Efficiency Improvement Research Articles

Thermal insulation and energy performance's assessment of a mycelium-based composite wall for sustainable buildings

Bio-composite insulation materials play a crucial role in reducing the environmental impact of buildings. This paper numerically investigates the eco-friendly application of mycelium in south-facing walls in Marrakech, Morocco, using 2D CFD simulations. In this context, the thermal efficiency of bio-sourced insulating materials was assessed and compared to that of conventional insulating materials. The study basically aims at the time lag and the decrement factor analysis to evaluate the dynamic thermal performance of a multilayer wall insulated with mycelium. A life cycle cost analysis (LCCA) is performed to establish the optimal thickness of the mycelium insulation, which was turned out to be 0.08m. This optimization leads to a substantial improvement in energy efficiency, resulting in energy savings increasing by 87.4% in winter and 55.9% in summer. Besides, during the last 72hours of the simulation, the indoor surface temperature drops by approximately 4 °C on summer days and raises by approximately 1 °C on winter days. The thickness of mycelium insulation was found to have a significant impact on energy savings, increasing them from 56% to 93%, and representing nearly a 1.7-fold improvement. The study has also targeted annual CO2 emissions to reveal a potential reduction of around 72% using optimal mycelium composite insulation. Finally, a comparative analysis with the guidelines of Moroccan thermal regulations was achieved. The obtained findings exhibit that the examined configuration excels in terms of thermal performance, economic feasibility, and environmental benefits.

Techno-economic optimization and working fluid selection of a biogas-based dual-loop bi-evaporator ejector cooling cycle involving power-to-hydrogen and water facilities

Biogas-fueled decentralized energy systems featuring gas turbines emerge as pivotal players in the quest for more adaptable and eco-friendly energy solutions. This study presents the design of a cutting-edge multigeneration system that harnesses the potential of a gas turbine coupled with ejector-driven dual-loop bi-evaporator technology, reverse osmosis desalination, proton exchange membrane electrolysis, and an organic Rankine cycle. The research encompasses an extensive sensitivity analysis and deploys a genetic algorithm-based optimization technique. Through meticulous Optimization, the system achieves remarkable outcomes, including electricity generation, cooling capacity, heating capacity, desalinated water production, and hydrogen yield, measured at 957.3 kW, 231.4 kW, 272.3 kW, 7.336 kg/s, and 0.99 kg/h, respectively. Notably, this performance surpasses the base case by 2% and 8.9%, yielding exergy efficiency and total unit cost improvements of 33.3% and 16.4 $/GJ. Among the critical decisions made was selecting an organic working fluid for the organic Rankine cycle. Through rigorous evaluation, isobutene emerged as the optimal choice, demonstrating significantly improved output power compared to alternatives. Isobutane as the working fluid led to a substantial increase in overall exergy efficiency and a resultant total unit cost of 18.06 $/GJ, accompanied by an impressive 23.48% exergy efficiency.

Artificial intelligence in pharmacy an overview

Intelligent technologies will someday replace or enhance human talent in many areas. Artificial intelligence is the intelligence exhibited by robots or software. It falls under the field of computer science. Computer scientists are becoming more and more interested in studying artificial intelligence because it has significantly enhanced human lives in a variety of ways. Over the past 20 years, artificial intelligence has led to a major boost in the performance of industrial and service systems. Expert systems are a rapidly developing technology that are the result of research into artificial intelligence. Artificial intelligence applications known as expert systems are widely used today to solve complex problems in a range of fields, including science, engineering, business, medicine, and weather forecasting. Artificial intelligence technology have led to improvements in quality and efficiency in certain sectors. This page gives a summary of the technology and some possible uses for it. This paper will also look at the current applications of artificial intelligence technologies in the fields of computer games, accounting databases, hospital inpatient care, medical image classification, network intrusion, Power System Stabilization (PSS) design, and network security against hackers.

