchment areas. In addition, we found that the Indosinian granodiorite is enriched in sulfophile elements, e.g., Zn, Ag and Cd, and the Variscan granite quartz diorite (P1γδο) coexists with Cu and associated elements. Therefore, the proposed algorithm is an effective method for mining co-existence patterns of elements and provides an insight into their enrichment mechanisms.

Understanding how species that follow different life-history strategies respond to stressful temperature can be essential to efficient treatments against agricultural pests. Here we focus on how the development and reproduction of C. medinalis is influenced by exposure to different rearing temperatures in the immature stage. We found that low (18 or 22 °C) or high (30 and 34 °C) rearing temperatures negatively affected the immature development and flight performance compared to the normal temperature 26 °C, with higher larval and pupal mortality, lower pupation and eclosion rates and shorter flight duration and distance. Low rearing temperatures significantly slowed down the immature process, but accelerated adult reproduction. However, high rearing temperatures had the opposite impacts. Interestingly, the flight of adults with un-mature rearing low temperatures (18 and 22 °C) significantly decreased their lifetime fecundity and mating frequency, but increased pre-oviposition period of females compared to the control; On contrast, high rearing temperatures (30 and 34 °C) significantly accelerated onset of oviposition and enhanced synchrony of spawning. These results indicate high rearing temperatures in the immature stage are more likely to trigger the onset of migration, but low rearing temperatures induces adults to have a greater resident propensity with stronger reproductive ability.

With the rapid development of satellite remote sensing technology, the volume of image datasets in many application areas is growing exponentially and the demand for Land-Cover and Land-Use change remote sensing data is growing rapidly. It is thus becoming hard to efficiently and intelligently retrieve the change information that users need from massive image databases. In this paper, content-based image retrieval is successfully applied to change detection and a content-based remote sensing image change information retrieval model is introduced. First, the construction of a new model framework for change information retrieval in a remote sensing database is described. Then, as the target content cannot be expressed by one kind of feature alone, a multiple-feature integrated retrieval model is proposed. Thirdly, an experimental prototype system that was set up to demonstrate the validity and practicability of the model is described. The proposed model is a new method of acquiring change detection information from remote sensing imagery and so can reduce the need for image pre-processing, deal with problems related toseasonal changes as well as other problems encountered in the field of change detection. Meanwhile, the new model has important implications for improving remote sensing image management and autonomous information retrieval.

Purpose: To explore parents’ perceptions of the educational intervention programme regarding their children’s postoperative pain management. Design and Methods: A qualitative descriptive study was conducted. Thirty-two parents whose children underwent inpatient elective surgery were recruited from the two intervention groups (received an educational booklet and a video, with or without an hour of face-to-face teaching session) for this qualitative evaluation of the intervention. Participants were asked to comment on the content and delivery methods of the intervention via individual face-to-face semi-structured interviews. Thematic analysis was used to identify themes from the data. Results: Three themes were generated from 32 participants’ interview data: current pain management practices, experiences and benefits of the educational intervention, and suggestions to improve pain management. Conclusions: Our findings suggested that the educational intervention in children’s postoperative pain management was helpful for parents and their children. However, it is necessary to improve educational materials and equip healthcare professionals with non-pharmacological pain relief methods. Practice Implications: Our findings reveal the current challenges in extensively adopting non-pharmacological pain relief methods. Healthcare professionals can do more to routinely integrate pharmacological and non-pharmacological pain management strategies in relieving pain effectively. Future research could develop technology-based programmes to increase ease of access. Trial Registration Number: ISRCTN24910957.

Remote patient monitoring systems are helpful since they can provide timely and effective healthcare facilities. Such online telemedicine are usually achieved with the help of sophisticated and advanced wearable sensor technologies. The modern type of wearable connected devices enables the monitoring of vital sign parameters such as: heart rate variability (HRV) also known as electrocardiogram (ECG), blood pressure (BLP), Respiratory rate and body temperature. The ubiquitous problem of wearable devices is power demand for signal transmission, such devices require frequent battery charge which causes serious limitations to the continuous monitoring of vital data. To overcome this, the current study provides a primary report for collecting kinetic energy from human daily activities for monitoring Human vital signs, the harvested energy is used to sustain the battery autonomy of wearable devices, which enables longer monitoring time of vital data. A thorough review of available commercial ECG devices is first provided, and different methods evaluated in other literature to improve the monitoring time of wearable IOT devices. Besides, a novel type of Stress or exercise ECG monitoring device based on Microcontroller PIC18F4550 and Wi-Fi device ESP8266 is proposed in this study, which is cost effective and enables real time monitoring of heart rate on cloud during normal daily activities. In order to achieve both portability and maximum power, the harvester has smallest structure and low friction. Neodymium magnets are chosen for their highest magnetic force. Due to nonlinear magnetic force interaction of the magnets, the nonlinear part of the dynamic equation has inverse quadratic form. Electromechanical damping is considered in this study and the quadratic non linearity is approximated using MacLaurin expansion, which enables to find the law of motion for general case of studies using classical methods for dynamic equations and find the suitable parameters for the harvester. The oscillations are enabled by applying an initial force and there is loss of energy due to the electromechanical damping. A typical numerical application is computed with Matlab software and ODE45 solver is used to verify the accuracy of the method.

The perturbations of DNA methyltransferase 3 alpha (DNMT3A) may cause uncontrolled gene expression, resulting in cancers and tumors. The DNMT inhibitors Azacytidine (AZA) and Zebu-larine (ZEB) inhibit the DNMT family with no specificities and consequently would bring side effects during the treatment. Therefore, it is vital to understand their inhibitory mechanisms in DNMT3A to inform the new inhibitor design for DNMTs. Herein, we carried out molecular dynamics (MD) and quantum mechanics/molecular mechanics (QM/MM) simulations to investigate the inhibitory mechanisms of AZA and ZEB. The results were compared to the methyl transfer of cytosine. We showed AZA might stop the methyl transfer process, whereas the ZEB might be stuck in a me-thyl-transferred intermediate (IM3). Such IM3 state then fails the elimination due to the unique protein dynamics that result in missing the catalytic water chain. Our results brought atomic-level insights into the mechanisms of the two drugs in DNMT3A, which could benefit the new generation of drug design for the DNMTs.

