bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection Limits of Antibiotics in Wastewater by Real-Time UV–VIS Spectrometry at Different Optical Path Length
Authors: Li Feng , Wang Xiaodong , Yang Manzi , Zhu Ming , Chen Wei , Li Qiran , Sun Delin , Bi Xuejun , Maletskyi Zakhar , Ratnaweera Harsha
Published: December 2022

Real-time monitoring of antibiotics in hospital and pharmaceutical wastewater using ultraviolet–visible (UV–Vis) spectroscopy is considered a promising method. Although gas chromatography–mass spectrometry (GC–MS) and other methods can detect antibiotics with quite low limits of detection (LOD), they possess various limitations. UV–Vis spectroscopy combined with chemometric methods is a promising choice for monitoring antibiotics. In this study, two immersed in situ UV–Vis sensors were used to explore the relationship between absorption spectra and antibiotics and study the influence of the optical path length on the LOD. The LODs of sensor 2 using a 10 cm optical path is up to 300 times lower than that of sensor 1 using a 0.5 mm optical path. Moreover, multiple antibiotics in the wastewater were investigated in real-time manner. The absorption spectra of 70 groups of wastewater samples containing different concentrations of tetracycline, ofloxacin, and chloramphenicol were measured. The results indicate that the nine wavelengths selected by interval partial least squares (iPLS) after the second derivative pretreatment have better predictability for ofloxacin and the six wavelengths selected by competitive adaptive reweighted sampling (CARS) after the first derivative. The multi-fold cross-validation results indicate that the model has a good predictive ability.
Microstructure and Magnetic Properties Dependence on the Sputtering Power and Deposition Time of TbDyFe Thin Films Integrated on Single-Crystal Diamond Substrate
Authors: Lv Zhenfei , Shen Xiulin , Guo Jinxuan , Cao Yukun , Lan Chong , Ke Yanghui , Yang Yixian , Qi Junyi
Published: December 2022

As giant magnetostrictive material, TbDyFe is regarded as a promising choice for magnetic sensing due to its excellent sensitivity to changes in magnetic fields. To satisfy the requirements of high sensitivity and the stability of magnetic sensors, TbDyFe thin films were successfully deposited on single-crystal diamond (SCD) substrate with a Young’s modulus over 1000 GPa and an ultra-stable performance by radio-frequency magnetron sputtering at room temperature. The sputtering power and deposition time effects of TbDyFe thin films on phase composition, microstructure, and magnetic properties were investigated. Amorphous TbDyFe thin films were achieved under various conditions of sputtering power and deposition time. TbDyFe films appeared as an obvious boundary to SCD substrate as sputtering power exceeded 100 W and deposition time exceeded 2 h, and the thickness of the films was basically linear with the sputtering power and deposition time based on a scanning electron microscope (SEM). The film roughness ranged from 0.15 nm to 0.35 nm, which was measured by an atomic force microscope (AFM). The TbDyFe film prepared under a sputtering power of 100 W and a deposition time of 3 h possessed the coercivity of 48 Oe and a remanence ratio of 0.53, with a giant magnetostriction and Young’s modulus effect, suggesting attractive magnetic sensitivity. The realization of TbDyFe/SCD magnetic material demonstrates a foreseeable potential in the application of high-performance sensors.
Concentrated Stream Data Processing for Vegetation Coverage Monitoring and Recommendation against Rock Desertification
Authors: Lu Guanyao
Published: December 2022

The vegetation covering regions is confined due to deforestation, mining industries, and environmental factors. The intensified deforestation and industrial development processes impact the vegetation coverage and fail to meet the food demands. Therefore, accurate monitoring of such regions aids in preventing adversary processes and their plant extinction. The monitoring process requires accurate data collection and analysis to identify the root cause that can be due to human/climatic/environmental changes. This article introduces a concentrated stream data processing method (CSDPM) assisted by an extreme learning paradigm. The different causes are analyzed using the extracted features in different learning perceptron layers. In this learning, the accumulated data is analyzed for similar features and trained for the consecutive or lagging input data streams. The monitoring process concluded with the learning output by classifying the plant extinction reason. Therefore, the identified reason is addressed through official policies with new recommendations or alternate vegetation improvements. More specifically, the data concentrated towards deforestation are the fundamental data required for feature matching. The features are initially trained from the existing datasets and previously acquired data from the converted landscapes. This proposed method is analyzed using the metrics analysis rate, analysis time, recommendation rate, and complexity.
Creating Transformation: South African Jews in Australia
Authors: Rutland Suzanne D.
Published: December 2022

