bluuebunny/crossref_metadata_2025 huggingface dataset:
Person-Specific Gaze Estimation from Low-Quality Webcam Images
Authors: Ansari Mohd Faizan , Kasprowski Pawel , Peer Peter
Published: April 2023

Gaze estimation is an established research problem in computer vision. It has various applications in real life, from human–computer interactions to health care and virtual reality, making it more viable for the research community. Due to the significant success of deep learning techniques in other computer vision tasks—for example, image classification, object detection, object segmentation, and object tracking—deep learning-based gaze estimation has also received more attention in recent years. This paper uses a convolutional neural network (CNN) for person-specific gaze estimation. The person-specific gaze estimation utilizes a single model trained for one individual user, contrary to the commonly-used generalized models trained on multiple people’s data. We utilized only low-quality images directly collected from a standard desktop webcam, so our method can be applied to any computer system equipped with such a camera without additional hardware requirements. First, we used the web camera to collect a dataset of face and eye images. Then, we tested different combinations of CNN parameters, including the learning and dropout rates. Our findings show that building a person-specific eye-tracking model produces better results with a selection of good hyperparameters when compared to universal models that are trained on multiple users’ data. In particular, we achieved the best results for the left eye with 38.20 MAE (Mean Absolute Error) in pixels, the right eye with 36.01 MAE, both eyes combined with 51.18 MAE, and the whole face with 30.09 MAE, which is equivalent to approximately 1.45 degrees for the left eye, 1.37 degrees for the right eye, 1.98 degrees for both eyes combined, and 1.14 degrees for full-face images.
A Lightweight Intelligent Network Intrusion Detection System Using One-Class Autoencoder and Ensemble Learning for IoT
Authors: Yao Wenbin , Hu Longcan , Hou Yingying , Li Xiaoyong
Published: April 2023

Network intrusion detection technology is key to cybersecurity regarding the Internet of Things (IoT). The traditional intrusion detection system targeting Binary or Multi-Classification can detect known attacks, but it is difficult to resist unknown attacks (such as zero-day attacks). Unknown attacks require security experts to confirm and retrain the model, but new models do not keep up to date. This paper proposes a Lightweight Intelligent NIDS using a One-Class Bidirectional GRU Autoencoder and Ensemble Learning. It can not only accurately identify normal and abnormal data, but also identify unknown attacks as the type most similar to known attacks. First, a One-Class Classification model based on a Bidirectional GRU Autoencoder is introduced. This model is trained with normal data, and has high prediction accuracy in the case of abnormal data and unknown attack data. Second, a multi-classification recognition method based on ensemble learning is proposed. It uses Soft Voting to evaluate the results of various base classifiers, and identify unknown attacks (novelty data) as the type most similar to known attacks, so that exception classification becomes more accurate. Experiments are conducted on WSN-DS, UNSW-NB15, and KDD CUP99 datasets, and the recognition rates of the proposed models in the three datasets are raised to 97.91%, 98.92%, and 98.23% respectively. The results verify the feasibility, efficiency, and portability of the algorithm proposed in the paper.
Compact Harmonic Vernier Sensor Based on an In-Fiber FPI with Three Reflector System for Simultaneous Gas Pressure and Temperature Measurement
Authors: Dan Jinxiao , Dang Wenjie , Li Zeren , Nan Pengyu , Xin Guoguo , Lim Kok-Sing , Ahmad Harith , Yang Hangzhou
Published: April 2023

In this work, we proposed a sensitivity-enhanced temperature sensor, a compact harmonic Vernier sensor based on an in-fiber Fabry–Perot Interferometer (FPI), with three reflective interfaces for the measurement of gas temperature and pressure. FPI consists of air and silica cavities formulated by single-mode optical fiber (SMF) and several short hollow core fiber segments. One of the cavity lengths is deliberately made larger to excite several harmonics of the Vernier effect that have different sensitivity magnifications to the gas pressure and temperature. The spectral curve could be demodulated using a digital bandpass filter to extract the interference spectrum according to the spatial frequencies of resonance cavities. The findings indicate that the material and structural properties of the resonance cavities have an impact on the respective temperature sensitivity and pressure sensitivity. The measured pressure sensitivity and temperature sensitivity of the proposed sensor are 114 nm/MPa and 176 pm/°C, respectively. Therefore, the proposed sensor combines ease of fabrication and high sensitivity, making it great potential for practical sensing measurements.
Indirect Calorimetry in Spontaneously Breathing, Mechanically Ventilated and Extracorporeally Oxygenated Patients: An Engineering Review
Authors: Priem Sebastiaan , Jonckheer Joop , De Waele Elisabeth , Stiens Johan
Published: April 2023

