There are many cases in the construction industry when decision making related to the specific elements of the single-family houses is left to the property owners. The choice of the internal stairs design is one of them. While stair-related injuries are among the most common reasons for children’s accidents at home, stair safety awareness in different target groups becomes an important matter to prevent kid injuries in domestic environments. Eleven staircase parameters affecting children’s safety in single-family houses were determined in this study. The online survey dedicated to collecting and assessing the importance of these parameters was constructed and spread in Lithuania. The new modification of the VASMA (Visual Analogue Scale Matrix for Criteria Weighting) methodology called VASMA-C was proposed to analyse collected data and to expose opinions differences in three target groups: experts in the field, apartment residents and house residents living with children. The comparative study disclosed that staircase landing is the parameter whose importance among the expert and non-expert evaluators differs the most. It was also revealed that apartment residents have the most divergent understanding of staircase safety compared with the rest of the target groups. These findings indicate that different customers need diverse information about the staircase parameters affecting children's health and the stair vendors should be aware of these demands.
The deposition of ultrafine particulate matter (UFPM) in the gas flow in the channeloccurs as they settle due to adhesion and under the influence of gravity. A treatment ofthe multi-channel cyclone is based on centrifugal filtration, with the two-phase gas flowin constant contact with the curved elements installed in the separation chamber. Prevailing gas flow trajectories were analyzed in a 3D printed multi-channel cyclone at 11-18.5 m3/h gas flow rate. The intensity of adhesion of UFPM (0.4-5 μm in size) tothe surface at their low concentration (no more than 10 mg/m3) was visuallyevaluated under normal and up to 95% humidity conditions. The focus is on theadhesion of the UFPM to the surface of polylactic acid. By the discrete element methodit was achieved the results of the coefficient of restitution to normal and tangentialdirection for 0.5 μm, 1.0 μm and 2.0 μm particles with the surface, as well as changesin force were equal to at normal up to 3 μN and tangential up to 1 μN over time in 20ns.
Bridge management includes all actions in the life cycle of the bridge, to ensure its safety, stability, and functionality. Numerous problems have been identified that are primarily related to the organization of planning and the role of decision-making in the reconstruction of the historic pedestrian bridges. The planning process for the reconstruction of these bridges is crucial due to increased traffic load, poor condition, or damage to bridges. Some of these bridges are part of the cultural heritage, while some are unfairly neglected. The motivation for this research arose from the need to establish the priority for the reconstruction of historic pedestrian bridges to achieve their safety, stability, functionality, and cultural preservation. For this reason, a new decision support model based on intuitionistic fuzzy group decision-making to the multi-criteria analysis is created. The model combines multi-criteria method Evaluation Based on Distance from Average Solution and grey relational degree (GRD) with intuitionistic fuzzy theory. Three relevant decision groups of experts are formed, with the knowledge and expertise in the area of research problematic, establishing criteria for the evaluation. A new approach to the consistency of criteria weights is proposed. The intuitionistic fuzzy likelihood function is developed for the aggregation of bridge evaluations. Furthermore, GRD values are calculated to determine the reconstruction priority ranking of bridge for each decision group. The final ranking is defined by integrating Integer Linear Programming (ILP) and Ant Colony Optimization (ACO), determining spatial-functional, time, and financial constraints.
Purpose – the purpose of the article is to identify factors of cultural economics and examine their impact on countries’ competitiveness. Research methodology – in this study, the following factors have been determined to affect the competitiveness of the European Union countries: cultural employment by age (18–65), general government expenditure on cultural services, households expenditure on cultural goods, persons working as creative and performing artists, authors, journalists and linguists engaged in individual activity and employment. Panel data, which are processed with the Gretl software, are used for the study. Findings – the results revealed that all the distinguished factors affect the competitiveness of the European Union countries; however, general government expenditure by function has the most significant effect. Research limitations – the article analyses all countries of the European Union except Romania because there is a lack of statistical data on this country, which interferes with the research. Practical implications – as cultural economics is linked to both the public and private sectors, the revenue and the products it generates undoubtedly contribute to the country’s economic development and, hence, competitiveness. Originality/Value – cultural economics is an interdisciplinary field of scientific research described and analysed by various authors as the interaction of human-made activities with new technologies, various artistic forms, knowledge, and creativity. Consequently, cultural economics has received more and more attention. However, the factors of cultural economics and their impact on a country’s competitiveness level is a fragmentarily examined topic which shows its originality.
