bluuebunny/crossref_metadata_2025 huggingface dataset:
Baseline Calibration of L-Band Spaceborne Bistatic SAR TwinSAR-L for DEM Generation
Authors: Mou Jingwen , Wang Yu , Hong Jun , Wang Yachao , Wang Aichun
Published: June 2023

The Terrain Wide-swath Interferometric L-band Synthetic Aperture Radar (TwinSAR-L) mission is a spaceborne bistatic synthetic aperture radar (SAR) mission to derive a high-quality global digital elevation model (DEM). The prerequisite of the high-accuracy DEM is knowing the interferometric baseline with high precision. The challenging problem is that the baseline of the bistatic system is highly dynamic due to the fast relative motion between the two satellites. In this paper, a pixel-related baseline model based on the geometrical shift is proposed to accurately reflect the position change of satellites. The baseline error is then calibrated using height gradient information and a small number of point targets with a slight incidence angle difference, eliminating the need for low-frequency corner reflectors and avoiding the difficulty of selecting a calibration site. The proposed method has been successfully exploited during the initial Commissioning Phase of TwinSAR-L, demonstrating its effectiveness in evaluating the precise baseline and supporting the generation of high-precision DEM.
A Machine Learning Model Ensemble for Mixed Power Load Forecasting across Multiple Time Horizons
Authors: Giamarelos Nikolaos , Papadimitrakis Myron , Stogiannos Marios , Zois Elias N. , Livanos Nikolaos-Antonios I. , Alexandridis Alex
Published: June 2023

The increasing penetration of renewable energy sources tends to redirect the power systems community’s interest from the traditional power grid model towards the smart grid framework. During this transition, load forecasting for various time horizons constitutes an essential electric utility task in network planning, operation, and management. This paper presents a novel mixed power-load forecasting scheme for multiple prediction horizons ranging from 15 min to 24 h ahead. The proposed approach makes use of a pool of models trained by several machine-learning methods with different characteristics, namely neural networks, linear regression, support vector regression, random forests, and sparse regression. The final prediction values are calculated using an online decision mechanism based on weighting the individual models according to their past performance. The proposed scheme is evaluated on real electrical load data sensed from a high voltage/medium voltage substation and is shown to be highly effective, as it results in R2 coefficient values ranging from 0.99 to 0.79 for prediction horizons ranging from 15 min to 24 h ahead, respectively. The method is compared to several state-of-the-art machine-learning approaches, as well as a different ensemble method, producing highly competitive results in terms of prediction accuracy.
Testing the Effect of Bathymetric Data Reduction on the Shape of the Digital Bottom Model
Authors: Mujta Wiktor , Wlodarczyk-Sielicka Marta , Stateczny Andrzej
Published: June 2023

Depth data and the digital bottom model created from it are very important in the inland and coastal water zones studies and research. The paper undertakes the subject of bathymetric data processing using reduction methods and examines the impact of data reduction according to the resulting representations of the bottom surface in the form of numerical bottom models. Data reduction is an approach that is meant to reduce the size of the input dataset to make it easier and more efficient for analysis, transmission, storage and similar. For the purposes of this article, test datasets were created by discretizing a selected polynomial function. The real dataset, which was used to verify the analyzes, was acquired using an interferometric echosounder mounted on a HydroDron-1 autonomous survey vessel. The data were collected in the ribbon of Lake Klodno, Zawory. Data reduction was conducted in two commercial programs. Three equal reduction parameters were adopted for each algorithm. The research part of the paper presents the results of the conducted analyzes of the reduced bathymetric datasets based on the visual comparison of numerical bottom models, isobaths, and statistical parameters. The article contains tabular results with statistics, as well as the spatial visualization of the studied fragments of numerical bottom models and isobaths. This research is being used in the course of work on an innovative project that aims to develop a prototype of a multi-dimensional and multi-temporal coastal zone monitoring system using autonomous, unmanned floating platforms at a single survey pass.
Healthcare Application of In-Shoe Motion Sensor for Older Adults: Frailty Assessment Using Foot Motion during Gait
Authors: Huang Chenhui , Nihey Fumiyuki , Ihara Kazuki , Fukushi Kenichiro , Kajitani Hiroshi , Nozaki Yoshitaka , Nakahara Kentaro
Published: June 2023