This study aims to develop an in-situ field repair approach, special for aircraft composite structures, to enhance the interlaminar toughness of plain woven composites (PWCs) by adding multi-walled carbon nanotubes (MWCNTs). MWCNTs are dispersed at each interface between prepreg layers by means of solvent spraying with the density is 1.58 g/m2. And then, the layers are stacked with the predefined sequence and cured at 120℃ and 1 bar pressure using the heat repairing instrument. Moreover, double cantilever beam (DCB) standard test is used to investigate the interlaminar toughening effect due to the MWCNTs. For comparison, original samples are also prepared, the results indicate that the introduction of MWCNTs can favorably enhance the interlaminar toughness of PWCs at field repair approach and the Mode I fracture energy release rate GIC increases by 102.92%. Based on finite element method (FEM) of continuum damage mechanics, the original and MWCNTs toughening specimen under DCB Mode I fracture are modeled and analyzed. The simulation and experiment are in good agreement. Finally, the toughening mechanism of MWCNTs is explored by scanning electron microscope (SEM), it is founded that a large amount of Fiber-matrix (F-M) interface debonding and matrix cracking of mountain shape are the major modes of fracture accompanied with few fiber breakage and matrix peeling off for the MWCNTs toughening specimens.

Keywords: Porcine reproductive and respiratory syndrome virus, baculovirus surface display vectors, neutralizing antibody, IFN-γ, IL-4.

Background Successful treatment for patients with metastatic colorectal cancer who failed to response to first-line treatment has been a challenge due to their low response rate for later-line treatment and poor progression free survival and overall survival. The application of dendritic cell-cytokine-induced killer cells (DC-CIK) immunotherapy combined with conventional treat-ment, either surgical resection or chemotherapy, showed improvement in survivals in first-line treatment for metastatic colorectal cancer. In this retrospective study, we aimed to evaluate the benefit of dendritic cell-cytokine-induced killer cells (DC-CIK) immunotherapy for patient with refractory metastatic colorectal cancer. Methods A total of 20 patients with refractory metastatic colorectal cancer receiving cell-cytokine-induced killer cells (DC-CIK) immunotherapy were enrolled to this study. Among these patients, 11 patients responded to the treatment and the remaining 9 patients did not. All patients were followed for at least one years and the determination of treatment response was mainly based on image study at 6 months after the completion of treatment. Data were analyzed with Kaplan-Meier method and log-rank test. Results The treatment response rate of the study group is 55% (11/20). The median progression free sur-vival (PFS) and median overall survival (OS) of responsive patients was 7 months and 12 months, respectively. The median overall survival of irresponsive patients was 9.5 months. Four responsive patients received subsequent metastectomy or cytoreduction plus hyperthermic in-traperitoneal chemotherapy surgery (CRS + HIPEC). Conclusion DC-CIK cell-based immunotherapy may provide benefits for patients with refractory mCRC with improved response rate and progression free survival.

Lung adenocarcinoma (LUAD) is the most common lung cancers, which accounts for about 35%-40% of all lung cancer patients. Despite therapeutic advancements in recent years, the overall survival time of the LUAD patients still remain poor, especially KRAS mutant LUAD. Therefore, it is necessary to further explore novel targets and drugs to improve the prognosis of LUAD. Ferroptosis, an iron-dependent regulated cell death (RCD）caused by lipid peroxidation, has attracted much attention recently as an alternative target for apoptosis in LUAD therapy. Ferroptosis has been found closely related with LUAD, at its every stage, including initiation, proliferation and progression. In this review, we will provide a comprehensive overview on ferroptosis mechanisms, it’s regulation in LUAD, and application of targeting ferroptosis for LUAD therapy.

Xinjiang, as a climate-sensitive region in northwest China, holds significant importance in studying extreme weather events for agricultural production and socioeconomic development. Based on data from 52 meteorological stations and 23 extreme climate indicators in Xinjiang from 1960 to 2021, the 5a moving average, linear trend estimation, climate tendency rate, and GIS spatial analysis methods are used to analyze the distribution and change characteristics of extreme climate. The results revealed that from 1960 to 2021, TXx, TNx, TXn, TNn, FD, ID, TN10p, TX10p, and WSDI showed a significant upward trend, while SU, TR, TN90p, TX90p, and CSDI showed a significant downward trend. What is more, the range of changes in the extreme temperature indexes from 1990 to 2021 is higher than that of 1960 to 1989. The high-value areas of extreme indexes are primarily concentrated in the northern part, while the high-value areas of cold event indexes are mainly distributed in the southern part. The upward/downward trends all accounting for over 80.00% of the entire region. The Rx1day, Rx5day, PRCPTOT, R95p, R99p, R10, R20, and R25 showed a significant growth trend from 1960 to 2021, and the range of change in the extreme precipitation indexes from 1990 to 2021 was lower than that from 1960 to 1989. Moreover, their high-value areas and high climate tendency areas are mainly concentrated in the northern and western parts of Xinjiang, with upward trends all accounting for over 71.00% of the entire region. The research results provide theoretical foundations for formulating climate risk strategies in the northwest region of China.

