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Understanding soil phosphorus (P) distribution and its key drivers is fundamental for sustainable P management. In this study, a 21-year fertilization experiment on black soil was carried out, setting up five fertilization treatments: unfertilized control (CK), nitrogen and potassium (NK), nitrogen, P and potassium (NPK), NPK plus straw (NPKS), and NPK plus manure (NPKM). The distribution and effecting factors of P pools within soil aggregates were investigated. Compared to CK, the NK and NPK treatments decreased calcium-associated P concentration in all aggregate fractions. Meanwhile, the NPK treatment significantly increased the organic P extracted from NaOH in unaggregated particles (<0.053 mm). This was mainly due to the reduction in soil pH. The NPKS and NPKM treatments increased almost all P forms in aggregates, especially Ca-P. For the NPKM treatment, inorganic P extracted from resin, NaHCO3, and NaOH increased as aggregate size increased. This was mainly because straw or manure addition promoted soil organic carbon (SOC) storage in aggregates, creating more sorption sites via association with amorphous metallic minerals, and, thus, facilitating P accumulation. In conclusion, decreasing soil pH by chemical fertilizers is an effective strategy for mobilizing soil P, whereas increasing SOC by straw or manure facilitates P accumulation. [ABSTRACT FROM AUTHOR]

Controlled-release urea (CRU) fertilizers are widely used in agricultural production to reduce conventional nitrogen (N) fertilization-induced agricultural greenhouse gas emissions (GHGs) and improve N use efficiency (NUE). However, the long-term effects of different CRU fertilizers on GHGs and crop yields in vegetable fields remain relatively unexplored. This study investigated the variations in GHG emissions at four growth stages of lettuce in the spring and autumn seasons based on a five-year field experiment in the North China Plain. Four treatments were setup: CK (without N application), U (conventional urea—N application), ON (20% reduction in urea—N application), CRU (20% reduction in polyurethane-coated urea without topdressing), and DCRU (20% reduction in polyurethane-coated urea containing dicyandiamide [DCD] without topdressing). The results show that N application treatments significantly increased the GHG emissions and the lettuce yield and net yield, and DCRU exhibited the lowest N2O and CO2 emissions, the highest lettuce yield and net yield, and the highest lettuce N content of the N application treatments. When compared to U, the N2O emission peak under CRU and DCRU treatments was notably decreased and delayed, and their average N2O emission fluxes were significantly reduced by 10.20–20.72% and 17.51–29.35%, respectively, leading to a significant reduction in mean cumulative N2O emissions during the 2017–2021 period. When compared to U, the CO2 fluxes of DCRU significantly decreased by 8.0–16.54% in the seedling period, and mean cumulative CO2 emission decreased by 9.28%. Moreover, compared to U, the global warming potential (GWP) and greenhouse gas intensity (GHGI) of the DCRU treatment was significantly alleviated by 9.02–17.13% and 16.68–20.36%, respectively. Compared to U, the N content of lettuce under DCRU was significantly increased by 6.48–17.25%, and the lettuce net yield was also significantly increased by 5.41–7.71%. These observations indicated that the simple and efficient N management strategy to strike a balance between enhancing lettuce yields and reduce GHG emissions in open-field lettuce fields could be obtained by applying controlled-release urea containing DCD without topdressing. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) frameworks are essential for development since they offer pre-built tools and libraries that speed up and simplify the production of AI models, leveraging symmetry to save time and effort. They guarantee effective computing by modifying code for particular hardware, facilitating quicker testing and deployment. The identification of a suitable and optimal AI framework for development is a multi-criteria decision-making (MCDM) dilemma, where the considered AI frameworks for development are evaluated by considering various criteria and these criteria may have dual aspects (positive and negative). Thus, in this manuscript, we diagnosed a technique of MCDM within the bipolar fuzzy set (BFS) for identification and selection of optimal AI framework for development. In this regard, we diagnosed probability aggregation operators (AOs) within BFS, such as probability bipolar fuzzy weighted averaging (P-BFWA), probability bipolar fuzzy ordered weighted averaging (P-BFOWA), immediate probability bipolar fuzzy ordered weighted averaging (IP-BFOWA), probability bipolar fuzzy weighted geometric (P-BFWG), probability bipolar fuzzy ordered weighted geometric (P-BFOWH), and immediate probability bipolar fuzzy ordered weighted geometric (IP-BFOWG) operators. The diagnosed technique would be based on these invented probably AOs. Afterward, in this manuscript, we took a case study and obtained the optimal AI framework for development by employing the diagnosed technique of MCDM. We also investigated the comparison of the devised theory with certain prevailing theories to reveal the dominance and significance of the devised theory. [ABSTRACT FROM AUTHOR]