Frailty poses a threat to the daily lives of healthy older adults, highlighting the urgent need for technologies that can monitor and prevent its progression. Our objective is to demonstrate a method for providing long-term daily frailty monitoring using an in-shoe motion sensor (IMS). We undertook two steps to achieve this goal. Firstly, we used our previously established SPM-LOSO-LASSO (SPM: statistical parametric mapping; LOSO: leave-one-subject-out; LASSO: least absolute shrinkage and selection operator) algorithm to construct a lightweight and interpretable hand grip strength (HGS) estimation model for an IMS. This algorithm automatically identified novel and significant gait predictors from foot motion data and selected optimal features to construct the model. We also tested the robustness and effectiveness of the model by recruiting other groups of subjects. Secondly, we designed an analog frailty risk score that combined the performance of the HGS and gait speed with the aid of the distribution of HGS and gait speed of the older Asian population. We then compared the effectiveness of our designed score with the clinical expert-rated score. We discovered new gait predictors for HGS estimation via IMSs and successfully constructed a model with an “excellent” intraclass correlation coefficient and high precision. Moreover, we tested the model on separately recruited subjects, which confirmed the robustness of our model for other older individuals. The designed frailty risk score also had a large effect size correlation with clinical expert-rated scores. In conclusion, IMS technology shows promise for long-term daily frailty monitoring, which can help prevent or manage frailty for older adults.
Split-Belt Treadmill Adaptation Improves Spatial and Temporal Gait Symmetry in People with Multiple Sclerosis
Authors: Hagen Andrew C. , Acosta Jordan S. , Geltser Chaia S. , Fling Brett W.
Published: June 2023

Multiple sclerosis (MS) is a neurodegenerative disease characterized by degradation of the myelin sheath resulting in impaired neural communication throughout the body. As a result, most people with MS (PwMS) experience gait asymmetries between their legs leading to an increased risk of falls. Recent work indicates that split-belt treadmill adaptation, where the speed of each leg is controlled independently, can decrease gait asymmetries for other neurodegenerative impairments. The purpose of this study was to test the efficacy of split-belt treadmill training to improve gait symmetry in PwMS. In this study, 35 PwMS underwent a 10 min split-belt treadmill adaptation paradigm, with the faster paced belt moving under the more affected limb. Step length asymmetry (SLA) and phase coordination index (PCI) were the primary outcome measures used to assess spatial and temporal gait symmetries, respectively. It was predicted that participants with a worse baseline symmetry would have a greater response to split-belt treadmill adaptation. Following this adaptation paradigm, PwMS experienced aftereffects that improved gait symmetry, with a significant difference between predicted responders and nonresponders in both SLA and PCI change (p < 0.001). Additionally, there was no correlation between SLA and PCI change. These findings suggest that PwMS retain the ability for gait adaptation, with those most asymmetrical at baseline demonstrating the greatest improvement, and that there may be separate neural mechanisms for spatial and temporal locomotor adjustments.
Design and Evaluation of an Alternative Control for a Quad-Rotor Drone Using Hand-Gesture Recognition
Authors: Khaksar Siavash , Checker Luke , Borazjan Bita , Murray Iain
Published: June 2023

Gesture recognition is a mechanism by which a system recognizes an expressive and purposeful action made by a user’s body. Hand-gesture recognition (HGR) is a staple piece of gesture-recognition literature and has been keenly researched over the past 40 years. Over this time, HGR solutions have varied in medium, method, and application. Modern developments in the areas of machine perception have seen the rise of single-camera, skeletal model, hand-gesture identification algorithms, such as media pipe hands (MPH). This paper evaluates the applicability of these modern HGR algorithms within the context of alternative control. Specifically, this is achieved through the development of an HGR-based alternative-control system capable of controlling of a quad-rotor drone. The technical importance of this paper stems from the results produced during the novel and clinically sound evaluation of MPH, alongside the investigatory framework used to develop the final HGR algorithm. The evaluation of MPH highlighted the Z-axis instability of its modelling system which reduced the landmark accuracy of its output from 86.7% to 41.5%. The selection of an appropriate classifier complimented the computationally lightweight nature of MPH whilst compensating for its instability, achieving a classification accuracy of 96.25% for eight single-hand static gestures. The success of the developed HGR algorithm ensured that the proposed alternative-control system could facilitate intuitive, computationally inexpensive, and repeatable drone control without requiring specialised equipment.
The Smart Drifter Cluster: Monitoring Sea Currents and Marine Litter Transport Using Consumer IoT Technologies
Authors: Merlino Silvia , Calabrò Vincenzo , Giannelli Carlotta , Marini Lorenzo , Pagliai Marco , Sacco Lorenzo , Bianucci Marco
Published: June 2023

The study of marine Lagrangian transport holds significant importance from a scientific perspective as well as for practical applications such as environmental-pollution responses and prevention (e.g., oil spills, dispersion/accumulation of plastic debris, etc.). In this regard, this concept paper introduces the Smart Drifter Cluster: an innovative approach that leverages modern “consumer” IoT technologies and notions. This approach enables the remote acquisition of information on Lagrangian transport and important ocean variables, similar to standard drifters. However, it offers potential benefits such as reduced hardware costs, minimal maintenance expenses, and significantly lower power consumption compared to systems relying on independent drifters with satellite communication. By combining low power consumption with an optimized, compact integrated marine photovoltaic system, the drifters achieve unlimited operational autonomy. With the introduction of these new characteristics, the Smart Drifter Cluster goes beyond its primary function of mesoscale monitoring of marine currents. It becomes readily applicable to numerous civil applications, including recovering individuals and materials at sea, addressing pollutant spills, and tracking the dispersion of marine litter. An additional advantage of this remote monitoring and sensing system is its open-source hardware and software architecture. This fosters a citizen-science approach, enabling citizens to replicate, utilize, and contribute to the improvement of the system. Thus, within certain constraints of procedures and protocols, citizens can actively contribute to the generation of valuable data in this critical field.
Fall Recognition Based on an IMU Wearable Device and Fall Verification through a Smart Speaker and the IoT
Authors: Lin Hsin-Chang , Chen Ming-Jen , Lee Chao-Hsiung , Kung Lu-Chih , Huang Jung-Tang
Published: June 2023

