Multiple Techniques Research Articles

Effect of glass powder on compressive strengths and microstructure of ultra-high-performance concrete

The most common methods for dealing with waste glass are landfilling or incineration, which cause wastage of resources. The method for preparing ultra-high-performance concrete (UHPC) by partially substituting cement with glass powder (GP) was herein studied in order to realize the high value treatment of waste glass. The experimental results indicated that incorporation of 5% GP brought the highest compressive strengths for UHPC, which was increased by 5.11%, compared to the control UHPC in 28 days. Furthermore, the later-stage compressive strengths for UHPC at 60 days increased continuously with incorporation of 10% and 15% GP, respectively, indicating that GP does not hinder the development of strengths. Using multiple micro testing techniques, it was indicated that, GP exhibited pozzolanic reaction and dilution effect, which can enhance cement hydration and increased the amount of hydration products. Thus, the microstructure of UHPC with appropriate amount of GP was significantly improved. In addition, the CO2 emissions and production costs for UHPC decreased steadily with increased GP content. Compared to the control UHPC, UHPC with 15% GP exhibited decreased by 1.47% in production costs and 7.39% in CO2 emissions.

In Vitro Propagation Technology for the Endangered Aquatic Species Nymphoides coronata.

Nymphoides coronata is an endangered aquatic plant species with significant medicinal and ecological importance. To preserve N. coronata from going extinct, we need to provide seedlings and efficient multiplication techniques so that it can be extensively studied. This study aimed to identify the most suitable sterilization treatment, growth medium, and substrate for the cultivation and propagation of N. coronata. Ethanol sterilization, fungicide treatment, and sterile water washing were the most important sterilization steps. A combination of 6-benzylaminopurine (6-BA) and indoleacetic acid (IAA) was the most suitable medium for bud induction and shoot proliferation. The use of α-naphthaleneacetic acid (NAA) increased the rooting rate and rooting time compared to indole-3-butyric acid (IBA). Increasing the concentration of NAA from 0.5 to 1.0 mg/L increased the rooting rate from 78 to 100% and reduced the rooting time from 7 to 5 days. The survival rate of N. coronata seedlings was 100% in a mixture of red soil and sand (1:1, w/w). As a result, the procedure mentioned above could potentially be used to safely propagate this rare species on a large scale. These findings provide valuable insights into the optimal conditions for the successful cultivation and propagation of N. coronata, which can contribute to the conservation and sustainable use of this important rare plant species.

Generating realistic infrared spectra using artificial neural networks

AbstractArtificial spectra were generated to match the different acid solubility properties of the rocks. The purpose of generating artificial spectra was to increase the number of samples available for future data processing with a convolutional neural network. The samples were collected from different geological matrices during targeted rock tests to support industrial applications. The inherent characteristics of the samples are their uneven distribution in the parameter space of the features and their limited availability for data‐intensive studies. Both data set characteristics constrain the prediction performance of the machine learning methods to estimate the unknown solubility of samples in the chosen acids. If the sample multiplication techniques are performed without considering the relationship between solubility of samples and their infrared spectra, the synthetic samples adversely impact the efficacy of the prediction method. By utilizing a dimensionality reduction technique (principal component analysis) and a neural network, we established a relationship between the solubility of the samples and their infrared spectra. Infrared spectra of the samples used for learning the model could be efficiently reproduced and infrared spectra of created samples could be generated. The reliability of the applied method has been shown by the comparison of the original and artificial spectra through a mean Pearson correlation coefficient and by comparing the closest neighbors to each other. This method can be used to create new samples and their infrared spectra, where different constraints must be met and the samples must be connected to the infrared spectrum.

Forecasting sustainable development goals scores by 2030 using machine learning models

AbstractThe Sustainable Development Goals (SDGs) set by the United Nations are a worldwide appeal to eliminate poverty, preserve the environment, address climate change, and guarantee that everyone experiences peace and prosperity by 2030. These 17 goals cover various global issues concerning health, education, inequality, environmental decline, and climate change. Several investigations have been carried out to track advancements toward these goals. However, there is limited research on forecasting SDG scores. This research aims to forecast SDG scores for global regions by 2030 using ARIMAX and LR (Linear Regression) smoothed by HW (Holt‐Winters') multiplicative technique. To enhance model performance, we used predictors identified from the SDGs that are more likely to be influenced by Artificial Intelligence (AI) in the future. The forecast results for 2030 show that “OECD countries” (80) (with a 2.8% change) and “Eastern Europe and Central Asia” (74) (with a 2.37% change) are expected to achieve the highest SDG scores. “Latin America and the Caribbean” (73) (with a 4.17% change), “East and South Asia” (69) (with a 2.64% change), “Middle East and North Africa” (68) (with a 2.32% change), and “Sub‐Saharan Africa” (56) (with a 7.2% change) will display lower levels of SDG achievement, respectively.

