Correlation Coefficient Research Articles

Classifying alkaliphilic proteins using embeddings from protein language model

Alkaliphilic proteins have great potential as biocatalysts in biotechnology, especially for enzyme engineering. Extensive research has focused on exploring the enzymatic potential of alkaliphiles and characterizing alkaliphilic proteins. However, the current method employed for identifying these proteins that requires web lab experiment is time-consuming, labor-intensive, and expensive. Therefore, the development of a computational method for alkaliphilic protein identification would be invaluable for protein engineering and design. In this study, we present a novel approach that uses embeddings from a protein language model called ESM-2(3B) in a deep learning framework to classify alkaliphilic and non-alkaliphilic proteins. To our knowledge, this is the first attempt to employ embeddings from a pre-trained protein language model to classify alkaliphilic protein. A reliable dataset comprising 1,002 alkaliphilic and 1,866 non-alkaliphilic proteins was constructed for training and testing the proposed model. The proposed model, dubbed ALPACA, achieves performance scores of 0.88, 0.84, and 0.75 for accuracy, f1-score, and Matthew correlation coefficient respectively on independent dataset. ALPACA is likely to serve as a valuable resource for exploring protein alkalinity and its role in protein design and engineering.

A low-profile high-isolation endfire MIMO antenna based on spoof surface plasmon polaritons for X-band applications

This work proposes a three-port, low-profile, coplanar endfire multiple-input-multiple-output (MIMO) antenna based on spoof surface plasmon polaritons (SSPPs). The proposed antenna comprises a coplanar waveguide (CPW)-fed SSPPs transmission line (TL). A transition to transform the CPW quasi-TEM mode to the SSPPs mode. The radiator section with asymmetric discontinuities converts the bounded SSPPs waves into radiating waves. The proposed MIMO antenna exploits the inherent feature of high isolation in the SSPPs TL due to its strong field confinement competency. Wider beamwidths for ample azimuth and elevation coverage with a stable pattern in the endfire direction are achieved in the 9.52–11.23 GHz operating band. In the operating band, the MIMO antenna has an average realized gain of 6 dBi. Mainly, it has high isolation below -35 dB (measured) in the operating range, a maximum envelope correlation coefficient (ECC) of 1.5 × 10−3, and a total active reflection coefficient (TARC) value below 0.3. The measured results are closely matched with the simulated ones in terms of S-parameters, radiation pattern, ECC, TARC, and CCL.

Development and validation of the gratitude for food scale for Japanese adults.

Gratitude for food is a concept associated with various aspects of healthy and sustainable diet and originates from Buddhism and Shintoism in Japan. Against this background, a scale specifically targeting adults is essential for boosting studies concerning gratitude for food. This study aimed to adapt the Gratitude for Food Scale (GFS), originally developed for Japanese children, to Japanese adults and to examine the reliability and validity of GFS for adults (GFS-A). This cross-sectional study used baseline and one-week follow-up data from a longitudinal survey. The analysis included 1800 Japanese adults at baseline and 1380 at the one-week follow-up based on completion of self-administered questionnaires in February 2023. Construct validity was confirmed using exploratory and confirmatory factor analyses. Further, Spearman's and intraclass correlation coefficients and Cronbach's alpha were calculated to confirm criterion validity and reliability (test-retest and internal consistency). Participants' mean (SD) age was 40.2 (11.2) years (women: n = 900, 50.0%) at baseline. The analysis revealed a one-factor structure comprising five items with good model fit. Criterion validity was confirmed by the correlation coefficients between the total GFS score and the gratitude questionnaire and the sub-score of awareness and appreciation for food, which represents a subscale of the expanded mindful eating scale. Moreover, test-retest reliability and internal consistency were confirmed. From this study's results, we can see that the developed GFS-A is an appropriate scale with good reliability and validity for measuring Japanese adults' gratitude for food.