A fall is one of the most devastating events that aging people can experience. Fall-related physical injuries, hospital admission, or even mortality among the elderly are all critical health issues. As the population continues to age worldwide, there is an imperative need to develop fall detection systems. We propose a system for the recognition and verification of falls based on a chest-worn wearable device, which can be used for elderly health institutions or home care. The wearable device utilizes a built-in three-axis accelerometer and gyroscope in the nine-axis inertial sensor to determine the user’s postures, such as standing, sitting, and lying down. The resultant force was obtained by calculation with three-axis acceleration. Integration of three-axis acceleration and a three-axis gyroscope can obtain a pitch angle through the gradient descent algorithm. The height value was converted from a barometer. Integration of the pitch angle with the height value can determine the behavior state including sitting down, standing up, walking, lying down, and falling. In our study, we can clearly determine the direction of the fall. Acceleration changes during the fall can determine the force of the impact. Furthermore, with the IoT (Internet of Things) and smart speakers, we can verify whether the user has fallen by asking from smart speakers. In this study, posture determination is operated directly on the wearable device through the state machine. The ability to recognize and report a fall event in real-time can help to lessen the response time of a caregiver. The family members or care provider monitor, in real-time, the user’s current posture via a mobile device app or internet webpage. All collected data supports subsequent medical evaluation and further intervention.
Chemical Characterization, Antioxidant, Insecticidal and Anti-Cholinesterase Activity of Essential Oils Extracted from Cinnamomum verum L.
Authors: Beniaich Ghada , Zouirech Otmane , Allali Aimad , Bouslamti Mohammed , Maliki Imane , El Moussaoui Abdelfattah , Chebaibi Mohamed , Nafidi Hiba-Allah , Bin Jardan Yousef A. , Bourhia Mohammed , Taleb Mustapha
Published: June 2023

This study is aimed at evaluating the potential of the essential oil of Cinnamomum verum (EOCV) as an antioxidant, as an insecticide against Callosobruchus maculatus and for its anti-acetylcholinesterase activity. To this end, EOCV was extracted via hydrodistillation from this plant, and the identification of the phytochemicals was performed using gas chromatography–mass spectrometry (GC–MS). The antioxidant power was determined via in vitro tests, the insecticidal ability was tested via exposing C. maculatus to EOCV, and molecular docking was used to evaluate the anti-cholinesterase ability. The results of these GC–MS analyses show that the main composition of EOCV comprises Cinnamaldehyde dimethyl acetal (64.50%), cinnamicaldehyde (35.04%) and α-Copaene (0.11%). The insecticidal potential of the studied OEs, determined by using the inhalation test, and expressed as the concentration of EOs required for the death of 50% of the insects (LC50) and that required the death of 95% of adults (LC95) after 96 h of exposure, was 3.99 ± 0.40 and 14.91 ± 0.10 μL/L of air, respectively. In the contact test, 96 h of exposure gave an LC50 and LC95 of 3.17 ± 0.28 and 8.09 ± 0.05 μL/L of air, respectively. A comparison of the antioxidant activity of EOCV to that of ascorbic acid via DPPH free radical scavenging ability and Ferric Reducing Antioxidant Power (FRAP) revealed the IC50 and EC50 values of EOCV to be much higher than that obtained for ascorbic acid, and the molecular docking simulation revealed Coumarin, Piperonal, Cinnamaldehyde dimethyl and alpha-Copaene as possessing potential inhibitory activities against human acetylcholinesterase. However, further experimental validation is needed to enhance the prospects of this study.
Assessment of Two Materials as Adsorbents for the Effective Removal and Further Pre-Concentration of Gallium from Aqueous Solutions: Mesoporous Carbon vs. Clinoptilolite
Authors: Sáez Patricia , Bernabé Ignacio , Gómez José Mª. , Díez Eduardo , Fraile Cristina , García Noelia , Rodríguez Araceli
Published: June 2023

