Improvements In Technology Research Articles

Oral CT Contrast Agents: What's New and Why, From the AJR Special Series on Contrast Media.

Current CT oral contrast agents improve the conspicuity of and confidence in bowel and peritoneal findings in many clinical scenarios, particularly for outpatient and oncologic abdominopelvic imaging. Yet, existing positive and neutral oral contrast agents may diminish the detectability of certain radiologic findings, frequently in the same scans in which the oral contrast agent improves the detectability of other findings. With ongoing improvements in CT technology, particularly multienergy CT, opportunities are opening for new types of oral contrast agents to further improve anatomic delineation and disease detection using CT. The CT signal of new dark oral contrast agents and of new high-Z oral contrast agents promises to combine the strengths of both positive and neutral oral CT contrast agents by providing distinct CT appearances in comparison with bodily tissues, iodinated IV contrast agents, and other classes of new CT contrast agents. High-Z oral contrast agents will unlock previously inaccessible capabilities of multienergy CT, particularly photon-counting detector CT, for differentiating simultaneously administered IV and oral contrast agents; this technique will allow generation of rich 3D, intuitive, perfectly coregistered, high-resolution image sets with individual contrast agent "colors" that provide compelling clarity for intertwined intraabdominal anatomy and disease processes.

Recent Patents for Optical Component Polishing Technology

Background: Fluid jet polishing, Airbag polishing, Magnetorheological polishing, and Ion beam polishing are all emerging polishing technologies commonly used for processing optical components, which can be used to manufacture various high-precision and high-quality optical components. Their processing mechanisms are to remove materials by high-speed jet impacting the surface of the workpiece; using a spherical flexible airbag as a polishing tool to obtain a super-smooth surface by adding polishing fluid containing fine abrasives; controlling the magnetic field to form a flexible polishing belt of Magnetorheological fluid, which undergoes relative motion to achieve material removal; using a neutral ion beam to bombard the surface of the workpiece to remove workpiece surface atoms and obtain a super-smooth surface through energy and momentum transfer between ions and workpiece atoms. The characteristics and removal mechanisms of various polishing methods are briefly described, and the advantages and key issues that need to be addressed for each polishing technology are pointed out, and suggestions and prospects for future research, application, and development are also given. Objective: In order to meet the growing demand for high-precision optical components and mass-manufactured optical components, this paper aims to study the various polishing technologies that are continuously improved and suggestions are made for future research and development directions. Method: This paper reviews the current patents related to various polishing technologies, such as Fluid jet polishing, Airbag polishing, Magnetorheological polishing and Ion beam polishing and other representative polishing technologies. Results: Various types of polishing technologies have been studied, and the main problem at the current stage is the lack of accuracy. The problem of the polishing device, such as fluid jet polishing, only considers the change of fluid velocity and pressure to construct the removal function model for analysis and summary, and suggestions for the latest research progress of various polishing technologies are given. Conclusion: The improvement and optimization of polishing technology are beneficial to improving the polishing accuracy and quality of optical components and have great help for the future development of related patents.

Gravitational effects on optical lens fabrication: First insides on Earth- and microgravity experiments

Abstract Understanding the effects of gravity on manufacturing processes is a pioneering extension of the process parameter space used to date. Until now, the improvement of manufacturing technologies has mainly focused on process parameters such as temperature, pressure, and material composition, as access to variable gravity environments is limited. The Einstein-Elevator opens up new possibilities for the variation of these process parameters and the development of in-space manufacturing technologies. Together with the research of innovative production processes for optical components within the PhoenixD Cluster of Excellence, this creates an entirely new field of research. The research presented here focuses on investigating gravity's effects on dispensed optical lens production. Using a jet dispenser, sessile droplets are produced during a flight phase in the Einstein-Elevator and cured directly by UV polymerization. As part of this study, optical lenses were produced and compared under microgravity and Earth's gravitational conditions. Geometric properties such as height and contact angle of the lenses produced were analyzed. It was found that lenses fabricated under microgravity have a larger contact angle than those fabricated under Earth gravity. Similarly, the height increases with decreasing gravity. These results are consistent with the theoretical assumptions described, although generalized theories to describe the morphology of a sessile droplet are not yet available. The case study findings on the influence of gravity as a process parameter on drop morphology represent a fundamental improvement for additive manufacturing technologies, especially for in-space manufacturing.

