High-Sensitivity PtSe2 Surface Plasmon Resonance Biosensor Based on Metal-Si-Metal Waveguide Structure

PtSe2 as a novel TMDCs material is used to modify the traditional SPR biosensors to improve the performance. On this basis, this research proposes a metal-Si-metal waveguide structure to further improve the performance of the biosensor. In this study, we not only studied the effects of waveguide structures containing different metals on the performance of biosensor, but also discussed the performance change of the biosensor with the change of PtSe2 thickness. After the final optimization, a BK7-Au-Si-Au-PtSe2 (2 nm) biosensor structure achieved the highest sensitivity of 193.8°/RIU. This work provides a new development idea for the study of SPR biosensors with waveguide structures in the future.

Minimizing Carbon Footprint by Smart Sustainable Reservoir Management

Sustainability and reducing carbon footprint has attracted attention in the oil and gas industry to optimize recovery and increase efficiency. The 4th Industrial Revolution has made an enormous impact in the oil and gas industry and on analyzing carbon footprint reduction opportunities. This allows classification of various reservoir operations, installation of permanent sensors and robots on the field, and reduction of overall power consumption. We present an overview of new AI approaches for optimizing reservoir performance while reducing their carbon footprint. We will outline the significant carbon emissions contributors for field operations and how their impact will change throughout the production's lifecycle from a reservoir. Based on this analysis, we will outline via an AI-driven optimization framework areas of improvement to reduce the carbon footprint considering the uncertainty. We analyzed the framework's performance on a synthetic reservoir model with several producing wells, water, and CO2 injecting wells. Beneficial in reducing carbon emissions from the field is the reuse and injection of CO2 for enhancing hydrocarbon production from the reservoir. One hundred different scenarios were then investigated utilizing an innovative autoregressive network model to determine the impact of these components on the overall carbon emission of the field and determine its uncertainty. The conclusions from the analysis were then incorporated into a data-driven optimization routine to minimize carbon footprint while maximizing reservoir performance. The final optimization results of the showcase outlined the ability to reduce the carbon footprint significantly.

Graphical Optimization Method for Symmetrical Bidirectional Corridor Progression

The graphical progression method can obtain grand coordinated schemes with minimal computational complexity. However, there is no standardized solution for this method, and only a few related studies have been found thus far. Therefore, based on the in-depth discussion of the graphical optimization theory mechanism, a process-oriented and high-efficiency graphical method for symmetrical bidirectional corridor progression is proposed in this study. A two-round rotation transformation optimization process of the progression trajectory characteristic lines (PTC lines) is innovatively proposed. By establishing the updated judgment criteria for coordinated mode, the first round of PTC line rotation transformation realizes the optimization of coordinated modes and initial offsets. Giving the conditions for stopping rotation transformation and determining rotation points, rotation directions, and rotation angles, the second round of PTC line rotation transformation achieves the final optimization of the common signal cycle and offsets. The case study shows that the proposed graphical method can obtain the optimal progression effect through regular graphing and solving, although it can also be solved by highly efficient programming.

Optimization of Lead Base Perovskite Solar Cell with ZnO and CuI as Electron Transport Material and Hole Transport Material Using SCAPS-1D

Perovskite solar cells (PSCs) research is substantially drawing attention because of the fast improvement in their power conversion efficiency (PCE), cheapness, possibility to tune the bandgap, low recombination rate, high open circuit voltage, excellent ambipolar charge carrier transport and strong and broad optical absorption. In this research, Zinc oxide as electron transport material (ETM) and copper iodide as hole transport material (HTM) have been optimized using SCAPS-1D simulation software. The thickness, bandgap, of ZnO (ETM) and CuI (HTM) was investigated. Results shows that the thickness and bandgap were found to strongly influence the PCE of perovskite solar cell. ZnO/CuI was found to be a better replacement to TiO2/Cu2O for stability and low degradation rate. It was observed that the maximum efficiency is 22.04%, Voc of 0.84V, JSC of 32.83mA/cm2 and FF of 79.79% was obtained when the thickness of ETM and HTM layer of (CH3NH3PbI3) PSCs which was found to be optimum at 0.2μm for the final optimization.

