Editorial: the March 2022 cover paper

Journal of Materials Science -     

Resource management in UAV-assisted MEC: state-of-the-art and open challenges

Wireless Networks - Unmanned aerial vehicles (UAV) have been widely used in various fields because of their high mobility and portability. At the same time, due to the rapid development of...     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Dysprosium doped copper oxide (Cu1-xDyxO) nanoparticles enabled bifunctional electrode for overall water splitting

The production of hydrogen, a favourable alternative to an unsustainable fossil fuel remains as a significant hurdle with the pertaining challenge in the design of proficient, highly productive and sustainable electrocatalyst for both oxygen evolution reaction (OER) and hydrogen evolution reaction (HER). Herein, the dysprosium (Dy) doped copper oxide (Cu_1-xDy_xO) nanoparticles were synthesized via solution combustion technique and utilized as a non-noble metal based bi-functional electrocatalyst for overall water splitting. Due to the improved surface to volume ratio and conductivity, the optimized Cu_1-xDy_xO (x = 0.01, 0.02) electrocatalysts exhibited impressive HER and OER performance respectively in 1 M KOH delivering a current density of 10 mAcm^?2 at a potential of ?0.18 V vs RHE for HER and 1.53 V vs RHE for OER. Moreover, the Dy doped CuO electrocatalyst used as a bi-functional catalyst for overall water splitting achieved a potential of 1.56 V at a current density 10 mAcm^?2 and relatively high current density of 66 mAcm^?2 at a peak potential of 2 V. A long term stability of 24 h was achieved for a cell voltage of 2.2 V at a constant current density of 30 mAcm^?2 with only 10% of the initial current loss. This showcases the accumulative opportunity of dysprosium as a dopant in CuO nanoparticles for fabricating a highly effective and low-cost bi-functional electrocatalyst for overall water splitting.     

Effects of feed composition,protein denaturation and storage of milk serum protein/lactose powders on lactosylation

During whey powder production, the feed is subjected to several heat treatments which can cause lactosylation of proteins. In this study, lactosylation of whey proteins was evaluated in spray-dried powders before and after storage by varying the native protein fraction as well as the serum protein/lactose ratio in the powders. The lactosylation of native α-lactalbumin and β-lactoglobulin in the powders before storage was not affected to a large extent by the protein denaturation or if the feed had been heat treated in a high or low lactose environment. After storage (relative humidity of 23.5%, 30 °C, 25 days), the kinetic of lactosylation tended to increase with increasing native protein fraction and bulk protein content in the powders. An explanation could be that proteins dissolved in the lactose glassy structure might have a lower reactivity, while proteins present in the protein glassy structure with dissolved lactose may display higher lactosylation reactivity.     

A review of phosphorescent and fluorescent phosphors for fingerprint detection

Currently, the efficient detection of fingerprints is essential for the crime investigations. Revealing fingerprints is commonly achieved with fluorescent organic compounds but they are not efficient for fingerprint detection on porous or reflective surfaces. In order to solve the problem of collecting fingerprints on porous/reflective surfaces, inorganic phosphors have been employed, since they have characteristics of variable color emission, afterglow, high chemical stability and nano-size, which allow the fingerprint detection on any porous or non-porous surfaces. Due to these last properties, this review presents a summary about the use of phosphorescent and fluorescent phosphors for the detection of latent fingerprints. First, we discussed the main physical and chemical characteristics of the fingerprints which permit their detection and collection from any surface. After this, we presented the main morphological, structural and luminescent properties of the phosphorescent and fluorescent phosphors that allow their use for fingerprint detection. Later, we demonstrated with pictures of fingerprints (with and without light emission from the phosphors deposited on them) that both, phosphorescent and fluorescent phosphors can be used to visualize fingerprints with high resolution and high contrast without interference of the background surface, which is ideal for its collection and registration in the Automated Fingerprint Identification System (AFIS). We believe that this review could be useful to understand how to select an appropriate phosphorescent or fluorescent material for fingerprint detection depending on the type of surface (porous or non-porous, reflective or not reflective) where the fingerprint is deposited.     

Extraction and characterization of hydroxyapatite-based materials from grey triggerfish skin and black scabbardfish bones

The conversion of food industry by-products to compounds with high added value is nowadays a significant topic, for social, environmental, and economic reasons. In this paper, calcium phosphate-based materials were obtained from black scabbardfish (Aphanopus carbo) bones and grey triggerfish (Balistes capriscus) skin, which are two of the most abundant fish by-products of Madeira Island. Different calcination temperatures between 400 and 1000°C were employed. Materials obtained from calcination of bones of black scabbard fish were composed by homogeneous mixtures of hydroxyapatite (Ca₁₀(PO4)₆(OH)₂, HAp) and β-tricalcium phosphate (β-Ca₃(PO₄)₂, β-TCP). Because of the high biocompatibility of HAp and the good resorbability of β-TCP, these natural biphasic materials could be very relevant in the field of biomaterials, as bone grafts. The ratio between HAp and β-TCP in the biphasic compound was dependent on the calcination temperature. Differently, the material obtained from skin of grey triggerfish contained HAp as the main phase, together with small amounts of other mineral phases, such as halite and rhenanite, which are known to enhance osteogenesis when used as bone substitutes. In both cases, the increase of calcination temperature led to an increase in the particles size with a consequent decrease in their specific surface area. These results demonstrate that from the fish by-products of the most consumed fishes in Madeira Island it is possible to obtain bioceramic materials with tunable composition and particle morphology, which could be promising materials for the biomedical field.     

Role of Endocrine-Disrupting Chemicals in the Pathogenesis of Non-Alcoholic Fatty Liver Disease: A Comprehensive Review

Non-alcoholic fatty liver disease (NAFLD) is considered the most common liver disorder, affecting around 25% of the population worldwide. It is a complex disease spectrum, closely linked with other conditions such as obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome, which may increase liver-related mortality. In light of this, numerous efforts have been carried out in recent years in order to clarify its pathogenesis and create new prevention strategies. Currently, the essential role of environmental pollutants in NAFLD development is recognized. Particularly, endocrine-disrupting chemicals (EDCs) have a notable influence. EDCs can be classified as natural (phytoestrogens, genistein, and coumestrol) or synthetic, and the latter ones can be further subdivided into industrial (dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (pesticides, insecticides, herbicides, and fungicides), residential (phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (parabens). Several experimental models have proposed a mechanism involving this group of substances with the disruption of hepatic metabolism, which promotes NAFLD. These include an imbalance between lipid influx/efflux in the liver, mitochondrial dysfunction, liver inflammation, and epigenetic reprogramming. It can be concluded that exposure to EDCs might play a crucial role in NAFLD initiation and evolution. However, further investigations supporting these effects in humans are required.     

Blockchain for Collaborative Businesses

Mobile Networks and Applications - Blockchain applications have continuously improved ever since its first debut on cryptocurrency. From then on, its uses have branched out from the financial...