Sci, Volume 4, Issue 4 (December 2022) – 16 articles

Whilst several methods exist to provide sample estimates of the probability distribution function at several points, for the probability density of continuous stochastic variables, only a gross representation through the histogram is typically used. It is shown that the newly introduced concept of knowable moments (K-moments) can provide smooth empirical representations of the distribution function, which in turn can yield point and interval estimates of the density function at a large number of points or even at any arbitrary point within the range of the available observations. The proposed framework is simple to apply and is illustrated with several applications for a variety of distribution functions. Full article

Technical systems generate an increasing amount of data as integrated sensors become more available. Even so, data are still often scarce because of technical limitations of sensors, an expensive labelling process, or rare concepts, such as machine faults, which are hard to capture. Data scarcity leads to incomplete information about a concept of interest. This contribution details causes and effects of scarce data in technical systems. To this end, a typology is introduced which defines different types of incompleteness. Based on this, machine learning and information fusion methods are presented and discussed that are specifically designed to deal with scarce data. The paper closes with a motivation and a call for further research efforts into a combination of machine learning and information fusion. Full article

In this work, briquettes from mattress waste are manufactured and the acoustic properties of the materials produced are checked. Briquettes are made at temperatures between 170 and 185 °C using waste from viscoelastic memory foam (VMF) and applying pressures between 25 and 75 MPa. Later, the properties of the materials such as their bulk density, porosity, and compaction factor are measured. Afterwards, the materials are subjected to a test to determine the sound reduction index at different frequencies. This is completed with a home-made system in which the acoustic signal is compared in the presence and absence of the mattress briquettes using MATLAB^® software (Mathworks, Natick, MA, USA) for signal computing. The results are also compared with a reference acoustic insulation material. The runs show that the materials produced from mattress waste are able to reduce the intensity of sound in a similar way to commercial materials. In fact, reduction indices with prepared briquettes are much higher in the frequencies that most affect the human ear, compared to a reference insulating material. Full article

This paper addresses the management of digital–informational transformation of industrial enterprises. Any transformation requires the coordinated action of several independent actors. Similarly, the digital–informational transformation required for the fourth industrial revolution (i.e., Industry 4.0) requires the involvement of multiple actors from the public and private sectors. This applies to an individual company as well as to the entire sector, regardless of the desired level of transformation. The increasing dissolution of boundaries between industrial and non-industrial actors is therefore essential for Industry 4.0. This paper addresses the above dissolution activities, focusing on cross-company networks and management issues. The management aspects of the following factors are examined: culture change, strategies, degree of digitalization, degree of networking, Internet of Things, digital ecosystems, human resources, organizational development, hierarchies, cross-functional collaboration, cost drivers, innovation pressures, supply chains, enterprise resource planning systems and corporate acquisitions/mergers. Based on the findings on the above factors, a management-driven model of the “transformation to Industry 4.0” for manufacturing companies is presented and discussed. This work thus complements the existing literature on Industry 4.0, as the majority of the literature on Industry 4.0 deals with technical problem solving at the field level. Full article

Artificial neural networks in their various different forms convincingly dominate machine learning of the present day. Nevertheless, the manner in which these networks are trained, in particular by using end-to-end backpropagation, presents a major limitation in practice and hampers research, and raises questions with regard to the very fundamentals of the learning algorithm design. Motivated by these challenges and the contrast between the phenomenology of biological (natural) neural networks that artificial ones are inspired by and the learning processes underlying the former, there has been an increasing amount of research on the design of biologically plausible means of training artificial neural networks. In this paper we (i) describe a biologically plausible learning method that takes advantage of various biological processes, such as Hebbian synaptic plasticity, and includes both supervised and unsupervised elements, (ii) conduct a series of experiments aimed at elucidating the advantages and disadvantages of the described biologically plausible learning as compared with end-to-end backpropagation, and (iii) discuss the findings which should serve as a means of illuminating the algorithmic fundamentals of interest and directing future research. Among our findings is the greater resilience of biologically plausible learning to data scarcity, which conforms to our expectations, but also its lesser robustness to additive, zero mean Gaussian noise. Full article