Засоренность посевов и урожайность сои в зависимости от способов обработки почвы, посева и защиты от сорных растений

The primary soil treatment along with herbicide application plays an important role in decreasing weed number in soybean sowings as this crop is differed with slow growth and is not competitive with weeds in the initial phase of development. The purpose of the research is improvement of soybean cultivation tech-nology through increasing of the efficiency of main technological methods (primary soil treatment, sowing method, and chemical ways of weeds control) on leached black soil of the Western Ciscaucasia that will promote high yield of seeds. The research was conducted in 2020–2022. The experiment scheme includes two sowing methods: wide-row (70 cm inter-row spacing) and common row (15 cm interrow spac-ing); three methods of the primary soil treatment: moldboard (25–27 cm), subsurface (25–27 cm), and surface (12–14 cm) ploughing; three herbicide applications in a phase of 1–3 true leaves: Concept, OD (1.0 l/ha), tank mixtures Geyzer, CCS (2.0 l/ha), Tan-to, CCS (0.75 l/ha), Harmony, DFS (7.0 g/ha), Ba-zagran, WS (3.0 l/ha), and Shogun, EC (1.0 l/ha) (standard). The highest weed infestation of soybean sowings was stated in variants with subsurface and surface soil treatments. The application of Concept and the tank mixture of Harmony, Bazagran, and Shogun was very effective – to 87.7% and 88.3%, respectively. The highest yield (2.57–2.68 t/hа) was obtained in variants with subsurface and surface soil treatments in common row sowing at the application of a herbicide Concept and a tank mixture of Har-mony, Bazagran, Shogun.

The regulatory basis of migratory behaviour in birds: different paths to similar outcomes

Animal migration is a fascinating phenomenon that has puzzled mankind since the time of ancient Greece. It is a process widespread across a varied range of taxa and it shines especially in birds which, because of their mobility, display an amazing diversity of routes and strategies. With the advances in tracking devices and improvements of sequencing technologies, recent work provides support for a strong genetic influence of several migratory traits across different species. However, there is little to no evidence of any common sequence‐based mechanism behind this complex behaviour, nor any unifying principle explaining it. We review how the focus in understanding the genetic basis for migratory traits should be shifted towards studying regulatory mechanisms of gene expression instead of the traditional candidate gene approach. Importantly, a role for gene expression as the underlying driver of the migratory phenotype can resolve the opposing and often strong views that migration is mainly either under genetic or environmental influence. We emphasise that research should take new directions, reinforcing that there is probably not a common genetic basis for how migration is regulated in birds. Here, we support the notion that 1) migration can only evolve this fast if it is a quantitative trait with a large standing variation; 2) the main drivers for migration evolution seem to be diverse expression–regulation mechanisms rather than gene‐level polymorphisms; and 3) non‐coding sequences of the genome, epigenetics and structural variation might be more important in shaping complex traits than previously thought. Further, we present several hypotheses outlining how these regulatory mechanisms might work across different bird species defining certain migratory traits.

Is Native Naïve? Comparing Native Game Engines and WebXR as Immersive Analytics Development Platforms.

Native game engines have long been the 3-D development platform of choice for research in mixed and augmented reality. For this reason, they have also been adopted in many immersive visualization and immersive analytics systems and toolkits. However, with the rapid improvements of WebXR and related open technologies, this choice may not always be optimal for future visualization research. In this article, we investigate common assumptions about native game engines versus WebXR and find that while native engines still have an advantage in many areas, WebXR is rapidly catching up and is superior for many immersive analytics applications.

Improving the calculation module for estimating pollutant emission from conventional and hybrid regional aircraft