Out-of-focus holography at the Effelsberg telescope

Context. Out-of-focus (OOF) holography can be used to determine the aperture deformations of radio telescopes that lead to errors in the phase of the complex aperture distribution. In contrast to traditional methods, OOF holography can be performed without a reference antenna, which has a number of practical advantages. Aims. The aim of this work is to develop a standard procedure for OOF holography at the Effelsberg telescope. This includes performing OOF holography observations and the development of dedicated software, the pyoof package, to compute aberrations of the telescope’s optical system. Methods. Based on the OOF holography method developed at the Green Bank telescope, we adapted the approach to the Effelsberg 100 m telescope in order to determine the aberrations of the aperture phase distribution (phase-error maps). Results. The developed OOF holography software is presented as well as the results from observations at Effelsberg. Early results reveal gravitation-related residual deformation not contained in the previously existing aperture and pointing model, and hence we propose changes to the model to counteract aberrations in the telescope’s surface. Conclusions. The OOF holography method (observations and pyoof package) works as expected at the Effelsberg 100 m telescope and is able to validate the good performance of the existing finite element model. Test measurements show that slight improvements of the aperture efficiency and gain elevation dependence are possible but limited in the current configuration.

A poly(L-lactic Acid)-based flexible piezoelectric energy harvester with micro-zigzag structures

Piezoelectric energy harvester (PEH) holds great potential for flexible electronics and wearable devices. However, the power conversion efficiency of flexible PEH (fPEH) has often been a limiting factor, especially under variable excitation. Herein, we propose a practical solution: a poly(L-lactic acid)-based fPEH with 3D-printed micro-zigzag structures. This design not only broadens the operational bandwidth and enhances low-frequency response but also offers a tangible improvement in the power conversion efficiency of fPEH. The micro-zigzag structure was designed and fabricated using a digital light processing 3D printing technique with acrylates, a method that is readily accessible to researchers and engineers in the field. Mechanical properties of the 3D-printed acrylic elastomers with different compositions were investigated to obtain the material parameters, and then fPEH with the sandwich structure was fabricated via sputtering and packaging. Subsequently, numerical simulation was conducted on the micro-zigzag structures to determine the structure sizes and oscillation frequencies of fPEH. Finally, four micro-zigzag structures with 3-, 4-, 5- and 6 mm lengths were tested to obtain oscillation frequencies of 51, 37, 22, and 21 Hz consistent with the simulation. The output voltages of fPEH are 11–30 mV with the load ranges of 60–100 MΩ. Stability evaluation showed that the fPEH can work under low frequency (<100 Hz) and broadband conditions. The micro-zigzag structure provided new insights for the design of fPEH, paving the way for more efficient and practical energy harvesting solutions in the future.

Design and Application of Intelligent Control System for Molten Iron Transportation Based on 5G Technology

Molten transport is an important link in the iron and steel enterprise production, involves many complex factors, artificial management is difficult. Therefore, puts forward a kind of molten iron transport wisdom control system based on 5G technology, which mainly contains the intelligent identification tracking system, equipment status collection information acquisition system, locomotive vehicle terminal system, etc. Combined with the analysis of the actual application situation, the system could integrate all the processes and elements of molten iron production and transportation, realize the integration of operation and management, and also promote the improvement of the turnover efficiency of molten iron tank, reduce the demand for personnel, and reduce the labor cost.

A survey on the application of online and offline blended teaching in microendodontics

Objective: To evaluate the effect of online and offline blended teaching in microendodontics, attempting to promote the widespread application of blended teaching mode in Operative Dentistry and Endodontics. Methods: A questionnaire survey was carried out among 865 trainees who attended the blended teaching in microendodontics combined the online theory curriculum and offline practice training from April 6 to 28 in 2022, organized by Department of Operative Dentistry and Endodontics, Hospital of Stomatotogy, Sun Yat-sen University. The content of questionnaire included trainees' basic information as well as their perspectives and expectations on the teaching mode. Data was analyzed by SPSS 24.0 and Chi-square test was used for enumeration data. Results: A total of 855 trainees participated in the valid survey with the effective recall rate of 98.8% (855/865), 50.3% (430/855) of which were young people in 18-30 years old. Their working period ranged from 0.5 to 40 years. Physicians and physician assistants occupied 40.9% (350/855) and 32.9% (281/855), respectively. And the intermediate and senior titles accounted for 26.2% (224/855). The proportion of trainees who had used and never used dental operative microscope (DOM) were 70.5% (603/855) and 29.5% (252/855), respectively. The blended teaching in microendodontics was universally approved by the trainees, which showed more superiority in the improvement of learning efficiency and interest, comprehension of knowledge as well as practical ability, etc., compared to the traditional offline teaching. For the current stomatology education, trainees were inclined to choose the blended teaching mode combining online theory curriculum and offline practice training, whereas 41.3% (353/855) and 39.6% (339/855) of trainees agreed that the teaching effectiveness was likely influenced by the condition and frequency of the offline training, respectively. Besides, significant differences were detected in the question about the factors affecting the blended teaching effectiveness of microendodontics between the trainees who had used and not used DOM (χ²=13.37, P=0.004). Conclusions: The application of online and offline blended teaching in microendodontics was affirmed to have some advantages, and it should be considered that the discrepancy in the level of expertise among trainees probably influenced the teaching effectiveness, which may promote the quality and effect of teaching, the spread and sharing of microendodontics, and provide experience and reference for the practice teaching of Operative Dentistry and Endodontics.