Physical activity is a crucial factor for maintaining not only physical health status, but vast amounts of research have shown its link with better mental health. Supporting the use of gyms for the safety of its practitioners is vital in the new norm and living with COVID-19. Therefore, in this study we show research supporting the development of a framework for a Total Safe-Care Fitness Solution based on a multimodal COVID-19 tracking system integrating computer vision and data from wearable sensors. We propose a framework with three areas that need to be integrated: a COVID-19 vaccine and health status recognition system (QR code scan prior to entry to the gym, and physiological signals monitored by a smart-band and a health questionnaire filled in prior to entry to the gym); an accident detection system (video and smart-band based); and a gym-user digital tracking system (CCTV and smart-band based). We show the proposed architecture for the integration of these systems and provide practical tips on how to implement it in testbeds for feasibility testing. To the best of our knowledge, this is the first proposed COVID-19 tracking system of use in gyms that includes a predictive model for accident detection for safer exercise participation through health monitoring. Full article

The goal of this paper is to provide an initial assessment of water-vapor feedback (WVF) in humid urban heat island (UHI) environments based on temperature difference data. To achieve this, a novel temperature difference WVF model was developed that can analyze global and UHI local temperature difference data. Specifically, the model was applied to a comparative temperature literature study of similar cities located in humid versus dry climates. The literature study found that the daytime UHI ΔT was observed to be 3.3 K higher in humid compared to dry climates when averaged over thirty-nine cities. Since the direct measurement of WVF in UHI areas could prove challenging due to variations in the temperature lapse rates from tall buildings, modeling provides an opportunity to make a preliminary assessment where measurements may be difficult. Thus, the results provide the first available UHI ΔT WVF model assessment. The preliminary results find local water-vapor feedback values for wet-biased cities of 3.1 Wm⁻²K⁻¹, 3.4 Wm⁻²K⁻¹, and 4 Wm⁻²K⁻¹ for 5 °C, 15 °C, and 30 °C UHI average temperatures, respectively. The temperature difference model could also be used to reproduce literature values. This capability helps to validate the model and its findings. Heatwave assessments are also discussed, as they are strongly affected by UHI water-vapor feedback and support the observation that humid regions amplify heat higher than UHIs in dry regions, exacerbating heatwave problems. Furthermore, recent studies have found that urbanization contributions to global warming more than previously anticipated. Therefore, cities in humid environments are likely larger contributors to such warming trends compared to cities in dry environments. These preliminary modeling results show concern for a strong local UHI water-vapor feedback issue for cities in humid environments, with results possibly over a factor of two higher than the global average. This assessment also indicates that albedo management would likely be an effective way to reduce the resulting WVF temperature increase. Full article

Hydrogels based on mixed zirconium/europium ions and benzene tricarboxylic acid were synthesized by hydrothermal reaction. A solid glass-like material is formed upon drying, showing strong reddish luminescence. The system was characterized by solid-state nuclear magnetic resonance, thermal analyses, and infrared spectroscopy. The results reveal the amorphous character of the structure and the presence of at least four types of binding modes between the metal oxide clusters and benzene tricarboxylic acid. On the other hand, thermogravimetric analysis (TGA) showed high thermal stability, with the material decomposing at temperatures higher than 500 °C. The combination of intense Eu³⁺ luminescence with large thermal stability makes this material a strong candidate for application as a luminescent red marker for gunshot residue (GSR). As proof of concept, we show the feasibility of this application by performing shooting tests using our compound as a GSR marker. After the shots, the residual luminescent particles could be visualized in the triggered cartridge, inner the muzzle of the firearm, and a lower amount on the hands of the shooter, using a UV lamp (λ = 254 nm). Remarkably, our results also show that the Eu³⁺ emission for the GSR is very similar to that observed for the original solid material. These characteristics are of huge importance since they provide a chance to use smaller amounts of the marker in the ammunition, lowering the costs of potential industrial manufacturing processes. Full article

The semantic web invests in systems that work collaboratively. In this article we show that the collaborative way is not enough, because the system must ‘understand’ the data resources that are provided to it, to organize them in the direction indicated by the system’s core, the algorithm. In order for intelligent systems to imitate human cognition, in addition to technical skills to model algorithms, we show that the specialist needs a good knowledge of the principles that explain how human language constructs concepts. The content of this article focuses on the principles of the conceptual formation of language, pointing to aspects related to the environment, to logical reasoning and to the recursive process. We used the strategy of superimposing the dynamics of human cognition and intelligent systems to open new frontiers regarding the formation of concepts by human cognition. The dynamic aspect of the recursion of the human linguistic process integrates visual, auditory, tactile input stimuli, among others, to the central nervous system, where meaning is constructed. We conclude that the human linguistic process involves axiomatic (contextual/biological) and logical principles, and that the dynamics of the relationship between them takes place through recursive structures, which guarantee the construction of meanings through long-range correlation under scale invariance. Recursion and cognition are, therefore, interdependent elements of the linguistic process, making it a set of sui generis structures that evidence that the essence of language, whether natural or artificial, is a form and not a substance. Full article