Since the 1960s Australian Jewry has doubled in size to 117,000. This increase has been due to migration rather than natural increase with the main migration groups being South Africans, Russians, and Israelis. Of the three, the South Africans have had the most significant impact on Australian Jewry—one could argue that this has been transformative in Sydney and Perth. They have contributed to the religious and educational life of the communities as well as assuming significant community leadership roles in all the major Jewish Centres where they settled. This results from their strong Jewish identity. A comparative study undertaken by Rutland and Gariano in 2004–2005 demonstrated that each specific migrant group came from a different past with a different Jewish form of identification, the diachronic axis, which impacted on their integration into Jewish life in Australia, the synchronic axis as proposed by Sagi in 2016. The South Africans identified Jewishly in a traditional religious manner. This article will argue that this was an outcome of the South African context during the apartheid period, and that, with their stronger Jewish identity and support for the Jewish-day- school movement, they not only integrated into the new Australian-Jewish context; they also changed that context.
Etna Output Rate during the Last Decade (2011–2022): Insights for Hazard Assessment
Authors: Calvari Sonia , Nunnari Giuseppe
Published: December 2022

During the last two decades, the Etna volcano has undergone several sequences of lava fountaining (LF) events that have had a major impact on road conditions, infrastructure and the local population. In this paper, we consider the LF episodes occurring between 2011 and 2022, calculating their erupted volumes using the images recorded by the monitoring thermal cameras and applying a manual procedure and a dedicated software to determine the lava fountain height over time, which is necessary to obtain the erupted volume. The comparison between the results indicates the two procedures match quite well, the main differences occurring when the visibility is poor and data are interpolated. With the aim of providing insights for hazard assessment, we have fitted some probabilistic models of both the LF inter-event times and the erupted volumes of pyroclastic material. In more detail, we have tested power-law distributions against log-normal, Weibull, generalised Pareto and log-logistic. Results show that the power-law distribution is the most likely among the alternatives. This implies the lack of characteristic scales for both the inter-event time and the pyroclastic volume, which means that we have no indication as to when a new episode of LF will occur and/or how much material will be erupted. What we can reasonably say is only that short inter-event times are more frequent than long inter-event times, and that LF characterised by small volumes are more frequent than LF with high volumes. However, if the hypothesis that magma accumulates on Etna at a rate of about 0.8 m3s−1 holds, the material accumulated in the source region from the beginning of the observation period (2011) to the present (2022) has already been ejected. In simple terms, there is no accumulated magma in the shallow storage that is prone to be erupted in the near future.
Research on Self-Noise Suppression of Marine Acoustic Sensor Arrays
Authors: Tan Haoyu , Liu Guochang , Li Haoxuan , Zhang Guojun , Cui Jiangong , Yang Yuhua , He Changde , Jia Licheng , Zhang Wendong , Wang Renxin
Published: December 2022

Marine acoustic sensors can detect underwater acoustic information. The cilium micro-electro-mechanical system (MEMS) vector hydrophone (CVH) is the core component of the ocean noise measurement system. The performance of the CVH, especially its self-noise, has received widespread attention. In this paper, we propose a solution to improve the performance of the CVH using an array to detect environmental noise in a complex deep-water environment. We analyzed the self-noise source of the CVH and the noise suppression principle of the four-unit MEMS vector hydrophone (FUVH). In addition, we designed the pre-circuit of the FUVH, completed the cross-beam structure by the MEMS processing, and packaged a FUVH. Then, we tested the performance of a packaged FUVH. Finally, the experimental results show that the FUVH reduces the self-noise voltage power spectrum by 6 dB compared to the CVH structure. The FUVH achieves better linearity at low frequencies without reducing the bandwidth and sensitivity. In addition, it minimizes the equivalent self-noise levels by 5.18 and 5.14 dB in the X and Y channels, respectively.
An Object- and Shapelet-Based Method for Mapping Planted Forest Dynamics from Landsat Time Series
Authors: Xue Xiaojing , Wei Caiyong , Yang Qin , Tian Lingwen , Zhu Lihong , Meng Yuanyuan , Liu Xiangnan
Published: December 2022