Multi-objective optimization of muffler for vehicle air-conditioning compressor pipeline

The noise reduction of air-conditioning systems has gradually become an urgent problem with the comfortable requirement of driving, and the muffler is a commonly used noise reduction equipment for air-conditioning pipeline. In this article, the transmission loss of prototype muffler is co-simulated at different speeds. For optimizing the muffler, a new method that combines orthogonal optimization and detailed optimization is proposed. In orthogonal optimization, the multi-objectives orthogonal test is used to analyze the effect of four structural parameters (the shoulder height, the length of the cavity, the diameter of cavity, and the length of intubation) on the average transmission loss, the transmission loss at 1120Hz, and the frequency band width below 4dB. The influence of different factors on the transmission loss is studied at different speeds, and it found that the length of intubation has a significant impact on the transmission loss. In detailed optimization, the method is characterized by rapidity in the design of air conditioning system of vehicle, and the final optimization model is determined. The results show that the optimized structure is better than the original structure. The maximum reduction of average noise can reach 11.99dB, and the maximum noise reduction at 1120Hz reach 8.58dB.

The Coevolution of RuBisCO, Photorespiration, and Carbon Concentrating Mechanisms in Higher Plants

Ribulose-1,5-bisphosphate (RuBP) carboxylase/oxygenase (RuBisCO) is the carbon-fixing enzyme present in most photosynthetic organisms, converting CO2 into organic matter. Globally, photosynthetic efficiency in terrestrial plants has become increasingly challenged in recent decades due to a rapid increase in atmospheric CO2 and associated changes toward warmer and dryer environments. Well adapted for these new climatic conditions, the C4 photosynthetic pathway utilizes carbon concentrating mechanisms to increase CO2 concentrations surrounding RuBisCO, suppressing photorespiration from the oxygenase catalyzed reaction with O2. The energy efficiency of C3 photosynthesis, from which the C4 pathway evolved, is thought to rely critically on an uninterrupted supply of chloroplast CO2. Part of the homeostatic mechanism that maintains this constancy of supply involves the CO2 produced as a byproduct of photorespiration in a negative feedback loop. Analyzing the database of RuBisCO kinetic parameters, we suggest that in genera (Flaveria and Panicum) for which both C3 and C4 examples are available, the C4 pathway evolved only from C3 ancestors possessing much lower than the average carboxylase specificity relative to that of the oxygenase reaction (SC/O=SC/SO), and hence, the higher CO2 levels required for development of the photorespiratory CO2 pump (C2 photosynthesis) essential in the initial stages of C4 evolution, while in the later stage (final optimization phase in the Flaveria model) increased CO2 turnover may have occurred, which would have been supported by the higher CO2 levels. Otherwise, C4 RuBisCO kinetic traits remain little changed from the ancestral C3 species. At the opposite end of the spectrum, C3 plants (from Limonium) with higher than average SC/O, which may be associated with the ability of increased CO2, relative to O2, affinity to offset reduced photorespiration and chloroplast CO2 levels, can tolerate high stress environments. It is suggested that, instead of inherently constrained by its kinetic mechanism, RuBisCO possesses the extensive kinetic plasticity necessary for adaptation to changes in photorespiration that occur in the homeostatic regulation of CO2 supply under a broad range of abiotic environmental conditions.