Indirect calorimetry (IC) is considered the gold standard for measuring resting energy expenditure (REE). This review presents an overview of the different techniques to assess REE with special regard to the use of IC in critically ill patients on extracorporeal membrane oxygenation (ECMO), as well as to the sensors used in commercially available indirect calorimeters. The theoretical and technical aspects of IC in spontaneously breathing subjects and critically ill patients on mechanical ventilation and/or ECMO are covered and a critical review and comparison of the different techniques and sensors is provided. This review also aims to accurately present the physical quantities and mathematical concepts regarding IC to reduce errors and promote consistency in further research. By studying IC on ECMO from an engineering point of view rather than a medical point of view, new problem definitions come into play to further advance these techniques.
A Cylindrical Near-Field Acoustical Holography Method Based on Cylindrical Translation Window Expansion and an Autoencoder Stacked with 3D-CNN Layers
Authors: Wang Jiaxuan , Zhang Weihan , Zhang Zhifu , Huang Yizhe
Published: April 2023

The performance of near-field acoustic holography (NAH) with a sparse sampling rate will be affected by spatial aliasing or inverse ill-posed equations. Through a 3D convolution neural network (CNN) and stacked autoencoder framework (CSA), the data-driven CSA-NAH method can solve this problem by utilizing the information from data in each dimension. In this paper, the cylindrical translation window (CTW) is introduced to truncate and roll out the cylindrical image to compensate for the loss of circumferential features at the truncation edge. Combined with the CSA-NAH method, a cylindrical NAH method based on stacked 3D-CNN layers (CS3C) for sparse sampling is proposed, and its feasibility is verified numerically. In addition, the planar NAH method based on the Paulis–Gerchberg extrapolation interpolation algorithm (PGa) is introduced into the cylindrical coordinate system, and compared with the proposed method. The results show that, under the same conditions, the reconstruction error rate of the CS3C-NAH method is reduced by nearly 50%, and the effect is significant.
mCrutch: A Novel m-Health Approach Supporting Continuity of Care
Authors: Arcobelli Valerio Antonio , Zauli Matteo , Galteri Giulia , Cristofolini Luca , Chiari Lorenzo , Cappello Angelo , De Marchi Luca , Mellone Sabato
Published: April 2023

This paper reports the architecture of a low-cost smart crutches system for mobile health applications. The prototype is based on a set of sensorized crutches connected to a custom Android application. Crutches were instrumented with a 6-axis inertial measurement unit, a uniaxial load cell, WiFi connectivity, and a microcontroller for data collection and processing. Crutch orientation and applied force were calibrated with a motion capture system and a force platform. Data are processed and visualized in real-time on the Android smartphone and are stored on the local memory for further offline analysis. The prototype’s architecture is reported along with the post-calibration accuracy for estimating crutch orientation (5° RMSE in dynamic conditions) and applied force (10 N RMSE). The system is a mobile-health platform enabling the design and development of real-time biofeedback applications and continuity of care scenarios, such as telemonitoring and telerehabilitation.
A Rehabilitation of Pixel-Based Spectral Reconstruction from RGB Images
Authors: Lin Yi-Tun , Finlayson Graham D.
Published: April 2023

Recently, many deep neural networks (DNN) have been proposed to solve the spectral reconstruction (SR) problem: recovering spectra from RGB measurements. Most DNNs seek to learn the relationship between an RGB viewed in a given spatial context and its corresponding spectra. Significantly, it is argued that the same RGB can map to different spectra depending on the context with respect to which it is seen and, more generally, that accounting for spatial context leads to improved SR. However, as it stands, DNN performance is only slightly better than the much simpler pixel-based methods where spatial context is not used. In this paper, we present a new pixel-based algorithm called A++ (an extension of the A+ sparse coding algorithm). In A+, RGBs are clustered, and within each cluster, a designated linear SR map is trained to recover spectra. In A++, we cluster the spectra instead in an attempt to ensure neighboring spectra (i.e., spectra in the same cluster) are recovered by the same SR map. A polynomial regression framework is developed to estimate the spectral neighborhoods given only the RGB values in testing, which in turn determines which mapping should be used to map each testing RGB to its reconstructed spectrum. Compared to the leading DNNs, not only does A++ deliver the best results, it is parameterized by orders of magnitude fewer parameters and has a significantly faster implementation. Moreover, in contradistinction to some DNN methods, A++ uses pixel-based processing, which is robust to image manipulations that alter the spatial context (e.g., blurring and rotations). Our demonstration on the scene relighting application also shows that, while SR methods, in general, provide more accurate relighting results compared to the traditional diagonal matrix correction, A++ provides superior color accuracy and robustness compared to the top DNN methods.
Damage Quantification and Identification in Structural Joints through Ultrasonic Guided Wave-Based Features and an Inverse Bayesian Scheme
Authors: Wu Wen , Cantero-Chinchilla Sergio , Yan Wang-ji , Chiachio Ruano Manuel , Remenyte-Prescott Rasa , Chronopoulos Dimitrios
Published: April 2023

