bluuebunny/crossref_metadata_2025 huggingface dataset:
Classification and Identification of Contaminants in Recyclable Containers Based on a Recursive Feature Elimination-Light Gradient Boosting Machine Algorithm Using an Electronic Nose
Authors: Ba Fushuai , Peng Peng , Zhang Yafei , Zhao Yongli
Published: October 2023

Establishing an excellent recycling mechanism for containers is of great importance for environmental protection, so many technical approaches applied during the whole recycling stage have become popular research issues. Among them, classification is considered a key step, but this work is mostly achieved manually in practical applications. Due to the influence of human subjectivity, the classification accuracy often varies significantly. In order to overcome this shortcoming, this paper proposes an identification method based on a Recursive Feature Elimination-Light Gradient Boosting Machine (RFE-LightGBM) algorithm using electronic nose. Firstly, odor features were extracted, and feature datasets were then constructed based on the response data of the electronic nose to the detected gases. Afterwards, a principal component analysis (PCA) and the RFE-LightGBM algorithm were applied to reduce the dimensionality of the feature datasets, and the differences between these two methods were analyzed, respectively. Finally, the differences in the classification accuracies on the three datasets (the original feature dataset, PCA dimensionality reduction dataset, and RFE-LightGBM dimensionality reduction dataset) were discussed. The results showed that the highest classification accuracy of 95% could be obtained by using the RFE-LightGBM algorithm in the classification stage of recyclable containers, compared to the original feature dataset (88.38%) and PCA dimensionality reduction dataset (92.02%).
Ultrafast Infrared Laser Crystallization of Amorphous Ge Films on Glass Substrates
Authors: Cheng Yuzhu , Bulgakov Alexander V. , Bulgakova Nadezhda M. , Beránek Jiří , Zukerstein Martin , Milekhin Ilya A. , Popov Alexander A. , Volodin Vladimir A.
Published: October 2023

Amorphous germanium films on nonrefractory glass substrates were annealed by ultrashort near-infrared (1030 nm, 1.4 ps) and mid-infrared (1500 nm, 70 fs) laser pulses. Crystallization of germanium irradiated at a laser energy density (fluence) range from 25 to 400 mJ/cm2 under single-shot and multishot conditions was investigated using Raman spectroscopy. The dependence of the fraction of the crystalline phase on the fluence was obtained for picosecond and femtosecond laser annealing. The regimes of almost complete crystallization of germanium films over the entire thickness were obtained (from the analysis of Raman spectra with excitation of 785 nm laser). The possibility of scanning laser processing is shown, which can be used to create films of micro- and nanocrystalline germanium on flexible substrates.
Zircon as a Monitoring Tool for the Magmatic–Hydrothermal Process in the Granitic Bedrock of Shitouping Ion-Adsorption Heavy Rare Earth Element Deposit, South China
Authors: Gong Liangxin , Wang Xianguang , Zhang Defu , Zhong Wen , Cao Mingxuan
Published: October 2023

The Shitouping pluton in Jiangxi Province, southern China, hosts an ion-adsorption heavy rare earth element (HREE) deposit identified by a recent geological survey. This study reveals the HREE pre-enrichment mechanism during the magmatic–hydrothermal process of granitic bedrock based on the comprehensive study of zircon structure and composition. Zircon from the Shitouping pluton, composed of syenogranite and monzogranite, can be categorized into three types based on structure and compositions. The Type-1 zircons, the predominate type in monzogranite, are early magmatic zircons with prismatic crystals and bright oscillatory zoning in CL images. In contrast, the late magmatic-hydrothermal zircons (Type-2 and Type-3) mainly occur in the syenogranite. The Type-2 zircons occur as dark CL images and euhedral crystals crystallized during the late magmatic stage. The Type-3 zircons with irregular zoning and abundant mineral inclusions in BSE images are possibly formed via intense hydrothermal alteration during the hydrothermal stage. The increase in Y/Ho ratios from Type-1 to Type-3 zircon indicates that the Shitouping syenogranites underwent magmatic to hydrothermal evolution. Compared with Type-1 and Type-2 zircons, Type-3 zircons exhibit the highest concentrations of F and HREEs. The significant increase in HREE concentrations both in zircons and bulk-rock composition of syenogranite can be attributed to the introduction of HREE-rich fluids during magma evolution. Therefore, we propose that the increase in HREE contents in zircon reflect the exsolution of HREE-rich fluids during a late stage in the magma evolution, which is an important factor controlling HREE enrichment in Shitouping syenogranites and furthermore in the generation of ion-adsorption HREE deposits.
Synthesis, Herbicidal Activity, Mode of Action, and In Silico Analysis of Novel Pyrido[2,3-d]pyrimidine Compounds
Authors: Min Lijing , Liang Wei , Bajsa-Hirschel Joanna , Ye Peng , Wang Qiao , Sun Xinpeng , Cantrell Charles L. , Han Liang , Sun Nabo , Duke Stephen O. , Liu Xinghai
Published: October 2023

