Selective separation and characterisation of dual ACE and DPP-IV inhibitory peptides from rainbow trout (Oncorhynchus mykiss) protein hydrolysates

Microwave pretreatment and hydrolysis were applied to rainbow trout (Oncorhynchus mykiss) by-products to produce bioactive peptides with dual in vitro angiotensin-I converting enzyme (ACE) and dipeptidyl-peptidase IV (DPP-IV) inhibitory activities. Peptides were fractionated using the single step electrodialysis with ultrafiltration membrane (EDUF). Concentration of cationic peptides (CP) increased in the recovery solution, reaching 125 μg mL⁻¹ after a 4-h treatment with migration rate of 15.68 ± 2.98 g m⁻² h. CP fractions displayed ACE and DPP-IV I inhibitory properties, with IC₅₀ values of 0.0036 mg mL⁻¹ and 1.23 mg mL⁻¹ respectively. The bioactivity was attributed to the low molecular weight peptides (300–500 Da) recovered. CP exhibited non-competitive inhibition patterns for ACE and DPP-IV, which were dose dependent. These results showed that bioactive peptides can successfully be separated from complex hydrolysate mixtures by EDUF. The fractionated peptides can serve as potential functional food ingredients or nutraceuticals for the management of hypertension and diabetes.     

Nuclear DNA barcodes for cod identification in mildly-treated and processed food products

Gadoids are a group of fish with historical importance in the fishing industry. The high demand for cod is one of the reasons why cod products are often mislabelled, and numerous observations have been made on the replacement of Atlantic cod (Gadus morhua) by cheaper species or its illegal capture in contravention of fish quotas. Fish species identification is traditionally based on morphological features, but this may be difficult in case of heat-treated or processed products, or where the species look similar, as in the Gadoid group. DNA-based approaches (using either nuclear or mitochondrial DNA) are most commonly used in this case, due to their high specificity and to the high resilience of the target molecules to food processing techniques. In this article, we identified, using an automated screening approach, novel barcode regions and their associated primers in the nuclear genome, to be used for the efficient identification of Gadoids. The barcode regions were tested on official and commercial samples, raw or mildly treated products, like frozen, or salted, as well as pre-cooked complex mixtures and processed samples, using next-generation sequencing (NGS) technique. The method proposed could complement existing fish identification strategies in establishing an efficient framework to detect and prevent frauds along the food chain.     

Risk probability predictions for coal enterprise infrastructure projects in countries along the Belt and Road Initiative

The Belt and Road Initiative has significantly promoted the construction and development of coal enterprises along the Belt and Road through the building of a new platform that encourages global economic cooperation. This study examines problems caused by the uncertainty of risk occurrence during the process of coal enterprise construction as part of the Belt and Road Initiative. Consequently, the study identifies and classifies various risk factors. In total, 11 types of risks and 39 risk factors involved in the construction process are summarized. These include natural, cultural, religious, marketing, and outsourcing-related risks. A prediction indicator system was also established to apply to the risk occurrence probability related to coal mine construction along the Belt and Road. In this regard, the study embedded an improved artificial fish swarm algorithm (IAFSA) into a cerebellar model articulation controller (CMAC) neural network model and collected risk probability details for the construction of the Barapukuria Coal Mine in Bangladesh from 2013 to 2018 as sample data. By researching the model and sample, this study obtained various risk occurrence probability intervals. Moreover, diversified risk probabilities were verified and predicted. Finally, this study empirically proves that an IAFSA–CMAC parallel coupling algorithm is able to achieve precise predictions about risks. This finding has great significance for risk management and control in the coal enterprises of countries along the Belt and Road.     

Effect of clove extract pretreatment and drying conditions on lipid oxidation and sensory discrimination of dried omena (Rastrineobola argentea) fish

Sun‐drying is a low‐cost, low‐technology fish preservation method frequently employed in developing areas. However, the process promotes lipid oxidation and its associated undesired flavours and odours. This study investigated low‐technology solutions for impact on lipid oxidation and sensory attributes of oven‐dried omena fish (Rastrineobola argentea). Two oven‐drying conditions and four doses of clove water extract ‘dip’ pretreatments were studied in a complete factorial design. Lipid oxidation in dried fish was assessed by TBARS, peroxide value and fatty acid analysis by GC‐FID. Results showed that soaking in 10 g L^?1 clove water extract for 1 h and oven‐drying at 150 °C × 30 min significantly reduced TBARS and peroxide values in omena fish by 77% and 79%, respectively, and polyene index showed improved retention of long‐chain polyunsaturated fats, compared to original drying condition. Lastly, panellists of a triangle test were able to discriminate between biscuits made with the modified and original dried fish.     

