Core-shell particles are heterogenous micro- or nanoparticles with solid, liquid or gas core encapsulated by a protective solid shell. The unique composition of core and shell materials imparts smart properties to the particles. Core-shell particles are gaining increasing attention as tuneable and versatile carriers for pharmaceutical and biomedical applications including targeted drug delivery, controlled drug release, and biosensing. This review first provides an overview of fabrication methods for core-shell particles, followed by a brief discussion on their application and a detailed analysis on manipulation including assembly, sorting, and triggered release. We compile current methodologies employed for manipulation of core-shell particles and demonstrate how existing methods of assembly and sorting micro/nanospheres can be adopted or modified for core-shell particles. Various triggered release approaches for diagnostics and drug delivery are also discussed in detail.

Introduction: Hemostatic dysfunction during extracorporeal membrane oxygenation (ECMO) due to blood-circuit interaction and the consequences of shear stress by flow rates lead to rapid activation of the coagulation cascade and thrombus formation in the ECMO system and blood vessels. In this study, we aimed to identify the incidence and risk factors for cannula-associated arterial thrombosis (CaAT) post-decannulation. Methods: A retrospective study of patients undergoing arterial cannula removal following ECMO. We evaluated the incidence of CaAT and compared clinical characteristics, pre-ECMO severity, and daily hemostasis parameters in patients with and without CaAT. Multivariate analysis revealed the risk factors for CaAT. Results: Forty-seven patients requiring venoarterial ECMO or hybrid methods were recruited to be screened for thrombosis. The median SOFA score was 11 (8-13). CaAT occurred in 29 patients (61.7%), with thrombosis in the superficial femoral artery accounting for 51.7%. Limb ischemia complications in the group with CaAT was 17.2%. In multivariate analysis, an ECMO flow rate of 100 mL/min was determined to be the independent factor for CaAT with an OR of 0.84 (95% CI, 0.73–0.95, p=0.008). Conclusion: In patients successfully weaned from ECMO, the incidence of CaAT was 61.7%. Our study found that a low-flow rate of ECMO was an independent risk factor for CaAT.

This article explored how some state policies on rehabilitation, protection and utilization of mangroves are implemented at two locals; namely, Ca Mau provice and its sub-unit Ngoc Hien District as well as Ho Chi Minh City and its sub-unit Can Gio District and what are considered as emgerging issues in the implementation process. The study employed mixed research methods including document and thematic analysis, in-depth interviews, and group discussion. The findings showed that state policies would be adapted through the ways in which these two locals manage to silmultaneously orient their work toward accommodating the madates placed upon them and cope with the reality of socio-economic difficulties at their levels. The findings also showed some issues that need to consider addressing; namely, locals’ struggles to fill the gaps between written and implemented policies in mangrove rehabilitation, conflict among sectors and stakeholders in mangrove utilization and protection, problems in guaranteeing adequate budget for in-need-locals, inconsistence in policies on "forest: water surface” ratio in mangrove-shrimp farm, and unintended consequences in forest thinning and exploitation regimes. Based on the finding analysis, the articles discussed lessons learned from the policy implementation process on mangrove rehabilitation, management and forest allocation to household in the south of Vietnam.

Edge computing has emerged as a significant computing trend alongside the rapid expansion of the Internet of Things (IoT). Computing operations at the network’s edge offer a solution to the high latency and service overload challenges often associated with cloud computing. Additionally, the Secure Hash Algorithm-3 (SHA-3) plays a crucial role in ensuring data integrity and is implemented for numerous applications in the IoT field. Therefore, integrating the SHA-3 accelerator into edge computing is essential. Moreover, recent studies about SHA-3 have primarily focused on achieving high performance and optimizing resource utilization for SHA-3. However, these studies have overlooked the crucial aspect of data transfer between the external memory and the hash function block, as transfer time plays a significant role. This paper proposes an efficient SHA-3 architecture designed for System-on-Chip (SoC) Field Programmable Gate Array (FPGA) to address the aforementioned challenges and be suitable for real edge computing. The architecture contains three key techniques. First, the harmony of padding and Direct Memory Access (DMA) for managing the data transfer process and enhancing performance efficiency based on Serial Input to Parallel Output (SIPO) and a barrel shifter. Secondly, implementing internal pipelining within the Round Function (RF) to reduce critical path delays and optimize resource utilization. Finally, designing four modes (SHA3-224, SHA3-256, SHA3-384, and SHA3-512) to cater to various applications. Our architecture is implemented and tested on the DE10-Standard Development Kit (Cyclone V SX SoC-5CSXFC6D6F31C6N), which is integrated into the FPGA and is controlled by a Dual-Core ARM Cortex-A9 processor. The result is up to 38.34 Gbps in throughput and 5.61 Mbps/ALM in efficiency for the RF computation, 28.02 Gbps in throughput, and 3.63 Mbps/ALM for the full proposed architecture.

Abstract. This paper proposes a Second Order Terminal Sliding Mode (2TSM) approach to the trajectory tracking of Differential Drive Mobile Robot (DDMR). Within this cascaded control scheme, the 2TSM dynamic controller, at the inner most loop, tracks the robot’s velocity quantities; while a kinematic controller, at the outer most loop, regulates the robot’s positions. In this manner, chattering is greatly attenuated and finite time convergence is guaranteed by the second order TSM manifold which involves higher order derivatives of the state variables, resulting in inherently robust as well as fast and better tracking precision. The simulation results demonstrate the merit of the proposed control methods.

The fishmeal production industry is essential for providing protein for animal feed in the aquaculture sector. However, the industry faces challenges related to energy consumption and environmental sustainability. This study evaluates the energy efficiency and environmental benefits of waste heat recovery (WHR) technologies in a fishmeal production plant in Vietnam. Data were collected from the plant between 2016 and 2022, and a specific energy consumption (SEC) indicator and a comprehensive methodology were utilized. Implementing an economizer as a WHR technology resulted in a 55.5% decrease in SEC compared to the state before installation. The enhanced energy efficiency also translated to reduced energy consumption per output unit. Moreover, the economizer contributed to annual energy savings of 4,537.57 GJ/year and cost savings of $26,474.49. Additionally, carbon dioxide (CO2) emissions associated with producing one ton of fishmeal decreased by 58.37%. These findings highlight the potential for WHR technologies to improve energy efficiency and reduce the environmental footprint of fishmeal production. The study's results provide valuable insights for practitioners and policymakers in promoting energy efficiency practices and reducing environmental impact in the industry.

Optical wireless communication is a promising emerging technology that addresses the limitations of radio-frequency-based wireless technologies. This study presents a novel hybrid modulation for optical camera communication (OCC); it integrates two waveforms transmitted from a single transmitter light-emitting diode (LED) and received by two rolling-shutter camera devices. Then, a smart camera with a high-resolution image sensor captures the high-frequency signal, and a low-resolution image sensor from a smartphone camera captures the low-frequency signal. Through this hybrid scheme, two data streams are transmitted from a single LED lamp; this reduces the cost of the indoor OCC device compared to one that transmits two signals from two different LEDs. In proposed scheme, rolling-shutter orthogonal frequency-division multiplexing is used for the high-frequency signals, and M-ary frequency-shift keying is used for the low-frequency signals in the time domain. This proposed scheme is compatible with smart phone camera and USB camera. By controlling the OCC parameters, the hybrid scheme can be implemented with high performance for a communication distance of 10 m.

Mangrove ecosystems play an important role in local livelihoods in coastal regions of tropical and subtropical countries. However, in recent years urbanisation has changed the income structure of residents near mangroves. Different landscapes provide different job opportunities; thus, analysis of regional landscape patterns is important for understanding income structures. In this study, surveys on the income structure and landscape patterns of the surrounding areas of three mangrove sites were conducted in the Hau and Hoang Mai River estuaries in Nghe An Province, North-Central Vietnam. The results revealed that both natural and socio-economic landscape components affected income structure. The major occupations in the study area were agriculture, including husbandry, sea fishing, and trading. Land morphology and river type were the major factors influencing the income from agriculture, while coastline morphology primarily affected income from sea fishing. Community-based trading was carried out in the study area; thus, the population inside each administrative unit was a significant factor increasing income, while the retail market size in an area had significant negative effects, potentially due to the increasing number of competitors. Our study aimed to evaluate mangrove ecosystem importance for local livelihoods in relation to landscape patterns, and the results contribute to urban planning based on the conservation and sustainable use of mangrove ecosystems.

During the pandemic, home-cooked meals have received more attention as people get more time for themselves and their families. It cannot deny that people have more time to prepare meals, and it is safer to cook at home since they can avoid direct contact with people who can potentially F0 or F1. For that particular reason, the number of home cooking has increased rapidly. In the article, the author pointed out that in comparison to the previous time, 42.0 percent of respondents said they cooked more frequently during the lockdown, while just 7.0 percent said they cooked less frequently. The increase in cooking frequency had a more significant impact on women than on men (p<0.05). Those who said they cooked more regularly spent more time preparing meals (78\%) and trying new recipes (73.6\%), as well as spending more time baking (67.1 percent ). In particular, the consumption of “comfort” foods (salty snacks, sweets) showed a significant rise, ranging from (23\%) to (60\%) of respondents who declared snacking more studied.Moreover, articles pointed out that in conjunction with the dramatic reduction in energy expenditure due to the impossibility of going out, this situation could have led to energy imbalance and, thus, weight gain. Noticing the massive rise in home cooking, the search for new recipes, and the need for balance meals, the idea for a cooking app called "Cooking Papa" has been proposed. As far as the research goes, the concept of "cooking" seems close but yet not easy to define. The Oxford English Dictionary defines cooking as “to prepare food by the action of heat. However, limited evidence suggests that people interpret the meaning of cooking quite differently. Moreover, the terms ‘homemade’, ‘convenience,’ ‘proper cooking,’ ‘cook,’ ‘basic ingredients,’ and ‘ready prepared’ are not uniformly understood.

Ethanol produced from various biobased sources (bioethanol) has been gaining high attention lately due to its potential to cut down net emissions of carbon dioxide while reducing burgeoning world dependence on fossil fuels. Global ethanol production has increased more than six-fold from 18 billion liters at the turn of the century to 110 billion liters in 2019 (1,2). Sugar cane and corn have been used as the major feedstocks for ethanol production. Lignocellulosic biomass has recently been considered as another potential feedstock. This paper reviews recent developments and current status of commercial production of ethanol across the world. The review includes the ethanol production processes used for each type of feedstock, both currently practiced at commercial scale and newly developed technologies, and production trends in various regions and countries in the world.

Curcuma longa is only a rich source of curcumin (1) and its major analogues demethoxycurcumin (2) and bisdemethoxycurcumin (3) among the Curcuma species. The content ratio of these three curcumins in turmeric is depended on the varieties and growing environment. Recently, curcumin (1) has been reported as potential inhibitor of hepatic and enzymatic protein tyrosine phosphatase 1B (PTP1B) and its related disorders such as hypertriglyceridemia, hyperlipidemia and liver steatosis. Thus, we further purified curcumins (1–3) from C. longa and investigated their inhibitory effects against PTP1B and α-glucosidase enzymes. As the result, curcumins (1–3) exhibited potential PTP1B inhibition with IC50 values of 37.8 ± 1.4, 45.3 ± 0.7, and 72.6 ± 1.1 μM, respectively, and α-glucosidase inhibition with similar manner (IC50 values of 78.2 ± 0.2, 82.4 ± 0.6, and 90.6 ± 1.0 μM, respectively). These results reveal a key role of methoxylation in the variation of PTP1B and α-glucosidase inhibitory activity for these curcumins. In addition, density functional theory (DFT) was used accompanying with molecular docking (MD) to analyze the ligand stability and the interaction of curcumins (1–3) with PTP1B and glucoside hydrolase proteins. Assay-based results and the MD data obtained are highly correlation suggesting that the deterioration of the enzyme activity caused by the distortion of structural conformation of PTP1B and glucoside hydrolase may be related to the arrangement of amino acids in protein structure. This reported for the first time that inhibitory effects of curcumins (1–3) against PTP1B and glucoside hydrolase have been examined in vitro and in silico as well.

Nowadays, the uses of laser and optics in the medical areas are extremely vivid, especially low-level laser therapy. The light with the wavelength of 633 nm to 1200 nm could penetrate and propagate deep in biological tissue. To develop the low-level laser therapy device, optimizing light delivery is critical to accurately stimulate the biological effects inside the biological tissue. Nevertheless, each form of the tissues at each zone on the body had various refractive optic, absorption, scattering, and anisotropy coefficients. This paper describes the simulation results of low-level laser propagation from skin surface at the lower spine, the knee, the femur and the prostate gland with four wavelengths (633 nm, 780 nm, 850 nm, and 940 nm) by the Monte Carlo method. These simulation results are the base for developing the low-level laser therapy device, that could be used in clinical for treating the fracture, knee osteoarthritis, spinal degeneration, and benign prostatic hypertrophy.

Malaysia generates significant quantities of lignocellulosic wastes through the production of crude palm oil (CPO). Over the years, the accumulation of the oil palm wastes (OPW) have become an environmental burden. These problems can be addressed by pretreatment and valorisation of OPW in bioenergy as envisioned in the National Biomass Strategy (NBS-2020). However, current strategies for the OPW valorisation are inefficient and unsustainable resulting in increased environmental challenges. Therefore, this paper proposes the pelletization and torrefaction of oil palm empty fruit bunches (OPEFB). Furthermore, the thermal degradation behaviour and potential product yields from OPEFB pellet torrefaction will be examined. The results revealed that the mass yield (M_Y) decreased from 67.89% to 33.11%, whereas energy yield (E_Y) decreased from 88.29% to 49.18% as the torrefaction temperature increased from 250 °C to 350 °C. However, the energy density (D_E) increased from 1.30 to 1.49 due to the increase in higher heating value (HHV) from 22.85 MJ/kg to 26.10 MJ/kg. Likewise, the severity factor (S_F) increased from 5.89 to 8.84 with increasing torrefaction temperature. The results also revealed that effect of temperature on the torrefaction parameters; M_Y, E_Y, D_E, and HHV are slightly reduced after 300 °C. Overall, the findings demonstrate that torrefaction improved the fuel properties and energy recovery potential of the OPEFB pellets.