INDIDO: A novel low-power approach for domino logic circuits

Power dissipation in Nanoelectronic circuits at advanced technology nodes is dominated by leakage power dissipation. This is due to an increase in short channel effects in the scaled transistors.The VLSI industry is seeking alternative options to enhance the performance of portable electronic systems by ensuring higher speed and reduced power dissipation. In the ultra-deep submicron (DSM) regime, a new device called the fin-shaped field effect transistor (FinFET) was developed to replace CMOS technology. FinFET, a multi-gate device, significantly reduces power dissipation compared to planer MOS (Metal Oxide Semiconductor ) transistor, but it doesn’t entirely resolve the issue. To further reduce power dissipation in the ultra DSM regime, low power approaches are required. Domino logic, a widely-used dynamic logic, is commonly utilized in high-speed VLSI architectures. In this research work, a novel INput Dependent Inverter DOmino (INDIDO) logic approach for low-power domino logic circuits using FinFET devices is proposed. A comparative analysis between the proposed INDIDO method and the existing approaches is performed for domino logic circuits for various performance metrics at the 16 nm technology node. In this research, various circuits like domino buffer, domino OR, domino AND, domino XOR and domino half adder are designed using the proposed INDIDO approach.The proposed INDIDO FinFET buffer circuit offers significant improvement in energy efficiency and FOM (Figure of Merit) by 53.18% and 82% respectively as compared to conventional FinFET footed domino buffer circuit. Beside this, proposed circuits like INDIDO OR, INDIDO AND, INDIDO XOR and INDIDO Half adder circuit follow the same trend as INDIDO buffer circuit and show better performance parametres in comparison to the existing low power domino approaches as well. In addition to this, the proposed INDIDO buffer circuits are also analyzed for PVT(process voltage and temperature) variability.This whole analysis makes us to conclude that proposed INDIDO approach reduces power dissipation and delay penalty, have high noise tolerance capacity, more immunity against PVT variations and high energy efficiency in comparison to the already existing techniques.

Biomaterial Improves the Stability of Perovskite Solar Cells by Passivating Defects and Inhibiting Ion Migration.

With the rapid improvement of power conversion efficiency (PCE), perovskite solar cells (PSCs) have broad application prospects and their industrialization will be the next step. Nevertheless, the performance and long-term stability of the devices are limited by the defect-induced nonradiative recombination centers and ions' migration inside the perovskite films. Here, usnic acid (UA), an easy-to-obtain and efficient natural biomaterial with a hydroxyl functional group (-OH) and four carbonyl groups (-C═O) was added to MAPbI3 perovskite precursor to regulate the crystallization process by slowing the crystallization rate, thereby expanding the crystal size and preparing perovskite films with low defect density. In addition, UA anchors the uncoordinated Pb2+ and suppresses the migration of I-ions, which enhances the stability of the perovskite film. Consequently, an impressive PCE exceeding 20% was achieved for inverted structure MAPbI3-based PSCs. More impressively, the optimized PSCs maintained 78% of the initial PCE under air with high humidity (RH ≈ 65%, 25-30 °C) for 1000 h. UA can be extracted from the plant, usnea, making it inexpensive and easy to obtain. Our work demonstrates the application of the plant material in PSCs and their industrialization, which is significant nowadays.