Large-scale afforestation in arid and semi-arid areas with fragile ecosystems for the purpose of restoring degradation and mitigating climate change has raised issues of decreased groundwater recharge and ambiguous climatic benefits. An accurate planted forest mapping method is necessary to explore the impacts of afforestation expansion on fragile ecosystems. However, distinguishing planted forests from natural forests using remote sensing technology is not a trivial task due to their strong spectral similarities, even when assisted by phenological variables. In this study, we developed an object- and shapelet-based (OASB) method for mapping the planted forests of the Ningxia Hui Autonomous Region (NHAR), China in 2020 and for tracing the planting years between 1991 and 2020. The novel method consists of two components: (1) a simple non-iterative clustering to yield homogenous objects for building an improved time series; (2) a shapelet-based classification to distinguish the planted forests from the natural forests and to estimate the planting year, by detecting the temporal characteristics representing the planting activities. The created map accurately depicted the planted forests of the NHAR in 2020, with an overall accuracy of 87.3% (Kappa = 0.82). The area of the planted forest was counted as 0.56 million ha, accounting for 67% of the total forest area. Additionally, the planting year calendar (RMSE = 2.46 years) illustrated that the establishment of the planted forests matched the implemented ecological restoration initiatives over the past decades. Overall, the OASB has great potential for mapping the planted forests in the NHAR or other arid and semi-arid regions, and the map products derived from this method are conducive to evaluating forestry eco-engineering projects and facilitating the sustainable development of forest ecosystems.
Regulation of Evapotranspiration in Different Precipitation Zones and Its Application in High-Temperature and Drought Monitoring
Authors: Wang Lijuan , Guo Ni , Yue Ping , Hu Die , Sha Sha , Wang Xiaoping
Published: December 2022

When drought occurs in different regions, evapotranspiration (ET) changes differently with the process of drought. To achieve an accurate monitoring of large-scale drought using remote sensing, it is particularly necessary to clarify the temporal and spatial characteristics of ET changes with soil water content (SWC). Firstly, based on the measured data, combined with the artificial intelligence particle swarm optimization (PSO) algorithm, an empirical model of ET retrieval by FY–4A satellite data was established and the spatial–temporal characteristics of ET changes with SWC were further analyzed. Lastly, different ET regulation regions were distinguished to achieve the remote sensing monitoring of large-scale drought based on SWC. The main results are as follows: (1) The correlation coefficient between the ET estimated by the empirical model and the measured value was 0.48 and the root mean square error was 24 W·m−2. (2) In the areas with extreme water shortage, water limits the conversion rate of net radiation (Rn) to ET (ECR) and surpasses Rn to become the determinative factor of ET. (3) In extreme arid areas, ET has a significant positive correlation with WVP and SWC. In other precipitation areas, ET has a significant linear correlation with WVP, but the slope of the linear fitting line is different for precipitation. The relationship between ET and SWC is more complex. In areas with precipitation exceeding 800 mm, the correlation between SWC and ET is not significant. In areas with precipitation between 200 mm and 800 mm or in alpine regions, SWC and ET have a quadratic relationship. (4) ECR has quadratic correlations with WVP and SWC, and ECR reaches the maximum when WVP = 0.182 kPa and SWC = 0.217 m3∙m−3. ET may be inhibited for water shortage or water supersaturation. (5) In areas where SWC determines ET, the ET stress index (ESI) is inversely proportional to SWC, and in areas where heat affects ET, the ESI is directly proportional to SWC. Therefore, for the accurate monitoring of large-scale drought, various drought monitoring criteria should be determined in different areas and periods, considering information on precipitation, the underlying surface type, and digital elevation.
Considerations and Challenges for Real-World Deployment of an Acoustic-Based COVID-19 Screening System
Authors: Grant Drew , McLane Ian , Rennoll Valerie , West James
Published: December 2022

Coronavirus disease 2019 (COVID-19) has led to countless deaths and widespread global disruptions. Acoustic-based artificial intelligence (AI) tools could provide a simple, scalable, and prompt method to screen for COVID-19 using easily acquirable physiological sounds. These systems have been demonstrated previously and have shown promise but lack robust analysis of their deployment in real-world settings when faced with diverse recording equipment, noise environments, and test subjects. The primary aim of this work is to begin to understand the impacts of these real-world deployment challenges on the system performance. Using Mel-Frequency Cepstral Coefficients (MFCC) and RelAtive SpecTrAl-Perceptual Linear Prediction (RASTA-PLP) features extracted from cough, speech, and breathing sounds in a crowdsourced dataset, we present a baseline classification system that obtains an average receiver operating characteristic area under the curve (AUC-ROC) of 0.77 when discriminating between COVID-19 and non-COVID subjects. The classifier performance is then evaluated on four additional datasets, resulting in performance variations between 0.64 and 0.87 AUC-ROC, depending on the sound type. By analyzing subsets of the available recordings, it is noted that the system performance degrades with certain recording devices, noise contamination, and with symptom status. Furthermore, performance degrades when a uniform classification threshold from the training data is subsequently used across all datasets. However, the system performance is robust to confounding factors, such as gender, age group, and the presence of other respiratory conditions. Finally, when analyzing multiple speech recordings from the same subjects, the system achieves promising performance with an AUC-ROC of 0.78, though the classification does appear to be impacted by natural speech variations. Overall, the proposed system, and by extension other acoustic-based diagnostic aids in the literature, could provide comparable accuracy to rapid antigen testing but significant deployment challenges need to be understood and addressed prior to clinical use.
A Pilot Study on the Inter-Operator Reproducibility of a Wireless Sensors-Based System for Quantifying Gait Asymmetries in Horses
Authors: Timmerman Iris , Macaire Claire , Hanne-Poujade Sandrine , Bertoni Lélia , Martin Pauline , Marin Frédéric , Chateau Henry
Published: December 2022