Development and validation of the perceived symptom manageability scale among people living with the human immunodeficiency virus

Background“Perceived Symptom Manageability (PSM)” is essential in symptom management among people living with HIV. As a standardized assessment instrument was lacking, we developed a PSM scale for people living with human immunodeficiency virus (PSM-HIV).MethodsData analysis was performed using the sample from HIV-designated medical institutions (N = 540). Psychometric testing, namely reliability and validity, is assessed by unidimensionality, internal consistency, exploratory and confirmatory factor analysis, and structural equation modeling.ResultsThe final version of the PSM- HIV scale contained 15 items. This scale was submitted to a principal components analysis with varimax rotation, and three factors were obtained, explained by a total variance of 63.10%. The three factors were named Cognitive-Behavioral, Affective Interaction, and Self-Attitude. The results show that the scale had high reliability, Cronbach’s α of the scale ranged from 0.71 to 0.92, and the Intraclass Correlation Coefficient was 0.88. The structural equation model supports a factor model with the acceptable fit (χ2/df (CMIN/DF) = 2.50, Root Mean square Residual (RMR) = 0.03, Goodness-of-Fit Index (GFI) = 0.93, Adjusted Goodness of Fit Index (AGFI) = 0.90, Normed Fit Index (NFI) = 0.93, Incremental Fit Index (IFI) = 0.96, Comparative Fit Index (CFI) = 0.96). The average variance extracted was 0.38 ∼ 0.59, and the composite reliability was 0.70 ∼ 0.91, indicating that the convergent validity of the scale is acceptable. Subjects with different stages of the disease reached significance(χ2 = 9.02; df = 2, P<0.05), meaning moderate Known-Groups Comparison Validation.ConclusionsThe PSM-HIV scale is a valid instrument that measures overall attitude and belief about controlling or coping with HIV-relevant symptoms.

Real-time mapping of crop canopy temperature using a wireless network of infrared thermometers on a central pivot

Efficient irrigation is essential for sustainable food production and regional water security. Temperature measurements provide information about crop water status, which allows the estimation of water needs and precise irrigation scheduling. This paper proposes a technology for agricultural irrigation management that combines cost-effective implementation with the ability to map crop canopy temperatures using a wireless network of infrared thermometers on a center pivot. The technology integrates Wireless Sensor Networks (WSN) with scalability options, IoT capabilities, and web data availability, enabling precise plant water stress quantification based on canopy temperature and soil water content. It facilitates real-time irrigation prescriptions while the center pivot is in motion, with canopy temperature sensors providing accurate readings of +/- 0.5 °C without additional calibration. Nonlinear Autoregressive Network with Exogenous Inputs (NARX) and Long Short-Term Memory (LSTM) neural network models were trained to predict irrigation prescriptions, achieving Root Mean Squared Error (RMSE < 4.18 mm) and correlation coefficient (r^2 > 0.82). This technology will allow the definition of real-time and site-specific prescriptions for variable-rate irrigation systems using infrared temperature sensors. Future work includes exploring LoRaWAN technologies, implementing a Differential Global Positioning System (DGPS), improving spatial resolution with data fusion algorithms, refining irrigation prescription models, reducing sensor costs and developing models considering soil and crop effects.

Highly efficient catalytic degradation of organic dyes using iron nanoparticles synthesized with Vernonia Amygdalina leaf extract

Today, nanoscience explores the potential of nanoparticles due to their extraordinary properties compared to bulk materials. The synthesis of metal nanoparticles using plant extracts is a very promising method for environmental remediation, which gets global attention due to pollution-led global warming. In the present study, iron nanoparticles (FeNPs) were successfully synthesized by the green method using Vernonia amygdalina plant leaf extract as a natural reducing and capping agent. Biosynthesized FeNPs were characterized with different analytical techniques such as UV–visible, FT-IR, XRD, and SEM. The analysis revealed the formation of amorphous FeNPs with an irregular morphology and non-uniform distribution in size and shape. The average particle size was approximately 2.31 µm. According to the catalytic degradation investigation, the FeNPs produced via the green approach are highly effective in breaking down both CV and MB into non-toxic products, with a maximum degradation efficiency of 97.47% and 94.22%, respectively, when the right conditions are met. The kinetics study exhibited a high correlation coefficient close to unity (0.999) and (0.995) for the degradation of MB and CV, respectively, for the zero-order pseudo-kinetics model, which describes the model as highly suitable for the degradation of both dyes by FeNPs compared to other models. The reusability and stability of biosynthesized nano-catalysts were studied and successfully used as efficient catalysts with a slight decrease in the degradation rate more than four times. The results from this study illustrate that green synthesized FeNPs offer a cost-effective, environmentally friendly, and efficient means for the catalytic degradation of organic dyes.