Phosphorus (P) leaching from excessive P application is the primary pathway of P losses in agricultural soils. Different P fertilizer practices have mixed effects on P leaching. We conducted a meta-analysis of the relevant literature regarding the response of crop yields, soil-available P (AP), and total P (TP) leaching to reduced P input (RP) and an inorganic-organic combination fertilizer (NPKM) for different agricultural land-use types. Compared to conventional P application (CP), RP (10~90% reduction) did not reduce crop yields in vegetable fields (experiments were 1~4 years) but significantly reduced cereal yields by 4.57%. Compared to chemical fertilizer (NPK), NPKM significantly increased cereal yields by 12.73%. Compared to CP, RP significantly reduced AP at 0~60 cm in vegetable and cereal fields. The greatest reduction occurred at 20~40 cm in vegetable fields (40.29%) and 0~20 cm in cereal fields (34.45%). Compared to NPK, NPKM significantly increased the AP at 0~60 cm in vegetable fields, with the greatest increase (52.44%) at 20~40 cm. The AP at 0~40 cm in cereal fields significantly increased under the NPKM treatment, with the greatest increase at 0~20 cm (76.72%). Compared to CP, RP significantly decreased TP leaching by 16.02% and 31.50% in vegetable and cereal fields, respectively. Compared to NPK, NPKM significantly increased TP leaching in vegetable fields (30.43%); no significant difference in leaching occurred in cereal fields. P leaching, in response to RP, was influenced by the P amounts applied (34.49%); soil organic matter (14.49%); and TP (12.12%). P leaching in response to NPKM was influenced by multiple factors: rainfall (16.05%); soil organic matter (12.37%); soil bulk density (12.07%); TP (11.65%); pH (11.41%). NPKM was more beneficial for improving yields in cereal fields with low soil fertility and lower P-leaching risks. [ABSTRACT FROM AUTHOR]

Voriconazole is widely used in the treatment and prevention of invasive fungal diseases. Common drug-induced liver injuries increase the economic burdens and the risks of premature drug withdrawal and disease recurrence. This study estimated the disposal cost of voriconazole-related liver injury, explored the risk factors of voriconazole-related liver injury in hospitalized patients, and established a predictive model of liver injury to assist clinicians and pharmacists in estimating the probability or risk of liver injury after voriconazole administration to allow for early identification and intervention in patients at high risk of liver injury. A retrospective study was conducted on the selected inpatients whose blood concentration of voriconazole was measured in the West China Hospital of Sichuan University from September 2016 to June 2020. The incidence and disposal cost of voriconazole-related liver injuries were calculated. The incidence of voriconazole-related liver injury was 15.82% (217/1372). The disposal cost has been converted to 2023 at a discount rate of 5%. The median (P25, P75) disposal cost of severe liver injury (n = 42), general liver injury (n = 175), and non-liver injury (n = 1155) was 993.59 (361.70, 1451.76) Chinese yuan, 0.00 (0.00, 410.48) yuan, and 0.00 (0.00, 0.00) yuan, respectively, with a statistically significant difference (p < 0.001). Single factor analysis and multiple factor logistic regression were used to analyze the risk factors of voriconazole-related liver injury. The voriconazole-related liver injury was related to the trough concentration (Cmin, OR 1.099, 95% CI 1.058–1.140), hypoproteinemia (OR 1.723, 95% CI 1.126–2.636), and transplantation status (OR 0.555, 95% CI 0.325–0.948). The prediction model of liver injury was Logit (P)= −2.219 + 0.094 × Cmin + 0.544 × Hydroproteinemia − 0.589 × Transplantation, and the prediction model nomogram was established. The model validation results showed that the C-index of the derivation set and validation set was 0.706 and 0.733, respectively. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was 0.705 and 0.733, respectively, indicating that the model had good prediction ability. The prediction model will be helpful to develop clinical individualized medication of voriconazole and to identify and intervene in the cases of patients at high risk of voriconazole-related liver injury early on, in order to reduce the incidence of voriconazole-related liver injuries and the cost of treatment. [ABSTRACT FROM AUTHOR]

