Abstract: In this paper, we take a different approach to de Broglie wavelength, as we relate it to relativistic physics. The quantum energy of the photon radiated by a body with de Broglie wavelength, as it moves with velocity v, can be defined within relativistic physics by rest energy E₀. In this way, we can show the connection between the quantum of radiation energy of the body and the rest of energy E₀ and thus combine what has been incompatible so far, namely relativistic and quantum physics. So, here we discuss the unification of relativistic and quantum physics by introducing the factor k that is analog to the Lorentz factor in Einstein's theory of relativity.
Abstract: The use of vegetable oil (or natural ester) as an insulating fluid in electrical transformers is a trend that aims to contribute to environmental preservation since it is biodegradable and non-toxic. Besides, vegetable oil has high flash and combustion points, being considered a fire safety fluid. However, vegetable oil is usually less stable towards oxidation than mineral oil. Both insulating fluids, mineral and vegetable oils, need to be tested periodically according to specific standards. Oxidation stability can be determined by the induction period measured by conductivity method (Rancimat) by monitoring the effectivity of oil’s antioxidant additives, a methodology already developed for food application and biodiesel but still not standardized for insulating fluids. Besides adequate oxidation stability, fluids must be compatible with transformer's construction materials under normal operating conditions to ensure that damage to the oil and parts of the transformer does not occur. ASTM standard and Brazilian normative differ in parameters evaluated, which reveals the need to regulate tests for each oil type. The aim of this study was to assess oxidation stability and compatibility of vegetable oils to suggest the best way to assure a viable performance of vegetable oil as transformer insulating fluid. The determination of the induction period for several vegetable insulating oils from the local market by using Rancimat was carried out according to BS EN 14112 standard, at different temperatures (110, 120, and 130 °C). Also, the compatibility of vegetable oil was assessed according to ASTM and ABNT NBR standards. The main results showed that the best temperature for use in the Rancimat test is 130 °C, which allows a better observation of conductivity change. The compatibility test results presented differences between vegetable and mineral oil standards that should be taken into account in oil testing since materials compatibility and oxidation stability are essential for equipment reliability.
Abstract: Analysis of the human microbiome using metagenomic
sequencing data has demonstrated high ability in discriminating
various human diseases. Raw metagenomic sequencing data require
multiple complex and computationally heavy bioinformatics steps
prior to data analysis. Such data contain millions of short sequences
read from the fragmented DNA sequences and stored as fastq files.
Conventional processing pipelines consist in multiple steps including
quality control, filtering, alignment of sequences against genomic
catalogs (genes, species, taxonomic levels, functional pathways,
etc.). These pipelines are complex to use, time consuming and
rely on a large number of parameters that often provide variability
and impact the estimation of the microbiome elements. Training
Deep Neural Networks directly from raw sequencing data is a
promising approach to bypass some of the challenges associated with
mainstream bioinformatics pipelines. Most of these methods use the
concept of word and sentence embeddings that create a meaningful
and numerical representation of DNA sequences, while extracting
features and reducing the dimensionality of the data. In this paper
we present an end-to-end approach that classifies patients into disease
groups directly from raw metagenomic reads: metagenome2vec. This
approach is composed of four steps (i) generating a vocabulary of
k-mers and learning their numerical embeddings; (ii) learning DNA
sequence (read) embeddings; (iii) identifying the genome from which
the sequence is most likely to come and (iv) training a multiple
instance learning classifier which predicts the phenotype based on
the vector representation of the raw data. An attention mechanism
is applied in the network so that the model can be interpreted,
assigning a weight to the influence of the prediction for each genome.
Using two public real-life data-sets as well a simulated one, we
demonstrated that this original approach reaches high performance,
comparable with the state-of-the-art methods applied directly on
processed data though mainstream bioinformatics workflows. These
results are encouraging for this proof of concept work. We believe
that with further dedication, the DNN models have the potential to
surpass mainstream bioinformatics workflows in disease classification
tasks.