For the aviation sector, it is extremely important to devise revolutionary solutions in the field of technology to restrain the potential impact of civil aviation on the environment to the level of the established strategic goals of ACARE (FlightPath2050). The introduction of innovative technologies (improvement of the combustion chamber, the introduction of electric hybrid power plants on airplanes, and the use of alternative aviation fuel) will ensure the sustainable growth of air transportation. To assess the effectiveness of advanced technologies, it is extremely important to have a model for calculating global/local emissions that takes into account the parameters of the flight path of conventional and hybrid aircraft, operational characteristics of the aircraft engine and hybrid powerplant, and the features of sustainable fuel. The improved module for calculating emission indices by combining the module for calculating the parameters of the flight path and the results of calculating the thermogas-dynamic calculation of the aircraft engine makes it possible to detect the influence of fuel consumption (engine thrust) on the values of the emission indices. This feature is representative for evaluating the efficiency of hybrid powerplants because the electrification of the aircraft fleet is primarily aimed at reducing fuel consumption. The analysis of simulation results reveals that the fuel consumption and EINOx are significantly reduced (for the climb stage – 25 %; for the descent stage – 30 %) for the hybrid AN26 compared to the conventional AN26. The specified operational measure, in the part of the low-pitch descend, significantly reduces EICO for the hybrid AN26 by an average of 50 % compared to the descend stage for the conventional trajectory. The results of calculations for the entire flight path demonstrate that the use of a hybrid power plant for An26 contributes to an average reduction of fuel consumption by 10 %, NOx emissions by 25 %, water vapor emissions by 10 %, and CO2 by 10 %.

Integrated Hybrid Engine Cycle Design and Power Management Optimization

Abstract A novel integrated gas turbine cycle design and power management optimization methodology for parallel hybrid electric propulsion architectures is presented in this paper. The gas turbine multipoint cycle design method is extended to turboprop and turbofan architectures, and several trade studies are performed initially at the cycle level. It is shown that the maximum degree of electrification is limited by the surge margin levels of the booster in the turbofan configuration. An aircraft mission-level assessment is then performed using the integrated optimization method initially for an A320 Neo style aircraft case. The results indicate that the optimal cycle redesigned hybrid electric propulsion system (HEPS) favors takeoff and climb power on-takes while optimal retrofit HEPS favor cruise power on-takes. It is shown that for current battery energy density (250 Wh/Kg), there is no fuel burn benefit. Furthermore, even for optimistic energy density values (750 Wh/kg) the maximum fuel burn benefit for a 500 nm mission is 5.5% and 4% for redesigned and retrofit HEPS, respectively. The power management strategies for HEPS configurations also differ based on gas turbine technology with improvement in gas turbine technology showing greater scope for electrification. The method is then extended to ATR 72 style aircraft case, showing greater fuel burn benefits across the flight mission envelope. The power management strategies also change depending on the objective function, and optimum strategies are reported for direct operating cost or fuel burn. The retrofit case studies show a benefit in direct operating cost compared to redesigned case studies for ATR 72. Finally, a novel multimission approach is shown to highlight the overall fuel burn and direct operating cost benefit across the aircraft mission cluster.

Enhancing online health consultations through fuzzy logic-integrated attribute-based encryption system

Online health consultations are becoming more popular as a result of technological improvements. Patients routinely look for information about medical disorders online, which could jeopardize the privacy of medical records and increase the workload of healthcare professionals. Nonetheless, academics continue to be extremely concerned about issues related to the quality characteristics that relate to the current architectural models, such as energy consumption, latency, resource utilization, scalability, and packet loss. This method, however, also results in a significant strain being placed on medical experts who must sort through vast amounts of medical records to extract certain information. This paper presents a novel ciphertext policy attribute-based encryption method coupled with fuzzy logic to overcome these issues. This solution uses a hybrid structure of IPFS and blockchain to store data and enables complex bidirectional access control. Before being added to IPFS, medical records are encrypted. To ensure data integrity, related IPFS hash indexes are then added to the blockchain. Utilizing attribute-based technology, users’ data is encrypted to give them fine-grained bidirectional access control. A thorough security analysis proves the system’s resilience, especially when faced with chosen plaintext assaults inside the random oracle model. Tests for this study were conducted using 10–50 attribute sets. This paper’s technique solely makes use of a hash operation. All things considered; the study demonstrates that the proposed design is more efficient than earlier schemes. Thus, from the comparison study above, it can be concluded that the system presented in this work is more efficient. Results from simulations provide additional support for the suggested methodology by highlighting the improved computing efficiency of users as compared to baseline conventional systems. This study demonstrates how technological advancement and healthcare requirements can coexist harmoniously, paving the way for secure and effective online medical consultations that are powered by fuzzy logic.

