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A kind of Agriophyllum squarrosum bread (SMMB) was developed with Agriophyllum squarrosum flour and wheat flour as main raw materials. In this study, the formula of SMMB was optimized by single factor tests and response surface test. Then the texture, color and flavor of SMMB under optimized condition were compared with traditional bread (BMB) by using texture analyzer, colorimeter and gas chromatography-ionmobility spectrometry (GC-IMS). The results showed that when the proportion of Agriophyllum squarrosum flour in the mixed powder was 19.1%, and based on the total amount of mixed powder, adding of 2.5% yeast, 14.5% sugar, 10% butter, 1% edible salt, 0.5% ameliorant as well as 50% water, the SMMB was golden in color, full in shape, exquisite and uniform in internal organization, and had a unique flavor of Agriophyllum squarrosum. The SMMB also had the highest sensory score of 86.96 under the optimized condition. Compared with BMB, the color of SMMB was obviously different with decreased lightness, but increased redness and yellowness. The hardness, cohesion and elasticity were also increased in SMMB. The main flavor substances of the two types of bread were similar, but the contents of alcohols, aldehydes and ketones in SMMB were relatively higher, while the contents of esters and heterocyclic substances were lower than that of BMB. The different relative contents of flavor substances endowed SMMB with higher mellow, citrus, grass and malty flavor, while the flavor of ester, nutty and toasty was lower. This project would provide a theoretical basis for the application of Agriophyllum squarrosum in bread.

Abstract As one of the most common spatial light modulators, linear micromirror arrays (MMAs) based on microelectromechanical system (MEMS) processes are currently utilized in many fields. However, two crucial challenges exist in the fabrication of such devices: the adhesion of silicon microstructures caused by anodic bonding and the destruction of the suspended silicon film due to residual stress. To solve these issues, an innovative processing method assisted by temporary anchors is presented. This approach effectively reduces the span of silicon microstructures and improves the Euler buckling limit of the silicon film. Importantly, these temporary anchors are strategically placed within the primary etching areas, enabling easy removal without additional processing steps. As a result, we successfully achieved wafer-level, high-yield manufacturing of linear MMAs with a filling factor as high as 95.1%. Demonstrating superior capabilities to those of original MMAs, our enhanced version boasts a total of 60 linear micromirror elements, each featuring a length-to-width ratio of 52.6, and the entire optical aperture measures 5 mm × 6 mm. The linear MMA exhibits an optical deflection angle of 20.4° at 110 Vdc while maintaining exceptional deflection flatness and uniformity. This study offers a viable approach for the design and fabrication of thin-film MEMS devices with high yields, and the proposed MMA is promising as a replacement for digital micromirror devices (DMDs, by TI Corp.) in fields such as spectral imaging and optical communication.

In order to explore the effects of different drying methods on the properties of sour cassava starch (SCS), which were processed from cassava starch by lactobacillus fermentation, and then dried under five drying methods including hot air drying (HA), heat pump drying (HP), vacuum freeze drying (VF), spray drying (SD) and sun-drying (S). The properties of SCS were determined, and the comprehensive score was evaluated by coefficient of variation method. The results showed that the SCS processed by HA, with the highest span value of 2.36, had the lowest clarity, blue number and oil retention of 21.57%, 8.96 and 1.74 g/g, respectively. The SCS dried by HP had the lowest specific area of 351.83 m2/kg, had the highest bulk density, water separation and retrogradation of 0.87 g/m, 33.02% and 74.89%, respectively. The product dried by VF, with the lowest bulk density, repose angle and water separation of 0.73 g/mL, 37.49° and 4.64%, respectively, with the highest clarity. Blue number and water-holding ability of 27.03%, 19.64 and 1.43 g/g, respectively, as well as the highest solubility. The SCS processed by SD had the highest specific area, repose angle and oil retention of 407.43 m2/kg, 54.11° and 2.33 g/g, respectively. However, it had the lowest retrogradation of 67.00%. The SCS dried by S, with the lowest span value and water-holding ability of 1.73 and 1.08 g/g. Comprehensive score results indicated that the SCS dried by VF, SD, S, HA and HP, with the comprehensive score of 0.60, 0.38, 0.18, −0.50 and −0.64, respectively. In summary, the best properties of SCS products could be obtained by VF, followed by SD, and then by S, HA and HP were the worst.