Impact of the Free Trade Zone policy on firm labour investment efficiency: evidence from China

ABSTRACT This study employs the staggered difference-in-differences (DID) method to examine the impact of the Free Trade Zone (FTZ) policy on firm labour investment efficiency. Utilizing data from Chinese A-listed companies between 2011 and 2021, we find a significant improvement in labour investment efficiency (LIE) attributable to FTZ. The underlying mechanism involves FTZ optimizing the business environment, reducing transaction costs and adjusting the composition of human capital. Moreover, the positive effects are more pronounced in labour-intensive and non-state-owned companies. FTZ restrains over-hiring and alleviates under-hiring, thereby enhancing LIE. The findings offer valuable insights for enhancing labour allocation through thoughtfully crafted public policies.

Reticular Ratchets for Directing Electrochemiluminescence.

Electrochemiluminescence (ECL) involves charge transfer between electrochemical redox intermediates to produce an excited state for light emission. Ensuring precise control of charge transfer is essential for decoding ECL fundamentals, yet guidelines on how to achieve this for conventional emitters remain unexplored. Molecular ratchets offer a potential solution, as they enable the directional transfer of energy or chemicals while impeding the reverse movement. Herein, we designed 10 pairs of imine-based covalent organic frameworks as reticular ratchets to delicately manipulate the intrareticular charge transfer for directing ECL transduction from electric and chemical energies. Aligning the donor and acceptor (D-A) directions with the imine dipole effectively facilitates charge migration, whereas reversing the D-A direction impedes it. Notably, the ratchet effect of charge transfer directionality intensified with increasing D-A contrast, resulting in a remarkable 680-fold improvement in the ECL efficiency. Furthermore, dipole-controlled exciton binding energy, electron/hole decay kinetics, and femtosecond transient absorption spectra identified the electron transfer tendency from the N-end toward the C-end of reticular ratchets during ECL transduction. An exponential correlation between the ECL efficiency and the dipole difference was discovered. Our work provides a general approach to manipulate charge transfer and design next-generation electrochemical devices.

A Novel Constraint-Aware Flexible Model with Ant Colony Optimization for Symmetrical Travel Recommendation

This paper proposes a flexible travel recommender model (FTRM) that emphasizes the symmetry between user preferences and travel constraints, addressing key challenges in the field such as the integration of diverse constraint types and the customization of travel itineraries. The key contribution of the proposed model lies in its integration with the item constraints data model (ICDM), which effectively manages a plethora of constraint types. Additionally, this study develops a novel algorithm inspired by ant colony optimization (ACO) principles, demonstrating performance metrics that are comparable to state-of-the-art algorithms in this field. A comprehensive set of systematic experimental analyses is conducted, employing various models across diverse situational contexts, with the primary goal of illustrating the capabilities of the proposed symmetrical FTRM using real-world data from the Durham dataset. The obtained results highlight the model’s ability to accommodate diverse constraint types, facilitating the customization of travel itineraries to suit individual user preferences and achieve a balanced and symmetrical travel experience. Specifically, our model outperforms existing models in terms of flexibility and customization, showing significant improvements in user satisfaction and itinerary efficiency.

Research on Improved Crystallization Properties and Underlying Mechanism of the Sb2Te3 Phase-Change Thin Film by Inserting Sn15Sb85 Layers.

As a non-volatile semiconductor memory technology, phase-change memory has a wide range of application prospects as a result of the excellent comprehensive performance. In this paper, multilayer thin films based on Sb2Te3 material were designed and prepared by inserting the Sn15Sb85 layer. The thermal and electrical properties of superlattice-like Sb2Te3/Sn15Sb85 phase-change films can be adjusted by controlling the thickness ratio of Sb2Te3/Sn15Sb85. In comparison to the monolayer Sb2Te3 film, the multilayer layer Sb2Te3/Sn15Sb85 materials have a higher crystallization temperature, larger crystallization activation energy, and longer data lifetime, indicating the great improvement of thermal stability. The changes in the phase structure and vibrational modes of multilayer Sb2Te3/Sn15Sb85 films were characterized by X-ray diffraction and Raman spectroscopy, respectively. The presence of Sn15Sb85 layers restrains grain growth and refines the grain size. The multilayer Sb2Te3/Sn15Sb85 films exhibit better surface flatness, smaller surface potential undulation, and lower thickness variations than single-layer Sb2Te3. Phase-change memory cells based on the [Sb2Te3 (1 nm)/Sn15Sb85 (9 nm)]5 thin film has a lower threshold voltage (1.9 V) and threshold current (3.1 μA) compared to the Ge2Sb2Te5 film. Meanwhile, the electrical heating model of a phase-change memory cell based on a [Sb2Te3 (1 nm)/Sn15Sb85 (9 nm)]5 multilayer structure was established by multiphysics coupling analysis, proving the great improvement in heat transfer performance and efficiency. The experimental and theoretical studies confirm that the insertion of the Sn15Sb85 layer can significantly improve the crystallization properties of Sb2Te3 films, paving the way for optimizing the phase-change materials by regulating the microstructural parameters.