Artesunate (ART), a plant based semi-synthetic antimalarial drug, is emerging as a new class of effective cancer chemotherapeutics. However, the dosage of ART required to have an anti-cancer effect on cancer cells is greater than that needed to exterminate malarial parasites. The goal of this study was to develop an effective combination therapy to reduce the dose-dependent side effects of ART both in vitro and in vivo. In our study, 4-phenylbutyrate (4-PB), a histone deacetylase inhibitor (HDAC), exhibited significant synergistic induction of apoptosis in MCF-7 cells in combination with ART. The IC₅₀ of ART decreased significantly from 55.56 ± 5.21 µM to 24.71 ± 3.44 µM in MCF-7 cells. ART treatment increased cellular oxidative stress, and the resulting generation of intracellular reactive oxygen species (ROS) caused extensive DNA damage in the cell. The extent of ROS production and cell cycle arrest were further enhanced by 4-PB treatment. In further investigation, we found that 4-PB attenuated mRNA expression of crucial DNA damage response (DDR) elements of the nonhomologous end-joining (NHEJ) pathway, consequently enhancing the DNA damaging effect of ART. Furthermore, the combination therapy resulted in improvement in the life expectancy of the treated mice and a prominent reduction in tumour volume without interfering with the normal biochemical, haematological and histological parameters of the mice. Overall, our study revealed a novel combination therapy in which 4-PB potentiated the cytotoxicity of ART synergistically and provided a promising combination drug for effective cancer therapy. Full article

Functional analysis is a well-developed field in the discipline of Mathematics, which provides unifying frameworks for solving many problems in applied sciences and engineering. In particular, several important topics (e.g., spectrum estimation, linear prediction, and wavelet analysis) in signal processing had been initiated and developed through collaborative efforts of engineers and mathematicians who used results from Hilbert spaces, Hardy spaces, weak topology, and other topics of functional analysis to establish essential analytical structures for many subfields in signal processing. This paper presents a concise tutorial for understanding the theoretical concepts of the essential elements in functional analysis, which form a mathematical framework and backbone for central topics in signal processing, specifically statistical and adaptive signal processing. The applications of these concepts for formulating and analyzing signal processing problems may often be difficult for researchers in applied sciences and engineering, who are not adequately familiar with the terminology and concepts of functional analysis. Moreover, these concepts are not often explained in sufficient details in the signal processing literature; on the other hand, they are well-studied in textbooks on functional analysis, yet without emphasizing the perspectives of signal processing applications. Therefore, the process of assimilating the ensemble of pertinent information on functional analysis and explaining their relevance to signal processing applications should have significant importance and utility to the professional communities of applied sciences and engineering. The information, presented in this paper, is intended to provide an adequate mathematical background with a unifying concept for apparently diverse topics in signal processing. The main objectives of this paper from the above perspectives are summarized below: (1) Assimilation of the essential information from different sources of functional analysis literature, which are relevant to developing the theory and applications of signal processing. (2) Description of the underlying concepts in a way that is accessible to non-specialists in functional analysis (e.g., those with bachelor-level or first-year graduate-level training in signal processing and mathematics). (3) Signal-processing-based interpretation of functional-analytic concepts and their concise presentation in a tutorial format. Full article

Industry 4.0 is one of the most influential trends in manufacturing as of now. Coined as the fourth industrial revolution it promises to overthrow entrenched structures opening new pathways for innovation and value creation. Like all revolutions, it is accompanied by disruption and uncertainty. Consequently, many manufacturing companies struggle to adopt an Industry 4.0 perspective that benefits their performance. Hence, our goal was to develop a method for increasing firm performance through Industry 4.0. A key factor was to focus on the entire company as a socio-technical system to depict the numerous interactions between people, technology, and business/organization. To realize the method, we combined consortium research, design science, and method engineering. We gathered comprehensive data from workshops, interviews, and five case studies, which we used to develop the method. It consists of four phases: a maturity model to determine the status quo, a procedure to derive a target position, a pattern-based approach to design the socio-technical system, and a procedure to define a transformation setup. Our approach is the first to combine maturity models with foresight and extensive prescriptive knowledge. For practitioners, the method gives orientation for the future-oriented planning of their transformation processes. Full article