Extravasation, the unintended leakage of intravenously administered substances, poses significant challenges in cancer treatment, particularly during chemotherapy and radiotherapy. This comprehensive review explores the pathophysiology, incidence, risk factors, clinical presentation, diagnosis, prevention strategies, management approaches, complications, and long-term effects of extravasation in cancer patients. It also outlines future directions and research opportunities, including identifying gaps in current knowledge and proposing areas for further investigation in extravasation prevention and management. Emerging technologies and therapies with the potential to improve extravasation prevention and management in both chemotherapy and radiotherapy are highlighted. Such innovations include advanced vein visualization technologies, smart catheters, targeted drug delivery systems, novel topical treatments, and artificial intelligence-based image analysis. By addressing these aspects, this review not only provides healthcare professionals with insights to enhance patient safety and optimize clinical practice but also underscores the importance of ongoing research and innovation in improving outcomes for cancer patients experiencing extravasation events.

This study examines the Willingness-To-Pay (WTP) of consumers and the determinants of eco-labeling for the organic cocoa powder produced in the Dong Nai UNESCO Biosphere Reserve (DNBR), Southern Vietnam. Eco-labels are designed according to Tiers of eco-labeling for biosphere reserves (BR) introduced by UNESCO include BR Destination (Tier 1), BR Quality Label (Tier 2), and Professional Certification Label (Tier 3). Questionnaires are delivered to 203 customers in the DNBR and nearby places, such as Dong Nai and HCMC. This study employs a hybrid approach using descriptive statistics, ANOVA test, and Partial Least Squares Structural Equation Model (PLS-SEM). The results indicate that gender and educational level have a positive effect on consumers' preferences. Customers are willing to pay more for cocoa powder with an eco-label than one with an organic label. Perceived food safety and product knowledge lower customers’ WTP, whereas agricultural environment and pricing concerns increase it. Tier 2 is suggested for labeling cocoa powder in the DNBR. The DNBR Management Board, together with the federal and provincial governments, should all follow a similar certification process. Increased eco-label awareness is crucial for the future of environmentally responsible shopping and responsible business practices.

Modern agriculture demands for comprehensive information about the plant itself. Conventional chemistry-based analytical methods - due to their low throughput and high associated cost - are no longer capable of providing these data. In recent years, remote reflectance-based characterization has developed as one of the most promising solutions for rapid assessments for plant attributes. However, in many cases, expensive equipment is required because accurate quantifications need assessment of the full reflectance spectrum. We examined the versatility of visible colour sensors as reflectance measuring devices for biological / biochemical quantifications on sweet basil (Ocimum basilicum). Our results indicate for the wide potential of spectral colour sensors for quantitative determination of leaf phenolic compounds, flavonoids in particular, and non-invasive plant phenotyping in agricultural applications by low-cost sensors.

In this paper, the classical least square (CLS) method with molecular absorption spectrophotometric measurement was used to determine simultaneously of paracetamol (PAR), ibuprofen (IBU), and caffeine (CAF) in tablets. The absorbance spectra of the standard solutions and samples were measured over a wavelength from 220 to 300 nm with a 0.5 nm step. The concentration of PAR, IBU and CAF in the sample solutions were calculated by using a program called CLS-Excel written in Microsoft Excel 2016 and Visual Basic for Applications (VBA). The method and CLS-Excel program were tested on mixed standard laboratory samples with different PAR, IBU, and CAF concentration ratios, and they showed small errors and satisfying repeatability. An analytical procedure for tablets containing PAR, IBU, and CAF was developed. The reliability of the procedure was proved via the recovery and repeatability of the analysis results with an actual tablet sample and comparing the mean contents of active substances in the tablets obtained from the analytical procedure with the from the HPLC method. The procedure is simple with a reduced cost compared with the HPLC standard method.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer characterized by the lack of estrogen receptors (ER), progesterone receptors, and HER-2 receptors. Thus, TNBC tumours do not benefit from the current therapies targeting ER or HER-2. Therefore, there is an urgent need to develop novel treatment for this subtype of breast cancer. Marijuana is a common name given to Cannabis plants, a group of plants in the Cannabis genus of the Cannabaceae family. Cannabis plants are among the oldest cultivated crops, traced back at least 12,000 years and are well known for their multi-purpose usage, including medicinal purposes. The main active compounds extracted from Cannabis plants are 21-carbon-containing terpenophenolics, which are referred to as phytocannabinoids. Of these, the tetrahydrocannabinol (THC) group contains highly potent cannabinoids, including delta-9-tetrahydrocannabinol (∆9-THC) and delta-8-tetrahydrocannabinol (∆8-THC), which are the most abundant THCs and are largely responsible for psychological and physiological effects of marijuana. The use of Cannabis plants for medicinal purposes was first recorded in 2337 BC in China, where Cannabis plants were used to treat pains, rheumatism, and gout. Recently, several cannabinoids have been approved for a number of treatments, one of which is the treatment of nausea and vomiting caused by chemotherapy in cancer patients. Furthermore, increasing evidence shows that cannabinoids not only attenuate side effects due to cancer treatment, but might also potentially possess direct antitumor effects in several cancer types, including breast cancer. However, anti-tumour activity of marijuana has been variable in different studies and even promoted tumour growth in some cases. In addition, the mechanisms of cannabinoid action in cancer remain unclear. This review summarizes evidence about the mixed actions of cannabinoids in cancer in general and triple-negative breast cancer in particular.

Butyl rubber-based composite (BRC) is one of the most popular materials for the fabrication of protective glove against chemical and mechanical risks. However, in many working places such as metal manufacturing or automotive mechanical services, its mechanical hazards usually appear together with metalworking fluids (MWFs). The presence of these contaminants, particularly at high temperature, could modify its properties due to the scission, the plasticization, the crosslinking of polymer network and thus led to severe modification of mechanical and physicochemical properties of material. This work aims to determine the effect of temperature and a metalworking fluid on mechanical behavior of butyl rubber composite dealing with crosslinking density, cohesion forces and elastic constant of BRC on the based on Mooney-Rivlin’s theory. The effect of temperature with and without MWFs on thermo dynamical properties and morphology of butyl membranes is also investigated. The prediction of service lifetime is then evaluated from extrapolation of Arrhenius plot at different temperatures.

Reducing CO2 emissions is urgently needed to slow down the impacts of climate change. CO2 capture using an amine solution has been developed and implemented on pilot and commercial scales. However, amine scrubbing, in particular, produces a lot of degraded solvent as waste and is energy intensive. Solid sorbents have been called to overcome those drawbacks. In this work, waste biomass-derived carbon materials were developed and tested for CO2 capture and conversion. Advanced thermal chemical processes i.e. hydrothermal and pyrolysis were applied to produce materials from agri-food waste such as soybean and okara. It was found that the number of functional groups (-C=O and -OH) in activated carbon appears in the synthesized materials, implying the generation of surface oxygenated groups. Preliminary results showed that the synthesized activated carbons are obtained with good yields, and a relatively high surface area, which may be applied as CO2 adsorption materials to solve the CO2 emission problems.

A simple fabrication method in the surface modification of electroosmotic silicon microchannel using thermal dry oxidation is presented. The surface modification is done by coating the silicon surface with a silicon dioxide (SiO₂) layer using thermal oxidation process. The process is aimed not only to improve the surface quality of the channel to be suitable for electroosmotic fluid transport but also to reduce the channel width using a simple technique. Initially, the parallel microchannel array with dimensions of 0.5 mm length and width ranging from 1.8 µm to 2 µm are created using plasma etching on the 2x2 cm <100> silicon substrate. The oxidation of silicon channel in a thermal chamber is then conducted to create the SiO₂ layer. The layer properties and the quality of the surface are analyzed using SEM and surface profiler, respectively. The results show that the maximum oxidation growth rate occurs in the first 4 hours of oxidation time and the rate decreases by time as the oxide layer becomes thicker. It is also found that the surface roughness is reduced with the increase of process temperature and oxide thickness. The scallop effect on the vertical wall due to plasma etching process also improved with the presence of the oxide layer. After the oxidation, the channel width is reduced by ~40%. The demonstrated method is suggested for the fabrication of a uniform channel cross section with high aspect ratio in sub-micro and nanometer scale that will be useful for the electroosmotic flow (EOF) manipulation of the biomedical fluid sample.

This paper investigates experiences of how local cultural norms and social capital influenced the disaster relief process following the 2011 GEJET disaster. To underline social capital’s multiple‐influence aspects, this paper draws from field research that focuses on collective and individual social capital in disaster relief to systematise the findings according to the social capital framework. The paper uncovers new effects of individual social capital and collective capital in a mega-disaster context, thus contributing to pushing the research agenda toward a more critical appraisal of individual social capital and collective capital. We contribute to the nascent but growing literature that clarifies the relationship between social capital and disaster resilience. A qualitative study was conducted to capture the essence of their shared experiences. Findings revealed three main themes capturing the essence of the research participants’ disaster experiences. First, disaster response relied mostly on locally driven relief due to a clear understanding of the local culture. Second, there was an urgency to establish a sense of normalcy by providing quality supplies that would help survivors. Third, Japanese gender roles and expectations were reflected in the disaster relief process. The themes establish a wide array of lived experiences that are important to reflect on the role social capital plays in the policy-making and needs assessment processes in post-disaster relief and response efforts. The findings provide insights for integrating social dimensions into a humanitarian aid culture as citizens work towards a sense of normalcy.

The Cauto River Basin (CRB), the heartland of Cuban agriculture, has been hit hard by drought and water shortage. In response to this pressing issue, this study provides a comprehensive as-sessment of water supply, demand and balance within the Cauto River Basin, considering the baseline and projected socio-economic and climatic conditions by coupling of SWAT and WEAP models. The obtained results reveal that the annual flow in the CRB is projected to slightly de-crease (2.5%) in which the reduction in the rainy season (3.1%) is higher than that in the dry sea-son (1.3%). Total water demand in the baseline scenario is around 1.194 billion m3, dominated by agriculture (96%), with rice crop requiring nearly half. For the future scenario of 2050, the study shows a 16.6% surge in demand to 1.394 billion m3, driven by climate change and agricultural expansion. However, domestic use decreases by 10% due to population reduction. Water deficit in the future is projected to increase by 52% from 172.4 to 262.7 million m3 due to rising water demand and declining water supply. This study shows that integrating a hydrological model into a water allocation model is a promising approach to estimate the water supply, demand and balance, which is a crucial component of water resources management.

A simple and sensitive liquid chromatography-tandem mass spectrometry (LC– MS/MS) method has been developed for the simultaneous determination of atorvastatin (ATOR), ezetimibe (EZM) and their three metabolites including o-hydroxyl atorvastatin (o-OH ATOR), p-hydroxyl atorvastatin (p-OH ATOR), and ezetimibe-glucuronide (EZM-G) in human plasma using benzyl paraben (BP) as internal standard (IS). The analytes and IS were ionized using ESI positive ion mode (ATOR, o-OH ATOR, and p-OH ATOR), ESI negative ion mode (EZM, EZM-G, and BP), and operated in multiple reaction monitoring (MRM) mode. They were next extracted by salting-out assisted liquid–liquid extraction with acetonitrile, and then analyzed by liquid chromatography on a reversed-phase chromatographic column (50 mm × 4.6 mm; 3.5 µm), using a mixture of ac-etonitrile and an acetic acid solution (0.5%) as the mobile phase, showing high extraction effi-ciency (>70%), and a minimized matrix effect. The method was satisfactorily validated, and showed excellent linearity over wide concentration ranges of 0.06–15 ng/mL, 0.6–150 ng/mL, 0.4–100 ng/mL, 0.12–30 ng/mL, and 0.05–3 ng/mL for EZM, EZM-G, ATOR, o-OH ATOR, and p-OH ATOR, respectively.

This study aimed to evaluate the effect of incorporating linseed oil and fish oil in the diet on intake, ruminal fermentation milk yield and milk fatty acid profile in dairy goats. Four crossbred Saanen lactating goats in mid-lactation and milking 1.30±0.28 g/day were used in a 4 × 4 Latin square design. The basal diet consisted of concentrate and Para grass (C:F 40:60). Treatments included the basal diet without oil supplement (Ctrl) or with 2.5% linseed oil (LO2.5), 2.5% linseed oil and fish oil (3:2, w/w, LFO2.5), and 4.16% linseed oil and fish oil (3:2, w/w, LFO4.16). Diets had no effect on intake, milk yield, milk composition and ruminal fermentation patterns (P > 0.05). The lower (P < 0.05) proportions of C10:0-C14:0 in milk fat were observed with LFO4.16 compared with Ctrl. Compared with the Ctrl and linseed oil added alone, feeding LFO4.16 resulted in a 589% and 303% increase in C18:1 t11, respectively. Milk c9,t11 CLA was markedly increased with the LFO4.16 diet, accounting for 4.53 and 2.94 times greater concentrations than those in Ctrl and LO2.5 diets, respectively (P < 0.01). Goats fed LFO2.5 and LFO4.16 had greater levels of C22:6n-3 (0.63% and 0.87%; P < 0.001) compared with those fed Ctrl and LO2.5 diets (0.06% and 0.08%). Overall, the combined data suggested that including 4.16% linseed oil and fish oil in the diet of dairy goats is effective for improving the concentrations of healthy fatty acids in milk, without affecting milk production.