Natural products are a main source of new chemical entities for use in drug and pesticide discovery. In order to discover lead compounds with high herbicidal activity, a series of new pyrido[2,3-d] pyrimidine derivatives were designed and synthesized using 2-chloronicotinic acid as the starting material. Their structures were characterized with 1H NMR, 13C NMR and HRMS, and the herbicidal activities against dicotyledonous lettuce (Lactuca sativa), field mustard (Brassica campestris), monocotyledonous bentgrass (Agrostis stolonifera) and wheat (Triticum aestivum) were determined. The results indicated that most of the pyrido[2,3-d] pyrimidine derivatives had no marked inhibitory effect on lettuce at 1 mM. However, most of the pyrido[2,3-d] pyrimidine derivatives possessed good activity against bentgrass at 1 mM. Among them, the most active compound, 3-methyl-1-(2,3,4-trifluorophenyl)pyrido[2,3-d]pyrimidine-2,4(1H,3H)-dione (2o), was as active as the positive controls, the commercial herbicides clomazone and flumioxazin. Molecular simulation was performed with molecular docking and DFT calculations. The docking studies provided strong evidence that 2o acts as an herbicide by inhibition of protoporphyrinogen oxidase. However, the physiological results indicate that it does not act on this target in vivo, implying that it could be metabolically converted to a compound with a different molecular target.
Alizarin, an Agonist of AHR Receptor, Enhances CYP1A1 Enzyme Activity and Induces Transcriptional Changes in Hepatoma Cells
Authors: Liang Shengxian , Bo Haimei , Zhang Yue , Zhen Hongcheng , Zhong Li
Published: October 2023

The phytopigment alizarin was previously characterized as an anti-tumor drug owing to its antioxidant or antigenotoxic activities. However, the safety of alizarin is currently still under dispute. In this study, we explored the activity of alizarin in the AHR-CYP1A1 pathway and analyzed the transcriptional changes affected by alizarin using human hepatoma cell line HepG2-based assays. The results showed that alizarin decreased HepG2 cell viability in a dose-dependent manner, with IC50 values between 160.4 and 216.8 μM. Furthermore, alizarin significantly upregulated the expression of CYP1A1 and increased the ethoxyresorufin-O-deethylase activity. Alizarin also exhibited agonistic activity toward the AHR receptor in the XRE-mediated luciferase reporter gene assay, which was further confirmed via the molecular docking assay. In addition, the transcriptional analysis indicated that alizarin may act as a potential carcinogen through significantly enriching several items related to cancer in both DO and KEGG analysis. In brief, our findings indicated that alizarin shows agonistic activities to the AHR receptor through activating the AHR-CYP1A1 signaling pathway in HepG2 cells, which may lead to the risks for cancer developing.
Nanotribological Characteristics of the Al Content of AlxGa1−xN Epitaxial Films
Authors: Wen Hua-Chiang , Wu Ssu-Kuan , Liu Cheng-Wei , Dai Jin-Ji , Chou Wu-Ching
Published: October 2023

The nanotribological properties of aluminum gallium nitride (AlxGa1−xN) epitaxial films grown on low-temperature-grown GaN/AlN/Si substrates were investigated using a nanoscratch system. It was confirmed that the Al compositions played an important role, which was directly influencing the strength of the bonding forces and the shear resistance. It was verified that the measured friction coefficient (μ) values of the AlxGa1−xN films from the Al compositions (where x = 0.065, 0.085, and 0.137) were in the range of 0.8, 0.5, and 0.3, respectively, for Fn = 2000 μN and 0.12, 0.9, and 0.7, respectively, for Fn = 4000 μN. The values of μ were found to decrease with the increases in the Al compositions. We concluded that the Al composition played an important role in the reconstruction of the crystallites, which induced the transition phenomenon of brittleness to ductility in the AlxGa1−xN system.
Nanofibers and Nanotextured Materials: Design Insights, Bactericidal Mechanisms and Environmental Advances
Authors: Amna Touseef , Hassan M. Shamshi
Published: October 2023

Antibiotic resistance is rising and poses a serious threat to human health on a worldwide scale. It can make it more difficult to cure common infections, raise medical expenditures, and increase mortality. In order to combat the development of biofilms and treat fatal bacterial infections, multifunctional polymeric nanofibers or nanotextured materials with specific structural features and special physiochemical capabilities have become a crucial tool. Due to the increased antibiotic resistance of many diseases, nanofibers with antibacterial activity are essential. Electrospinning is a flexible process able to produce fine fibers with specified properties by modifying variables such as the concentration of the solution, the feed flow, and the electric voltage. Substantial advancements have been made regarding the formation of nanofibers or nanotextured materials for a variety of applications, along with the development of electrospinning techniques in recent years. Using well-defined antimicrobial nanoparticles, encapsulating traditional therapeutic agents, plant-based bioactive agents, and pure compounds in polymer nanofibers has resulted in outstanding antimicrobial activity and has aided in curing deadly microbial infections. A plethora of studies have revealed that electrospinning is an effective technique for the production of antimicrobial fibers for the environmental, biomedical, pharmaceutical, and food sectors. Nevertheless, numerous studies have also demonstrated that the surface characteristics of substrates, such as holes, fibers, and ridges at the nanoscale, have an impact on cell proliferation, adhesion, and orientation.
Ketogenic Diet Has Moderate Effects on the Fecal Microbiota of Wild-Type Mice
Authors: Rohwer Nadine , El Hage Racha , Smyl Christopher , Ocvirk Soeren , Goris Tobias , Grune Tilman , Swidsinski Alexander , Weylandt Karsten-H.
Published: October 2023