Semiparametric and multiplicative bias correction techniques for second-order discrete kernels

In this article, we propose to estimate the probability mass function (pmf) of a discrete supported random variable by a semiparametric bias corrected method using discrete associated kernels. This method consists in applying a two-stage multiplicative bias correction (MBC) approach for the initial parametric model in order to improve the accuracy of the estimator measured in terms of the vanishing bias. Various properties of the resulting semiparametric MBC discrete associated kernel estimator are provided (bias, variance, and mean integrated squared error). The common cross-validation technique and the Kullback–Leibler divergence are adapted for bandwidth selection. Monte Carlo simulations and a real-data application for count data illustrate the performance of the semiparametric-MBC estimator.

A novel code representation for detecting Java code clones using high-level and abstract compiled code representations.

In software development, it's common to reuse existing source code by copying and pasting, resulting in the proliferation of numerous code clones-similar or identical code fragments-that detrimentally affect software quality and maintainability. Although several techniques for code clone detection exist, many encounter challenges in effectively identifying semantic clones due to their inability to extract syntax and semantics information. Fewer techniques leverage low-level source code representations like bytecode or assembly for clone detection. This work introduces a novel code representation for identifying syntactic and semantic clones in Java source code. It integrates high-level features extracted from the Abstract Syntax Tree with low-level features derived from intermediate representations generated by static analysis tools, like the Soot framework. Leveraging this combined representation, fifteen machine-learning models are trained to effectively detect code clones. Evaluation on a large dataset demonstrates the models' efficacy in accurately identifying semantic clones. Among these classifiers, ensemble classifiers, such as the LightGBM classifier, exhibit exceptional accuracy. Linearly combining features enhances the effectiveness of the models compared to multiplication and distance combination techniques. The experimental findings indicate that the proposed method can outperform the current clone detection techniques in detecting semantic clones.

Fabry–Perot interference temperature sensor integrated high-power-laser optical fiber probe for laser ablation

In this study, an optical fiber probe with an extremely short integrated temperature sensor for high-power laser ablation was proposed and successfully fabricated. Both optical mode and wavelength multiplication were performed simultaneously using a double-clad fiber with a wavelength-division multiplication technique. The wavelength shift with temperature showed a linear relationship with a sensitivity of 10 pm/°C. High-power laser irradiation of 1000 mW or more using multimode transmission and fine temperature monitoring using single-mode transmission were performed simultaneously with a system response time of a few seconds. The laser wavelength selection and power variation can increase the variability of the heating region required for medical applications.

A Low-Voltage Self-Starting Boost Converter Using MPPT with Pulse Multiplication for Energy Harvesting

A single-inductor, low-voltage, three-step self-starting boost converter is proposed for photovoltaic (PV) energy harvesting. In order to enhance energy transfer efficiency, a variable-step Perturb and Observe (P&O) Maximum Power Point Tracking (MPPT) scheme has been devised based on a novel pulse multiplication technique. Upon overcoming the speed and accuracy limitations, the maximum power point (MPP) of the PV model is accurately tracked. In the boost converter, the average inductor current is utilized to implement closed-loop control of the MPPT loop, enhancing the stability of the tracking process and enabling efficient energy transmission. Finally, the boost converter is implemented using a 0.18 μm CMOS process, which is capable of self-starting and maintaining stable operations at input voltages ranging from 90 mV to 300 mV, achieving a peak efficiency of 93%.

Fear of failure among perfectionist students

Fear of failure (FOF) has been reported as a construct that hinders individuals from achieving higher, working harder, and even moving from one stage of development to another. Studies indicated that university students with traits perfectionism tend to develop FOF, which prevented them for achieving better accomplishment in their academic life. In order to obtain further knowledge to curb FOF among this population, this study investigates which one of the three dimensions of perfectionism (self-oriented, other-oriented, socially prescribed) is the main predictor of FOF. 351 participants from the target population of 4,000 undergraduate students from UCSI University, Kuala Lumpur, Malaysia were recruited via convenience sampling to provide us with their data through a Google Form. Perfectionism dimensions were measured by the multidimensional perfectionism scale and fear of failure by the performance failure appraisal inventory. The collected data was analyzed via simple and multiple regression by multiple regression technique, and the findings showed that self-oriented and other-oriented perfectionism did not significantly predict the fear of failure. However, socially prescribed perfectionism was the only significant predictor of the fear of failure among the perfectionism model, therefore indicating that it was the most significantly predictor as well. In conclusion, students are more likely to be afraid to fail when they believe that there is a social standard of perfection that they have to follow.