Dietary shift can enhance the environmental benefits of crop redistribution

Crop redistribution is widely recognized as an effective means of reducing the environmental costs of agricultural production without technological improvements. However, changes in food supply driven by dietary shift are rarely taken into account in crop redistribution. Based on inventory analysis of water consumption, land demand and carbon emission in crops production, this study constructed a linear optimization model to explore crop redistribution strategy and the saving potential of environmental costs in context of dietary shift. The results showed that crops production in 2030 would increase water consumption by 2.84%, land demand by 1.19%, and carbon emission by 1.31% compared with 2020 if the diet remained unchanged. Crop redistribution considering dietary shift provided an effective approach to achieve significant environmental benefits, including reductions in water consumption of 3.33%–14.91%, arable land use of 1.13%–13.90%, and carbon emission of 6.17%–20.26% compared to the baseline scenario, among which, dietary shift contributed 2.64 ± 6.12%, 0.75 ± 7.06%, and 1.32 ± 7.19%, respectively. The findings highlighted that appropriate dietary shift could enhance the environmental benefits of crop redistribution. Insights into the dietary shift and concomitant environmental benefits debate on crop redistribution have important policy implications for improving the sustainability of agricultural production.

CLIMATE CHANGE MITIGATION STRATEGIES IN THE OIL & GAS SECTOR: A REVIEW OF PRACTICES AND IMPACT

Climate change mitigation has become a pressing global challenge, with the oil and gas sector being a significant contributor to greenhouse gas emissions. This review examines climate change mitigation strategies within the oil and gas industry, focusing on practices and their impact. The oil and gas industry faces increasing pressure to reduce its carbon footprint and transition towards cleaner energy sources. Various mitigation strategies have been implemented, including technological innovations, operational improvements, and investments in renewable energy. These strategies aim to minimize greenhouse gas emissions, improve energy efficiency, and transition towards low-carbon alternatives. Technological innovations play a crucial role in mitigating climate change within the oil and gas sector. Advanced drilling techniques, such as horizontal drilling and hydraulic fracturing, have enabled companies to extract oil and gas more efficiently, reducing emissions per unit of production. Additionally, carbon capture, utilization, and storage (CCUS) technologies have been developed to capture and store carbon dioxide emissions from oil and gas operations, preventing them from entering the atmosphere. Operational improvements, such as reducing methane leaks and flaring, are also essential for climate change mitigation in the oil and gas industry. Methane is a potent greenhouse gas, and minimizing its release during extraction, processing, and transportation is critical for reducing the sector's overall emissions. Companies have implemented measures such as leak detection and repair programs, improved equipment maintenance, and enhanced monitoring systems to mitigate methane emissions effectively. Furthermore, investments in renewable energy and low-carbon technologies are increasingly common among oil and gas companies. Many companies are diversifying their portfolios to include solar, wind, and bioenergy projects, aiming to reduce their reliance on fossil fuels and contribute to the transition to a low-carbon economy. In conclusion, climate change mitigation strategies in the oil and gas sector encompass a range of technological, operational, and investment initiatives aimed at reducing greenhouse gas emissions and transitioning towards cleaner energy sources. While progress has been made, ongoing efforts and collaboration between industry stakeholders, governments, and civil society are essential to achieve meaningful impact in mitigating climate change.
 Keywords: Climate Change, Mitigation, Strategies, Oil and Gas Sector, Practices and Impact.

INNOVATIVE SOLUTIONS FOR LEARNERS WITH VISUAL IMPAIRMENTS

This paper explores the integration of innovative solutions in education to address the unique needs of learners with visual impairments. Despite education being a fundamental right, traditional methodologies often overlook this demographic, leading to significant learning barriers. The study examines the impact, efficacy, and potential improvements of assistive technologies (AT) and inclusive educational practices through a detailed review of recent literature. Key findings include the effective use of IT network programs, digital interface augmentation, haptic technology, and collaborative tools that support both visually impaired and sighted learners. By analyzing these technological interventions and educational strategies, the paper aims to highlight best practices, identify existing gaps, and propose directions for future research and development in making education more accessible and inclusive for visually impaired students.