The ketogenic diet (KD) is a high-fat, low-carbohydrate diet that has been reported to have neuroprotective effects. The health effects of KD might be linked to an altered gut microbiome, which plays a major role in host health, leading to neuroprotective effects via the gut-brain axis. However, results from different studies, most often based on the 16S rRNA gene and metagenome sequencing, have been inconsistent. In this study, we assessed the effect of a 4-week KD compared to a western diet (WD) on the colonic microbiome of female C57Bl/6J mice by analyzing fecal samples using fluorescence in situ hybridization. Our results showed distinct changes in the total number of gut bacteria following the 4-week KD, in addition to changes in the composition of the microbiome. KD-fed mice showed higher absolute numbers of Actinobacteria (especially Bifidobacteria spp.) and lower absolute levels of Proteobacteria, often linked to gut inflammation, in comparison with WD-fed mice. Furthermore, an increased abundance of the typically rare genus Atopobium was observed. These changes may indicate the possible anti-inflammatory effects of the KD. However, since the overall changes in the microbiota seem low, the KD effects might be linked to the differential abundance of only a few key genera in mice.
Trend in Breakfast Consumption among Primary School Children in Italy
Authors: Ciardullo Silvia , Salvatore Michele Antonio , Mandolini Donatella , Spinelli Angela , Bucciarelli Mauro , Andreozzi Silvia , Buoncristiano Marta , Nardone Paola
Published: October 2023

Eating breakfast daily improves cognitive function, may contribute to learning and academic performance in children and can decrease the risk of childhood obesity. The aim of this study was to analyse how breakfast consumption changed in the period from 2008/9 to 2019 in Italy among children aged 8–9 years old participating in the OKkio alla SALUTE surveys and to explore the associations with some socio-demographic and lifestyle factors. Information about children’s daily breakfast consumption (adequate, inadequate, and no breakfast) and the socio-demographic characteristics of the children and their mothers was collected through four questionnaires addressed to parents, children, teachers and head teachers. Data were analysed for the 272,781 children from 21 Italian regions from 2008/9 to 2019. The prevalence of adequate breakfast decreased from 60.7% in 2008/9 to 55.7% in 2019 and no breakfast from 10.9 to 8.7%; conversely, inadequate breakfast increased from 28.4 to 35.6%. Logistic regression models showed that the occurrence of inadequate or no breakfast consumption was significantly higher among girls, children living in the southern regions and children with less educated mothers. These findings highlight the need for effective interventions to increase daily breakfast consumption and its adequacy among children.
Geriatric Nutritional Risk Index as a Prognostic Factor for Renal Progression in Patients with Type 2 Diabetes Mellitus
Authors: Kim Eun Jung , Cho Ajin , Kim Do Hyoung , Park Hayne Cho , Yoon Joo Yeon , Shon Kyungjun , Kim Eunji , Koo Ja-Ryong , Lee Young-Ki
Published: October 2023

The aim of this study was to evaluate whether the geriatric nutritional risk index (GNRI) is associated with chronic kidney disease (CKD) progression in patients with type 2 diabetes mellitus (DM). In total, 1100 patients with type 2 DM with a follow-up duration > 1 year were included in this longitudinal study. The risk of CKD progression was assessed according to GNRI quartiles. Patients in the lowest GNRI quartile exhibited a significantly lower estimated glomerular filtration rate (eGFR), compared with those in quartile four. Moreover, these patients had poorer glycemic control and lower hemoglobin levels, body mass index, and albumin levels. Additionally, they exhibited a greater annual decline in eGFR. Multivariate logistic regression analysis showed that old age (>60 years), baseline eGFR, the presence of proteinuria, the use of angiotensin-converting enzyme inhibitors or angiotensin receptor blockers, and low GNRI were significantly associated with CKD progression. GNRI may serve as a valuable predictive tool for identifying the risk of adverse renal outcomes in patients with type 2 DM. It may potentially serve as a more feasible measure for assessing the nutritional status of these patients, as well as for predicting their clinical outcomes.
A Multi-Objective Local Optimization Method for Imaging Optical Systems
Authors: Zhao Shangnan , Wu Hongbo , Ye Haokun , Hu Jingaowa , Hu Mingyu , Zhang Xin
Published: October 2023

