It is always a difficult task to assign the peaks recorded from vibrational spectrum. Herein we explored a new pathway of density functional theory (DFT) simulation to present three kinds of spectra of ice XIV and can be referenced as inelastic neutron scattering (INS), IR, and Raman experimental spectrum. The INS spectrum is proportional to phonon density of states (PDOS) while the photon scattering signals reflect the normal vibration frequencies near the Brillouin zone (BZ) center. Based on good agreements with experimental data, we identified the relative frequency and made scientific assignments by normal vibration modes analysis. The debating two hydrogen bond (H-bond) peaks among ice phases from INS have been discussed and the dynamic process of H-bond vibrations were found to be classified into two basic modes. we deduce that two H-bond modes are a general rule among ice family and more works are ongoing to investigate this subject.

In 2015, the new installed capacity of global renewable energy power generation exceeded the newly installed capacity of conventional energy power generation, marking a structural change in the construction of the global power system. With the continuous improvement of wind energy utilization technology, the global wind power industry has developed rapidly in recent years. The world's available wind energy is 20 billion kilowatts and has become one of the most economical green power. In China, wind power has become the third largest source of electricity, with the installed capacity increasing from 3.1% in 2010 to 9.2% in 2017. In 2017, China's new installed capacity was 19,660 MW, accounting for 37.45% of the world's new installed capacity. This paper evaluates and compares the efficiency of wind power industry in the four regions of eastern, central, western and northeastern China through EBM models based on radial and non-radial factors. This paper discusses the contribution of China's wind power industry to CO2 emission reduction from the relationship between installed capacity efficiency and CO2 emission reduction efficiency. The conclusions show that the overall efficiency score and ranking of wind power in 2013-2017 is the best in the eastern region, followed by the northeast region and the western and central regions.

A typical vibrational spectrum in the ice phase has four separate bands: translation, libration, bending and stretching. Ice X, the final ice phase under high pressure, shows an exotic vibrational spectrum. Theoretically, an ideal crystal of ice X only has one peak at 998 cm-1 for Raman scattering and two peaks at 450 cm-1 and 1507 cm-1 for infrared absorption in this work. These three characteristic peaks are indicators of the phase transition between ice VII/VIII and ice X. Despite much experimental and theoretical work on ice X, only this study has clearly indicated these characteristic peaks in the region of the IR band. The phonon density of states shows quite different features than ice VIII, which could be verified by inelastic neutron scattering in the future. The dynamic processes of 15 vibrational normal modes are discussed and the typical hydrogen bonds are missing.

We report a prebiotically relevant solution to the N1-ribosylation of pyrimidine nucleobases, a well-known challenge in the RNA World hypothesis. It is found that the presence of metal cations and clay mineral enables the previously unachievable direct ribosylation of uracil, providing by far the highest yield. Spectroscopy and chromatography analyses confirmed the formation of ribosylated uracil. The method can also be extended to the ribosylation of 2-pyrimidinone. These findings are also compatible with the metal-doped-clay model developed by our lab for the unified route of the selection of ribose and subsequent syntheses of nucleotide and RNA.

The twisted Wang transform distribution family, defined as the composition of parameter shifted inverse CDF function with an original CDF function, is found to be most suitable for matching low shape factor distributions, characterizing hard to fit or to simulate reinsurance portfolio losses for some perils from our previous study. Among them, the best form for matching a hard-to-fit empirical loss distribution for a specific peril, is the Exponential Fractional Extra Power 0 Distribution in (0,1) with CDF:.The simplest yet still a good form of this family is the Transformed Hyperbolic Tangent Distribution with CDF:,which has analytical formulas for the moments. The twisted Wang transform distribution family is compared and confirmed to be superior to all other well-known distribution families through extensive numerical optimization practice, distribution forms guesses, and computer-aided exploration experiments.

A previously undescribed malformed half-engorged female Dermacentor nuttalli was noticed in our tick specimen collection. This tick exhibited abnormal legs compared with normal D. nuttalli ticks. The first leg on the right side and the third leg on the left side were much smaller than normal ticks, and reduced to a small and degenerated appendix, respectively. Both of their pulvillus and claws were absent.

Sedimentary microfacies division is the basis of oil and gas exploration research. The traditional sedimentary microfacies division mainly depends on human experience, which is greatly influenced by human factor and is low in efficiency. Although deep learning has its advantage in solving complex nonlinear problems, there is no effective deep learning method to solve sedimentary microfacies division so far. Therefore, this paper proposes a deep learning method based on DMC-BiLSTM for intelligent division of well-logging—sedimentary microfacies. First, the original curve is reconstructed multi-dimensionally by trend decomposition and median filtering, and spatio-temporal correlation clustering features are extracted from the reconstructed matrix by Kmeans. Then, taking reconstructed features, original curve features and clustering features as input, the prediction types of sedimentary microfacies at current depth are obtained based on BiLSTM. Experimental results show that this method can effectively classify sedimentary microfacies with its recognition efficiency reaching 96.84%.

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.

This work presents a new scheme for autonomous control and obstacle detection of a catamaran unmanned surface vessel. Based on the Newtonian mechanics, hydrodynamics, and maneuvering modelling group modelling principles in the attached coordinate system, a three-degree-of-freedom motion model of the catamaran unmanned surface vessel is constructed. The fuzzy inference method is used to overcome the drawback that the traditional PID control cannot tune the PID parameters online, and the trajectory controller is designed. Meanwhile, 3D LIDAR is used to achieve obstacle detection. The results of the trajectory tracking simulations and experiments verify the accuracy of the model design and the effectiveness of the autonomous control design.

The surface velocity of the Amery Ice Shelf (AIS) is vital to assessing its stability and mass balance. Previous studies have shown that the AIS basin has a stable multi-year average surface velocity. However, spatiotemporal variations in the surface velocity of the AIS and the underlying physical mechanism remain poorly understood. This study combined offset tracking and DInSAR methods to extract the monthly average surface velocity of the AIS and obtained the inter-annual surface velocity from the ITS_LIVE product. An uneven spatial distribution in inter-annual variation of the surface velocity was observed between 2000–2022, although the magnitude of variation was small at less than 20.5 m/yr. The increase and decrease in surface velocity on the eastern and western-central sides of the AIS, respectively, could be attributed to the change in the thickness of the AIS. There was clear seasonal variation in monthly average surface velocity at the eastern side of the AIS between 2017–2021, which could be attributed to variations in the area and thickness of fast-ice and also to variations in ocean temperature. This study suggested that changes in fast-ice and ocean temperature are the main factors driving spatiotemporal variation in the surface velocity of the AIS.

This study introduces a novel predictive model for atomization droplet size, developed through comprehensive data collected under elevated temperature and pressure conditions using a twin swirl airblast nozzle. The model, grounded in flow instability theory, has been meticulously parameterized using the Particle Swarm Optimization (PSO) algorithm. Through rigorous analysis, including analysis of variance (ANOVA), the model has demonstrated robust reliability and precision, with a maximum relative error of 19.3% and an average relative error of 6.8%. Compared to the classical atomization model by Rizkalla and Lefebvre, this model leverages theoretical insights and incorporates a range of interacting variables, enhancing its applicability and accuracy. Spearman correlation analysis reveals that air pressure and the air pressure drop ratio significantly negatively impact droplet size, whereas the fuel-air ratio (FAR) shows a positive correlation. Experimental validation at ambient conditions shows that the model is applicable with a reliability threshold of ≥0.13 and highlight the predominance of the pressure swirl mechanism over aerodynamic atomization at higher fuel flow rates (q > 1.25 kg/h). This research effectively bridges theoretical and practical perspectives, offering critical insights for the optimization of airblast nozzle design.

Theoretical physics addresses the fundamental principles of nature and the mysteries of the universe. In the last century, the theory of relativity challenged people's understanding of time and space, while quantum mechanics revealed various forms of energy. However, the concept of gravity remains elusive. All matter in the universe is composed of energy that can be converted into other forms, yet it is always conserved. However, achieving a state of equilibrium, represented by the equal sign, can be challenging to achieve on both macro and quantum scales. A phenomenon that can transition from one state to infinity is called collision and is essential for understanding natural phenomena and physical processes throughout the universe. In the study of general relativity cannot be three-dimensional problems to gain mathematical inspiration, understand the application of new dimensions. Here, we elucidate the nature of gravity, which inspires the solution of the Riemann hypothesis. Our results show that the conduction mode of dimensional energy is defined by Euler's formula. And a special mode of collision is derived which translates into vibration.

This empirical research is part of a larger project beginning in 2020 and ongoing until 2023 exploring the impact of the COVID-19 pandemic on young caregivers aged 5-25 years and their families in Canada. Utilizing the social determinants of health as a conceptual framework, this case study emphasizes the voices of professionals offering services to young caregiver clients during the pandemic, and explores their perspectives on the impact of the pandemic on young caregivers and their families. Across three (3) different organizations offering programs and services to young caregiver clients in Ontario, six (6) individual interviews were conducted with directors/program managers and four (4) group interviews were conducted with thirteen (13) staff members who worked directly with young caregivers and their families. Nineteen (19) service providers participated in total. The results of this study highlight five (5) primary themes that emerged through data analysis: i) the role of service providers, ii) the impact of the COVID-19 pandemic on organizations and service providers supporting young caregivers and their families, iii) barriers for service users, iv) helpful resources for service providers and organizations, and v) resources needed/preferred by service providers and organization. The pandemic significantly impacted young caregivers and their families, as reported by professionals, and organizations working with young caregivers and their families were tasked with addressing increased service demands and adapting service delivery to follow public health guidelines.

This study uses machine learning to predict the convergence results of the Duffing equation with and without damping. The Duffing equation represents a nonlinear second-order differential equation with interesting behavior in undamped free vibration and forced vibration with damping. Convergence alternates randomly between 1 and -1 in undamped free vibration, depending on initial conditions. For forced vibration with damping, multiple factors influence vibration patterns. We utilize the fourth-order Runge-Kutta method to collect convergence results for both conditions. Machine learning techniques, specifically the long short term memory (LSTM) and LSTM-Neural Network (LSTM-NN) method, are employed to predict these convergence values. The LSTM-NN model is a hybrid approach that combines the LSTM method with the addition of hidden layers of neurons. Both the LSTM and LSTM-NN models are thoroughly explored and analyzed in this research. The research process involves three stages: data preprocessing, training, and verification. The results show that the LSTM-NN model becomes more adept at predicting binary datasets, boasting an impressive accuracy of up to 98%. However, when it comes to predicting multiple solutions, the traditional LSTM method outperforms the LSTM-NN approach.

This qualitative research study is a part of a larger research project exploring the experiences of young caregivers aged 5-26 years and their families navigating the COVID-19 pandemic between 2020 to 2023. Data was collected from 14 young caregivers who participated in baseline interviews. The central research question guiding this study: What was, is, and will be the impact of changing public health restrictions on young caregivers and their families during the pandemic and pandemic recovery? Seven themes emerged through analysis: 1) Navigating Care During the Height of Public Health Restrictions, 2) Neighbourhood and Built Environment During the Pandemic, 3) Perceptions Towards COVID and Public Health Restrictions/Efforts, 4) The Impact of Public Health Restrictions on Relationships, 5) Mental Health Challenges of Being a Young Caregiver During a Pandemic, 6) Navigating Formal Services and Supports and 7) Recommendations from Young Caregivers. The findings from this empirical research suggest that young caregivers found it easier to navigate their caregiving responsibilities when public health restrictions and work-from-home mandates were initially implemented, however, this later changed due to challenges in finding respite from caregiving, maintaining social connections with friends, creating personal space at home, and finding adequate replacements of programs once offered in-person.

The ZIPs (ZRT/IRT-like proteins) play critical roles in the absorption, transport, and intracellular balance of metal ions essential for various physiological processes in plants. However, little is known about the pan-genomic characteristics and properties of ZIP genes in cucumber (Cucumis sativus L.). In this study, we identified 10 CsZIP genes from the pan-genome of 13 C. sativus accessions. Among them, only CsZIP10 showed no variation in protein sequence length. We analyzed the gene structure, conserved domains, promoter cis-elements, and phylogenetic relationships of these 10 CsZIP genes derived from "9930". Based on phylogenetic analysis, the CsZIP genes were classified into three branches. Amino acid sequence comparison revealed the presence of conserved histidine residues in the ZIP proteins. Analysis of promoter cis-elements showed that most promoters contained elements responsive to plant hormones. Expression profiling in different tissues showed that most CsZIP genes were expressed at relatively low levels in C. sativus leave, stem, and tendril, and CsZIP7 and CsZIP10 were specifically expressed in root, indicating their potential involvement in the absorption and transport of metal ions. Transcriptomic data indicated that these 10 ZIP genes displayed responses to both downy mildew and powdery mildew, and CsZIP1 were significantly downregulated after both salt and heat treatments. In conclusion, this study deepens our understanding of the ZIP gene family and enhances our knowledge of the biological functions of CsZIP genes in C. sativus.