In this paper, defect detection and identification in aluminium joints is investigated based on guided wave monitoring. Guided wave testing is first performed on the selected damage feature from experiments, namely, the scattering coefficient, to prove the feasibility of damage identification. A Bayesian framework based on the selected damage feature for damage identification of three-dimensional joints of arbitrary shape and finite size is then presented. This framework accounts for both modelling and experimental uncertainties. A hybrid wave and finite element approach (WFE) is adopted to predict the scattering coefficients numerically corresponding to different size defects in joints. Moreover, the proposed approach leverages a kriging surrogate model in combination with WFE to formulate a prediction equation that links scattering coefficients to defect size. This equation replaces WFE as the forward model in probabilistic inference, resulting in a significant enhancement in computational efficiency. Finally, numerical and experimental case studies are used to validate the damage identification scheme. An investigation into how the location of sensors can impact the identified results is provided as well.
Symmetry of the Neck Muscles’ Activity in the Electromyography Signal during Basic Motion Patterns
Authors: Figas Gabriela , Hadamus Anna , Błażkiewicz Michalina , Kujawa Jolanta
Published: April 2023

The activity of muscles during motion in one direction should be symmetrical when compared to the activity of the contralateral muscles during motion in the opposite direction, while symmetrical movements should result in symmetrical muscle activation. The literature lacks data on the symmetry of neck muscle activation. Therefore, this study aimed to analyse the activity of the upper trapezius (UT) and sternocleidomastoid (SCM) muscles at rest and during basic motions of the neck and to determine the symmetry of the muscle activation. Surface electromyography (sEMG) was collected from UT and SCM bilaterally during rest, maximum voluntary contraction (MVC) and six functional movements from 18 participants. The muscle activity was related to the MVC, and the Symmetry Index was calculated. The muscle activity at rest was 23.74% and 27.88% higher on the left side than on the right side for the UT and SCM, respectively. The highest asymmetries during motion were for the SCM for the right arc movement (116%) and for the UT in the lower arc movement (55%). The lowest asymmetry was recorded for extension–flexion movement for both muscles. It was concluded that this movement can be useful for assessing the symmetry of neck muscles’ activation. Further studies are required to verify the above-presented results, determine muscle activation patterns and compare healthy people to patients with neck pain.
Quantification of Health Claim-Relevant Tyrosol and Hydroxytyrosol after Direct Hydrolysis Improves Customer Understanding and Mitigates Market Distortion
Authors: Mair Alex , Fischnaller Martin , Lutz Oliver M. D. , Corradini Danilo , Skaltsounis Alexios-Leandros , Stathopoulos Panagiotis , Jakschitz Thomas A. E. , Rainer Matthias , Bonn Günther K.
Published: April 2023

The EFSA-approved claim that olive oil is beneficial for cardiovascular health suffers from ambiguities that lead to a vague and potentially subjective interpretation of the underlying analytical data. Misunderstandings among customers, but also market distortions are possible consequences. In this study, a rapid and simple analytical technique is presented that circumvents the ambiguity by measuring levels of putative health-promoting compounds as the equivalent of tyrosol and hydroxytyrosol, cleaving such moieties from more complex constituents such as oleuropein and oleocanthal. Since the direct hydrolysis of the olive oil is the central element of the process, the reaction temperature, time, reagent concentration and reagent type were optimized. In addition, the influence of co-solvents, which might support the intermittent miscibility of the two phases during hydrolysis, was investigated. The analytical and economic implications are discussed particularly in the context of a commonly used technique.
Impact of the Anatomical Accelerometer Placement on Vertical Jump Performance Characteristics
Authors: Cabarkapa Damjana V. , Cabarkapa Dimitrije , Philipp Nicolas M. , Fry Andrew C.
Published: April 2023

With rapid technological development over recent years, the use of wearable athlete monitoring devices has substantially gained popularity. Thus, the purpose of the present study was to examine the impact of the anatomical placement of an accelerometer on biomechanical characteristics of countermovement vertical jump with and without an arm swing when compared to the force plate as a criterion measure. Seventeen recreationally active individuals (ten males and seven females) volunteered to participate in the present study. Four identical accelerometers sampling at 100 Hz were placed at the following anatomical locations: upper-back (UB), chest (CH), abdomen (AB), and hip (HP). While standing on a uni-axial force plate system sampling at 1000 Hz, each participant completed three non-sequential maximal countermovement vertical jumps with and without an arm swing. All devices recorded the data simultaneously. The following variables of interest were obtained from ground reaction force curves: peak concentric force (PCF), peak landing force (PLF), and vertical jump height (VJH). The findings of the present study reveal that the most appropriate anatomical locations to place the accelerometer device when attempting to estimate PCF, PLF, and VJH during a countermovement vertical jump with no arm swing are CH, AB, and UB, and during a countermovement vertical jump with an arm swing are UB, HP, and UB, respectively. Overall, these findings may help strength and conditioning professionals and sports scientists to select appropriate anatomical locations when using innovative accelerometer technology to monitor vertical jump performance characteristics.
Recurring Errors in Studies of Gender Differences in Variability
Authors: Hill Theodore P. , Arden Rosalind
Published: April 2023

