Hasil untuk "Special industries and trades"

Henning Schulte, Christian Ammon, Frauke Hagenkamp-Korth et al.

Previous studies have shown that ammonia emissions can be continuously reduced through the application of a urease inhibitor (UI) in cattle and pig farming. However, there is no information on whether the use of these inhibitors also has an effect on other emissions, and whether it leads to an increase or decrease in these emissions. In this study, carbon dioxide, ammonia, methane, nitrous oxide and odour emissions were measured in three mechanically ventilated, fully slatted pig fattening houses in Germany during 2019–2020. The UI was applied daily to compartments, and effects on emission values were comparatively analysed using four different calculation approaches: linear mixed model, direct case-control, case-control in time and a novel ratio-difference approach. As expected, a significant reduction in ammonia emissions of 22–24 % was observed across all four calculation approaches and all three farms, confirming the effectiveness of the UI; no decisive effects on carbon dioxide, methane or odour emissions were found. Effects on nitrous oxide emissions could not be reliably analysed due to low concentrations which were below the Fourier-transform infrared spectroscopy (FTIR) quantification limit. It is recommended to calculate the reduction effect using a combined approach so that over- and underestimation of the effect can be avoided. Two approaches are available for this purpose: the ratio-difference and linear mixed model. The ratio-difference approach has a simplicity of calculation and the ability to achieve results very similar to those of the linear mixed model.

Cristiano Manetti da Cruz, Mercia Pandolfo Provin, Ana Laura de Sene Amâncio Zara

Objectives: To identify expenses with the purchase of medicines and supplies by the Municipal Health Department of Canguçu/RS, through legal proceedings, from 2017 to 2021. Methods: It is a quantitative, descriptive, and retrospective study, using the docu-ment analysis technique. Secondary data on public costs, available on the Transparency Portal, were used. The amounts spent and the origins of the resources used for the acqui-sition of these drugs were analyzed. Results: There was an increase of 297.93% in spen-ding on legal proceedings for the acquisition of medicines and pharmaceutical supplies through judicial blockades. Of these, more than 76% refer to antineoplastic medications. The basic care budget increased by 132.41% in this period and the costs of pharmaceu-tical assistance almost doubled from R$ 854,248.86, in 2017, to R$ 1,524,871.92, in 2021, with a significant increase during the pandemic period. Comparing the expen-diture on purchasing medicines through blockages by court permits in 2021 and the amount spent on pharmaceutical assistance in the same period, it is noted that the cost is very similar, but a small portion of the population is served through judicialization. Conclusions: There was a considerable increase in spending on purchasing medicines due to court decisions. The Municipal Health Department is obliged to acquire medicines that do not belong to the Municipal Medication List, through judicial blocking of public accounts, because the government of the State of Rio Grande do Sul does not send these medicines to users with approved lawsuits.

Christine Böttcher, Debra McDavid, Angelica M. Jermakow et al.

Conclusions: This study has demonstrated that a relatively simple and robust protoplast isolation, DNA-free protoplast transfection and plant regeneration workflow can be used to efficiently produce nontransgenic, diploid, edited clones with desired phenotypes of four elite winegrape cultivars, including the highly recalcitrant Cabernet Sauvignon.

G. de Mathelin, C. Hartl-Nesic, A. Kugi

The performance of industrial robotic work cells depends on optimizing various hyperparameters referring to the cell layout, such as robot base placement, tool placement, and kinematic design. Achieving this requires a bilevel optimization approach, where the high-level optimization adjusts these hyperparameters, and the low-level optimization computes robot motions. However, computing the optimal robot motion is computationally infeasible, introducing trade-offs in motion planning to make the problem tractable. These trade-offs significantly impact the overall performance of the bilevel optimization, but their effects still need to be systematically evaluated. In this paper, we introduce metrics to assess these trade-offs regarding optimality, time gain, robustness, and consistency. Through extensive simulation studies, we investigate how simplifications in motion-level optimization affect the high-level optimization outcomes, balancing computational complexity with solution quality. The proposed algorithms are applied to find the time-optimal kinematic design for a modular robot in two palletization scenarios.