A comparative assessment of OMP and MATLAB for parallel computation

The prime goal of parallel computing is the simultaneous parallel execution of several program instructions. Consequently, to accomplish this, the program should be divided into independent sets so that each processor can execute its program part concurrently with the other processors. This study compares OMP and MATLAB, two important parallel computing simulation tools, through the use of a dense matrix multiplication technique. The results showed that OMP outperformed the MATLAB parallel environment by over 8 times in sequential execution and 6 times in parallel execution. From this proposed method, it was also observed that OMP with an even slower processor performs much better than MATLAB with a higher processor. Thus, the present analysis indicates that OMP is a superior environment for parallel computing and should be preferred over parallel MATLAB.

An Approach to the Performance of Passport Services through Workload and Work Environment: Study at the Wonosobo Immigration Office

This study aims to identify the effect of workload and work environment on the performance of passport issuance services at the Wonosobo Immigration Office. Workload is defined as a series of tasks that must be carried out by a work unit within an organization or by an individual who serves in a position within a certain period of time. Meanwhile, the work environment is defined as a place where a worker completes his duties in accordance with the goals to be achieved. There is a mismatch in the number of human resources in passport services compared to the high level of passport applications. The research method used in this research is quantitative method. Data collection was carried out through observation and distribution of questionnaires. Sampling using total sampling techniques, and data analysis was carried out using a Likert scale. The data analysis technique applied in this study is using multiple linear regression data analysis techniques. The results of data collection show the significance of workload of 0.32 and work environment of 0.21 greater than 0.05, which means that there is an influence of workload and work environment on employee performance in passport services. This study recommends increasing the number of human resources and improving the work environment to improve the performance of passport issuance services.

Standardization of in vitro multiplication technique for Areca concinna Thwaites, an endangered palm species for its conservation and utilization

Standardization of in vitro multiplication technique for Areca concinna Thwaites, an endangered palm species for its conservation and utilization

The influence of microphase separation structure of silicon-containing polyurethane on its wear resistance

This study incorporated polydimethylsiloxane (PDMS) and a kind of siloxane-based chain extender (SDO) into polyether urethanes (PEU). The correlation between microphase separation structure and mechanical properties, surface properties and wear resistance were investigated using multiple characterization techniques such as DSC, DMA, SAXS, ATR-FTIR, and XPS. The addition of PDMS significantly reduced the friction coefficient of PEU and enhances the hydrophobicity. The addition of SDO helped to improve the compatibility between PDMS and hard segments of PEU as proved by the fact that the glass transition temperatures of PDMS segments were shifted to higher temperatures and the fraction of loosely hydrogen-bonded carbonyls increased. Due to the improved interfacial adhesion between the immiscible segments, the wear resistance of PEU modified by both PDMS and SDO was obviously enhanced.

Hydration behavior and cementitious properties of steel slag: From an early age to a long-term

In China, steel slag as a solid waste caused land occupation and environmental pollution, and its utilization ratio is relatively low. To increase the utilization field and ratio of steel slag, hydration behavior and cementitious properties of three types of steel slag were investigated and compared based on test results from an early age to a long-term via multiple techniques. Experimental results suggested that steel slag showed a strong latent hydraulic activity at a later age, and the mechanical strength of steel slag paste specimens (w/b=0.3) could reach 15 MPa at 360 days. Cementitious properties of steel slag were primally depended on the hydration of calcium silicate (C3S and C2S), calcium aluminate (ferrite), glassy phase in steel slag, especially for calcium silicate. The sum amount of calcium silicate in used steel slag was approximately from 21% to 28%, and the amount of C2S was significantly greater than that of C3S. The hydration of C2S and glassy phase resulted in the continuous increase in bound water content of steel slag, and a certain content of C2S still existed in pastes at 360 days. The mechanical strength of steel slag pastes markedly increased at a later age due to more hydrates formed in the microstructure.