In this research, the adsorption of gallium onto natural zeolite (clinoptilolite) and two mesoporous-activated carbons were compared and evaluated. The clinoptilolite was treated with HCl (HCPL), while mesoporous-activated carbons (MCSG60A and MCO1) were synthesized by replica method, using sucrose as the carbon precursor and silica gel as the template. These carbonaceous materials showed large pore sizes and mesoporous surface, as well as a suitable surface chemistry for cation adsorption, which promotes a high negative charge density. On the other hand, zeolites have narrower pore sizes, which hinders the material diffusion inside the particle; however, its strength is their ion exchange capacity. Regarding the gallium kinetic studies, it is described by Pseudo-second order model for both sorts of adsorbents. MCO1 is the best carbonaceous adsorbent studied, with a capacity of 4.58 mg/g. As for zeolites, between the two zeolites studied, HCPL showed the best results, with a gallium adsorption capacity of 3.1 mg/g. The gallium adsorption mechanism onto MCO1 material is based on physisorption, while HCPL is mainly retained due to an ion-exchange process. Regarding the Giles classification, MCO1 isotherm described an H-4 pattern of high affinity and characteristic of multilayer adsorption. The Double-Langmuir model fits properly within these experimental results. In the case of zeolites, HCPL adsorption isotherm followed an L-2 pattern, typical of monolayer adsorption—the Sips model is the one that better describes the adsorption of gallium onto the zeolite.
Optimization of Taxi Allocation for Minimizing CO2 Emissions Based on Heuristics Algorithms
Authors: Mondal Manik , Sano Kazushi , Kato Teppei , Puppateravanit Chonnipa
Published: June 2023

Recently, the rapid climate change caused by increasing CO2 emissions has become a global concern. Efficient transportation systems are necessary to reduce CO2 emissions in cities. Taxi services are an essential part of the transportation system, both in urban areas with high demand and in rural areas with inadequate public transportation. Inefficient taxi services cause problems such as increased idle times, resulting in increased CO2 emissions. This study proposes a taxi allocation model that minimizes taxi idle time costs for efficient taxi service operation. We also propose three heuristic algorithms to solve the proposed model. At last, we conduct a case study by using real taxi data in Nagaoka, Japan. By comparing the three algorithms, the dynamic greedy algorithm produced the best result in terms of idle time cost and CPU time. The findings indicate that by minimizing idle time costs and reducing the number of taxis, it is possible to achieve a significant 81.84% reduction in CO2 emissions within the transportation sector. Further, in order to estimate the idle time costs the sensitivity of demand is considered.
Imagining Decent Work towards a Green Future in a Former Forest Village of the City of Istanbul
Authors: Selçuk İklil , Nircan Zeynep Delen , Coşkun Burcu Selcen
Published: June 2023

This paper addresses issues pertaining to the future of work and sustainability through the lens of a case study of ecological deterioration and how it destroys and creates green jobs in a forest village of Istanbul. As elsewhere in major urban centres of developing countries, the hyper-expansion of city regions due to authoritarian developmentalism fosters the state-led construction sector in Turkey. Growth-driven economic policies continue to have adverse effects on the environment, resulting in deforestation among an array of ecological damage. Based on a qualitative analysis of oral history interviews and observations informed by a larger interdisciplinary research project, we observe resilience in the forest village under scrutiny as certain types of work are abandoned, and new forms are created by adaptation to the ecological and social conditions. The perceptions of changing conditions by locals vary across existing ethnic, gender, and class hierarchies in the local community. Moreover, our findings indicate that the types of work available in the village prior to urban transformation were not all decent or green. In face of ongoing ecological deterioration in a (formerly) forest community, participatory micro-initiatives, and grassroots, utilizing local community projects emerge that nevertheless pursue a green and just transition. We focus on one such initiative, the Community Fungi platform, to demonstrate the possibility of working towards a collective imagination of a green future inspired by past but unforgotten sustainable communal practices, in the context of the forest village under scrutiny in this paper.
The Reinforcement of Early Growth, Extract, and Oil of Silybum marianum L. by Polymer Organic Cover and Bacteria Inoculation under Water Deficit
Authors: Taghvaei Mansour , Kordestani Mojtaba Dolat , Saleh Mohammad , Mastinu Andrea
Published: June 2023

Early growth water stress reduces the extract and fresh oil of Silybum marianum L. (S. marianum) shoots. Two experiments were conducted to reduce the effects of early growth drought. Treatments in the first experiment were organic seed cover fillers at three levels (control, vermicompost, and peat moss), hydrogel at seven levels (control, 2, 4, and 6 g hydrogelF1 per kg OSC, and 2, 4, and 6 g hydrogelA200 per kg organic seed cover), and water deficit at three levels (100, 50, and 25% of field capacity), and in the second experiment, seeds were inoculated with bacteria at four levels (control, Pseudomonas fluorescens, Pseudomonas putida, and their combination) and water deficit at four levels (100, 50, and 25% of field capacity). Our results showed that milk thistle seeds are sensitive to water deficit at the emergence stage. Covering milk thistle (S. marianum) seeds with organic seed cover increased water retention around the seeds and improved emergence percentage. Use of organic seed cover with hydrogel increased relative water content (RWC), leaf area, and shoot length, and increased extracts and oils in fresh shoots. Bacterial inoculation also improved initial growth and reduced the effect of water stress on the plant, and increased leaf number, extract, and oil. The combination of bacteria had a positive effect on initial growth and inoculation of seeds, P. fluorescens and P. putida increased relative water content (RWC), shoot height, and specific leaf area, and increased extract and oil under water deficit conditions. A comparison of the results showed that seed inoculation is a simple method without new culture medium, and improves extract and oil under water deficit conditions.
Minimally Invasive Peritoneal Dialysis Catheter Insertion with Intraoperative Ultrasound-Doppler Measurement of Rectus Muscle Width and Inferior Epigastric Artery Localization
Authors: Janež Jurij , Grosek Jan
Published: June 2023