A fabric air dispersion system (FADS) is a type of flexible air supply system that integrates air transmission and distribution. This innovative system has the potential to address common issues such as uneven air supply and surface condensation, which are often associated with traditional ventilation systems. Existing numerical simulation studies on fiber ducts have encountered problems with mesh generation and simulation accuracy. This work develops a simulation method based on the equivalent discounting method to overcome these challenges. The proposed method is utilized to investigate the flow and heat transfer characteristics inside fiber ducts while also examining the effects of various shapes and opening configurations. The findings indicate that the temperature rise inside the duct is positively correlated with flow rate, with higher temperatures resulting from faster flow speeds. The temperature rise of FADS with four rows of openings increased by 0.4 k compared to other opening methods. Additionally, the study shows that increasing the number of rows of openings in the fiber duct leads to a faster decay of flow velocity and a higher temperature rise. At the same time, increasing the number of openings in the duct slightly reduces flow velocity while slightly increasing the temperature rise. The presence of more fiber duct elbows leads to greater local resistance, which accelerates the decay of the flow velocity and increases the temperature rise. Compared to the "1"-shaped FADS, the temperature rises of the "L"-shaped and "U"-shaped systems have increased by 0.9 k and 2.9 k, respectively. [ABSTRACT FROM AUTHOR]

Understanding the transformation of accumulated phosphorus (P) is vital for P management. However, previous studies are limited to a few sites in Chinese agroecosystems. In this study, to investigate the temporal-spatial differences of transformation from accumulated P to available P (determined by the Olsen method), a dataset was assembled based on 91 national long-term experimental sites across China in the recent 31 years (1988–2018). A boosted regression tree (BRT) and a structural equation model (SEM) were used to analyze the factors influencing the transformation. The results showed that the transformation from accumulated P to available P in South China (1.97 mg kg−1) was significantly higher than that in other regions (0.69–1.22 mg kg−1). Soil properties were the main driving factors with a relative contribution of 81.8%, while climate and management practices explained 7.8% and 10.4% of the variations, respectively. Furthermore, SEM analysis revealed that the soil organic matter (SOM) could positively and directly affect the transformation, whereas the soil pH, soil silt content, and P fertilizer had negative and direct effects on it. For the first time, this study analyzed the transformation from soil accumulated P to available P at a national scale and at multiple sites and quantified the contribution of the main influencing factors. These results help to predict the soil available P content across different agroecosystems based on the input amount of P fertilizer, contributing to the regional precise management of P fertilizer application. [ABSTRACT FROM AUTHOR]

Understanding the renal region-specific metabolic alteration in different animal models of diabetic nephropathy (DN) is critical for uncovering the underlying mechanisms and for developing effective treatments. In the present study, spatially resolved metabolomics based on air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) was used to compare the local metabolic changes in the kidneys of HFD/STZ-induced diabetic rats and db/db mice. As a result, a total of 67 and 59 discriminating metabolites were identified and visualized in the kidneys of the HFD/STZ-induced diabetic rats and db/db mice, respectively. The result showed that there were significant region-specific changes in the glycolysis, TCA cycle, lipid metabolism, carnitine metabolism, choline metabolism, and purine metabolism in both DN models. However, the regional levels of the ten metabolites, including glucose, AMP, eicosenoic acid, eicosapentaenoic acid, Phosphatidylserine (36:1), Phosphatidylserine (36:4), Phosphatidylethanolamine (34:1), Phosphatidylethanolamine (36:4), Phosphatidylcholine (34:2), Phosphatidylinositol (38:5) were changed in reversed directions, indicating significant differences in the local metabolic phenotypes of these two commonly used DN animal models. This study provides comprehensive and in-depth analysis of the differences in the tissue and molecular pathological features in diabetic kidney injury in HFD/STZ-induced diabetic rats and db/db mice. [ABSTRACT FROM AUTHOR]

To achieve transformation, libraries must undertake a profound and rapid reconfiguration of space. The spatial literacy competencies of librarians are directly related to the construction and service level of library spaces. This paper clarifies the concept of spatial literacy and its constituent elements. Using the method of systematic literature review, the current status of research on librarians' spatial literacy is analyzed from three aspects: spatial theory, spatial method, and spatial practice by focusing on the trajectory of library space-related literature. [ABSTRACT FROM AUTHOR]

Cowpea is an important leguminous crop in arid and semi-arid tropical regions. However, it is sensitive to the temperature and photoperiod. In this study, 41 new lines of cowpea were evaluated in sowing seasons of spring (SpS), summer (SuS), and autumn (AuS) at Wuming, Guangxi province, China. Nine agronomic and yield-related traits were investigated and analyzed. The results showed that the pod width (0.8 cm) was similar among sowing seasons. For all other traits, the values were lowest at SuS, except the number of branches per plant, which was lowest (2.5) at AuS. Strong correlations were detected for the growth period, plant height, pod length, pod width, and 100-seed weight (p < 0.01) across the sowing seasons. A principal component analysis revealed that the first three components could explain 72.47% of the total variations. On the basis of the possible yield, growth period, and growth habit, we identified nine new lines suitable for different sowing seasons in Guangxi. The results of this study suggest these new cowpea lines may be useful for increasing crop production and for breeding new varieties. [ABSTRACT FROM AUTHOR]