The TiO₂ nanostructures resulted by pyrolysis of TiCl₄ at low temperature of 80 ^oC are found to be a mixture of amorphous TiO₂ complexes and anatase nanostructure whose ratio depends on the pH of the pyrolysis medium. At low pH level, the resulting TiO₂ nanostructure is predominant anatase and gradually shifts to the amorphous TiO₂ complexes with pH level increasing. By means of heat treatment, the amorphous TiO₂ complexes can be converted back to the anatase nanostructure and then transform to rutile with the elevating temperature. Amongst of the TiO₂ nanostructure recovered from amorphous TiO₂ complexes, the anatase shows to be the most effective photocatalyst in decomposition of methylene blue.

In the Vietnamese Mekong delta, soil quality and crop yield are steadily declining under rice monocultures with three crops per year. The objective of this study was to evaluate the medium-term effects of rotating rice with upland crops and adding organic amendments on rice yield and relate it to soil quality. A field trial with split-plot design including two factors and three replicates was carried out from 2017 to 2020, over the course of nine consecutive cropping seasons. Crop rotations and organic amendments were applied as main-plot and subplot factors, respectively. The rotations were: 1) rice–rice–rice (R–R–R), 2) soybean–rice–rice (So–R–R), and 3) sesame–rice–rice (Se–R–R), while organic amendment treatments included: i) no amendment (NO-AM); ii) compost of rice straw and cow manure (RS+CM), and iii) sugarcane compost (SGC); the composts were applied at a rate of 2.0 t ha-1. The rotation cycle started with the so-called spring–summer (SS), followed by summer–autumn (SA) and ended with the winter–spring (WS) season. Rice yield significantly (P &lt; 0.05) increased by organic amendments after nine growing seasons (2019–2020 WS), with an increment of 5.1% for RS+CM (7.07 ton/ha) and 6.1% for SGC (7.14 ton/ha). Contrary to our expectation, rotations with upland crops did not significantly increase rice yield. Rice yield significantly and positively correlated with an integrated soil quality index SQI (r = 0.86) for the topsoil (0–15 cm), but not for the subsoil (15–30 cm). The increased availability of soil nutrients (Si and marginally also P) and improved soil physical properties probably induced by organic amendments, along with other soil properties under study, cumulatively attributed to enhanced rice yield. Use of a SQI involving several soil quality indicators enables to overall quantify the importance of soil fertility for rice yield versus other factors and it provides an effective means of quantifying the integrated effect of improved management. Moreover, integrating a wide range of soil quality indicators in a SQI ensures its applicability across diverse settings, including different crop rotations and various soil types.

Background: Acute hepatopancreatic necrosis disease (AHPND), is a bacterial disease of whiteleg shrimp, which has a high mortality rate (100%) and incurs economic losses. Our objective was to identify the genes which lead to cell and organ damage and investigate bioproducts to prevent and treat. Methods: Litopenaeus vannamei shrimp in Thua Thien Hue province, Vietnam were collected from an infected pond and analysed at the Institute of Biotechnology, Hue University. The PirA gene of Vibrio parahaemolyticus strain K5 was isolated and analyzed for nucleotide sequence and paired with the expression vector pQE30. The expression vector was transformed into E. coli strain M15, the PirA recombinant protein was expressed in the form of 6xHis-PirA fusion protein of about 15 kDa. PirA recombinant protein was purified and determined the PirAvp binding ratio, cloning and sequencing of PirA gene from Vibrio parahaemolyticus strain K5 causing AHPND by PCR method with specific primers and molecular weights of PirAvp and the PirAvp complex. Results: PirA gene from Vibrio parahaemolyticus strain K5 was cloned into pGEM-T easy vector (Promega, USA) and screened E. coli TOP10 colonies containing pGEM T easy/PirA recombinant plasmid on LB agar/ampicillin/IPTG/X-Gal medium. PCR showing a band of about 347 bp, matching the size of PirA gene and two nucleotide sequences (BamHI and HindIII). The results showed that PirA gene has a length of 336 bp and similar to PirA gene on GenBank (Code: KU556825.1). The results of protein extracted from E. coli M15 recombinant cells and 6xHis-PirA target protein was collected in elution fractions from EF2 to EF6, showed that the concentration of 6xHis-PirA protein and EF3 elution fraction collected a highest protein concentration (1,586.54 µg/ml). Conclusions: The purified PirA recombinant protein will provide materials for development research to create biological products to prevent and treat AHPND.

This article conducts a bibliometric analysis focusing on the influence of globalization and technology in the academic context. Previous studies have focused on analyzing the relationship between the number of research citations and international collaboration, but no study has explored it in the scope of consumer behavior and retail. Leveraging the Scopus database, the research analyzes a significant corpus of 2,111 documents from 1971 to 2022. The findings reveal a distinct surge in academic output related to the topic of technology, reflecting a growing interest in understanding the interaction between technological factors and consumer behavior. The study also explores trends in international collaboration in publications as well as its impact on citation counts.

(1) Background: Sentinel lymph node (SLN) mapping represents an accurate and feasible technique for the surgical staging of endometrial and cervical cancer. This is commonly performed by conventional laparoscopy or robotic-assisted laparoscopy, but in recent years, a new retroperitoneal transvaginal natural orifice transluminal endoscopic surgery (vNOTES) approach has been described. This technique provides easy visualization of lymphatic afferent vessels and pelvic lymph nodes, early SLNs assessment, and a coherent mapping methodology following the lymphatic flow from caudal to cranial. However, only a few publications have reported it. Following the IDEAL (Idea Development Exploration Assessment Long-term follow-up) framework, research concerning this technique is at stage 2a, with only small case series as evidence of its feasibility. Its standardized description appears necessary to provide the surgical homogeneity required to move further. (2) Methods: description of a standardized approach for retroperitoneal pelvic SLN mapping by vNOTES. (3) Results: we described a 10-step approach to successfully perform retroperitoneal vNOTES SLN mapping, including pre-, intra-, and postoperative management. (4) Conclusions: This IDEAL stage 2a study could help other surgeons approach this new technique, and it proposes a common methodology necessary to evolve through future IDEAL stage 2b (multi-center studies) and stage 3 (randomized controlled trials) studies.

Artificial Intelligence innovations, such as chatbots and specialized education suggestion tools, provide potential interactive and on-demand pedagogical engagement between non-Christians and Christians with Christianity. However, there is little empirical research on the readiness, acceptance, and adoption of A.I.'s involvement in religious education in a secular state, such as Vietnam. This research addresses the literature gap by providing an entrepreneurial analysis and customer perspectives on the ideas of A.I.'s involvement in religious education. Specifically, the study explores whether the Vietnamese across different ages and religious orientations accept and have enough skills to adopt A.I.'s religious education innovation. The interview sample is 32 participants, selected based on their religious orientation (Christians & Non-Christians) and age (Generation X, Generation Y & Generation Z). Most respondents are open to A.I. application in religious education except for the Church's personnel. However, only gen Z generations are fully prepared to adopt this innovation. Theoretically, the research customizes the Unified Theory of Acceptance and Use of Technology model into religious innovation context. Practically, this research acts as market research on the demand for A.I.'s religious innovation in Vietnam, an insight for future religious tech entrepreneurs.

Osteoclasts (OCs) are the multinucleated, bone-resorbing giant cells originally differentiated from a monocyte/macrophage lineage. OC differentiation and maturation, also called osteoclastogenesis, are strictly regulated by a variety of signaling pathways primarily induced by the interactions of two prerequisite cytokines, macrophage colony-stimulating factor (M-CSF) and the receptor activator of nuclear factor-κB ligand (RANKL) to their respective surface receptors, c-fms and RANK, in OC precursors (pre-OCs). Rab11 has emerged as the spatiotemporal regulators of intracellular vesicular transport in the endosomal recycling system; however, how it regulates osteoclastogenesis is incompletely understood. OC-triggered bone resorption is best characterized to be immensely dependent upon lysosomal function, the intracellular acidic organelles containing more than 50 acid hydrolases secreted into bone matrix microenvironment (BME). On the contrary, it is little known about the lysosomal function on modulating the turnover of c-fms and RANK surface receptors via Rab GTPase-mediated vesicular transport, thereby dictating osteoclastogenesis. In this review, I briefly describe the mechanism underlying lysosome-induced osteoclastogenesis via the Rab11-mediated modulation of the surface receptors in OCs.

Initial periods of adsorption kinetics play an important role in estimating the initial adsorption rate and rate constant of adsorption process. Several adsorption processes rapidly occur, and the experimental data of adsorption kinetics under the initial periods can contain potential errors. The pseudo-second-order (PSO) kinetic model has been popularly applied in the field of adsorption. The use of the nonlinear optimization method to obtain the parameters of the PSO model can minimize error functions during modelling compared to the linear method. However, the nonlinear method has limitations in that it cannot directly recognize potential errors in the experimental points of time-dependent adsorption, especially under the initial periods. In this study, for the first time, the different linear types (Types 1–6) of the PSO model are applied to discover the error points under the initial periods. The result indicated that the fitting method using its linear equations (Types 2–5) is really helpful for identifying the error (doubtful) experimental points from the initial periods of adsorption kinetics. The imprecise points lead to low adjusted R2 (adj-R2), high reduced χ2 (red-χ2), and high Bayesian information criterion (BIC) values. After removing those points, the experimental data were adequately fitted with the PSO model. statistical analyses demonstrated that the nonlinear method must be used for modelling the PSO model because its red-χ2 and BIC were lower than the linear method. Type 1 has been extensively applied in the literature because of its very high adj-R2 (0.9999) and its excellent fitting to experimental points. However, its application should be limited because the potential errors from experimental points were not identified by this type. For comparison, the other kinetic models (i.e., pseudo-first-order, pseudo-nth-order, Avrami, and Elovich) are applied. The modelling result using the nonlinear forms of those models indicated that the fault experimental points from the initial periods were not detected.

Smart City has emerged as the mainstream paradigm for urban governance innovation, sustainable development, and strategy upgrades, which is drawing attention from scholars worldwide. However, current frameworks for Smart City assessment remain incomplete and simplistic. In is paper, 30 national or provincial capitals in China were selected and we designed a tri-dimensional SPI model—Social, Physical, and Information Space—for smart city spatial development assessment. Utilizing methods such as entropy weighting, coupled coordination degree models, and the Dagum Gini coefficient, this study assesses the spatial development and coupled coordination of 30 cities from 2011 to 2019. Finally, by means of BP neural networks, the study examines the contribution of each indicator to the spatial coupled coordination. The results indicated that with a narrowing disparity in development speeds among different regions, the spatial coupled coordination development level of smart capitals in China has steadily increased, presenting a pattern of staggered distribution. Moreover, the IS subsystem plays the most significant role in coupled coordination. The significance of this research lies in its tri-dimensional spatial perspective of the spatial development and coupled coordination differences of the Smart City, providing evidence-based support for the regional layout and optimization in China.

Global agriculture has been forced to increase food production to feed the growing human population, while confronting various environmental obstacles such as global warming, resistance to pathogens, and constraints on arable land caused by soil salinity, drought, rising sea level, saltwater intrusion, and urbanization. Regarding abiotic stresses, salinity is a worldwide problem for agricultural production. Many efforts, therefore, have been made to cope with the environmental challenges, however, the progress of salinization, which is mainly caused and accelerated by anthropogenic activities, is likely faster than our progress in finding ways to deal with this problem. In addition, drought represents a global threat to the production of major crops. In addition, pests and pathogens cause significant crop losses and diminish global food security. Among the various strategies that have been investigated and applied in plant science, antimicrobial peptides derived from plants have caught widespread attention from scientists since these peptides exhibit beneficial biological activities. In agricultural science, there have been reports on the roles of antimicrobial peptides with active properties against biotic and abiotic stresses. Non-specific plant lipid transfer proteins, thionins, systemins, defensins, cyclotides, and heveins-like antimicrobial peptides are common antimicrobial peptides that have been found to be involved in the defense system against fungi and insect pests. Based on their potential ability to protect crops from pests, bacteria, and pathogenic fungi, the use of antimicrobial peptide genes in creating transgenic plants has been largely conducted during the last decades, and these studies have obtained positive results against the growth of fungi and bacteria. This review will focus on the latest progress in studies of antimicrobial peptides related to biotic and abiotic stress tolerance in plants. We will also update the current progress in the development of antimicrobial peptide-based transgenic crops.

Renal clear cell carcinoma (ccRCC) comprises over 75% of all renal tumors and arises in the epithelial cells of the proximal convoluted tubule. Molecularly ccRCC is characterized by copy number alterations (CNAs) such as the loss of chromosome 3p and VHL inactivation. Additional driver mutations (SETD2, PBRM1, BAP1, and others) promote genomic instability and tumor cell metastasis through the dysregulation of various metabolic and immune-response pathways. Many researchers identified mutation, gene expression, and proteomic signatures for early diagnosis and prognostics for ccRCC. Despite a tremendous influx of data regarding DNA alterations, gene expression, and protein expression, the incorporation of these analyses for diagnosis and prognosis of RCC into the clinical application has not been implemented yet. In this review, we focused on the molecular changes associated with ccRCC development, along with gene expression and protein signatures, to emphasize the utilization of these molecular profiles in clinical practice. These findings, in the context of machine learning and precision medicine, may help to overcome some of the barriers encountered for implementing molecular profiles of tumors into the diagnosis and treatment of ccRCC.