HybridAC/DC microgrids(HMG) are emerging as an attracting method for integrating the AC/DC distributed energy resources(DERs) with the features of high-performance and low-cost. In the isolated hybrid AC/DC microgrid (IHMG), the key problem is how to balance the power variation and regulate the voltage and frequency. Various energy storage systems (ESS)and interlinking converter (IC) technologies are viable for this application. The present study proposes a novel unified power flow model to evaluate and compare the abilities of the ESS with different connection topologies and ICs with different control approaches to maintain the voltage and frequency stability of the IHMG. In order to investigate the performance of the proposed scheme, five operation modes of the IHMG are defined and explained. The classification is based on the connection topologies and control modes of the ESS/IC in the IHMG. Then, a set of generic PF equations are derived. Moreover, three binary matrices are applied in the construction of the unified power equations. These matrices are used for describing the running state of the IHMG. Finally, in order to verify the proposed scheme, it is applied to several case studies of the IHMG. The operation characteristics of multi-DC subgrids IHMG in different modes, particularly when an external disturbance occurs, are investigated.

The decline in Pinus sylvestris var. mongolica in the introduction area has had a high profile in recent years. For the ecological restoration, management and silvicultural design of Mongolian pines in the introduction area, it is necessary to conduct a comprehensive and in-depth study on the ecological adaptation mechanism of Mongolian pines in provenances. The ecological process of water and nutrient accumulation as well as the influence of environmental factors on the photosynthetic physiology are the key to revealing the ecological adaptation mechanism of Mongolian pines. According to the differences of climate in the distribution area of Mongolian pines, sampling sites were set up, the effects of environmental factors on leaf δ13C and the relationship between leaf δ13C and nutrient content were analyzed. The results showed that leaf δ13C values were ranging from - 29.7 ‰ to - 23.76 ‰. The ecological stoichiometry, including LC (522.81 mg·g-1), LN (16.04 mg·g-1), LP (1.19 mg·g-1) and L-N:P (13.56), indicated that leaf photosynthesis and water use efficiency is greatly affected by environmental conditions, Mongolian pines had strong ability of carbon fixation, and its growth was obviously restricted by nitrogen. Although there was no significant correlation between δ13C with stoichiometric parameters in leaf, photosynthesis was the key link in the process of carbon fixation. It also showed that Pinus sylvestris var. mongolica was a stomatal limited plant. Leaf δ13C had significant correlation with climatic factors. VPD is the dynamic factor affecting the photosynthetic physiological process in leaves. Air and soil moisture are the dominate factors affecting the leaf stomatal conductance and determines leaf δ13C value, while other factors indirectly affect leaf δ13C by its impact on relative humidity or soil water content. Soil phosphorus content affected by clay is a key factor affecting soil water availability and soil nutrient cycling. Photosynthetic process in leaf is the dynamic process affecting the nutrient accumulation.

Raman spectroscopy is a type of inelastic scattering that provides rich information about a sub-stance based on the coupling of the energy levels of their vibrational and rotational modes with incident light. It has been applied extensively in many fields. As there is an increasing need for remote detection of chemicals in planetary exploration and anti-terrorism, it is urgent to develop a compact and easily transportable fully automated remote Raman detection system for trace detection and identification of information with high-level confidence about the target’s compo-sition and conformation in real-time and for real field scenarios. Here, we present an unmanned vehicle-based remote Raman system, which includes a 266 nm air-cooling passive Q-switched nanosecond pulsed laser of high-repetition frequency, a gated ICMOS, and an unmanned vehicle. This system obtains good spectral signals from remote distances ranging from 3 m to 10 m for simulating realistic scenarios, such as aluminum plate, woodblock, paperboard, black cloth, and leaves, and even for detected amounts as low as 0.1 mg. Furthermore, a CNN-based algorithm is implemented and packaged into the recognition software to achieve fast and more accurate de-tection and identification. This prototype provides a proof-of-concept for an unmanned vehicle with accurate remote substance detection in real-time, which can be helpful for remote detection and identification of hazardous gas, explosives, their precursors, and so forth.

Clarifying the impact mechanism of digital transformation of enterprises on the M&A efficiency of listed companies can provide a factual basis for improving capital market regulatory policies. Taking the mergers and acquisitions of listed companies from 2007 to 2021 as a research sample, the influence mechanism of the digital transformation degree of companies on their M&A efficiency was studied. The research results show that the digital transformation of listed companies will improve their M&A efficiency. Digital transformation will reduce the degree of mispricing of stocks of M&A companies, curb conflicts between managers and agents of M&A companies, and improve their M&A efficiency. Further research finds that the promotion effect of digital transformation on M&A efficiency is more significant in non-state-owned companies, with a higher degree of financing constraint and high analyst attention. In the future, regulatory authorities should actively promote the digital transformation of listed companies, curb mispricing and management agency problems in the capital market with digital governance, and improve the efficiency of mergers and acquisitions in the capital market.

Purpose:To explore (theoretically) the key parameters and their influence on the time profiles of photosensitizer (riboflavin), free radicals, singlet oxygen, oxygen and the efficacy of corneal collagen crosslinking (CXL)in both type-I and oxygen-mediated type-II mechanisms, specially the role of oxygen and the initiator regeneration. Methodology:Coupled kinetic equations are derived and numerically solved under the quasi-steady state condition for the 2-pathway mechanisms of CXL. The key parameters explored include (bI, V, Q', K, K',Q,P) and their influence on the time profiles of photosensitizer (riboflavin, C), radicals (R), singlet oxygen(S), oxygen (X) and efficacy (E), parameters of (K,K',Q) define the relative strength of type-I and type-II process. The oxygen depletion profile, X(t), and the associated singlet oxygen, S(t), depend on the parameters of V, Q' and the initial value of oxygen. The coupling strength given by (bI) governs almost all profiles, where b is an effective absorption parameter and I is the UV light intensity.Results:Our numerical method for CXL dynamic profiles demonstrated the following important features: (i) Type-I and type-II coexit in CXL, in the presence of oxygen. However, there is no type-II when oxygen is depleted or in a condition without oxygen. (ii) Type-I with bimolecular termination, the radical R(t) is a function of [K'(bIgC)]^0.5, leading to the steady-state efficacy given by a scaling law of 1/(bI)^0.5, in contract to that of type-II which is almost independent to the light intensity. (iii) The depletion rate (2 to 5 minutes) of X(t) is much faster than that of C(t) (10 to 20 minutes), (iv) Thepure type-II profile, has a transition point from straight line to saturating curve and matches the depletion point of singlet oxygen S(t). (v) Improved CXL efficacy of type-I and type-II may be achieved by external supply of photoinitiator (riboflavin) and oxygen, respectively.

A facile iridium/graphene-catalyzed methodology providing an efficient synthetic route for C-N bond formation is reported. This catalyst can directly promote the formation of C-N bonds, without pre-activation steps, and without solvents, alkalis and other additives. This protocol provides a direct N -alkylation of amines using a variety of primary and secondary alcohols with good selectivity and excellent yields. Charmingly, the use of diols resulted in intermolecular cyclization of amines, and such products are privileged structures in biologically active compounds. Two examples illustrate the advantages of this catalyst in organic synthesis: the tandem catalysis to synthesize hydroxyine, and the intermolecular cyclyzation to synthesize cyclizine. Water is the only by-product, which makes this catalytic process sustainable and environmentally friendly.

The objective of this investigation was to enhance the sensory appeal of Cerasus humilis (C. humilis) juice and ascertain potential interactions among bioactive compounds within a functional juice matrix. Sensory attributes, color, antioxidant potential, polyphenol and vitamin C (VC) concentrations, and sugar levels were assessed. Diverse dosage combinations were examined to determine their impact on the quality of both C. humilis and Green grape juices. Among the formulations, CG5 exhibited elevated antioxidant activit y and polyphenol content (455.02 mg TE/100 ml and 173.1 mg/100 ml, respectively), coupled with favorable consumer preference. Notable variations in compound content were observed across the seven analyzed juices. In the blended juices (CG1–CG5), interactions between distinct juices influenced VC and sugar levels, with other bioactives contributing to beneficial modifications, displaying a progressive rise. This study innovatively crafted delectable and convenient C. humilis juice, upholding its intrinsic high antioxidant activity, thereby presenting a novel avenue for marketable functional juice offerings.

The material undergoes high temperature and high strain rate deformation process during cutting process, may induce the dynamic recrystallization behavior and result the evolution of dynamic mechanical properties of the material to be machined. In this paper, the modified Johnson-Cook(J-C) model for Nickel based powder metallurgy superalloy considering dynamic recrystallization behavior in high strain rate and temperature is proposed. The dynamic mechanical properties of the material under different strain rates and temperature conditions are obtained by quasi-static compression test and split Hopkinson pressure bar (SHPB) test. The coefficients of the modified J-C model are obtained by linear regression method. The modified model is verified by comparison with experimental and model prediction results. The results show that the modified J-C model proposed in this paper can accurately describe the mechanical properties of nickel-based powder metallurgy superalloys at high temperature and high strain rate. Which provides help for studying the cutting mechanism and finite element simulation of nickel-based powder metallurgy superalloy.

Recurrent sunspot groups were studied by using the Debrecen Photoheliographic Data (DPD) which covers more than 40 years. For this task it is necessary to make unambiguous the identification of the returning solar active regions. It starts with an algorithmic listing of possible returns, then the candidates of the algorithmic identifications are checked by the unique HTML-feature of the DPD. The final check is the application of an asymmetric Gaussian function introduced in previous articles to describe the development of short-lived sunspot groups observed continuously from start to end on the visible solar disc. The data of correctly identified recurrent sunspot groups fit surprisingly well to this function throughout the rotations enabling the reconstruction of the development also on the far side of the sun. The primary goal was to find any relationship between the maximum area and the lifetime deduced from the data of the asymmetric curves. This relationship is more complex than earlier results in the literature for short-lived groups. The lifetimes exhibit weak dependencies on the heliographic latitude and solar cycle phase. An apparently returning active area is rather an active nest if its data do not fit to the asymmetric Gaussian.

Recent advances and demands in clinical applications drive a large amount of research to hydroxyapatite (HA) composite coatings fabricated by plasma spray. However, lower degree of HA crystallinity related to high temperature exposure in plasma spray usually leads to rapid weakening and disintegration of HA coatings and often promotes inflammatory responses in the surrounding tissue. In this research, graphene nanosheet (GNS) reinforced HA coatings were fabricated using plasma spray and followed by heat and hydrothermal treatment (hereafter referred to as thermal treatment). The addition of GNSs resulted in competing phenomenon to influence HA crystallinity viz. increased portion of the partially melted/unmelted zones and higher cooling rate during splat formation, leading to slight increase in HA crystallinity (~46.0-51.3%) in the as-sprayed coating. XRD and FTIR results showed that thermal treatment was capable of inducing significant transformation of amorphous HA to the crystalline form and removing other foreign non-HA compounds through regaining OH- ion, and therefore HA coatings displayed ~45.5-47.1% improvements in HA crystallinity regardless of addition or not of the GNS nanofillers. Microstructure observations revealed that thermal treatment enabled microcrack propagation due to stresses caused by crystallisation and phase transformations, and the residual partially melted/unmelted zone of the thermally treated GNS/HA coating was significantly decreased in size. More importantly, the added GNSs contributed greatly to the significant increase in surface nanoroughness of the thermally treated HA coatings owing to the fact that much more structural defects along with the GNSs mainly induced by thermal treatment might act as nucleation sites to accelerate HA nanoparticle precipitation, which would be beneficial for the improved adhesion strength of the osteoblast cells on the coating surface.

In this study, composite nanofiber films comprising polyvinyl alcohol, wheat gluten, and glucose (PWG) were fabricated using electrospinning, followed by cross-linking via the Maillard cross-linking. Various mass concentrations of ferulic acid (FA) were incorporated into the PWG films. The results indicate that the average diameter of the FA-PWG films decreased from 449 nm to 331 nm as the concentration of FA increased, until reaching a concentration of 12%, after which a significant increase in diameter was observed. Subsequent Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and differential scanning calorimetry (DSC) results suggested that FA was distributed in the sample films in an amorphous form through hydrogen and ester bonds. Additionally, release experiments and antimicrobial tests on FA-PWG sample films showed good con-trolled release of FA and excellent anti-Escherichia coli and Staphylococcus aureus activity of this film. These findings all indicate that the FA-PWG nanofiber film is a potential candidate for food active packaging.

Although the Orthotropic steel decks (OSDs) have been widely used in the construction of long-span bridges, there are frequently reported fatigue cracks after years of operation, and the bridge deck overlay also presents severe damage due to OSD crack-induced stiffness reduction. The ultra-high performance concrete (UHPC), recognized as the most innovative cementitious composites and the next generation of high-performance materials, shows high strength, ductility, toughness and well performance on durability. After its first application to the OSD bridge in early 2000s, the orthotropic Steel-UHPC composite deck has been comprehensively studied worldwide. This review will summarize some important studies and findings on behavior and fatigue performance of orthotropic steel-UHPC composite deck. The existing studies and engineering application indicate that such deck system presents good bending behavior and high fatigue performance. The failure mode of shear studs in UHPC layer is dominated by shear fractures. The cracking of UHPC layer shall consider the superposition effect of stress from both the whole bridge structure and local decks. While some reasonable structural details in the traditional OSD may not work for the orthotropic steel-UHPC composite deck. It is recommended to evaluate the stress behavior and structural parameters, as well as fatigue life by conducting the field test under in-service traffic conditions.