Open vegetable fields in China are a major anthropogenic source of nitrous oxide (N2O) emissions due to excessive nitrogen (N) fertilization. A 4 yr lettuce experiment was conducted to determine the impacts of controlled-release fertilizers (CRFs) and nitrification inhibitors (NIs) on lettuce yield, N2O emissions and net economic benefits. Five treatments included (i) no N fertilizer (CK), (ii) conventional urea at 255 kg N ha–1 based on farmers' practice (FP), (iii) conventional urea at 204 kg N ha–1 (OPT), (iv) CRF at 204 kg N ha–1 (CU) and (v) CRF (204 kg N ha–1) added with NI (CUNI). No significant differences were found in the lettuce yields among different N fertilization treatments. Compared with FP, the cumulative N2O emissions were significantly decreased by 8.1%, 38.0% and 42.6% under OPT, CU and CUNI, respectively. Meanwhile, the net benefits of OPT, CU and CUNI were improved by USD 281, USD 871 and USD 1024 ha–1 compared to CN, respectively. This study recommends the combined application of CRF and NI at a reduced N rate as the optimal N fertilizer management for the sustainable production of vegetables in China with the lowest environmental risks and the greatest economic benefits. [ABSTRACT FROM AUTHOR]

With the coming of the 2022 Beijing Winter Olympic Games, China's artificial ice rink construction will be in rapid development. A parametric evaluation of the cooling pipe in a direct evaporation rink was performed by numerical simulation. The results showed that the influence of the temperature of the antifreeze pipe on the ice surface temperature can be ignored. The evaporation temperature of the working medium in the cooling pipe is between −32 °C and −22.4 °C to ensure the ice surface temperature is between −5 °C and −3 °C. With the increase in the cooling pipe spacing, the required evaporation temperature of the working medium in the cooling pipe and the uniformity of the ice surface temperature decreased. The required evaporation temperature of the working medium in the cooling pipe decreases by 1.2–1.5 °C for every 10 mm increment of spacing. With the increase in the cooling pipe diameter, the required evaporation temperature of the working medium in the cooling pipe and the uniformity of the ice surface temperature increase. The required evaporation temperature of the working medium in the cooling pipe increases by 2.2–2.9 °C for every 5 mm increment of diameter. The maximum temperature difference of ice surface temperature ranged from 0.004 °C to 0.111 °C. [ABSTRACT FROM AUTHOR]

In this paper, we present the multi-stage attentive network (MSAN), an efficient and good generalization performance convolutional neural network (CNN) architecture for motion deblurring. We build a multi-stage encoder–decoder network with self-attention and use the binary cross-entropy loss to train our model. In MSAN, there are two core designs. First, we introduce a new attention-based end-to-end method on top of multi-stage networks, which applies group convolution to the self-attention module, effectively reducing the computing cost and improving the model's adaptability to different blurred images. Secondly, we propose using binary cross-entropy loss instead of pixel loss to optimize our model to minimize the over-smoothing impact of pixel loss while maintaining a good deblurring effect. We conduct extensive experiments on several deblurring datasets to evaluate the performance of our solution for deblurring. Our MSAN achieves superior performance while also generalizing and compares well with state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Understanding the effects of a fertilization regime on the long-term accumulation and transformation of soil phosphorus (P) is essential for promoting the development of sustainable management of soil P. Based on a 29-year field experiment in Mollisol, the compositions and changes of P forms using a modified Hedley sequential extraction method, solution 31P-NMR and P K-edge XANES and soil properties were investigated under continuous mono maize with and without manure (NPKM and NPK). Results showed a stronger positive related coefficient between soil total P and labile P, and mid-labile P fraction was found in NPKM than in NPK treatment. It indicated NPKM could improve the availability of soil accumulated P and reduce its transformation to stable P. Accumulated inorganic P (Pi) was dominated by aluminum phosphate (Al-P) and monobasic calcium phosphate monohydrate (MCP) for NPK treatment, Al-P, MCP, and tricalcium phosphate for NPKM treatment with XANES analysis, which contributed to the P availability in Mollisol. Moreover, the proportion of IHP with XANES and ratio of orthophosphate diesters to monoesters in NPK compared to NPKM indicated the higher Po lability with NPK treatment. Pi, especially NaHCO3-Pi and NaOH-Pi, were the potential sources of resin-Pi. Soil organic matter (SOM), organic-bound iron, and alumina oxide (Fep + Alp) showed significant influence on the transformation of P forms. Our research suggested that due to the rise in SOM and Fep + Alp, the fertilization regime significantly increased most highly active soil P fractions, especially in NPKM treatment. This work gives new insight into sustainable P management, which benefits the reduction in soil P accumulation. [ABSTRACT FROM AUTHOR]

