market demand
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In recent years, the market demand for products enhanced with ingredients derived from natural products, such as polyphenols, is rapidly increasing. Laurus nobilis L., known as bay, sweet bay, bay laurel, Roman laurel or daphne is an evergreen Mediterranean shrub whose leaves have traditionally been used in cuisines and folk medicine due to their beneficial health effects, which can nowadays be scientifically explained by various biological activities of the leaf extracts. Many of these activities can be attributed to phenolic compounds present in L. nobilis leaves which include flavonoids, phenolic acids, tannins (proanthocyanidins) and lignans. In order to enable efficient industrial utilization of these valuable compounds, it is crucial to establish optimal extraction procedures resulting in the highest yields and quality of the extracts. This paper offers the first systematic review of current literature on the influence of conventional and advanced extraction techniques, including microwave-assisted, ultrasound-assisted, enzyme-assisted, supercritical-CO2 and mechanochemical-assisted extraction on the phenolic content of L. nobilis leaf extracts, allowing more efficient planning of further research and simplifying the steps towards industrial utilization of this plant.

AbstractIn this paper, we analyze a firm choice between crowdfunding and bank financing. For many entrepreneurs, it is an important issue. We analyze a model where the choice of financing is affected by moral hazard problem regarding the choice of production scale that favors bank financing, and by the uncertainty about market demand that favors crowdfunding. We argue that long crowdfunding campaigns or campaigns with large targets usually are less efficient in mitigating moral hazard problem than small/short campaigns. We also argue that high-quality firms and firms with potentially large markets will tend to select bank financing while projects with largest amount of investment should select mixed financing where the firm uses a short crowdfunding campaign and a bank loan. Most of our model empirical predictions have not been directly tested so far while they are indirectly consistent with available evidence.

The impact of soft drinks on obesity has been widely investigated during the last decades. Conversely, the role of obesity as a factor influencing the demand for soft drinks remains largely unexplored. However, understanding potential changes in the demand for soft drinks, as a result of changes in the spread of obesity, may be useful to better design a comprehensive strategy to curb soft drink consumption. In this paper, we aim to answer the following research question: Does the prevalence of obesity affect the demand for soft drinks? For this purpose, we collected data in a sample of 97 countries worldwide for the period 2005–2019. To deal with problems of reverse causality, an instrumental variable approach and a two-stage least squares method were used to estimate the impact of the age-standardized obesity rate on the market demand for soft drinks. After controlling for several demographic and socio-economic confounding factors, we found that a one percent increase in the prevalence of obesity increases the consumption of soft drinks and carbonated soft drinks by about 2.37 and 1.11 L per person/year, respectively. Our findings corroborate the idea that the development of an obesogenic food environment is a self-sustaining process, in which obesity and unhealthy lifestyles reinforce each other, and further support the need for an integrated approach to curb soft drink consumption by combining sugar taxes with bans, regulations, and nutrition education programs.

In recent decades, increasing attention has been paid to food safety and organic horticulture. Thus, people are looking for natural products to manage plant diseases, pests, and weeds. Essential oils (EOs) or EO-based products are potentially promising candidates for biocontrol agents due to their safe, bioactive, biodegradable, ecologically, and economically viable properties. Born of necessity or commercial interest to satisfy market demand for natural products, this emerging technology is highly anticipated, but its application has been limited without the benefit of a thorough analysis of the scientific evidence on efficacy, scope, and mechanism of action. This review covers the uses of EOs as broad-spectrum biocontrol agents in both preharvest and postharvest systems. The known functions of EOs in suppressing fungi, bacteria, viruses, pests, and weeds are briefly summarized. Related results and possible modes of action from recent research are listed. The weaknesses of applying EOs are also discussed, such as high volatility and low stability, low water solubility, strong influence on organoleptic properties, and phytotoxic effects. Therefore, EO formulations and methods of incorporation to enhance the strengths and compensate for the shortages are outlined. This review also concludes with research directions needed to better understand and fully evaluate EOs and provides an outlook on the prospects for future applications of EOs in organic horticulture production.

The continuous expansion of the market demand and scale of commercial amidoxime chelating resins has caused large amounts of resin to be discarded around the world. In this study, the waste amidoxime chelating resin was reutilized as an adsorbent for the removal and recovery of Pb(II), Cu(II), Cd(II) and Zn(II) ions from aqueous solutions. The physical morphology and chemical composition of the waste amidoxime chelating resin (WAC-resin) from the factory was characterized by the elemental analyzer, X-ray photoelectron spectroscopy and Fourier-transform infrared spectroscopy. The influence of the initial metal ions concentration, contact time, temperature and the solution pH on the adsorption performance of the metal ions was explored by batch experiments. It was shown that the optimal pH was 4. Kinetic studies revealed that adsorption process corresponded with the pseudo-second-order kinetic model and the adsorption isotherm was consistent with the Langmuir model. At room temperature, the adsorption capacities of WAC-resin for Pb2+, Cu2+, Zn2+ and Cd2+ reached 114.6, 93.4, 24.4 and 20.7 mg/g, respectively.