Repeatability and reproducibility of any measuring system must be evaluated to assess possible limitations for its use. The objective of this study was to establish the repeatability and the inter-operator reproducibility of a sensors-based system (EQUISYM®) for quantifying gait asymmetries in horses.. Seven wireless IMUs were placed on the head, the withers, the pelvis, and the 4 cannon bones on three horses, by four different operators, four times on each horse, which led to a total of 48 repetitions randomly assigned. Data were collected along three consecutive days and analysed to calculate total variance, standard deviation and the variance attributable to the operator on multiple asymmetry variables. Maximal percentage of variance due to the operator (calculated out of the total variance) was 5.3% and was related to the sensor placed on the head. The results suggest a good reproducibility of IMU-based gait analysis systems for different operators repositioning the system and repeating the same measurements at a succession of time intervals. Future studies will be useful to confirm that inter-operator reproducibility remains valid in larger groups and on horses with different degrees of locomotor asymmetry.
A Comprehensive Review on Photoacoustic-Based Devices for Biomedical Applications
Authors: Barbosa Rita Clarisse Silva , Mendes Paulo M.
Published: December 2022

The photoacoustic effect is an emerging technology that has sparked significant interest in the research field since an acoustic wave can be produced simply by the incidence of light on a material or tissue. This phenomenon has been extensively investigated, not only to perform photoacoustic imaging but also to develop highly miniaturized ultrasound probes that can provide biologically meaningful information. Therefore, this review aims to outline the materials and their fabrication process that can be employed as photoacoustic targets, both biological and non-biological, and report the main components’ features to achieve a certain performance. When designing a device, it is of utmost importance to model it at an early stage for a deeper understanding and to ease the optimization process. As such, throughout this article, the different methods already implemented to model the photoacoustic effect are introduced, as well as the advantages and drawbacks inherent in each approach. However, some remaining challenges are still faced when developing such a system regarding its fabrication, modeling, and characterization, which are also discussed.
Digital-Twin-Assisted Edge-Computing Resource Allocation Based on the Whale Optimization Algorithm
Authors: Qiu Shaoming , Zhao Jiancheng , Lv Yana , Dai Jikun , Chen Fen , Wang Yahui , Li Ao
Published: December 2022

With the rapid increase of smart Internet of Things (IoT) devices, edge networks generate a large number of computing tasks, which require edge-computing resource devices to complete the calculations. However, unreasonable edge-computing resource allocation suffers from high-power consumption and resource waste. Therefore, when user tasks are offloaded to the edge-computing system, reasonable resource allocation is an important issue. Thus, this paper proposes a digital-twin-(DT)-assisted edge-computing resource-allocation model and establishes a joint-optimization function of power consumption, delay, and unbalanced resource-allocation rate. Then, we develop a solution based on the improved whale optimization scheme. Specifically, we propose an improved whale optimization algorithm and design a greedy initialization strategy to improve the convergence speed for the DT-assisted edge-computing resource-allocation problem. Additionally, we redesign the whale search strategy to improve the allocation results. Several simulation experiments demonstrate that the improved whale optimization algorithm reduces the resource allocation and allocation objective function value, the power consumption, and the average resource allocation imbalance rate by 12.6%, 15.2%, and 15.6%, respectively. Overall, the power consumption with the assistance of the DT is reduced to 89.6% of the power required without DT assistance, thus, improving the efficiency of the edge-computing resource allocation.
Temporal Dashboard Gaze Variance (TDGV) Changes for Measuring Cognitive Distraction While Driving
Authors: Marx Cyril , Kalayci Elem Güzel , Moertl Peter
Published: December 2022

A difficult challenge for today’s driver monitoring systems is the detection of cognitive distraction. The present research presents the development of a theory-driven approach for cognitive distraction detection during manual driving based on temporal control theories. It is based solely on changes in the temporal variance of driving-relevant gaze behavior, such as gazes onto the dashboard (TDGV). Validation of the detection method happened in a field and in a simulator study by letting participants drive, alternating with and without a secondary task inducing external cognitive distraction (auditory continuous performance task). The general accuracy of the distraction detection method varies between 68% and 81% based on the quality of an individual prerecorded baseline measurement. As a theory-driven system, it represents not only a step towards a sophisticated cognitive distraction detection method, but also explains that changes in temporal dashboard gaze variance (TDGV) are a useful behavioral indicator for detecting cognitive distraction.
Reduction of Crosstalk Errors in a Surface Encoder Having a Long Z-Directional Measuring Range
Authors: Hong Yifan , Sato Ryo , Shimizu Yuki , Matsukuma Hiraku , Shimizu Hiroki , Gao Wei
Published: December 2022