In Taiwan, mountainous areas account for approximately two-thirds of the total area. The steep terrain and concentrated rainfall during typhoons cause landslides, which pose a considerable threat to mountain settlements. Therefore, models for analyzing rainfall-induced landslide hazards are urgently required to ensure adequate land use in mountainous areas. In this study, focusing on Pingtung County in southern Taiwan, we developed a landslide hazard index (IRL) to land use. Using FORMOSA-2 and SPOT-5 satellite images, data were collected before and after four typhoons (one in 2009 and three in 2013). The ArcGIS random tree classifier was used for interpreting satellite images to explore surface changes and disasters, which were used to analyze slope disturbances. The product of the maximum 3-h rolling rainfall intensity and effective accumulated rainfall was used as a rainfall trigger index (IRT). Considering environmental and slope disturbance factors, an index of slope environmental strength potential (ISESP) was developed through logistic regression (LR). Landslide hazard to land use was estimated using IRT and ISESP. The average coefficient of agreement (Kappa) was approximately 0.71 (medium to high accuracy); the overall accuracy of slope environmental strength potential analysis was approximately 80.4%. At a constant ISESP, IRT increased with the increasing hazard potential of rainfall-induced landslides. Furthermore, IRT and ISESP were positively correlated with landslide occurrence. When large ISESP values occur (e.g., fragile environment and high land development intensity), small IRT values may induce landslides.

Studies on the neurobiological causes of anxiety disorders suggest that the GABA system in-creases synaptic concentration and enhances the affinity of GABAA (type A) receptors for ben-zo-diazepine ligands. Flumazenil antagonizes the benzodiazepine binding site of the GABA (γ-aminobutyric acid) type /benzodiazepine receptor (BZR) complex in the central nervous sys-tem (CNS). The integration of the metabolites of flumazenil by LC-tandem mass spectrometry will complete understanding of the in vivo metabolism of flumazenil and accelerate radio-pharmaceutical inspection and registration. The main goal of our study was to investigate using reversed-phase HPLC (PR-HPLC) coupled with electrospray ionization triple quadrupole tan-dem mass spectrometry (ESI-QqQ MS) for the identification of flumazenil and its metabolites in a hepatic matrix. And a carrier-free nucleophilic fluorination with automatic synthesizer for [18F]flumazenil which applied to in vivo nano-positron emission tomography (Nano-PET)/computed tomography (CT) imaging and ex vivo bio-distribution used to analyze in normal rats. The study showed that 50% of the flumazenil was bio-transformed at 60 min by the rat liver homogenate, while one metabolite (M1) was a methyl transesterification product of flumazenil. In a rat liver microsomes system, two metabolites were identified (M2 and M3) as its carboxylic acid and hydroxylated ethylester forms, respectively. [18F]flumazenil in vivo nanoPET/CT imag-ing and ex vivo bio-distribution assay also showed significant effects on GABAA receptor availa-bility in the amygdala, prefrontal cortex, cortex, and hippocampus in the rat brain, worriless about the formation of metabolites. We showed completion of the bio-transformed course of flumazenil by the hepatic system; and [18F]flumazenil can be a good ligand and serve as a PET agent for determination of GABAA/BZR complex for multiplex neurological syndromes in the clinical stage.

We tested selecting data randomly or proportionally in class imbalanced sample. Collecting data into the training and test set according to the initial ratio of QSOs, galaxies and stars were rec-ommended. We experimented using the original imbalanced data or introducing the class balance technologies: SMOTE, SMOTEENN, SMOTETomek, ADASYN, BorderlineSMOTE1, Border-lineSMOTE2, and RandomUndersampling. The SMOTEENN performed the best in the Sample 1. The LightGBM, CatBoost, XGBoost, and RF were compared when adopting the SMOTEENN using the petroMag_u, petroMag_g, petroMag_r, petroMag_i, petroMag_z, J, H, Ks, W1, W2, W3, W4 magnitudes as features. All of the precisions or recalls exceeded 0.94. The RF cost a little more time than the other three algorithms, but resulted in the best evaluating indicators. Utilizing the SMOTEENN +RF technology, the precision, recall and f1-score for QSOs (galaxies, stars) could achieve 0.98 (0.99, 0.98), 0.99 (0.96, 1.00), 0.98 (0.97, 0.99) respectively in Sample 1. Utilizing the SMOTEENN +RF technology, the precision, recall and f1-score for QSOs (galaxies, stars) could achieve 0.94 (0.96, 0.96), 0.98 (0.90, 0.97), 0.96 (0.93, 0.97) using the petroMag_u, petroMag_g, petroMag_r, petroMag_i, petroMag_z, W1, W2, W3, W4 magnitudes as features.

COVID-19 is a highly infectious respiratory illness caused by SARS-CoV-2, and acute lung injury (ALI) is the major cause of COVID-19. The challenge in studying SARS-CoV-2 pathogenicity is the limited availability of animal models. Therefore, it is necessary to establish animal models that can reproduce multiple characteristics of ALI to study therapeutic applications. The present study established a mouse model that has features of ALI that are similar to COVID-19 syndrome to investigate the role of ACE2 and the administration of the Chinese herbal prescription NRICM101 in ALI. Mice with genetic modifications, including overexpression of human ACE2 (K18-hACE2 TG) and absence of ACE2 (mACE2 KO), were intratracheally instillated with hydrochloric acid. The acid intratracheal instillation induced severe immune cell infiltration, cytokine storms, and pulmonary disease in mice. Compared with K18-hACE2 TG mice, mACE2 KO mice exhibited dramatically increased levels of multiple inflammatory cytokines (IL-6, TNF-α, and TGF-β1) in bronchoalveolar lavage fluid, histological evidence of lung injury, and dysregulation of MAPK and MMP activation. In mACE2 KO mice, NRICM101 could ameliorate the disease progression of acid-induced ALI. In conclusion, the established mouse model provided an effective platform for researchers to investigate pathological mechanisms and develop therapeutic strategies for ALI, including COVID-19-related ALI.

A variety of myricetin derivatives bearing ferulic acid amide scaffolds were designed and synthesized. The structures of all title compounds were determined by 1 H NMR, 13 C NMR, 19 F NMR and HRMS. Preliminary bioassays suggested that some of the target compounds exhibited remarkable antiviral activities. In particular, compound 4l possessed significant protection activity against tobacco mosaic virus (TMV), with an half maximal effective concentration (EC50) value of 196.11 μg/mL, which was better than commercial agent ningnamycin (447.92 μg/mL). Meanwhile, microscale thermophoresis (MST) indicated that compound 4l have strong binding capability to tobacco mosaic virus coat protein (TMV-CP) with dissociation constant (Kd) values of 0.34 μmol/L, which was better than ningnamycin (0.52 μmol/L). These results suggest that novel myricetin derivatives bearing ferulic acid amide scaffolds may be considered as an activator for antiviral agents.