Although the importance of supply chain management in the construction sector has been recognized in recent years, its implementation still faces significant challenges. For the long-term evaluation of this creative sector, numerous intricate sustainability components, such as environmental, social, and financial, are necessary. The study focuses on longterm sustainability considerations in the supply chain in the construction sector. This work aims to address this information and examine sustainable supply chain management (SSCM) research in the construction sector in this manner. More than 95 publications were studied from the beginning of 2017 to the end of 2021 using both in-depth content analysis and bibliometric methodologies. Several issues of SSCM in construction have been found including environmental, economic and social patterns which are most commonly known as the triple bottom line, typically enhanced by artificial intelligence. Many challenges were discovered including inefficiencies in the logistics system and a shortage of funding, environmental issues in demolition procedures and difficulties in applying sustainability measures due to high skill, data, and time requirements. The article offers a broad list of potentials for improving the current situation in the construction sector by using various types of supply chains such as increasing investment in energy conservation and emission reduction technologies to drive sustainable development, establishing strong green supply chain relationships, and forming a Covid-19 financial support group for small construction companies among other things. The study’s findings suggested that due to the significance of long-term relationships between construction companies, suppliers and customers, smart technology could make it simpler to reach every supply chain link. After an exhaustive literature review 59 research questions were formulated for the future research. In the future, the importance of these questions could be determined using expert questionnaires and multi-criteria evaluation. Keyword : construction industry, supply chain management, construction supply chain, research questions, logistics, sustainable construction, systematic review
The last two decades have faced a significantly increased number of telecommunication antennas emitting electromagnetic radiation in residential areas. The theoretical simulation of the dispersion of the energy flux density of the electromagnetic field has been performed applying the physical peculiarities of the waves generating electromagnetic radiation. Having evaluated studies on simulation, the visual representation of the spread of electromagnetic radiation has been carried out according to the results obtained applying the AutoCad package. A comparison of the simulated value of the energy flux density radiated from antennas for mobile telecommunications with the measured one has disclosed an overlap of 30%. The simulation of the energy flux density showed that, in the close proximity zone (under a distance of 30 m), antennas radiate values within the range 10–10,000 uW/cm2. At a distance larger than 30 m, the values of energy flux density fluctuate from 10 to 0.001 uW/cm2.
Introduction Many forecasting methods are used to predict sales, such as the moving average method, naive method, exponential smoothing methods, Holt's linear method, and others. The results brought by these models are quite different. Forecast delivered by the naive method is entirely accurate for an extended period, like 3–5 years, Holt's methods are bringing accurate one-year period forecasts. The planning decisions have several levels, meaning different forecasting results. However, the authors that are testing various forecasting methods are not discussing results researched in different planning levels (retail chain and different pharmacies). The study is given to the construction of the forecasting model covering both planning levels, which later is empirically tested for the Lithuania retail case: Purpose The development of the forecasting model for reduction of shortages in drug supply. To achieve this goal, the author revises the improvement of drug availability weekly. Research Methodology The construction of the forecasting model is incorporating outliers' detection methods and sales by pharmacies to minimize shortage. In the forecasting model, the author uses Theil's U 2 test to evaluate forecasting accuracy. Findings During analysis, the author constructs the model application for forecasting drug sales where weekly availability is highly recommended. The results show that forecasting on individual pharmacies level using the integration of these plans approach leads to higher accuracy. Research Limitations The research covers 3 months of sales data. Das and Chaudhury suggest for short-sales period products use 36 days' time horizon. Ayati et al. discuss short and long-term time horizons for planning sales of drugs. Kanyalkar and Adil analyzed multi-site production and suggest that the time horizon should cover the longest lead time required for delivery of raw material, which is 12 weeks, and select 3 months (i.e., 13 weeks) as short-term time period horizon. Wongsunopparat and Chaveesuk forecast drug sales for 1-month and 12-month periods and compare the results. In this study, the focus is on short-term time-horizon, which is considered as 3 months period and also represents the longest lead-time. In the future, the study could review other periods. The author has incorporated the review of eight forecasting methods into the study by leaving other forecasting methods unresearched. Future studies could also incorporate different ARIMA methods into shortage reduction case analysis. Practical Implications Presented forecasting model could be useful for practitioners, which analyze the reduction of the shortage of prescribed drugs. There the revision of repeated purchases is recommended for national authorities, wholesalers, and pharmacies aiming to minimize shortage. Originality/Value The analysis to reach the highest forecast accuracy and identification of a forecasting approach which responds to the fluctuation of weekly sales for the whole pharmacy chain and separate pharmacies. The study contributes to drug sales review, where most authors analyze the total volume, which is not separated by pharmacies.