Low-emittance photoinjector-enabled cutting-edge scientific instruments, such as free-electron lasers, inverse Compton scattering light sources, and ultrafast electron diffraction, will greatly benefit from the improved repetition rate. In this paper, we proposed a specifically designed S-band radio frequency (RF) photoinjector to obtain low emittance and kilohertz (kHz) high-repetition rates simultaneously. By lowering the gradient, much lower RF power is needed to feed the electron gun, and then the heat problem is much easier to handle. Meanwhile, by optimizing the length of the gun’s first cell from the normal case of 0.6-cell to 0.4-cell, the launch phase and the extraction field are significantly improved, thus ensuring the generation of low-emittance electron beams. In our design, the proposed 1.4-cell RF gun can work effectively under different field gradients ranging from 30 MV/m to 100 MV/m. For a standard case of 60 MV/m, 2.5 MW peak RF power with μs level pulse width is sufficient, thus offering the feasibility of improving the repetition rate to kHz level with a standard 5 MW irradiation klystron. In addition, simulated electron beams with a low emittance of 0.29 mm.mrad@200 pC can be generated by this proposed photoinjector, showing that this high-repetition rate injector holds the potential to deliver high-quality beams comparable to those of state-of-the-art S-band photoinjectors. Combining the merits of low emittance and high-repetition rate, this proposed photoinjector will provide a new possibility for future free-electron laser facilities operating at repetition rates ranging from kHz to tens of kHz.

Abstract To further improve the frequency regulation stability of wind farm, and optimize the state of charge (SOC) basepoint, charge and discharge rate and recovery capacity of energy storage. In an isolated, off‐grid state, a two‐layer optimization method is proposed, taking into account the frequency regulation reliability and SOC adaptive adjustment of the wind storage. In the upper layer, the model predictive control theory is adopted to optimize the energy‐storage frequency regulation output power with the goal of minimizing the wind storage frequency regulation power deviation. While solving the problem of low‐frequency regulation reliability of wind farm, the SOC recovery basepoint and frequency regulation power of energy storage are optimized. At the SOC optimization layer, based on the upper SOC recovery basis point, we propose a dynamic recovery method for energy‐storage SOC that considers both the SOC recovery demand and grid‐bearing capacity, to determine the energy‐storage recovery power. By determining the frequency regulation or recovery power, we propose a calculation method to optimize the energy‐storage charge and discharge coefficients as per the SOC for avoiding excessive charging and discharging. The simulation results show that, under continuous disturbance, the root‐mean‐square deviations of the proposed method is 80.13% and 62.63% lower than those of the fixed K and SOC methods, respectively. Furthermore, the proposed method exhibits the best SOC maintenance effect.

Cassava is a kind of crop with extreme barren tolerance, strong stress resistance and rich starch. In our country, cassava has long been used as a non-food energy crop to produce starch, alcohol and feed. In recent years, the development of breeding, popularization and deep-processing technology of the edible cassava have greatly expanded the development space of cassava in the food industry. Firstly, the varieties and nutritional value of the edibble cassava are introduced in this article, and then the present research and application situation of the edibble cassava in food industry field are summarized, from three aspects: Fresh edibble cassava, edible cassava whole flour and starch, and modified starch. On this basis, the developmental advantage and the problems of the edible cassava are analyzed, the development prospect of the edible cassava in food industry are forecasted, such as variety breeding, storage and preservation technologies, processing technologies and product development, in order to offer some references for our country's edible cassava industrial in the future.

Abstract Cellulose paper has emerged as an ideal sensing element for wearable pressure sensors owing to its inherent flexibility, high porosity, and light weight. However, traditional paper‐based pressure sensors use metal‐based materials as electrodes, which significantly limits the unique advantages of paper, particularly in terms of degradability. In this study, a degradable pressure sensor is designed by combining the highly conductive poly(3,4‐ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) Xuan paper electrode with a low‐conductivity PEDOT:PSS tissue paper sensitive layer. Notably, Xuan paper, also called rice paper, has been a prominent substrate owing to its softness and good durability. By introducing a perforated structure in the sensitive layer, a novel sensing mechanism, conductivity conversion under pressure, is realized to improve the sensitivity. The obtained sensor exhibits a high sensitivity (13.9 kPa−1 at < 8.3 kPa, 151 kPa−1 at 8.3–20.8 kPa), ensuring that it can precisely monitor the full‐range human activities. Additionally, as the sensor does not rely on metal materials, it can degrade in water or fire without causing any negative environmental impacts. These findings establish a new approach to producing highly sensitive degradable sensors, which hold significant potential for application in green electronics, paper‐based sensing matrices, new prosthetics, and other fields.