The Application of Digital Transformation in Accounting Education: A Case Study of Internet + Technology Improving Academic Performance

This study aims to evaluate the impact of the application of Internet + technology in accounting education on academic performance, with a special focus on the academic performance changes of 2022 accounting students of Ningxia Vocational and Technical College of Finance and Economics. The study adopted a quantitative analysis method to evaluate the effects of these technologies by comparing and analyzing students' scores before and after receiving Internet + technology teaching. The data was collected from the school's student status management system, covering the performance records of 124 students. SPSS software was used for data processing and analysis, and the academic performance before and after the technology application was compared through Wilcoxon signed-rank tests. The results show that the average score of students increased significantly after the application of technology, from 48.27 points to 85.40 points, indicating that Internet + technology has played a significant role in improving academic performance in accounting. This performance improvement is attributed to the flexible learning resources, enhanced interactive learning environment, and practical learning materials provided by Internet+ technology. Research also explores the potential of these technologies to improve the quality of teaching and develop students' critical thinking and problem-solving skills. Based on these findings, the study recommends that educators integrate Internet+ technology in accounting course design and calls for future research to expand the sample scope and use qualitative methods to gain an in-depth understanding of students' feelings and feedback on digital learning tools. Overall, this study highlights the importance of integrating digital technology into accounting education and provides empirical support and reference direction for other educational institutions to implement teaching reforms in similar fields. As technology continues to develop, the education field should continue to explore and adapt to new technologies to prepare students for the needs of the future accounting industry.

Impact of climatic factors and poverty on wheat yields via machine learning in a semi-arid region across West Asia.

Abstract Winter-sown wheat is particularly vulnerable to high temperatures in spring. However, little is known concerning the impact of high temperatures and other climatic and non-climatic factors in combination on winter-sown wheat yields in arid and semi-arid regions. Therefore, in this study we investigate the impacts of high temperatures and other climatic indices, including evapotranspiration and aridity index during spring months, and non-climatic factors, including technology improvement and poverty ratio on irrigated and dryland wheat yields. We employed Random Forests a machine learning technique to our long-term data (1980-2010) and annual wheat yields (irrigated and dryland) for 27 provinces of Iran. The results show that technology improvement and poverty ratio are the most important variables which explain irrigated wheat yields variability. Temperatures above 31°C, evapotranspiration and aridity index are the other variables that alter irrigated whet yields in the region during the period 1980-2010. Dryland wheat yields mainly explained by temperatures above 31°C. Poverty ratio, technology improvement, evapotranspiration and aridity index ranked after high temperatures above 31°C, respectively. This study demonstrates that, although, in arid areas technological improvement and irrigation may avoid yield reduction due to high temperatures in spring months, in poor arid areas and dryland systems, high temperatures significantly reduce wheat yields.

Total Factor Productivity Growth in the Indian Food Processing Industry: A Non-parametric Investigation

This study analysed total factor productivity growth (TFPG) in the Indian food processing industry in the organised sector. The results showed that TFPG in this industry resulted from technical progress and that the role of change in technical efficiency was insignificant. Therefore, for sustainable output growth, the application of new technologies must be followed by adaptation. In this context, policymakers should consider sub-sectoral heterogeneity when designing policies for the Indian food processing industry so that the rates of applying technology and its adaptability can be matched for each industry sub-sector. Thus, the study offers a strong note of caution about investments in technological improvements.

Recent advances in the treatment of renal stones using flexible ureteroscopys.

Upper urinary tract stones are a common urological disease that can be treated by flexible ureteroscopy (FURS) through the natural urinary tract, in addition to extracorporeal shock wave lithotripsy and percutaneous nephrolithotomy. The advantages of FURS are less trauma, faster recovery, and fewer complications, while its disadvantages include poor results of lithotripsy and stone extraction when dealing with larger stones, and prolonged operation time. Over the last two decades, the emergence of new technologies such as FURS combined with negative pressure suction, robot-assisted FURS, and artificially intelligent FURS, coupled with improvements in laser technology (the use of thulium fiber lasers and the invention of single-use flexible ureteroscopes (su-fURS) suitable for primary level application, have significantly increased the global adoption of FURS. This surge in usage holds a promising future in clinical application, benefiting a growing number of patients with renal calculi. Accompanied by changes in technical concepts and therapeutic modalities, the scope of indications for FURS is broadening, positioning it as a potential primary choice for urolithiasis treatment in the future. This review outlines the progress in employing FURS for the treatment of renal calculi in order to generate insights for further research.