Electroporation-based antitumor therapies, including bleomycin electrotransfer, calcium electroporation, and irreversible electroporation, are very effective on directly treated tumors, but have no or low effect on distal nodules. In this study, we aimed to investigate the abscopal effect following calcium electroporation and bleomycin electrotransfer and to find out the effect of the increase of IL-2 serum concentration by muscle transfection. The bystander effect was analyzed in in vitro studies on 4T1tumor cells, while abscopal effect was investigated in an in vivo setting using Balb/c mice bearing 4T1 tumors. ELISA was used to monitor IL-2 serum concentration. We showed that, similarly to cell treatment with bleomycin electrotransfer, the bystander effect occurs also following calcium electroporation and that these effects can be combined. Combination of these treatments also resulted in the enhancement of the abscopal effect in vivo. Since these treatments resulted in an increase of IL-2 serum concentration only in mice bearing one but not two tumors, we increased IL-2 serum concentration by muscle transfection. Although this did not enhance the abscopal effect of combined tumor treatment using calcium electroporation and bleomycin electrotransfer, boosting of IL-2 serum concentration had a significant inhibitory effect on directly treated tumors.
This paper presents a new Dynamic Multi-Attribute Decision-Making method based on Markovian property, which can predict the performance of each alternative in the future and at the same time allows modeling interrelationship among different periods. To this aim, the criteria and decision alternatives in different periods are determined at first, and the information of decision matrices over the decision-making horizon is gathered. To increase the robustness of the results, criteria weights are extracted using the Entropy method in each period and alternatives performance is evaluated using different Multi-Attribute Decision-Making methods. To attain the final rank of alternatives in each period, the results of different methods are aggregated by the Correlation coefficient and standard deviation method. Following this, the rank transformation matrices of alternatives during the evaluation horizon are extracted and the stable rank probability of alternatives is calculated based on limiting probability. Eventually, the overall rank of alternatives is determined using a linear assignment-based method. The proposed model has been used in the promotion of the sales staff in a private company to show the model effectiveness in a real-world problem. Results are compared with some well-known methods (five methods, to be exact). Finally, the trustworthiness and acceptability of the method are assessed based on features discussed in the literature.
In areas with a semi-arid or arid climates, dust storms are caused by winds blowing on the surfaces with loose and dry soils. Dust storms can influence different aspects of human life, such as health, agricultural practices, urban, rural, and transportation infrastructures. Since 15 years ago, dust storms, as one of the leading environmental hazards, have occurred with increased frequency, spatial extent, and intensity in the Middle East. Several satellite-based dust-detection algorithms are introduced for identifying dust emission sources and dust plumes when rising in the atmosphere. In this research, four common algorithms, namely Brightness Temperature Difference, Normalized Difference Dust Index, Thermal-Infrared Dust Index, and D-parameter, were evaluated using MODIS Level 1B and MODIS Deep Blue AOD products in two dust storms in the Khuzestan province, Iran. Detection thresholds for the indices was derived by a comparison of dust-present versus dust-free conditions data considering different coverage of land and inspecting related periods. The detection proficiency of the algorithms was different for various events; thus previously obtained thresholds were not applicable in the algorithms performed in the Khuzestan region. Initially, dust was effectively and adequately detected by MODIS AOD. It was also revealed that MODIS thermal infrared (TIR) band algorithms or algorithms combining TIR and reflectance bands could detect dust better than reflectance-based ones. However, some commission errors were caused by substantial differences among their susceptibility to distinguish dust, cloud, and the surface. Overall, among the algorithms, TDI and D-parameter performed the best over dust sources in the Khuzestan province.