The past quarter century has seen a resurgence of research on the controversial topic of gender differences in variability, in part because of its potential implications for the issue of under- and over-representation of various subpopulations of our society, with respect to different traits. Unfortunately, several basic statistical, inferential, and logical errors are being propagated in studies on this highly publicized topic. These errors include conflicting interpretations of the numerical significance of actual variance ratio values; a mistaken claim about variance ratios in mixtures of distributions; incorrect inferences from variance ratio values regarding the relative roles of sociocultural and biological factors; and faulty experimental designs. Most importantly, without knowledge of the underlying distributions, the standard variance ratio test statistic is shown to have no implications for tail ratios. The main aim of this note is to correct the scientific record and to illuminate several of these key errors in order to reduce their further propagation. For concreteness, the arguments will focus on one highly influential paper.
Macroplastics in the Bottom of the Veracruz Reef System National Park
Authors: Morales Jiménez Citlalmina , Lango Reynoso Fabiola , del Refugio Castañeda Chávez María , Navarrete Rodríguez Gabycarmen
Published: April 2023

The presence of macroplastics in the marine ecosystem is one of the most serious types of pollution today. On the seabed of reef ecosystems, macroplastics are an indicator of contamination because they are easily observable due to their size greater than 2.5 cm. When these wastes sink, they cause serious damage, such as physical changes to the seabed, entanglement, ingestion and transport of invasive species, and can serve as vectors for other pollutants. The main types of macroplastics found in this research work correspond to 57% fishing gear, 14% plastic fragments and 9% textiles. Most of the macroplastics were located in the Veracruz reef subsystem, in the Gallega, Anegada de adentro, Ingenieros, Pájaros and Hornos reefs; In the Antón Li-zardo reef subsystem, macroplastics were found in the Anegadilla reef and in the middle. In reference to the concentration of macroplastics at the bottom of the PNSAV, it is possible to point out that the higher the density of the material with respect to seawater, the economic activities carried out near the reefs have a greater influence, both in the distribution and in the classification of macroplastics, compared to the hydrodynamics. Finally, with all these elements, a theoretical model of distribution and concentration of macroplastics in reef bottoms is proposed.
On the Importance of Data Quality Assessment of Crowdsourced Meteorological Data
Authors: Vuckovic Milena , Schmidt Johanna
Published: April 2023

This study reflects on the quality aspects of urban meteorological time series obtained by crowdsourcing, specifically the air temperature and humidity data originating from personal weather stations (PWS) and the related implications for empirical and numerical research. A number of year-long hourly-based PWS data were obtained and compared to the data from the authoritative weather stations for selected areas in the city of Vienna, Austria. The results revealed a substantial amount of erroneous occurrences, ranging from singular and sequential data gaps to prevalent faulty signals in the recorded PWS data. These erroneous signals were more prominent in humidity time series data. If not treated correctly, such datasets may be a source of substantial errors that may drive inaccurate inferences from the modelling results and could further critically misinform future mitigation measures aimed at alleviating pressures related to climate change and urbanization.
The Accuracy of Land Use and Cover Mapping across Time in Environmental Disaster Zones: The Case of the B1 Tailings Dam Rupture in Brumadinho, Brazil
Authors: Filho Carlos Roberto Mangussi , do Valle Junior Renato Farias , de Melo Silva Maytê Maria Abreu Pires , Mendes Rafaella Gouveia , de Souza Rolim Glauco , Pissarra Teresa Cristina Tarlé , de Melo Marília Carvalho , Valera Carlos Alberto , Pacheco Fernando António Leal , Fernandes Luís Filipe Sanches
Published: April 2023

The rupture of a tailings dam causes several social, economic, and environmental impacts because people can die, the devastation caused by the debris and mud waves is expressive and the released substances may be toxic to the ecosystem and humans. There were two major dam failures in the Minas Gerais state, Brazil, in the last decade. The first was in 2015 in the city of Mariana and the second was in 2019 in the municipality of Brumadinho. The extent of land use and cover changes derived from those collapses were an expression of their impacts. Thus, knowing the changes to land use and cover after these disasters is essential to help repair or mitigate environmental degradation. This study aimed to diagnose the changes to land cover that occurred after the failure of dam B1 in Brumadinho that affected the Ferro-Carvão stream watershed. In addition to the environmental objective, there was the intention of investigating the impact of image preparation, as well as the spatial and spectral resolution on the classification’s accuracy. To accomplish the goals, visible and near-infrared bands from Landsat (30 m), Sentinel-2 (10 m), and PlanetScope Dove (4.77 m) images collected between 2018 and 2021 were processed on the Google Earth Engine platform. The Pixel Reduction to Median tool was used to prepare the record of images, and then the random forest algorithm was used to detect the changes in land cover caused by the tailings dam failure under the different spatial and spectral resolutions and to provide the corresponding measures of accuracy. The results showed that the spatial resolution of the images affects the accuracy, but also that the selected algorithm and images were all capable of accurately classifying land use and cover in the Ferro-Carvão watershed and their changes over time. After the failure, mining/tailings areas increased in the impacted zone of the Ferro-Carvão stream, while native forest, pasture, and agricultural lands declined, exposing the environmental deterioration. The environment recovered in subsequent years (2020–2021) due to tailings removal and mobilization.
RAID: Robust and Interpretable Daily Peak Load Forecasting via Multiple Deep Neural Networks and Shapley Values
Authors: Jang Joohyun , Jeong Woonyoung , Kim Sangmin , Lee Byeongcheon , Lee Miyoung , Moon Jihoon
Published: April 2023