Curcumin loaded fish scale collagen-HPMC nanogel for wound healing application: Ex-vivo and In-vivo evaluation

The objective of the present investigation was to formulate curcumin loaded fish scale collagen (FSC)-hydroxypropyl methyl cellulose (HPMC K100) nanogel (CNG) for wound healing application. The curcumin nanoemulsion was prepared, characterized and loaded in FSC-HPMC nanogel. The nanogel was evaluated for ex-vivo permeation, in-vivo, skin irritation, and stability study. Ex-vivo permeation study demonstrated that CNG prolonged release and exhibited higher percent contraction value of wound compared to other formulations. In skin irritation study, formulation produced the score of less than 2 compared to control. It concluded that curcumin loaded FSC-HPMC nanogel could be prepared for wound healing applications.     

Developing English domestic occupancy profiles

ABSTRACT

Occupancy patterns are necessary to estimate energy demand and evaluate thermal comfort in households. Because of this, many European countries are developing representative domestic schedules to replace outdated criteria. This paper evaluates the state of knowledge of UK domestic occupancy patterns and develops new domestic occupancy profiles for England. The presented research (1) characterizes methods for collecting occupancy data and inferring patterns; (2) identifies and assesses the quality of categories of occupancy patterns used in building simulation; and (3) develops updated occupancy profiles. A systematic scoping review identified social and monitoring surveys as the most deployed data-collection methods. A systematic literature review also established that the occupancy categories most frequently used in UK building simulation are (a) a family with dependent children where the parents work full time; and (b) a retired elderly couple who spend most of their time indoors. The interview sample from the English Housing Survey 2014–15 was used to map household typologies. Results show that categories (a) and (b) combined amount to only 19% of England’s households, which suggest models are over-reliant on these groups. Considering this result, the paper develops occupancy patterns for England derived from 2015 UK Time Use Survey diaries for each household typology previously identified.     

Process-mining enabled feedback: “Tell me what I did wrong” vs. “tell me how to do it right”

Fast advancement of technology has led to an increased interest for using information technology to provide feedback based on learning behavior observations. This work outlines a novel approach for analyzing behavioral learner data through the application of process mining techniques specifically targeting a complex problem solving process. We realize this in the context of one particular learning case, namely, domain modeling. This work extends our previous research on process-mining analysis of domain modeling behavior of novices by elaborating with new insights from a replication study enhanced with an extra observation on how novices verify/validate models. The findings include a set of typical modeling and validation patterns that can be used to improve teaching guidance for domain modeling courses. From a scientific viewpoint, the results contribute to improving our knowledge on the cognitive aspects of problem-solving behavior of novices in the area of domain modeling, specifically regarding process-oriented feedback as opposed to traditional outcome feedback (is a solution correct? Why (not)?) usually applied in this type of courses. Ultimately, the outcomes of the work can be inspirational outside of the area of domain modeling as learning event data is becoming readily available through virtual learning environments and other information systems.     

Applying an anchor based patent mapping approach: Basic conception and the case of carbon fiber reinforcements

Patent mapping is an important method for analyzing technological patterns both for scientific research and strategic tasks in companies. In this paper we focus on a specific type of technological pattern, namely the analysis of patents' positions in relation to predefined positions of application fields. For this purpose we use an anchoring approach. We apply semantic patent measurement and discuss RadViz as a powerful method to visualize the measurement's results and to provide insightful motion patterns for monitoring technology change. Moreover, we present an algorithm to define so called anchor points as high dimensional reference points by using textual elements of patents. By the example of carbon fiber reinforcements we demonstrate the usefulness of our approach. Thus, our approach enables academics to analyze important types of technological patterns like convergence or divergence by means of a new instrument and gives practitioners like the R&D management of companies the opportunity to build a reliable strategic business decision support.