Since the advent of the OBORI, it was subjected to numerous studies. However, most previous studies investigated only the potential impact of the OBORI on the Chinese economy and geopolitics. Therefore, its real effect on Chinese international commerce in OBORI countries is not evaluated yet. Accordingly, this study intends to model the OBORI effect on Chinese product brand purchases across country members. The assessment is made on 18362 purchases of the International Online Consumers (IOCs) from a Chinese international online selling platform. The Data was obtained from a programming language and the octopus software. The OBORI policy's effect on Chinese brands' purchases was examined through a Different In Different Model (DIDM). Results show that the impact of OBORI is weak in the real market. However, it could be significant if OBORI includes more developed and economically strong countries. To Chinese brands and policymakers, we show how the inclusion in the OBORI project of developed countries could contribute more to Chinese product brands' purchases. Thus, the study enables decision-makers to understand the current impact of OBORI on the real market and its potential effect if more developed and economically strong countries are included.

The lower reaches of the Changhua River are located in the northwest of Hainan Island, and the shallow groundwater in this area is the main water source for residents living at both sides of the river. In order to sustain the exploitation and use of water resources in this area, it is essential to clarify the chemical characteristics and the formation mechanism of the groundwater. We collected 100 sets of shallow groundwater samples from the lower reaches of the Changhua River, and analyzed the chemical characteristics of the groundwater in shallow aquifers as well as its controlling factors by means of the methods including descriptive statistical analysis, Piper diagram, Gibbs diagram, and ion ratio. The results show that the overall characteristics of groundwater in the study area are near-neutral to weakly alkaline nature, indicating a generally oxidized environment. The groundwater involves in 56 chemical types, and the most predominant types are Ca•Na-HCO3 and Ca-HCO3, respectively. NO- 3 has become a macro component exceeding SO2- 4in most of the sampling groundwater, suggesting a significant impact of human activities in this area. At the same time, the chemical characteristics of groundwater in the study area are mainly affected by the water-rock interaction, while the water-rock interaction is mostly affected by the dissolution of silicate rocks and less by the dissolution of carbonate rocks and evaporite rocks. According to the ion ratio results, Na+ and K+ in the study area are mainly from the leaching of silicate rocks, Ca2+ and Mg2+ are mainly from the dissolution of carbonate rocks, in addition to a certain degree of cationic exchange. NO- 3 is mainly related to human activities, and the human activities are more affected by agricultural activities and domestic sewage than by industrial and mining activities. This study can provide a reference for the development and protection of shallow groundwater in the lower reaches of the Changhua River.

Maize, a crop of international relevance, frequently undergoes xylem embolism due to water shortage, negatively impacting growth, yield, and quality. Consequently, a refined comprehension of xylem embolism is vital for enhancing maize cultivation. Notwithstanding extensive research and the generation of analytical models for embolism mechanisms, prevalent models often disregard crop-specific hydraulic processes and the formation of embolisms via air bubbles in the xylem conduit. In this research, we present an inventive model applying pipe cavitation parameters to discern water potential and bubble formation in maize leaf xylem. The model integrates pivotal physiological traits of maize—leaf count, leaf vein count, and average leaf radius—demonstrating robust correlations. Furthermore, we constructed a percentage conductivity loss (PLC) curve based on pre-dawn leaf water potential and compared it with our model, offering interval data to observe embolisation events triggered by air bubbles. Utilizing experimental data, our novel cavitation-parameters based model effectively corresponds with observed bubble phenomena and appropriately characterizes water transport in plant xylem conduits. This method enabled us to observe the transition from bubble occurrence to cavitation embolism microscopically, which aligned with the embolism intervals provided by the model. This procedure reveals potential trends in bubble-induced embolism and deepens our knowledge of microscopic plant hydraulics and crop embolism. This work establishes a basis for understanding the generation of bubble embolisms in maize, assists in evaluating maize plant water status for efficient water supply management throughout the growth cycle, and contributes towards potential water management strategies for maize.

The service conditions of underground coal mine equipment are poor, and it is difficult to accurately extract the fault characteristics of rolling bearings. In order to better improve the accuracy of fault identification of rolling bearings, a fault detection method based on multiscale permutation entropy and SOA-SVM is proposed. First, the whale optimization algorithm is used to select the modal analysis number K and the penalty factor α of the variational mode decomposition algorithm. Then, the vibration signal of rolling bearings is dissolved according to the optimized variational mode decomposition algorithm, and the multi-scale permutation entropy of the main intrinsic mode function is calculated. Finally, the feature values of the matrix are entered into the SVM algorithm optimized by the seagull optimization algorithm to obtain the classification result. The experimental results based on the published rolling bearing datasets of Western Reserve University show that the identification success rate of the proposed method can reach 98.75%. The fault detection of the rolling bearings can be completed accurately and efficiently.

This study aims to explore predictors of the foreign investment from China coming into Rwanda. One of the components of Rwanda’s economy is the investment it receives from other countries. In order to achieve these objectives, the study gathers econometric secondary data from 2007 to 2020 quarterly which were availably provided by National Statistics of China, World Bank, UNCTAD, National Institute of Statistics of Rwanda, and the National bank of Rwanda. From literature and based on the availability of data, market size, trade openness, infrastructure, and human capital were measured as predictors of Chinese FDI. The data is analyzed using linear regression in Stata. The finding of the study showed that variables have a positive effect on FDI from China, and it found that though FDI had an effect on overall economy of Rwanda, the effect was not statistically significant. The study suggested that Rwanda’s policy on foreign investment should aim to attract and encourage Chinese investment to increase the economy of Rwanda. To encourage more FDI, the Rwandan government can offer Chinese investors greater ownership, locational, and internalization benefits. It also should continue to strengthen economic policy transparency since it lowers transaction costs and hence improves incentives for foreign investment.

Abstract Plant uptake and assimilation of essential nitrogen compounds from the soil are mainly in the form of nitrate and ammonium ions. Plant nitrate transporters (NRTs) play a crucial role in nitrate uptake from the soil into the roots. NRT structural analysis reveals the mechanisms by which these transporters function. Similarly, plant ammonium transporters (AMTs) mediate the uptake of ammonium ions, and their structural analysis has provided valuable information on their mechanisms. After nitrogen uptake by plant roots, the nitrogen metabolism pathway involves the incorporation of nitrogen into organic compounds. Glutamine synthetase (GS) and glutamate synthase (GoGAT) are the master players in this pathway. They work together to convert ammonium ions into glutamine and glutamate, respectively. Different isoforms of GS and GoGAT exist, enabling plants to fine-tune nitrogen metabolism based on environmental cues. Under severe abiotic stress conditions, nitric oxide (NO) has been found to enhance plant survival under drought. Furthermore, the interaction between salinity stress and nitrogen availability in plants has been studied, with NO identified as a potential mediator of responses to salt stress. On the other hand, excessive use of nitrate fertilizers can lead to health and environmental issues. Therefore, alternative strategies, such as establishing nitrogen fixation in plants through diazotrophic microbiota, have been explored to reduce reliance on synthetic fertilizers. Ultimately, genomics can identify new genes related to nitrogen fixation, which could be harnessed to improve plant productivity. By deciphering the genetic basis of nitrogen-fixing traits, researchers aim to develop crops that efficiently utilize nitrogen from the environment.

Until now, the literature on Chinese International Online Shopping (CIOS) (B2C export from China) mainly concentrated on the potential income that it constitutes for Chinese international trade. However, regarding International Online Consumers' (IOCs) purchase behaviors, research does not provide insight into the impact of Countries' Level of Economic Development (CLED) on the IOCs' preferences and choices about Chinese brands. Based on 9971 purchases about Chinese mobile phone brands, countries' macroeconomic data, and a multinomial logistics model (MLM), we examined IOCs' preferences and choices about Chinese brands. The result shows that the CLED influences IOCs' preferences and choices. Consequently, accounting of CLED in consumers’ preferences and choices introduces a new dimension in understanding IOCs' behaviors and attitudes towards Chinese mobile phone brands. This work contributes to Chinese brands' globalization research from the perspective of CLED. Such a model can be used to guide e-retailers and brand managers.

This paper briefly reviews the state of the art in artificial intelligence including inductive and deductive methods. Deep learning and ensemble machine learning lie in inductive methods while automated reasoning implemented in deductive computer languages (Prolog, Otter, and Z3) is based on deductive methods. In the inductive methods, intelligence is inferred by pseudorandom number for creating the sophisticated decision trees in Go (game), Shogi (game), and quiz bowl questions. This paper demonstrates how to wisely use the pseudorandom number for solving coin-weighing puzzles with the deductive method. Monte Carlo approach is a general purpose problem-solving method using random number. The proposed method using pseudorandom number lies in one of Monte Carlo methods. In the proposed method, pseudorandom number plays a key role in generating constrained solution candidates for coin-weighing puzzles. This may be the first attempt that every solution candidate is solely generated by pseudorandom number while deductive rules are used for verifying solution candidates. In this paper, the performance of the proposed method was measured by comparing with the existing open source codes by solving 12-coin and 24-coin puzzles respectively.

Due to the global warming and dynamic changes in pathogenic virulence, leaf rust caused by Puccinia triticina has greatly expanded its epidermic region and become a severe threat to global wheat production. Genetic bases of wheat resistance to leaf rust mainly relies on the leaf rust resistance (Lr) gene or quantitative trait locus (QLr). Although these genetic loci have been insensitively studied during the last two decades, an updated overview of Lr/QLr in a genome-wide level is urgently needed. This review summarized recent progresses in genetic studies of wheat resistance to leaf rust. Wheat germplasms with great potentials in genetic improvement of resistance to leaf rust were highlighted. Key information about the genetic loci carrying Lr/QLr were summarized. A genome-wide chromosome distribution map for all the Lr/QLr was generated based on the released wheat reference genome. In conclusion, this review has provided valuable sources for both wheat breeders and researchers to understand the genetics of resistance to leaf rust in wheat.

This article explores the relationship between Wang Yangming's philosophy and the new quality productivity, revealing how the new quality productivity, while inheriting the core ideas of Yangming's philosophy, achieves a higher level through innovation and development. The new quality productivity emphasizes the integration and innovation of knowledge, technology, and information, characterized by knowledge-driven innovation, information technology support, sustainable green development, and global collaborative development. The fusion of Yangming's philosophy and the new quality productivity holds significant theoretical and practical implications.

This article presents, for the first time, the efficacy and curing depth analysis of photo-thermal dual polymerization in metal (Fe) polymer composites for 3D printing of a 3-component (A/B/M) system based on the proposed mechanism of our group, in which the co initiators A and B are Irgacure-369, and charge-transfer complexes (CTC), respectively; and the monomer M is filled by Fe. Our formulas show the depth of curing (Zc) is an increasing function of the light intensity, but a decreasing function of the Fe and photoinitiator concentrations. Zc is enhanced by the additive [B] which produces extra thermal radical for polymerization under high temperature. The heat (or temperature) increase in the system has two components : (i) due to the light absorption of Fe filler, and (ii) heat released from the exothermic photopolymerization of the monomer. The heat is transported to the additive (or co-initiator) [B] to produce extra radical R' and enhance the monomer conversion function (CF). The Fe filler leads to temperature increase, but also limits the light penetration leading to lower CF and Zc, which could be overcome by the additive initiator [B] in thick polymers. Optimal Fe for maximal CF and Zc are explored theoretically.

The performance of bearings plays a pivotal role in determining the dependability and security of rotating machinery. In intricate systems demanding exceptional reliability and safety, the ability to accurately forecast fault occurrences during operation holds profound significance. Such predictions serve as invaluable guides for crafting well-considered reliability strategies and executing maintenance practices aimed at enhancing reliability. In order to ensure the reliability of bearing operation, this article investigates the application of three advanced techniques—Maximum Correlation Kurtosis Deconvolution (MCKD), Multi-Scale Permutation Entropy (MPE), and Long Short-Term Memory (LSTM) recurrent neural networks—for the prediction of the remaining useful life (RUL) of rolling bearings. Each technique's principles, methodologies, and applications are comprehensively reviewed, offering insights into their respective strengths and limitations. Case studies and experimental evaluations are presented to assess their performance in RUL prediction. Findings reveal that MCKD enhances fault signatures, MPE captures complexity, and LSTM excels in modeling temporal patterns. The root mean square error of the prediction results is 0.007. The fusion of these techniques offers a comprehensive approach to RUL prediction, leveraging their unique attributes for more accurate and reliable predictions.

Coalbed Methane(CBM) production enhancement for single wells is a big problem to CBM industrialization. Low production is due to insufficient gas generation by thermogenic. Luckily, Biogenic gas was found in many areas and its supply is assumed to improve coalbed methane production. Therefore, microbial simulation experiment will demonstrate the effectiveness of the assumption. From microbial simulation experiment on different coal ranks, it is found that microbes can use coals to produce biogas under laboratory conditions. With different temperatures for different experiments, it turns out that the gas production at 35 ℃ is greater than that at 15℃,indicating that 35℃ is more suitable for microbes to produce gas. According to quantitative experiments, adding exogenous nutrients or exogenous bacteria can improve CBM production. Moreover, the production enhancement ratio can reach up to 115% under the condition of adding exogenous bacterial species, while the ratio for adding nutrients can be up to 144%.