Accurate daily peak load forecasting (DPLF) is crucial for informed decision-making in energy management. Deep neural networks (DNNs) are particularly apt for DPLF because they can analyze multiple factors, such as timestamps, weather conditions, and historical electric loads. Interpretability of machine learning models is essential for ensuring stakeholders understand and trust the decision-making process. We proposed the RAID (robust and interpretable DPLF) model, which enhances DPLF accuracy by recognizing daily peak load patterns and building separate DNN models for each day of the week. This approach was accessible for energy providers with limited computational resources, as the DNN models could be configured without a graphics processing unit (GPU). We utilized scikit-learn’s MLPRegressor for streamlined implementation, Optuna for hyperparameter optimization, and the Shapley additive explanations (SHAP) method to ensure interpretability. Applied to a dataset from two commercial office buildings in Richland, Washington, RAID outperformed existing methods like recurrent neural networks, Cubist, and HYTREM, achieving the lowest mean absolute percentage error values: 14.67% for Building 1 and 12.74% for Building 2. The kernel SHAP method revealed the influence of the previous day’s peak load and temperature-related variables on the prediction. The RAID model substantially improved energy management through enhanced DPLF accuracy, outperforming competing methods, providing a GPU-free configuration, and ensuring interpretable decision-making, with the potential to influence energy providers’ choices and promote overall energy system sustainability.
Assessing CSR Reports of Top UK Construction Companies: The Case of Occupational Health and Safety Disclosures
Authors: Fotiadis Stefanos , Evangelinos Konstantinos I. , Konstantakopoulou Foteini , Nikolaou Ioannis E.
Published: April 2023

As health and safety in construction is a major concern worldwide, this paper examines the occupational health and safety (OHS) disclosures of leading companies. A composite disclosure index was devised, based on the Global Reporting Initiative (GRI) Standards for Corporate Social Responsibility (CSR) Reporting, and focuses on the information found in such reports of corporations pertaining to the United Kingdom (UK) construction industry, in an attempt to identify trends in OHS reporting from a sample of fifteen corporations. The results disclose that construction companies fall short in reporting OHS objectives. The prevention and mitigation measures of OHS impacts and occupational health services are the only indicators in which companies reach medium to good performance. In contrast, issues of young workers exposed to hazards pertaining to suppliers are not reported by the sample. Five sample firms were identified as not revealing any information on OHS, while there was no disclosure by at least nine companies.
Sustainability Topics Integration in Supply Chain and Logistics Higher Education: Where Is the Middle East?
Authors: Rosi Maja , Obrecht Matevž
Published: April 2023

The global logistics industry has grown significantly in the last decade and has become essential to global business activities. In addition, the logistics industry is vital in transportation, urbanization in the Middle East, and transshipment through the Middle East. Due to their increasing importance and size, there is an increasing demand for adequately qualified people capable of managing the logistics systems and supply chains holistically and sustainably to avoid problems caused by unsustainable practices in mobility, transport, and supply chains. However, it is unclear whether the logistic and supply chain education of future leaders, managers, and engineers will follow SDG goals, the rise of new trends, and green technologies or lag behind. This paper pioneered a systematic approach and analyzed Middle Eastern countries regarding their sustainability integration into higher education programs related to supply chain management and logistics studies. It revealed enormous differences among countries and a lack of sustainability topics in most studied countries. Some countries are also significantly more oriented toward partial logistics challenges such as transport efficiency instead of sustainable supply chains, which are becoming critical challenges for the near future and must be accompanied by formal and life-long learning on sustainability-related topics. The circular economy and corporate social responsibility are especially neglected. It was also revealed that sustainability integration in higher education does not correlate with sustainability scores and the ranking of countries within the sustainability index.
Land Use/Cover Change, Fragmentation, and Driving Factors in Nepal in the Last 25 Years
Authors: Ning Chunying , Subedi Rajan , Hao Lu
Published: April 2023

Because of the influence of climate change and human activities, an in-depth analysis of land use/cover change (LUCC) and its drivers in Nepal is important for local community forestry management and sustainable development. This paper analyzed the direction, magnitude, and rate of LUCCs and their spatial aggregation, as well as landscape fragmentation in Nepal, from 1995 to 2020 using the ESA/CCI (European Space Agency Climate Change Initiative) dataset. A total of 10 factors including population, socioeconomic development, climate factors, and forest management factors were selected to determine the dominant driving factors affecting LUCC in Nepal by Principal component analysis (PCA) and linear regression analysis. Our study showed that climate change, human activities, and forest management (e.g., community forestry) all influenced LUCC. In Nepal, land use/cover shifted among forest, shrub, grassland, and cropland from 1995 to 2020, mainly from forest to cropland. The most significant LUCC in recent decades has been caused by the expansion of cropland and urbanization. The area of coniferous and broadleaf forests decreased from 1995 to 2001 due to deforestation and forest degradation, and recovered gradually after 2001, which was attributed to the successful practice of community forestry in Nepal. Accelerated urbanization was also found in Nepal, and the significant expansion of construction land came mainly came from cropland. Land fragmentation in Nepal was severe and exhibited spatial aggregation characteristics. Human activities played a greater role in LUCC in Nepal than climate factors. The community forestry, GDP growth, and precipitation were positive driving factors for increases in forest area, while the development of the services sector and rising temperature were negative driving factors.
The Spatiotemporal Dynamic Impact Mechanism of Soil Greenhouse Gases under Precipitation Based on Environmental Law
Authors: Zhang Wei , Zhang Fang
Published: April 2023