Abstract: In this experimental study, the behaviors of Mixed Oxidant solution components (MOS) and sodium hypochlorite (HYPO) as the most commonly applied surface disinfectant were compared through the effectiveness of chlorine disinfection as a function of the contact time and residual chlorine. In this regard, the variation of pH, free available chlorine (FAC) concentration, and electric conductivity (EC) of disinfection solutions in different concentrations were monitored over 48 h contact time. In parallel, the plant stress activated by chlorine-based disinfectants was assessed by comparing MOS and HYPO. The elements of pH and EC in the plant-soil and their environmental impacts, spread by disinfection solutions were analyzed through several concentrations of FAC including 500 mg/L, 1000 mg/L, and 5000 mg/L in irrigated water. All the experiments were carried out at the service station of Sant Cugat, Spain. The outcomes indicated lower pH and higher durability of MOS than HYPO at the same concentration of FAC which resulted in promising stability of FAC within MOS. Furthermore, the pH and EC value of plant-soil irrigated by NaOCl solution were higher than that of MOS solution at the same FAC concentration. On-site generation of MOS as a safe chlorination option might be considered an imaginary future of smart cities.
Abstract: This paper explores what effective leadership is being employed in the engineering, technology, and construction (ETC) industry. Organizations need to understand what character traits are being used and what leadership styles work to promote sustainability and improve the triple bottom line. This paper looks at multiple publications on leadership and character traits effective for managers and leaders in the ETC industry. The ETC industry is a trillion-dollar industry, and understanding ways to improve leadership is vital for organizations' successful outcomes. With improvements to the managerial and leadership, there could be ways for organizations to profit more and cut down on cost costs. Finding ways to improve motivation can help organizations improve safety, improve culture, and increase employee motivation. From the research, this paper has found that situational leadership, transformational, and transactional are the most effective leadership styles that individuals can use in the ETC industry for leadership. Character traits that are the most effective have been identified in this research paper. This research has contributed to the ways individuals who start in the engineering and technology industry can improve upon their leadership skills as they are promoted into managerial and leadership roles. The need for managerial positions in the ETC industry, such as project and construction managers, to improve is vital for successful outcomes and creating a high-level performance. The study helps provide a gap in the limited research available to improve ETC leadership for all organizations' present and future.
Abstract: The ancestral relationship between humans and geographical environment has long been at the center of an interdisciplinary dialogue, which sees one of its main research nodes in the relationship between memory and places. Given its deep complexity, this symbiotic connection continues to look for a proper definition that appears increasingly negotiated by different disciplines. Numerous fields of knowledge are involved, from anthropology to semiotics of space, from photography to architecture, up to subjects traditionally far from these reasonings. This is the case of Design of Communication, a young discipline, now confident in itself and its objectives, aimed at finding and investigating original forms of visualization and representation, between sedimented knowledge and new technologies. In particular, Design of Communication for the Territory offers an alternative perspective to the debate, encouraging the reactivation and reconstruction of the memory of places. Recognizing mnemotopes as a cultural object of vertical interpretation of the memory-place relationship, design can become a real mediator of the territorial fixation of memories, making them increasingly accessible and perceptible, contributing to build a topography of memory. According to a mnemotopic vision, Communication Design can support the passage from a memory in which the observer participates only as an individual to a collective form of memory. A mnemotopic form of Communication Design can, through geolocation and content map-based systems, make chronology a topography rooted in the territory and practicable; it can be useful to understand how the perception of the memory of places changes over time, considering how to insert them in the contemporary world. Mnemotopes can be materialized in different format of translation, editing and narration and then involved in complex systems of communication. The memory of places, therefore, if stabilized by the tools offered by Communication Design, can make visible ruins and territorial stratifications, illuminating them with new communicative interests that can be shared and participated.