In order to enhance the efficiency and combined performances of nitriding layer, aluminum-modified plasma nitriding (Al-PN) was developed in this research by adding some FeAl particles around the samples during plasma nitriding (PN) for 42CrMo steel. The results show that the efficiency is dramatically enhanced almost 6 times comparing with traditional PN, with the effective hardening layer increasing from 224 μm to 1246 μm at 520℃/4h. More importantly, the compound layer increased just a little bit from 11.64 μm to 14.32 μm, which remarkably reduces the ratio of the compound layer thickness to effective hardening layer thickness, thus being quite beneficial to decrease the brittleness level, making the brittleness level decreasing from Level 4 to Level 1. Meanwhile, ultra-high surface hardness and excellent wear behaviors are obtained by aluminum-modified plasma nitriding (Al-PN) due to the formation of dispersed strengthening phased of AlN and FexAl in the nitriding layer, with the surface hardness increasing from 755 HV0.025 to 1251 HV0.025, wear rate decreasing from 8.15 x10-5g N-1 m-1 to 4.07 x10-5g N-1 m-1. In other words, comparing with PN, the wear resistance has been almost doubled by Al-PN. Therefore, the research can provide comprehensive insights into the surface characteristics and combined performances of the aluminum-modified plasma nitriding layer.

Deposition/printing of materials with sub-1 μm precision and size (cross sections) is required for optical and electrical micro-devices. Crystalline c-ITO (Indium tin oxide) nanostructures were patterned on glass with a precision that formed gaps of 20-50 nm between individual disks or lines of ∼ 250 nm diameter or width. The absorbed energy density [J/cm3] followed the second order dependence on pulse energy. This facilitated high resolution and precision for nanoscale laser writing at the 515 nm laser wavelength. Patterns for optical elements such as circular gratings and micro-disks were laser printed using ITO as a resist. Unexposed amorphous a-ITO was chemically removed in aqueous 1% vol. HF solution. This use of a-ITO as solid-resist is promising for metamaterial and micro-optical applications.

Searching over a sorted list is a classical problem in computer science. Binary Search takes at most log2n+1 tries to find an item in a sorted list of size n. Interpolation Search achieves an average time complexity of Ο(loglogn) for uniformly distributed data. Hybrids of Binary Search and Interpolation Search are also available to handle data with unknown distributions. This paper analyzes the computation cost of these methods and shows that interpolation can significantly affect their performance — accordingly, a new method, Interpolation Once Binary Search (IOBS), is proposed. The experimental results show that IOBS outperforms the hybrids of Binary Search and Interpolation Search for nonuniformly distributed data.

Cucumber (Cucumis sativus L.) is a vital economic vegetable crop, and TRM (TONNEAU1 Recruiting Motif) gene plays a key role in cucumber organ growth. However, the pan-genomic characteristics of the TRM gene family and their expression patterns under different stresses have not been reported in cucumber. In this study, we identified 29 CsTRMs from the pan-genomes of 13 cucumber accessions, with CsTRM29 existing only in PI183967. Most CsTRM proteins exhibited differences in sequence length, except five CsTRMs having consistent protein sequence lengths among the 13 accessions. All CsTRM proteins showed amino acid variations. Analysis of CsTRM gene expression patterns revealed that six CsTRM genes strongly changed in short-fruited lines compared with long-fruited lines. And four CsTRM genes strongly responded to salt and heat stress, while CsTRM14 showed responses to salt stress, powdery mildew, gray mold and downy mildew. Some CsTRM genes were induced or suppressed at different treatment timepoint, suggesting that cucumber TRM genes may play different roles in responses to different stresses, with expression patterns varying with stress changes. Remarkably, the expression of CsTRM21 showed considerable change between long and short fruit and in responses to abiotic stresses (salt stress, heat stress) as well as biotic stresses (powdery mildew, gray mold), suggesting a dual role of CsTRM21 in both fruit shape determination and stress resistance. Collectively, this study provided a base for further functional identification of CsTRM genes in cucumber plant growth and stress resistance.

The metro station ridership features are associated significantly with the built environment factors of the pedestrian catchment area surrounding metro stations. The existing studies have focused on the impact on total ridership at metro stations, ignoring the impact on varying patterns of metro station ridership. Therefore, the reasonable identification of metro station categories and built environment factors affecting the varying patterns of ridership in different categories of stations is very important for metro construction. In this study, we developed a data-driven framework to examine the relationship between varying patterns of metro station ridership and built environment factors in these areas. By leveraging smart card data, we extracted the dynamic characteristics of ridership and utilized hierarchical clustering and K-means clustering to identify diverse patterns of metro station ridership, and finally identified six main ridership patterns. We then developed a new built environment measurement framework and adopted multinomial logistic regression analysis to explore the association between ridership patterns and built environment factors. (1) The clustering analysis result revealed that six station types were classified based on varying patterns of passenger flow, representing distinct functional characteristics. (2) The regression analysis indicated that diversity, density, and location factors were significantly associated with most station function types, while destination accessibility was only positively associated with employment-oriented type station, and centrality was only associated with employment-oriented hybrid type station. These results could inform the coordinated development of rail transit and land use, and the renewal and enhancement of the built environment in the pedestrian catchment area surrounding metro stations.

In many countries, increasing concern for animal welfare is driving retailer commitments and government legislation that aim to improve the lives of farmed fish. One aspect of fish welfare involves stunning fish prior to slaughter. The feasibility of stunning depends on the species of fish and physical farm characteristics. In this article, we provide an overview of stunning before slaughter in European sea bass and sea bream aquaculture, one of the largest finfish farming industries in the developed world that does not yet stun most of its production. Sea bass and sea bream stunning necessitates the use of electrical stunning equipment aboard harvest vessels, often a significant distance from the shoreline; this presents an interesting engineering and policy challenge. Together, Türkiye, Greece, Spain, and Italy produced over 400,000 t of sea bass and sea bream in 2020. In Türkiye and Greece, farms are numerous and located very close to the shoreline. In Spain and Italy, farms are few and located far from the shoreline. The highest average production is found in farms from Türkiye (1,000 t) and Spain (1,300 t, and lower average production is found in Greece (300 t) and Italy (350 t). Producer progress towards the installation of electrical stunning appears comparatively well-developed for Türkiye, Spain, and Greece, though we emphasise that producers and other stakeholders require continued support to realise this opportunity. Producers in Italy appear slower to make progress on this aspect of animal welfare and may require additional support.

This paper proposes an innovative approach to address the challenge of softening deformation of thermal-curable thermosets during additive manufacturing. This approach involves the development of a composite powder composed of thermosetting materials with distinct curing temperatures, the utilization of Cold Spray Additive Manufacturing (CSAM) technology for 3D printing, and the application of a stepwise isothermal curing process. The corresponding effectiveness is validated by case studies. The results demonstrate that samples printed via CSAM maintain a solid state without deformation. During the post-curing process, each component of the composite material cures independently while the other components remain in a solid state, providing structural support for the whole material, thereby effectively reducing the softening deformation during the post-curing process. This approach offers a novel perspective for the additive manufacturing of thermal-curable thermosets.

Based on the resource-based theory, the current study examines the relationship between competitive strategies and strategic alliance performance. Furthermore, big data predictive analytics is treated as a boundary condition between competitive strategies and strategic alliance performance. Big data of predictive analytics in operations and industrial management has been a focal point in the current era. There has been little attention has about big data predictive analytics influences on competitive strategies and strategic alliance performance, especially in developing countries like Pakistan. A survey instrument was used to record the responses from 331 employees of the telecom sectors companies working in Pakistan. Study findings show that big competitive strategies have a positive and significant relationship with strategic alliances performance. It was also found that big data predictive analytics plays the role of moderator between competitive strategies and strategic alliance performance. The study add a new perspective and contribution to the literature on big data predictive analytics, strategic alliance performance, and competitive strategies in Pakistan's telecom sector companies. Further, the study results explain that big data analytics is just like the companies' lifeblood in the current era. The efficient and effective use of big data analytics, companies can boost their standards in a competitive environment.

Abstract: Because of outstanding heat resistance and processing qualities, benzoxazine resins are widely employed in a variety of applications. However, traditional benzoxazine resins still confront hurdles in today's engineering applications, such as can’t long-term service in high-temperature settings and inadequate toughness. Four alkyne-functionalized benzoxazines with phthalide side group and cyano group of varying molecular weights were produced in this study. Fourier trans-form infrared spectroscopy (FT-IR) and hydrogen nuclear magnetic resonance spectroscopy ( 1H-NMR ) were used to characterize the resin structure, and differential scanning calorimetry (DSC) was used to investigate the thermal curing kinetics at different warming rates, the apparent activation energy was 116.9 kJ/mol. In-situ FTIR was used to investigate the cure mechanism. Dynamic mechanical analysis (DMA) was used to evaluate the gelationation time of BOZ series resins at various temperatures, and the curing process was designed by combined the results of DSC. The Tg of the composites made using BOZ-1N21 as the matrix was 336°C, which was much higher than the Tg of the BP-a resin made with aniline, phenolphthalein, and formaldehyde (Tg=251°C). As a result, the resin system is expected to be employed in applications requiring high-temperature resistance and toughness.

In this paper, quasi-static axial compression tests are performed on the nodal Moso bamboos to study the size effect on energy absorption of the bamboos and the damage pattern of the multiple bamboo columns. Experimental results show that under the same moisture content, growth age and growing environment, the specific energy absorption (SEA) of the test samples increases with the increase of the out-diameter and thickness of the bamboo columns, indicating that size effect exists for energy absorption of the Moso Bamboos. For the multiple bamboo columns, there are mainly three failure modes for the constituent single bamboo columns: splitting above the node, splitting below the node and splitting through the node. Also, the tensile tests are conducted on three kinds of dog-bone shaped bamboo samples to investigate the macroscopic tensile fracture mode in the longitudinal direction of Moso bamboos. Results show that there is no direct relationship between the fracture pattern and moisture content of the bamboos, as well as the growth age of the bamboos. However, the tensile loading rate and the shape of the dog-bone shaped bamboo sample could affect the macroscopic fracture pattern of the bamboos in some cases.

Accurate segmentation of the Left Ventricle (LV) in Echocardiogram (Echo) images is essential for cardiovascular analysis. Conventional techniques are labor-intensive and exhibit inter-observer variability. Deep learning has emerged as a powerful tool for automated medical image segmentation, offering advantages in speed and potentially superior accuracy. This study explores the efficacy of employing the YOLO (You Only Look Once) segmentation model for automated LV segmentation in Echo images. YOLO, a cutting-edge object detection model, achieves exceptional speed-accuracy balance through its well-designed architecture. It utilizes efficient dilated convolutional layers and bottleneck blocks for feature extraction, while incorporating innovations like path aggregation and spatial attention mechanisms. These attributes make YOLO a compelling candidate for adaptation to LV segmentation in Echo images. We posit that by fine-tuning a pre-trained YOLO based model on a well-annotated Echo image dataset, we can leverage the model's strengths in real-time processing and precise object localization to achieve robust LV segmentation. The proposed approach entails fine-tuning a pre-trained YOLO model on a rigorously labeled Echo image dataset. Model performance has been evaluated using established metrics such as mean Average Precision (mAP) at an Intersection over Union (IoU) threshold of 50% (mAP50) with 98.31%and across a range of IoU thresholds from 50% to 95% (mAP50:95) with 75.27%. Successful implementation of YOLO for LV segmentation has the potential to significantly expedite and standardize Echo image analysis. This advancement could translate to improved clinical decision-making and enhanced patient care.

The nutrient absorption and utilization efficiency in the roots of seedlings are beneficial for increasing crop yield. Creating marker assisted selection for wheat root traits can assist wheat breeders in choosing robust roots to maximize nutrient uptake. Exploring and identifying the effect of different nitrogen applications on RSA is of great significance for breeding nitrogen efficient wheat varieties. In this study, A total of 243 wheat varieties native to the Yellow and Huai Valley regions of China were utilized for genome-wide association studies (GWAS). Furthermore, a recombinant inbred line (RIL) population of 123 lines derived from the cross between Avocet and Chilero was utilized for linkage examination and confirmation of the hereditary loci distinguished by GWAS. Five RSA traits include the relative number of root tips (RNRT); relative total root length (RTRL); relative total root surface area (RTRS); relative total root volume (RTRV) and relative average root diameter (RARD) where evaluated under two N conditions—normal N (NN) supply and low N (LN)—to characterize the NUE of each accession. GWAS and linkage analysis were performed by integrating data from the wheat 660k single nucleotide polymorphism (SNP) chip and diversity arrays technology (DArT) to identify genetic loci associated with RSA. The results showed that based on the ratio of RSA related traits under two N supply conditions, a total of 598 SNP markers, which are significantly associated with RSA related traits, were detected at 160 genetic loci by GWAS. A total of 10 QTL loci related to RSA were dis-covered and identified by linkage mapping. In which, three significant RSA related Quantitative Trait Locus (QTL) were identified, namely qRtrl-3D, qRnrt-3D, and qRtrl-7D. The study has the potential to enhance the effectiveness of selecting root traits in wheat breeding programs, offering valuable insights into the genetic underpinnings of nitro-gen use efficiency (NUE) in wheat. This could lead to the creation of NUE wheat varieties by implementing focused breeding strategies.

The minimum dominating tree (MDT) problem consists of finding a minimum weight sub-graph from an undirected graph, such that each vertex not in this sub-graph is adjacent to at least one of the vertices in it, and the sub-graph is connected without any ring structures. This paper presents a Dual Neighborhoods Search (DNS) algorithm for solving the MDT problem, which integrates several distinguishing features, such as two neighborhoods collaboratively working for optimizing the objective function, a fast neighborhood evaluation method to boost the searching effectiveness, and several diversification techniques to help the searching process jump out of the local optimum trap thus obtaining better solutions. DNS improves the previous best-known results for 4 public benchmark instances while providing competitive results for the remaining ones. Several ingredients of DNS are investigated to demonstrate the importance of the proposed ideas and techniques.