Nathan Lane

I study the impact of industrial policies on industrial development by considering an important episode during the East Asian miracle: South Korea's heavy and chemical industry (HCI) drive, 1973--1979. Based on newly assembled data, I use the introduction and termination of industrial policies to study their impacts during and after the intervention period. (1) I reveal that heavy-chemical industrial policies promoted the expansion and dynamic comparative advantage of directly targeted industries. (2) Using variation in exposure to policies through the input-output network, I demonstrate that the policy indirectly benefited downstream users of targeted intermediates. (3) The benefits of HCI persisted even after the policy ended, as some results were slower to appear. The findings suggest that the temporary drive shifted Korean manufacturing into more advanced markets and supported durable change. This study helps clarify the lessons drawn from the East Asian growth miracle. JEL Codes: L5, O14, O25, N6. Keywords: industrial policy, East Asian miracle, economic history, industrial development, Heavy-Chemical Industry Drive, Heavy and Chemical Industry Drive.

Yong Wang, Hongbo Kang, Doudou Wu et al.

Vitek Mercedes, Matjaž Mirjam Gosenca

The principal function of skin is to form an effective barrier between the human body and its environment. Impaired barrier function represents a precondition for the development of skin diseases such as atopic dermatitis (AD), which is the most common inflammatory skin disease characterized by skin barrier dysfunction. AD significantly affects patients’ quality of life, thus, there is a growing interest in the development of novel delivery systems that would improve therapeutic outcomes. Herein, eight novel lyotropic liquid crystals (LCCs) were investigated for the first time in a double-blind, interventional, before-after, single-group trial with healthy adult subjects and a twice-daily application regimen. LCCs consisted of constituents with skin regenerative properties and exhibited lamellar micro-structure, especially suitable for dermal application. The short- and long-term effects of LCCs on TEWL, SC hydration, erythema index, melanin index, and tolerability were determined and compared with baseline. LCCs with the highest oil content and lecithin/Tween 80 mixture stood out by providing a remarkable 2-fold reduction in TEWL values and showing the most distinctive decrease in skin erythema levels in both the short- and long-term exposure. Therefore, they exhibit great potential for clinical use as novel delivery systems for AD treatment, capable of repairing skin barrier function.

Neil A. Chriss

This is the third paper in a series concerning the game-theoretic aspects of position-building while in competition. The first paper set forth foundations and laid out the essential goal, which is to minimize implementation costs in light of how other traders are likely to trade. The majority of results in that paper center on the two traders in competition and equilibrium results are presented. The second paper, introduces computational methods based on Fourier Series which allows the introduction of a broad range of constraints into the optimal strategies derived. The current paper returns to the unconstrained case and provides a complete solution to finding equilibrium strategies in competition and handles completely arbitrary situations. As a result we present a detailed analysis of the value (or not) of trade centralization and we show that firms who naively centralize trades do not generally benefit and sometimes, in fact, lose. On the other hand, firms that strategically centralize their trades generally will be able to benefit.

David Wichner, Jeffrey Wishart, Jason Sergent et al.

Safety Management Systems (SMSs) have been used in many safety-critical industries and are now being developed and deployed in the automated driving system (ADS)-equipped vehicle (AV) sector. Industries with decades of SMS deployment have established frameworks tailored to their specific context. Several frameworks for an AV industry SMS have been proposed or are currently under development. These frameworks borrow heavily from the aviation industry although the AV and aviation industries differ in many significant ways. In this context, there is a need to review the approach to develop an SMS that is tailored to the AV industry, building on generalized lessons learned from other safety-sensitive industries. A harmonized AV-industry SMS framework would establish a single set of SMS practices to address management of broad safety risks in an integrated manner and advance the establishment of a more mature regulatory framework. This paper outlines a proposed SMS framework for the AV industry based on robust taxonomy development and validation criteria and provides rationale for such an approach. Keywords: Safety Management System (SMS), Automated Driving System (ADS), ADS-Equipped Vehicle, Autonomous Vehicles (AV)

Lukas Hammel, J. Otto, Frank Will et al.