Abstract: During COVID-19, the depression rate has increased dramatically. Young adults are most vulnerable to the mental health effects of the pandemic. Lower-income families have a higher ratio to be diagnosed with depression than the general population, but less access to clinics. This research aims to achieve early depression detection at low cost, large scale, and high accuracy with an interdisciplinary approach by incorporating clinical practices defined by American Psychiatric Association (APA) as well as multimodal AI framework. The proposed approach detected the nine depression symptoms with Natural Language Processing sentiment analysis and a symptom-based Lexicon uniquely designed for young adults. The experiments were conducted on the multimedia survey results from adolescents and young adults and unbiased Twitter communications. The result was further aggregated with the facial emotional cues analyzed by the Convolutional Neural Network on the multimedia survey videos. Five experiments each conducted on 10k data entries reached consistent results with an average accuracy of 88.31%, higher than the existing natural language analysis models. This approach can reach 300+ million daily active Twitter users and is highly accessible by low-income populations to promote early depression detection to raise awareness in adolescents and young adults and reveal complementary cues to assist clinical depression diagnosis.
Abstract: The built-up area is a significant proxy to measure regional economic growth and reflects the Gross Provincial Product (GPP). However, an up-to-date and reliable database of built-up areas is not always available, especially in developing countries. The cloud-based geospatial analysis platform such as Google Earth Engine (GEE) provides an opportunity with accessibility and computational power for those countries to generate the built-up data. Therefore, this study aims to extract the built-up areas in Eastern Economic Corridor (EEC), Thailand using day and nighttime satellite imagery based on GEE facilities. The normalized indices were generated from Landsat 8 surface reflectance dataset, including Normalized Difference Built-up Index (NDBI), Built-up Index (BUI), and Modified Built-up Index (MBUI). These indices were applied to identify built-up areas in EEC. The result shows that MBUI performs better than BUI and NDBI, with the highest accuracy of 0.85 and Kappa of 0.82. Moreover, the overall accuracy of classification was improved from 79% to 90%, and error of total built-up area was decreased from 29% to 0.7%, after night-time light data from the Visible and Infrared Imaging Suite (VIIRS) Day Night Band (DNB). The results suggest that MBUI with night-time light imagery is appropriate for built-up area extraction and be utilize for further study of socioeconomic impacts of regional development policy over the EEC region.
Abstract: Autonomous vehicles look set to drastically alter the way we move people and goods, in urban as well as rural areas. However, little has been written about Africa with this regard. Moreover, in order for this new technology to be adopted, user acceptance is vital. The current research examines the user acceptance of autonomous minibus shuttles, as a solution for first/last mile public transport in Pretoria, South Africa. Of the respondents surveyed, only 2.31% perceived them as not useful. Respondents showed more interest in using these shuttles in combination with the bus rapid transit system (75.4%) as opposed to other modes of public transportation (40%). The significance of these findings is that they can help ensure that the implementation of autonomous public transport in South Africa is adapted to the local user. Furthermore, these findings could be adapted for other South African cities and other cities across the continent.
Abstract: In parallel with the appearance of new materials, brick masonry had and still has an essential part of the construction market today, with new technical challenges in designing bricks to meet additional requirements. Being used in structural applications, predicting the performance of clay brick masonry allows a significant cost reduction, in terms of practical experimentation. The behavior of masonry walls depends on the behavior of their elementary components, such as bricks, joints, and coatings. Therefore, it is necessary to consider it at different scales (from the scale of the intrinsic material to the real scale of the wall) and then to develop appropriate models, using numerical simulations. The work presented in this paper focuses on the mechanical characterization of the terracotta material at ambient temperature. As a result, the static Young’s modulus obtained from the flexural test shows different values in comparison with the compression test, as well as with the dynamic Young’s modulus obtained from the Impulse excitation of vibration test. Moreover, the Young's modulus varies according to the direction in which samples are extracted, where the values in the extrusion direction diverge from the ones in the orthogonal directions. Based on these results, hollow bricks can be considered as transversely isotropic bimodulus material.