Delve into the dynamic realms of neuroscience, neurology, and psychiatry with this groundbreaking editorial, unveiling the intricate mechanisms of brain function and dysfunction. Explore the latest advancements in molecular biology, genetics, epigenetics, pharmacology, and neuroimaging that are revolutionizing our understanding of neurological and psychiatric disorders. Uncover the challenges and gaps in translating cutting-edge research into practical clinical applications, aiming to enhance the lives of patients and their families. Discover the pivotal role of neuroplasticity in reshaping the brain's adaptability throughout life, alongside the promising potential of non-invasive brain stimulation techniques like transcranial magnetic stimulation and transcranial direct current stimulation. Embark on a journey of innovation and collaboration as researchers and clinicians strive to bridge the gap between bench and bedside, offering hope for improved diagnosis, prevention, and treatment of complex neurological and psychiatric conditions. Join us in this exploration of transformative ideas and novel interventions that hold the key to a brighter future for individuals and society.

Sensory descriptive analysis was used to evaluate the aged Feng-flavored baijiu. The results indicated that there are notable differences in the samples of different ages. The samples with shorter storage times and fresh distilled Baijiu present bran flavor, and fresh green flavor. with the increase of storage time, the fragrance of honey, sweetness, flowers, and aging gradually increases. The samples of Feng-flavored baijiu were dected by Headspace solid-phase microextraction (HS-SPME) combined with comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC–TOFMS) , in total, 496 sustances were identified in all samples, mainly containing 14 types of substances, such as esters, aldehydes etc., of which 42 substances were found in Feng-flavored baijiu for the first time. Chemometrics was used to analyze the key differential compounds. 143 differential compounds closely related to aging were preliminarily screened, and principal component analysis revealed that these samples were separated by year. 65 differential compounds were selected out by partial least squares discriminant analysis(PLS-DA). Furthermore, 43 key differential compounds were selected from the aged Feng-flavored baijiu combined with variable importance in projection and Pearson correlation coefficients. Partial least squares regression (PLSR) was used to research the correlation of sensory properties and key differential compounds, and the results indicated that most compounds were closely related to the aged Baijiu . This study afford theoretical basis and reference for flavor research of Feng-flavored baijiu.

The central nervous system (CNS) is the final frontier in drug delivery because of the blood-brain barrier (BBB), which poses significant barriers to the access of most drugs to their targets. Kynurenic acid (KYNA), a tryptophan (Trp) metabolite, plays an important role in behavioral functions and abnormal KYNA levels have been observed in neuropsychiatric conditions. The current challenge lies in delivering KYNA to the CNS owing to its polar side chain. Recently, C-3 side chain modified KYNA analogs have been shown to cross the BBB; however, it is unclear whether they retain the biological functions of the parent molecule. This study examined the impact of KYNA analogs, specifically SZR-72, SZR-104, and the newly developed SZRG-21, on behavior. The analogs were administered intracerebroventricularly (i.c.v.), and their effects on the motor domain were compared with those of KYNA. Specifically, open field (OF) and rotarod (RR) tests were employed to assess motor activity and skills. SZR-104 increased horizontal exploratory activity in the OF test at a dose of 0.04 μmol/4 μL, while SZR-72 decreased vertical activity at doses of 0.04 and 0.1 μmol/4 μL. In the RR test, however, neither KYNA nor its analogs showed any significant differences in motor skills at either dose. Side chain modification affects affective motor performance and exploratory behavior, as the results show for the first time. In this study, we showed that KYNA analogs alter emotional components such as motor-associated curiosity and emotions. Consequently, drug design necessitates the development of precise strategies to traverse the BBB while paying close attention to modifications in their effects on behavior.

To effectively estimate airport terminal area capacity and assess the maximum throughput the sector can achieve when the capacity is given, this research proposes an approach to assess the terminal area capacity from the viewpoint of service provision resources. Terminal area capacity is optimized based on the equilibrium of air traffic service resource supply and demand. The supply-demand nexus is examined in consideration of terminal area route structure, traffic flow characteristics, and safety regulations. A flight service probability matrix and a terminal area demand and supply service time model are constructed to quantify resource expenditure at varied capacity levels. A optimization model is then developed to apportion maximal capacity under resource limitations. Model computation and computation results demonstrate the deviation between estimated and amended capacities is under 0.3 flight sorties per hour. The outcomes are congruent with historical statistics, thereby validating the accuracy and reliability of the model proposed in this study. Given capacity parameters, the model can deduce the maximal aircraft quantity served concurrently in terminal areas during peak periods. These revelations indicate the submitted model furnishes theoretical foundation and reference for terminal area sector partition and traffic alerting.

The promoter of the RECEPTOR-LIKE CYTOPLASMIC KINASE VI_A2 gene contains nine binding sites for the REPLUMLESS transcription factor. In agreement, the expression of the kinase gene was strongly downregulated in the rpl-4 mutant. Comparing phenotypes of loss-of-function mutants, it was revealed that both genes are involved in stem growth, phyllotaxis, organization of the vascular tissues, and the replum, highlighting potential functional interactions. Expression of the RLCKVI_A2 gene from the constitutive 35S promoter could not complement the rpl-4 phenotypes, but exhibited a dominant positive effect on stem growth and affected vascular differentiation and organization. The results also indicated that the number of vascular bundles is independently regulated from stem thickness. Although our study cannot demonstrate the direct link between the RPL and RLVKVI_A2 genes, it highlights the significance of the proper developmental regulation of the RLCKVI_A2 promoter for balanced stem development.

MicroRNAs (miRNA) exert regulatory actions via base-pairing with their binding sites on target mRNAs. Cooperative-binding, i.e., synergism, among binding sites on a mRNA is biochemically well-characterized. We studied whether this synergism is reflected in global relationship between miRNA-mediated regulatory activity and miRNA-binding-site count on the target mRNAs, i.e., leading to a non-linear relationship between the two. Recently, using our own and public datasets, we have enquired into miRNA regulatory actions: first, we analyzed the power-law distribution pattern of miRNA binding sites; second, strikingly, mRNAs for core miRNA regulatory apparatus proteins have extra-ordinarily high binding site counts, forming self-feedback-control loops; third, we revealed that tumor suppressor mRNAs generally have more sites than oncogene mRNAs; and fourth, we characterized enrichment of miRNA target mRNAs in translationally less-active polysomes relative to more-active polysomes. In these four studies, obvious correlation was observed qualitatively between the extent to which a mRNA is miRNA-regulated and its binding sites count. This paper summarizes the used datasets. We also re-analyzed the correlation by comparative linear and non-linear regression analyses. The results support a non-linear, instead of linear, relationship between the two parameters, conceivably a transcriptome-level reflection of cooperative-binding/synergism among miRNA binding sites on a target mRNA.

Neurodegeneration is a major problem in neuroscience and medicine as it causes and worsens many neurological and psychiatric disorders. It involves gradual loss of neurons at different levels of the brain, affecting cognition, emotion, behavior, consciousness, and attention. Understanding the causes and consequences of neurodegeneration is crucial for identifying the risk factors, biomarkers, and treatments. However, the current therapies are mostly symptomatic and ineffective. Therefore, new and innovative methods, such as noninvasive brain stimulation (NIBS), are needed to modulate brain activity and plasticity in a safe and reversible manner. This field is rapidly developing, with a focus on exploring new clinical applications, mechanisms, and combinations of NIBS and drugs. This special issue covers the latest progress and challenges in the study of neurodegeneration in cognitive impairment and mood disorders from the experimental, clinical, and translational perspectives. It addresses the complexity and diversity of these conditions, the lack of disease-modifying treatments, the ethical and practical issues of conducting research in vulnerable and diverse populations, the integration and interpretation of data from multiple sources and modalities, and the development and validation of novel methods such as NIBS, artificial intelligence, and drug repurposing. Collaborative efforts among various stakeholders are needed to improve our knowledge and treatment of neurodegeneration underlying cognitive impairment and mood disorders.

Forest-grass intercropping patterns of protected cultivation has been widely used to increase productivity and sustainability in modern agriculture. However, there have been few studies of wolfberry (L. barbarum) intercropping and it is cultivated mostly by clean tillage. This paper takes 10 kinds of wolfberry-forage intercropping patterns, compares the effects of different planting modes on the growth, yield, photosynthetic characteristics, nutritional quality, and the degree of occurrence of diseases and pests, which aims to make clear the effects of wolfberry-forage intercropping patterns on wolfberry. The results showed that different intercropping combinations had different effects on wolfberry. The overall effect of Wolfberry-forage intercropping patterns on the growth of wolfberry were promote the photosynthetic characteristics. Ryegrass could increase the branch number, Lvyuan 5 and mangel increase branch length; Mangel, clover, sweet sorghum, ryegrass and stipas could reduce the damage of powdery mildew by 69%, and alfalfa, stipa and ryegrass could reduce the occurrence of aphids by 67% (P<0.05). Intercropping could increase carotenoids, flavonoids and ascorbic acid contents to improve wolfberry quality by 21%, 53% and 127%, respectively (P<0.05). Among all the performances, wolfberry-mangel intercropping has absolute advantages in promoting wolfberry yield and quality increase. Therefore the best patterns of wolfberry-mangel, wolfberry-ryegrass, wolfberry-alfalfa and wolfberry-clover were chosen.

Health issues of children with intellectual disabilities (ID) have gained significant attention as a key focus of China health goals. This study aimed to compare the differences in displacement skills and problem behaviors among children with varying degrees and types of ID, while also exploring their relationship. The study included 90 participants who were children with ID and had completed TGMD-2 displacement skills and Strengths and Difficulties Questionnaire (SDQ) assessments. Covariance, partial correlation, and multiple linear regression analyses were conducted to examine the differences and correlations between these factors. The findings revealed that higher severity of intellectual disability was associated with lower scores in locomotor skills and increased manifestation of problem behaviors. Notably, there were significant variations in locomotor skills and problem behaviors among children with different types of intellectual disabilities. There is a positive correlation between locomotor skills and problem behaviors in children with intellectual disabilities, where locomotor skills can predict the occurrence of problem behaviors. In Conclusion, the research confirms that the development of locomotor skills can have a positive impact on the accompanying problem behaviors of children with developmental disabilities.

Idiopathic scoliosis (IS) is an unexplained dysplasia of the spine that can occur at any age, with idiopathic scoliosis making up the largest proportion of the total population worldwide, approximately 2-3%. Scoliosis is not just a cosmetic defect, but the development of the spinal deformity can lead to cardiovascular and respiratory lesions, often resulting in serious health problems. Treatment of the condition usually involves major surgery, which is both a physical and financial burden for patients. In order to clarify the aetiology of IS and provide a theoretical basis for new diagnostic and treatment methods IS, it is important to use different animal models for experiments. Zebrafish is an emerging model animal with a short reproductive cycle, minimal breeding expenses, and other beneficial traits including in vitro fertilisation, in vitro development, and embryo transparency. As a result, genetic alteration and observation are simpler than with traditional model animals. This study examines the history of animal models for IS research, focuses on the benefits and drawbacks of zebrafish as an IS model and the advances it provides to IS research, and anticipates zebrafish application prospects in IS research.

Sea surface salinity (SSS) is one of the Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS). Acquiring high-quality SSS datasets with high spatial-temporal resolution is cruicial for research on the hydrological cycle and earth climate. This study assessed the quality of SSS data provided by four high-resolution ocean reanalysis products, including the Hybrid Coordinate Ocean Model (HYCOM) 1/12° global reanalysis, the The Copernicus Global 1/12° Oceanic and Sea Ice GLORYS12 Reanal-ysis, the Simple Ocean Data Assimilation (SODA) reanalysis, the ECMWF Oceanic Reanalysis System 5 (ORAS5) product and the Estimating the Circulation and Climate of the Ocean Phase II (ECCO2) reanalysis. Regional comparison in the Mediterranean Sea shows that reanalysis largely depicts the accurate spatial SSS structure away from river mouths and coastal areas but slightly underestimates the mean SSS values. Better SSS reanalysis performance is found in the Levantine Sea while larger SSS uncertainties are found in the Adriatic Sea and the Aegean Sea. The global comparison with CMEMS level-4 (L4) SSS show generally con-sistent large-scale structures. The mean ΔSSS between monthly gridded reanalysis data and in situ analyzed data is -0.1 PSU in the open seas between 40°S and 40°N with the mean Root Mean Square Deviation (RMSD) generally smaller than 0.3 PSU and the majority of correlation coefficients higher than 0.5. Comparison with collocated buoy salinity shows that reanalysis products well captures the SSS variations at the locations of tropical moored buoy arrays at weekly scale. Among all the four products, the data quality of HYCOM re-analysis SSS is highest in marginal sea, GLORYS12 has the best performance in the global ocean especially in tropical regions. Comparatively, ECCO2 has the overall worst performance to reproduce SSS states and variations by showing the largest discrepancies with CMEMS L4 SSS.

The increasing trend of studying the innate softness of robotic structures and amalgamating it with the benefits of the extensive developments in the field of embodied intelligence has led to sprouting of a relatively new yet extremely rewarding sphere of technology. The fusion of current deep reinforcement algorithms with physical advantages of a soft bio-inspired structure certainly directs us to a fruitful prospect of designing completely self-sufficient agents that are capable of learning from observations collected from their environment to achieve a task they have been assigned. For soft robotics structure possessing countless degrees of freedom, it is often not easy (something not even possible) to formulate mathematical constraints necessary for training a deep reinforcement learning (DRL) agent for the task in hand, hence, we resolve to imitation learning techniques due to ease of manually performing such tasks like manipulation that could be comfortably mimicked by our agent. Deploying current imitation learning algorithms on soft robotic systems have been observed to provide satisfactory results but there are still challenges in doing so. This review article thus posits an overview of various such algorithms along with instances of them being applied to real world scenarios and yielding state-of-the-art results followed by brief descriptions on various pristine branches of DRL research that may be centers of future research in this field of interest.

