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Several factors may play critical roles in alterations to product quality during storage of hog plum juice. This study aims to evaluate variations to physicochemical, antioxidant, anti-nutritional properties and microbial stability of hog plum juice during storage.

Juice was produced from hog plum fruits and stored for eight weeks at refrigerated and ambient conditions. Physicochemical, antioxidant properties, antinutritional factors and microbial properties of juices were determined using standard procedures

Degradation of ascorbic acid was higher in juices stored at ambient conditions (64.4%) compared to those stored by refrigeration (44.4%). Trends were similar for total phenolic, total flavonoid and total carotenoid contents. Total phenolic, total carotenoid and lycopene contents of fresh juice were 3.9 mg GAE/mL, 4.0 mg/mL and 1.3 mg/mL, which were not significantly different (at p = 0.08, 0.07 and 0.08, respectively) from the values at two weeks of storage at refrigerated conditions (3.9 mg GAE/mL, 3.9 mg/mL and 1.3 mg/mL). A sharp decrease of more than 40% (p = 0.02) in lycopene was recorded after four weeks, irrespective of storage temperature. Pasteurized hog plum juice showed no microbial growth until after four weeks of refrigerated storage when 1 CFU/mL each of bacterial and fungal growth were recorded. The juices, however, showed higher susceptibility to fungal growth as storage period increased.

Other variables not considered in this study such as nature of packaging materials may have significantly contributed to the observed data set. Further studies may, therefore, widen the scope of discussion to evaluate the associated relationship of these variables. Hog plum juice retained a considerable amount of bioactive components during refrigerated storage, which makes it a viable nutraceutical drink with industrial potentials and possible positive health implications for consumers.

This study provides new information that support the possible classification and use of hog plum juice as a safe functional beverage for human consumption.

Although the effect of storage temperature was significant in most of the properties studied, storage duration seems to have a greater influence on the stability of quality parameters during the storage of hog plum juice.

The purpose of this paper is to determine the effect of adding Aloe vera powder (AVP) in the production of mahewu with the aim of determining its shelf-life and sensory qualities.

Mahewu was produced at home (Sample B) and in the laboratory (Sample C) using a standard home-made procedure with the addition of AVP. A control mahewu (Sample A) was produced without AVP. Shelf-life was determined by following the chemical, microbiological, physical properties at 36 ± 2 °C for 60 days and the sensory properties of the products were also evaluated.

Physicochemical analysis revealed decreases in pH ranging between 3.3 and 2.4 from day 15–60 days of storage in all three samples. There was a significant increase (p < 0.05) in titratable acidity (0.2–1.8%) of all mahewu samples during storage. Total soluble solids were different amongst the samples from day 15 to day 60. The colour of the products was significantly different (p = 0.05) with respect to L*, a* and b* throughout the storage period. Microbiological results revealed an increase in coliforms bacteria, lactic acid bacteria, and yeast during storage. Sensory analysis showed that the control mahewu was more preferred than AVP added mahewu.

The study may help small-scale brewers to increase the shelf-life of mahewu.

Results of this study showed that the addition of AVP extended shelf-life of mahewu up to 15 days at 36 ± 2 °C.

Purpose – This work aims to study the treatment of adsorbant on the increasing liquid hydrocarbon quality produced by pyrolysis low density polyethylene (LDPE) plastic waste at low temperature. The hydrocarbon distribution, physicochemical properties and emission test were also studied due to its application in internal combustion engine. This research uses pure Calcium carbonate (CaCO₃) and pure activated carbon as adsorbant, LDPE type clear plastic samples with control variable that is solar gas station.

Design/Methodology/Approach – LDPE plastic waste of 10 kg were vaporized in the thermal cracking batch reactor using LPG 12 kg as fuel at range temperature from 100 to 300°C and condensed into liquid hydrocarbon. Furthermore, this product was treated with the mixed CaCO₃ and activated carbon as adsorbants to decrease contaminant material.

Findings – GC-MS identified the presence of carbon chain in the range of C6–C44 with 24.24% of hydrocarbon compounds in the liquid. They are similar to diesel (C6–C14). The 30% of liquid yields were found at operating temperature of 300°C. The calorific value of liquid was 46.021 MJ/Kg. This value was 5.07% higher than diesel as control.

Originality/Value – Hydrocarbon compounds in liquid produced by thermal cracking at a low temperature was similar to liquid from a catalytic process.

Automatic DNA-binding protein (DNA-BP) classification is now an essential proteomic technology. Unfortunately, many systems reported in the literature are tested on only one or two datasets/tasks. The purpose of this study is to create the most optimal and universal system for DNA-BP classification, one that performs competitively across several DNA-BP classification tasks.

Efficient DNA-BP classifier systems require the discovery of powerful protein representations and feature extraction methods. Experiments were performed that combined and compared descriptors extracted from state-of-the-art matrix/image protein representations. These descriptors were trained on separate support vector machines (SVMs) and evaluated. Convolutional neural networks with different parameter settings were fine-tuned on two matrix representations of proteins. Decisions were fused with the SVMs using the weighted sum rule and evaluated to experimentally derive the most powerful general-purpose DNA-BP classifier system.

The best ensemble proposed here produced comparable, if not superior, classification results on a broad and fair comparison with the literature across four different datasets representing a variety of DNA-BP classification tasks, thereby demonstrating both the power and generalizability of the proposed system.