Significant efforts have been made to characterize viral diversity in bats from China. Many of these studies were prospective and focused mainly on Rhinolophus bats that could be related to zoonotic events. However, other species of bats that are part of ecosystems identified as virus diversity hotspots have not been studied in-depth. We analyzed the virome of a group of Myotis fimbriatus bats collected from the Yunnan Province during 2020. The virome of M. fimbriatus revealed the presence of families of pathogenic viruses such as Coronavirus, Astrovirus, Mastadenovirus, and Picornavirus, among others. The viral sequences identified in M. fimbriatus were characterized by significant divergence from other known viral sequences of bat origin. Complex phylogenetic landscapes implying a tendency of co-specificity and relationships with viruses from other mammals characterize these groups. The most prevalent and abundant virus in M. fimbriatus individuals was an alphacoronavirus. The genome of this virus shows evidence of recombination and is likely the product of ancestral host-switch. The close phylogenetic and ecological relationship of some species of the Myotis genus in China may have played an important role in the emergence of this alphacoronavirus. [ABSTRACT FROM AUTHOR]

The variable diapause features of bivoltine silkworm (Bombyx mori) strains regulated by environmental signals in the embryonic stage are closely related to epigenetics. Previously, we showed that the expression of YTHDF3 is significantly different in the pupae of the bivoltine silkworm Qiufeng developed from eggs incubated at a normal temperature (QFHT, diapause egg producer) compared to those from eggs incubated at a low temperature (QFLT, nondiapause egg producer), indicating that the expression of diapause-associated genes is regulated by the m6A modification level. However, how YTHDF3 regulates the expression of diapause-related genes remains unclear. In this study, we observed that the knockdown of B. mori YTHDF3 resulted in delayed embryo development, while the overexpression of YTHDF3 resulted in the transformation of nondiapause-destined eggs into a mixture of diapause and nondiapause eggs. Further studies showed that YTHDF3, as a reading protein, can recognize the m6A site of Cyp307a1 and Cyp18a1 genes in the ecdysone synthesis pathway (ESP), and the overexpression of YTHDF3 affects the diapause traits of the silkworm by decreasing the stabilities of mRNAs of Cyp307a1 and Cyp18a1 and inhibiting their translation. The above results demonstrate that m6A modification mediates YTHDF3 to affect the expression levels of its target genes, Cyp307a1 and Cyp18a1, in the ESP to regulate diapause in bivoltine B. mori. This is the first report of the m6A methylation regulation mechanism in diapause in B. mori and provides new experimental data for clarifying the diapause regulation network. [ABSTRACT FROM AUTHOR]

A series of arene Ru(II) complexes, [(η6-MeC6H5)Ru(L)Cl]Cl, (L=o-ClPIP, 1; m-ClPIP, 2 and p-ClPIP, 3) (o-ClPIP=2-(2-chlorophenyl)imidazo[4,5-f][1,10]phenanthroline; m-ClPIP=2-(3-chlorophenyl)imidazo[4,5-f][1,10]phenanthroline; p-ClPIP=2-(4-chlorophenyl)imidazo[4,5-f][1,10]phenanthroline) was synthesized and investigated as a potential apoptosis inducer in chemotherapy. Spectroscopy and molecular docking simulations show that 1 exhibits moderated binding affinity to KRAS G-quadruplex DNA by groove mode. Further, in vitro studies reveal that 1 displays inhibitory activity against MCF-7 growth with IC50 = 3.7 ± 0.2 μM. Flow cytometric analysis, comet assay, and immunofluorescence confirm that 1 can induce the apoptosis of MCF-7 cells and G0/G1 phase arrest through DNA damage. In summary, the prepared arene Ru(II) complexes can be developed as a promising candidate for targeting G-quadruplex structure to induce the apoptosis of breast cancer cells via binding and stabilizing KRAS G-quadruplex conformation on oncogene promoter. [ABSTRACT FROM AUTHOR]