With the advancements in Web of Things, Artificial Intelligence, and other emerging technologies, there is an increasing demand for artificial visual systems to perceive and learn about external environments. However, traditional sensing and computing systems are limited by the physical separation of sense, processing, and memory units that results in the challenges such as high energy consumption, large additional hardware costs, and long latency time. Integrating neuromorphic computing functions into the sensing unit is an effective way to overcome these challenges. Therefore, it is extremely important to design neuromorphic devices with sensing ability and the properties of low power consumption and high switching speed for exploring in-sensor computing devices and systems. In this review, we provide an elementary introduction to the structures and properties of two common optoelectronic materials, perovskites and transition metal dichalcogenides (TMDs). Subsequently, we discuss the fundamental concepts of neuromorphic devices, including device structures and working mechanisms. Furthermore, we summarize and extensively discuss the applications of perovskites and TMDs in in-sensor computing. Finally, we propose potential strategies to address challenges and offer a brief outlook on the application of optoelectronic materials in term of in-sensor computing.

Cassava flour (CF) was used as a raw material to replace wheat flour (WF) at levels of 0% (control), 10%, 20%, 30%, 40%, and 50% to prepare wheat–cassava composite flour (W-CF) and dough. The effects of different CF substituting levels on the functional properties of the W-CF and dough were investigated. The results show that an increase in CF led to a decrease in the moisture, protein, fat, and b* values of W-CF. The crude fiber, ash, starch, L*, a* values, iodine blue value (IBV), and swelling power (SP) of the composite flour increased gradually. It was found that the water absorption, hardness, and chewiness of the W-CF dough increased with an increase in the CF substitution level. A different trend could be observed with the springiness and cohesiveness of the W-CF dough. The resistance to extension, extensibility, and the extended area of the W-CF dough at all substitution levels was significantly lower than that of the WF dough. The elasticity and cohesiveness of the dough tended to increase for CF content from 10% to 30%, followed by a decrease at a higher replacement. Pearson correlation analysis indicated that the substitution levels of CF had a significant influence on the proximate analysis and functional properties of the W-CF and dough. This study will provide important information on choosing CF substitution levels for different products.

Abstract This paper studied a tripartite evolutionary game of stakeholders in environmental pollution control. Most previous studies on this issue are limited to a focus on system dynamics with two-party game problems and lack a spatial analysis of strategy evolution. The parameters adopted are too few, and the influencing factors considered are too simple. The purpose of the paper is to introduce more parameters to study, which will have an important impact on the strategy choices of participants and the evolution path of the strategy over time. We construct a tripartite evolutionary game model of sewage enterprises, governments and the public. We establish a payment matrix and replicator equations as our method, and we also implement parameter simulations in MATLAB. In summary, we found that the reward and punishment mechanism plays an important role in environmental pollution control. Specifically: intensifying rewards and penalties will help encourage sewage enterprises to meet the discharge standard and the public to participate in pollution control action. However, increased rewards will reduce government's willingness to adopt incentive strategies; Government's reward for public's participation in the action must be greater than the increased cost of participation; Reducing the cost of sewage enterprise can also encourage them to implement standard emissions. The research presented in this paper further improves standard emissions and designs reasonable reward and punishment mechanism.