Laparoscopic peritoneal dialysis catheter insertion is an established method for peritoneal dialysis catheter placement. One critical aspect of this procedure is rectus sheath tunneling. Proper peritoneal dialysis catheter incorporation within the abdominal wall is important for reducing pericatheter leaks and for proper peritoneal dialysis functioning. Particularly, accurate positioning of the internal cuff within the rectus muscle sheath is crucial to prevent potential dialysate fluid leakage. In the present report, we describe the utilization of intraoperative ultrasound as a valuable tool for determining the ideal location of the internal cuff and assessing the course of the inferior epigastric artery during rectus sheath tunneling. This technique aims to optimize the position of the internal cuff and minimize complications such as vessel injury and pericatheter leaks. Furthermore, we demonstrate that post-catheter insertion, ultrasound imaging offers valuable insights into evaluating the appropriate placement of the internal cuff, external subcutaneous cuff, and potential bleeding within the abdominal wall.
An Efficient Siamese Network and Transfer Learning-Based Predictive Maintenance System for More Sustainable Manufacturing
Authors: Caliskan Abdullah , O’Brien Conor , Panduru Krishna , Walsh Joseph , Riordan Daniel
Published: June 2023

Legacy machinery poses a specific challenge when integrated into modern manufacturing lines. While modern machinery provides swift methods of integration and inbuilt predictive maintenance (PdM), older machines, while physically fully functional, are less attractive to reuse, a specific reason being their lack of ready-to-implement PdM hardware and models. More sustainable manufacturing operations can be achieved if the useable lifespan of functional older machinery can be extended through retrofittable PdM and modern industrial communication systems. While PdM models can be developed for a class (make/model) of machine with retrofitted sensing, it is often found that legacy machines will deviate greatly from their original form, through nonstandard maintenance and component replacement actions during their lengthy lifespan. This would mean that each legacy machine would require a custom PdM model, a cost often leading to the removal or nonusage of legacy machines. This paper proposes a framework designed for the generation of an efficient PdM algorithm which would allow for the reuse of legacy machines retrofitted with low-cost sensing in modern manufacturing for increased sustainability. Given a limited number of data samples collected from a machine to be maintained, we aim to predict a failure or/and maintenance time by making use of the difference between the characteristics of the variation of the healthy and unhealthy data collected from the machine. We measure the healthiness of the machine by using a Siamese network trained with a public dataset and fine-tuned with data samples obtained from machines with similar characteristics. Although we use different training and testing datasets coming from completely different sources, we obtain reasonable results thanks to the proposed technique. The results of simulations and the statistical analysis enable us to devise a transfer learning technique and a Siamese network employed for failure detection in the machine. The proposed system will allow for the continued use of older machines in modern facilities, enabling more sustainable manufacturing models.
Women Entrepreneurs Who Break through in Reward-Based Crowdfunding: The Influence of Entrepreneurial Orientation
Authors: Zhao Ke , Wang Hongwei , Wang Wei
Published: June 2023

Based upon social identity theory, having a strategic entrepreneurial orientation is crucial for ventures seeking funding, since entrepreneurial orientation (viewed as an entrepreneurial organizational culture) has a significant influence on investors’ decision-making for resource allocation. However, the attitude of investors toward women entrepreneurs’ behavioral orientation is controversial. Women entrepreneurs may not benefit from specific behavioral orientations because of gender bias. In this study, we had a sample of 5105 ‘design and technology’ campaigns with explicit gender information on Kickstarter, utilizing a computer-aided text analysis dictionary of entrepreneurial orientation to examine whether the five dimensions of entrepreneurial orientation signals affected the relationship between women entrepreneurs and their performance in reward-based crowdfunding. Our findings demonstrated that investors tended to support women entrepreneurs who displayed many of the signals for autonomy and risk-taking, while backers were skeptical of women entrepreneurs displaying a high number of the signals for proactiveness. This study will enable an in-depth understanding of the link between investors’ decision-making and women’s entrepreneurial behaviors, in addition to determining which specific entrepreneurial behavior is important for helping women entrepreneurs to obtain funding in the context of reward-based crowdfunding, from a practical perspective.
Nitrite-Oxidizing Bacterial Strains Isolated from Soils of Andean Ecosystems and Their Potential Use in Nitrogen Reduction
Authors: Salazar Jazmin M. , Calle Jessica , Pereira Steeven , Cordero Paula , Matovelle Carlos
Published: June 2023