Abstract: Air Defense Systems contain high-value assets that are
expected to fulfill their mission for several years - in many cases,
even decades - while operating in a fast-changing, technology-driven
environment. Thus, it is paramount that decision-makers can assess
how effective an Air Defense System is in the face of new developing
threats, as well as to identify the bottlenecks that could jeopardize
the security of the airspace of a country. Given the broad extent
of activities and the great variety of assets necessary to achieve
the strategic objectives, a systems approach was taken in order to
delineate the core requirements and the physical architecture of an
Air Defense System. Then, value-focused thinking helped in the
definition of the measures of effectiveness. Furthermore, analytical
methods were applied to create a formal structure that preliminarily
assesses such measures. To validate the proposed methodology, a
powerful simulation was also used to determine the measures of
effectiveness, now in more complex environments that incorporate
both uncertainty and multiple interactions of the entities. The results
regarding the validity of this methodology suggest that the approach
can support decisions aimed at enhancing the capabilities of Air
Defense Systems. In conclusion, this paper sheds some light on
how consolidated approaches of Systems Engineering and Operations
Research can be used as valid techniques for solving problems
regarding a complex and yet vital matter.
Abstract: Innovation is the key element of economic development and a key factor in social processes. Technical innovations can be identified as prerequisites and causes of social change and cannot be created without the renewal of society. The study of social innovation can be characterised as one of the significant research areas of our day. The study’s aim is to identify the process of social innovation, which can be defined by input, transformation, and output factors. This approach divides the social innovation process into three parts: situation analysis, implementation, follow-up. The methods associated with each stage of the process are illustrated by the chronological line of social innovation. In this study, we have sought to present methodologies that support long- and short-term decision-making that is easy to apply, have different complementary content, and are well visualised for different user groups. When applying the methods, the reference objects are different: county, district, settlement, specific organisation. The solution proposed by the study supports the development of a methodological combination adapted to different situations. Having reviewed metric and conceptualisation issues, we wanted to develop a methodological combination along with a change management logic suitable for structured support to the generation of social innovation in the case of a locality or a specific organisation. In addition to a theoretical summary, in the second part of the study, we want to give a non-exhaustive picture of the two counties located in the north-eastern part of Hungary through specific analyses and case descriptions.
Abstract: Spintronic, also termed spin electronics or spin transport electronics, is a kind of new technology, which exploits the two fundamental degrees of freedom- spin-state and charge-state of electrons to enhance the operational speed for the data storage and transfer efficiency of the device. Thus, it seems an encouraging technology to combat most of the prevailing complications in orthodox electron-based devices. This novel technology possesses the capacity to mix the semiconductor microelectronics and magnetic devices’ functionalities into one integrated circuit. Traditional semiconductor microelectronic devices use only the electronic charge to process the information based on binary numbers, 0 and 1. Due to the incessant shrinking of the transistor size, we are reaching the final limit of 1 nm or so. At this stage, the fabrication and other device operational processes will become challenging as the quantum effect comes into play. In this situation, we should find an alternative future technology, and spintronic may be such technology to transfer and store information. This review article provides a detailed discussion of the spintronic technology: fundamentals, materials, devices, circuits, challenges, and current research trends. At first, the fundamentals of spintronics technology are discussed. Then types, properties, and other issues of the spintronic materials are presented. After that, fabrication and working principles, as well as application areas and advantages/disadvantages of spintronic devices and circuits, are explained. Finally, the current challenges, current research areas, and prospects of spintronic technology are highlighted. This is a new paradigm of electronic cum magnetic devices built on the charge and spin of the electrons. Modern engineering and technological advances in search of new materials for this technology give us hope that this would be a very optimistic technology in the upcoming days.
Abstract: Clustering is an unsupervised learning technique for aggregating data objects into meaningful classes so that intra cluster similarity is maximized and inter cluster similarity is minimized in data mining. However, no single clustering algorithm proves to be the most effective in producing the best result. As a result, a new challenging technique known as the cluster ensemble approach has blossomed in order to determine the solution to this problem. For the cluster analysis issue, this new technique is a successful approach. The cluster ensemble's main goal is to combine similar clustering solutions in a way that achieves the precision while also improving the quality of individual data clustering. Because of the massive and rapid creation of new approaches in the field of data mining, the ongoing interest in inventing novel algorithms necessitates a thorough examination of current techniques and future innovation. This paper presents a comparative analysis of various cluster ensemble approaches, including their methodologies, formal working process, and standard accuracy and error rates. As a result, the society of clustering practitioners will benefit from this exploratory and clear research, which will aid in determining the most appropriate solution to the problem at hand.