As one of the effective renewable energy sources, wind energy has received attention because it is sustainable energy. Accurate wind speed forecasting can pave the way to the goal of sustainable development. However, current methods ignore the temporal characteristics of wind speed, which leads to inaccurate forecasting results. In this paper, we propose a novel SSA-CCN-ATT model to forecast the wind speed. Specifically, singular spectrum analysis (SSA) is first applied to decompose the original wind speed into several sub-signals. Secondly, we build a new deep learning CNN-ATT model that combines causal convolutional network (CNN) and attention mechanism (ATT). The causal convolutional network is used to extract the information in the wind speed time series. After that, the attention mechanism is employed to focus on the important information. Finally, a fully connected neural network layer is employed to get wind speed forecasting results. Three experiments on four datasets show that the proposed model performs better than other comparative models. Compared with different comparative models, the maximum improvement percentages of MAPE reaches up to 26.279%, and the minimum is 5.7210%. Moreover, a wind energy conversion curve was established by simulating historical wind speed data. [ABSTRACT FROM AUTHOR]

The use of wind power generation can reduce the pollution in the environment and solve the problem of power shortages on offshore islands, grasslands, pastoral areas, mountain areas, and highlands. Wind speed forecasting plays a significant role in wind farms. It can improve economic and social benefits and make an operation schedule for wind turbines on large wind farms. This paper proposes a combined model based on the existing artificial neural network algorithms for wind speed forecasting at different heights. We first use the wavelet threshold method with the original wind speed dataset for noise reduction. After that, the three artificial neural networks, extreme learning machine (ELM), Elman neural network, and Long Short-term Memory (LSTM) neural network, are applied for wind speed forecasting. In addition, the variance reciprocal method and social cognitive optimization (SCO) algorithm are used to optimize the weight coefficients of the combined model. In order to evaluate the forecasting performance of the combined model, we select wind speed data at three heights (20 m, 50 m and 80 m) at the National Wind Technology Center M2 Tower. The experimental results show that the forecasting performance of the combined model is better than the single model, and it has a good forecasting performance for the wind speed at different heights. [ABSTRACT FROM AUTHOR]

Here, a series of half-sandwich arene Ru(II) complexes with difluorinated ligands [Ru(η6-arene)(L)Cl] (L1 = 2-(2,3-difluorophenyl)imidazole[4,5f][1,10]-phenanthroline; L2 = 2-(2,4-difluorophenyl)imidazole[4,5f][1,10]-phenanthroline; arene = benzene, toluene, and p-cymene) were synthesized and characterized. Molecular docking analysis showed that these complexes bind to c-myc G-quadruplex DNA through either groove binding or π–π stacking, and the relative difluorinated site in the main ligand plays a role in regulating the binding mode. The binding behavior of these complexes with c-myc G-quadruplex DNA was evaluated using ultraviolet–visible spectroscopy, fluorescence intercalator displacement assay, fluorescence resonance energy transfer melting assay, and polymerase chain reaction. The comprehensive analysis indicated that complex 1 exhibited a better affinity and stability in relation to c-myc G-quadruplex DNA with a DC50 of 6.6 μM and ΔTm values of 13.09 °C, than other molecules. Further activity evaluation results displayed that this class of complexes can also inhibit the growth of various tumor cells, especially complexes 3 and 6, which exhibited a better inhibitory effect against human U87 glioblastoma cells (51.61 and 23.75 μM) than other complexes, even superior to cisplatin (32.59 μM). Owing to a befitting lipophilicity associated with the high intake of drugs by tumor cells, complexes 3 and 6 had favorable lipid-water partition coefficients of −0.6615 and −0.8077, respectively. Moreover, it was found that complex 6 suppressed the proliferation of U87 cells mainly through an induced obvious S phase arrest and slight apoptosis, which may have resulted from the stabilization of c-myc G-quadruplex DNA to block the transcription and expression of c-myc. In brief, these types of arene Ru(II) complexes with difluorinated ligands can be developed as potential inducers of S-phase arrest and apoptosis through the binding and stabilization of c-myc G-quadruplex DNA, and could be used in clinical applications in the future. [ABSTRACT FROM AUTHOR]

High yields, high stress resistance, and wide adaptability are important cultivar traits, especially for crops sensitive to the photoperiod and temperature. Mung bean (Vigna radiata) is a typical short-day plant, traditionally cultivated in Asian countries, and consumed all over the world. However, there has long been relatively little research regarding its genetic improvement until in recent decades. Zhonglv 5 is a mung bean cultivar that was developed via crossbreeding in China in the early part of this century. It has since played an important role in improving mung bean production in the country because of its high yields, high stress tolerance, and wide adaptability. We herein describe the development of Zhonglv 5, summarize its yield performance and adaptability in diverse eco-regions within China, and predict its potential future uses to provide information relevant for mung bean breeding, production, trade, and related industries. [ABSTRACT FROM AUTHOR]