Strong-aroma Baijiu is a traditional Chinese spirit distilled from grains that undergo solid-state fermentation. At the end of each fermentation cycle, a significant quantity of Huangshui accumulates at the bottom of the fermentation pit, constituting one of the primary by-products in the brewing process of strong-flavor liquor. In this report, the chemical component analysis of Huangshui obtained from a strong-flavor liquor factory revealed a diverse array of organic acids, alcohols, esters, starch, reducing sugars, amino acids, and other compounds present in Huangshui. Additionally, two specialized solid-state fermentation models were developed to investigate the formation process of Huangshui. Our findings demonstrate a positive correlation between the yield of Huangshui and the initial moisture content of fermented grains. It is concluded that Huangshui is the percolate produced during the solid-state brewing process of strong-flavor liquor, with its water content originating from the initial moisture of fermented grains.

The log interpretation and evaluation of Chang 8 tight sandstone reservoir in Longdong West area, Ordos Basin, is facing great challenges due to the existence of low resistivity contrast oil pays. To better guide the exploration of oil resources in this area, the characteristics and control mechanism of low resistivity contrast oil pays were studied in this research. Firstly, according to the relative value of apparent resistivity increase rate of the target formation, the reservoir was divided into two types: low resistivity contrast oil pay (LRCP) and high resistivity oil pay (HRP). Then, the reservoir characteristics were studied by comparing and analyzing the experimental data, formation water data and logging data collected from the two reservoir types. On this basis, the control mechanism of LRCP was studied and summarized into reservoir micro factors and regional macro factors, respectively. It is found that the reservoir rock composition between LRCP and HRP is basically the same. Compared with HRP reservoir, the average porosity and permeability of LRCP reservoir are relatively better, but the pore structure is relatively poorer because of the high content of micro pores. When the filling pressure of crude oil is sufficient enough, the high oil saturation can be formed in LRCP reservoir. The high irreducible water saturation and high formation water salinity are the main micro factors reduced the reservoir resistivity. Besides, the difference of hydrocarbon expulsion capacity of source rock and the regional difference of formation water salinity are the macro factors influenced the distribution of LRCP and HRP from vertical and horizontal of the region. The formation of LRCP is controlled by the comprehensive influence of reservoir micro factors and regional macro factors. And the comprehensive consideration of the influence of micro factors and macro factors on LRCP is suggested during the log interpretation and evaluation.

Piceatannol is a naturally occurring polyphenolic compound that is widely found in grapes, blueberries, mushrooms, passion fruit and other edible fruits and vegetables. It has a variety of biological activities and pharmacological effects, including anti-inflammatory, antioxidation, antiaging, antiviral, antitumor, anticancer, antiatherosclerosis, antiparasitic, immunoregulatory, and cardiovascular protection effects. The aim of this study was to investigate the antiherpesvirus effects of piceatannol. Pseudorabies virus (PRV) belongs to the family Herpesviridae. PRV has a wide host range and can cause cytopathic effects (CPEs) in PK-15 cells. Therefore, PRV was used as a model to study the antiherpesvirus effect of piceatannol. In this study, we evaluated the antiviral activity of piceatannol against PRV in vitro and in vivo. The results showed that piceatannol could reatrain PRV multiplication in PK-15 cells in a dose-dependent manner. The 50% inhibitory concentration (IC50) was 0.0307 mg/mL, the IC50 was 0.0307 mg/mL, and the selectivity index (SI, CC50/IC50) was 3.68. The addition of piceatannol at different stages of PRV infection inhibited the viral adsorption and intracellular replication phases of PRV. Piceatannol significantly reduced the expression levels of the IE180, EP0, UL29, UL44, US6 and UL27 genes of PRV within 48 h, significantly reduced the expression levels of the PRV gB and gD proteins, and reduced PRV-induced apoptosis. Molecular docking showed that piceatannol had good binding activity with the PRV gB and gD proteins. The results of animal experiments in vitro indicated that piceatannol could delay the onset of disease, improve the survival rate of the mice (14.3%), reduce the viral load in the brain and kidney of the mice, alleviate the pathological changes in the mouse tissues and organs, and increase the levels of TNF-α, IEN-γ and IL-4 in the serum of the mice. These data indicate that piceatannol has good anti-PRV activity in vitro and in vivo, indicating that it could be a novel antiherpesvirus infection agent in the future.

Arylsulfatase and β-glucuronidase are two important enzymes in human, which play important role on dynamic equilibrium of steroidal estrogens. This work probably for the first time reported that hydrogen peroxide (H2O2), hypochlorite and peracetic acid (PAA) could effectively inhibit the activities of arylsulfatase and/or β-glucuronidase. The 50 percent of inhibitions (IC50) of H2O2, and PAA on arylsulfatase were found to be 142.90±9.00, 91.83±10.01, and 43.46±2.92 μM, respectively. The corresponding respective IC50 of hypochlorite and PAA on β-glucuronidase were 704.90±41.40 and 23.26±0.82 μM, while H2O2 showed no inhibition on β-glucuronidase. It was further revealed that the inhibition of hypochlorite on both arylsulfatase and β-glucuronidase was irreversible. On the contrary, the inhibition by H2O2 and PAA was reversible. Moreover, it was found that the inhibitions of arylsulfatase and/or β-glucuronidase by these three chemicals were pH-dependent, among which the inhibition by H2O2 was competitive and non-competitive for PAA. In general, H2O2 and hypochlorite can be endogenously produced in human, which suggested that the two compounds are potential endocrine disruption compounds (EDCs) as they can cause endocrine disruption via inhibition of arylsulfatase and β-glucuronidase. This work further indicated that any agent that can induce production of H2O2 or hypochlorite in human is potential EDC, which explains why some EDCs with very weak or no estrogenic potency can cause endocrine disruption that confirmed in epidemiological studies.

The efficiencies of conventional triple organic Rankine cycle (TORC) configurations are restricted by the low critical temperatures of common working fluids (＜320 °C). This paper proposes a high-temperature TORC system. A near-azeotropic mixture biphenyl/diphenyl oxide (BDO), which has stellar track record in the high-temperature ORC applications, is innovatively adopted as the top and middle ORC fluid simultaneously. The top cycle evaporation temperature is up to 400 °C in view of BDO’s high stability. Five conventional organic fluids are chosen for the bottom ORC. Fundamentals of the TORC system are illustrated, and mathematical models are built. Thermo-economic performance is investigated. The results hint that the optimal thermodynamic property is achieved on the use of benzene as the bottom fluid. The maximum thermal and exergy efficiencies are respectively 40.86% and 74.14%. The largest irreversible loss occurs inside the heat exchanger coupling the middle and bottom ORCs, accounting for above 30% of the total entropy generation. The levelized energy cost (LEC) is 0.0284 $/kWh. Given the same heat source condition, the TORC system can boost efficiency by 1.02% and drive down LEC by 0.0024 $/kWh compared with a BDO mixture-based cascade ORC.

Edge detection is one of the key issues in the field of computer vision and remote sensing image analysis. Although many different edge-detection methods have been proposed for gray-scale, color, and multispectral images, they still face difficulties when extracting edge features from hyperspectral images (HSIs) that contain a large number of bands with very narrow gap in the spectral domain. Inspired by the clustering characteristic of the gravitation, a novel edge-detection algorithm for HSIs is presented in this paper. In the proposed method, we first construct a joint feature space by combining the spatial and spectral features. Each pixel of HSI is assumed to be a celestial object in the joint feature space, which exerts gravitational force to each of its neighboring pixel. Accordingly, each object travels in the joint feature space until it reaches a stable equilibrium. At the equilibrium, the image is smoothed and the edges are enhanced, where the edge pixels can be easily distinguished by calculating the gravitational potential energy. The proposed edge-detection method is tested on several benchmark HSIs and the obtained results were compared with those of three state-of-the-art approaches. The experimental results confirm the efficacy of the proposed method

Light-colored and transparent polyimide (PI) films with good high-temperature dimensional stability are highly desired for advanced optoelectronic applications. However, in practice, the simultaneous achievement of good optical and thermal properties in one PI film is usually difficult due to the inter-conflicting molecular design for the polymers. In the present work, a series of PI-SiO2 nanocomposite films (ABTFCPI) were developed based on the PI matrix derived from hydrogenated pyromellitic anhydride (HPMDA) and an aromatic diamine containing benzanilide and trifluoromethyl substituents in the structure, 2,2'-bis(trifluoromethyl)-4,4'-bis[4-(4-aminobenzamide)]biphenyl (ABTFMB). The inorganic SiO2 fillers were incorporated into the nanocomposite films with the form of colloidal nanoparticles dispersed in the good solvent of N,N-dimethylacetamide (DMAc) for the PI matrix. The derived ABTFCPI nanocomposite films showed good film-forming ability, flexible and tough nature, good optical transparency, and good thermal properties with the loading amounts of SiO2 up to 30 wt% in the system. The ABTFCPI-30 film with the SiO2 content of 30 wt% in the film showed the optical transmittance of 79.6% at the wavelength of 400 nm (T400) with a thickness of 25 μm, the yellow index (b*) of 2.15, and the 5% weight loss temperatures (T5%) of 491 oC, which are all comparable to those the pristine ABTFCPI-0 matrix without filler (T400=81.8%; b*=1.77; T5%=492 oC). Meanwhile, the ABTFCPI-30 film exhibited obviously enhanced high-temperature dimensional stability with the linear coefficients of thermal expansion (CTE) of 25.4×10-6/K in the temperature range of 50 to 250 oC, which is much lower than that of the AMTFCPI-0 film (CTE=32.7×10-6/K).

As an important support for power system with high penetration of renewable energy, energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption, and its installed capacity under the source-grid-load scenario is rising year by year, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under the source-grid-load scenarios, and proposes a comprehensive benefit evaluation method of energy storage projects based on fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super efficiency data envelopment analysis (DEA) model, which considers the perspective of economic and social environment. Firstly, the functional requirements of energy storage on the source-grid-load scenarios are explored respectively, and the characteristics of various functions are analyzed to form functional combination schemes. Secondly, index modeling is carried out from three aspects: the whole life cycle cost, functional combination benefit and social environmental benefit, and the comprehensive benefit evaluation index system of energy storage project is proposed, which includes both economic and social environment. Then, the intuitionistic trapezoidal fuzzy number is combined with DEMATEL to form an effective analysis method for the input-output relationship of the indexes, and the comprehensive evaluation is realized based on the super efficiency DEA model. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios respectively.

An optimal scheduling strategy for cooling, heating and power (CCHP) joint-power-supply system is proposed to improve energy utilization and minimize costs in this paper. Firstly, the mathematical model of CCHP system is established. Particle swarm optimization (PSO) is used to optimize the regularization coefficient C and the kernel parameter λ which can affect the prediction accuracy of KELM(PSO-KELM). Then PV generation and load prediction model are established by PSO-KELM. In order to jump out of local optimal solution, Cauchy variation is introduced in SFLA local update, and adaptive mutation operation is carried out on SFLA individuals. The predictions of PV generation and load power by PSO-KELM are imported into the objective function, and the microgrid dispatching model is solved by the improved SFLA algorithm. Compared with the traditional GA-KELM and KELM, PSO-KELM has faster convergence and prediction accuracy. Compared with the power supply division, the operation cost of the power grid is reduced by the proposed optimization dispatching strategy of CCHP micro-grid.

Cadmium (Cd) is a toxic non–essential element to plants, and its accumulation in crops has significant adverse effects on human health. The cross–talk between copper (Cu) and Cd has been reported, but the molecular mechanisms remain unknown. Here, the function of wheat Cu transporter 3D (TaCOPT3D) in Cd tolerance was investigated. The TaCOPT3D transcripts significantly accumulated in wheat roots under Cd exposure. To test whether TaCOPT3D was involved in response to Cd stress, overexpressing lines with altered expression of TaCOPT3D transporters were compared to wild–type (WT) plants. The results showed that, under 20 μM Cd treatment, TaCOPT3D–overexpression lines exhibited more biomass and lower Cd accumulation in roots, shoots, and grains compared to WT plants. In addition, the TaCOPT3D–overexpression lines demonstrated less reactive oxygen species (ROS) and a greater amount of active antioxidant enzymes under Cd conditions than WT plants. Moreover, TaCOPT3D–overexpression lines highly reduced Cd accumulation under exposure to 20 μM Cu. The regulation pathway of TaCOPT3D in response to Cd stress was investigated, and transcription factor (TF) TaWRKY22, which targeted the TaCOPT3D promoter, was identified. Therefore, TaCOPT3D can serve as a candidate gene for decreasing Cd accumulation in wheat through genetic engineering.