Plants of the golden Camellia group are not only high-quality camellia germplasm , but also a plant group with rich medicinal and nutritional value, which are used as food, cosmetics and traditional medicine in China. There are approximately 50 species in this group around the world, and more than 30 species of golden camelliaplants have been published in China. The leaves and flowers of these species have similar shapes, so they are often confused as species. Our study used simplified genome sequencing technology to construct a phylogenetic tree of plants in the Chinese golden Camellia group and describe the evolutionary relationships . At the same time, the secondary metabolic indexes of total phenols, total flavonoids, total anthocyanins and ellagic acid in the leaves were determined., and principal component clustering analysis was performed . The results showed that the chemical classification and genetic phylogenetic trees showed some of the same trends, indicating that Camellia chinensis can be used as Biomarkers for chemical type. The research results provide phylogenetic information for the genotype and performance diversity of golden camelliaregionally distributed in China. At the same time, molecular biology phylogenetic methods are used to understand or explain the characteristics of secondary metabolites of golden Camellia , and provide theoretical basis for the search and development of potential bioactive substances.

This paper develops a novel energy universal service bus system (EUSBS) based on emerging energy Internet (E-net) technologies. This EUSBS is a unified identification and plug-and-play interface platform to which high penetration distributed energy and equipment (DEE), including photovoltaic (PV), fans, electric vehicle charging stations (EVCSs), energy storage equipment (ESE), and commercial and residential users (CRUs), can access in a coordinated control and optimized utilization mode. First, the functions design, overall framework and topology architecture design of the EUSBS are expounded, among which the EUSBS is mainly composed of a hardware system and a software platform. Moreover, several future application scenarios are presented. Then, the hardware part of EUSBS is designed and developed, including the framework design of this hardware subsystem, and development of the hardware equipment for PV access, fans access, EVCS access, ESE access, and CRU access. The hardware subsystem consists of smart socket, and household/floor/building concentrators. Based on this, the prototypes development of EUSBS hardware equipment is completely demonstrated. Third, the software part of the EUSBS is developed as a cloud service platform for electricity use data analysis of DEE. This software subsystem contains the power quality & energy efficiency analysis module, optimization control module, information and service module, and data monitoring and electricity behavior analysis module. Based on this design, the software interfaces are developed. Finally, an application study on energy management and optimization of a smart commercial building is conducted to evaluate the functions and practicality of this EUSBS. The EUSBS developed in this paper is able to overcome difficulties in big data collection and utilization on sides of distribution network and electricity utilization, and eventually implement a deep information-energy fusion and a friendly supply-demand interaction between the grid and users. This contribution presents a detailed and systematic development scheme of the EUSBS, and moreover, the laboratory prototypes of the hardware and software subsystems have been developed based on E-net technologies. This paper can provide some thoughts and suggestions for the research of active distribution network and comprehensive energy management and optimization in power systems, as well as references and guidance for researchers to carry out research regarding energy management, optimization and coordinated control of the smart buildings.

Objective: To evaluate the clinical efficacy of antibiotic bone cement plus lateral bone repositioning for severe diabetic foot and its impact on wound healing rate. Methods: Sixty patients with hemodialysis anemia admitted to the endocrinology department of our hospital from July 2020 to July 2021 were included and randomly assigned to receive antibiotic bone cement plus lateral bone repositioning (observation group) or vacuum sealing drainage (VSD) (control group). Outcome measures included skin temperature of the affected limb, ankle-brachial index, sensory threshold, foot wound healing, dorsalis pedis artery hemodynamics, lower limb function and clinical efficacy. Results: Antibiotic bone cement plus lateral bone repositioning resulted in significantly higher treatment efficiency and transcutaneous partial pressure of oxygen, smaller wound, and lower trauma pH versus VSD, suggesting that antibiotic bone cement plus lateral bone repositioning contributes to potentiating the treatment efficacy and reducing the foot ulcer trauma, thereby facilitating rapid recovery. Patients given antibiotic bone cement plus lateral bone repositioning had larger vascular internal diameter and blood flow and better sensory conduction velocity of the common peroneal nerve and the motor conduction velocity of the tibial nerve versus those given VSD, indicating its vascular and neurological benefits. Conclusion: Antibiotic bone cement plus lateral bone repositioning enhances the treatment efficiency, boosts trauma healing, and promotes postoperative functional recovery of patients.

Water area segmentation in remote sensing is of great importance for flood monitoring. To overcome some challenges in this task, we construct the Water Index and Polarization Information (WIPI) multi-modality dataset and propose a multi-Modality Fusion and Gated multi-Filter U-Net (MFGF-UNet) convolutional neural network. The WIPI dataset enhances the water information and reduces the data dimension. In particular, the Cloud-Free label provided in the database effectively mitigates the issue of scarcity of labeled samples Since a single form or uniform kernel size cannot handle the variety in size and shape of water bodies, we proposed the gated multi-filter inception (GMF-Inception) module in our MFGF-UNet. Moreover, we utilize the attention mechanism by introducing the Gated Channel Transform (GCT) skip connection and integrating GCT into GMF- Inception to further improve model performance. Extensive experiments on three benchmarks, including WIPI, Chengdu and GF2020 datasets demonstrate that our method achieves favorable performance with lower complexity and better robustness against six competing approaches. For example, on WIPI, Chengdu and GF2020 datasets, the proposed MFGF-UNet model achieves F1 of 0.9191, 0.7410, and 0.8421, respectively, which average F1 on three datasets is 0.0045 higher than the U-Net model and reduces 62% average GFLOPs. New WIPI dataset, code and trained models have been released on GitHub