A large proportion of today's building projects are realized in existing buildings. This almost always requires the sensitive deconstruction of existing building fabric. Deconstruction technologies have to fulfill high requirements particularly in inner-city residential areas and during ongoing building use, both for construction projects in the existing building stock and for new construction activities. Currently used demolition technologies rarely meet the growing requirements in building practice. Common demolition and separation methods are characterized by high emissions, such as vibrations and noise, large quantities of blasting material, slow performance progress or high physical effort. An alternative technology is the electrodynamic Electric-Impulse-Technology (EIT). The process technology, initially developed for applications in mining and special civil engineering, is based on the destruction of solid materials by high-voltage pulses. On the basis of large-scale tests in mining dimensions, it was possible to demonstrate high dissolving capacities with low energy input. The research project aimed to investigate the basics for transferring the EIT to low-emission and selective material removal in civil and structural engineering. Extensive laboratory tests were conducted on sand-lime and concrete specimens to verify the adaptation of the EIT. It was found out that the technology is suitable for use in the construction industry. Further research is to be conducted to investigate the identified areas of application in greater depth and to further develop EIT for practical use.

M.F.B. Stodt, J. Kiefer, U. Fritsching

Flame spray pyrolysis (FSP) is a technique for the synthesis of metal oxide nanoparticles by combusting precursor solutions in a spray flame. The combustion of certain precursor solutions is known to lead to severe droplet disruptions (μ-explosions) in the spray flame that are linked to the synthesis of homogeneous and phase-pure nanoparticles. In this work, a broad spectrum of suitable subsonic operating conditions for the synthesis of iron oxide nanoparticles by FSP is investigated to understand the influence of the jet Reynolds number and turbulence on the onset of μ-explosions and droplet dynamics in spray flames. In order to enable a coherent comparison between differently operated spray flames using an iron(III) nitrate nonahydrate solution, the gas-to-liquid mass ratio and, hence, the oxygen/fuel ratio have been kept constant in order to identify the influence of flow conditions on the droplet dynamics. From the analysis of the droplet sizes in the spray and in the spray flame, it is found that in all combusting sprays, the droplet sizes convert from unimodal (after atomization) to bimodal droplet size distribution (DSD) due to the presence of μ-explosions. The occurrence and evolution of the bimodal DSD reveal that high jet Reynolds numbers result in narrower DSD and in a sharper separation of both DSD probability peaks (modal values). A straightforward 1-step kinematic model is presented to describe the conversion of unimodal to bimodal DSD considering the evaporation of droplets as well as the disruption of droplets to mimic the effect of μ-explosions. The temporal evolution of droplets in FSP is investigated by spatially resolved velocity data that reveal the formation of a temporal self-similarity. The resulting iron oxide nanoparticle size decreases with increasing jet Reynolds number. The turbulent mixing and residence times in the flame, primarily set by the jet Reynolds number, are identified as key design parameters for FSP.

Allison Woodruff, Renee Shelby, Patrick Gage Kelley et al.

Generative AI is expected to have transformative effects in multiple knowledge industries. To better understand how knowledge workers expect generative AI may affect their industries in the future, we conducted participatory research workshops for seven different industries, with a total of 54 participants across three US cities. We describe participants' expectations of generative AI's impact, including a dominant narrative that cut across the groups' discourse: participants largely envision generative AI as a tool to perform menial work, under human review. Participants do not generally anticipate the disruptive changes to knowledge industries currently projected in common media and academic narratives. Participants do however envision generative AI may amplify four social forces currently shaping their industries: deskilling, dehumanization, disconnection, and disinformation. We describe these forces, and then we provide additional detail regarding attitudes in specific knowledge industries. We conclude with a discussion of implications and research challenges for the HCI community.