Abstract: Additive Manufacturing processes are becoming increasingly established in the industry for the economic production of complex prototypes and functional components. Laser beam melting (LBM), the most frequently used Additive Manufacturing technology for metal parts, has been gaining in industrial importance for several years. The LBM process chain – from material storage to machine set-up and component post-processing – requires many manual operations. These steps often depend on the manufactured component and are therefore not standardized. These operations are often not performed in a standardized manner, but depend on the experience of the machine operator, e.g., levelling of the build plate and adjusting the first powder layer in the LBM machine. This lack of standardization limits the reproducibility of the component quality. When processing metal powders with inhalable and alveolar particle fractions, the machine operator is at high risk due to the high reactivity and the toxic (e.g., carcinogenic) effect of the various metal powders. Faulty execution of the operation or unintentional omission of safety-relevant steps can impair the health of the machine operator. In this paper, all the steps of the LBM process chain are first analysed in terms of their influence on the two aforementioned challenges: reproducibility and work safety. Standardization to avoid errors increases the reproducibility of component quality as well as the adherence to and correct execution of safety-relevant operations. The corresponding lean method 5S will therefore be applied, in order to develop approaches in the form of recommended actions that standardize the work processes. These approaches will then be evaluated in terms of ease of implementation and their potential for improving reproducibility and work safety. The analysis and evaluation showed that sorting tools and spare parts as well as standardizing the workflow are likely to increase reproducibility. Organizing the operational steps and production environment decreases the hazards of material handling and consequently improves work safety.
Abstract: The global sanitation workforce bridges the gap between sanitation infrastructure and the provision of sanitation services through essential public service work. Manual pit emptiers often perform the work at the cost of their dignity, safety, and health as their work requires repeated heavy physical activities such as lifting, carrying, pulling, and pushing. This exposes them to occupational and environmental health hazards and risking illness, injury, and death. The study will extend the studies by presenting occupational health risks and suggestions for improvement in informal settlements of Nairobi, Kenya. This is a qualitative study conducted among sanitation stakeholders in Korogocho, Mukuru and Kibera informal settlements in Nairobi. Data were captured using digital voice recorders, transcribed and thematically analysed. The discussion notes were further supported by observational notes made during the interviews. These formed the basis for a robust picture of occupational health of manual pit emptiers; a lack or inappropriate use of protective clothing, and prolonged duration of working hours were described to contribute to the occupational health hazard. To continue working, manual pit emptiers had devised coping strategies which include working in groups, improvised protective clothing, sharing the available protective clothing, working at night and consuming alcohol drinks while at work. Many of these strategies are detrimental to their health. Occupational health hazards among pit emptiers are key for effective working and is as a result of a lack of collaboration amongst stakeholders linked to health, safety and lack of PPE of pit emptiers. Collaborations amongst sanitation stakeholders is paramount for health, safety, and in ensuring the provision and use of personal protective devices.
Abstract: A magnetic induction based underwater communication
link is evaluated using an analytical model and a custom
Finite-Difference Time-Domain (FDTD) simulation tool. The
analytical model is based on the Sommerfeld integral, and a full-wave
simulation tool evaluates Maxwell’s equations using the FDTD
method in cylindrical coordinates. The analytical model and FDTD
simulation tool are then compared and used to predict the system
performance for various transmitter depths and optimum frequencies
of operation. To this end, the system bandwidth, signal to noise
ratio, and the magnitude of the induced voltage are used to estimate
the expected channel capacity. The models show that in seawater, a
relatively low-power and small coils may be capable of obtaining a
throughput of 40 to 300 kbps, for the case where a transmitter is at
depths of 1 to 3 m and a receiver is at a height of 1 m.