Diesel engines, as power equipment, are widely used in the fields of automobile industry, ship and power equipment. Due to wear or faulty adjustment, the valve train clearance abnormal fault is a typical failure of diesel engines, which may result in the performance degradation, even valve fracture and cylinder hit fault. However, the failure mechanism features mainly in time domain and angular domain, on which the current diagnosis methods based, are easily affected by working conditions or hard to extract accurate enough, as the diesel engine keeps running in transient and non-stationary process. This work arms at diagnosing this fault mainly based on frequency band features which would change when the valve clearance fault occurs. For the purpose of extracting a series of frequency band features adaptively，a decomposition technique based on improved variational mode decomposition is investigated in this work. As the connection between the features and the fault is fuzzy, the random forest algorithm is used to analyze the correspondence between features and faults. In addition, the feature dimension is reduced to improve the operation efficiency according to importance score. The experimental results under variable speed condition show that the method based on variational mode decomposition and random forest is capable to detect valve clearance fault effectively.

Traditional edible barbecue products use with lemon juice not only make the barbecue more delicious but also reduce the risk of PAHs in the barbecue products. One of the major economics crops in Taiwan, the waste from citrus fruits was very tremendous mass. However, the peelings of citrus fruits are rich in essential oil, especially, the limonene is the major. Whether the anti-carcinogenesis activities of terpene, such as limonene, in citrus fruits essential oil extraction. This study to demonstrate the PAHs content in fish skin increased markedly after being roasted at 210℃ for 20 minutes and greater mutagenicity risk of roasted fish skin was observed by Ame's test. The reduction of mutagenicity risk of roasted fish skin, which the antimutagenic abilities of substances in descending order were limonene > cold pressure oil > lemon >grapefruit. The antimutagenicity rate and ability of the three extracts were limonene: 18–23%; cold-pressed lemon oil: 18–22%; and steam distilled lemon essential oil: 8–16%. The obvious anti- mutagenicity effects against the PAHs mutagenicity of roasted fish skins can be found in citrus fruits essential oil extraction.

Scattering hyperspectral technology is a nondestructive testing method with many advantages. Here, we propose a method to improve the accuracy of egg freshness, research the influence of incident angles of light source on the accuracy and explain its mechanism. A variety of weak classifiers classify eggs based on the spectra after preprocessing and feature wavelength extraction to obtain three classifiers with the highest accuracy. The three classifiers are used as metamodels of stacking ensemble learning to improve the highest accuracy from 96.25% to 100%. Moreover, the highest accuracy of scattering, reflection, transmission and mixed hyperspectral of eggs are 100.00%, 88.75%, 95.00% and 96.25%, respectively, indicating that the scattering hyperspectral for egg freshness detection is better than that of the others. In addition, the accuracy is inversely proportional to the angle of incidence due that the smaller the incident angle, the camera collects a larger proportion of scattering light, which contains more biochemical parameters of an egg than that of reflection and transmission. These results are very important for improving the accuracy of non-destructive testing and selecting the incident angle of the light source, and have potential applications in online non-destructive testing.

The water cushion depth of stilling basin with shallow-water cushion is a key factor that affects the flow regime of hydraulic jump in the basin. However, the specific depth at which the water cushion is considered as “shallow” has not be stated clearly for now, and only conceptual description is provided. This paper attempts to specify the best water cushion depth based on the flow regime of hydraulic jump and underflow speed; namely, in case of critical hydraulic jump in the basin, the best water cushion depth is located where the minimum distance to the bottom plate of the stilling basin is 1/5~1/4 of the water cushion depth. The theoretical analysis indicates, at different inclinations of discharge chute (θ) and depth ratios of inlet (m), instead of monotonic change, the Froude number (Fr) at inlet of the stilling basin with shallow-water cushion firstly reduces and then increases as the flow velocity at discharge chute inlet (V) increases; the parameters of inflection point (critical flow velocity and critical Fr) increase as the inclinations of discharge chute (θ) and depth ratios of inlet (m) increase. Such regularity is the theoretical basis for selecting representative study cases. The reliability of the large eddy simulation calculation results are verified by a model test; in the paper, 30 cases including five different Froude numbers and six shallow-water cushion depths are selected, for calculating the hydraulic factors such as flow profile, flow regime and flow velocity in the stilling basin with shallow-water cushion; and the varying pattern between the best depth of stilling basin with shallow-water cushion (depth-to-length ratio) and the inflow Froude number is obtained which indicates that the best depth of stilling basin with shallow-water cushion varies little as the change of the Froude number before reaching the critical Froude number; however, the best depth-to-length ratio of stilling basin with shallow-water cushion increases as the Froude number increases after the critical Froude number is reached. The study results in this paper are of reference significance to design and calculation of the stilling basin with shallow-water cushion.

Novel Ca3(BTC)2 metal-organic frameworks with different sizes and shapes constructed by Ca2+ and trimesic acid as metal center and ligands respectively were synthesized by a surfactant-assisted method. The relationship between the quantity of surfactant and the particle morphology of the product have been further studied. The samples were characterized by scanning electron microscope, powder X-ray diffraction and Inductively coupled plasma mass spectrometry. The results indicated that the size and shape of Ca3(BTC)2 could be regulated by changing the quantity of surfactant. Rod- and sheet-like Ca3(BTC)2 MOFs have been readily availabled. The removal kinetics of heavy metals of Pb(II) were also studied by rod-like Ca3(BTC)2. The results showed that as-synthesized Ca3(BTC)2 could effectively remove heavy metals of Pb(II) from the sewage.

The buildup dynamics of diode-pumped passively mode-locked solid-state laser is thoroughly explored by the real-time measurement with temporal sampling rate up to 40 GHz. A concise cavity is developed to ensure the transient dynamics purely arising from the gain medium and saturable absorber. Experimental results reveal that the laser output in the buildup process exhibits numerous passively Q-switched pulses followed with a damped relaxation oscillation prior to the stable mode locking. Furthermore, it is confirmed that the laser output has already displayed single clean mode-locked pulses inside the first several Q-switched envelopes before stepping into the stage of relaxation oscillation. The present real-time exploration is expected to provide important information for practical applications with temporal modulation of the pump intensity.