To solve the problem of energy constraint and spectrum scarcity for cognitive radio wireless sensor networks (CR-WSNs), an underlay decode-and-forward relaying scheme is considered, where the energy constrained secondary source and relay nodes are capable of harvesting energy from a multi-antenna power beacon (PB) and using that harvested energy to forward the source information to the destination. Based on the time switching receiver architecture, three relaying protocols, namely, hybrid partial relay selection (H-PRS), conventional opportunistic relay selection (C-ORS), and best opportunistic relay selection (B-ORS) protocols are considered to enhance the end-to-end performance under the joint impact of maximal interference constraint and transceiver hardware impairments. For performance evaluation and comparison, we derive exact and asymptotic closed-form expressions of outage probability (OP) and throughput (TP) to provide significant insights into the impact of our proposed protocols on the system performance over Rayleigh fading channel. Finally, simulation results validate the theoretical results.

The Ca Mau Peninsula situated in the Mekong Delta of Vietnam, features a low-lying terrain. Over recent years, the region has encountered the adverse impacts of climate change, leading to both land subsidence and rising sea levels. In this study, we assessed the land subsidence susceptibility in the Ca Mau peninsula utilizing three Boosting machine learning models: AdaBoost, Gradient Boosting, and Extremely Gradient Boosting (XGB). Eight key factors were identified as the most influential in land subsidence within Ca Mau: land cover (LULC), Groundwater levels, distance to roads, Digital Terrain Model (DTM), normalized vegetation index (NDVI), geology, soil composition, and proximity to rivers and streams. A dataset comprising 1950 subsidence sample points was employed for the model, with 1910 points obtained from the PSInSAR Radar method, and the remaining points derived from leveling measurements. The sample points were split, with 70% allocated to the training set and 30% to the testing set. Following computation and execution, the three models underwent evaluation for accuracy using statistical metrics such as the ROC curve, Area under the curve (AUC), Specificity, Sensitivity, and Overall Accuracy. The research findings revealed that the XGB model exhibited the highest accuracy, achieving an AUC above 0.9 for both the training and test sets. Consequently, XGB was chosen to construct a land subsidence susceptibility map for the Ca Mau peninsula.

This study was conducted to investigate the status of regional linkage in tourism development in in the Midlands and Northern Mountains of Vietnam. The data was collected from a survey of 755 people, including officials from State management bodies in charge of tourism, officials and staffs at tourism resorts, tourism firms, tourism scientists and tourists. In addition, we conducted 10 group discussions, interviewed 30 State tourism agency officials and tourism firms in the Midland and Mountainous provinces of Vietnam. The results show that tourism development in Vietnam in general and the Northwest region in particular is extremely fragmented, not yet forming a regional linkage; Regional and national tourism development programs are just formalistic. The main cause of the situation is the limited regional integration policy in Vietnam, the lack of appropriate regional governance mechanisms and inactive participation of the private sector in regional integration. Based on the findings, we propose a tourism sector linkage model; besides, policy implications are given for fulfilling the linkage policy in the Midlands and Northern Mountains area.

The emergence of the Covid-19 pandemic has created both negative and positive changes, including implementing the circular economy across the globe. This Systematic Review follows the PRISMA statement and employs the Text Mining (Voyant Tools) technique to visualize and analyze the impacts of the Covid-19 on three aspects of the circular economy: economic, social, and environmental. The research employs Latent Dirichlet Allocation (LDA) to identify five major topics: (1) Shortage of medical equipment but high medical waste during Covid-19 due to the high demand in healthcare; (2) The long term negative impacts of lockdown on economic and social activities because of Covid-19 pandemic; (3) The reports on impacts of Covid-19 pandemic on the manufacturing globally, and their coping strategies and new opportunities; (4) The impacts of international restriction on the tourism, trade, shipping, and aviation industry, causing billion-dollar losses; (5) The reduction of pollution with health environment improvements with example cases from China and EU. The research identifies current literature gaps in the circular economy and Covid- 19 topics and encourages the application of text mining tools into researching to stimulate the research process and assist in communicating with the public.

Various wood fibres, including pine and flax, are used in wood–plastic composites (WPCs). This paper studies the effect of the lignin content on the morphological and thermal degradation and damage due to the ultraviolet (UV) aging of polypropylene/flax (PP-flax) and polypropylene/pine (PP-pine) fibres composites. Flax and pine fibres exhibited distinct densities of 1.51 and 1.47 g/cm³, respectively, potentially influenced by growth factors and varying compositions of light substances, such as hemicellulose, lignin, and impurities. The thermal decomposition mass loss increased proportionally with the percentage of lignin in the fibre. From 238°C to 390°C, the pine fibre exhibited a 72% mass loss compared to flax fibre, which showed a 54% mass loss, owing to the higher lignin content in pine fibres. Based on differential scanning calorimetry (DSC), the fibre composition affected the material melting temperature. Moreover, DSC curves revealed a higher degree of crystallinity in the case of the PP-flax biocomposite (12%) compared to pure polypropylene (9%) and PP-pine (6%). This result can be attributed to the high content of crystalline components in flax fibres, such as cellulose. Acoustic emissions analysis confirmed that the high lignin content delays degradation and mitigates the appearance of microcracks on the surface of the PP-pine biocomposite. Overall, the study provides valuable data for understanding the UV degradation phenomenon in biocomposites and highlights the influence of fibre composition on material performance.

This paper introduces an advanced method that integrates contingent valuation and machine learning (CVML) to estimate residents’ demand for reducing or mitigating environmental pollutions and climate change. To be precise, CVML is an innovative hybrid machine-learning model, and it can leverage a limited amount of survey data for prediction and data enrichment purposes. The model comprises of two interconnected modules: Module I, an unsupervised learning algorithm, and Module II, a supervised learning algorithm. Module I is responsible for grouping the data into groups based on common characteristics, thereby grouping the corresponding dependent variable, whereas Module II is in charge of demonstrating the ability to predict and the capacity to appropriately assign new samples to their respective category based on input attributes. Take a survey on the topic of air pollution in Hanoi in 2019 as an example, we found that CVML can predict households’ willingness– to– pay for polluted air mitigation at a high degree of accuracy (i.e., 98%). We found that CVML can help users reduce costs or save resources because it makes use of secondary data that is available on many open data sources. These findings suggest that CVML is a sound and practical method that could be widely applied in a wide range of fields, particularly environmental economics and sustainability science. In practice, CVML could be used to support decision-makers in improving the financial resources to maintain and/or further support many environmental programs in years to come.

Employing remote sensing techniques to evaluate crop residue cover (CRC) enables rapid mapping of tillage practices over large cropland areas, which has significant practical implications for monitoring the implementation of conservation tillage practices. This research utilized Sentinel-2 MSI and Landsat-8 OLI remotely sensed data, various spectral indices were calculated and the datasets were correlated with the field-measured CRC data. Selected spectral indices, highly significantly correlated, were chosen to build a correlation model between the indices and the CRC. Considering Sentinel-2 MSI and Landsat 8 OLI remotely sensed data variations in spectral and spatial scales, the accuracy of CRC models was evaluated using R2 and RMSE values. From the results, it's evident that all six spectral indices, including STI, NDTI, SRNDR, NDI5, NDI7 and NDSVI, registered correlation coefficients with the CRC exceeded 0.3 in the study area. STI and NDTI showed a stronger correlation to CRC, with coefficients of 0.810 and 0.803, respectively. For the Landsat 8 data, the lowest correlation obtained was for NDSVI with the Landsat 8 data with a correlation coefficient of 0.358. Applying the linear regression technique, STI and NDTI obtained higher accuracy compared to other indices in the Sentinel-2 MSI data. For NDTI and STI, The R2 values were 0.650 and 0.665, respectively, while their corresponding RMSE values were 3.96% and 4.03%. The highest model accuracy was obtained for the STI and NDTI constructed from the Landsat 8 OLI data (R2 values 0.41 and 0.40; RMSE values 5.25% and 5.27%, respectively). The CRC model built using partial least squares regression (PLSR) exhibited greater precision when applied to the Sentinel-2 MSI data (R2 value 0.894; RMSE value 2.18%) in comparison to the Landsat 8 OLI data (R2 value 0.695; RMSE value 3.70%). PLSR has the potential to enhance the precision of the model. In addition, the study area shows that the estimation of the CRC is better in the one-dimensional linear regression model and the PLSR model created with the Sentinel-2 MSI optical data compared to the Landsat 8 OLI optical remotely sensed data. The validation suggests that the CRC estimation in the study area is more precise when using the model relying on Sentinel-2 satellite imagery rather than the Landsat 8 OLI imagery.

In this study, we use descriptive statistics and data visualization techniques to analyze datasets and identify patterns and relationships between bikeshare and other transportation modes. We also use regression analysis to quantify the impact of various factors on bikeshare usage. Our results indicate that bikeshare trips during the pandemic were much longer compared to pre-pandemic times. Moreover, usage of bikeshare differed by user group, with casual users showing a greater increase in usage compared to subscribers. We plotted bivariate choropleth maps to visualize the spatial distribution of changes in bikeshare usage. Our findings suggest that an increase in bikeshare travel was associated with a reduction in travel by ride-hailing and public transit, especially in the northern part of the city, indicating a potential replacement of other modes of transportation. On the western and southern boundary of the city, bikeshare had a complementary effect with other modes. Overall, the data acquired for this study provides a valuable opportunity to understand the behavior of bikeshare users in Chicago, the intercorrelation of bikeshare with other transportation modes, and the impact of infrastructure on bikeshare usage. The findings of this study can inform the design and implementation of bikeshare systems in other cities and contribute to the development of a more sustainable transportation system.

Amid escalating urbanization, devising rational commercial space layouts is a critical challenge. Leveraging machine learning, this study uses a Back-propagation (BP) neural network to optimize commercial spaces in Weinan City's central urban area. The results indicate an increased number of commercial facilities with a trend of multi-centered agglomeration and outward expansion. Based on these findings, we propose a strategic framework for rational commercial space development emphasizing aggregation centers, development axes, and spatial guidelines. This strategy provides valuable insights for urban planners in small and medium-sized cities in the Yellow River Basin and metropolitan areas, ultimately showcasing the power of machine learning in enhancing urban planning.

Significant amounts of anthropogenic radionuclides were introduced in ocean waters following nuclear atmospheric tests and development of the nuclear industry. Dispersion of artificial dissolved radionuclides has been extensively measured for decades over the European continental shelf. The radionuclide measurement and release fluxes databases provided here represent an exceptional opportunity to validate dispersion hydrodynamic models. MARS hydrodynamic model have been applied at different scales to reproduce in realistic conditions the measured dispersion. Specific methods have been developed to obtain qualitative and quantitative results and perform model/measurement comparisons. Model validation concerns short to large scales with dedicated surveys following the dispersion: it was performed within two and three dimensions framework and from minutes and hours following a release up to several years. Results are presented concerning the dispersion of radionuclides in marine systems deduced from standalone measurements, or according to model comparisons. It allows characterising dispersion over the continental shelf, pathways, transit times, budgets and source terms. This review exhibits the main features retained from the point of view of radiotracers, hydrodynamic models and model/measurement methods with perspectives of applications in other areas or oceanographic domains.

Achieving the dual development of rural revitalization and urbanization is an important strategic goal of China’s current modernization. Rural population and settlements are the main components of the countryside in traditional agricultural areas, and play an important role in the development of the countryside itself in terms of urban and rural land use and in the formation of urban and rural development patterns. This study analyzes the spatial and temporal changes in rural populations and settlements at the township level, as well as the degree and type of coupled development. A framework for urban–rural development relationships based on different types of coupled development is proposed, and a model of urban–rural forces is constructed to derive the spatial pattern of urban–rural development at the township level that may be formed in the future. Our study shows that the rural population and settlements in the study area are characterized by significant spatial and temporal dynamics, indicating that traditional rural areas are in a process of rapid development and change. The results of the township-level coupling measurements present four types of development in terms of the spatial pattern of urban–rural development: A-type is most likely to produce new cities or satellite towns in the Jixi–Harbin–Qiqihar area in the future; B-type is the fastest dying area in the future, located in the Harbin and Qitaihe clusters, with a tendency to merge into Harbin; C-type is the area to be focused on in the future to attract population and strictly control the growth of the rural settlement area to avoid it turning into B-type; D-type may develop regional township centers in the future in the combined area of Jiamusi City, Suihua City and Mudanjiang City. The results of the study provide experience in realizing rural revitalization according to local conditions. The new spatial pattern of urban–rural development provides an important reference for formulating land use policies, optimizing urban–rural land allocation and realizing integrated urban–rural development strategies.

Health of migrant is a widely studied topic. It has been argued that migrant health may deteriorate over time. Though migrants are ‘a hard to reach’ population in survey data, this paper builds on a unique dataset provided by Médecins du Monde from five countries. We study self perceived health (SPH) in connection with socio-economic and demographic factors and length of stay. Results show different results for men and women. Asylum seekers compared to other documented migrants have a worse health. Migrants with better living conditions tend to be in better health. Employment and stable accommodation has a positive effect on SPH. Women from poorer countries have a better physical SPH after 3 months of residing in the host country. This paper contributes widely to knowledge of health of migrants. Contrarily to other evidence, health of migrants tends to improve for some migrants.

Government support plays an important role in Chinese economy. New energy industries, concerning innovation-driven source and environmental protection, are also supported by government. This paper aims to study the effects of the traditional government support at supply side on firms’ innovation and development. In this paper, we propose enterprise behavior model including characteristics of new energy industries, and study the innovation reaction of firms to government support in different situation. We further use propensity score matching to verify the results in theoretical model, and conduct robustness analysis. Our main conclusions include: (1) In the normal years government support can only promote the innovation output of firms which have innovated, however, can not promote the innovation probability of firms which have not innovated. That is to say, government support can only enhance the intensive margin of innovation, but can not enhance the extensive margin of innovation with less competition. (2) In the situation of bad economic environment and intense competition, firms’ innovation probability rises as the government support increase. Therefore, government should provide more R&D special subsidies and implement strict financial supervision to make the effectiveness of support policies especially in the normal years.