A novel systematic approach for robust numerical simulation of carbon fiber-reinforced plastic circular tubes: Utilizing machine-learning techniques for calibration and validation

Developing a reliable and robust finite element model of a carbon fiber-reinforced plastic (CFRP) composite structure is investigated by using the LS-DYNA solver and Python. This study tries to provide a systematic numerical approach to cover the principal impediment to adaptation of composite energy absorbers, that is the lack of a reliable predictive method. The proposed procedure aims to further the understanding of advanced composite structures’ behavior during the crash phenomenon by developing an accurate finite element model. To do so, the mechanical properties of the material were extracted from American Society for Testing and Materials (ASTM) standard test methods, followed by experimental investigation of circular CFRP tubes undergoing quasi-static loading. A numerical simulation framework was then utilized to scrutinize the effectiveness of simulation parameters on the crushing mechanism. Finally, a systematic approach based on machine learning techniques was performed to adjust non-physical modeling parameters for further calibration and validation. In this regard, a versatile Python code was developed to automate pre-processing, processing, and post-processing steps. The code also provides a groundwork to perform machine learning techniques. Interestingly, the numerical and experimental results were highly correlated with a correlation coefficient of almost 90%. Additionally, several non-physical numerical parameters were found to be inactive, while some else were identified as effective parameters, and their corresponding effectiveness was quantitatively extracted and discussed for the first time in the literature.

Spatio-temporal Mapping of Population Density and their Characteristics of the Eastcentral Rajmahal Highlands, Jharkhand, India

Population growth and population density are two important variables for population studies. The study of human resource reveals that population in the Eastcentral Rajmahal Highlands is gradually increasing. The decadal disparity of population growth of the study area shows a positive trend with distinct fluctuations rate of increase. The study area shows the change in population density from 206 persons per sq. km and 381 persons per sq. km in 1971 and 2011 respectively. The co-efficient of correlation between population growth and population density is highly positive relationship. Maximum populations are settled in the rural areas. Only 10.79 % (47,584) of the population are urban. It represents an unbalanced rural-urban population ratio and it also shows that rural economy particularly agriculture is dominating in the study area. The purpose of this paper is to analyse as well as spatial and temporal mapping of population density in the study area.

Evaluating the influence of Cynodon dactylon on the wave force and wave erosion in the water-level fluctuation zone of the Three Gorges Reservoir Area

Wave erosion is the main erosion type in the water-level fluctuation zone (WLFZ) of the Three Gorges Reservoir Area (TGRA). Despite vegetation can effectively mitigate wave erosion in the WLFZ, its influence on the wave force and wave erosion remains unclear. Therefore, the wave experiments were conducted under 3 Cynodon dactylon coverage rates (0, 30% and 60%) and 9 wave conditions (3 wave heights of 4, 6 and 8 cm combined with 3 wave periods of 1, 2 and 3 s) to analyse the wave force (expressed as the wave pressure on the slope surface and the pore water pressure in the slope) and wave erosion rate, and the factors influencing wave erosion were identified. The results indicated that the wave pressure, pore water pressure and wave erosion rate increased by 19.14%–104.75%, 16.84%–65.04% and 23.33%–91.64%, respectively, as wave height increases. The wave pressure decreased by 1.50%–31.23% followed by an increase by 22.05% to 87.10% with the increase of wave period, whereas the pore water pressure and wave erosion rate decreased by 28.33%–53.59% and 20.46%–63.59%, respectively. However, these quantities decreased by 2.10%–50.84%, 17.06%–40.23% and 17.28%–82.18%, respectively, with the increase of Cynodon dactylon coverage rate. It was also discovered that the pore water pressure and Cynodon dactylon coverage rate attained the highest positive and negative correlation coefficients with the wave erosion rate, respectively. In addition, pore water pressure accumulation is the most critical influence factor on wave erosion, and Cynodon dactylon could effectively reduce the pore water pressure via its roots, thus improving the slope wave erosion resistance. This study could be useful to understand the mechanism of plants on controlling wave erosion and could provide a scientific reference for wave erosion control and the ecological construction in the WLFZ.