Addressing the inherent limitations of conventional local optimization methodologies such as damping least squares (DLS) and adaptation algorithms, this study proposes a novel approach to multi-objective optimization for imaging optical systems. The proposed method entails the formulation of a multi-objective optimization mathematical framework, where the objectives are established upon lateral aberration and wave aberration criteria. Subsequently, enhancements are made to the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) by implementing a directional initial population strategy and parallel optimization with multiple-trajectory planning. The genesis of the initial population is rooted in the gradient direction information extracted from the starting positions. This strategic foundation precludes potential efficiency limitations in subsequent optimization stages arising from undesirable initial population quality. By employing mechanisms such as differentiation and mutation to sustain population diversity, the trajectory of evolution is guided by the first- and second-order derivatives of the optimal individual, thereby elevating the quality of the evolutionary offspring population. The fusion of the parent and offspring populations yields a composite population, which undergoes rapid and non-dominated sorting, crowding calculation, and elite strategies. Empirical results illustrate the validation of the proposed methodology. The proof-of-concept paradigm demonstrates high efficiency in multi-objective local optimization for imaging optical systems.
An Integrated Photoelasticity-Based Approach for the Reconstruction of Stress Profiles and Optical Anisotropy of GRIN Lenses
Authors: Lipovskii Andrey A. , Dolzhenko Dmitry I. , Kapralova Viktoria M. , Karov Dmitry D. , Korotkov Alexander S. , Loboda Vera V. , Nikitina Elizaveta A. , Sudar Nicolay T. , Zhurikhina Valentina V.
Published: October 2023

The paper shows that it is possible to obtain reliable information on the dependence of the radial distribution of longitudinal birefringence in glass cylindrical elements with a radial distribution of refractive index (GRIN lenses) on the basis of transverse polarization tomography data on residual stresses. This does not require complicated procedures of sample preparation, as is necessary in the case of longitudinal translucency measurements. The approach developed was verified in the experiments with a set of different GRIN lenses formed with the ion exchange technique, and the closeness of the data obtained from transversal and conventional longitudinal transmission measurements was demonstrated.
Impact of the Configurational Microstructure of Carboxylate-Rich Chitosan Beads on Its Adsorptive Removal of Diclofenac Potassium from Contaminated Water
Authors: Elsayed Rasha E. , Hassanein Dina , El-Sayed Mayyada M. H. , Madkour Tarek M.
Published: October 2023

A novel adsorbent–contaminant system was investigated for its ability to remove a contaminant of emerging concern, diclofenac potassium, from contaminated water. Bio-based crosslinked chitosan beads functionalized with poly(itaconic acid) side chains were examined for their potential to remove the emerging contaminant. To evaluate the impact of the polymeric microstructure on its adsorptive capacity, several adsorbent samples were prepared using different combinations of initiator and monomeric concentrations. Fourier Transform Infrared (FTIR) analysis confirmed the crosslinking of the chitosan chains and the incorporation of the carboxylic groups on the surface of the final chitosan beads. After the grafting copolymerization process, an additional peak at 1726 cm−1 corresponding to the carboxylic C=O groups of the grafted chains appeared, indicating the successful preparation of poly(IA)-g-chitosan. Thermal stability studies showed that the grafting copolymerization improved the thermal stability of the beads. X-ray and Scanning Electron Microscopy confirmed the successful grafting of the itaconic acid on the surface of the beads. The study revealed that the higher the initiator concentration, the greater the number of side chains, whereas the higher the monomeric concentration, the longer the length of these side chains. The adsorption mechanism involved hydrogen bonding to the carboxylic groups of the grafted chains along with n-π* stacking interaction between the amino group of the chitosan and the aromatic rings of diclofenac potassium. The adsorption efficiencies of diclofenac potassium onto the grafted beads were significantly improved compared to the unfunctionalized chitosan beads, reaching values above 90%. The removal efficiency of grafted chitosan increased with an increase in the concentration in the range of 10–30 ppm and then flattened out in the range of 30–50 ppm. The removal efficiencies of 1–50 ppm of DCF ranged between about 75% and 92% for the grafted chitosan and 30–45% for the crosslinked chitosan. Rapid adsorption occurred within 20 min for all grafted sample combinations, and the adsorption kinetics followed a pseudo-second-order model with qe values ranging from 28 to 44.25 g/mg and R2 values greater than 0.9915. The results highlight the potential of grafted chitosan beads in removing emerging contaminants from contaminated water without harming the environment.
The Role of Religion in the Family Life of People with Disabilities: A Legal and Social Study
Authors: Mikołajczuk Krzysztof , Zielińska-Król Katarzyna
Published: October 2023

The family holds a special place in human life. Given the importance of marriage and family for the welfare of people, the Catholic Church strives to protect these values. The Church’s stance towards people with disabilities is unequivocally protective and inclusive, but it also recognises that the right to marriage and family life is not absolute. Not all people with disabilities are able to start a family or fulfil the obligations of marriage and family life. In canon law, the Church sets forth certain conditions for contracting a valid marriage, taking into account the human resources that make a person capable of such a commitment. This article examines the narratives of people with disabilities who participated in a study on religiosity, faith, and prayer, and how these can provide meaning to disability in the context of marital and family life. The research findings confirm our hypothesis that faith and religious practices provide people with disabilities with a sense of meaning in life and help them stabilise difficult moments and experiences; prayer is a source of peace, patience, and gentleness, and it improves the quality of life of both people with disabilities and their families; faith and religious practices help people with disabilities make sense of everyday difficulties, gain perspective, and overcome their weaknesses or egocentrism; religiousness is a source of meaning in life. Faith and religion play an important role in participants’ efforts to accept their lives, provide care, and show love. Moreover, they have a positive impact on the rehabilitation process.
Taiyi: The Axis of Philosophy of the Laozi
Authors: Huang Yongfeng , Li Zhikun
Published: October 2023