Plants have developed unique mechanisms to cope with the harsh environmental conditions to compensate for their lack of mobility. A key part of their coping mechanisms is the synthesis of secondary metabolites. In addition to their role in plants’ defense against pathogens, they also possess therapeutic properties against diseases, and their use by humans predates written history. Viruses are a unique class of submicroscopic agents, incapable of independent existence outside a living host. Pathogenic viruses continue to pose a significant threat on global health, leading to unprecedented fatalities on a yearly basis. The use of medicinal plants as a natural source for an-tiviral agents has been widely reported in literature in the past decades. Metabolomics is a powerful research tool for the identification of plant metabolites with antiviral potentials and can be used to isolate compounds with antiviral activities in plants and study the biosynthetic pathways involved in viral disease progression. This review discusses the use of medicinal plants as antiviral agents, with a special focus on the metabolomics evidence supporting their efficacy. Additionally, suggestions are made for the optimization of various metabolomics methods for characterizing the bio-active compounds in plants and subsequent understanding of the mechanism of their operation.

Thyroid hormones have a catabolic effect on bone homeostasis. Hence, this study aimed to evaluate serum vitamin D, calcium, and phosphate and bone marker levels and bone mineral density (BMD) among patients with different thyroid diseases. This cross-sectional study included patients with underlying thyroid diseases (n=64, hyperthyroid; n=53 euthyroid; and n=18, hypothyroid) and healthy controls (n=64). BMD was assessed using z-score and left hip and lumbar bone density (g/cm2). Results showed that the mean serum vitamin D Levels of all groups was low (<50 nmol/L). Thyroid patients had higher serum vitamin D levels than healthy controls. All groups had normal serum calcium and phosphate levels. The bone marker levels were significantly high in the hyperthyroid group and low in the hypothyroid group. The z-score for hip and spine did not significantly differ between thyroid patients and control groups. The hip bone density was remarkably low in the hyperthyroid group. In all groups, the serum vitamin D levels were below the cutoff value. However, thyroid patients had a higher serum vitamin D level than healthy controls. The carboxy terminal collagen crosslink and procollagen type I N-terminal propeptide levels were high in hyperthyroid patients and low in hypothyroid patients. Further, hyperthyroid patients had a low hip BMD.

Receptor-interacting protein kinase 1 (RIPK1) plays a crucial role in controlling inflammation and cell death. Its function is tightly controlled through post-translational modifications, enabling its dynamic switch between promoting cell survival and triggering cell death. Phosphorylation of RIPK1 at various sites serves as a critical mechanism for regulating its activity, exerting either activating or inhibitory effects. Perturbations in RIPK1 phosphorylation status have profound implications for the development of severe inflammatory diseases in humans. This review explores the intricate regulation of RIPK1 phosphorylation and dephosphorylation and highlights the potential of targeting RIPK1 phosphorylation as a promising therapeutic strategy for mitigating human diseases.

In order to increase the number of tourism in ecotourism, enhance the ecotourism attractions. It is essential to construct the ecotourism service system for the Penghu National Scenic Area because the ecology system is sensitive and frangible. This study adopts the Fuzzy Delphi method and Analytic Hierarchy Process (AHP) to establish an index framework of ecotourism service system of Penghu National Scenic Area. The results indicated that there are 4 dimensions which include 21 factors service attributes are identified as the service system for traveling. The findings are concluded as follows:(1)the security management capability is the main principle for ecotourism service system;(2)the ecological diversity is fundamental for the marine environment and the core resource for ecotourism;(3)the transportation capacity and environmental quality need to improve; (4)the marine environmental resources is the most important item for sound ecotourism development; (5)the enhancement of the operation willingness of local communities can promote ecotourism development;(6)the natural resources should be protected to provide an ideal recreational environment for ecotourism;(7)the development of ecotourism needs to support local conservation to achieve sustainability. The perspectives of sustainability and service system are involved to support the value of this study, which can continuously sustain Penghu archipelago.

Ras homolog enriched in brain (Rheb1 and Rheb2), a small GTPase, regulates neuronal activity and has drawn attention for its implications in cancer development, especially breast cancer. This study explores the multifaceted role of Rheb1 in cancer, elucidating its involvement in crucial cel-lular processes such as proliferation, apoptosis resistance, migration, invasion, metastasis, and inflammatory responses. Despite these acknowledged connections, a comprehensive understanding of the intricate interplay between Rheb1 and cancer remains elusive. This review consolidates cur-rent knowledge on the impact of Rheb1 on cancer hallmarks and examines the potential of Rheb1 as a therapeutic target in cancer treatment. The review underscores the need for a more profound comprehension of the molecular mechanisms underlying Rheb1-mediated oncogenic processes. Furthermore, the review emphasizes the exploration of Rheb1 inhibitors as a promising avenue for cancer therapy. This study, by bringing to light the complex associations between Rheb1/Rheb2 and cancer, delivers valuable insights to the scientific community. These insights are instrumental in guiding the identification of novel targets and advancing the development of effective therapeu-tic strategies for treating cancer.

In the context of intelligent and integrative lighting, in addition to the need for color quality and brightness, the non-visual effect is essential. This refers to the retinal ganglion cells (ipRGCs) and their function, first proposed in 1927. The melanopsin action spectrum has been published in CIE S 026/E: 2018 with the corresponding melanopic equivalent daylight (D65) illuminance (mEDI), melanopic daylight (D65) efficacy ratio (mDER) and 4 other parameters. Due to the importance of mEDI and mDER, this work synthesizes a simple computational model of mDER as the main research objective, based on a database of 4214 practical spectral power distributions (SPDs) of daylight, conventional, LED, and mixed light sources. In addition to the high correlation coefficient R2 of 0.96795 and the 97% confidence offset of 0.0067802, the feasibility of the mDER model in intelligent and integrated lighting applications has been extensively tested and validated. The uncertainty between the mEDI calculated directly from the spectra and that obtained by processing the RGB sensor and applying the mDER model has reached ± 3.3% after an appropriate matrixing process and proper illumination characterization combined with the successful mDER calculation model. This result opens the potential of low-cost RGB sensors for applications in intelligent and integrative lighting systems to optimize and compensate the non-visual effective parameter mEDI using daylight and artificial light in indoor spaces. The goal of the research on RGB sensors and the corresponding processing method are also presented and their feasibility is methodically demonstrated. A comprehensive investigation with a huge amount of color sensor sensitivities is necessary in a future work of other researches.

Graphene-based nanoparticles possess remarkable physiochemical properties, making them promising for diverse applications in biomedicine, agriculture, food, and industrial applications. These nanoparticles have also been used in the fight against COVID-19. Human and environmental exposure to graphene-based nanomaterials is increasing at an unprecedented rate. However, there is still a huge knowledge gap regarding its safety in clinical applications. The topic remains controversial; although several routes of degradation exist, the cytotoxicity of graphene-based nanoparticles has been demonstrated. Various factors that can influence the cytotoxicity of graphene-based materials are discussed. This review summarizes the physiochemical properties of graphene-based materials and critically examines the possible effects of graphene-based nanoparticles on the molecular level and adverse health outcomes. While oxidative stress-mediated cell damage has been proposed as a primary cytotoxicity mechanism for graphene-based materials, various in vivo biodistribution and cytotoxicity mechanisms are also highlighted. Therefore, this review of the literature provides an overview of the cytotoxicity of GBMs and raises concerns about their widespread application with potential hazardous consequences on the environment and human health.

In recent years, drones have been used in a wide range of fields such as agriculture, transportation of goods, and security. Drones equipped with communication facilities are expected to play an active role as base stations in areas where ground base stations are unavailable, such as disaster areas. In addition, asynchronous operation is being considered for local 5G in order to support all kinds of use cases. In asynchronous operation, cross-link interference between base stations is an issue. This paper attempts to reduce the interference caused by the drone network by introducing circularly polarized antennas. Numerical analyses are conducted to validate the effectiveness of the proposed system, where SIRs (Signal-to-Interference Ratio) are shown to be improved significantly as the numerical evaluation results.

Non-Orthogonal Multiple Access (NOMA) is the key technology promised to be applied in next-generation networks in the near future. In this study, we propose a multi-points cooperative relaying (MPCR) NOMA model instead of just using a relay as the previous studies. Based on the channel state information (CSI), the base station (BS) selects a closest user equipment (UE) and sends a superposed signal to this UE as a first relay node. We have assumed that there are N UEs in the network and Nth UE, which is farthest from BS, has the poorest quality signal transmitted from the BS compared other UEs. Nth UE received the forwarded signal from N-1 relaying nodes that are UEs with better signal quality. At the ith relaying node, it detect its own symbol by using successive interference cancellation (SIC) and will forward the composite signal to the next closest user, namely i+1th UE, and include an excess power which will use for energy harvesting (EH) intention at the next UE. By these, the farthest UE in network can be significantly improved. In addition, closed-form expressions of outage probability for users over both the Rayleigh and Nakagami-m fading channels are also presented. Analysis and simulation results performed by Matlab software which are presented accurately and clearly show that the effectiveness of our proposed model and this model consistents with the multi-access wireless network in future.

In response to the growing need for efficient energy conversion technologies, this pa-per introduces an innovative Tubular Thermoelectric Generator (TTEG), specifically de-signed for high-efficiency conversion of waste heat into electrical energy. Unlike conven-tional flat plate thermoelectric generators (FTEGs), the TTEG incorporates full-ring ther-moelectric elements within a tubular layout, offering a novel approach to thermal energy recovery from fluid-based systems. This design significantly enhances the heat transfer capabilities, thereby improving the efficiency of energy conversion. Comprehensive simulations and analyses form the core of this study, where the per-formance of the TTEG is rigorously compared with traditional FTEGs. These comparisons highlight the advantages of the tubular design in terms of energy conversion efficiency and practical applicability in various scenarios. The findings reveal that the TTEG not only outperforms its flat plate counterparts but also presents a scalable and adaptable so-lution for waste heat recovery in a wide range of industrial and automotive applications. This research contributes to the field of energy science and technology by presenting a detailed experimental setup, complete with reproducible procedures and results. It opens new pathways for the development of more sustainable and efficient energy conversion systems, aligning with the goal of harnessing renewable and sustainable energy sources. The potential applications of this technology in enhancing energy efficiency and reducing environmental impact are vast, making it a significant step forward in the quest for clean and sustainable energy solutions.

AISI 1050 steel circular pocket milling under minimum quantity lubrication (MQL) surroundings including nozzle elevation angle, lubricant flow rate, air pressure and cutting speed was studied. The machined surface quality (Ra) was evaluated for Up-milling side and Down-milling side. In this study, to obtain an manifest explanation on the pivotal effective parameters of MQL surroundings and cutting speed on the machined surface quality (Ra) through analyzing Taguchi L9 (34-2) approach and ANOVA calculation to identify those parameters, by utilizing the experimental outcomes to interpret three-dimensional (3D) surface plots and the diagrams of Signal-to-Noise ratios and major impact plots of Mean. The obtained outcomes of optimal operating parameters indicated that the pivotal effective parameters of MQL surroundings are nozzle elevation angle and lubricant flow rate on the machined surface quality. Simultaneously, a quadratic mathematical paradigm generated by using response surface design (RSD) and desirableness function evaluation were utilized to forecast the optimal values of the machined surface quality compared to Taguchi method. The results unveiled that the optimal values of the machined surface quality are adjacent to experimental attained values. The machined surface quality has been significantly improved using MQL surroundings.

Salinity acts as a critical environmental filter on microbial communities in natural systems, negatively affecting microbial diversity. However, how salinity affects the community assembly remains unclear. This study used Wendeng multi-pond saltern as a model to evaluate the prokaryotic community composition and diversity and quantify the relative importance of ecological processes across salinity gradients. Results showed that low saline salterns (45-80 g/L) exhibited higher bacterial diversity than those in high saline salterns (175-265 g/L). The relative abundance of taxa assigned to Halanaerobiaceae, Haloferacaceae, Desulfohalobiaceae, Phormidiaceae, Rohodobacteraceae, and Nitrococcaceae was higher with increasing salinity. Salinity and pH were the primary environmental factors that directly or indirectly determined the composition and diversity of prokaryotic communities. Microbial co-occurrence network dynamics were more complex in the sediment than in water of salterns. An infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis (iCAMP) showed that microbial community assembly in sediment and water differed. Our findings provide more information about microbial community structure and the importance of various ecological processes in controlling microbial community diversity and succession along salinity gradients in water and sediment environments.

This work emphasizes to use silver decorative method to enhance the antibacterial activity of TiO₂ and ZnO nanoparticles. These silver decorated nanoparticles (hybrid nanoparticles) were synthesized by using sodium borohydride as a reducing agent, with the weight ratio of Ag precursors: oxide nanoparticles = 1: 30. The morphology and optical property of these hybrid nanoparticles were investigated using transmission electron microscopy (TEM) and UV–vis spectroscopy. The agar-well diffusion method was used to evaluate their antibacterial activity against both Staphylococcus aureus and Escherichia coli bacteria, with or without light irradiation. The TEM images indicated clearly that silver nanoparticles (AgNPs, 5-10 nm) were well deposited on the surface of nano-TiO₂ particles (30-60 nm). Besides, smaller AgNPs (< 2 nm) were dispersed on the surface of nano-ZnO particles (20-50 nm). UV-vis spectra confirmed that the hybridization of Ag and oxide nanoparticles led to shift the absorption edge of oxide nanoparticles to the lower energy region (visible region). The antibacterial tests indicated that both oxide pure nanoparticles did not exhibit inhibitory against bacteria, with or without light irradiation. However, the presence of AgNPs in their hybrids, even at low content (< 40 mg/mL) leads to a good antibacterial activity and the higher inhibition zones under light irradiation as compared to that in dark was observed.