There is a chain reaction between precipitation patterns and atmospheric greenhouse gases. Understanding the impact mechanism of the spatiotemporal dynamics of soil greenhouse gases under precipitation changes is of great significance, allowing for a more accurate assessment of soil greenhouse gas budgets under future precipitation patterns. In view of this, the research uses sensors to collect environmental sample data and gas concentration data, using Conv-LSTM to achieve data analysis. The research also introduces the kernel DM model to optimize the gas distribution modeling problem. Compared to manual periodic monitoring or gas monitoring using a single mobile robot, the gas distribution model used in this study is innovative. The innovation lies in its ability to capture global gas flow trends in data sampling and predictive analysis. The results show that when soil moisture changes between 5% and 35%, the soil carbon dioxide gas flux after the water addition treatment takes a 20% soil moisture level as the inflection point, showing a trend of first increasing, and then decreasing. This indicates that the mathematical model proposed in this study is effective in collecting and analyzing environmental data.
Stakeholder Engagement in the Co-Design of Regional Bioeconomy Strategies
Authors: Szarka Nora , García Laverde Laura , Thrän Daniela , Kiyko Orest , Ilkiv Mykhailo , Moravčíková Danka , Cudlínová Eva , Lapka Miloslav , Hatvani Nóra , Koós Ákos , Luks Aleksandra , Martín Jimenez Ignacio
Published: April 2023

Increasing recognition and importance is being given to regions for their role in supporting Europe’s transformation towards a sustainable and circular bioeconomy system. Regions are often feedstock producers and can provide the proximity of regional actors along the value chain. If supported and mobilized, actors can coordinate strategic paths for regional bioeconomy development and keep value added in the region. Regional bioeconomy strategies are an important instrument to reach such a process, which implies great efforts of coordination among relevant stakeholders. In this research, we developed a guideline to establish flexible dynamic bioeconomy platforms—Regional Bioeconomy Hubs (RBHs)—that bring together bioeconomy-related stakeholders from policy, academia, industry, and society in a structured procedure (quadruple-helix context) and to establish regional bioeconomy strategies. The guideline was applied to five Central and Eastern European regions and validated in the framework of the POWER4BIO project. As a result, all regions successfully applied the guideline, established their RBH, and developed a regional bioeconomy strategy or recommendations for the development of such a strategy.
Co-Application of Sewage Sludge, Chinese Medicinal Herbal Residue and Biochar Attenuated Accumulation and Translocation of Antibiotics in Soils and Crops
Authors: Pan Min , Lee Shing Him , Luo Liwen , Chen Xun Wen , Sham Yik Tung
Published: April 2023

Sewage sludge (SL), Chinese medicinal herbal residues (CMHRs) and the raw materials of biochar (BC) are normally treated as wastes. However, SL, CMHRs and BC are potential candidates for soil amendments. The performances of soils amended with three different proportions (5%, 10% and 20% on a dry-weight basis) of SL-BC and SL-CMHR-BC in terms of ameliorating soil properties and attenuating antibiotics in soil–plant systems were investigated with two common crop species: carrot and lettuce. The amended soils in general showed higher nutrient levels than the control soils, and particularly for the 20% SL-CMHR-BC. The soils with 10% or 20% SL-BC or SL-CMHR-BC apparently retarded the germination performances of the two crop species, but the negative effects were not noticeable after a growing period. Six target antibiotics, amoxicillin (AMX), tetracycline (TC), sulfamethazine (SMX), norfloxacin (NOR), erythromycin (ERY) and chloramphenicol (CAP), were applied for growing the crops by using irrigation water with 3 μg L−1 (IW3) and 30 μg L−1 (IW30) of each antibiotic. The amended soils led to lower levels of antibiotics in the soils and crop tissues as compared with the control, with the 20% SL-CMHR-BC soils showing the most pronounced effect. The effects of the soil amendments on the bioconcentration factor (BCF) varied, but generally with lower values in the amended soils. Both SL-BC and SL-CMHR-BC were proven in the study as potential soil amendments for alleviating the environmental dispersal and human exposure risks of different antibiotics, and specifically 20% SL-CMHR-BC.
Stakeholder Empowerment in Sustainable Rural Development Partnerships: Two Case Studies from Italy
Authors: Esengulova Nazgul , Carella Massimo Manrico , Lopolito Antonio
Published: April 2023