The parameter estimation problem for polynomial phase signals (PPSs) arises in a number of fields, including radar, sonar, biology, etc. In this paper, a fast algorithm of parameter estimation for monocomponent PPS is considered. We propose the so-called LSU-EKF estimator, which combines the least squares unwrapping (LSU) estimator and the extended Kalman filter (EKF). First, the coarse estimates of the parameters of PPS are obtained by the LSU estimator using a small number of samples. Subsequently, these coarse estimates are used to initial the EKF. Monte-Carlo simulations show that the computation complexity of the LSU-EKF estimator is much less than that of the LSU estimator, with little performance loss. Similar to the LSU estimator, the proposed algorithm is able to work over the entire identifiable region. Moreover, in the EKF stage, the accurate estimated results can be output point-by-point, which is useful in real applications.

Background: Accurate prediction of patients’ response to therapy is clinically indispensable, howbeit challenging. With increased understanding of the human genome and malignancies, there is the renaissance of in silico pharmacogenomics with renewed interest in drug response predictability based on gene-drug interaction. Objective: Evidence-based transcript-proteome profiling is essential for synthesizing clinically applicable algorithms for predicting response to anticancer therapy, including immune checkpoint blockade (ICBT); thus, saving physicians’ time, reducing polypharmacy, and curtailing unnecessary treatment expense. In this study, we tested and validated the hypothesis that a selected proteomic signature in ICBT-naïve patients is sufficient for the prediction of response to ICBT. Methods: Using a multimodal approach consisting of computational pharmacogenomics, transcript-proteome analytics, mathematical modeling, and machine learning systems; we delineated therapy-sensitivity and stratified patients into graduated response groups based on their proteomic profile. Protein expression levels in our cohort tissue specimens were evaluated based on T cell- and non-T cell- inflamed phenotypes by immunohistochemistry. Results: We established β-catenin, PDL1, CD3 and CD8 expression-based ICBT response model. Statistical regression models validated the predictive association between our predefined algorithms and therapeutic outcome. Interestingly, our 4-gene prediction classifier was constitutively independent of tumor tissue origin, correctly stratified patients into high-, low-, and non- responders pre-treatment, with high prediction accuracy, and exhibited good association with patients’ performance status and prognosis (p < 0.01). Conclusion: Our findings demonstrate the possibility of accurate proteomics based ICBT response prediction and provide a putative basis for drug response prediction based on selective proteome profile in untreated cancer patients.

Soil enzyme activity can be affected by both production and degradation, as enzymes can be degraded by proteases. However, the impact of nutrient addition on enzyme activity is often solely attributed to changes in enzyme production without fully considering degradation. Here, we demonstrated that the activities of β-1,4-glucosidase (BG), β-D-cellobiohydrolase (CBH), β-1,4-Xylosidase (BX), and β-1,4-N-acetyl-glucosaminnidase (NAG) were comparable in nitrogen (N) and phosphorus (P) fertilized soils and the unfertilized control under field conditions, but the reduction in activity was substantially greater in the fertilized soils during short-term laboratory incubation. The results show that the interruption of the natural, continuous supply of organic matter or non-soil microbial-derived enzymes, which typically occurs under field conditions, leads to a more significant reduction in apparent enzyme activities in fertilized soils compared to unfertilized control. This may be attributed to the higher abundance of protease in fertilized soils, resulting in faster enzyme degradation. Interestingly, P fertilization alone did not have a similar effect, indicating that N fertilization is likely the main cause of the larger decreases in enzyme activity during incubation in fertilized soils compared to unfertilized control soils, despite our study site being poor in P and rich in N. These findings highlight the importance of considering enzyme degradation when investigating material dynamics in forest ecosystems, including the impact of nutrient addition on enzyme activity, as enzyme production alone may not fully explain changes in apparent enzyme activity.

Blocking the interaction of the SARS-CoV-2 spike protein with the human angiotensin-converting enzyme II (hACE2) protein serves as a therapeutic strategy for treating COVID-19. Traditional Chinese medicine (TCM) treatments containing bioactive products could alleviate the symptoms of severe COVID-19. However, the emergence of SARS-CoV-2 variants has complicated the process of developing broad-spectrum drugs. As such, the aim in this study was to explore the efficacy of TCM treatments for SARS-CoV-2 variants through targeting the interaction of the viral spike protein with the hACE2 receptor. The antiviral activity was systematically evaluated using a pseudovirus system. Scutellaria baicalensis was found to be effective against SARS-CoV-2 infection through affecting the interaction of viral spike protein with the hACE2 protein. The active molecules of S. baicalensis were identified and analyzed. Baicalein and baicalin, a flavone and a flavone glycoside, respectively, found in S. baicalensis, exhibited strong inhibitory activities, targeting the viral spike protein or hACE2 protein, respectively. Under optimized conditions, virus infection was inhibited by 98% via baicalein-treated pseudovirus and baicalin-treated hACE2. In summary, we identified the potential SARS-CoV-2 inhibitors of the interaction of the Omicron spike protein and hACE2 receptor from S. baicalensis. Future studies on the therapeutic application of baicalein and baicalin against SARS-CoV-2 variants are needed.

The concentration of heavy metals in sediment is an important factor for assessing the quality of the nearshore environment. Geochemical background values are the normal concentrations of heavy metals in the natural environment. The use of different background values results in different evaluation results. Heavy metal (Cu, Pb, Zn, Cr, Cd, As, and Hg) concentration profiles along a sediment core were investigated to obtain background values and assess the depositional processes and contamination levels in Laizhou Bay. Apart from As and Hg, all other metals had similar distribution patterns and could be divided into four stages since marine isotope stage (MIS) 2. The results of the enrichment factor, geoaccumulation index, Pearson’s correlation coefficient, Nemerow pollution index, principal component analysis, and potential ecological risk index showed that element enrichment or contamination in the core sediments was absent and that all heavy metals were mainly naturally sourced. The changes in heavy metals since MIS 2 in the core sediments were predominantly related to the sedimentary environment, sediment sources, and mean grain size. The average values of the heavy metals in the U2 unit formed during the Middle Holocene can be used as reference values for background values.