Baduanjin exercise is a traditional Chinese health-Qigong routine, created by an ancient physician for health promotion. Its mild-to-moderate exercise intensity is suitable for individuals with medical conditions. Recently, a large number of trials were conducted to investigate the effects of Baduanjin exercise in patients with chronic obstructive pulmonary disease (COPD). It needs to be determined whether Baduanjin exercise prescription is beneficial for the management of COPD patients. Thus, we conducted a systematic review to objectively evaluate the existing literature on this topic. We searched six databases (PubMed, Web of Science, Cochrane Library, Scopus, CNKI, and Wanfang) from its inception till early May, 2018. The adapted PEDro scale was used for study quality assessment of all randomized controlled trials (RCT). The pooled effect size (Hedge’s g) of exercise capability (6-Minute Walking Test, 6-MWT), lung function parameters (forced expiratory volume in first second, FEV1; forced volume vital capacity, FVC; FEV1/FVC ratio), and quality of life were calculated based on the random-effects model. Twenty RCTs (n = 1975 COPD patients) were included in this review, with sum scores of the adapted PEDro scale between 5 and 9. Study results of meta-analysis indicate that Baduanjin is effective in improving exercise capability (Hedge’s g = 0.69, CI 0.44 to 0.94, p < 0.001, I2 = 66%), FEV1 (Hedge’s g = 0.47, CI 0.22 to 0.73, p < 0.001, I2 = 68.01%), FEV1% (Hedge’s g = 0.38, CI 0.21 to 0.56, p < 0.001, I2 = 54.74%), FVC (Hedge’s g = 0.39, CI 0.22 to 0.56, p < 0.001, I2 = 14.57%), FEV1/FVC (Hedge’s g = 0.5, CI 0.33 to 0.68, p < 0.001, I2 = 53.49%), and the quality of life of COPD patients (Hedge’ s g = - 0.45, CI -0.77 to - 0.12, p < 0.05, I2 = 77.02%), as compared to control groups. Baduanjin exercise as an adjunctive treatment may potentially improve exercise capability and pulmonary function of COPD patients as well as quality of life. Baduanjin exercise could be tentatively prescribed for COPD in combination with the conventional rehabilitation program to quicken the process of recovery. To confirm the positive effects of Baduanjin exercise for COPD patients, future researchers need to consider our suggestions mentioned in this article.

Fresh water is valuable nonrenewable resource and plays an important role of maintaining economic and social development. Condisering its large population and consumption potential, water resources deficit will certainly impede basic industries sustainable development of China in the near future. Application of sewage irrigation, to some extent, was regarded as an alternative way to solve the problem of agricultural irrigation water shortage in some areas (such as North China). However, accompanied with extensive implementation of sewage irrigation, some problems on sewage irrigation in agriculture are gradually obvious, especially serious pollution and destruction for farmland. In this paper, the effects of sewage irrigation on soil physical (soil bulk density, soil resistance to penetration and field capacity), chemical (pH, soil organic matter, nitrogen, phosphrous, patassium, heavy metal and organic pollutants) and biological characteristics (soil microorganism and enzyme activities) of farmland in China were systematically reviewed on the base of the current utilization status of China’s farmland sewage irrigation and some feasible suggestions were put forward to the development prospect for the future. This review will be beneficial for promoting healthy development of sewage irrigation and providing theoretical support for reclamation and high efficiency of effluents in China.

The comparison of three types of ionosonde data from Europe during an Interplanetary Coronal Mass Ejection (ICME) and a Stream Interaction Regions (SIRs) / Corotating Interaction Regions (CIRs) -driven geomagnetic storm event is detailed in this study. The selected events are 16-20 March 2015 for the ICME-driven and 30 May to 04 June 2013 for the SIR/CIR-driven one. Ionospheric data from three European ionosonde stations, namely Pruhonice (PQ), Sopron (SO) and Rome (RO), are investigated. The ionospheric F2-layer responses to these geomagnetic events are analyzed with the ionospheric foF2 and h’F2 parameter, the calculated deltafoF2 and deltahF2 values, ratio of Total Electron Content (rTEC) and Thermosphere, Ionosphere, Mesosphere, Energetics and Dynamics (TIMED) satellite Global Ultraviolet Imager (GUVI) thermospheric [O]/[N2] measurement data. The storm-time and the quiet day mean values are also compared, and it can be concluded that the quiet day curves are similar at all stations while the storm-time ones showed the latitudinal dependence during the development of the storm. As a result of the electron density comparison, during the two events it can be concluded that SSC that characterized the ICME induced a Travelling Atmospheric Disturbance (TAD) seen in the European stations, while this is not in the SIR/CIR-driven ionospheric storm, which showed a stronger and more prolonged negative effect in all stations probably due to the season.

The rapid development of electrochemical CO2 reduction offers a promising route to convert in-termittent renewable energy into products of high value-added fuels or chemical feedstocks. However, low faradaic efficiency, low current density, and a narrow potential range still limited the large-scale application of CO2RR electrocatalyst. Herein, monolith 3D bi-continuous nano-porous Bismuth (np-Bi) electrodes are fabricated via a simple one-step electrochemical dealloying strategy from Pb-Bi binary alloy. The unique bi-continuous porous structure ensures highly effective charge transfer, meanwhile the controllable millimeter-size geometric porous structure enables easy catalyst adjustment to expose highly suitable surface curvatures with abundant reactive sites. This results in a high selectivity of 92.6% and superior potential window (400 mV, selectivity >88%) for electrochemical reduction of carbon dioxide to formate. Our scalable strategy provides a feasible pathway for mass-producing high-performance and versatile CO2 electrocatalysts.

BACKGROUND: Chronic hepatitis B infected with Hepatitis B virus remains a major health concern worldwide. Despite standard interferon-α and nucleotide analogues have been shown to reduce the deterioration of liver disease among chronic hepatitis B patients, covalently closed circular DNA was still difficult to eradicate. METHODS: A literature search of Pubmed and Web of science was performed with the following key words: ‘CRISPR’, ‘CRISPR/Cas9’, ‘hepatitis B’, ‘HBV’, ‘chronic hepatitis B’ and ‘HBV cccDNA’. The information about CRISPR/Cas9 for the treatment of HBV cccDNA or hepatitis B was reviewed. RESULTS: CRISPR/Cas9 could treat hepatitis B through suppressing or clearing HBV cccDNA with different gRNAs. CONCLUSION: With the emergence of CRISPR/Cas9 (the RNA-guided clustered regulatory interspaced short palindromic repeats, CRISPR) editing technology, clearance of hepatitis B virus and better prevention of liver carcinoma seemed to be possible.

Thermal fluctuations in two-dimensional (2D) isotropy systems at non zero finite temperatures can destroy the long-range (LR) magnetic order due to Mermin-Wanger theory. Interestingly, the magnetic anisotropy related to spin-orbit coupling (SOC) could stabilize magnetic order in 2D systems. Recently, 2D FexGeTe2 (3≤x≤7) with high curie temperature (TC), as a typical 2D van der Waals metallic ferromagnet, has not only made significant progress in synthetic methods and controlling ferromagnetism (FM), but also actively explored many device applications. In this Review, we introduce six experimental methods, ten ferromagnetic modulation strategies, and three spintronic devices of 2D FexGeTe2 materials. Overall, we have outlined the challenges and potential research directions in this field.

Plants of the genus Monochoria have long been utilized in food, cosmetics, and traditional herbal treatment. Thailand has the highest species diversity of this genus and a new member, Monochoria angustifolia (G. X. Wang) Boonkerd & Tungmunnithum has been recently described. This plant is called “Siam Violet Pearl” as a common name or “ไข่มุกสีม่วงแห่งสยาม” as its vernacular name in the same meaning in Thai language. Despite their importance, few researches on Monochoria species have been conducted. This study, thus, provided the results to fill in this gap by: i) determining flavonoids phytochemical profiles of 25 natural populations of M. angustifolia covering the whole floristic regions in Thailand, and ii) determining antioxidant activity using various antioxidant assays to investigate the probable mechanism. The results revealed that M. angustifolia presented a higher flavonoid content than the outgroup, M. hastata. Our results also revealed that flavonoids might be used to investigate Monochoria evolutionary connections and for botanical authentication. The various antioxidant assays revealed that M. angustifolia extracts preferentially act through a hydrogen atom transfer antioxidant mechanism. Pearson correlation analysis indicated significant correlations emphasizing that the antioxidant capacity is most probably the result of a complex phytochemical combinations rather than of a single molecule. Altogether, these results showed that this new species provide an attractive alternative starting material with phytochemical variety and antioxidant potential for the phytopharmaceutical industry.

Intelligent systems are increasingly present in various areas of society, gaining special relevance in healthcare environments. In this work, grounded on previous developments proposed by the authors, the evolution and improvement of a novel intelligent system focused on the diagnosis of obstructive sleep apnea (OSA) is addressed. To do this, starting from two packages of information of a heterogeneous nature, and deploying a set of Machine Learning classification algorithms, focused each of them on different levels of the apnea-hypopnea index (AHI), as well as a set of cascaded expert systems, it is possible to obtain a series of risk metric pairs (Statistical Risk, Symbolic Risk) for each AHI level, understood as a warning forecast associated with the early detection of the pathology. The risk indicators of each pair are subsequently aggregated by means of a symbolic inference system, whose knowledge base was determined using the automatic rule generation approach proposed by Wang and Mendel. At the output of each inference system, a risk indicator is obtained for each AHI level, the Apnea Risk, whose interpretation makes it possible to discriminate between patients who could suffer OSA and those who do not, as well as to generate the appropriate recommendations. For the initial tests of the system, the design and development of a specific software artifact was carried out using data from 4,400 patients from the Álvaro Cunqueiro Hospital in Vigo, obtaining when applied to the test set AUC values within the range 0.74–0.88, which invites optimism and points to the benefits expected from the architecture of the proposed intelligent system.

In this paper, under the symmetric entropy and the scale squared error loss functions, we consider the maximum likelihood (ML) estimation and Bayesian estimation of the Shannon entropy and Rényi entropy of the two-parameter inverse Weibull distribution. In the ML estimation, the dichotomy is used to solve likelihood equation. In addition, the approximation confidence interval is given by the Delta method. Because the form of estimation results is more complex in the Bayesian estimation, the Lindley approximation method is used to achieve the numerical calculation. Finally, Monte Carlo simulations and a real data set are used to illustrate the results derived. By comparing the mean square error between the estimated value and the real value, it can be found that the performance of ML estimation of Shannon entropy is better than that of Bayesian estimation, and there is no significant difference between the performance of ML estimation of Rényi entropy and that of Bayesian estimation.

The E-learning system has achieved great development after the pandemic. In this work, we proposed three artificial intelligence-based enhancements to our linguistic interactive E-learning system from different aspects. Compared with the original phonetic transcription exam system, our enhancements include an MFCC+CNN-based disordered speech classification module, a Transformer-based Grapheme-to-Phoneme converter, and a Tacotron2-based IPA-to-Speech speech synthesis system. This work not only provides a better experience for the users of this system but also explores the utilization of artificial intelligence technologies in the E-learning field and linguistic field.

A series of Ni/KIT6 catalystprecusors with 25wt.%Ni loading amount were reduced in H₂ at 400, 450, 500, and 550ºC, respectively. The studied catalysts were investigated by XRD, Quasiin-situ XPS, BET, TEM, and H₂-TPDanalysis methods.It was found that reduction temperature is an important factor affecting the hydrodeoxygenation (HDO) performance of the studied catalysts. The reduction temperature influences mainly the content of active components, crystal size, and the abilityfor adsorbing and activatingH2. The developed pore structure and large specific surface area of the KIT-6 support favored the Ni dispersion.The RT450 catalyst, which was prepared in H₂ atmosphere at 450 ºC, has the best HDO performance. Ethyl acetate can be completely transformed, and maintain 96.8% ethane selectivity and 3.2% methane selectivity at 300 ºC. The calculated apparent activation energies of the prepared catalysts increased in the following order: RT550 > RT400 > RT500 > RT450.

A large core size and bending resistance are very important properties of mid-infrared energy transfer fibers, but large core sizes usually lead to a deterioration of bending properties. A negative-curvature nested node-free anti-resonant hollow-core fiber (AR-HCF) based on quartz is proposed. It was made by adding a nested layer to a previous AR-HCF design to provide an additional anti-resonance region while keeping the gap between adjacent tubes strictly correlated to the core diameter to produce a node-free structure. These features improve the fiber’s bending resistance while achieving a larger core diameter. The simulation results show that the radial air-glass anti-resonant layer is increased by the introduction of the nested anti-resonant tube, and the weak interference overlap between the fiber core and the cladding mode is reduced, so the fiber core’s limiting loss and the sensitivity to bending are effectively reduced. When the capillary wall thickness t of the fiber is 0.71 μm, the core diameter D is 70 μm, the ratio of the inner diameter of the cladding capillary to the core diameter d/D is 0.62, and the diameter of the nested tube is d0=29 μm, the fiber has a lower limiting loss at the wavelength of 2.79 μm, and the limiting loss is 3.28×10-4 dB/m. At the same time, the optimized structure also has good bending resistance. When the bending radius is 30 mm, the bending loss is only 4.72×10-2 dB/m. To our knowledge, this is the first research to achieve an anti-bending low-loss micro-structure hollow fiber with a bending radius of less than 30 mm in the 2.79 μm band. An anti-bending low-loss anti-resonant hollow-core fiber with this structure constitutes a reliable choice for the light guiding system of a 2.79 μm band erbium laser therapy instrument.