Taiyi 太一, the void and dark central region of the celestial sphere, carries symbolic implications that resonate with the essence of ultimate reality in the philosophical framework of the Laozi 老子. It assumes a metaphorical representation of the ultimate reality and its movement pattern, serving as the axis from which the fundamental concepts and principal branches of this philosophy unfurl. The concept of Taiyi exerts a profound and far-reaching impact on the philosophical discourse of the Laozi. It assumes the mantle of a signifier for the ultimate reality within the philosophical framework of the Laozi, while its dynamic motion patterns imbue the cosmological principles of this philosophy. On a pragmatic level, Taiyi unveils profound and nuanced insights into human nature and the epistemology expounded by the Laozi.
Solar Potential Analysis of Bus Shelters in Urban Environments: A Study Case in Ávila (Spain)
Authors: Sánchez-Aparicio María , González-González Enrique , Martín-Jiménez Jose Antonio , Lagüela Susana
Published: October 2023

The presence of shadows is one of the main disadvantages of photovoltaic solar panel installations in urban environments. This article analyses their effect on solar installations performed on urban elements where the use of solar energy can be considered novel: bus shelters. For this purpose, the PVGIS tool is used in combination with a new methodology for the extraction of the shadow horizon profile from LiDAR point clouds. The results show a 29.90% and 37% reduction of calculated solar radiation using horizon profiles derived from LiDAR point clouds of 0.5 pts/m2 and 1 pt/m2, respectively, versus no horizon profile. By taking shading into account, thanks to this study it is possible to make a more realistic prediction of the use of the electrical energy generated by the sun to cover urban energy consumption in bus shelters. Results show that the energy surplus produced overall allows these elements to be converted into charging points for light electric vehicles, allowing up to 35 units per day/bus shelter to be charged. The use of bus shelters as a place to generate clean energy through solar energy and charge light vehicles makes it possible to move towards sustainable and environmentally friendly cities.
Evaluation of Multi-Spectral Band Efficacy for Mapping Wildland Fire Burn Severity from PlanetScope Imagery
Authors: Hamilton Dale , Gibson William , Harris Daniel , McGath Camden
Published: October 2023

Increased spatial resolution has been shown to be an important factor in enabling machine learning to map burn extent and severity with extremely high accuracy. Unfortunately, the acquisition of drone imagery is a labor-intensive endeavor, making the capture of drone imagery impractical for large catastrophic fires, which account for the majority of the area burned each year in the western US. To overcome this difficulty, satellites, such as PlanetScope, are now available which can produce imagery with remarkably high spatial resolution (approximately three meters). In addition to having higher spatial resolution, PlanetScope imagery contains up to eight bands in the visible and near-infrared spectra. This study examines the efficacy of each of the eight bands observed in PlanetScope imagery using a variety of feature selection methods, then uses these bands to map the burn extent and biomass consumption of three wildland fires. Several classifications are produced and compared based on the available bands, resulting in highly accurate maps with slight improvements as additional bands are utilized. The near-infrared band proved contribute most to increased mapping accuracy, while the green 1 and yellow bands contributed the least.
Analysis of Volatile Components and Antibacterial Activity of Silver Wormwood Essential Oils from Different Habitats by E-Nose Combined with GC-MS
Authors: Yang Yiqin , Guo Dongyun , Yang Shujie , Hu Huiquan , Luo Xiaorong , Wan Na
Published: October 2023

Electronic nose (E-nose) combined with gas chromatography–mass spectrometry (GC-MS) was used to analyze the volatile components of silver wormwood from different habitats, and the antibacterial activity of essential oils was also studied, to provide a scientific basis for quality control of silver wormwood and rational utilization of their essential oils. In this study, the total content of essential oils in silver wormwood was determined by steam distillation; the volatile components were conducted in an overall analysis by E-nose combined with chemometrics; the volatile components were analyzed and identified by GC-MS; and two G-negative bacteria and one Gram-positive bacteria were used as test bacteria to determine the antibacterial activity of the essential oils from silver wormwood. The results showed that principal component analysis (PCA) and linear discriminant analysis (LDA) of E-nose could distinguish the essential oils of silver wormwood from different habitats, and the odor difference of essential oils was obvious. A total of 87 volatile components were identified by GC-MS, and there were significant differences in components and contents in silver wormwood from different habitats; PCA and hierarchical cluster analysis (HCA) could effectively distinguish silver wormwood from different habitats. The essential oils from silver wormwood from different habitats all had a certain inhibitory effect on Bacillus subtilis, Staphylococcus aureus, and Escherichia coli. Therefore, the combination of E-nose and GC-MS could quickly distinguish silver wormwood from different habitats and provide a reference for quality control, drug selection, and comprehensive utilization of silver wormwood.
A Rule-Based Automated Chemical Recognition Algorithm for a Multi-Cell Multi-Detector Micro Gas Chromatograph
Authors: Xu Qu , Qin Yutao , Gianchandani Yogesh B.
Published: October 2023