Abstract Neuromorphic system based on artificial synaptic devices is considered as a potential candidate to realize the in‐memory computing and parallel processing of data for overcoming the von Neumann bottleneck. However, to fully imitate the complicated functions of the biological neural networks at the hardware level is still a challenging task. In this work, a multi‐terminal MoS2 synaptic transistor is developed, which not only simulates various biological synaptic behaviors, including paired pulse facilitation (PPF), excitatory/inhibitory post‐synaptic current (EPSC/IPSC), spike‐rate‐dependent plasticity (SRDP), and spike‐timing‐dependent plasticity (STDP), but also can independently mimic the parallel signal processing and transmissions in biological multipolar neurons. By combining the multi‐terminal MoS2 synaptic transistor with the micro‐structured polydimethylsiloxane (PDMS) pressure sensors, an intelligent tactile recognition system is built up, which can realize the spatiotemporal recognition of touch position. Furthermore, with sensor selection, the spatiotemporal modulation of synaptic plasticity and the human learning and forgetting behaviors to the knowledge with different difficulty degrees can be mimicked. This work provides a novel interconnection scheme for simulating signal transmission and processing among neurons, showing broad application prospects of the multi‐terminal MoS2 synaptic transistor in intelligent human–computer interaction and bionic neuromorphic perception systems.

The study aims to evaluate the relationships between characteristics of regional rice raw material and resulting quality of rice noodles. Four of most commonly used rice cultivars in Guangxi for noodles production were investigated. The results showed that compositions of rice flour primarily affected gelatinization and retrogradation, which then influenced the textural and sensory properties of rice noodles. Amylose content had strong positive correlation with peak viscosity (PV) and trough viscosity (TV) of rice flour (P < 0.01). PV and TV had strong negative correlations with adhesive strength (P < 0.01) and positive correlations with chewiness (P < 0.05), hardness, peak load and deformation at peak of rice noodles (P < 0.01). Protein content had positive correlation with the Setback of rice flour (P < 0.05), which is known to have influences on retrogradation. In addition, solubility had positive correlations with cooking loss (P < 0.01) and broken rate (P < 0.05) of rice noodles and strong negative correlation with its springiness (P < 0.01). Swelling power had negative correlation with broken rate (P < 0.05). As sensory score of rice noodles was negatively correlated with broken rate (P < 0.05) and cooking loss (P < 0.01) and positively correlated with springiness (P < 0.01), solubility and swelling power of rice flours were presumed to be useful for predicting consumer acceptability of rice noodles.

Graphene is widely used in tunable photonic devices due to its numerous exotic and exceptional properties that are not found in conventional materials, such as high electron mobility, ultra-thin width, ease of integration and good tunability. In this paper, we propose a terahertz metamaterial absorber that is based on patterned graphene, which consists of stacked graphene disk layers, open ring graphene pattern layers and metal bottom layers, all separated by insulating dielectric layers. Simulation results showed that the designed absorber achieved almost perfect broadband absorption at 0.53–1.50 THz and exhibited polarization-insensitive and angle-insensitive characteristics. In addition, the absorption characteristics of the absorber can be adjusted by changing the Fermi energy of graphene and the geometrical parameters of the structure. The above results indicate that the designed absorber can be applied to photodetectors, photosensors and optoelectronic devices.

Abstract The design of micropolarizer array (MPA) patterns in Fourier domain provides an efficient approach to reconstruct and investigate the polarization information. Inspired by Alenin’s works, in this paper, we propose an improved design model to cover both 2 × N MPAs and other original MPAs, by which an entirely new class of MPA patterns is suggested. The performance of the new patterns is evaluated through Fourier domain analysis and numerical simulations compared with the existing MPAs. Particularly, we analyze the reconstruction accuracy of the first three Stokes parameters and degree of linear polarization (DoLP) in detail. The experimental results confirm that the 2 × 2 × 2 MPA provides the highest reconstruction quality of s 0, s 1, s 2 and DoLP in terms of quantitative measures and visual quality, while the 3 × 3 diagonal MPA achieves the state-of-the-art best results in case of single-snapshot systems. The guidance of this extended model and new diagonal MPAs show its massive potential for the division of focal plane (DoFP) polarization imaging applications.