The funds allocated through the EU Rural Development Programme provided the engine for local stakeholders to interact, forming mixed collaboration partnerships. This paper investigates the structure of such partnerships with the aim of verifying whether (R1) there are significant differences between the various stakeholder categories in influencing the rural development process, and (R2) which categories of stakeholders are more empowered in directing the design of sustainable rural development. The study is focused on two Italian cases: the regions of Apulia and Veneto. Using a combination of SNA and nonparametric tests, the results demonstrate that the empowerment of the stakeholders followed unequal paths in the two cases; i.e., a central role is clearly played by economic associations in Apulia, while this power is more distributed between different kinds of stakeholders in the case of Veneto. Agricultural associations in Apulia play an important role in the densely connected rural development network, promoting information flow and collective action. On the other hand, the weakness of this configuration lies in the fact that the rural development agenda can receive strong pressure from the agricultural sector, pushing more sectoral strategies in turn. Private companies play a key role in Veneto’s rural development, bridging the network gaps between more clustered local groups and increasing pluralism and inclusion. However, the network is sparse and shrinking, posing challenges in terms of coordination and collective action. This kind of evaluation makes policymakers and managers aware of both the most influential and weakest actors. This is crucial to improving the effectiveness and sustainability of the project, as they can involve the most influential groups from the early stages of the design process to ensure support as well as address the needs of the lagging stakeholder categories to reinforce tacit rules, trust, accountability, and responsibilities.
Improving the Degradation Kinetics of Industrial Dyes with Chitosan/TiO2/Glycerol Films for the Sustainable Recovery of Chitosan from Waste Streams
Authors: Hoang Nhung T. Tuyet , Nguyen D. Duc
Published: April 2023

This study investigates the potential of a combined photocatalysis–adsorption approach to effectively degrade near wash yellow (NWY), a commonly used and highly persistent dye in the textile industry, notorious for its challenging treatment and removal from wastewater due to its colorfastness. A chitosan–glycerol (CTiG) film combined with titanium dioxide was examined in both batch and continuous-flow experiments under visible solar irradiation. The results show that this combination was more effective than a pure chitosan film (60%) or chitosan–glycerol film (63%), with up to 83% degradation of NWY achieved in just 60 min of visible solar irradiation. The kinetics of the film were evaluated using both pseudo-first-order and Langmuir–Hinshelwood kinetic models. The rate constant values (k, min−1) decreased with increasing NWY concentration from 20 to 80 mg/L, and k was found to be greater than twice as high under visible solar irradiation as it was in the dark. The Langmuir–Hinshelwood model’s KLH (reaction rate constant) and KL (adsorption coefficient) values were 0.029 mg/L·min and 0.019 L/mg, respectively. The optimal conditions for NWY degradation were found to be 4% TiO2 to chitosan ratio, glycerol/chitosan ratio of 40%, and a pH of 7. In the continuous-flow model, the CTiG film was submerged in an 8 L NWY solution (80 mg/L) and degraded at a rate of 22.6 mg NWY/g film under natural sunlight. This study contributes to the development of effective and sustainable methods for the degradation of dyes from textile industry wastewater.
Exploring Technical Efficiency in Water Supply Evidence from Ecuador: Do Region Location and Management Type Matter?
Authors: Cabrera Barbecho Fanny , Sarmiento Juan Pablo
Published: April 2023

The efficiency that drinking water suppliers have, is widely analyzed in the literature due to the importance of its proper diagnosis in the regulation of the sector. These regulations seek, via the reduction of inefficiencies, to counteract water access crises. This research calculates the level of input-oriented technical efficiency of Ecuador’s potable water service providers in the period 2014–2017. It analyzes its determinants, focusing on the effect of the geographic region (Highlands, Coast, and Amazon), as well as the type of management, specifically municipal departments and autonomous public enterprises. For this purpose, the semi-parametric method of data envelopment analysis (DEA) with double bootstrap is used. The results suggest that drinking water suppliers could save the inputs used while maintaining their level of production. In addition, it was found that the level of technical efficiency differs by geographic region but not by the type of management used. The natural Highlands region is more efficient compared to the Coast and Amazon region, suggesting climatic and natural resource distribution heterogeneities that induce this difference. The result by type of management shows that the advantages indicated by some literature regarding the technical, financial, and administrative autonomy of public companies may not improve efficiency compared to municipal departments.
Review on Biogeochemical Characteristics of Typical Antibiotics in Groundwater in China
Authors: Xiao Wenyu , Zhao Xiaobing , Teng Yanguo , Wu Jin , Zhang Tianyi
Published: April 2023