WT Al-shaibani, Tareq Babaqi, Abdulraqeeb Alsarori

The use of steel is essential in many industries, including infrastructure, transportation, and modern architecture. Predicting power consumption in the steel industry is crucial to meet the rising demand for steel and promoting city development. However, predicting energy consumption in the steel industry is challenging due to several factors, such as the type of steel produced, the manufacturing process, and the efficiency of the manufacturing facility. This research aims to contribute by creating a predictive model that estimates power consumption in the steel industry. The unique approach combines linear regression to predict a continuous variable related to power consumption and the KNN clustering method to identify the demanding load type. This study's novelty lies in the development of a model that accurately predicts energy consumption in the steel industry, leading to more sustainable and efficient practices. This research contributes to enabling industries to anticipate and optimize their energy consumption, leading to more sustainable practices and economic development.

J. Jussila, E. Nagy, K. Lähtinen et al.

Climate change sets high pressures on the construction industry to decrease greenhouse gas emissions. Due to the carbon storage properties and potential to use renewable resources efficiently, wooden multi-storey construction (WMC) is an interesting alternative for the construction industry to enhance sustainable development combined with the aesthetic and well-being benefits of wood perceived among many consumers. For forest industry firms, industrial wood construction is a possibility to seek for business opportunities and bring socio-economic benefits for local economies. Despite positive drivers, WMC still remains a niche even in the forest-rich countries.The purpose of our study is to add understanding on the WMC market development by conducting a systematic literature analysis on international peer-reviewed studies from the past 20 years. Our special focus is on the role of WMC in the housing markets studied from the perspectives of the demand, supply and local governance factors. As specific aims, we 1) synthesize the key barriers and enabling factors for the WMC market growth; 2) identify the actors addressed in the existing studies connected to the WMC market development, and 3) summarize research methods and analytical approaches used in the previous studies. As a systematic method to make literature searches in Web of Science and Scopus for years 2000–2020, we employed PRISMA guidelines. By using pre-determined keywords, our searches resulted in a sample of 696 articles, of which 42 full articles were after selection procedure included in-depth content analysis. Our results showed cost-efficiency gains from industrialized prefabrication and perceived sustainability benefits by consumers and architects enabled a WMC market diffusion. The lack of experiences on the WMC, and path dependencies to use concrete and steel continue to be key barriers for increased WMC. Although our research scope was the global WMC market development, most of the literature concerned the Nordic region. The key actors covered in the literature were businesses (e.g., contractors, manufacturers and architects) involved in the wood construction value-chains, while residents and actors in the local governance were seldomly addressed. Currently, case studies, the use of qualitative data sets and focus on the Nordic region dominate the literature. This hinders the generalizability of findings in different regional contexts. In the future, more research is needed on how sustainability-driven wood construction value-chains are successfully shaping up in different geographical regions, and how they could challenge the dominant concrete-based construction regime.

Yingfan Tao, Wenxian Zheng, Wenming Yang et al.

Manikandan Srinivasan P., Dharmakkan Nesakumar, Sumana Nagamani

The experimental study of the heat transfer coefficient of nanofluid plays a significant role in improving the heat transfer rate of the heat exchanger. A natural convection apparatus was used to study heat transfer in the suspension of Al2O3 nanoparticles in a water-ethylene glycol mixture base fluid. The effects of the heat input, the nanoparticle volume fraction, and the base fluid concentration on the heat transfer coefficient were studied using a 23 full factorial design matrix (16 experimental runs) and the MINITAB Design software. The levels for the heat input, nanoparticle volume fraction, and base fluid concentration were 10 and 100 W, 0.1 and 1 vol.%, and 30 and 50 vol.%, respectively. The residual, contour, 3D surface plots, and Pareto chart were drawn from the experimental results. The observed heat transfer coefficient showed the highest enhancement with the high level of the nanoparticle volume fraction and a moderate enhancement with the high level of heat input, and a slight enhancement with the base fluid concentration.