Neuromorphic computing systems can perform memory and computing tasks in parallel on artificial synaptic devices through simulating synaptic functions, which is promising for breaking the conventional von Neumann bottlenecks at hardware level. Artificial optoelectronic synapses enable the synergistic coupling between optical and electrical signals in synaptic modulation, which opens up an innovative path for effective neuromorphic systems. With the advantages of high mobility, optical transparency, ultrawideband tunability, and environmental stability, graphene has attracted tremendous interest for electronic and optoelectronic applications. Recent progress highlights the significance of implementing graphene into artificial synaptic devices. Herein, to better understand the potential of graphene-based synaptic devices, the fabrication technologies of graphene are first presented. Then, the roles of graphene in various synaptic devices are demonstrated. Furthermore, their typical optoelectronic applications in neuromorphic systems are reviewed. Finally, outlooks for development of synaptic devices based on graphene are proposed. This review will provide a comprehensive understanding of graphene fabrication technologies and graphene-based synaptic device for optoelectronic applications, also present an outlook for development of graphene-based synaptic device in future neuromorphic systems.

In this work, the polycaprolactone (PCL) scaffold with specific surface morphology was prepared by cryogenic printing technique. Biocompatible hydroxyapatite (HA) was added to the PCL matrix to enhance the surface properties and bioactivity of the scaffolds. The effects of HA on the mechanical strength and surface morphology were studied systematically. It was found that the extra surface morphology of filament enhanced the exposure of the HA particles, which induced a positive synergistic effect on surface properties. The wettability and bio-mineralization were significantly improved, and the protein adsorption capacity was 4.5 and 3.9 times than the ones of sample with 20%HA and smooth surface, respectively. Rat bone mesenchymal stem cells (rBMSCs) were used as the cell model to evaluate the cellular response to the specific surface of the scaffolds. The results showed that the scaffolds with 20–40% HA and extra surface had better proliferation ratio. The ALP assay also demonstrated that the synergistic effect was beneficial to cell osteogenic differentiation, and the ALP level was significantly higher than that of pure PCL and smooth PCL/HA composite scaffold samples at the 14th day. Therefore, the PCL/HA composite scaffold with extra surface morphology had better potential for bone tissue engineering.

Abstract The decreasing pixel size of digital image sensors for high-resolution imaging brings a great challenge for the matching color filters. Currently, the conventional dye color filters with pixel size of several microns set a fundamental limit for the imaging resolution. Here, we put forward a kind of structural color filter with circular nanohole-nanodisk hybrid nanostructure arrays at sub-diffraction-limit spatial resolution based on the uncoupled localized surface plasmon polaritons (LSPPs). Due to the uncoupled LSPPs taking effect, the pixel could generate an individual color even though operating as a single element. The pixel size for the minimum color filtering is as small as 180 × 180 nm2, translating into printing pixels at a resolution of ~ 141,000 dots per inch (dpi). In addition, through both the experimental and numerical investigations, the structural color thus generated exhibits wide color gamut, large viewing angle, and polarization independence. These results indicate that the proposed structural color can have enormous potential for diverse applications in nanoscale optical filters, microscale images for security purposes, and high-density optical data storage.

Poverty alleviation is the first battle to realize the rural revitalization strategy in China, and research on the sustainable livelihood of rural households is of great significance to solving the problem of rural poverty. Based on the sustainable livelihood framework, the reasonable scale and structure of fiscal expenditure is an inevitable requirement in producing sustainable livelihood capital toward this aim. In this study, the system Gaussian mixed model was used to analyze the impact of fiscal expenditure on farmers’ livelihoods. Representative survey data uses panel data from 48 counties across Liangshan Prefecture, Ganzi Prefecture, and Aba Prefecture in Sichuan, China. The results are as follows: (1) The average stock of human capital in 2010 to 2015 was the highest in the composition of farmers’ livelihood capital; (2) natural capital and physical capital were positively affected by the total scale of fiscal expenditure, agriculture, forestry, and water expenditure, and the former was negatively affected by general public service expenditure, education expenditure, social security and employment expenditure, and medical expenditure; (3) financial capital and the total amount of livelihood capital were positively affected by the total scale of fiscal expenditure, agriculture, forestry and water expenditure, education expenditure, social security and employment expenditure, and medical expenditure, and negatively affected by general public service expenditure; (4) human capital was positively affected by the total scale of fiscal expenditure, education expenditure, social security and employment expenditure, and medical expenditure; and (5) social capital was positively affected by agriculture, forestry and water expenditure, and education expenditure.