Background: The aim of this study was to investigate the risk of obstructive sleep apnea (OSA) among ankylosing spondylitis (AS) patients in a nationwide population. Methods: We conducted a nationwide cohort study between 2003 and 2013 using the Taiwan National Health Insurance Research Database. The AS cohort included 2210 patients who were newly diagnosed between 2003 and 2013. Randomly selected non-AS controls were matched at a 1:4 ratio based on age, sex and index date. The endpoint of OSA was occurrence or the end of 2013. Cumulative incidences, hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated after adjusting for age, gender, comorbidities and co-medications. Multivariate analyses were performed using Cox proportional hazards model. Due to violation of the proportionality assumption, landmark analysis was conducted to explore the risk of OSA during specific follow-up periods. Results: The adjusted HR (aHR) of OSA for the AS group was 2.826 (95% C.I. = 1.727–4.625) compared to the control group. On landmark analysis, aHR was 7.919 (95% C.I. = 3.169–19.792) for AS group 0–24 months from index date, and decreased to 1.816 (95% C.I. = 0.944–3.494) at ≥ 24 months from index date. On subgroup analyses increased risks of OSA in AS group compared to the control group were found for both males and females (aHRs were 4.533 (95% C.I. = 1.441–14.262) and 2.672 (95% C.I. = 1.522–4.692) for females and males, respectively). On age stratified analysis, there was significant risk only for the 40–59 age group with aHR of 3.913 (95% C.I. = 1.890–8.102). Conclusions: A higher risk of developing OSA was found among newly diagnosed AS cohort during the 12-year follow-up period, especially within 2 years after AS index date and in the 40–59 age group.

Saikosaponin (SS) a is a compound with various pharmacological properties and easily degraded into SSb1 and SSg in acid condition. In present work another two new degradation products of SSa formed under acid hydrolytic condition were detected and isolated by analytical and semi-preparative liquid chromatography technology, furthermore their structures were characterized as hydroxyl-saikosaponin a and SSb2 by spectral analysis, which is not only essential in stability-indicating method development and validation but also could be used as a worst case to assess the analytical method performance of SSa. Moreover their structural transformation pathways were also proposed.

Novel multifunctional fluorescent chemosensors composed of electrospun (ES) nanofibers with high sensitivity toward pH, mercury ions (Hg²⁺), and temperature were prepared from poly(N-Isopropylacrylamide-co-N-methylolacrylamide-co-rhodamine derivative) (poly(NIPAAm-co-NMA-co-RhBN2AM)) by employing electrospinning process. NIPAAm and NMA moieties provide hydrophilic and thermo-responsive properties (absorption of Hg²⁺ in aqueous solutions), and chemical cross-linking sites (stabilization of the fibrous structure in aqueous solutions), respectively. The fluorescent probe, RhBN2AM is highly sensitive toward pH and Hg²⁺. Synthesis of poly(NIPAAm-co-NMA-co-RhBN2AM) with different compositions were carried on via free-radical polymerization. ES nanofibers prepared from sensory copolymers with a 71.1:28.4:0.5 NIPAAm: NMA: RhBN2AM ratio (P3 ES nanofibers) exhibited significant color change from nonfluorescent to red fluorescence while sensing pH or Hg²⁺, and high reversibility of on/off switchable fluorescence emission when Hg²⁺ and ethylenediaminetetraacetic acid (EDTA) were sequentially added. The P3 ES nanofibrous membranes had a higher surface-to-volume ratio to enhance their performance than did the corresponding thin films. In addition, the fluorescence emission of P3 ES nanofibrous membranes exhibited second enhancement above the lower critical solution temperature. Thus, the ES nanofibrous membranes prepared from P3 with on/off switchable capacity and thermo-responsive characteristics can be used as multifunctional sensory devise for specific heavy transition metal (HTM) in aqueous solutions.

This paper aims to develop a hierarchical risk assessment model using the newly-developed evidential reasoning (ER) rule, which constitutes a generic conjunctive probabilistic reasoning process. In this paper, we first provide a brief introduction to the basics of the ER rule and emphasize the strengths for representing and aggregating uncertain information from multiple experts and sources. Further, we discuss the key steps of developing the hierarchical risk assessment framework systematically, including (1) formulation of risk assessment hierarchy, (2) representation of both qualitative and quantitative information, (3) elicitation of attribute weights and information reliabilities, (4) aggregation of assessment information using the ER rule and (5) quantification and ranking of risks using utility-based transformation. The proposed hierarchical risk assessment framework can potentially be implemented to various complex and uncertain systems. A case study on the fire/explosion risk assessment of marine vessels demonstrates the applicability of the proposed risk assessment model.

Currently, data regarding optimal treatment modality, response, and outcome specifically for N3 head and neck cancer are lacking. This study aimed to compare the treatment outcomes between definitive concurrent chemoradiotherapy (CCRT) to the neck and upfront neck dissection followed by adjuvant CCRT. 93 N3 squamous cell carcinoma head and neck cancer patients were included. Primary tumor treatment was divided to definitive CCRT (CCRT group) or curative surgery followed by adjuvant CCRT (surgery group). Neck treatment was also classified into two treatment modalities: definitive CCRT to the neck (CCRT group) or curative neck dissection followed by adjuvant CCRT (neck dissection group). Overall, the 2-year overall survival (OS), local recurrence-free survival (LRFS), regional recurrence-free survival (RRFS), and distant metastasis-free survival (DMFS) were 51.8%, 47.3%, 45.6%, and 43.6%, respectively. In both oropharyngeal cancer and nonoropharyngeal cancer patients, in terms of OS, LRFS, RRFS or DMFS no difference was noted regarding primary tumor treatment (CCRT vs. surgery) or neck treatment (CCRT vs. neck dissection). In summary, N3 neck patients treated with definitive CCRT can achieve similar outcomes to those treated with upfront neck dissection followed by adjuvant CCRT. Cautions should be made to avoid overtreatment for this group of patients.