Assessment and modeling of benzene micropollutant in surface waters proximal to coal-fired thermal power plants

ABSTRACT Micropollutants of priority have gained significant attention due to their rising concentrations and persistence in aquatic environments. Among these significant micro-pollutants is benzene, released into the environment because of mining activities, thermal power plants, and certain industrial operations, thereby contributing to environmental contamination. This study monitored benzene concentrations in the Orhaneli River over a year, employing an artificial neural network (ANN) approach to formulate a predictive model for benzene micropollutant concentrations. To provide input to the ANN, Principal Component Analysis (PCA) was employed, utilizing parameters such as precipitation, temperature, humidity, pH, flow rate, dissolved oxygen, conductivity, total organic carbon, and total nitrogen. Eleven backpropagation algorithms were compared, with the Levenberg-Marquardt algorithm identified as the optimal training algorithm. For the selected training algorithm, an optimized number of 6 neurons in the hidden layer provided the best predictions for benzene concentrations. The three-layered optimized ANN model achieved an impressive correlation coefficient (R2) of 0.9889.

Development, validation, and reliability of the Chrononutrition Profile Questionnaire-Pregnancy (CPQ-P)

BackgroundDuring pregnancy, physiological changes can affect eating and sleeping habits, which may eventually have negative consequences for maternal and foetal health. To better understand these changes, it is essential to develop a reliable questionnaire that addresses lifestyle habits such as snacking and daytime napping. This study aimed to determine the validity and reliability of the Chrononutrition Profile Questionnaire-Pregnancy (CPQ-P).MethodsA total of 399 women in their second and third trimester of pregnancy were recruited from government maternal and child health clinics in Kuala Lumpur and Putrajaya and completed a self-administered online questionnaire. Content validity was conducted with an expert panel consisting of 4 members. Confirmatory factor analysis (CFA) using maximum likelihood was conducted to determine the construct validity. Internal consistency was determined by Cronbach’s alpha coefficient (CAC), while the test-retest reliability was conducted using intraclass correlation coefficient (ICC).ResultsThe questionnaire had an appropriate content validity index of 0.91. The CPQ-P consists of 22 items, measuring 5 constructs, including morning chrono-habits, sleeping habits, evening eating, temporal eating, and pregnancy symptoms. The factor model showed good fit with χ2/df = 2.486, GFI = 0.893, CFI = 0.912, and RMSEA = 0.065. The 22 items in CPQ-P showed fair to excellent test-retest reliability (ICC: 0.42 to 0.98). The 5 constructs in CPQ-P were found to have a good to excellent internal consistency (α = 0.612–0.963).ConclusionsThe CPQ-P is a valid and reliable tool for assessing lifestyle habits during pregnancy. The questionnaire can be used to identify areas where pregnant women may need additional support or intervention to adopt healthy behaviours and reduce the risk of adverse maternal and foetal outcomes.Trial registrationNCT05700136 (clinicaltrials.gov). Trial registration date: 26/01/2023.

A Novel Validated GC-MS/MS Method for the Estimation of N-Nitroso Dimethyl Amine and N-Nitroso Diethyl Amine in Zidovudine.

A novel method has been developed for the estimation of N-Nitroso dimethyl amine impurities (NDMA) and N-Nitroso diethyl amine (NDEA) in Zidovudine by using Gas chromatograph Triple Quadrupole Mass with Liquid autosampler (GC-MS/MS) and the method is validated as per International Conference on Harmonization recommendations. Sample analysis was executed for Zidovudine by developed method. Both NDMA and NDEA were detected in below quantitation limit for the Zidovudine batches. Efficient chromatographic separation was achieved on a DB-WAX 30m length × 0.25mm internal diameter, 0.5-μm film thickness, Triple quad-8040 GC-MS/MS. Quantification was carried out at Triple quad electron ionization source was at a column flow of 1.5mL/min at a column oven temperature 50°C. The precision was in the range of 0.9-2.5% for NDMA and 0.8-2.3% for NDEA, and regression analysis shows as r value (correlation coefficient) of is >0.99. This method is capable to detect the NDMA and NDEA impurities in Zidovudine at a level of 0.006ppm for limit of detection and 0.018ppm for limit of quantitation with respect to test concentration of 66.66mg/mL.

