Attribute Identification and Predictive Customisation Using Fuzzy Clustering and Genetic Search for Industry 4.0 Environments

Today´s factory involves more services and customisation. A paradigm shift is towards “Industry 4.0” (i4) aiming at realising mass customisation at a mass production cost. However, there is a lack of tools for customer informatics. This paper addresses this issue and develops a predictive analytics framework integrating big data analysis and business informatics, using Computational Intelligence (CI). In particular, a fuzzy c-means is used for pattern recognition, as well as managing relevant big data for feeding potential customer needs and wants for improved productivity at the design stage for customised mass production. The selection of patterns from big data is performed using a genetic algorithm with fuzzy c-means, which helps with clustering and selection of optimal attributes. The case study shows that fuzzy c-means are able to assign new clusters with growing knowledge of customer needs and wants. The dataset has three types of entities: specification of various characteristics, assigned insurance risk rating, and normalised losses in use compared with other cars. The fuzzy c-means tool offers a number of features suitable for smart designs for an i4 environment

Identifying smart design attributes for Industry 4.0 customization using a clustering Genetic Algorithm

Industry 4.0 aims at achieving mass customization at a mass production cost. A key component to realizing this is accurate prediction of customer needs and wants, which is however a challenging issue due to the lack of smart analytics tools. This paper investigates this issue in depth and then develops a predictive analytic framework for integrating cloud computing, big data analysis, business informatics, communication technologies, and digital industrial production systems. Computational intelligence in the form of a cluster k-means approach is used to manage relevant big data for feeding potential customer needs and wants to smart designs for targeted productivity and customized mass production. The identification of patterns from big data is achieved with cluster k-means and with the selection of optimal attributes using genetic algorithms. A car customization case study shows how it may be applied and where to assign new clusters with growing knowledge of customer needs and wants. This approach offer a number of features suitable to smart design in realizing Industry 4.0

Designing a techonolgy for the elderly: Elderband and elderalert

The number of adults aged between 60 and older experiencing fall is alarming.Therefore prevention of fall among elderly assisted by technology is this research priority.There are various fall detection devices and smartphone applications available in the market which all have the same aim, acting as a medium to notify the emergency contacts of the location and time when user falls. The users of those devices and applications are mainly elderly who may have suffered from falls or have difficulties which may lead to more serious injuries.However, there are a number of constraints posed by these available fall detection devices and applications. The fall detection devices are expensive and some require monthly subscription.The devices need to be carried with the user at all times to ensure the fall can be detected.Therefore, this research aims to minimize the mentioned disadvantages with the introduction of ElderBand and ElderAlert. ElderBand is a smart wearable which is lightweight and can be worn by user at all times.ElderAlert is a smartphone application which enables notifications to the emergency contacts in case of a fall. Both ElderBand and ElderAlert are connected via Bluetooth for the fall detection system to work.ElderBand transmit acceleration data continuously to ElderAlert to estimate a fall. It then notifies the emergency contact when a fall is detected. This research provides ideas on how technology could be designed for better quality of life for the elderly

Insights into the Ecological Roles and Evolution of Methyl-Coenzyme M Reductase-Containing Hot Spring Archaea

Several recent studies have shown the presence of genes for the key enzyme associated with archaeal methane/alkane metabolism, methyl-coenzyme M reductase (Mcr), in metagenome-assembled genomes (MAGs) divergent to existing archaeal lineages. Here, we study the mcr-containing archaeal MAGs from several hot springs, which reveal further expansion in the diversity of archaeal organisms performing methane/alkane metabolism. Significantly, an MAG basal to organisms from the phylum Thaumarchaeota that contains mcr genes, but not those for ammonia oxidation or aerobic metabolism, is identified. Together, our phylogenetic analyses and ancestral state reconstructions suggest a mostly vertical evolution of mcrABG genes among methanogens and methanotrophs, along with frequent horizontal gene transfer of mcr genes between alkanotrophs. Analysis of all mcr-containing archaeal MAGs/genomes suggests a hydrothermal origin for these microorganisms based on optimal growth temperature predictions. These results also suggest methane/alkane oxidation or methanogenesis at high temperature likely existed in a common archaeal ancestor

4-[(2,4-Dimethyl-1,3-oxazol-5-yl)meth­yl]-4-hydr­oxy-2-methyl­isoquinoline-1,3(2H,4H)-dione

In the title isoquinolinedione derivative, C16H16N2O4, the piperidine ring in the tetra­hydro­isoquinoline unit adopts a half-boat conformation. The essentially planar oxazole ring [maximum deviation = 0.004 (2) Å] is inclined at a dihedral angle of 36.00 (8)° to the tetra­hydro­isoquinoline unit. In the crystal structure, pairs of inter­molecular C—H⋯O and O—H⋯N inter­actions link the mol­ecules into chains incorporating R 2 2(9) ring motifs. Two neighbouring chains are further inter­connected by inter­molecular C—H⋯O inter­actions into chains two mol­ecules wide along the a axis

AKR1C3 in carcinomas: from multifaceted roles to therapeutic strategies

Aldo-Keto Reductase Family 1 Member C3 (AKR1C3), also known as type 5 17β-hydroxysteroid dehydrogenase (17β-HSD5) or prostaglandin F (PGF) synthase, functions as a pivotal enzyme in androgen biosynthesis. It catalyzes the conversion of weak androgens, estrone (a weak estrogen), and PGD2 into potent androgens (testosterone and 5α-dihydrotestosterone), 17β-estradiol (a potent estrogen), and 11β-PGF2α, respectively. Elevated levels of AKR1C3 activate androgen receptor (AR) signaling pathway, contributing to tumor recurrence and imparting resistance to cancer therapies. The overexpression of AKR1C3 serves as an oncogenic factor, promoting carcinoma cell proliferation, invasion, and metastasis, and is correlated with unfavorable prognosis and overall survival in carcinoma patients. Inhibiting AKR1C3 has demonstrated potent efficacy in suppressing tumor progression and overcoming treatment resistance. As a result, the development and design of AKR1C3 inhibitors have garnered increasing interest among researchers, with significant progress witnessed in recent years. Novel AKR1C3 inhibitors, including natural products and analogues of existing drugs designed based on their structures and frameworks, continue to be discovered and developed in laboratories worldwide. The AKR1C3 enzyme has emerged as a key player in carcinoma progression and therapeutic resistance, posing challenges in cancer treatment. This review aims to provide a comprehensive analysis of AKR1C3’s role in carcinoma development, its implications in therapeutic resistance, and recent advancements in the development of AKR1C3 inhibitors for tumor therapies

Case report: Aortoesophageal fistula—an extremely rare but life-threatening cardiovascular cause of hematemesis

Aortoesophageal fistula (AEF) is an extremely rare cardiovascular etiology of hematemesis and upper gastrointestinal bleeding. As such, its recognition and diagnosis are challenging and may be delayed when such patients present to the emergency department (ED). Without timely surgical intervention, AEF is almost always fatal. Awareness of AEF as a possible diagnosis and consequently early identification of these patients presenting to the ED are therefore crucial in optimizing clinical outcomes. We report a 45-year-old male presenting to the ED with the classical triad of an AEF (Chiari's triad)—midthoracic pain or dysphagia, a sentinel episode of minor hematemesis, then massive hematemesis with risk of exsanguination. The case report highlights the importance of considering the differential diagnosis of AEF when evaluating patients presenting to the ED with hematemesis, especially if they have predisposing risk factors such as prior aortic or esophageal surgeries, aortic aneurysms, or thoracic malignancies. Patients suspected of having AEF should be prioritized for early computed tomography angiography to expedite diagnosis and treatment