A chemical recognition algorithm is an integral part of any autonomous microscale gas chromatography (µGC) system for automated chemical analysis. For a multi-detector µGC system, the chemical analysis must account for the retention time of each chemical analyte as well as the relative response of each detector to each analyte, i.e., the detector response pattern (DRP). In contrast to the common approaches of heuristically using principal component analysis and machine learning, this paper reports a rule-based automated chemical recognition algorithm for a multi-cell, multi-detector µGC system, in which the DRP is related to theoretical principles; consequently, this algorithm only requires a small amount of calibration data but not extensive training data. For processing both the retention time and the raw DRP, the algorithm applies rules based on expert knowledge to compare the detected peaks; these rules are located in a customized software library. Additionally, the algorithm provides special handling for chromatogram peaks with a small signal-to-noise ratio. It also provides separate special handling for asymmetrical peaks that may result from surface adsorptive analytes. This work also describes an experimental evaluation in which the algorithm used the relative response of two complementary types of capacitive detectors as well as a photoionization detector that were incorporated into the µGC system of interest. In these tests, which were performed on chromatograms with 21–31 peaks for each detector, the true positive rate was 96.3%, the true negative rate was 94.1%, the false positive rate was 5.9%, and the false negative rate was 3.7%. The results demonstrated that the algorithm can support µGC systems for automated chemical screening and early warning applications.
Assessing the Venturing of Rural and Peri-Urban Youth into Micro- and Small-Sized Agricultural Enterprises in the Eastern Cape Province, South Africa
Authors: Thibane Zimi , Mdoda Lelethu , Gidi Lungile , Mayekiso Anele
Published: October 2023

This study aimed to empirically assess the venturing by rural and peri-urban youth into micro- and small-sized agricultural enterprises in the Eastern Cape Province, South Africa. The aim of the study was achieved by focusing on the following specific objectives: analyzing youth involvement in agricultural enterprises; estimating the factors that influence youth participation in micro- and small-sized agricultural enterprises; and identifying constraints and opportunities for youth involvement in micro- and small-sized agricultural enterprises in the Eastern Cape Province. The study used multi-stage and snowballing sampling to select the respondents, and cross-sectional primary data were collected from 120 youths who ventured into micro- and small-sized agricultural enterprises. Only 70 youths from the sample participated in agricultural enterprises. The study was geared toward proposing a funding framework aligned with the characteristics of small- and micro-sized enterprises (SMEs) which can be used by both development finance institutions (DFIs) and commercial banks to assess applications for funding SMEs.
Modeling Impact of Transportation Infrastructure-Based Accessibility on the Development of Mixed Land Use Using Deep Neural Networks: Evidence from Jiang’an District, City of Wuhan, China
Authors: Almansoub Yunes , Zhong Ming , Safdar Muhammad , Raza Asif , Dahou Abdelghani , Al-qaness Mohammed A. A.
Published: October 2023

Mixed land use (MLU) plays a crucial role in fostering a sustainable urban development, vibrant communities, and efficient land utilization, providing a viable solution for smart growth, inclusive public transit, and urban sustainability. This study employs deep neural network (DNN) models: multilayer perceptron (MLP), and long short-term memory (LSTM), to analyze the effect of the transportation infrastructure-based accessibility on the prevalence of MLU patterns, based on the following data: infrastructure-based accessibility measures represented by the logsum (or transport supply), MLU patterns at the parcel level, and floor space prices by space type, for the years 2012 and 2015. Furthermore, the proposed methods are applied to the Jiang’an District of the city of Wuhan, China, at the parcel level as the case study. The study results reveal that MLU is predominantly accessible in areas close to the city center, characterized by a high density, and is relatively scarce on the city outskirts. Notably, parcels exhibiting mixed residential–commercial and residential land-use patterns underwent significant changes between 2012 and 2015, particularly in regions with robust accessibility via non-motorized modes and public transit, specifically in the central and southern parts of Jiang’an District. This transition is evident under scenario 3 (walk, bike, bus, subway) and scenario 6 (walk, bus, car) considered in this study. Furthermore, the study observed a substantial expansion in mixed commercial–residential and commercial districts, significantly near the high-transit accessibility area of subway line 1, as demonstrated in scenario 7 (bike, subway, taxi). The results from the MLP models show a mean relative error (MRE) of 4.7–14.08% for the MLU, and the LSTM models show an MRE of 3.74–10.38% for the MLU. More importantly, both the training and forecasting errors of the above models are lower, in most cases, than those reported in the literature. Moreover, these results indicate that the transportation supply or the infrastructure-based accessibility (represented by logsum) significantly influences MLU patterns.
Study of Ecosystem Degradation Dynamics in the Peruvian Highlands: Landsat Time-Series Trend Analysis (1985–2022) with ARVI for Different Vegetation Cover Types
Authors: Cano Deyvis , Pizarro Samuel , Cacciuttolo Carlos , Peñaloza Richard , Yaranga Raúl , Gandini Marcelo Luciano
Published: October 2023