Hongjie Jia, Huiyuan Wang, Yan Cao et al.

Abstract In modern society, system integration that enables multiple subsystems to function as one is emerging in various fields like industry, commerce, and infrastructure. Although it has been proved that integration value could be tapped to the maximum with controllable cost by optimising the integration schemes in certain fields, there is still a lack of a general method for modelling and analysing the process of system integration. To address this need, this paper proposes an analysis framework of system integration. The concepts of integration object, integration strategy, integration time, integration cost and integration value are introduced to describe the integration process. Further, three optimisation models of the local optimisation (OPT1), phase optimisation (OPT2) and integration optimisation (OPT3) are constructed. The proposed framework can also supervise and compare the performance of intermediate processes of different integration schemes. Two case studies in the commerce and energy fields are analysed to illustrate the function of the proposed framework.

Svetlana V. Domnina, Elena V. Savoskina, Oksana А. Guzhova

The aim of the study is to identify the role of the innovative component in the system of quality management of highways. An analysis of the proportion of new technologies and materials used to improve the quality of roads, the dynamics of accidents on sections of federal highways, where new technologies and materials were used, as well as the condition of roads was carried out. The data became the basis for the formation of factors that improve road safety. A regression model of the dependence of road safety on the quality of roads (with three variables) was developed. With the help of the model it is possible to predict the impact of changes in the variables on the number of road accidents. The study developed a system of quality management of roads and highlighted the innovative components, such as controlling effects, management tools, factors, innovative technologies and elements of the integral indicator of innovation. New horizons in the system of quality management of roads – innovation, which forms the need to improve all of its elements (planning, construction management, construction technology, its organization, organization of labor of employees), taking into account the practice of quality management of roads based on the standards of project management of the International Association of Project Management. This will improve the quality of the road object. As a result, there will be an economic effect from the introduction of the quality management system of road works. Roads are among the institutional support processes for the formation of public welfare and security of the country. However, there is still a problem of low satisfaction with the condition of roads by the population. Despite the active participation of the state in the development of the transport industry, quality management systems in Russian road organizations are not always effective. Most of them focus their attention on solving technical problems and issues of operational management. New horizons in the system of quality management of roads should open the program of innovative development of the state company “Russian Highways”. This program focuses on improving the quality of roads through the introduction of technological initiatives at all stages of road construction. Application of the principle “open innovations” strengthens the need to include the block of innovations in the standardized model of the quality management system (QMS). In this regard, it becomes obvious to develop a road quality management system taking into account the innovation component. The purpose of this study is to develop a system of quality management of roads, taking into account the innovative component. Method and methodology of work: in the process of work were used general scientific methods of research: analysis of scientific and educational literature; process approach; comparative analysis; system analysis, synthesis; method of correlation and regression analysis; methods of tabular and graphical representation of data, as well as standards of project management. Results: – A correlation and regression model of the dependence of road traffic safety on the quality of roads (on three variables) was developed; – developed a quality management system at all stages of road construction, taking into account the innovative component. Scope of the results: the proposed results can be used to improve the quality management system of roads in the Russian Federation.

董彦军, 王晓甜, 马红明 et al.

电力负荷具有非线性和时序性的特点，为了深入研究各特征变量对于电力负荷预测的重要性，进而获得更高的电力负荷预测精度，提出了基于随机森林（random forest，RF）算法及长短期记忆网络（long short-term memory，LSTM）的混合负荷预测模型。首先根据时间日期因素及气候因素建立高维特征数据集作为随机森林模型的输入，通过随机森林算法筛选出重要特征量，并使其与历史负荷结合作为LSTM模型的输入，经过粒子群算法对LSTM模型进行参数寻优后得到RF-LSTM混合模型及负荷预测结果。使用该方法对河北电网某台区的电力负荷进行预测，结果表明该混合模型的预测精度比未经特征变量筛选的传统单一的随机森林算法、LSTM模型以及BP神经网络更为理想。