Fire simulation effects on the transformation of iron minerals in alpine soils

Heat-induced changes in topsoil iron (Fe) species triggered by the relatively low temperatures (Ts) produced by wildfires (200–300 °C) have not been fully elucidated. Changes in the chemistry of Fe minerals can produce cascading impacts on the environment, and the resulting aftermath may be exacerbated in erosion-prone alpine soils. The aim of this study was to determine - at environmentally realistic conditions - changes in the composition and crystallinity of Fe species, and the dispersible organic matter (OM) pool (evaluated by the pyrophosphate extraction), as a function of rising Ts, native Fe phases and OM in alpine soils. Multiple techniques were employed, including X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), magnetic measurements and Fe K-edge X-ray absorption spectroscopy (XAS). The results demonstrated the dominance of poorly crystalline Fe phases at 300 °C. At the same T, we observed the partial conversion of maghemite to hematite (supporting the involvement of oxidative processes) and, in the presence of high organic carbon (OC) contents, an enrichment in magnetic minerals (suggesting the onset of reducing conditions). The heat-induced modifications in Fe species and organic compounds did not promote the stabilization of the remaining OM, highlighting the weak nature of soil organo-mineral associations in an after-fire scenario. These phenomena can be further aggravated in case of the steep terrain that characterize alpine soils.

Improving depth uncertainty in plenoptic camera-based velocimetry

This work describes the development of a particle tracking velocimetry (PTV) algorithm designed to improve three-dimensional (3D), three-component velocity field measurements using a single plenoptic camera. Particular focus is on mitigating the longstanding depth uncertainty issues that have traditionally plagued plenoptic particle image velocimetry (PIV) experiments by leveraging the camera’s ability to generate multiple perspective views of a scene in order to assist both particle triangulation and tracking. 3D positions are first estimated via light field ray bundling (LFRB) whereby particle rays are projected into the measurement volume using image-to-object space mapping. Tracking is subsequently performed independently within each perspective view, providing a statistical amalgamation of each particle’s predicted motion through time in order to help guide 3D trajectory estimation while simultaneously protecting the tracking algorithm from physically unreasonable fluctuations in particle depth positions. A synthetic performance assessment revealed a reduction in the average depth errors obtained by LFRB as compared to the conventional multiplicative algebraic reconstruction technique when estimating particle locations. Further analysis using a synthetic vortex ring at a magnification of − 0.6 demonstrated plenoptic-PIV capable of maintaining the equivalent of 0.1–0.15 voxel accuracy in the depth domain at a spacing to displacement ratio of 5.3–10.5, an improvement of 84–89% compared to plenoptic-PIV. Experiments were conducted at a spacing to displacement ratio of approximately 5.8 to capture the 3D flow field around a rotor within the rotating reference frame. The resulting plenoptic-PIV/PTV vector fields were evaluated with reference to a fixed frame stereoscopic-PIV (stereo-PIV) validation experiment. A systematic depth-wise (radial) component of velocity directed toward the wingtip, consistent with observations from prior literature and stereo-PIV experiments, was captured by plenoptic-PTV at magnitudes similar to the validation data. In contrast, the plenoptic-PIV did not discern any coherent indication of radial motion. Our algorithm constitutes a significant advancement in enhancing the functionality and versatility of single-plenoptic camera flow diagnostics by directly addressing the primary limitation associated with plenoptic imaging.Graphical abstract

Reyanning mixture inhibits M1 macrophage polarization through the glycogen synthesis pathway to improve lipopolysaccharide-induced acute lung injury