Nitrification is part of the nitrogen cycle that occurs naturally in ecosystems. It is related to the presence of microorganisms and their metabolism, especially bacteria, which are involved in oxidizing compounds such as NH4+ and NO2− to NO3−. In this study, we evaluated the nitrification potential in 12 bacteria strains that belong to the genera Aeromonas, Bacillus, Buttiauxella, Mycobacterium, Paenibacillus, Serratia, and Yersenia, which are part of the cultivable microbial community from soil in a native forest and pine forest in The Labrado area within the Machangara micro-watershed in the Andes located in the south of Ecuador. This investigation aims to identify heterotrophic and lithoautotrophic strains using specific culture media for ammonium oxidative (AOL-AOH) and nitrate oxidation bacteria (ONL-ONH). The formation of nitrifying halos in the culture media allowed the identification of 10 strains with nitrifying potential. Five strains were from the pine forest, four were isolated from the native forest, and one strain was shared between both forests. The Serratia and Yersinia genera have a high NO2− oxidation capacity. Their inoculation in synthetic water rich in nitrogenous products allowed us to determine 40% and 94% nitrite reduction percentages and cell retention times of 20 to 40 days. Our results are promising for their possible potential use in environmental bioremediation processes through inoculation in wastewater for the biological removal of nitrogenous compounds.
Influence of Dry-Wet Cycles on the Structure and Shear Strength of Loess
Authors: Wang Xiaoliang , Li Hongru , Zhong Yue , Zhang Longfei , Yang Xi , Han Xiaoning , Hu Zaiqiang
Published: June 2023

The dry-wet cycle is an important factor that causes slope instability and foundation settlement in loess regions. In order to study the effects of the dry-wet cycle on the structure and shear strength of loess, isotropic compression tests and triaxial shear tests were carried out on loess with different numbers of dry-wet cycles. The results show that the dry-wet cycles mainly reduce the cohesion of loess, and the most obvious decline is after the first cycle; however, they have no effect on the angle of internal friction of loess. The structural yield strength and structural parameters of loess can represent the structure of loess well, which gradually decrease with the increase in the number dry-wet cycles and water content. The initial yield surface is approximately an ellipse, which gradually shrinks with the increase in water content and dry-wet cycles. The structure and cohesion of loess have similar changes, and there is an obvious exponential function relationship between them.
Evaluation of MSWX Bias-Corrected Meteorological Forcing Datasets in China
Authors: Lin Hai , Yang Yi , Wang Shuguang , Wang Shuyu , Tang Jianping , Dong Guangtao
Published: June 2023

Near-surface meteorological forcing (NSMF) datasets, mixed observations, and model forecasts are widely used in global climate change and sustainable development studies. For practical purposes, it is important to evaluate NSMF datasets, especially those released latest, and determine their strengths and limitations. In this study, we evaluate the performance of Multi-Source Weather (MSWX) in China over the period of 1979–2016. For comparison, ECMWF Reanalysis version 5 (ERA5), China Meteorological Forcing Dataset (CMFD) and Princeton Global Forcing (PGF) dataset are also evaluated to determine the strengths and weaknesses of MSWX. The following variables are compared with observations over 2400 stations: 2 m air temperature (T2m), 2 m daily maximum air temperature (Tmax), 2 m daily minimum air temperature (Tmin), precipitation (P), and 10 m wind speed (V10). The evaluation is conducted in terms of climatology, inter-annual variations and seasonal cycles. Results show that MSWX reasonably reproduces the spatial pattern of T2m with root-mean-square errors (RMSEs) below 1.12 °C and spatial correlations above 0.97, but underestimates Tmax and overestimates Tmin, with biases ranging from −2.0 °C to 2.0 °C, especially over the North China and Northeast China. Compared with ERA5 and PGF, MSWX can better simulate the inter-annual variations of surface air temperature with high spatial correlations (>0.97) but shows higher RMSEs than PGF. For precipitation, MSWX accurately captures the primary features of precipitation, including significant characteristics or patterns of the precipitation climatology and inter-annual variation. Its inter-annual variation shows low RMSEs ranging from 0.55 mm/day to 0.8 mm/day, compared to ERA5 and PGF. However, regions with abundant precipitation exhibit higher biases. Because the biased Global Wind Atlas (GWA3.1) is used for the wind bias correction of MSWX, MSWX significantly overestimates the annual mean wind speed, but it is consistently well-correlated with observations, with RMSEs less than 1.5 m/s and spatial correlations greater than 0.6 over the period of 1979–2016. This study reveals both the advantages and disadvantages of MSWX, and indicates the need for research into climate change and sustainable development in East Asia.
Designing, Modeling, and Fabrication of a Novel Solar-Concentrating Spittoon against COVID-19 for Antibacterial Sustainable Atmosphere
Authors: Sharma Abhimannyu , Kumar Dheeraj , Kumar Amit , Faisal Nadeem , Kumar Naresh , Pandey Shatrudhan , Hasnain S. M. Mozammil , Al-Hazani Tahani Mohamed , AlKahtane Abdullah A. , Alkahtani Saad , Chatterjee Rajeshwari
Published: June 2023