Charcoal is an environmentally friendly, biodegradable, and economical material. This material is usually produced by slow pyrolysis-the heating of wood or other substances in the absence of oxygen. The aim of this study was to investigate the acoustic efficiency of charcoal and design an acoustic diffuser that utilizes charcoal. Samples of different types of tree charcoal-birch (Betula pendula), pine (Pinus sylvestris), and oak (Quercus robur)-with different thicknesses were used for the acoustic efficiency measurements. The sound absorption and sound reflection properties of charcoal were investigated. The bulk density of charcoal was measured. In this study, an impedance tube with two microphones was employed as the measurement method. The results of the impedance tube measurements showed that the charcoal samples had high sound reflection coefficients, the highest value of which was 1. The 50 mm samples of birch had a high bulk density of 473 kg/m 3. The sample of 50 mm thick oak had the best reflection coefficient at 0.99. Reflection depended on the surface's acoustic properties, and the sound reflection coefficient increased with the increase in the density. Charcoal measurements, due to the high reflection coefficient of the material , were used for the design of a sound diffuser, which included wooden perforated plates filled with cylindrical elements of wood charcoal.
A generalized orthopair fuzzy set can express uncertain information easier than most other processes, which gives us more space for decision-making. In recent times, the selection of healthcare waste treatment (HCWT) technology can be considered as multi-criteria decision-making (MCDM) problem due to the involvement of multiple conflicting criteria. To reduce the unhealthy impact on the ecosystem and promote sustainable disposal, researchers have investigated MCDM problems to select apt HCWTs. In a bid to the minimize negative environmental impact of healthcare waste, researchers adopted MCDM, and faced challenges such as: (i) handling uncertainty/subjective randomness; (ii) imputation of missing values; and (iii) consideration to experts’ attitude and interdependencies during MCDM process. To remedy these, this paper has attempted to establish a novel decision model with generalized orthopair fuzzy information (GOFI). Initially, missing values are systematically imputed. Experts' preferences were fused to obtain an aggregated matrix by considering the interdependencies among experts. Also, criteria weights were computed utilizing attitude-based entropy measures, and HCWTs were ranked using the GOFI-evaluation based on distance from average solution (GOFI-EDAS) approach. Lastly, the methodology's superiority was validated using an illustrative example, followed by a comparison with extant models. The results confirm that the developed framework is more efficient than and consistent with earlier methods under uncertainty.
Neuromodulation applications of nanosecond electric pulses (nsEP) are hindered by their low potency to elicit action potentials in neurons. Excitation by a single nsEP requires a strong electric field which injures neurons by electroporation. We bypassed the high electric field requirement by replacing single nsEP stimuli with high-frequency brief nsEP bursts. In hippocampal neurons, excitation thresholds progressively decreased at nsEP frequencies above 20–200 kHz, with up to 20–30-fold reduction at sub-MHz and MHz rates. For a fixed burst duration, thresholds were determined by the duty cycle, irrespective of the specific nsEP duration, rate, or number of pulses per burst. For 100-μs bursts of 100-, 400-, or 800-ns pulses, the threshold decreased as a power function when the duty cycle exceeded 3–5 %. nsEP bursts were compared with single “long” pulses whose duration and amplitude matched the duration and the time-average amplitude of the burst. Such pulses deliver the same electric charge as bursts, within the same time interval. High-frequency nsEP bursts excited neurons at the time-average electric field 2–3 times below the threshold for a single long pulse. For example, the excitation threshold of 139 ± 14 V/cm for a single 100-μs pulse decreased to 57 ± 8 V/cm for a 100-μs burst of 100-ns, 0.25-MHz pulses (p < 0.001). Applying nsEP in bursts reduced or prevented the loss of excitability in multiple stimulation attempts. Stimulation by high-frequency nsEP bursts is a powerful novel approach to excite neurons at paradoxically low electric charge while also avoiding the electroporative membrane damage.