Ethnopharmacological relevanceReyanning (RYN) mixture is a traditional Chinese medicine composed of Taraxacum, Polygonum cuspidatum, Scutellariae Barbatae and Patrinia villosa and is used for the treatment of acute respiratory system diseases with significant clinical efficacy. Aim of the studyAcute lung injury (ALI) is a common clinical disease characterized by acute respiratory failure. This study was conducted to evaluate the therapeutic effects of RYN on ALI and to explore its mechanism of action. Materials and methodsUltra-high-performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS) was used to analyze the chemical components of RYN. 7.5 mg/kg LPS was administered to induce ALI in rats. RYN was administered by gavage at doses of 2 ml/kg, 4 ml/kg or 8 ml/kg every 8 h for a total of 6 doses. Observations included lung histomorphology, lung wet/dry (W/D) weight ratio, lung permeability index (LPI), HE staining, Wright-Giemsa staining. ELISA was performed to detect the levels of TNF-α, IL-6, IL-10, Arg-1,UDPG. Immunohistochemical staining detected IL-6, F4/80 expression. ROS, MDA, SOD, GSH/GSSG were detected in liver tissues. Multiple omics techniques were used to predict the potential mechanism of action of RYN, which was verified by in vivo closure experiments. Immunofluorescence staining detected the co-expression of CD86 and CD206, CD86 and P2Y14, CD86 and UGP2 in liver tissues. qRT-PCR detected the mRNA levels of UGP2, P2Y14 and STAT1, and immunoblotting detected the protein expression of UGP2, P2Y14, STAT1, p-STAT1. ResultsRYN was detected to contain 1366 metabolites, some of the metabolites with high levels have anti-inflammatory, antibacterial, antiviral and antioxidant properties. RYN (2, 4, and 8 ml/kg) exerted dose-dependent therapeutic effects on the ALI rats, by reducing inflammatory cell infiltration and oxidative stress damage, inhibiting CD86 expression, decreasing TNF-α and IL-6 levels, and increasing IL-10 and Arg-1 levels. Transcriptomics and proteomics showed that glucose metabolism provided the pathway for the anti-ALI properties of RYN and that RYN inhibited lung glycogen production and distribution. Immunofluorescence co-staining showed that RYN inhibited CD86 and UGP2 expressions. In vivo blocking experiments revealed that blocking glycogen synthesis reduced UDPG content, inhibited P2Y14 and CD86 expressions, decreased P2Y14 and STAT1 mRNA and protein expressions, reduced STAT1 protein phosphorylation expression, and had the same therapeutic effect as RYN. ConclusionRYN inhibits M1 macrophage polarization to alleviate ALI. Blocking glycogen synthesis and inhibiting the UDPG/P2Y14/STAT1 signaling pathway may be its molecular mechanism.

CAREER DEVELOPMENT DAN WELFARE ALLOWANCES TERHADAP EMPLOYEE PERFORMANCE PADA KARYAWAN LEMBAGA AMIL ZAKAT

This study aims to explore and analyze the influence of career development and welfare benefits on employee performance at amil zakat institutions. The method used is a quantitative method that focuses on hypothesis testing. The sample used was 45 employees, using a random sampling technique. Data was collected by distributing questionnaires which were then processed using SPSS tools through multiple linear regression techniques. We consider validity and reliability to determine the reliability of the research statement items. Then, this study also considers classic assumptions such as normality, multicollinearity, and heteroscedasticity. After all that is fulfilled, then the hypothesis testing is carried out. The findings of this study prove that career development and welfare benefits have a significant positive effect on employee performance.

Mechanically and Thermally Robust Gel Electrolytes Built from A Charged Double Helical Polymer.

Polymer electrolytes have received tremendous interest in the development of solid-state batteries, but often fall short in one or more key properties required for practical applications. Herein, a rigid gel polymer electrolyte prepared by immobilizing a liquid mixture of a lithium salt and poly(ethylene glycol) dimethyl ether with only 8 wt% poly(2,2'-disulfonyl-4,4'-benzidine terephthalamide) (PBDT) is reported. The high charge density and rigid double helical structure of PBDT lead to formation of a nanofibrillar structure that endows this electrolyte with stronger mechanical properties, wider temperature window, and higher battery rate capability compared to all other poly(ethylene oxide) (PEO)-based electrolytes. The ion transport mechanism in this rigid polymer electrolyte is systematically studied using multiple complementary techniques. Li/LiFePO4 cells show excellent capacity retention over long-term cycling, with thermal cycling reversibility between ambient temperature and elevated temperatures, demonstrating compelling potential for solid-state batteries targeting fast charging at high temperatures and slower discharging at ambient temperature.

SISTEM PENDUKUNG KEPUTUSAN PENERIMA BERAS MISKIN (RASKIN) DENGAN METODE WEIGHTED PRODUCT BERBASIS WEB PADA KELURAHAN PLELEN

The Plelen Subdistrict Office is one of the government offices in Batang district, Central Java, which implements the RASKIN program, where the selection of prospective RASKIN recipients is still recorded manually. So that residents who should receive assistance will receive it according to the required criteria and will no longer be the wrong target for RASKIN recipients. Therefore, there is a need for a Decision Support System that can make it easier for sub-district employees to make decisions for residents who receive Poor Rice (RASKIN). With the existence of a decision support system (DSS), the aim is to make decisions more quickly and accurately. One method used is Weighted Product. The Weighted Product method is a method of determining order (priority) in multicriteria analysis and uses a multiplication technique to connect attribute ratings, where the rating of each attribute must first be raised to the power of the weight of the attribute in question.