Comparison of urban physical environments and thermal properties extracted from unmanned aerial vehicle images and ENVI-met model simulations

Identifying the thermal properties of urban areas and integrating these properties into spatial planning is essential for sustainable development. Continuous and efficient improvements of urban thermal environments require novel studies, which are limited to date. This study addresses this gap by presenting a comparison of the physical environments and thermal properties of an urban area (Changwon National University, Gyeongsangnam-do, South Korea) based on unmanned aerial vehicle (UAV) images and ENVI-met model simulations. We predicted the thermal environment of the study area using UAV images and explored the potential application of UAVs in spatial planning. The comparison revealed that the coefficient of determination (R2) between mean radiant temperature (Tmrt) values simulated by the ENVI-met model and predicted from UAV images was 0.168–0.320. Significant differences were observed in shaded areas and vegetated regions with tall trees, where UAVs encountered difficulties in collecting accurate information due to obstructed visibility. The discrepancies between the simulated and predicted Tmrt values highlight the limitations of UAVs in capturing data in shaded and densely vegetated areas, as well as disparities in the physical environments determined by the two methods. Despite these limitations, UAVs can be valuable tools for urban and environmental planning. Future advancements addressing these limitations may enable UAVs to efficiently diagnose urban thermal environments and guide improvement efforts.

Comparison of Greenhouse Gas Emission Assessments of Solar and Energy Efficiency Improvements at Small Water Resource Recovery Facilities

Small water resource recovery facilities (WRRFs) account for the majority of centralized systems in the world and have higher energy intensities than large facilities. This study compares potential greenhouse gas emission reductions based on on-site solar energy and energy efficiency (E2) improvements made at small WRRFs. Case study data from 31 existing small WRRFs in Nebraska were collected and included 35 site-specific energy efficiency (E2) recommendations and on-site solar renewable energy systems integrated at three facilities, and the data were used to compare the benefits of on-site solar energy and E2 improvements made at small WRRFs. Improvements in E2 (e.g., improved aeration control) presented the largest reduction in emissions per dollar invested. They often exhibited shorter paybacks, with operational changes in aeration strategies showing the highest impact (up to 0.2 kg CO2eq/m3 treated water). On-site solar systems showed the largest net potential for reducing environmental footprint (0.35 kg CO2eq/m3) but often showed the smallest emissions reduction per cost. While the use of both E2 improvements and the integration of on-site solar renewable energy can significantly improve the sustainability of small WRRFs, on-site solar has advantages for small facilities in that it often requires less operational involvement, allows for greater facility resiliency, and presents less uncertainty in terms of environmental benefit.

A Pilot Clinical and Technical Validation of an Immersive Virtual Reality Platform for 3D Anatomical Modeling and Contouring in Support of Surgical and Radiation Oncology Treatment Planning.

The aim of this study was to validate a novel medical virtual reality (VR) platform used for medical image segmentation and contouring in radiation oncology and 3D anatomical modeling and simulation for planning medical interventions, including surgery. The first step of the validation was to verify quantitatively and qualitatively that the VR platform can produce substantially equivalent 3D anatomical models, image contours, and measurements to those generated with existing commercial platforms. To achieve this, a total of eight image sets and 18 structures were segmented using both VR and reference commercial platforms. The image sets were chosen to cover a broad range of scanner manufacturers, modalities, and voxel dimensions. The second step consisted of evaluating whether the VR platform could provide efficiency improvements for target delineation in radiation oncology planning. To assess this, the image sets for five pediatric patients with resected standard-risk medulloblastoma were used to contour target volumes in support of treatment planning of craniospinal irradiation, requiring complete inclusion of the entire cerebral-spinal volume. Structures generated in the VR and the commercial platforms were found to have a high degree of similarity, with dicesimilarity coefficient ranging from 0.963 to 0.985 for high-resolution images and 0.920 to 0.990 for lower resolution images. Volume, cross-sectional area, and length measurements were also found to be in agreement with reference values derived from a commercial system, with length measurements having a maximum difference of 0.22mm, angle measurements having a maximum difference of 0.04°, and cross-sectional area measurements having a maximum difference of 0.16 mm2. The VR platform was also found to yield significant efficiency improvements, reducing the time required to delineate complex cranial and spinal target volumes by an average of 50% or 29min.