Inference of the Paramentes of a Bioreactor via Approximate Bayesian Evidence

In the context of the recent water crisis, the development and improvement of technologies for efficiently treating wastewater becomes increasingly necessary. Aligned with this, the activated sludge process is widely used in biological wastewater treatment plants to remove carbon and nutrients from wastewater. Although significant advancements have been achieved in recent years in modelling these processes to improve their performance and energy efficiency, the models are still complex and difficult to calibrate using data from real plants. In this work, we use Bayesian inference frameworks to estimate the parameters of the activated sludge process. We employ Gaussian processes to estimate the solution to the differential equations of the activated sludge process model and we fit this estimation to manufactured data of the observations of the wastewater. We find that the use of the Bayesian inference framework outperforms the classical approach in scenarios where measurements are more strongly affected by noise.

Levelized cost of driving for medium and heavy-duty battery electric trucks

The total cost of ownership (TCO) of trucks is known as one of the main decision-making factors by logistics operators for adopting alternative powertrains such as battery electric trucks (BETs). In this study, we develop a very detailed levelized cost of driving (LCOD) model to analyse the TCO of BETs and conventional trucks (CTs) in medium and heavy-duty truck weight classes. The model has methodological advancements such as developing opportunity costs for charging activities, using a detailed operational time calculation, and analysing the optimum driving ranges or battery sizing. By implementing an extensive sensitivity analysis of LCOD for CTs and BETs over 43 variables, it is revealed that the key parameters such as operational driving range, battery pack price, state of charge of battery, driver cost, “mid-shift” charging power, ambient temperature, opportunity charging, and driving speed have major impacts on the cost competitiveness of BETs vs. CTs. In addition, the impact of battery and charging technology improvements as well as designing optimum driving ranges are examined in three different operational trip profiles (urban, short-haul or regional, long-haul). The result shows that: 1) BETs in urban trip profiles with the current and/or short-term battery technology might be economically viable alternatives for CTs without the help of the policy measures, 2) BETs with below 40 t gross vehicle weight and the long-term improvements in battery technology in all the operational trip profiles might be economically viable alternatives for CTs without the help of the policy measures, and 3) the implementation of policy measures affecting the relative costs of CTs and BETs and development of fast-charging facilities would be needed to support the above 40 t BETs in short-haul and long-haul trips for the current and/or short-term as well as mid-term battery technologies.

The Role of Uig Linkages in Improving Competitive Advantage: A Case of the Clothing, Textiles, Leather, and Footwear Industry of South Africa

The South African clothing, textiles, leather, and footwear (CTLF) sector has been under competitive attack, mainly from Asian countries. The many studies undertaken so far have not focused on the role of research and development linkages among university, industry, and government (UIG), and hence, this study was undertaken. This study uses mixed methods, interviews of managers and directors from UIG actors, and a survey of CTLF firms to understand the role of UIG linkages in improving competitive advantage. The data was thematically and descriptively analysed. The findings highlight that most CTLF firms were not involved in UIG research and development linkages. As a result, CTLF firms have not utilised researchers available in the universities nor research-related industry and government funding that supports innovation and technological improvements. For the CTLF to improve its competitive advantage, its development strategies must include being engaged in UIG research and development linkages. 
 
 Received: 28 September 2023 / Accepted: 3 February 2024 / Published: 5 March 2024

Application of integrated geophysical techniques in geothermal exploration in Binhai County, Jiangsu Province

AbstractIntegrated geophysical technology is a necessary and effective means for geothermal exploration. However, integration of geophysical technology for large‐scale surveys with those for geothermal reservoir localization is still in development. This study used the controlled source audio‐frequency magnetotelluric method technology for large‐scale exploration to obtain underground electrical structure information and micromotion detection technology to obtain underground wave velocity structure information. The combination of two detection technologies was used for local identification of geothermal reservoirs. Further, auxiliary correction and inversion constraint were implemented through the audio magnetotelluric sounding technology for maximum authenticity restoration of the near‐ and transition‐field data. Through these technology improvements, a geothermal geological model was established for the Binhai County of Jiangsu Province in China and potential geothermal well locations were identified. On this basis, a geothermal well was drilled nearly 3000 m deep, with a daily water volume of over 2000 m3/day and a geothermal water temperature of 51°C at the well head. It is found that predictions using the above integrated geophysical exploration technology are in good agreement with the well geological formation data. This integrated geophysical technology can be effectively applied for geothermal exploration with high precision and reliability.