Abstract A new, fast and efficient method, hyphenated microwave-assisted aqueous two-phase extraction (MA-ATPE) was applied in the extraction of α-solanine from Solanum retroflexum. This environmentally friendly extraction method applied water and ethanol as extraction solvents. Central composite design (CCD) was performed which included numerical parameters such as time, mass of plant powder and microwave power. The categorical factors included the chaotrope — NaCl or the kosmotrope — Na2CO3. Fitting the central composite design response surface model to the data generated a quadratic model with a good fit (R2 = 0.920). The statistically significant (p < 0.05) parameters such as time and mass of plant powder were influential in the extraction of α-solanine. Quantification of α-solanine was achieved using a robust and sensitive feature of the ultra-high performance quadrupole time of flight mass spectrometer (UHPLC-qTOF-MS), multiple reaction monitoring (MRM). The optimized condition for the extraction of α-solanine in the presence of NaCl and Na2CO3 was a period of 1 min at a mass of 1.2 g using a microwave power of 40%. Maximal extraction of α-solanine was 93.50 mg kg−1 and 72.16 mg kg−1 for Na2CO3 and NaCl, respectively. The synergistic effect of salting-out and microwave extraction was influential in extraction of α-solanine. Furthermore, the higher negative charge density of the kosmotrope (Na2CO3) was responsible for its greater extraction of α-solanine than chaotrope (NaCl). The shorter optimal extraction times of MA-ATPE make it a potential technique that could meet market demand as it is a quick, green and efficient method for removal of toxic metabolites in nutraceuticals.

Abstract Background Elderly care service projects (ECSPs) aim to provide care services with the help of market forces on the supply side to satisfy the huge demand of the elderly. Subsidies play an important role in motivating the investors to invest in the ECSPs immediately. The optimal subsidy scheme should balance the policy costs and the investors’ interests. Methods Based on the policy background of China, this study applied the real options theory to compare the effects of construction subsidy and operating subsidy on achieving policy goals from the perspective of uncertain actual demand. It introduced numerical examples to identify the optimal subsidy scheme and embedded the data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS) to verify the uncertainty of actual demand. Results The results showed that in the context of uncertain actual demand, operating subsidy has greater advantages in reducing investment thresholds, saving subsidy costs and increasing spillover values. Moreover, a sound quality supervision system, a differentiated operating subsidy scheme and a sustainable growth market demand environment are conducive to increasing the long-term interests of the government and the investors. Conclusions The study emphasized the importance of subsidy selection in the context of uncertain actual demand, and provided a practical reference for policy designers in China and other developing countries to choose the optimal subsidy scheme for the ECSPs.

The discourse of employability revolves around the mitigation of mismatch between educational outcomes and the job market demand.  This discourse is pertinent in engineering education as it is dedicated to producing human resources with the required employability skills. In this context, the students - to whom employability is transformed - are in the central focus. Their perceptions about their abilities in demonstrating and performing in the world of work require attention to connect education and their work. Considering this, the level of perceived employability of the engineering students studying in their final year was measured by using a self-constructed scale in a representative sample of 314 students of Kathmandu valley. The finding shows that the graduating students’ perceived employability was not consolidated and optimised to reflect on their behaviour and practices. It is at the level of ‘emergence’ and ‘presence’, which is thus not enough to see in their abilities to perform better. Therefore, the students were not able to perform as per the expectation of the market.  The key implication of this study is that the gap of work-study transition stipulated to be minimised for the employability of the graduates with their exposure in the world of work.

This paper examines two assumption: First, whether inadequate practical training, including much shortened apprenticeship training, has negatively affected the employability and incomes of graduates of TVET institutions in Nepal, and the second, whether it is good institutional management and governance that provide the systems for quality training and positive labour market outcomes. Tracer studies and an institutional assessment of Jiri Technical School (JTS) confirm the first assumption. The review of select literature on institution building and the benchmarking of JTS’ operative practices against those of high performing educational institutions (in India) confirm the second assumption. It is argued that poor management and governance of TVET institutions drifts the mission of Technical Schools away from their initial socio-economic mandate: the provision of skilled human resource and access to qualification opportunities to the youth having the aptitudes for such an education. Social rather than labour market demand with corresponding politics is one major force for such deviation. To revitalise the JTS, it is proposed to bank on the federalisation of the TVET governance system to professionalise Board, Management and teachers for enhanced labour market outcomes in closer cooperation between actors from the education and employment systems.

Through big data mining, enterprises can deeply understand the consumer preferences, behavior characteristics, market demand and other derived data of customers, so as to provide the basis for formulating accurate marketing strategies. Therefore, this paper proposes a marketing management big date mining method based on deep trust network model. This method first preprocesses the big data of marketing management, including data cleaning, data integration, data transformation and data reduction, and then establishes a big data mining model by using deep trust network to realize the research on the classification of marketing management data. Experimental results show that the proposed method has 99.08% accuracy, the capture rate reaches 88.11%, and the harmonic average between the accuracy and the recall rate is 89.27%, allowing for accurate marketing strategies.