A modified two-axis surface encoder is proposed to separately measure both the in-plane displacement and the Z-directional out-of-plane displacement with minor crosstalk errors. The surface encoder is composed of a scale grating and a small-sized sensor head. In the modified surface encoder, the measurement laser beam from the sensor head is designed to be projected onto the scale grating at a right angle. For measurement of the X- and Y-directional in-plane scale displacement, the positive and negative first-order diffracted beams from the scale grating are superimposed on each other in the sensor head, producing interference signals. On the other hand, the Z-directional out-of-plane scale displacement is measured based on the principle of a Michelson-type interferometer. To avoid the influence of reflection from the middle area of the transparent grating, which causes periodic crosstalk errors in the previous research, a specially fabricated transparent grating with a hole in the middle is employed in the newly designed optical system. A prototype sensor head is constructed, and basic performances of the modified surface encoder are tested by experiments.
Investigating Cardiorespiratory Interaction Using Ballistocardiography and Seismocardiography—A Narrative Review
Authors: Balali Paniz , Rabineau Jeremy , Hossein Amin , Tordeur Cyril , Debeir Olivier , van de Borne Philippe
Published: December 2022

Ballistocardiography (BCG) and seismocardiography (SCG) are non-invasive techniques used to record the micromovements induced by cardiovascular activity at the body’s center of mass and on the chest, respectively. Since their inception, their potential for evaluating cardiovascular health has been studied. However, both BCG and SCG are impacted by respiration, leading to a periodic modulation of these signals. As a result, data processing algorithms have been developed to exclude the respiratory signals, or recording protocols have been designed to limit the respiratory bias. Reviewing the present status of the literature reveals an increasing interest in applying these techniques to extract respiratory information, as well as cardiac information. The possibility of simultaneous monitoring of respiratory and cardiovascular signals via BCG or SCG enables the monitoring of vital signs during activities that require considerable mental concentration, in extreme environments, or during sleep, where data acquisition must occur without introducing recording bias due to irritating monitoring equipment. This work aims to provide a theoretical and practical overview of cardiopulmonary interaction based on BCG and SCG signals. It covers the recent improvements in extracting respiratory signals, computing markers of the cardiorespiratory interaction with practical applications, and investigating sleep breathing disorders, as well as a comparison of different sensors used for these applications. According to the results of this review, recent studies have mainly concentrated on a few domains, especially sleep studies and heart rate variability computation. Even in those instances, the study population is not always large or diversified. Furthermore, BCG and SCG are prone to movement artifacts and are relatively subject dependent. However, the growing tendency toward artificial intelligence may help achieve a more accurate and efficient diagnosis. These encouraging results bring hope that, in the near future, such compact, lightweight BCG and SCG devices will offer a good proxy for the gold standard methods for assessing cardiorespiratory function, with the added benefit of being able to perform measurements in real-world situations, outside of the clinic, and thus decrease costs and time.
A Denoising and Fourier Transformation-Based Spectrograms in ECG Classification Using Convolutional Neural Network
Authors: Safdar Muhammad Farhan , Nowak Robert Marek , Pałka Piotr
Published: December 2022

The non-invasive electrocardiogram (ECG) signals are useful in heart condition assessment and are found helpful in diagnosing cardiac diseases. However, traditional ways, i.e., a medical consultation required effort, knowledge, and time to interpret the ECG signals due to the large amount of data and complexity. Neural networks have been shown to be efficient recently in interpreting the biomedical signals including ECG and EEG. The novelty of the proposed work is using spectrograms instead of raw signals. Spectrograms could be easily reduced by eliminating frequencies with no ECG information. Moreover, spectrogram calculation is time-efficient through short-time Fourier transformation (STFT) which allowed to present reduced data with well-distinguishable form to convolutional neural network (CNN). The data reduction was performed through frequency filtration by taking a specific cutoff value. These steps makes architecture of the CNN model simple which showed high accuracy. The proposed approach reduced memory usage and computational power through not using complex CNN models. A large publicly available PTB-XL dataset was utilized, and two datasets were prepared, i.e., spectrograms and raw signals for binary classification. The highest accuracy of 99.06% was achieved by the proposed approach, which reflects spectrograms are better than the raw signals for ECG classification. Further, up- and down-sampling of the signals were also performed at various sampling rates and accuracies were attained.
A Hybrid Rule-Based and Data-Driven Approach to Illegal Transshipment Identification with Interpretable Behavior Features
Authors: Deng Lei , Niu Yuchen , Jia Limin , Liu Wen , Zang Yu
Published: December 2022