Shallow landslides pose serious threats to human existence and economic development, especially in the Himalayan areas. Landslide susceptibility mapping (LSM) is a proven way for minimizing the hazard and risk of landslides. Modeling as an essential step, various algorithms have been applied to LSM. In this study, information value (IV) and logistic regression (LR) were selected as representatives of the conventional algorithms, categorical boosting (CatBoost) and conventional neural networks (CNN) as the advanced algorithms, for LSM in Yadong county, and their performance was compared. To begin with, 496 historical landslide events were compiled into a landslide inventory map, followed by a list of 11 conditioning factors, forming a data set. Secondly, the data set was randomly divided into two parts, 80% of which was used for modeling and 20% for validation. Finally, the area under the curve (AUC) and statistical metrics were applied to validate and compare the performance of the models. The results showed that the CNN model performed the best (AUC 0.974 and accuracy=93.3%), while the LR model performed the worst (AUC 0.974 and accuracy=93.3%) and CatBoost model performed better (AUC 0.974 and accuracy=93.3%). Besides, the LSM constructed by the CNN model did a more reasonable prediction of the distribution of susceptible areas. As for feature selection, did a more detailed analysis of conditioning factors but the results were uncertain. The result analyzed by GI may be more reliable but fluctuates with the amount of data. The conclusion reveals that the accuracy of LSM can be further improved with the advancement of algorithms, by determining more representative features, which serve as a more effective guide for land use planning in the study area or other highlands where landslides are frequent.

Liquid biopsy is a rapidly emerging field which involves the minimal/non-invasive assessment of signature somatic mutations through analysis of circulating tumor DNA (ctDNA) shed by tumor cells in bodily fluids. The broad, unmet need for liquid biopsy lung cancer detection is the lack of multiplex platform that can detect a mutation panel of lung cancer genes using minimum amount of sample, especially for ultra-short ctDNA (usctDNA). Here we developed a non-PCR and non-NGS-based single droplet based multiplexing microsensor technology “Electric Field-Induced Released and Measurement (EFIRM) Liquid Biopsy” (m-eLB) for lung can-cer-associated usctDNA. The m-eLB provides multiplexable assessment of usctDNA within a single droplet of biofluid in only one well of micro-electrodes, as each electrode coated with dif-ferent probes for the ctDNA. In this m-eLB prototype, it demonstrates accuracy for 3 tyrosine ki-nase inhibitor related EGFR target sequences in synthetic nucleotides. The accuracy for the multi-plexing assay has an AUC of 0.98 for L858R, Ex19del, AUC of 0.94 for Ex19 deletion and AUC of 0.93 for T790M. By combining the 3 EGFR assay together, the AUC was 0.97 for the multiplexing assay.

In this work, numerical simulations for the absorption and scattering efficiencies of spheroid core–shell nanoparticles (CSNs) were conducted and studied using the discrete-dipole approximation method. The characteristics of surface plasmon resonances (SPR) depend upon shell thickness, the compositions of the core and shell materials, and the aspect ratio of the constructed CSNs. We used different core@shell compositions, specifically Au@SiO₂, Ag@SiO₂, Au@TiO₂, Ag@TiO₂, Au@Ag, and Ag@Au, for extinction spectra analysis. We also investigated coupled resonance mode wavelengths by adjusting the composition’s layer thickness and aspect ratio. In this study, we show that the extinction efficiency of the Ag@TiO₂ core–shell nanoparticles (CSNPs) was higher than that of the others, and we examined the impact of TiO₂ shell thickness and Ag core radius on SPR peak positions. From the extinction spectra we found that the Ag@TiO₂ nanoparticle had better refractive index sensitivity and figure of merit when the aspect ratio was set to 0.3. All of the experimental results proved that the tunability of these plasmonic resonances was highly dependent on the material used, the layer thickness, and the aspect ratio of the core@shell CSNPs.

Contaminants of Emerging Concern (CECs), a new category of contaminants in limelight, is a major issue of global concern. The pervasive nature of CECs and its harmful effects, such as cancer, reproductive disorders, neurotoxicity etc., make the situation alarming. The perilous nature of CECs lies in the fact that even very small concentration of CECs can cause great impacts on living beings. It also has a nature of bioaccumulation. Thus, it is the ultimate need to have efficient sensors for detection of CECs to ensure safe living environment. Electrochemical sensors are an efficient platform for CEC detection as they are highly selective, sensitive, stable, reproducible, and prompt, and can detect very low concentrations of analyte. Major classes of CECs are pharmaceuticals, illicit drugs, personal care products, endocrine disruptors, newly registered pesticides, and disinfection by-products. This review focusses on CECs, including their sources and pathways, health effects caused by them, and electrochemical sensors as reported in literatures under each category for the detection of major CECs.

Since the outbreak of the COVID-19 pandemic, patients infected with COVID-19 may experience abnormal heart rates, posing potential health risks. This study proposes a non-contact method for measuring heart rate (HR) and heart rate variability (HRV) to effectively reduce the risk of infection and assist healthcare professionals in more accurate diagnosis and treatment. In this study, except for the different image acquisition method, other research processes and methods are similar to the research methods in [15]. The image acquisition method is changed from forehead image to palm image. The new non-contact measurement performance of the proposed method can effectively not only avoid infection concerns but also obtain heart rate and HRV quickly and conveniently, providing higher accuracy for physiological parameters, root mean square error (RMSE), and mean absolute percentage error (MAPE) compared to those in recently published papers.