The high-Andean vegetation ecosystems of the Bombón Plateau in Peru face increasing degradation due to aggressive anthropogenic land use and the climate change scenario. The lack of historical degradation evolution information makes implementing adaptive monitoring plans in these vulnerable ecosystems difficult. Remote sensor technology emerges as a fundamental resource to fill this gap. The objective of this article was to analyze the degradation of vegetation in the Bombón Plateau over almost four decades (1985–2022), using high spatiotemporal resolution data from the Landsat 5, 7, and 8 sensors. The methodology considers: (i) the use of the atmosphere resistant vegetation index (ARVI), (ii) the implementation of non-parametric Mann–Kendall trend analysis per pixel, and (iii) the affected vegetation covers were determined by supervised classification. This article’s results show that approximately 13.4% of the total vegetation cover was degraded. According to vegetation cover types, bulrush was degraded by 21%, tall grass by 18%, cattails by 16%, wetlands by 14%, and puna grass by 13%. The Spearman correlation (p < 0.01) determined that degraded covers are replaced by puna grass and change factors linked with human activities. Finally, this article concludes that part of the vegetation degradation is related to anthropogenic activities such as agriculture, overgrazing, urbanization, and mining. However, the possibility that environmental factors have influenced these events is recognized.
Comparative Studies of Thermal Conductivity Determination in Synthetic Wood with Recyclable Waste Content Using an Experimental Design Approach
Authors: Judele Loredana , Proaspăt Eduard , Teodorescu Razvan Ionut , Lepadatu Daniel , Bucur Daniel
Published: October 2023

Waste has become an everyday subject, especially its efficient recycling due to the increasing decline in the planet’s primary resources. Therefore, their recovery is intended to be total and with minimal energy consumption. Biomass waste is fully recoverable in raw or processed states and in combination with other compatible waste types (including wastewater from construction, polymers, and sunflower seeds). It represents the basic elements for obtaining synthetic wood to replace natural wood, which is very expensive and difficult to obtain (lasts for several years). This paper proposes three methods to determine the thermal conductivity of these new materials (synthetic wood) to guarantee and optimise their thermal characteristics. The determination of thermal characteristics in insulating materials is usually performed experimentally in a double climate chamber or more simply using a special instrument of the ISOMET type, but under these conditions, the sample must meet certain conditions imposed by the manufacturer to be tested. Thus, two experimental investigation methods are used to which a numerical method is added, which consists of modelling by the finite element method with an adequate programme of heat transfer through these materials. Four samples with variable content of recyclable waste obtained through combinations resulting from six different experimental design plans with two controlled factors were analysed to optimise synthetic wood recipes for the efficiency of their hygro-thermal characteristics. The content of the tested samples varied relative to the quantity and number of recyclable wastes included in the final recipe. Thus, the thermal conductivity obtained was different for each sample but close to that of similar synthetic wood-type materials and natural wood.
Life Cycle Assessment and Building Information Modeling Integrated Approach: Carbon Footprint of Masonry and Timber-Frame Constructions in Single-Family Houses
Authors: Mazur Łukasz , Olenchuk Anatolii
Published: October 2023

The analysis of the carbon footprint of buildings is a key tool for assessing the impact of different buildings on climate change. Several frameworks and methodologies are available to calculate the footprint of buildings, including standards and norms, Life Cycle Assessment (LCA), and dedicated software tools. The use of Building Information Modeling (BIM) programme for these calculations is both scientifically justified and very practical. This scientific publication focuses on the application of a BIM-based research methodology to analyse the carbon footprint of a single-family house. The research process included the following steps: (i) the design of a single-family house with masonry construction using Archicad 26, BIM programme, (ii) simulation of the building energy performance using the EcoDesigner Star plug-in, (iii) LCA using the plug-in for Archicad, (iv) preparation of a second model with timber-frame construction for comparison, and (v) comparative analysis of the single-family house models with masonry construction (building A) and timber-frame (building B). Analysis of the results highlights significant differences in CO2e emissions between buildings and the varying impact of individual elements on the total CO2e emissions of the buildings studied. Building A had significantly higher net emissions, amounting to 43,226.94 kg CO2e, in stark contrast to Building B’s significantly lower 13,522.13 kg CO2e. This discrepancy was also mirrored in the emission intensity, with Building A emitting at a rate of 281.06 kg CO2e/m2 compared to Building B’s 96.72 kg CO2e/m2. These findings are relevant for future work on sustainable building design and construction aiming to minimise negative environmental impacts. The goal of minimising the cumulative carbon footprint of buildings is critical to achieve the Sustainable Development Goals and combating climate change.
Designing the Location–Routing Problem for a Cold Supply Chain Considering the COVID-19 Disaster
Authors: Abbasi Sina , Moosivand Maryam , Vlachos Ilias , Talooni Mohammad
Published: October 2023

In this study, a location routing problem (LRP) model was considered for the distribution network of multiple perishable food items in a cold supply chain (CSC) where vehicles can refuel at gas stations during light of the COVID-19 disaster. Fuel consumption is assumed to vary depending on the cargo transported between nodes when using a non-standard fuel fleet. The problem was formulated as a mixed-integer linear programming (MILP) model to reduce the production of carbon dioxide (CO2). The model was validated using several numerical examples which were solved using the software, LINGO 17.0. The results show that fuel consumption could be reduced in this case. Due to the complexity of the problem, genetically simulated annealing algorithms were developed to solve the actual size problems, and their performance was also evaluated.
Exploring the Applicability of Regression Models and Artificial Neural Networks for Calculating Reference Evapotranspiration in Arid Regions
Authors: Abdel-Fattah Mohamed K. , Kotb Abd-Elmabod Sameh , Zhang Zhenhua , Merwad Abdel-Rhman M. A.
Published: October 2023