Abstract 6415: Comparison the results from PD-L1 IHC and PD-L1 multiplex immunofluorescence for the prediction of anti-PD-1 immunotherapeutic response

Abstract PD-L1 immunohistochemistry (IHC) is a popular clinical test before anti PD-1/PD-L1 immunotherapy (IMT). Multiplex immunofluorescence (mIF) exhibits its advantage to evaluate more than one target on one FFPE section to provide the features of multiple target expression and co-expression signals. Here, based on our pathology controlled mIF detection system and AI based analysis data, we compared IHC PD-L1 TPS to mIF PD-L1 TPS, PD-L1 positive rate, and other target positive rates in one mIF panel, to evaluate their correlations. The correlations of IHC PD-L1 TPS, mIF PD-L1 TPS, mIF PD-L1 positive rate and other marker positive rate to anti PD-1 IMT response were further analyzed in this study. Thirty melanoma patient samples in this study have received PD-1 IMT. 13 cases exhibited partial response (PR) and 17 cases were progressive disease (PD). PFS of PR group and PD group was 27.3 and 4.8 months, respectively. Archived patient FFPE sections were examined utilizing mIF of PN 6-Plex Detection Kit (Beijing PhenoVision Bio Co., Itd) targeted CD68, CD3, CD20, S100, PD-L1 (CST, E1L3N) and PD-1. The staining images were scanned, tumor areas were labeled by pathologists and analyzed using PhenoVision mIF AI analysis system trained from Oncotopix Discovery system (Visopharm). Series sections were examined utilizing Dako PD-L1 IHC 22C3 pharmDx and TPS was scored by one clinical pathologist. mIF TPS was calculated after AI data analysis, using PD-L1/S100 co-positive cell number divided by S100 positive cell number. Data mining was performed using log-rank Mantel-Cox test, Cox regression analysis and binary logistic regression model in SPSS. In current study, the correlation between pathology scored TPS (pTPS) and mIF PD-L1 positive rate was observed (Pearson correlation coefficient (PCC)=0.447, p&amp;lt;0.05). The consistency rate between pTPS and mIF TPS was 70% with no statistical significance. Moreover, the correlation between pTPS and mIF PD1/CD3 copositive rate was detected (PCC=0.604, p&amp;lt;0.01). Interestingly, mIF PD-1/CD3 copositive rate predicted PR and PD groups (AUC=0.8, p&amp;lt;0.01). Not pTPS nor mIF PD-L1 rate showed predictions here. Current results indicate that pTPS exhibited correlation to mIF PD-L1 positive rate instead of mIF PD-L1 TPS. CD3/PD-1 copositive rate but not pTPS nor mIF PD-L1 positive rate, shows its potential to predict anti PD-1 IMT response through the pathology controlled mIF detection system and AI based analysis system. Citation Format: Hongzhe Sun, Xia Liu, Tao Jiao, Qian Guo, Haizhen Du, Shuo Han, Lin Zhu, Zhifu Zhang, Yan Kong, Na Li. Comparison the results from PD-L1 IHC and PD-L1 multiplex immunofluorescence for the prediction of anti-PD-1 immunotherapeutic response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6415.