Automatic control of intelligent vehicles depends heavily on accurate lane-level location information. The traditional digital map cannot meet the automatic driving requirements, and it is very difficult for lane-level road maps (LRMs) to achieve a good balance between the representation accuracy and data storage volume. To tackle this problem, we obtain the recursive definition of a lane line by analyzing road lanes using the fractal geometry theory. Subsequently, we construct a recursive feedback system and model it. On this basis, an autonomous storage optimization LRM generation strategy based on cascaded NURBS is devised. According to the input data density, this framework generates an LRM with the minimum data storage volume within the error constraint. It is mainly composed of two modules: (1) a random fractal and (2) an adaptive iteration memory optimizer, based on cascaded NURBS error feedback. First, the whole lane is divided into several meta lane line modules. Second, data sampling/interpolation is carried out iteratively according to the NURBS fitting error and symmetry of road geometry. In this way, the storage space used to store lane lines and other information is automatically optimized. Last, a simulation experiment is carried out by using a dataset obtained from a park. The simulation results show that the proposed method can achieve high accuracy and high storage efficiency. Under the constraint of a 0.1 m curve fitting error, the average memory demand of the lane line elements is less than 2.4 bytes/m.

Graft reconstruction of the mandible is an important approach that aims at improving the appearance and functionality of defected mandibles. The traditional implant materials are generally bioinert, non-degradable, and that they lack favorable pore structures for cell proliferation, which limit their clinical application. In this study, we used boron-containing bioactive glass which was combined with a three-dimensional (3D) printing technology to construct an osteoinductive implant scaffold, according to the imaging instructions of CT scan on bone defects. Here, the boron-containing bioglass scaffold (B-BGs) was prepared through sol-gel processing and a 3D print technique. Different boron content of borosilicate bioglass was prepared by incorporating B2O3 (molar: 19.4 and 38.8%) into 58S bioglass to replace parts of SiO2. For fabricated mandible implants through three-dimensional 3D printing of B-BGs (size: 8 × 2 mm; pore size: 250 μm) modified with borosilicate bioglass powder and sodium alginate. Notably, the compressive strength of the B-BGs was about 3.8 Mpa, which supported mandibular activity. Subsequently, the excellent biocompatibility of B-BGs was confirmed using cytotoxicity in vitro studies. Finally, data from in vivo experiments demonstrated that the B-BGs could promote bone regeneration and they could almost get completely degraded within 4 weeks. Our results showed that the boron-containing bioglass could repair mandibular defects.

The aim of this study was to explore the relationships between structure alterations and postharvest berry abscission in “Muscat Kyoho” “Kyoho” and “Nanyu” table grapes stored for 0, 3, or 6 days at room temperature. Microstructure analysis showed that a large number of the stalk-berry junction cells of “Muscat Kyoho” and “Kyoho” were lignified and suberized at 0 day, whereas these events seldom occurred in “Nanyu.”Furthermore, the berry brush cells of the three varieties, especially those of “Nanyu,” were small and dense. At 3 days, the numbers of lignified and suberized cells of “Muscat Kyoho” and “Kyoho” were reduced, and the cells had degraded, ruptured, and disappeared by 6 days. The berry brush cells of “Muscat Kyoho” and “Kyoho” were larger and more loosely arranged than were those of “Nanyu.” Ultrastructure analysis showed that the cells increased in size from small to large and became loosely arranged; the smallest changes were observed in “Nanyu.” The cells of “Muscat Kyoho” and “Kyoho” were hydrolyzed, liquated, and covered by granular substances at 6 days, and these features were especially prominent in “Muscat Kyoho.” The detachment force of grapes declined steadily (p < 0.05) and was accompanied by an increase in berry abscission. “Nanyu” maintained the highest detachment force and the lowest berry abscission during storage (p < 0.05), followed by “Kyoho” and “Muscat Kyoho.” Structural alterations were directly related to berry abscission and correlated inversely with detachment force, with the greatest alterations occurring in “Muscat Kyoho,” followed by “Kyoho” and then “Nanyu.”