Abstract: Microstructural and mechanical properties of the eutectic Sn58Bi and micro-alloyed Sn57.6Bi0.4Ag solder alloys were compared. With the addition of Ag micro-alloy, the tensile strength was improved and this is attributed to a combination of microstructure refinement and an Ag3Sn precipitation hardening mechanism. However, ductility is slightly deteriorated due to the brittle nature of the Ag3Sn intermetallic compounds (IMCs). Additionally, a board level reliability study of Ag micro-alloyed Sn58Bi solder joints produced utilising a surface-mount technology (SMT) process, were assessed under accelerated temperature cycling (ATC) conditions. Results reveal that micro-alloyed Sn57.6Bi0.4Ag has a higher characteristic lifetime with a narrower failure distribution. This enhanced reliability corresponds with improved bulk mechanical properties. It is postulated that Ag3Sn IMCs are located at the Sn-Bi phase boundaries and suppress the solder microstructure from coarsening during the temperature cycling, hereby extending the time to failure.

We propose a novel plasmon nano-optical antenna that consists of three vertically superimposed discs with different materials. Two symmetrical nanometer-scale Yagi antenna elements with gold-material are embedded into the surface of the middle disc with silicon dioxide. Based on plasmon theory and Yagi antenna principle, we explore the properties of the far-field radiation and near-field transmission of the antenna in near infrared band. It is found that the pattern of the xoy plane in the antenna can be adjusted in arbitrary direction. The far-field pattern and near-field transmission spectrum can be reconfigured by changing the angle a of the Yagi antenna elements in the middle disc. Moreover, we also discuss the influences of the widths and lengths of the elements on the near-field transmission spectrum when a is fixed at 0 degree.

Current COVID-19 vaccines can effectively reduce disease severity and hospitalisation; however, they are not considerably effective in preventing infection and transmission. In this context, mucosal vaccines are pertinent to prevent SARS-CoV-2 infection and spread. In this study, we generated a replication-competent recombinant chimeric influenza A virus (IAV) expressing the receptor-binding domain (RBD) of SARS-CoV-2 prototype in the C-terminus of the neuraminidase (NA) of A/Puerto Rico/08/1934 H1N1 (PR8). The remaining seven segments from A/WSN/1933 H1N1 (WSN) were named PR8NARBD/WSN. We observed that the recombinant virus with the WSN backbone demonstrated improved expression of NA and RBD. A single intranasal dose of PR8NARBD/WSN in mice generated robust mucosal immunity, neutralising antibodies, cellular immunity, and tissue-resident memory T cells specific to SARS-CoV-2 and IAV. Importantly, immunisation with PR8NARBD/WSN viruses effectively protected mice against lethal challenges with H1N1, H3N2 IAV, and SARS-CoV-2 Beta variant and significantly reduced lung viral loads. Overall, our research demonstrates the promising potential of PR8NARBD/WSN as an attractive vaccine against emerging SARS-CoV-2 variants and influenza A virus infections.

Birefringence of 3 × 10^-3 is demonstrated inside cross-sectional regions of 100 µm, inscribed by axially stretched Bessel-beam-like fs-laser pulses along the c-axis inside sapphire. A high birefringence and retardance of λ/4 at mid-visible spectral range (green) can be achieved utilizing stretched beams with an axial extension of 30-40 µm. Conditions of laser writing chosen ensure that there are no formations of self-organised nano-gratings. This method can be adopted for the creation of polarisation optical elements and fabrication of spatially varying birefringent patterns for optical vortex generation.

This paper investigates the evolution of microstructures and precipitations of an ultra-low iron alloy 625 subjected to long term aging treatment by scanning electron microscope (SEM) and X-ray diffraction(XRD). Use ASTM G28A acid Fe3(SO4)2 erosion to represent intergranular corrosion weightlessness and corrosive morphology. The result shows that alloy at 750C by aging treatment for 40h, precipitated γ'' phase in the grain boundary. In high density area of γ'' phase, occurs γ'' phase to δ phase degeneration transformation by aging treatment for 200h and the needle-like δ phase becomes more with time prolonged. And γ'' phase degenerated to δ phase completely until treated for 1000h. The sample which has aging treatment tends to have intergranular corrosion and mainly because alloy element spreading leads to dilution area and grain boundary precipitated phase, plus interlaced δ phase’s dissolving, which makes sample grain particle fall off and this results in apparent weightlessness. The weightlessness rate(WLR) is related with precipitated volume score. With aging sensitization time change, can be described by Johnson-Mehl-Avrami equation, i.e.: $WLR=44.32\left[1-\text{exp}\left(-\frac{t}{10.99}\right)\right]+44.62\left[1-\text{exp}\left(-\frac{t}{327.8}\right)\right]+1.267\left(mm/a\right)$

Background: The scaffold protein tyrosine kinase substrate 4 (TKS4) undergoes tyrosine phos-phorylation by the epidermal growth factor receptor (EGFR) pathway via Src kinase. The TKS4 deficiency in humans is responsible for the manifestation of a genetic disorder known as Frank-Ter Haar syndrome (FTHS). Based on our earlier investigation, the absence of TKS4 triggers migration, invasion, and epithelial-mesenchymal transition (EMT)-like phenomena while concurrently suppressing cell proliferation in HCT116 colorectal carcinoma cells. This indicates that TKS4 may play a unique role in the progression of cancer. In this study, we demonstrated that the enhancer of zeste homolog 2 (EZH2) and the histone methyltransferase of polycomb repressive complex 2 (PRC2) are involved in the migration, invasion, and EMT-like changes in TKS4-deficient cells (KO). EZH2 is responsible for the maintenance of the trimethylated lysine 27 on histone H3 (H3K27me3). Methods: We performed the transcriptome sequencing, chromatin immunoprecipitation, protein and RNA quantitative studies, cell mobility, invasion, and proliferation studies combined with/without EZH2 activity inhibitor 3-deazanoplanocine (DZNep) Results: We detected an elevation of global H3K27me3 levels in the TKS4 KO cells, which could be reduced with treatment with DZNep, an EZH2 inhibitor. Inhibition of EZH2 activity reversed the phenotypic effects of the knockout of TKS4, reducing the migration speed and wound healing capacity of the cells as well as decreasing the invasion capacity, while the decrease in cell prolif-eration became stronger. In addition, inhibition of EZH2 activity also reversed most epithelial and mesenchymal markers. We investigated the wider impact of TKS4 deletion on the gene expression profile of colorectal cancer cells using transcriptome sequencing of wild-type and TKS4 knockout cells, particularly before and after treatment with DZNep. Additionally, we observed changes in the expression of several protein-coding genes and long non-coding RNAs that showed a recovery in expression levels following EZH2 inhibition. Conclusions: Our results indicate that the removal of TKS4 causes a notable disruption in the gene expression pattern, leading to the disruption of several signal transduction pathways. Inhibiting the activity of EZH2 can restore most of these transcriptomics and phenotypic effects.

This investigation delves into an examination of the growth dynamics observed in Central Taiwan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs This investigation delves into an examination of the growth dynamics observed in Central Tai-wan Science Park (CTSP) and Silicon Glen in Scotland, with a specific focus on their energy, environmental, and economic management. The aim is to predict and evaluate the latest advancements and applications of technology. In terms of energy, CTSP focuses on Taiwan's supply security and green transformation challenges, while Silicon Glen emphasizes Scotland's wind energy generation technologies. Both regions are committed to the development of renewable energy and smart grids. Regarding environmental aspects, CTSP and Silicon Glen prioritize environmental protection and sustainable development by implementing measures for environmental monitoring. In terms of economic management, CTSP, and Silicon Glen serve as key technology industry hubs in Taiwan and Scotland, respectively, attracting numerous high-tech and startup enterprises. Various means facilitate the growth of industries and foster innovations in different industrial spheres. Important factors contributing to this growth include policy support, availability of research materials, and provision of infrastructure. This research paper compares the successful case studies of two industrial parks, along with their environmental and economic management strategies. It explores the management principles that ensure the sustainable development and economic growth of industrial parks, aiming to assist decision-makers and relevant stakeholders in evaluating the sustainable development planning of industrial parks.

We propose Reduced Collatz Conjecture that is equivalent to Collatz Conjecture, which states that every positive integer can return to an integer less than it, instead of 1. Reduced Collatz Conjecture should be easier because some properties are presented in reduced dynamics, rather than in original dynamics (e.g., ratio and period). Reduced dynamics is a computation sequence from starting integer to the first integer less than it, and original dynamics is a computation sequence from starting integer to 1. Reduced dynamics is a component of original dynamics. We denote dynamics of x as a sequence of either computations in terms of ``I'' that represents (3*x+1)/2 and ``O'' that represents x/2. Here 3*x+1 and x/2 are combined together, because 3*x+1 is always even and followed by x/2. We formally prove that all positive integers are partitioned into two halves and either presents ``I'' or ``O'' in next ongoing computation. More specifically, (1) if any positive integer x that is i module $2^t$ (i is an odd integer) is given, then the first t computations (each one is either ``I'' or ``O'' corresponding to whether current integer is odd or even) will be identical with that of i. (2) If current integer after t computations (in terms of ``I'' or ``O'') is less than x, then reduced dynamics of x is available. Otherwise, the residue class of x (namely, i module $2^t$) can be partitioned into two halves (namely, i module $2^{t+1}$ and $i+2^t$ module $2^{t+1}$), and either half presents ``I'' or ``O'' in intermediately forthcoming (t+1)-th computation.

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.

Variations in the implant thread shape and occlusal load behavior may result in significant changes in the biological and mechanical properties of dental implants and surrounding bone tissue. Most previous studies consider a single implant thread design, an isotropic bone structure, and a static occlusal load. However, the effects of different thread designs, bone material properties, and loading conditions are important concerns in clinical practice. Accordingly, the present study performs Finite Element Analysis (FEA) simulations to investigate the static, quasi-static and dynamic response of the implant and implanted bone material under various thread designs and occlusal loading directions (buccal-lingual, mesiodistal and apical). The simulations focus specifically on the von Mises stress, displacement, shear stress, compressive stress and tensile stress within the implant and the surrounding bone. The results show that the thread design and occlusal loading rate have a significant effect on the stress distribution and deformation of the implant and bone structure during clinical applications. Overall, the results provide a useful insight into the design of enhanced dental implants for an improved load transfer efficiency and success rate.

COVID-19 is a pandemic with no cure. There is an urgent need for low-cost interventions. Macroclimate work through affecting microclimate. In many situations, man-made microclimate, such as air conditioning, may override the effect of natural macroclimate in determining SARS-CoV-2 pathogenicity. Ambient temperature (AT) has been roughly associated to SARS-CoV-2 transmission. To translate into a feasible practice in controlling COVID-19 pandemic, in-depth and implementable knowledge of AT role in SARS-CoV-2 transmission should be unveiled. This study aimed to determine if there is a ‘safe’ temperature that is comfortable to human beings while significantly inhibitory for SARS-CoV-2 pathogenicity. Data on monthly new deaths or new cases per million population (MDPM or MCPM) and monthly cumulated days with more cases than the previous day (DI) from March 2 to June 30, 2020 were collected from all 118 countries with population over five million. Monthly average AT negatively correlated with the transmission parameters. A significant decrease in transmission was observed when AT reached above 20 ºC. Monthly average (not average high) AT of countries with MDPM <2, MCPM<10, or DI<=7 was found to be between 24.54 and 26.89 ºC (25.18 ºC on average) with average standard error of 4.81. Thus, average AT <20, 20-25, >25 ºC were considered as high, medium, and low risk AT. Furthermore, MDPM in countries with AT <20 ºC were 80.93, 50.23, 13.52, and 5.05 times of those in countries with AT >25 ºC in March, April, May, and June, respectively. MDPM low-risk rates (<2) in countries with AT >25 ºC were 100, 83.33, 52.73, and 52.46%, respectively. In countries with AT <20 ºC, the trends were opposite. Setting indoor temperature to 25 ºC could decrease the need of social distancing for containing SARS-CoV-2 transmission. Ventilation and sanitizing the air with ultraviolet light in nonbusiness hours may be additionally effective. Cooling indoor temperature too low may be a reason of COVID-19 outbreak in some high AT countries. Authorities and the general population can evaluate COVID-19 risk level and manipulate microclimate to reduce the risk anywhere anytime based on local day average AT.

Lactic acid (LA) is a significant byproduct in Baijiu fermentation, with both D(-)-lactic acid (D(-)-LA) and L-lactic acid (L(+)-LA) being present due to the diverse microbial metabolism involved. L(+)-LA, a key industrial raw material, is metabolizable by humans, unlike D(-)-LA. This study aims to isolate microorganisms from fermented grains that preferentially produce L(+)-LA and apply these strains to Baijiu fermentation processes. We analyzed 106 commercially available Baijiu samples, along with fermented grains, yellow water, and Baijiu samples from 10 Baijiu factories, confirming the coexistence of D(-)-LA and L(+)-LA in fermentation products. Notably, a strong correlation was found between L(+)-LA in fermented grains and L-ethyl lactate (L(+)-EL) in Baijiu. Microbial community analysis revealed that Lactobacillus and Bacillus were the dominant bacterial groups, with a succession of microbial communities throughout fermentation. Two strains, A6 and B12, identified as Bacillus licheniformis and Bacillus cereus, respectively, were isolated for their high selectivity in L(+)-LA production. Both strains demonstrated a high yield of L(+)-LA in fermentation tests. Incorporating these strains into both liquid- and solid-state fermentation systems markedly increased the proportion of L(+)-EL relative to total ethyl lactate in Baijiu. This study successfully isolated and applied L(+)-LA-producing strains to fermentation models, offering a practical strategy for increasing L(+)-LA content in Baijiu.