Increasing global cement and steel consumption means that a significant amount of greenhouse gases and metallurgical wastes are discharged every year. Using metallurgical waste as supplementary cementitious materials (SCMs) shows promise as a strategy for reducing greenhouse gas emissions by reducing cement production. This strategy also contributes to the utilization and management of waste resources. Controlled low-strength materials (CLSMs) are a type of backfill material consisting of industrial by-products that do not meet specification requirements. The preparation of CLSMs using metallurgical waste slag as the auxiliary cementing material instead of cement itself is a key feature of the sustainable development of the construction industry. Therefore, this paper reviews the recent research progress on the use of metallurgical waste residues (including blast furnace slag, steel slag, red mud, and copper slag) as SCMs to partially replace cement, as well as the use of alkali-activated metallurgical waste residues as cementitious materials to completely replace cement for the production of CLSMs. The general background information, mechanical features, and properties of pozzolanic metallurgical slag are introduced, and the relationship and mechanism of metallurgical slag on the performance and mechanical properties of CLSMs are analyzed. The analysis and observations in this article offer a new resource for SCM development, describe a basis for using metallurgical waste slag as a cementitious material for CLSM preparation, and offer a strategy for reducing the environmental problems associated with the treatment of metallurgical waste. [ABSTRACT FROM AUTHOR]

Municipal household waste (MHW) separation is a fundamental way to achieve waste reduction and a recycling economy. This study takes the positions of government and residents in MHW separation as the research object, and aims to explore the change process and influencing factors of their decision-making behavior, which is of great significance to attract residents to participate in MHW separation and establish an effective MHW separation mechanism to solve MHW pollution. This paper firstly establishes an evolutionary game model between government and residents in MHW separation; secondly, the payoff matrix of the system is determined, and the replication dynamic equations under different constraints are calculated to obtain the evolutionary stability strategy of the system, and the stability conditions are analyzed; Finally, through numerical simulation, the decision-making behavior of MHW separation and its influencing factors are studied, and the rationality of the model is verified. The results show that: (1) In the process of MHW separation, residents often choose not to separate without government regulation; (2) Environmental fee rates and government effort have great impacts on residents' decision-making behavior; (3) The increase of penalty intensity can significantly drive residents to separate MHW; (4) The sensitivity of residents' behavior decision to subsidy coefficient is the lowest among all the variables, and the incentive effect of increasing subsidy coefficient is not obvious. The research results can not only provide theoretical guidance for policy makers to develop waste management policies, but also provide valuable insights for local communities to guide residents' MHW separation behavior. [ABSTRACT FROM AUTHOR]

In this research, we study the non-parametric portfolio selection problem with Value at Risk (VaR) minimization and establish a new enhanced Mixed Integer Linear Programming (MILP) formulation to obtain the optimal solutions considering the symmetric property of VaR. We identify that the new MILP formulation can significantly reduce the computation burden of the MILP solver CPLEX. To solve larger-scale practical portfolio selection problems in reasonable computation time, we also develop the Particle Swarm Optimization (PSO) algorithm integrating an efficient Fast Feasible Solution Detection (FFSD) scheme to obtain the near-optimal solutions. Using the simulated datasets with different distribution parameters and skewness and kurtosis patterns, some preliminary numerical results are provided to show the efficiency of the new formulation and FFSD scheme. [ABSTRACT FROM AUTHOR]

As energy saving becomes more and more popular, electric load forecasting has played a more and more crucial role in power management systems in the last few years. Because of the real-time characteristic of electricity and the uncertainty change of an electric load, realizing the accuracy and stability of electric load forecasting is a challenging task. Many predecessors have obtained the expected forecasting results by various methods. Considering the stability of time series prediction, a novel combined electric load forecasting, which based on extreme learning machine (ELM), recurrent neural network (RNN), and support vector machines (SVMs), was proposed. The combined model first uses three neural networks to forecast the electric load data separately considering that the single model has inevitable disadvantages, the combined model applies the multi-objective particle swarm optimization algorithm (MOPSO) to optimize the parameters. In order to verify the capacity of the proposed combined model, 1-step, 2-step, and 3-step are used to forecast the electric load data of three Australian states, including New South Wales, Queensland, and Victoria. The experimental results intuitively indicate that for these three datasets, the combined model outperforms all three individual models used for comparison, which demonstrates its superior capability in terms of accuracy and stability. [ABSTRACT FROM AUTHOR]