Facing with errors of a product after machining was a big title in this field. That will affect to product’s quality with unpredictable situation when products is in use for some particular application such as in medical facilities. Improving the precision of machine tools by exploring temperature on multiple points and measuring differential locations of the spindle is going to be executed in this study. A temperature measurement tool and a software running on Windows platform have been developed and combining with Non-bar system in order to support analyzing the temperature rising with the changes of length of the spindle to find the compensation solution based on eccentricity and length distortion. In this study, the whole tests have done on UX300 five – axis CNC machine tools for this investigation and the errors after applying compensation function have reduced 70% at least, with respect to the errors after machining without using compensation function.

Agricultural land fires have been linked to various and adverse impacts on ecosystems, food security and the agriculture sector. Understanding the patterns and drivers of agricultural land fires is essential for effective agricultural land fire management. The key objectives of this study were to (1) analyze the temporal and spatial patterns of agricultural land fires using satellite remote sensed data, (2) assess a range of environmental conditions that could drive the occurrence of agricultural land fires, (3) determine the best model for predicting agricultural land fires and (4) determine the relative contribution of each environmental condition variable on the best predictive model. We used both univariate and multivariate regressions for the fire prediction capability of four independent environmental conditions (fuel, weather, topographic and anthropogenic). Analysis of historical satellite data revealed that agricultural land fires were more frequent than forested land fires. Our analyses also revealed that fuel condition was the most important variable for predicting agricultural land fires followed by weather, topographic and anthropogenic conditions. This study provides a novel multivariate model for predicting agricultural land fires that harbors the potential to improve agricultural land fire management and reduce fire risk within the agricultural sector.

This paper provides a study on the development of solar energy, its prospects, and its impacts in Africa. Although the main focus is on technologies adopted for different uses (solar farms, mini-grids, off-grid, solar houses, irrigation, lighting, etc.), we also consider some aspects that increase the adoption of solar energy, such as legislation and business models. Finally, we will examine current and future solar projects managed by NGOs and international companies and how they benefit to leveraging social and economic standards, quality of life as well as capacity building in Africa. This study shows the plethoric interest of institutions outside Africa in the market of solar energy in the continent and that there is no African strategy to increase its independency toward a sustainable development particularly through energy transition.

We aimed to evaluate the association between daily dietary calcium intake and the risk of cardiovascular disease (CVD) in postmenopausal women using data from the Korean National Health and Nutrition Examination Survey (KNHANES). This cross-sectional study included 12,348 women aged 45–70 years who had reached natural menopause. They were classified into three groups according to daily dietary calcium intake: &lt; 400 mg, 400–800 mg, and &gt;800 mg. The risks of CVD, stroke, angina, and myocardial infarction were assessed in each group. Further, we performed subgroup analysis according to the post-menopause duration (≤10 vs. &gt;10 postmenopausal years). We performed logistic regression analysis with adjustment for age, menopausal age, income, urban area, education, insulin use, body mass index, hypertension, diabetes mellitus, dyslipidemia, high alcohol intake, smoking, exercise, oral contraceptive use, and hormonal therapy use. Calcium intake level was not significantly associated with the risk of CVD in the total population and the ≤10 postmenopausal years subgroup. However, in the &gt;10 postmenopausal years subgroup, daily calcium intake &gt;800 mg was associated with significantly decreased risks of all CVD (odds ratio [OR], 0.27; 95% confidence interval [CI], 0.11–0.64), stroke (OR, 0.06; 95% CI, 0.01–0.42), and myocardial infarction (OR, 0.27; 95% CI, 0.11–0.64). Our findings suggest that a dietary calcium intake of &gt;800 mg/day decreases the risk of CVD events in women who have been menopausal for &gt;10 years.

Bioethanol has been considered as an excellent alternative to fossil fuels since it importantly contributes to the reduced consumption of the crude oil and to the alleviation of environmental pollution [1]. Up to now, the baker yeast Saccharomyces cerevisiae is the most common eukaryotic microorganism used in ethanol production. The inability of S. cerevisiae to grow on pentoses, however, hinders its effective growth on plant biomass hydrolysates, which contain large amounts of C5 and C12 sugars. The industrial-scale bioprocessing requires high temperature bioreactors, diverse carbon sources, and the high titer production of volatile compounds [2]. These criteria indicate that the search for alternative microbes possessing useful traits that meet the required standards of bioethanol production is necessary. Compared to other yeasts, Kluyveromyces marxianus has several advantages over the others, e.g. it could grow on a broad spectrum of substrates (C5, C6 and C12 sugars) [3], tolerate to high temperature, toxin [4,5] and a wide range of pH values [6], and produce volatile short-chain ester [2]. K. marxianus also shows a high ethanol production rate at high temperature and is a Crabtree-negative species [7]. These attributes make K. marxianus a promise as an industrial host for the biosynthesis of biofuels and other valuable chemicals.

Recent studies have proven that synthetic aperture radar (SAR) automatic target recognition (ATR) models based on deep neural networks (DNN) are vulnerable to adversarial examples. However, existing attacks are easily failed in the case where adversarial perturbations cannot be fully fed to victim models. We call this situation perturbation offset. Moreover, since background clutter takes up most of the areas in SAR images and has low relevance to recognition results, fooling models with global perturbations is quite inefficient. This paper proposes a semi-whitebox attack network, called Universal Local Adversarial Network (ULAN), to generate universal adversarial perturbations (UAP) for the target regions of SAR images. In the proposed network, we calculate the model’s attention heatmaps through layer-wise relevance propagation (LRP), which is used to locate the target regions of SAR images that have high relevance to recognition results. In particular, we utilize a generator based on the U-Net to learn the mapping from noise to UAPs and craft adversarial examples by adding the generated local perturbations to target regions. Experiments indicate that the proposed method fundamentally prevents perturbation offset and achieves comparable attack performance to conventional global UAPs by perturbing only a quarter or less of SAR image areas.

Sharding shows great potential for extending the blockchain. The current challenge facing sharded blockchain technology lies in addressing the extended transaction confirmation times caused by isolated states between shards and unbalanced transaction allocation strategies. These factors contribute to an increase in cross-shard transactions and disproportionate shard workload, ultimately resulting in indefinite confirmation delays for cross-shard transactions. A critical priority for sharded blockchain systems is to conduct a comprehensive qualitative analysis to better understand and mitigate the prolonged transaction confirmation times. We introduce a Product-Form Queue Network (PFQN) model to address the transaction confirmation time problem in sharded blockchains and incorporate a new confirmation queue to more accurately simulate the actual transaction confirmation process in the blockchain. In addition, we provide a detailed quantitative analysis of the relationship between network load, consensus efficiency, and security in sharded blockchains, laying a theoretical foundation for achieving robustness and efficiency in sharded blockchains. This research not only contributes to addressing the scalability issues in sharded blockchains but also offers a new perspective for future research directions.

We have repeated the experiment performed recently by Krasznahorkay et al., (Phys. Rev. Lett. 116, 042501 (2016)), which may indicate a new particle called X17 in the literature. In order to get a reliable, and independent result, we used a different type of electron-positron pair spectrometer which have a more simple acceptance/efficiency as a function of the correlation angle, but the other conditions of the experiment were very similar to the published ones. We could confirm the presence of the anomaly measured at the Ex=18.15 MeV resonance, and also confirm their absence at the Ex=17.6 MeV resonance, and at Ep= 800 keV off resonance energies.

Chromophobe renal cell carcinoma (chRCC) and oncocytoma (RO) are renal tumor types originating from alpha intercalated cells of the collecting ducts of the kidney. Both tumor types have similar gross histological morphology and increased mitochondria, which leads to difficulties differentiating between these tumors, especially with core biopsy samples. This study aims to apply a machine learning approach to develop a molecular classifier based on transcriptomics data. Here we generated a meta-data set containing 62 chRCC and 45 RO gene expression arrays. Arrays were subjected to quality control steps, and genes were selected based on differential expression and ROC analysis. The final gene list was evaluated with UMAP based dimension reduction followed by density-based clustering with 95.5% accuracy. Molecular profiling by KEGG pathway analysis identified enrichment of fatty acid oxidation pathway in RO. We finally identified and validated the 30-gene signature, with an accuracy of 94.4% to distinguish chRCC from RO on UMAP analysis. Our results show that chRCC and RO have a distinct gene signature that can differentiate these tumors and complement histology for routine diagnosis of these two tumors.

Private Set Intersection Cardinality(PSI-CA) is a cryptographic method in secure multi-party computation that allows entities to identify cardinality of the intersection without revealing their private data.Traditional approaches assume similar-sized datasets and equal computational power, overlooking practical imbalances.In real-world applications, dataset sizes and computational capacities often vary, particularly in the Internet of Things and mobile scenarios where device limitations restrict computational types. Traditional PSI-CA protocols are inefficient here, as computational and communication complexities correlate with the size of larger datasets. Thus, adapting PSI-CA protocols to these imbalances is crucial.This paper explores unbalanced scenarios where one party (the receiver) has a relatively small dataset and limited computational power, while the other party (the sender) has a large amount of data and strong computational capabilities.This paper, based on the concept of commutative encryption, introduces Cuckoo filter, cloud computing technology, homomorphic encryption, among other technologies, to construct three novel solutions for unbalanced Private Set Intersection Cardinality (PSI-CA): an unbalanced PSI-CA protocol based on Cuckoo filter, an unbalanced PSI-CA protocol based on single cloud assistance, and an unbalanced PSI-CA protocol based on dual cloud assistance. Depending on performance and security requirements, different protocols can be employed for various applications.

Dry eye disease (DED) most commonly caused by evaporative subtypes and mainly induced by meibomian gland dysfunction (MGD). Intense pulsed light (IPL) combined with meibomian gland expression (MGX) is noninvasive treatment for improvement of ocular discomfort symptoms and MGD. In this prospective study between November 2020 and May 2022, the patients met the criteria of both ocular surface disease index (OSDI) ≥13 scores and standardized patient evaluation of eye dryness (SPEED)≥ 8 scores were enrolled in Kaohsiung Veteran General Hospital. Three separate treatment sessions of IPL therapy combined with MGX administered to the lower lids with an interval of 28 days. Further tear film assessment included lipid layer thickness (LLT), tear meniscus height (TMH), non-invasive tear break-up time (NIBUT), meibomian gland loss (MGL) either beforeor after 1st and 3rd IPL therapy combined with MGX. Besides, lissamine green staining and pain scores were also recorded. We totally enrolled 37 patients of 74 eyes. Men accounted for 18.92% (7/37). The mean age was 54.51 ± 11.72 years. The mean OSDI scores were 58.12 ± 22, while the SPEED scores were 17.03 ± 5.98. The mean Schirmer’s test was 3.66 ± 2.43 mm. After three sessions IPL treatment with MGX, the OSDI, SPEED, LLT, TMH, MGL, MGXS and pain scores were significantly improved. For the MGX scores (MGXS) ≤20 group, MGL and lissamine green scores showed significant improvements. For the MGXS >20 group, TMH and dry spot rate revealed statistically improvement. Noninvasive IPL therapy with MGX statistically improved not only dry eye symptoms but also tear film assessments.

The aim of this study was to investigate the physicochemical characterization and biological activities of chitosan (CH) based composite films with the incorporation of chestnut flower essential oil (CFEO). The composite films were prepared by casting method and characterized in terms of structural, morphological and mechanical properties via FT-IR, XRD, UV, SEM and TGA. The results proved the significantly increased water vapor permeability (WVP), heat resistance, antibacterial and antioxidant capabilities of CH-CFEO films. The incorporation of CH and CFEO enhanced the UV blocking, which made the film shield almost all UV light. Films with the tensile strength of 6.37 ± 0.41 MPa and elongation at break of 22.57 ± 0.35% were got with 6 mg mL-1 CFEO. Subsequently, the fruit preservation experiments also confirmed that the composite films could effectively extend the shelf life of bananas through their excellent water vapor and oxygen barrier. These desirable performances enable our newly developed composite films to be a remarkable packaging material to solve the fresh fruit preservation dilemma.

Background. To describe the characteristics of anterior mediastinal masses on conventional magnetic resonance imaging (MRI) and to assess the role of the Apparent Diffusion Coefficient (ADC) value in distinguishing benign from malignant mediastinal lesions. Methods. We conducted a retrospective cross-sectional study on 55 patients with anterior mediastinal mass who performed MRI before treatment. Biopsy and histopathological assessments were done after that. A radiologist evaluates the changes of signal intensity on these sequences: T1- weighted VIBE DIXON pre and post-contrast with Gadolinium, T2 HASTE, T2 TIRM, DWI/ADC, to determine the size, margin of the lesion, the presence of fat, cystic in it. ADCs values were calculated from the ADC maps which were constructed from b = 0 and b = 2000 Results. The study was composed of 55 patients, with 5 benign lesions and 50 malignant lesions. The ADCmean, ADCmedian, ADC10, and ADC90 in the histogram-based approach and hot-spot-ROI-based mean ADC for the malignant lesions was significantly lower than those found in benign lesions (P-value <0.05). The hot-spot-ROI-based mean ADC had the highest value in differentiation between benign and malignant mediastinal lesions, between group A (benign lesions, thymoma A, AB, B1) and group B (thymoma B2, B3 and other malignant lesions). The cut-off point of the ADC value differentiating malignant from benign mediastinal lesions was 1,17x10-3mm2/s with sensitivity of 80%, and specificity of 80%. The cut off point of the ADC value differentiating group A from group B was 0.99 x10-3mm2/s with sensitivity of 78,4%, and specificity of 88.9%. The cut-off point of the ADC value differentiating lymphoma from other malignant lesions was 0,91 x10-3mm2/s with sensitivity of 100%, and specificity of 60.5%. Conclusion. Diffusion-weighted MRI and measurement of ADC value in histogram-based approach and hot-spot-ROI-based mean ADC are very helpful in the differentiation between benign and malignant anterior mediastinal lesions.