Most DNA-BP methods proposed in the literature are only validated on one (rarely two) datasets/tasks. In this work, the authors report the performance of our general-purpose DNA-BP system on four datasets representing different DNA-BP classification tasks. The excellent results of the proposed best classifier system demonstrate the power of the proposed approach. These results can now be used for baseline comparisons by other researchers in the field.

In the developing field of nano-materials synthesis, copper oxide nanoparticles (NPs) are deemed to be one of the most significant transition metal oxides because of their intriguing characteristics. Its synthesis employing green chemistry principles has become a key source for next-generation antibiotics attributed to its features such as environmental friendliness, ease of use and affordability. Because they are more environmentally benign, plants have been employed to create metallic NPs. These plant extracts serve as capping, stabilising or hydrolytic agents and enable a regulated synthesis as well.

Organic chemical solvents are harmful and entail intense conditions during nanoparticle synthesis. The copper oxide NPs (CuO-NPs) synthesised by employing the green chemistry principle showed potential antitumor properties. Green synthesised CuO-NPs are regarded to be a strong contender for applications in the pharmacological, biomedical and environmental fields.

The aim of this study is to evaluate the anticancer potential of CuO-NPs plant extracts to isolate and characterise the active anticancer principles as well as to yield more effective, affordable, and safer cancer therapies.

This review article highlights the copper oxide nanoparticle's biomedical applications such as anticancer, antimicrobial, dental and drug delivery properties, future research perspectives and direction are also discussed.

Biodegradable polymers are widely used in personalized medical devices or scaffolds for tissue engineering. The manufacturing process should be finished with sterilization procedure. However, it is not clear how the different sterilization methods have an impact on the mechanical strength of the three-dimensional (3D)-printed parts, such as bone models or personalized mechanical devices. This paper aims to present the results of mechanical testing of polylactide-based bone models before and after sterilization.

Polylactide specimens prepared in fused filament fabrication technology were sterilized with different sterilization methods: ultraviolet (UV) and ethylene oxide. Mechanical properties were determined by testing tensile strength, Young’s modulus and toughness.

The tensile strength of material after sterilization was significantly higher after ethylene oxide sterilization compared to the UV sterilization, but in both sterilization methods, the specimens characterized lower tensile strength and Young’s modulus when compared to the control. In comparison of toughness results, there was no statistically significant differences. The findings are particularly significant in the perspective of using individual implants, bone grafts and dental guides.

Although fused filament fabrication (FFF) 3D printing devices equipped with UV light sterilization options are available, experimental results of the effect of selected sterilization methods on the mechanical strength of additively manufactured parts have not been described. This paper completes the present state of the art on the problem of sterilization of FFF parts from biodegradable materials.

The different performance tests were conducted on diesel engine compression ignition (CI) mode and CRDi engine.

The CI engine was suitably modified to CRDi engine with Toroidal re-entrant combustion chamber (TRCC) and was run in dual-fuel (DF) mode. Hydrogen (H₂) was supplied at different flow rates during the suction stroke, and 0.22 Kg/h of hydrogen fuel flow rate (HFFR) was found to be optimum. Diesel and biodiesel were used as pilot fuels. The CRDi engine with DF mode was run at various injection pressures, and 900 bar was found to be optimum injection pressure (IP) with 10o before top dead center (bTDC) as fuel injection timing (IT).

These operating engine conditions increased formation of oxides of nitrogen (NOx), which were reduced by exhaust gas recycle (EGR). With EGR of 15%, CRDi engine resulted in 12.6% lower brake thermal efficiency (BTE), 5.5% lower hydrocarbon (HC), 7.7% lower carbon monoxide (CO), 26% lower NOx at 80% load as compared to the unmodified diesel engine (CI mode).

The current research is an effort to study and evaluate the performance of CRDi engine in DF mode with diesel-H₂ and BCPO-H₂ fuel combinations with TRCC.

Modern meat processing requires automation and robotisation to remain sustainable and adapt to future challenges, including those brought by global infection events. Automation of all or many processes is seen as the way forward, with robots performing various tasks instead of people. Meat cutting is one of these tasks. Smart novel solutions, including smart knives, are required, with the smart knife being able to analyse and predict the meat it cuts. This paper aims to review technologies with the potential to be used as a so-called “smart knife” The criteria for a smart knife are also defined.

This paper reviews various technologies that can be used, either alone or in combination, for developing a future smart knife for robotic meat cutting, with possibilities for their integration into automatic meat processing. Optical methods, Near Infra-Red spectroscopy, electrical impedance spectroscopy, force sensing and electromagnetic wave-based sensing approaches are assessed against the defined criteria for a smart knife.

Optical methods are well established for meat quality and composition characterisation but lack speed and robustness for real-time use as part of a cutting tool. Combining these methods with artificial intelligence (AI) could improve the performance. Methods, such as electrical impedance measurements and rapid evaporative ionisation mass spectrometry, are invasive and not suitable in meat processing since they damage the meat. One attractive option is using athermal electromagnetic waves, although no commercially developed solutions exist that are readily adaptable to produce a smart knife with proven functionality, robustness or reliability.

This paper critically reviews and assesses a range of sensing technologies with very specific requirements: to be compatible with robotic assisted cutting in the meat industry. The concept of a smart knife that can benefit from these technologies to provide a real-time “feeling feedback” to the robot is at the centre of the discussion.