Wind energy is crucial renewable and sustainable resource, which plays a major role in the energy mix in many countries around the world. Accurately forecasting the wind energy is not only important but also challenging in order to schedule the wind power generation and to ensure the security of wind-power integration. In this paper, four kinds of hybrid models based on cyclic exponential adjustment, adaptive coefficient methods and the cuckoo search algorithm are proposed to forecast the wind speed on large-scale wind farms in China. To verify the developed hybrid models' effectiveness, wind-speed data from four sites of Xinjiang Uygur Autonomous Region located in northwest China are collected and analyzed. Multiple criteria are used to quantitatively evaluate the forecasting results. Simulation results indicate that (1) the proposed four hybrid models achieve desirable forecasting accuracy and outperform traditional back-propagating neural network, autoregressive integrated moving average as well as single adaptive coefficient methods, and (2) the parameters of hybrid models optimized by artificial intelligence contribute to higher forecasting accuracy compared with predetermined parameters. [ABSTRACT FROM AUTHOR]

The Chinese Mainland has become the largest production base and a major potential market for Taiwan's information and electronics industry. Thus, studying the spatiotemporal evolution of the Taiwanese-funded information technology and electronics industry in the Mainland from the value chain perspective is necessary. This will help deepen the labor division and collaboration between the cross-strait information technology (IT) and electronics industry for sustainable development. Using Taiwanese investments during 1991–2012 and detailed firm-level data for 1976–2012, this study examines the spatiotemporal trajectory and geographical patterns of the labor division of Mainland China's Taiwanese-funded IT and electronics industrial value chain from a modular perspective. Based on the characteristics of the modular production process, the Taiwanese-funded IT and electronics firms in Mainland China are divided into four modules—parts manufacturing (PM), key parts manufacturing (KPM), complete machine manufacturing (CMM), and design and marketing (DM). We found that: (1) technology and value witnessed clear stage changes; (2) the PM and CMM modules were more decentralized, and the four modules formed five clusters; and (3) despite an increase, the degree of the four geographical divisions of labor was relatively low. This study offers implications for research and IT policy and electronics enterprises' production practices. [ABSTRACT FROM AUTHOR]

With the rapid development of indoor localization in recent years; signals of opportunity have become a reliable and convenient source for indoor localization. The mobile device cannot only capture images of the indoor environment in real-time, but can also obtain one or more different types of signals of opportunity as well. Based on this, we design a convolutional neural network (CNN) model that concatenates features of image data and signals of opportunity for localization by using indoor scene datasets and simulating the situation of indoor location probability. Using the method of transfer learning on the Inception V3 network model feature information is added to assist in scene recognition. The experimental result shows that, for two different experiment sceneries, the accuracies of the prediction results are 97.0% and 96.6% using the proposed model, compared to 69.0% and 81.2% by the method of overlapping positioning information and the base map, and compared to 73.3% and 77.7% by using the fine-tuned Inception V3 model. The accuracy of indoor scene recognition is improved; in particular, the error rate at the spatial connection of different scenes is decreased, and the recognition rate of similar scenes is increased. [ABSTRACT FROM AUTHOR]

A series of arene Ru(II) complexes coordinated with phenanthroimidazole derivatives, [(η⁶-C₆H₆)Ru(l)Cl]Cl(1b L = p -ClPIP = 2-(4-Chlorophenyl)imidazole[4,5f] 1,10-phenanthroline; 2b L = m -ClPIP = 2-(3-Chlorophenyl)imidazole[4,5f] 1,10-phenanthroline; 3b L = p -NPIP = 2-(4-Nitrophenyl)imidazole[4,5f] 1,10-phenanthroline; 4b L = m -NPIP = 2-(3-Nitrophenyl) imidazole [4,5f] 1,10-phenanthroline) were synthesized in yields of 89.9%-92.7% under conditions of microwave irradiation heating for 30 min to liberate four arene Ru(II) complexes (1b, 2b, 3b, 4b). The anti-tumor activity of 1b against various tumor cells was evaluated by MTT assay. The results indicated that this complex blocked the growth of human lung adenocarcinoma A549 cells with an IC 50 of 16.59 μM. Flow cytometric analysis showed that apoptosis of A549 cells was observed following treatment with 1b. Furthermore, the in vitro DNA-binding behaviors that were confirmed by spectroscopy indicated that 1b could selectively bind and stabilize bcl-2 G-quadruplex DNA to induce apoptosis of A549 cells. Therefore, the synthesized 1b has impressive bcl-2 G-quadruplex DNA-binding and stabilizing activities with potential applications in cancer chemotherapy.