The problem of antibiotic contamination in the environment has attracted much attention in recent years. However, studies on antibiotic contamination in groundwater have only emerged in the last 15 years. In this study, we systematically reviewed the detection methods, distribution characteristics, risk, fate, and sources of antibiotics in groundwater in China, listed the concentrations of the main antibiotic types, and obtained the maximum concentrations by comparing the literature published in the last 10 years. The results show that 65 antibiotics were detected in groundwater in China, with sulfonamides and quinolones receiving the most attention. Antibiotic concentrations are influenced by hydrogeological conditions and seasonal variations, and the ecological risk in most areas is low to medium risk, which is relatively manageable. The highest concentrations found in most of the literatures were in the range of 10–1000 ng/L, but the maximum concentration can reach 47,444.5 ng/L, which requires extra attention. In addition, this study makes recommendations for improving groundwater monitoring surveys and protection measures to prevent the antibiotic contamination of groundwater more effectively.
Examining the Link between CSRD and FP in Korean Companies: The Moderating Effect of Company Reputation
Authors: Kodirjonova Nozimakhon , Kim Jong Dae
Published: April 2023

This study investigates two key aspects of Korean companies. First, we examine the significance of the relationship between corporate social responsibility disclosure and a company’s financial performance. Second, we explore the moderating role of company reputation in the link between corporate social responsibility disclosure and financial performance. We use data from Korean companies included in the Forbes Global 2000 list, employing a quantitative methodology and analyzing data from 66 Korean companies between 2017 and 2021. To estimate the relationship between the independent variable (corporate social responsibility disclosure) and the dependent variable (financial performance), we applied multiple regression models, using market value, sales, and net profit as control variables. Our study provides robust evidence of a positive and significant relationship between corporate social responsibility disclosure and the financial performance of Korean companies. We find that their influence is partially mediated by the company’s reputation, which serves as a signal of the firm’s ethical and social responsibility practices to stakeholders. Our results suggest that firms with a positive reputation for corporate social responsibility activities are more likely to experience enhanced financial performance, possibly due to increased stakeholder trust and loyalty, improved risk management, and enhanced access to capital.
A Reliability-Based Traffic Equilibrium Model with Boundedly Rational Travelers Considering Acceptable Arrival Thresholds
Authors: Wang Liang , Zhao Lei , Hu Xiaojian , Zhao Xinyong , Wang Huan
Published: April 2023

This paper examines the effects of boundedly rational decision characteristics on travelers’ route choice behavior. The concept of boundedly rational confidence level (BRCL) is redefined, which is the probability that a trip arrives between the acceptable earliest arrival time and the acceptable latest arrival time on the shortest travel time budget (TTB). Mathematically, the acceptable boundedly rational arrival thresholds are proposed. Then, a reliability-based boundedly rational traffic equilibrium model (R-BRTE) considering both travel time reliability and acceptable arrival thresholds is developed. Moreover, the equivalent variational inequality problem and uniqueness of solution on the proposed model are proved. A route-based solution algorithm is used to solve the proposed R-BRTE model. Numerical results present the important decision ideas of the proposed model. The results demonstrate that travelers’ bounded rationality has a great impact on their route choice behavior and network performance.
Innovation-Driven Policies, Corporate Governance Structure and Total Factor Productivity in Chinese Sports Sector: Evidence from Listed Sports Firms
Authors: Guo Ziyu , Chen Gang , Ding Yang
Published: April 2023

The sports industry, an emerging industry with low pollution and low emissions, plays an important role in the sustainable development of human society. Using 489 observations from a panel of 128 sports firms listed on the New Third Board in China from 2015 to 2020, this study investigated the effects of three different innovation-driven policies on the total factor productivity of sports firms and the moderating role of governance structure on this relationship. The results showed that high-tech enterprise tax relief was an important policy tool to promote the total factor productivity of sports enterprises, but the direct effects of government subsidies and pre-tax deduction of R&D expenses were not significant. In addition, governance structure had a positive moderating effect on the relationship between innovation-driven policies and the total factor productivity of sports firms. The positive effect of the pre-tax deduction of R&D expenses policy was more significant for sports firms with larger and more independent boards of directors. This study provides new insight into innovation policy development for the sports industry by showing that corporate governance has a significant impact on the effectiveness of innovation-driven policies. Furthermore, the findings provide practical guidance for both managers and government–industry policymakers in the sports industry.
An Empirical Study of the Influencing Factors of University–Enterprise Authentic Cooperation on Cross-Border E-Commerce Employment: The Case of Zhejiang
Authors: Fang Meiyu , Zhu Zhe
Published: April 2023

This paper investigates the positive influencing factors and the degree of influence of authentic university–enterprise cooperation on the employability of cross-border e-commerce graduates. We used the literature analysis method and Delphi method to construct 12 factors affecting employability and put forward corresponding hypotheses. We tested the data and correlation analysis by SPSS software and used structural equation modeling for parameter estimation and path coefficient measurement to construct a relationship model of the factors influencing the employability of college students by cross-border e-commerce university–enterprise cooperation. The results show that the university–enterprise authentic cooperation has positive impacts on college students’ employability in theoretical knowledge, learning, professional skills application, personal basic quality, and professional quality. With the rapid development of cross-border e-commerce, studying the factors that affect the employability of college students through university–enterprise cooperation can not only promote the further integration of industry and education but also further improve the employability of college students, thus promoting the development of social economy. Therefore, the research is of positive significance.