Helmet designs have not only been used successfully in integrative medicine for decades in acupuncture research, but they are also increasingly being used in the field of transcranial photobiomodulation (TPBM), primarily in so-called mental diseases. The author of this article has been dealing with developed helmet constructions for neuromonitoring for over 25 years and not only gives an overview of the development of these methods, but also shows new methods and perspectives. The future of this branch of research certainly lies in the development of so-called sensor-controlled therapy helmets for TPBM. Full article

In this study, we demonstrate that an open-domain conversational system trained on idioms or figurative language generates more fitting responses to prompts containing idioms. Idioms are a part of everyday speech in many languages and across many cultures, but they pose a great challenge for many natural language processing (NLP) systems that involve tasks such as information retrieval (IR), machine translation (MT), and conversational artificial intelligence (AI). We utilized the Potential Idiomatic Expression (PIE)-English idiom corpus for the two tasks that we investigated: classification and conversation generation. We achieved a state-of-the-art (SoTA) result of a 98% macro F1 score on the classification task by using the SoTA T5 model. We experimented with three instances of the SoTA dialogue model—the Dialogue Generative Pre-trained Transformer (DialoGPT)—for conversation generation. Their performances were evaluated by using the automatic metric, perplexity, and a human evaluation. The results showed that the model trained on the idiom corpus generated more fitting responses to prompts containing idioms 71.9% of the time in comparison with a similar model that was not trained on the idiom corpus. We have contributed the model checkpoint/demo/code to the HuggingFace hub for public access. Full article

The common method for producing casting molds for the fabrication of polydimethylsiloxane (PDMS) chips is standard photolithography. This technique offers high resolution from hundreds of nanometers to a few micrometers. However, this mold fabrication method is costly, time-consuming, and might require clean room facilities. Additionally, there is a need for non-micromechanics experts, who do not have specialized equipment to easily and quickly prototype chips themselves. Simple, so-called, makerspace technologies are increasingly being explored as alternatives that have potential to enable anyone to fabricate microfluidic structures. We therefore tested simple fabrication methods for a PDMS-based microfluidic device. On the one hand, channels were replicated from capillaries and tape. On the other hand, different mold fabrication methods, namely laser cutting, fused layer 3D printing, stereolithographic 3D printing, and computer numerical control (CNC) milling, were validated in terms of machine accuracy and tightness. Most of these methods are already known, but the incorporation and retention of particles with sizes in the micrometer range have been less investigated. We therefore tested two different types of particles, which are actually common carriers for the immobilization of enzymes, so that the resulting reactor could ultimately be used as a microfluidic bioreactor. Furthermore, CNC milling provide the most reliable casting mold fabrication method. After some optimization steps with regard to manufacturing settings and post-processing polishing, the chips were tested for the retention of two different particle types (spherical and non-spherical particles). In this way, we successfully tested the obtained PDMS-based microfluidic chips for their potential applicability as (bio)reactors with enzyme immobilization carrier beads. Full article

Following an agronomic approach for the Ca enrichment of Rocha pears, this study aimed to assess the interactions between mineral nutrients in fruit tissues at harvest and after storage for 5 months and to characterize the implications on the profile of sugars and fatty acids (FA). A total of seven foliar sprays (with concentrations of 0.1–0.6 kg·ha⁻¹ Ca(NO₃)₂ and 0.8–8 kg·ha⁻¹ CaCl₂) were applied to pear trees. After harvest, the fruits were stored for 5 months, in environmentally controlled chambers, and the mineral contents in five regions (on the equatorial section) of the fruits were assessed, while the sugar and FA content were quantified. For both dates, all foliar sprayed treatments, at different extends, increased Ca content in the center and near the epidermis of Rocha pear fruits and the levels of K, Mn, Fe, Zn and Cu also varied. At harvest, the Ca treatments did not affect the levels of sucrose, glucose, fructose and sorbitol and, after storage, their concentrations remained higher in Ca-treated fruits. Additionally, the tendency of the relative proportions of FA was C18:2 > C18:1 > C16:0 > C18:3 > C18:0 > chains inferior to 16 C (<16:0), but after storage it was C18:2 > C16:0 > C18:3 > C18:0 > C18:1 > chains inferior to 16 C (<16:0). It is concluded that the heterogeneous distribution of Ca in the tissues of Rocha pear fruits results from its absorption in the peel after Ca(NO₃)₂ and CaCl₂ sprays and from the xylemic flux in the core prior to maturity. Additionally, the hydrolysis of complex polysaccharides affects the contents of simpler sugars during maturation, ripening and senescence, while storage decreases the amount of total fatty acids (TFA), but the double bond index (DBI) indicate that cell membrane fluidity remains unaffected. Full article