How to improve enterprise performance has been a research topic widely studied by scholars for a long time. As economic globalization deepens, the business competition becomes increasingly harsh. Technology-based small and medium-sized enterprises (SMEs) play an important role in the rapid development of the country’s economy, especially in China. This study aims to investigate the mediating effect of knowledge integration capability in the relationship between corporate social capital and enterprise performance. The sample group used in this study were 300 technology-based SMEs in China. The research tool was a questionnaire adapted from previous scholars, which passed assessment in terms of content validity and reliability. Data were analyzed using structural equation modelling. The results show that: 1) corporate social capital has a positive impact on enterprise performance, but the impact differs between well-performing and poor-performing enterprises; and 2) knowledge integration ability plays a mediating role in the relationship between corporate social capital and enterprise performance, and the mediating role is the same for both well-performing and poor-performing enterprises. But it played a partial mediating role in the good-performance comparison group and a complete mediating role in the poor-performance comparison group. This study is useful for enterprise management in cultivating and developing the abundant social capital of enterprises and expanding channels for knowledge integration ability to increase enterprise performance.

This work evaluates the physical and physical-chemical parameters of the strawberry variety “Festival”, obtained in the soil and climate conditions of Humpata, Huila Province, Angola, following the transformation into sweet of adequate quality. The analyses made were: the mass determined on an analytical balance and the transversal and longitudinal diameters with a pachymeter. Other analyses were: total titratable acidity by volumetry, pH by potentiometry, total soluble solids by refractometry, moisture and ash by gravimetry. The study showed that the pH of the pulp was 3.41; and in the candy it was 3.31. The titratable acidity in the strawberry pulp had a value of 0.186 g/100 mL and in the jam 0.096 g/100 mL; the ascorbic acid content in the pulp was 18.60 mg∕100 g. The average soluble solids content in the pulp was 9.51 °Brix and for the jam 68.83 °Brix. These chemical characteristics of the pulp and jam provide information about their nutritional values.

The Cu_2–xSe nanoparticles were synthesized by high temperature pyrolysis, modified with aminated polyethylene glycol in aqueous solution and loaded with compound 2,2′–azobis[2–(2–imidazolin–2–yl)propane] dihydrochloride (AIPH). The obtained nanomaterials can induce photothermal effect and use heat to promote the generation of toxic AIPH radicals under the irradiation of near-infrared laser (808 nm), which can effectively kill cancer cells. A series of in vitro experiments can preliminarily prove that Cu_2–xSe–AIPH nanomaterials have strong photothermal conversion ability, good biocompatibility and anticancer properties.

Energy shortages and environmental damage have become serious problems facing the society today. Biomass can be a renewable energy source, which large-scale development and utilization are of great significance to industry and social life. Biomass pyrolysis technology can achieve effective utilization of biomass energy. It is necessary to optimize the pyrolysis reaction technology and device for realize the industrialization and large-scale production of biomass energy.

For five different regions in Kırklareli province, heavy metals; such as Pb, Ni, Cu, Mn, Cd, Cr, Co, Zn, Mo, and Fe in the mixture of leaves and flowers from linden trees (Tilia tomentosa L.) were analyzed by using flame atomic absorption spectroscopy after the samples were dissolved with microwave method. Also, organochloride pesticides; such as ∑BHC: [α-BHC, β-BHC, γ-BHC, and δ-BHC], ∑DDT: [4,4’-DDD, 4,4’-DDE, and 4,4’-DDT], α-Endosulfan, β-Endosulfan, Endosulfan sulfate, Heptachlor, Heptachlor-endo-epoxide, Aldrin, Dieldrin, Endrin aldehyde, Endrin ketone, Endrin and Methoxychlor in these samples were determined by utilizing gas chromatography mass spectroscopy after the samples were prepared for analyses by using QuEChERS method. The metal concentrations in the samples were in the range of 45.3 to 268 mg/kg for Mn, 0.25 to 18.8 mg/kg for Cu, 11.5 to 46.1 mg/kg for Zn, 128 to 1310 mg/kg for Fe, 10.4 to 38.6 mg/kg for Mo, 0.82 to 1.34 mg/kg for Cd, 0 to 6.45 mg/kg for Ni, 0 to 19.2 mg/kg for Pb, and 0 to 8.25 mg/kg for Cr. Moreover, the concentrations of organochloride pesticides in samples were usually determined to be lower than their maximum residue level values given the pesticide residue limit regulation of Turkish Food Codex. 

Fire, a phenomenon occurs in most parts of the world and causes severe financial losses, even, irreparable damages. Many parameters are involved in the occurrence of a fire; some of which are constant over time (at least in a fire cycle), but the others are dynamic and vary over time. Unlike the earthquake, the disturbance of fire depends on a set of physical, chemical, and biological relations. Monitoring the changes to predict the occurrence of fire is efficient in forest management. Method: In this research, the Persian and English databases were structurally searched using the keywords of fire risk modeling, fire risk, fire risk prediction, remote sensing and the reviewed papers that predicted the fire risk in the field of remote sensing and geographic information system were retrieved. Then, the modeling and zoning data of fire risk prediction were extracted and analyzed in a descriptive manner. Accordingly, the study was conducted in 1995-2017. Findings: Fuzzy analytic hierarchy process (AHP) zoning method was more practical among the applied methods and the plant moisture stress measurement was the most efficient among the remote sensing indices. Discussion and Conclusion: The findings indicate that RS and GIS are effective tools in the study of fire risk prediction.