Illegal transshipment of maritime ships is usually closely related to illegal activities such as smuggling, human trafficking, piracy plunder, and illegal fishing. Intelligent identification of illegal transshipment has become an important technical means to ensure the safety of maritime transport. However, due to different geographical environments, legal policies and regulatory requirements in each sea area, there are differences in the movement characteristics and geographical distribution of illegal transshipment behavior in different time and space. Moreover, in areas with dense traffic flow, normal navigation behavior can easily be identified as illegal transshipment, resulting in a high rate of misidentification. This paper proposes a hybrid rule-based and data-driven approach to solve the problem of missing identification in fixed threshold methods and introduces a traffic density feature to reduce the misidentification rate in dense traffic areas. The method is both interpretable and adaptable through unsupervised clustering to get suitable threshold distribution combination for regulatory sea areas. The evaluation results in two different sea areas show that the proposed method is applicable. Compared with other widely used identification methods, this method identifies more illegal transshipment events, which are highly suspicious, and gives warning much earlier. The proposed method can even filter out misidentification events from compared methods’ results, which account for more than half of the total number.
‘Finding My Own Way’: Mobilization of Cultural Capital through Migrant Organizations in Germany
Authors: Luft Niklas , Wallmeyer Paula , Barglowski Karolina , Bonfert Lisa
Published: December 2022

Migrant organizations (MOs), as associations that are founded, managed, and led by people with migration biographies, have recently emerged as facilitators of social protection interventions. This article is devoted to this barely debated issue of MOs in the field of social protection, by emphasizing their role in facilitating the mobilization and access to cultural capital as an important determinant of protection and wellbeing of people with migration biographies. Specifically, we study how MOs promote the formation and mobilization of skills and resources to be used in different fields, in particular in the education and labor markets. We find that MOs facilitate various occasions for their members to generate migration-specific cultural capital, predominantly in the field of education and language skills. MOs also promote the creation and institutionalization of cultural capital on the labor market. In addition, our results show that people with a migration background appreciate their participation in migrants’ organizations, because they allow them to pursue their own projects and find their own way through the different phases of migration and settlement, in often challenging environments.
Physico-Chemical Soil Properties Affected by Invasive Plants in Southwest Germany (Rhineland-Palatinate)—A Case Study
Authors: Jamin Jellian , Diehl Dörte , Meyer Michele , David Jan , Schaumann Gabriele Ellen , Buchmann Christian
Published: December 2022

The invasive plant species Impatiens glandulifera native to Asia mainly occupies European riparian ecosystems. It is still unclear to which extent this invasive plant can alter physico-chemical soil properties in terms of carbon turnover, microstructural stability and soil hydraulic properties threatening native plant species, here represented by Urtica dioica. Soil samples were collected from three sites in the Palatine forest near the river Queich, including bare soil (Control), or soil within dense stands of either I. glandulifera or U. dioica with similar texture. Basic soil parameters including SOM content and quality were analyzed. SOM is known to impact soil microstructural stability and soil hydraulic properties. We therefore assessed microstructural stability, the pore size distribution and the wettability. Our results implied more recalcitrant SOM for soil colonized by U. dioca including a lower pH. For soil colonized by I. glandulifera less recalcitrant SOM was detected indicating a reduced degradation which is likely given due to lignin as a predominant component in the plant biomass of I. glandulifera Soil microstructural stability was higher for soil colonized by the invader showing a slight increase with soil depth, due to higher SOM content. All in all, this case study indicates that I. glandulifera most likely affects the soil microbiome while basic soil parameters, soil hydraulic properties, wettability and soil microstructural stability showed no significant effect.
Investigation of E-27 and Candidate Countries’ Lifelong Learning, R&D–Innovation Performances and Gross Domestic Product by Multidimensional Scaling Analysis
Authors: Bulut Mustafa , Serçek Sadık , Demir Şeyhmus
Published: December 2022