Spreading infectious illnesses such as viral meningitis, hepatitis, and cytomegalovirus among people is facilitated by spitting in public. India is more prone to transferring infectious illnesses. Recent research discovered that the new Coronavirus may also be transmitted via an infected person’s saliva. Self-collected saliva from 91.7% of patients contains COVID-19. Numerous nations have prioritized preventing individuals from spitting in open or public areas such as hospitals, parks, airports, train stations, etc. The UVC range has a greater damaging effect on microbial cells because microorganisms’ intracellular components, such as RNA, DNA, and proteins, are sensitive to UVC photon absorption. In this article, the design and construction of a solar-concentrating spittoon is attempted. At its receiver, it can create a temperature of 390 K and 176 W of heat. At this temperature, most viruses (including Coronavirus), bacteria, and pathogens are inactivated. Daily, from 8:00 a.m. until 5:00 p.m., the solar-concentrating spittoon is functional. The solar-concentrating spittoon performance was best for nine hours. The receiver thermal efficiency was 80% and 20% of heat was lost to the surroundings. The overall efficiency was found to be 70%. During this time, most people spend their time outside, where this solar-powered spittoon can incinerate human cough and spit within one minute. The installation of this solar-concentrated spittoon will aid in preventing the spread of fatal dangerous diseases and cleaning the city.
The Environmental Impacts of Bar Soap Production: Uncovering Sustainability Risks with LCA Analysis
Authors: Gaurav Gaurav , Dangayach Govind Sharan , Meena Makkhan Lal , Chaudhary Vijay , Gupta Sumit , Jagtap Sandeep
Published: June 2023

Washing bar soap is widely used and vital in everyday life, especially in developing countries where demand is increasing due to population expansion. However, the production and use of washing bar soap have negative impacts on the environment, and the sustainability of soap packaging is also a concern. This research focuses on measuring the environmental effects of the production phase of washing bar soap while accounting for the differences in soap consumption across brands and consumer behavior during the use phase. The research aims to quantify the ecological burden caused by the production and use of 1 kg of bar soap through a Life Cycle Assessment (LCA) that follows ISO 14040 and 14044 standards. This study also addresses the resource-intensive aspect of soap packaging, particularly plastic packaging, and offers sustainability solutions through circular economy principles. GaBi v8.0 software is used to evaluate various environmental performance indicators, and the results show that eutrophication has the highest burden on the environment compared to other categories. This study highlights the importance of consumer behavior in reducing the environmental impact of washing bar soap, as the use stage of washing bar soap has the most significant impact in most categories.
Could the Sloping Land Conversion Program Promote Farmers’ Income in Rocky Desertification Areas?—Evidence from China
Authors: Zhao Rong , Jia Tianyu , Li He
Published: June 2023

The Sloping Land Conversion Program (SLCP) is a significant measure to achieve the Sustainable Development Goals (SDGs) proposed by the United Nations in 2015. SLCP plays an important role in poverty alleviation and income increase for farmers in poor areas. The purpose of this study is to analyze whether the income of farmers has increased after participating in SLCP, and whether SLCP has released the agricultural labor force to obtain non-agricultural income by participating in non-agricultural work. Based on the field investigation in Luocheng County and Longsheng County of Guangxi, Libo County, and Dushan county of Guizhou, this paper uses the method of propensity score matching (PSM) to explore the impact of SLCP on the income of farmers in rocky desertification areas. According to our research, it is found that: (1) SLCP has a positive effect of 5.2% on the average annual net income of farmers, a positive effect of 43.2% on agricultural income, and a negative effect of 9.8% on non-agricultural income, but all of the effects are insignificant. Selective deviation will overestimate the impact of SLCP on farmers’ total income and agricultural income and underestimate the impact on non-agricultural income. SLCP failed to promote the transformation of farmers into secondary and tertiary industries. The mechanism of SLCP to increase farmers’ income is complex. (2) Farmers’ participation in SLCP is influenced by work experience and education level in human capital, participation in skills training in social capital, and owning durable consumer goods in physical capital. Although SLCP will promote economic development under the condition of improving the ecological environment in the future, it is not advisable to exchange farmers’ livelihood for ecological construction at present. The implementation of SLCP should consider not only the overall ecological benefits, but also the short-term social and economic benefits.
An Exploration of Transformative Learning Applied to the Triple Bottom Line of Sustainability for Fashion Consumers
Authors: Chang Hyo Jung (Julie) , Rakib Nasir , Min Jaehan
Published: June 2023