The properties of the annual, semiannual and triennial oscillations (AO, SAO and TO) in the middle atmosphere have been investigated using the TIMED/SABER temperature data. The Lomb-Scargle and wavelet spectra were used to determine the dominant oscillations in the background temperature field. The AO is prominent at the mid-latitudes. The AO amplitudes present an asymmetry between the two Hemispheres, being larger in the mesosphere than in the stratosphere. The SAO dominates the tropical regions, with three amplitude maxima at altitudes of 45, 75, and 85 km. The SAOs in the upper mesosphere (75 km) are out of phase with those in the mesopause (85 km) in the tropical regions, which can generate an enhancement of 11 K at each equinox, contributing to the lower mesospheric inversion layer. The TO is significant in the tropical region, with amplitude being maximum at 35, 45 and 85 km. Result shows that there may be potential interaction by the TO with SAO at 85km at the equator. The relation between ENSO and TO has also been discussed. The ENSO signal may modulate the amplitude of the TO, mainly in the lower stratosphere. The real origin of the TO may lie in the wave-mean-flow interaction.

To characterize the fecal microbiota of lactating Bactrian camels, this study employed a random selection of camels, assigning them to three groups: the first parity group, the third parity group, and the fifth parity group. The fecal microbial community of lactating camels was assessed using 16S rRNA amplicon sequencing, and the resulting library was sequenced on an Illumina NovaSeq platform. The first parity group was characterized by Verrucomicrobiaceae as a distinctive bi-omarker, whereas Clostridiaceae exhibited a similar role to the third parity group. In terms of functional analysis, the relative abundance of the Steroid biosynthesis pathway was highest in the first parity group, whereas the fifth parity group demonstrated a higher relative abundance of the Tuberculosis pathway compared to the other groups. The first parity group exhibited the greatest presence of seven types of enzymes, whereas the fifth parity group displayed the highest levels of two specific enzymes. Additionally, a positive association was observed between the relative abundance of the Steroid biosynthesis pathway and Verrucomicrobiaceae. Furthermore, the relative abundance of the Tuberculosis pathway displayed positive correlations with 14 enzymes. In conclusion, this study revealed that different parity was associated with distinct fecal microbial ecologies in lactating Bactrian camels.

Distributed/semi-distributed models are considered to be sensitive to the spatial resolution of the data input. In this paper, we take a small catchment in high urbanized Yangtze River Delta, Qinhuai catchment as study area, to analyze the impact of spatial resolution of precipitation and the potential evapotranspiration (PET) on the long-term runoff and flood runoff process. The data source includes the TRMM precipitation data, FEWS download PET data, and the interpolated metrological station data. GIS/RS technique was used to collect and pre-process the geographical, precipitation and PET series, which were then served as the input of CREST (Coupled Routing and Excess Storage) model to simulate the runoff process. The results clearly showed that, the CREST model is applicable to the Qinhuai catchment; the spatial resolution of precipitation had strong influence on the modelled runoff results and the metrological precipitation data cannot be substituted by the TRMM data in small catchment; the CREST model was not sensitive to the spatial resolution of the PET data, while the estimation fourmula of the PET data was correlated with the model quality. This paper focused on the small urbanized catchment, suggesting the influential explanatory variables for the model performance, and providing reliable reference for the study in similar area.

In April 2019, a team of Keio University and Bucknell University students was assembled to participate in Ericsson Innovation Awards with a novel concept for generating renewable energy. This conceptual system consists of a vertical axis wind turbine, a crossflow marine hydrokinetic turbine, a floating platform integrated with a quadcopter system, and three to four temporary mooring lines with ship-type anchors. The proposed designed aims to offer solutions to two current problems of floating offshore wind energy: high construction cost of floating platforms and difficulties in maintenance of mooring lines. The combination of two vertical-axis turbines into a single floating platform would enable the system, namely ESwift, to extract energy from both wind and current resources. Additionally, due to the utilization of vertical axis turbines, the center of gravity of the proposed concept is significantly lower with respect to water level, compared to that of existing floating horizontal axis wind turbines, which would potentially reduce the floater's size and construction cost. Lastly, the integrated quadcopter mechanism would assist the floater in terms of stability and mobility, and enables an array of ESwifts to automatically rearrange for maximal energy generation. The authors hope that readers would find the idea described in this open access letter worth pursuing and would further develop and commercialize the ESwift concept.

Introduction: The goals of this retrospective cohort study of 129,443 persons admitted to Calgary acute care hospitals 2013-2021 were to ascertain correlations of “potentially inappropriate medi-cations” (PIMs), “potential prescribing omissions” (PPOs) and other risk factors with readmissions and mortality. Methods: Processing and analysis codes were built in Oracle Database 19c (PL/SQL), R and Excel. Results: The percentage dying during their hospital stay rose from 3.03% during the first to 7.2% during the 6th admission. The percentage dying within 6 months of discharge rose from 9.4% after the first to 24.9 after the sixth admission. Odds ratios (adjusted for age, gender and comorbidities) for readmission were the post-admission number of medications (1.16; 1.12-1.12), STOPP PIMs (1.16; 1.15-1.16); AGS Beers PIMs (1.11; 1.11-1.11) and START omissions not corrected with a prescription (1.39 (1.35-1.42). Odds ratios for mortality were post-admission number of medications (1.04; 1.04-1.05), STOPP PIMs (0.99; 0.96-1.00); AGS Beers PIMs (1.08; 1.07-1.08) and START omissions not corrected with a prescription (1.56 (1.50-1.63). START omissions corrected with a prescription correlated with a dramatic reduction in mortality (0.51; 0.49-0.53). Odds ratios for readmissions for the second through 39th admission were consistently higher if START PPOs were not corrected for the second admission (1.41; 1.36-1.46), third (1.41;1.35-1.48); fourth 1.35;1.28-1.44); fifth 1.38; 1.28-1.49); sixth (1.47;1.34-1.62) and 7th through 39th admission (1.23; 1.14-1.34). For all admissions when a pre-scription was given to correct START PPOs ORs for mortality within six months of discharge were dramatically improved (0.51; 0.49-0.53). This was also true for the second (0.52; 0.50-0.55; fourth (0.56; 0.52-0.61; fifth (0.63; 0.57-0.68); sixth (0.68; 0.61-0.76); and 7th through 39th admissions (0.71; 0.65-0.78). Conclusions: PPOs should be corrected by prescriptions and teams of family physicians, pharmacists and nurses should focus on patients’ understanding of their illnesses, medications and ability for self-care.

Neuroinflammatory responses are implicated in the pathogenesis of neurodegenerative diseases. In neurodegenerative diseases, neuroinflammatory reactions to neuronal injury are modulated by microglial cells, which are vital innate immune cells in the central nervous system. Activated microglial cells release proinflammatory cytokines, mediators, and neurotoxic factors that induce fatal neuronal injury. The present study investigated the anti-neuroinflammatory effects of cudratricusxanthone L (1), which was isolated from Cudrania tricuspidata. This compound reduced the levels of lipopolysaccharide-stimulated inflammatory mediators and cytokines, including nitric oxide, prostaglandin E2, interleukin (IL)-1β, tumor necrosis factor-α, IL-6, and IL-12. These effects suggested that cudratricusxanthone L (1) suppressed the nuclear factor-kappa B (NF-κB) signaling pathway. Specifically, cudratricusxanthone L (1) also attenuated the phosphorylation of Jun kinase and inhibited p38 mitogen-activated protein kinase (MAPK) signaling in BV2 and rat primary microglial cells. These results indicated that cudratricusxanthone L (1) effectively repressed neuroinflammatory processes in BV2 and rat primary microglial cells by inhibiting NF-κB and the MAPK signaling pathway.

The Soil and Water Assessment Tool (SWAT) is one of the most widely used hydrologic models. SWAT has been undergoing constant changes since its development. However, compartment review and testing of SWAT are comparably limited, especially the flood routing functions. In this study, the daily flood routing subroutines of different SWAT versions were reviewed and tested using a well observed segment of the Weser river located in Germany. Results show several problems with the flood routing subroutines of SWAT. The variable storage subroutine of SWAT (revision 664) does not transform the flood wave. Unphysical results could be obtained with the variable storage routing of SWAT (revision 528). The Muskingum subroutine of SWAT (revisions 664 and 528) overestimates channel evaporation (resulting in a bias of 14\% to 19% in streamflow) and underestimates transmission losses. Simulated results show that the timing and shape of the flood wave could be improved with a corrected Muskingum subroutine. Based on the results of this study, we suggest the SWAT user community to review their existing SWAT models to see how the aforementioned issues will affect their methods, findings and conclusions.

Current instrumental technology in evaluating performance of skin care creams is still rather limited and there are no industrial standard testing equipment, method and performance specifications for it. In this paper, we report our attempt in using an instrument called PhabrOmeter for this purpose. PhabrOmeter is a commercialized instrument for sensory performance evaluation of textiles, leather, paper and nonwoven and has been designated by American Association of Textile Chemists and Colorists (AATCC) as a standard test method for textiles, AATCC TM 202 in 2013. By adopting artificial skin samples treated with skin care creams, we have developed a procedure to apply this instrument for evaluation of skin care creams from sample preparation, measurement to data analysis and interpretation. The results using commercial skin care creams to demonstrate the feasibility and advantages of this instrument are provided.

In this paper, bikeshare data in Chicago on weather-friendly days in 2019 and 2020 were analyzed to investigate the variation in bikeshare travel before and during the pandemic. Our results show that bikeshare trips during the pandemic were much longer than prior to the pandemic. The increased rate of bikeshare usage was unbalanced spatially and varied significantly for different user types. Specifically, bikeshare was used significantly more by casual users than by subscribers, and the increase occurred much more in the outskirts of the city. The increase in bikeshare travel was associated with a reduction in travel by ride-hailing and public transit, especially in the urban periphery. The correlation of bikeshare use with the bus system was much less significant than with the rail system. Bike lanes/facilities had a mixed effect on bikeshare travel. Weekend bike trips increased in areas where there was no bike lane. Weekday trips, on the contrary, increased in the vicinity of bike greenways.

SARS-CoV-2 (2019-nCoV), a novel coronavirus, caused the pneumonia outbreak in China and continue to expand. The host receptor for 2019-nCoV Angiotensin-converting enzyme 2 (ACE2), is the same as the host receptor for SARS-CoV. Targeting ACE2 holds the promise for preventing and inhibiting 2019-nCoV infection. Chinese Medicine herbs could be a valuable pool for identifying active compounds for treating infection of 2019-nCoV. In this study, we summarize several active compounds, including baicalin, Scutellarin, Hesperetin, Nicotianamine and glycyrrhizin that could have potential anti-2019-nCoV effects. We conduct molecular docking to predict their capacity for binding ACE2, which may prevent the 2019-nCoV infection. We propose that these selected compounds worth further investigation for preventing 2019-nCoV.

In the construction of shield crossing existing mined tunnel without load, it is imperative to develop corresponding design standards that reflect actual engineering force characteristics to ensure the successful completion of tunnel construction. This research uses The MIDAS-GTS finite element software to facilitate the creation of a numerical model of the shield structure for an air-push-over mine tunnel project in Changsha, China, investigating the stress field’s evolution during shield construction, and calculating the maximum positive and negative bending moments and maximum axial forces for different structures and other force states under various construction conditions. This study's findings informed the design and construction optimisation of the shield tunnelling empty-push method. The outcomes of this numerical simulation led to several key findings: (1) The soil density exerted a significantly greater impact on the internal forces of the initial support structure than both the tunnel depth and soil Poisson's ratio. Additionally, a sudden shift in internal forces occurred within the 300-350 mm range when the lining thickness was altered. (2) Factors such as the tunnel depth, soil density, soil Poisson's ratio μ, and lining thickness have a similarly influenced internal forces of the segment and the initial support. Notably, the backfill layer thickness significantly affected the segment’s maximum axial force causing an abrupt change of approximately 300 mm. (3) Under the shield machine equipment’s weight constraint, it is essential to control the guide rail’s thickness, to prevent it from becoming overly large.

A study was carried out in a Waste Sorting Plant (WSP) located in France and treating dry recyclable household waste (DRHW) as well as dry recyclable commercial and industrial waste (DRCIW). The aim was to investigate the exposure to bioaerosol and dust. The aim of the study was to assess the extent to which the measurement of concentration, species composition and particle size distribution can contribute to a better assessment of the biological risks associated with exposure. Both stationary and personal bioaerosol and dust samples were collect in the (WSP). The results confirm that waste and waste sorting activities are sources of airborne fungi. Indeed, ambient concentrations ranged from 7.3×103 to 8.5×105 CFU/m3 for culturable moulds and up to up to 4 mg/m3 for dust. Personal exposure to inhalable dust was found up to 3 mg/m3 for dust and ranged from 8.6×103 to 1.5×106 CFU/m3 for fungi. Airborne fungal communities were found to be dominated by the Penicillium genera in both bioaerosols and settled dust samples, followed by the Aspergillus, Cladosporium, Wallemia, Mucor, and Rhizopus genera. Fungi were carried by particles of aerodynamic diameters mainly between around 2.0 and 10.0 µm. The findings dealing with size distribution and biodiversity of bioaerosols suggest that employees are exposed to complex bioaerosols during their work and helps to make a finer diagnosis of the risks involved, which is often difficult in the absence of any OEL for bioaerosols in general.