Exploiting the temporal characteristics of tidal stream power for green ammonia production

Green ammonia, a promising zero-carbon energy storage vector, has never been produced using solely tidal stream energy despite its predictable characteristics. Combining tidal stream sites with a phase difference (tidal phasing) facilitates anticorrelation between these sites’ power profiles, enabling a more consistent power output. Green ammonia production benefits from a steady and predictable power input. The objective of this paper is to determine if nearby tidal sites have a large enough phase difference (anticorrelation) to reduce the cost of ammonia production. Moreover, producing green ammonia from underutilized or unutilized remote and grid-constrained tidal stream sites may enable viability of these sites. This paper is the first analysis of green ammonia production using solely tidal stream energy and the first analysis of tidal phasing for green fuel production. Two UK case studies are presented in i) the North Channel of the Irish Sea and ii) Orkney. There are tidal sites in each which have a phase difference (e.g. the Mull of Kintyre/Sound of Islay, and Graemsay/North Ronaldsay with correlation coefficients of 0.17 and −0.02 respectively), utilising this phase difference reduces the levelized cost of ammonia by 8% in the Irish Sea and by 12% in Orkney.

A UPLC-MS/MS method for simultaneous determination of arachidonic acid, stearic acid, and related endocannabinoids in human plasma

Endocannabinoids (eCBs) exert considerable influence over energy metabolism, lipid metabolism, and glucose metabolism within the human body. Among the most biologically active cannabinoids identified thus far are 2-arachidonoylglycerol (2-AG), arachidonoyl ethanolamide (AEA), 1-stearoylglycerol (1-SRG), and stearoyl ethanolamide (SEA), which are derived from arachidonic acid (AA) and stearic acid (SA). However, despite the unique in bioactivities exhibited by eCBs, their determination in plasma has been hindered by the lack of sensitive analytical methods. The aim of this study was to develop and validate a highly sensitive and rapid method using ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) for accurate measurement of AEA, SEA, 2-AG, 1-SRG, AA, and SA levels in human plasma samples. Sample preparation involved a protein precipitation method and a methyl tert-butyl ether liquid-liquid extraction method. Chromatographic separation was accomplished by utilizing an ACQUITY UPLC BEH C8 column with a mobile phase of acetonitrile containing 0.1% formic acid and water containing 0.1% formic acid, flowing at a rate of 0.35 mL/min. AA-d8, 2-AG-d5, and AEA-d8 were selected as deuterated internal standards. The analytes were determined with MRM in both positive and negative ion mode. The lower limit of quantification ranged from 0.1 to 400 ng/mL, and the correlation coefficient (R2) was >0.99. Inter-day and intra-day precision exhibited values of 0.55–13.29% and 0.62%–13.90%, respectively. Recovery and matrix effect were within the range of 77.7%–109.7%, and 90.0%–113.5%, respectively. Stability tests confirmed the acceptability of all analytes. To demonstrate the effectiveness of the approach, it was implemented to assess and compare plasma samples from healthy volunteers (n = 49) and individuals with non-alcoholic fatty liver disease (NAFLD) (n = 62). The study revealed significant differences in AEA, SEA, AA, and SA levels between the two groups.

Comparative evaluation of drying methods for struvite produced from electrocoagulated source-separated urine: Implications for quality, energy and cost-effectiveness

Struvite precipitation from source-separated urine is crucial for waste utilization and sustainability. However, after precipitation, the high moisture content of struvite necessitates an additional drying process that can be costly and inefficient. In the present study, the performance of different drying methods—open sun drying, air drying, conventional drying (20–100 °C), and microwave drying (180–720 W) on the quality of struvite obtained from source-separated urine through electrocoagulation using Mg–Mg electrodes were evaluated. It was found that higher temperatures and power in the convective oven and microwave resulted in higher diffusivity (10−9-10−7 m2s−1), leading to reduced drying times. Different models were employed to comprehend the drying mechanism, and the one with the highest correlation coefficient (R2 = 0.99) and the lowest statistical values was selected. The key findings indicated that higher power and temperature levels were more cost-effective. However, characterization of the dried struvite using X-ray diffraction and Fourier-transformed infrared spectroscopy, disintegration of struvite crystals at temperatures above 60 °C in the conventional oven and 180 W in the microwave oven was observed. Based on the results, we conclude that sun drying is a cost-effective and environmentally friendly alternative for drying struvite without compromising its quality.