Sistem Pendukung Keputusan Penerima Bantuan Rumah Tak Layak Huni (RTLH) Di Kota Binjai Dengan Metode Simplemultiple Attribute Rating Technique (SMART) (STUDI KASUS: DINAS SOSIAL BINJAI)

Decision support system is defined as a system that is intended to support managerial decision makers in certain situations. Decision support systems are intended to be a tool for decision makers to expand their capabilities, but not to replace their judgment. This RTLH (Unfit for Living House) assistance must be right on target for poor people who meet the criteria as requirements for receiving RTLH assistance, so that residents who are unable to receive RTLH assistance can receive the assistance. In its implementation, the underprivileged population who is entitled to receive assistance unfit for habitation is determined by the Social Service (Dinsos). One of the methods in decision support is the Simple Multi Attribute Rating Technique (SMART) method or commonly abbreviated as the SMART method. The SMART method is a method that has minimum calculations and is very simple, but objective on the results of decision support. From research conducted using the SMART method, it was found that R9 with a final optimization value of 0.725 became the recipient of uninhabitable housing assistance from 10 alternative data on uninhabitable houses analyzed.

Indoor Acoustic Requirements for Autism-Friendly Spaces

The architecture of spaces for people on the autistic spectrum is evolving toward inclusive design, which should fit the requirements for independent, autonomous living, and proper support for relatives and caregivers. The use of smart sensor systems represents a valuable support to internal design in order to achieve independent living for impaired people. Accordingly, these devices can monitor or prevent hazardous situations, ensuring security and privacy. Acoustic sensor systems, for instance, could be used in order to realize a passive monitoring system. The correct functioning of such devices needs optimal indoor acoustic criteria. Nevertheless, these criteria should also comply with dedicated acoustic requests that autistic individuals with hearing impairment or hypersensitivity to sound could need. Thus, this research represents the first attempt to balance, integrate, and develop these issues, presenting (i) a wide literature overview related to both topics, (ii) a focused analysis on real facility, and (iii) a final optimization, which takes into account, merges, and elucidates all the presented unsolved issues.

Optimization of the CCT Curves for Steels Containing Al, Cu and B

New continuous cooling transformation (CCT) equations have been optimized to calculate the start temperatures and critical cooling rates of phase formations during austenite decomposition in low-alloyed steels. Experimental CCT data from the literature were used for applying the recently developed method of calculating the grain boundary soluble compositions of the steels for optimization. These compositions, which are influenced by solute microsegregation and precipitation depending on the heating/cooling/holding process, are expected to control the start of the austenite decomposition, if initiated at the grain boundaries. The current optimization was carried out rigorously for an extended set of steels than used previously, besides including three new solute elements, Al, Cu and B, in the CCT-equations. The validity of the equations was, therefore, boosted not only due to the inclusion of new elements, but also due to the addition of more low-alloyed steels in the optimization. The final optimization was made with a mini-tab tool, which discarded statistically insignificant parameters from the equations and made them prudently safer to use. Using a thermodynamic-kinetic software, IDS, the new equations were further validated using new experimental CCT data measured in this study. The agreement is good both for the phase transformation start temperatures as well as the final phase fractions. In addition, IDS simulations were carried out to construct the CCT diagrams and the final phase fraction diagrams for 17 steels and two cast irons, in order to outline the influence of solute elements on the calculations and their relationship with literature recommendations.

Conditional optimization of mortgage loan parameters

Subject. In the article, we calculate the period of a borrowing, in which the interest burden and monthly payments are minimal. Objectives. The aim is to create an algorithm to optimize the term of the mortgage loan, taking into account the amount of debt and interest rate of the loan. Methods. The study employs methods to analyze the formula of annuity payments of a mortgage loan, and to model the final optimization algorithm. Results. We developed an algorithm, to determine the optimal term of the loan, using the certain loan amount and interest rate. The study considers the case for banks, operating in Krasnoyarsk. Conclusions. The paper considers two parameters of a mortgage loan, i.e. the interest burden and the monthly payment, which is calculated, according to the annuity formula. Both parameters depend on the loan amount, the interest rate, and the period of the loan. However, the interest rate is set by the bank, so the only parameter that the borrower can change is the period of payment. By changing the term to maturity, it is possible to have a loan with minimum payments and interest burden. For the purpose of optimization, we consider both parameters simultaneously. Taking into account their versatile nature, we consider the optimal time, when payments and interest burden are minimized. The paper also reviews the case of optimization of credit parameters for construction enterprises of the Krasnoyarsk Krai, in various banks.