Reference evapotranspiration (ET0) is critical in agriculture and irrigation water management, particularly in arid and semi-arid regions. Our study aimed to develop an accurate and efficient model for estimating ET0 using various climatic variables as predictors. This research evaluated two model techniques, i.e., stepwise regression and artificial neural networks (ANNs), to identify the most effective model for calculating ET0. The two models were developed and tested based on climate data obtained from the whole climatic station of Egypt. The CLIMWAT 2.0 program was used to acquire the climate data for Egypt from a total of 32 stations. This software is a dedicated meteorological database created specifically to work with the CROPWAT computer program. The models were developed using average climate data spanning 29 years, from 1991 to 2020. The obtained data were utilized to compute reference evapotranspiration using CROPWAT 8, based on the Penman–Monteith equation. The results showed that the ANN model demonstrated superior performance in ET0 calculations compared to other methods, achieving a coefficient of determination (R2) of 0.99 and a mean absolute percentage error (MAPE) of 2.7%. In contrast, the stepwise model regression yielded an R2 of 0.95 and an MAPE of 8.06. On the other hand, the most influential climatic variables were maximum temperature, humidity, solar radiation, and wind speed. The findings of this study could be applied in various fields, such as agriculture, irrigation, and crop water requirements, to optimize crop growth under limited water resources and global environmental changes. Furthermore, our study identifies the limitations and challenges of applying these models in arid regions, such as data availability constraints and model complexity. We discuss the need for more extensive and reliable datasets and suggest future research directions, including ensemble modeling, remote sensing data integration, and evaluating climate change’s impact on ET0 estimation. Overall, this study contributes to the understanding of ET0 estimation in arid regions and provides valuable insights into the applicability of regression models and ANNs. The superior performance of ANNs offers potential advancements in water resource management and agricultural planning, enabling more accurate and informed decision-making processes.
How Does Urbanization Affect Carbon Emission Performance? Evidence from 282 Cities in China
Authors: Zhao Zhibo , Ren Jiamin , Liu Zheng
Published: October 2023

Improving carbon emission performance (CEP) is the key to realizing the goal of “carbon peaking and carbon neutrality” for China. Using a panel dataset of 282 cities at prefecture level and above in China from 2003 to 2017, this study employs the Global Malmquist–Luenberger (GML) index to measure CEP. Moreover, this study investigates the effect and transmission mechanisms of urbanization on CEP based on the extended STIRPAT model. The results show a significant positive “U-shaped” relationship between urbanization and CEP. When urbanization exceeds the inflection point, urbanization is conducive to improve CEP in Chinese cities. The mechanism analysis illustrates that human capital has a positive impact on CEP, while technological innovation inhibits it. The findings of this study can provide a scientific basis for local governments to formulate different strategies to improve China’s high-quality development through human capital accumulation and low cost and scale of low-carbon technologies.
Learning-Based Approaches for Voltage Regulation and Control in DC Microgrids with CPL
Authors: Güngör Mustafa , Asker Mehmet Emin
Published: October 2023

This article introduces a novel approach to voltage regulation in a DC/DC boost converter. The approach leverages two advanced control techniques, including learning-based nonlinear control. By combining the backstepping (BSC) algorithm with artificial neural network (ANN)-based control techniques, the proposed approach aims to achieve accurate voltage tracking. This is accomplished by employing the nonlinear distortion observer (NDO) technique, which enables a fast dynamic response through load power estimation. The process involves training a neural network using data from the BSC controller. The trained network is subsequently utilized in the voltage regulation controller. Extensive simulations are conducted to evaluate the performance of the proposed control strategy, and the results are compared to those obtained using conventional BSC and model predictive control (MPC) controllers. The simulation results clearly demonstrate the effectiveness and superiority of the suggested control strategy over BSC and MPC.
Optimizing Freight Vehicle Routing in Dynamic Time-Varying Networks with Carbon Dioxide Emission Trajectory Analysis
Authors: Song Rui , Qin Wanen , Shi Wen , Xue Xingjian
Published: October 2023

In this study, we formulate a freight vehicle path-planning model in the context of dynamic time-varying networks that aims to capture the spatial and temporal distribution characteristics inherent in the carbon dioxide emission trajectories of freight vehicles. Central to this model is the minimization of total carbon dioxide emissions from vehicle distribution, based on the comprehensive modal emission model (CMEM). Our model also employs the freight vehicle travel time discretization technique and the dynamic time-varying multi-path selection strategy. We then design an improved genetic algorithm to solve this complicated problem. Empirical results vividly illustrate the superior performance of our model over alternative objective function models. In addition, our observations highlight the central role of accurate period partitioning in time segmentation considerations. Finally, the experimental results underline that our multi-path model is able to detect the imprint of holiday-related effects on the spatial and temporal distribution of carbon dioxide emission trajectories, especially when compared to traditional single-path models.