The robust fusion estimation problem of a multi-sensor system with communication constraints, random packet drops, d-step state delays, and deterministic control inputs is investigated. The state augmentation method is used to transform the time delay system into a non-time delay system, and then a robust fusion estimation algorithm based on sensitivity penalty is proposed and the pseudo-cross-covariance matrix is updated. An event-triggered robust fusion estimator with state delay and deterministic control inputs is considered to make the model closer to reality while effectively reducing network congestion and lowering communication costs. Conditions are given to ensure that the estimation errors of the robust fusion estimator are uniform boundedness. Two sets of numerical simulations are provided to illustrate the effectiveness of the derived fusion estimator.

We estimated the risk of blood clots after COVID-19 vaccination accounting for the roles of vaccination in reducing the infection rate, and indirectly lowering the risk of blood clots caused by infection. A self-controlled case series method was used to examine the association between blood clots and COVID-19 vaccination. To deal with the bias due to under-reported infection among non-hospitalized subjects, a case-control study was used to compare the risk of blood clots in infected subjects to control subjects who were hospitalized due to physical injury. We found increased risks of blood clots after vaccination (incidence rate ratio is 1.13, 95% confidence interval (CI): [1.03, 1.24] after the first dose and 1.23, 95% CI: [1.13,1.34] after the second dose). Furthermore, vaccination attenuated the increased risk of blood clots associated with infection (odds ratio (OR) = 2.16, 95% CI: [1.93, 2.42] in unvaccinated versus OR=1.46, 95% CI: [1.25, 1.70] in vaccinated). A causal model was used to explain and weigh up possible risk factors for blood clots after COVID-19 vaccination. After accounting for vaccine efficacy against infection and the protection against infection-associated blood clots, receiving the COVID-19 vaccines decreases the risk of blood clots, especially during high infection rate period.

Recently, attention mechanisms have developed into an important tool for performance improvement of deep neural networks. In computer vision, attention mechanisms are generally divided into two main branches: spatial and channel attention. Both attention categories have their own advantages. The fusion of both attentions achieves higher performance, on the cost of the computational load. This paper introduces an innovative and lighter n-shifted sigmoid channel and spatial attention (CSA) module to reduce the computational cost and to improve the 3D scene relevant features selection. To validate the proposed attention module, 3D scene object detection in the deep Hough voting point sets is considered as the testing application. The proposed attention module with its piecewise n-shifted sigmoid activation function improves the network’s learning and generalization capacity which effectively predict bounding box parameters directly from 3D scenes and detect objects more accurately. This advantage is achieved by selectively attending to more relevant features of the input data. When used in the deep Hough voting point sets, the proposed attention module outperforms state-of-the-art 3D detection methods on the sizable SUNRGBD dataset. Experiments conducted showed an increase of 12.02 mean accuracy precision (mAP) when compared to the celebrated VoteNet (without attention). It also got 9.92 mAP higher compared to the MLVCNet, and 10.32 mAP higher than the Point Transformer. The proposed model not only decreases the sigmoid vanishing gradient problem but also brings out valuable features by fusing channel-wise and spatial information while improving accuracy results in 3D object detection.

Polymethyl methacrylate (PMMA) polymer is widely used in various fields today. In order to thoroughly reveal the structural impact performance of PMMA materials, this paper is based on the comprehensive Johnson-Cook constitutive model and damage failure model, and accurately confirm the J-C constitutive and damage failure model parameters of PMMA through material test data, The dynamic process of steel bullet impacting PMMA plate structure is analyzed by finite element software ABAQUS. The calculation results show that the numerical simulation results in this paper are in good agreement with the experimental test data. Therefore, the feasibility and accuracy of the impact analysis of PMMA structures based on J-C constitutive and damage failure models in this paper are studied. Finally, based on the J-C constitutive model and damage failure model, the variation of the residual velocity of the bullet with the PMMA plate thickness is analyzed in depth, that is, the results show that the residual velocity of the bullet has a certain linear relationship with the plate thickness.

In order to improve the performance of soft plantation wood, an environmentally friendly inorganic-organic hybrid wood modifier was developed. First, using urea and melamine as crosslinking agents, the waterborne glucose silicone resin (MUG) was prepared with glucose under the catalysis of inorganic acid and metal ions. Then MUG resin was diluted to 10% and 20% mass fraction, and compounded with sodium silicate (S) of 20% and 10% mass fraction, so the inorganic-organic hybrid G10S20 and G20S10 wood modifier were obtained respectively. Then plantation poplar wood (Populus tomentosa) were impregnated and modified with them. Their physical and mechanical properties were tested and compared with those of the wood treated with S of 20% mass fraction (S20). Infrared analysis showed that amino resin characteristic structure (CO-NH-) existed in MUG resin. The resin has good permeability. Compared with S20 modified wood, the degree of shrinkage of G10S20 or G20S10 modified wood is reduced, their moisture absorption is reduced, and their dimensional stability is improved. Waterborne glucose silicone modifier can effectively improve the wood density, modulus of elasticity, modulus of rapture and compression strength. SEM analysis showed that the cell wall of G20S10 modified wood was significantly thicker than the untreated wood, and there were columnar and granular solid substances attached in some cell cavities, ducts and corners, etc. EDX showed that the number of Si elements on the cell wall was significantly increased compared with the control, indicating that the modifier effectively entered the wood cell wall. The waterborne glucose silicone resin can greatly improve the physical and mechanical properties of wood through organic-inorganic hybridization. It is a green, non-formaldehyde, eco-friendly, low cost, compound wood modifier with broad application prospects.

Land use/land cover (LULC) and climate changes are two main factors directly affecting hydrologic conditions. However, very few studies in Vietnam have investigated changes in hydrological process under the impact of climate and land use changes on a basin scale. The objective of this study is to assess the individual and combined impacts of land use and climate changes on hydrological processes for the Nam Rom river basin, Northwestern Viet Nam using Remote Sensing (RS) and Soil and Water Assessment Tools (SWAT) model. SWAT model was used for hydrological process simulation. Results indicated that SWAT proved to be a powerful tool in simulating the impacts of land use and climate change on catchment hydrology. The change in historical land use between 1992 and 2015 strongly contributed to increasing hydrological processes (ET, percolation, ground water, and water yield), whereas, climate change led to significant decrease of all hydrological components. The combination of land use and climate changes significantly reduced surface runoff (-16.9%), ground water (-5.7%), water yield (-9.2%), and sediment load (-4.9%). Overall climatic changes had more significant effect on hydrological components than land use changes in the Nam Rom river basin during the 1992–2015. Under impacts of projected land use and climate change scenarios in 2030 on hydrological process of the upper Nam Rom river basin indicate that ET and surface flow are more sensitive to the changes in land use and climate in the future. In conclusion, the findings of this study will basic knowledge of the effects of climate and land-use changes on the hydrology for future development of integrated land use and water management practices in Nam Rom river basin.

Objective: This study aimed to demonstrate the availability of portable devices for nasal FeNO measurement, which could replace exhaled NO measurement based on the continuous aspiration of multiple flow measurement systems. Methods: A descriptive cross-sectional study. The healthy subjects without rhinosinusis disorders (control group) and those with diagnosed allergic rhinitis (AR group) were enrolled in the study. They underwent nasal and bronchial FeNO measurements by both fixed flow NObreath® connected to nasal mask and multiple flows HypAir FeNO®. Results: A total of 153 people were recruited including 63 healthy subjects and 90 subjects with AR. There were no statistically significant differences in anthropometric characteristics between the two groups (P > 0.05). There were a significant increase in FeNO values in the AR group compared to the control group; concentrations of nasal and bronchial FeNO mearsured by NObreath® were 76.0 ± 50.7 ppb (vs 36.0 ± 28.1 ppb, P < 0.01) and 32.3 ± 15.4 ppb (vs 9.2 ± 5.6 ppb, P < 0.001), and those mearsured by NObreath® Hypair FeNO® were 1796.9 ± 523.3 ppb (vs 400.2 ± 123.1 ppb, P < 0.001) and 37.3 ± 23.0 ppb (vs 17.4 ± 18.3 ppb, P < 0.01). A weak correlation between the values measured by NObreath® and Hypair FeNO® devices was observed (r = 0.023 and r = 0.089, respectively; p < 0.05). Conclusions: The handheld NObreath® device is effective in measuring FeNO concentrations in both normal subjects and AR patients. The advantages in price and size, creating a compact, low-cost device that is convenient for use and research.

Artistic image completion is fundamental for the preservation and restoration of invaluable art paintings and it has experienced significant progress through the implementation of deep learning methodologies. Despite these advancements, challenges persist, even with sophisticated approaches like Generative Adversarial Networks (GANs), particularly in achieving optimal results for high-resolution paintings. Small-scale texture synthesis and the inference of missing information from distant contexts present persistent issues, leading to distortions in lines and unnatural colors, especially in art paintings with complicated structures and textures. Concurrently, patch-based image synthesis has evolved by incorporating global optimization on the image pyramid to enhance structural coherence and details. However, methods relying on gradient-based synthesis encounter obstacles related to directionality, inconsistency, and the heavy computational burdens associated with solving the Poisson equation in non-integrable gradient fields. This paper introduces a groundbreaking approach, integrating Weighted Similarity-Confidence Laplacian Synthesis, to comprehensively address these challenges and advance the field of artistic image completion. This proposal addresses challenges not only in high-resolution artistic image completion but also makes a significant contribution to the broader field of patch-based synthesis by utilizing the Laplacian pyramid for enhanced edge-aware correspondence search. Experimental result confirms the effectiveness of our approach, offering promising outcomes for the preservation and restoration of art paintings with complicated details and irregular missing regions.

Currently, major e-commerce platforms are competing to improve their return services, while merchants are experiencing abuse of return policies by consumers. The effectiveness of lenient return policies is examined in helping e-commerce platforms gain a competitive advantage in this paper. A dual oligopoly model is established consisting of one platform that offers a lenient return policy with services like Instant Refunds and the other does not provide similar ones. The scenario where consumers are single-homing, while merchants are partial multi-homing is analyzed. In the scenario, many factors are examined to assess their impact on the scale of the bilateral user base and the profits for both platforms, including the proportion of consumer abusing return policies, the benefits derived from abusive returns, penalties. and costs. The findings indicate that: (1) With an increasing proportion of consumer abusing return policies, the multi-homing merchants on platform that offer lenient return service will choose to be exclusively affiliated with rival platform, accounting for a decrease in consumer base and lower platform profits compared to competitors. (2) Platform that provides lenient return policies should restrict the amount of returns to mitigate the impact of consumer abusing return policies on its profits. (3) When the proportion of consumers abusing return policies is relatively low, platform should choose moderate levels of penalty to increase the scale of both sides of users without excessively increasing costs. However. when this proportion is high, platforms should cease to offer lenient return and refund services.

Beyond semantic segmentation,3D instance segmentation(a process to delineate objects of interest and also classifying the objects into a set of categories) is gaining more and more interest among researchers since numerous computer vision applications need accurate segmentation processes(autonomous driving, indoor navigation, and even virtual or augmented reality systems…) This paper gives an overview and a technical comparison of the existing deep learning architectures in handling unstructured Euclidean data for the rapidly developing 3D instance segmentation. First, the authors divide the 3D point clouds based instance segmentation techniques into two major categories which are proposal based methods and proposal free methods. Then, they also introduce and compare the most used datasets with regard to 3D instance segmentation. Furthermore, they compare and analyze these techniques performance (speed, accuracy, response to noise…). Finally, this paper provides a review of the possible future directions of deep learning for 3D sensor-based information and provides insight into the most promising areas for prospective research.

Biomimicry in additive manufacturing often refers to topology optimization and the use of lattice structures, due to the organic shape of the topology-optimized designs, and the lattices often looking similar to many light-weight structures found in nature such as trabecular bone, wood, sponges, coral, to name a few. Real biomimetic design however involves the use of design principles taken in some way from natural systems. In this work we use a methodology whereby high resolution 3D analysis of a natural material with desirable properties is “reverse-engineered” and the design tested for the purpose. This allows more accurate replication of the desired properties, and adaption of the design parameters to the material used for production (which usually differs from the biological material). One such example is the impact-protective natural design of the glyptodont body armour. In this paper we report on the production of body armour models in metal (Ti4Al4V) and analyze the resulting mechanical properties, assessing their potential for impact protective applications. This is the first biomimetic study using metal additive manufacturing to date.

Precipitates are the primary source of strength for the Al-Mg-Si alloy. Aluminum alloy in the peak-aged state mainly contain β'' and β' precipitates. In the past, most of the literature only considered the strengthening effect of β''. Here we develop a single crystal intensity model including both precipitate enhancement effects for the first time. This model was subsequently implemented into a crystal plastic finite element method to model the uniaxial tensile process of a polycrystalline aggregate model of Al-Mg-Si alloy. The simulation results for uniaxial stretching are in good agreement with the experimental results, confirming that the constitutive parameters used for the single crystal strength model with two precipitates are based on realistic physical implications. Furthermore, by comparing the uniaxial tensile simulation results of a peak-aged alloy considering the actual precipitated phase composition of the alloy with those assuming that the precipitated phase is only the β'' phase, the predicted tensile strength of the former is around 5.65% lower than that of the latter, suggesting that the two kinds of precipitation should be considered separately when simulating the mechanical response of Al-Mg-Si alloy. It is highly expected that the present simulation strategy is not limited to the Al-Mg-Si alloys, and it can be equally applied to the other age-enhanced alloys.

Water resource is considered as a significant factor in development of regional environment and society. Water consumption prediction can provide important decision basis for the regional water supply scheduling optimisations. According to the periodicity and randomness nature of the daily water consumption data, a Markov modified autoregressive moving average (ARIMA) model is proposed in this study. The proposed model, combined with the Markov chain, can correct the prediction error, reduce the continuous superposition of prediction error, and improve the prediction accuracy of future daily water consumption data. The daily water consumption data of different monitoring points are used to verify the effectiveness of the model, and the future water consumption is predicted, in the study area. The results show that the proposed algorithm can effectively reduce the prediction error compared to the ARIMA.