Growing awareness and concern about sustainability worldwide has drawn attention to the sustainability practices of the textile and apparel industry and its consumers. In particular, educating consumers about sustainability becomes more important as it can increase their sustainability awareness and prompt action. Therefore, based on the transformative learning theory, this study was designed to explore the current knowledge of sustainability of Generation Z fashion consumers by observing and analyzing a focus group discussion. A qualitative research method was used, twenty participants in four focus groups participated, and two activities were implemented during the focus group sessions in this study. A thematic analysis was used to interpret the qualitative transcribed data. Five themes emerged from the focus group discussion, including Normalizing Customer Activism, Short-Sighted Actions, Story Sharing with Others, Filling the Information Gap, and Challenging but Not Impossible. The results show that consumers have a limited understanding of sustainability, i.e., they are primarily concerned about the environmental aspect of sustainability. However, the knowledge and discussion extracted through video and website browsing led to transformative learning among the participants, thereby changing their understanding of sustainability from a predominantly environmental perspective to one that encompasses social aspects. In addition, after this learning process, fashion consumers can perceive sustainability more holistically as a balance of the three aspects of sustainability. The findings of this study can be applied to inform educational programs and create opportunities for reframing marketing strategies by leveraging various technological platforms.
Identification of Saline Soils Using Soil Geochemical Data: A Case Study in Soda-Salinization Areas, NE China
Authors: Lan Tian , Lu Jilong , Hao Libo , Bai Rongjie , Sun Xiaohan , Zhao Xinyun , Wang Yongzhi
Published: June 2023

Identifying saline soils is of great importance for protecting land resources and for the sustainable development of agriculture. Total soil salinity (TSS) is the most commonly used indicator for determining soil salinization, but the application of soil geochemical data is rarely reported. In general, there is a significant relationship between TSS and the content of soil-soluble Na, which can be estimated by the difference between the bulk-soil Na2O content and its background value. In this study, the partial least squares regression (PLSR) method was employed to calculate the Na2O background value via a regression model between Na2O and SiO2, Al2O3, TFe2O3, Cr, Nb, and P in a 1:250,000 scale regional geochemical data set of soils in Jilin Province, NE China. We defined δNa as the difference between the bulk-soil Na2O value and the regression background value, which can be used as a geochemical indicator to identify saline soils. One hundred and five samples with known TSS contents in the study area were selected to test the capability of the indicator δNa. The result shows that the identification accuracy can be up to 75%, indicating that the indicator can provide a new means for saline soil identification.
The Impact of Digital Enterprise Agglomeration on Carbon Intensity: A Study Based on the Extended Spatial STIRPAT Model
Authors: Yang Shoufu , Zhao Hanhui , Chen Yiming , Fu Zitian , Sun Chaohao , Chang Tsangyao
Published: June 2023

The digital economy has broken the physical space limit, reshaped factor input ratios, and accelerated factor mobility, which drives carbon reduction and social sustainability. Digital enterprise agglomeration is becoming the new tendency and a significant spatial feature for digital economy development. This work aimed to study the impact of digital enterprise agglomeration on carbon intensity. This study first proposed an extended spatial stochastic IPAT (STIRPAT) theoretical framework and regarded digital enterprise agglomeration as a technology factor. Secondly, by building a dataset with 7,902,050 digital enterprises and using the distance-based Duranton and Overman index, this study evaluated the digital enterprise agglomeration of 278 cities from 2007 to 2017 in China. Thirdly, by matching micro digital enterprise data and macro city data, this study employed spatial Durbin, mediating, and moderating effects models to test the impact and mechanism of digital enterprise agglomeration on carbon intensity. There are four main findings: (1) There is a negative “U-shaped” correlation between digital enterprise agglomeration and local and neighboring cities’ carbon intensities, and the impact of neighboring digital enterprise agglomeration on local carbon intensity is more significant than the effect of regional digital enterprise agglomeration on local carbon intensity. (2) The impact of digital enterprise agglomeration on carbon intensity shows great differences under spatial, resource, industrial, and financial heterogeneity. (3) Digital enterprise agglomeration indirectly impacts carbon intensity in two ways: the green technology innovation effect and the industry structure rationalization effect. (4) Human capital enhances the role of digital enterprise agglomeration in reducing carbon intensity, whereas government intervention weakens the effect of digital enterprise agglomeration in decreasing carbon intensity. This paper suggests that digital enterprise agglomeration strategies should be dynamically adjusted based on local digital economy development and resource conditions.
Characterization of a New Powdered, Milk-Based Medicinal Plant (Alcea rosea) Drink Product
Authors: Mortas Mustafa
Published: June 2023

Alcea rosea, known as hollyhock, is an ornamental dicot flower in the Malvaceae family, and it has been used for different purposes, ranging from traditional medicine to food applications, through the use of its leaves, roots, and seeds. The hollyhock flowers possess several properties, including a diuretic, cooling, demulcent, emollient, febrifuge, and astringent effects. Hollyhock flowers were commonly included in a traditional medicine formulation for hypoglycemic or hypolipidemic treatments. Along with its use in traditional medicine, it has also been considered a valuable ingredient in some traditional food preparations; however, the processing of hollyhock into a new food product has not been studied. Accordingly, this study aimed to evaluate the production of a new product, a milk-based Hollyhock (Alcea rosea) powder, and its powder product characterization via particle size, water activity, density, flowability, etc., in addition to the determination of its chemical composition (with 5.73% ash and 29.12% protein). In this paper, we report the application of spray-dried milk-based hollyhock flower extract to produce a new ready-to-drink product of this medicinal plant for food sustainability.