Forests resources in Naltar Valley, Pakistan, are under continuous pressure because of limited access to off-farm opportunities and alternative source of energy. Therefore, this study underlines the essential demographic and socio-economic characteristics of rural livelihood on forest resource-dependent in the study area that explain the factors of forest dependency. To better estimate household forest dependency, we interviewed 248 randomly selected households using a semi-structured questionnaire. The binary logistic regression model was used to evaluate the potential determinants of forest resource dependency. The study revealed that age, education, household size, livestock income, agriculture income, and off-farm income were significantly influenced household dependency on forest resource, while other factors were not significant. Furthermore, the result shows that the income derived from the forests resources, agricultural products, livestock and off-farm activities contributes 39%, 33%, 16% and 12% respectively to the total household income. Forest income share from timber, firewood, honey, fodder, medicines, and fruits & vegetables are 46%, 52%, 1%, 1%, 0.41%and 0.47% respectively. Firewood has the most significant share in forest income and the primary source of energy mainly for cooking, and heating by the local community. To balance forest resource dependency and to conserve biodiversity, it is therefore essential to appreciate local communities by providing alternative income generation opportunities and provide them with alternative sources of domestic energy like hydroelectric power and biogas power. To this end, the proactive involvement of local communities in forest conservation is needed, as well as more plantation to meet the demand for fuelwood and thus reduce the pressure on forest resources. Keywords: Forest resource dependency, Fuelwood, Rural livelihoods, Logistic regression, Naltar Pakistan

Abstract Depending on the mobile species involved in the resistive switching process, redox random access memories and conductive bridge random access memories are widely studied with distinct switching mechanisms. Although the two resistance switching types have faithfully proved to be electrochemically linked in metal oxide‐based memristive devices, the corresponding photo‐induced transition has not yet been realized. Here, a photo‐induced transition through the integration of a graphene layer into a titanium oxide‐based memory device is demonstrated. Coupled with Raman mapping and an electron energy loss spectroscopy technique, the photo‐induced interaction at the heterostructure of graphene/titanium oxide are considered to dominate the transition process. Moreover, a negative differential resistance effect is observed by controlling the applied voltage, which can be credited to the saturation of trap centers (oxygen vacancies) and the increase of interfacial barrier at the graphene/titanium oxide heterojunction.

With the development of industrialization, the problem of environmental pollution has become increasingly serious. Environmental monitoring data, as a measurement index of environmental quality, is increasingly valued by governments and citizens. However, the accumulated real-time monitoring data of the environment at current stage is mostly used to write basic reports, while the hidden laws or values still need to be further explored. This paper proposes two original environmental prediction models and conducts improvement on these two methods separately to predict the quality of the atmospheric environment. The following research results are obtained: the multivariate linear equation is optimized through stepwise linear regression, which can accurately predict the short-term atmospheric environmental quality; the improved BP neural network can predict the mid-term and long-term atmospheric environmental quality through short-term training.

A novel S-Band Micro-Pulse electron Gun (MPG) which works at the left crossover point energy EcI on the Secondary Electron Yield (SEY) curve was proposed. The working principles of the MPG were presented. The maximum output beam current limited by space charge effects and beam loading effects was investigated by theoretical analysis. The result shows that the maximum beam current is decided by the parameters of the MPG such as resonant frequency, cavity length, shunt impedance and the secondary emission property of the cathode and grid, having nothing to do with the power flowed into the cavity. The low shunt impedance and the low slope of the SEY curve can help increasing the maximum beam current. According to the principles, a MPG with the frequency of 2.856 GHz has been designed and constructed. The steady working state was achieved by using oxygen free copper and molybdenum grid with different transmission coefficient. It was found a good agreement between the analysis and the experiments.

Theranostic prodrug plays a vital role in reducing the side effects and evaluating the therapeutic efficiency of prodrug in vivo. In particular, small conjugate-based theranostic prodrugs have attracted much attention because of their clear and simple structures. In this work, we synthesized a novel tumor-targeting and glutathione-activated conjugate-based theranostic prodrug (Cy-SS-MTX). The prodrug was constructed by conjugating Cy (IR780) to methotrexate (MTX) via a disulfide bond. The Cy dye as targeting molecule bring prodrug to cancer cells and then the prodrug was activated by the high levels of glutathione in tumor. In cell experiments, the results showed the excellent ability of prodrug to target tumor. Meanwhile, the prodrug apparently improved the anti-tumor ability and hugely reduced toxicity of free MTX on normal cells. Furthermore, owing to intramolecular charge transfer between Cy and MTX, the Cy structure in the prodrug showed an absorption peak at 654 nm in UV-Vis spectroscopy. However, when the disulfide bond of prodrug was broken by glutathione, a new UV-Vis absorption peak at 802 nm of Cy structure in prodrug was arised. At the same time, the fluorescence (FL) emission peak at 750 nm (excitation at 640 nm) would turn into 808 nm (excitation at 745 nm). What's more, the photoacoustic (PA) signal with excitation at 680 and 808 nm also changed. The experimental results in vivo showed that the prodrug has been successfully utilized for real-timely tracking MTX activation by FL and PA imaging upon near infrared laser excitation and cancer targeting therapy. Our studies further encourage application of small conjugate-based prodrug based on tumor-targeted heptamethine cyanine dye as reporter group for targeted therapy and real-timely tracking activation of drug.