In the paper, structure and properties of novel diamond composite with enhanced properties were presented and discussed. The samples were prepared using the method of cold pressing followed by the originally developed two-stage vacuum hot pressing under electric current activation. It was demonstrated that addition of different amounts of chromium diboride to the WC–6wt.%Co composite had significant effect on its microstructure, phase composition and, hence, mechanical characteristics. It was found that percentage 4wt.% of CrB2 provided the most advantageous characteristics. In the second stage of researches, this composition was used as a matrix for the diamond reinforcement. The obtained results of analysis suggested that enhancement of the composite could be attributed to the dispersed strengthening mechanism and structure modification. In particular, important role played reduction of the average grain size of the carbide phase from 5.6 to 3.4 μm, disappearance of pores at the Co binding phase, formation of inhibitor phase clusters at the interphase boundaries, and the specific pattern of phases present in the composite. Chromium diboride contributed also to the formation of dense and strong interface between diamond grits and refractory matrix. Advantageous distribution of residual stresses around the diamond grits appeared in the sintered samples with CrB2, providing additional fixation of the diamond reinforcement in the matrix. It was also demonstrated that further increase of CrB2 content above 4 wt.% in the WC–6wt.%Co composite material lead to a deterioration in its mechanical properties, which could be attributed to further, disadvantageous changes in the structure, especially in grain size and phase composition.
The article presents original technological methods that allow the improvement of the accuracy of the turning and grinding of elastic-deformable shafts by increasing their stiffness by controlling the state of elastic deformations. In particular, the adaptive control algorithm of the machining process that allows the elimination of the influence of the cutting force vibration and compensates for the bending vibrations is proposed. Moreover, a novel technological system, equipped with the mechanism enabling the regulation of the stiffness and dedicated software, is presented. The conducted experimental studies of the proposed methods show that, in comparison with the passive compliance equalization , the linearization control ensures a twofold increase in the shape accuracy. Compared to the uncontrolled grinding process of shafts with low stiffness, the programmable compliance control increases the accuracy of the shape by four times. A further increase in the accuracy of the shape while automating the processes of abrasive machining is associated with the proposed adaptive control algorithm. Moreover, the initial experiments with the adaptive devices prove that it is possible to reduce the longitudinal shape inaccuracy even by seven times.
Construction is one of the most developed industries of this century, especially thanks to the high rate of urbanization, mobility, and the tendency to fulfill global goals. A very important component of civil engineering is adequate and modern equipment which depends on the efficiency of execution of operations and processes in construction. A novel MCDM (multi-criteria decision-making) scheme was proposed in this paper, which means the development of the original and innovative DNMARCOS (Double normalized measurement alternatives and ranking according to the compromise Solution) for choosing a construction equipment among 16 variant solutions. For determination the criteria weights, an objective MEREC was applied, whose integration with the DNMARCOS method represents an additional contribution. The obtained results show that the first three alternatives Magnum MK 24.4Z-80/115 RH (A1); Magnum MK 28L-5-80/115 RH (A2); Magnum MK 25 H80 RH (A3) are the best solution for a construction company. To check the robustness of the proposed DNMARCOS method, a comparative analysis was made with the extant MCDM methods, and SCC (Spearman's correlation coefficient) coefficient and WS (Wojciech Sałabun) coefficients were calculated. The final results show the justification for the development of the original and innovative DNMARCOS model.
The usage of techniques of the artificial neural networks (ANNs) in the field of microwave devices has recently increased. The advantages of ANNs in comparison with traditional full-wave methods are that the prediction speed when the traditional time-consuming iterative calculations are not required and also the complex mathematical model of the microwave device is no longer needed. Therefore, the design of microwave device could be repeated many times in real time. However, methods of artificial neural networks still lag behind traditional full-wave methods in terms of accuracy. The prediction accuracy depends on the structure of the selected neural network and also on the obtained dataset for the training of the network. Therefore, the paper presents a systematic review of the implementation of ANNs in the field of the design and analysis of microwave devices. The guidelines for the systematic literature review and the systematic mapping research procedure, as well as the Preferred Report Items for Systematic Reviews and Meta-Analysis statements (PRISMA) are used to conduct literature search and report the results. The goal of the paper is to summarize the application areas of usage of ANNs in the field of microwave devices, the type and structure of the used artificial neural networks, the type and size of the dataset, the interpolation and the augmentation of the training dataset, the training algorithm and training errors and also to discuss the future perspectives of the usage of ANNs in the field of microwave devices.