Fiscal space for the immunisation program in Zambia– an efficiency analysis approach

ObjectiveThe immunisation programme in Zambia remains one of the most effective public health programmes. Its financial sustainability is, however, uncertain. Using administrative data on immunisation coverage rate, vaccine utilisation, the number of health facilities and human resources, expenditure on health promotion, and the provision of outreach services from 24 districts, we used Data Envelopment Analysis to determine the level of technical efficiency in the provision of immunisation services. Based on our calculated levels of technical efficiency, we determined the available fiscal space for immunisation.ResultsOut of the 24 districts in our sample, 9 (38%) were technically inefficient in the provision of immunisation services. The average efficiency score, however, was quite high, at 0.92 (CRS technology) and 0.95 (VRS technology). Based on the calculated level of technical efficiency, we estimated that an improvement in technical efficiency can save enough vaccine doses to supply between 5 and 14 additional districts. The challenge, however, lies in identifying and correcting for the sources of technical inefficiency.

Intraperitoneal laparoscopic single-site lymph node dissection in modified supine position during laparoscopic radical nephroureterectomy.

Technique modifications that aim to improve ergonomics of the surgical procedure without repositioning the upper tract urothelial carcinoma patients remain a challenge to urologists. We offer a novel technique to perform intraperitoneal laparoscopic single-site radical nephroureterectomy and pelvic lymph nodes dissection/retroperitoneal lymph nodes dissection in a supine position. Our novel technique is feasible and offers a significant improvement in operative efficiency, particularly in patients with locally advanced disease.

REVIEW OF DATA ANALYTICS AND INFORMATION SYSTEMS IN ENHANCING EFFICIENCY IN FINANCIAL SERVICES: CASE STUDIES FROM THE INDUSTRY

This study explores the transformative impact of integrating data analytics and information systems on enhancing efficiency in the financial services industry. The research highlights significant improvements in operational efficiency, risk management, and customer satisfaction through detailed case studies of JPMorgan Chase, Allstate Insurance, BlackRock, and Bank of America. The findings reveal that AI-driven analytics tools at JPMorgan Chase led to a 30% reduction in fraud-related losses and a 20% increase in customer satisfaction. Through predictive analytics, Allstate Insurance achieved a 40% reduction in claims processing time and a 25% improvement in underwriting accuracy. BlackRock reported a 35% increase in portfolio returns due to machine learning and predictive analytics. In comparison, Bank of America experienced a 22% increase in customer retention and a 15% rise in satisfaction through data-driven CRM systems. These outcomes underscore the critical role of advanced data analytics and information systems in driving innovation and operational excellence in financial services. The study emphasises the importance of continuous technological advancements and strategic implementation to maximise the benefits of these tools in the industry.

Contagious Stock Price Crashes Along the Supply Chain

Although risk management is widely regarded as an important topic within supply chain (SC) management, little research studies the contagious effect of risk factors along SC networks. By using stock price crashes as an indicator of risk factors, our study reveals that stock price crash risk can be transmitted from major customers to suppliers with a delay of up to two weeks. We show that the information opacity of suppliers is a factor that potentially contributes to the delayed crash contagion. We also find that the contagion effect becomes more pronounced as the importance of customers increases. Moreover, customer operational incidents have a more pronounced contagion effect on suppliers compared to customer financial incidents. Additionally, we find that suppliers tend to take strategic measures following the stock price crashes of their major customers, including diversifying their customer base, enhancing operational efficiency, and improving product quality. However, among these actions, only the improvement of operational efficiency effectively mitigates the adverse impact of customer stock price crashes on suppliers. Overall, our findings provide new insight into the distribution of risk factors across SC networks, highlighting the critical role of operational improvements in bolstering the resilience of firms to SC risks.