Vocational and technical education, which is offered in the quality required by the era, plays a major role in the growth of economies and the development of societies by raising entrepreneurs with R&D, P&D, and innovation awareness, as well as being a means of raising a productive workforce in a systematic and planned way. The lifelong learning journey also offers a great contribution to this process. The aim of this study is to evaluate the effects of these factors on the economies of countries by comparing the lifelong learning, entrepreneurship, and innovation performances of countries with their per capita gross domestic product within the scope of both the data in the Global Innovation Index (GII) report and the data in the European Innovation Index scoring table. Ideas produced by using information-intensive innovative technologies and the products that emerge with the realization of these ideas contribute to economic growth by strengthening the competitiveness and economic structure of countries, thus, increasing living standards and increasing welfare. In this respect, it is important to measure and evaluate the lifelong learning, R&D, and innovation performances of countries. A multidimensional scaling analysis method was used in the study. In the analysis of data and documents obtained, it has been found that the countries that construct and carry out their vocational education and training activities according to the realities and needs of today’s world, have high R&D, innovation, and lifelong learning performances. It has been seen that the value added created in this way is also high and that has a decisive effect on their economic growth.
Overcoming Risk Aversion Regarding Energy Efficiency Practices through Mimetic Pressure and Financial Slack: Findings from the Moroccan Manufacturing Sector
Authors: Bensouda Mehdi , Benali Mimoun
Published: December 2022

The Moroccan manufacturing sector consumes 24% of the country’s total energy production. Morocco is dealing with energy challenges related to its growing energy consumption, which has made energy efficiency a national priority. In this study, we construct a model that includes mimetic pressure and financial slack as drivers to reduce the intensity of risk aversion regarding electrical energy efficiency practices within companies. Our research model was empirically examined using survey data gathered from 193 manufacturing companies located in four Moroccan regions. Results show that risk aversion is negatively related to energy efficiency practices. Both mimetic pressure and financial slack are positively related to energy efficiency practices. Both mimetic pressure and financial slack reduce risk aversion. Mimetic pressure dampens the negative relationship between risk aversion and energy efficiency practices, while financial slack does not dampen the negative relationship between risk aversion and energy efficiency practices. This study shows the importance of mimetic pressure in reducing risk aversion regarding energy efficiency practices. Therefore, policymakers should publicize in the media companies that have gained from the adoption of energy efficiency practices and establish an award system of best energy efficiency practices in each industry. This study is an extension of the previous literature since we found that financial slack decreases the level of risk aversion, but this does not always translate into energy efficiency practices, as the previous literature assumes.
The Impact of Farmland Tenure Security on China’s Agricultural Production Efficiency: A Perspective of Agricultural Production Factors
Authors: Zhang Juan , Chen Qin
Published: December 2022

Improving agricultural production efficiency is an effective means to ensure food security and promote agricultural sustainable development in China. Stable agricultural land property rights help optimize the allocation of production factors and improve production efficiency, and it is of great practical significance to study the influence of farmland tenure security on agricultural production efficiency. Therefore, this research utilizes the 2018 data of the China Labor Dynamics Survey (CLDS) to analyze the influence of farmland tenure security on agricultural production efficiency and its internal transmission mechanism under the background of agricultural land ownership confirmation. The results show that the enhancement of farmland tenure security not only directly improves agricultural production efficiency, but also indirectly affects agricultural production efficiency through the intermediary variable of agricultural investment. Moreover, it also shows that farmland tenure security has heterogeneity effects on different farmer regions and production modes and can significantly improve the production efficiency of farmers in plain and hilly areas who adopt fully mechanized and partially mechanized farming. We suggest that policymakers should also deepen the reform of the rural factor market, develop diversified rural financial institutions, actively promote the involvement of small farmers in the public sector economy, and improve the service level of agricultural machinery in order to guide the development of the tertiary industry in non-plain areas and to reduce the land endowment effect of farmers.
Measuring Financial Sustainability and Social Adequacy of the Italian NDC Pension System under the COVID-19 Pandemic
Authors: Fratoni Lorenzo , Levantesi Susanna , Menzietti Massimiliano
Published: December 2022

The COVID-19 pandemic is presently influencing the financial sustainability and the social adequacy of public pension schemes. In this paper, we measure the effects of COVID-19 on the Italian public pension system by introducing a deterministic shock due to the pandemic in the evolution of the variables mainly involved in the system’s evaluation. These variables, namely the unemployment rate, wage growth rate, inflation rate, and mortality rates, are modeled in a stochastic framework. Our results show that COVID-19 worsens the financial sustainability of the pension system in the short–medium term, while it does not appreciably affect social adequacy in the medium term. The Italian pension system already showed a social adequacy problem before 2020, which the pandemic does not further deteriorate essentially.
Social and Environmental Regulations and Corporate Innovation
Authors: Cao Zhi , Mu Yinping
Published: December 2022