Abstract: Essential oils are one of the most important groups of biologically active substances present in plants. Due to the chemical diversity of components, essential oils and their preparations have a wide spectrum of pharmacological action. They have bactericidal, antiviral, fungicidal, antiprotozoal, anti-inflammatory, spasmolytic, sedative and other activities. They are expectorant, spasmolytic, sedative, hypotensive, secretion enhancing, antioxidant remedies. Based on preliminary pharmacological studies, we have developed a formulation called “Phytobiotic” containing essential oils, a feed additive for poultry as an alternative to antibiotics. Phytobiotic is a water-soluble powder containing a composition of essential oils of thyme, clary, monarda and auxiliary substances: dry extract of liquorice and inhalation lactose. On this stage of research, the goal was to study the chemical composition of provided phytobiotic, identify the main substances and determine their quantity, investigate the biological activity of phytobiotic through in vitro and in vivo studies. Using gas chromatography-mass spectrometry, 38 components were identified in phytobiotic, representing acyclic-, monocyclic-, bicyclic-, and sesquiterpenes. Together with identification of main active substances, their quantitative content was determined, including acyclic terpene alcohol β-linalool, acyclic terpene ketone linalyl acetate, monocyclic terpenes: D-limonene and γ-terpinene, monocyclic aromatic terpene thymol. Provided phytobiotic has pronounced and at the same time broad spectrum of antibacterial activity. In the cell model, phytobiotic showed weak antioxidant activity, and it was stronger in the ORAC (chemical model) tests. Meanwhile anti-inflammatory activity was also observed. When fowls were supplied feed enriched with phytobiotic, it was observed that gained weight of the chickens in the experimental group exceeded the same data for the control group during the entire period of the experiment. The survival rate of broilers in the experimental group during the growth period was 98% compared to -94% in the control group. As a result of conducted researches probable four different mechanisms which are important for the action of phytobiotics were identified: sensory, metabolic, antioxidant and antibacterial action. General toxic, possible local irritant and allergenic effects of phytobiotic were also investigated. Performed assays proved that formulation is safe.
Abstract: In this paper, we propose a miniaturized and wideband patch antenna for C-band applications. The antenna miniaturization is obtained by loading shorting vias along one patch edge. At the same time, the wideband performance is achieved by combining two resonances using one feed line. The measured results reveal that the antenna covers the frequency band 4.32 GHz to 6.52 GHz (41%) with a peak gain and a peak efficiency of 5.5 dBi and 87%, respectively. The antenna occupies a relatively small size of only 26 x 22 x 5.6 mm3, making it suitable for compact wireless devices requiring a stable unidirectional gain over a wide frequency range.
Abstract: The toxicity of lead associated with the lifecycle of perovskite solar cells (PSCs( is a serious concern which may prove to be a major hurdle in the path toward their commercialization. The current proposed lead-free PSCs including Ag(I), Bi(III), Sb(III), Ti(IV), Ge(II), and Sn(II) low-toxicity cations are still plagued with the critical issues of poor stability and low efficiency. This is mainly because of their chemical stability. In the present research, utilization of all inorganic CsSnGeI3 based materials offers the advantages to enhance resistance of device to degradation, reduce the cost of cells, and minimize the carrier recombination. The presence of inorganic halide perovskite improves the photovoltaic parameters of PCSs via improved surface coverage and stability. The inverted structure of simulated devices using a 1D simulator like solar cell capacitance simulator (SCAPS) version 3308 involves TCOHTL/Perovskite/ETL/Au contact layer. PEDOT:PSS, PCBM, and CsSnGeI3 used as hole transporting layer (HTL), electron transporting layer (ETL), and perovskite absorber layer in the inverted structure for the first time. The holes are injected from highly stable and air tolerant Sn0.5Ge0.5I3 perovskite composition to HTM and electrons from the perovskite to ETL. Simulation results revealed a great dependence of power conversion efficiency (PCE) on the thickness and defect density of perovskite layer. Here the effect of an increase in operating temperature from 300 K to 400 K on the performance of CsSnGeI3 based perovskite devices is investigated. Comparison between simulated CsSnGeI3 based PCSs and similar real testified devices with spiro-OMeTAD as HTL showed that the extraction of carriers at the interfaces of perovskite absorber depends on the energy level mismatches between perovskite and HTL/ETL. We believe that optimization results reported here represent a critical avenue for fabricating the stable, low-cost, efficient, and eco-friendly all-inorganic Cs-Sn-Ge based lead-free perovskite devices.