A New Strategy for Planning Urban Park Green Spaces by Considering Their Spatial Accessibility and Distributional Equity

Urban park green spaces (PGSs) are crucial social public resources that provide various ecological services and enhance human health and well-being. However, with the acceleration of urbanization, the accessibility and equity of urban PGS resources are increasingly threatened. This study aims to propose an integrated framework that considers accessibility and equity simultaneously to optimize the planning and layout of urban PGS within the high-speed ring road of Hefei City. This study first used an improved two-step floating catchment area (2SFCA) method to quantify the level of accessibility of urban PGS within the ring road. Then, with the use of Lorenz curves, Gini coefficients, and bivariate correlation coefficients, the equity characteristics of these PGSs were quantified and evaluated, followed by an analysis of their relationships to the accessibility levels. Based on this comprehensive evaluation, the particle swarm optimization (PSO) algorithm was employed to the areas with low accessibility and equity levels to propose targeted PGS optimization strategies. The results showed that the accessibility of PGS was unevenly distributed, exhibiting a clear spatial difference of “east–west clustering”. The number of subdistricts with good (52.24–94.78) and best (94.79–283.58) accessibility was four, which was less than one-tenth of the total number of subdistricts in the study area. At the subdistrict level, the Gini coefficients for the accessible area of all types of PGSs were substantially higher than the international warning line of 0.4, indicating a substantial inequity in the population’s access to PGS. The implemented PSO algorithm resulted in eight new parks being planned at the specific optimized locations. Based on the actual land use status of the selected sites, recommendations are provided for the planning and layout of PGS. This proposed framework offers valuable data and theoretical insights for urban public green space planning and design in similar regions.

Solubility evaluation of palm-based Mono-diacylglycerols (MDAGs) in food grade solvent (hexane, ethanol, acetone, water) using QSPR model approach

Mono-diacylglycerols (MDAGs) are emulsifiers widely used in the food industry. MDAGs based on refined bleached deodorized palm stearin (RBDPS) have not been widely developed. MDAGs have been synthesized using glicerolysis between RBDPS and glycerols. Due to their low solubility in food-grade solvents (hexane, ethanol, acetone, and water), it has been difficult to purify or fractionate MDAGs only by a simple method. This research attempted to develop a model of MDAGs solubility in food-grade solvents and understand the parameters that influence the solubility of MDAGs in food-grade solvents. The process used a combination of experimental data collection and quantitative structure–property relationship (QSPR) models. The QSPR model for MDAGs solubility in a single and binary solvent demonstrated that the descriptors of Δ dipole moment (Δµ), E HOMO, E LUMO, electronic energy, gap energy HOMO-LUMO (ΔE1, ΔE2) softness (S), electrophilicity index (ω), and electron transfer (ΔN) have a significant impact in determining the solubility of MDAGs. Both the single and the binary solvents solubility models can give satisfactory prediction results: the square of the correlation coefficient (R2pred) was 0.933 and 0.948, and the root-mean-square error (RMSE) was 0.075 and 0.031, respectively, for the whole data set. In addition, this paper provided a new and effective method for predicting the solubility of MDAGs in single and binary food-grade solvent systems.

Doubly stochastic subdomain mining with sample reweighting for unsupervised domain adaptive person re-identification

Clustering-based unsupervised domain adaptive person re-identification methods have achieved remarkable progress. However, existing works are easy to fall into local minimum traps due to the optimization of two variables, feature representation and pseudo labels. Besides, the model can also be hurt by the inevitable false assignment of pseudo labels. In order to solve these problems, we propose the Doubly Stochastic Subdomain Mining (DSSM) to prevent the nonconvex optimization from falling into local minima in this paper. And we also design a novel reweighting algorithm based on the similarity correlation coefficient between samples which is referred to as Maximal Heterogeneous Similarity (MHS), it can reduce the adverse effect caused by noisy labels. Extensive experiments on two popular person re-identification datasets demonstrate that our method outperforms other state-of-the-art works. The source code is available at https://github.com/Tchunansheng/DSSM.

Potential smoke-free dividend across local areas in England: a cross-sectional analysis

BackgroundThe value that might be added to local economies each year through the money that people who smoke tobacco would save if everyone quit smoking is called the ‘smoke-free dividend’....