Honey, as a bioindicator, can be used to determine the level of pollution in the environment with selected pollutants, including heavy metals. Twelve locations were selected for experimental studies near the main sources of pollution: industrial sites, landfills, railways, and highways. The honey samples were burned to ash, and the heavy metals in ashes were determined using aqua regia digestion in the microwave digestion system. The concentration of heavy metals (Cd, Cr, Cu, Pb, and Ni) was determined using a Buck Scientific model 210 VGP atomic absorption spectrophotometer with a graphite furnace atomizer and an acetylene-air flame. These median amounts of heavy metals were found in the analyzed honey samples: 0.0030 mg/kg for Cd, 0.0179 mg/kg for Pb, 0.0317 mg/kg for Cr, 0.0999 mg/kg for Cu, and 0.0332 mg/kg for Ni. The obtained results were compared with honey samples research conducted in other countries. It is difficult to compare the level of heavy metal results found in honey from different countries, as the type of honey, soil composition, rainfall, air temperature, the plants from which it was harvested, its vegetation and flowering duration, and the degree of anthropogenic pollution in the area differ. The heavy metal content tested in honey was found to be low, except for the Pb content in one sample of honey, and did not pose a risk to human health. A statistical analysis including average, median, standard deviation, confidence intervals, and Spearman coefficients was performed for the evaluation of the relationships between the heavy metal quantities and the determination of the impact of pollution sources (transport and industry). The correlation analysis showed a strong negative correlation coefficient between heavy metals and distance (r = −0.593 to −0.204).
Environmentally friendly goods are market-oriented goods that create less environmental damage. Their manufacture is related to a product development process designed to consider the environmental consequences that might develop throughout their life cycle. In reality, the global demand for herbal goods is expanding since herbal products are manufactured from plant extracts such as leaves, roots, flowers, and seeds, among others, and cause less environmental destruction. This study introduces a novel, eco-friendly demand determined by the usage of herbal and chemical substances in products. In this context, companies producing these products are encouraged. Firms are interested in producing eco-friendly products while keeping an eye on carbon emissions. This paper presents a sustainable inventory model of non-instantaneous decaying items that follow this eco-friendly demand under partially backlogged shortages. In this study, emission releases due to inventory setup, degradation, and holding were estimated, as were carbon emissions under cap and tax policies. This approach invests in green and preservation technologies to reduce carbon emissions and deterioration. To address the imprecision of the model's cost parameters, we converted them to Pythagorean fuzzy numbers. The optimum profit of the inventory model with carbon emissions is estimated by considering the time that the inventory level takes to reach zero and the replenishment time as decision variables. Numerical examples and a sensitivity analysis of significant parameters have been conducted to examine the effect of variation in the optimal inventory policy.
This paper provides an overview of the application of conducting polymers (CPs) used in the design of tactile sensors. While conducting polymers can be used as a base in a variety of forms, such as films, particles, matrices, and fillers, the CPs generally remain the same. This paper, first, discusses the chemical and physical properties of conducting polymers. Next, it discusses how these polymers might be involved in the conversion of mechanical effects (such as pressure, force, tension, mass, displacement, deformation, torque, crack, creep, and others) into a change in electrical resistance through a charge transfer mechanism for tactile sensing. Polypyrrole, polyaniline, poly(3,4-ethylenedioxythiophene), polydimethylsiloxane, and polyacetylene, as well as application examples of conducting polymers in tactile sensors, are overviewed. Attention is paid to the additives used in tactile sensor development, together with conducting polymers. There is a long list of additives and composites, used for different purposes, namely: cotton, polyurethane, PDMS, fabric, Ecoflex, Velostat, MXenes, and different forms of carbon such as graphene, MWCNT, etc. Some design aspects of the tactile sensor are highlighted. The charge transfer and operation principles of tactile sensors are discussed. Finally, some methods which have been applied for the design of sensors based on conductive polymers, are reviewed and discussed.
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