Copper is an indispensable micronutrient in human health, which has important effects on the promotion of angiogenesis and thus contributes to bone formation and antimicrobial activity. We used ion exchange and pneumatic printing methods to prepare hydroxyapatite (HA) microspheres with different copper content. The microspheres were characterized by scanning electron microscope (SEM), X-ray diffractometry (XRD) and X-Ray photoelectron spectroscopy (XPS). Considering the resistance of hydroxyapatite to biodegradation in vivo, the degradation rate of microspheres in modified simulated body fluids was studied. In addition, cell proliferation and antibacterial experiments were carried out to study the biological properties of microspheres. HA-1.5MCu microbeads treated by 1.5 mol/L CuSO4 curing solution have good performance on degradation, antibacterial properties and cell survival rate on day 7. The results showed that HA-1.5MCu microbeads may be used as a good repair material for bone defects.

As an important electron source, Micro-Pulse electron Gun (MPG) which is qualified for producing high average current, short pulse, low emittance electron bunches steadily holds promise to use as an electron source of Coherent Smith-Purcell Radiation (CSPR), Free Electron Laser (FEL). The stable output of S-band MPG has been achieved in many labs. To establish reliable foundation for the future application of it, the propagation of picosecond electron bunch produced by MPG should be studied in detail. In this article, the MPG which was working on the rising stage of total effective Secondary Electron Yield (SEY) curve was introduced. The self-bunching mechanism was discussed in depth both in the multipacting amplifying state and the steady working state. The bunch length broadening induced by the longitudinal space-charge (SC) effects was investigated by different theoretical models in different regions. The 2D PIC codes MAGIC and beam dynamic codes TraceWin simulations were also performed in the propagation. The result shows an excellent agreement between the simulation and the theoretical analysis for bunch length evolution.

Hemorrhagic Fever with Renal Syndrome (HFRS) is considered as a globally distributed infectious disease, which results in many deaths annually in Hubei Province, China. The outbreak of HFRS is usually characterized with spatio-temporal heterogeneity and is seasonally distributed. Further, it might also be impacted by the influencing factors such as socio-economic and geographical environment. To better understand and predict the outbreak of HFRS in the Hubei Province, the spatio-temporal pattern and influencing factors were investigated in this study. Moran's I Index value was adopted in spatial global autocorrelation analysis to identify the overall spatio-temporal pattern of HFRS outbreak. Kulldorff scan statistical analysis was performed to further identify the changing trends of the clustering patterns of HFRS outbreak. Spearman's rank correlation analysis was used to explore the possible influencing factors on HFRS epidemics such as climate and geographic. The results demonstrated that HFRS outbreak in Hubei Province decreased from 2005 to 2012 in general while increasing slightly from 2012 to 2014. The spatial and temporal scan statistical analysis indicated that HFRS epidemic was temporally clustered in summer and autumn from 2005 to 2014 except 2008 and 2011. The seasonal epidemic pattern of HFRS in Hubei Province was characterized by a bimodal pattern (March to May and September to November) while peaks often occurring in the spring time. SEOV-type HFRS was presumed to influence more on the total number of HFRS incidence than HTNV-type HFRS do. The average humidity and human population density were the main influencing factors during these years. HFRS outbreaks were more in plains than in other areas of Hubei Province. We did not find that whether the terrain of the wetland (water system) plays a significant role in the outbreak of HFRS incidence. With a better understanding of rodent infection rate, socio-economic status and ecological environment characteristics, this study may help to reduce the outbreak of HFRS disease.