In this study, we investigate the effects of mandatory social and environmental regulations (MSER) on firm innovation. In 2008, the Shanghai and Shenzhen Stock Exchange in China published regulations that mandate some public firms to disclose their social and environmental governance information in their annual reports. As the MSER apply only to selected firms, this provides an ideal setting for us to observe the effects of MSER on firm innovation. Using a difference-in-differences with propensity-score-matching methodology, we find that the treatment firms experience a significant increase in innovation in terms of the number of total patents and invention patents. More importantly, we further explore three possible mechanisms underlying this association, that is, the corporate social responsibility (CSR)-improving effect, information-disclosing effect, and market-reaction effect, and demonstrate that this positive relationship is mainly driven by the CSR-improving effect and market-reaction effect, manifesting in an improvement in CSR performance and a decline in transient institutional investors for the treatment firms, respectively.
Formulating an Excise Duty on Plastic: A Strategy to Manage Marine Plastic Waste in Indonesia
Authors: Irianto Okto , Mizuno Kosuke , Burhanuddin Safri , Triaswati Ninasapti
Published: December 2022

Plastic excise duty is one of the programs prescribed to combat the marine waste problem in Indonesia. This article presents an insight into the formulation of the government regulations needed to implement plastic excise duty. Initially planned to be implemented by 2018, the program is still in the process almost five years later. This article aims to identify the core issues discussed in the process, the stakeholders playing the central role, and their perspectives by interviewing key informants involved in the inter-ministerial committee. This research identified four ministries as definitive stakeholders as representatives of fiscal, industrial, and environmental groups. These groups have distinct interests in five core issues discussed during the negotiation process: the urgency of implementing an excise duty, its goals, scope of implementation, rate of tariff, and the settings for earmarking. This research found that environmental consideration was the central premise during the interministerial negotiation. However, the government’s hesitation to immediately implement an excise on plastic bags shows that currently, the government tends to prioritize economic considerations
Building a Low-Carbon Community: Influencing Factors of Residents’ Idle Resource-Sharing Behaviors
Authors: Yan Li , Dou Xiao
Published: December 2022

Promoting the sharing of idle resources to community residents is a potential means to building a low-carbon community. This study examined three communities with different attributes (college/university, middle and high income, and the elderly). An extended hypothesis model was constructed based on the theory of planned behavior. The influencing factors of community residents facing idle resource-sharing services were explored. Based on the equal sampling method, 100 questionnaires were randomly distributed in each community to verify the validity of the hypothesis model. The results show that residents’ attitudes, subjective behavioral norms, perceived behavioral control, service expectations, and environmental motivations positively influence residents’ behavioral intention to share their idle resources. The residents’ service expectations for idle resource-sharing are the most critical. Moreover, in terms of community attributes, its attitudes, subjective behavioral norms, and perceived behavioral control significantly influence residents’ behavioral intention to share idle resources. Specifically, the attitudes in the middle- and high-income community have opposite effects on residents from the attitudes in the college/university community and the elderly community. The hypothesis model proposed in this study provides a reference for building a low-carbon community from the perspective of residents’ restriction of resource-sharing.
Rural Tourism—Viable Alternatives for Preserving Local Specificity and Sustainable Socio-Economic Development: Case Study—“Valley of the Kings” (Gurghiului Valley, Mureș County, Romania)
Authors: Crăciun Andreea M. , Dezsi Ștefan , Pop Florin , Cecilia Pintea
Published: December 2022

Rural tourism, defined as a form of local initiative tourism, has at its forefront the involvement of the local community, who contribute significantly to the affirmation and promotion of this type of tourism. In order to be able to speak of the practice of this type of tourism in a given geographical area, it is first necessary to highlight the existence of a tourist heritage, both natural and anthropic, which identifies itself with the authentic character of the area, satisfying the need of the tourist to discover activities and tourist attractions with local specificity. The purpose of this research is to investigate the role of socio-economic and cultural aspects in the sustainable development of tourism in the Gurghiului Valley. The present study also aims to highlight the role of local entrepreneurs in the process of economic development in the area by means of new practices and sustainable approaches; this is based on efficient capitalization of the natural and anthropic tourism heritage of the area, defined by elements of authenticity. The methodology applied in this work is based on the study of specialized literature, along with case study on tourist activity in rural tourism. The research carried out is based on analysis of data from official sources of tourist data (the National Tourism Agency (hereafter NTA) and the National Institute of Statistics (hereafter NIS)), as well as research carried out in the field to see if there are discrepancies between what these two aforementioned official sources provide and the reality on the ground. Our research finally revealed the fact that Gurghiului Valley officially entered into the tourist landscape in 1990 through the lens of the Lăpușna student and preschool camp, and rural tourism has been organized in the study area since 2005. At the same time, research has shown that there is currently a need for much greater involvement and awareness both from local authorities and the resident population regarding the importance of rural tourism in the social and economic evolution of the local community.
H2O2-Enhanced As(III) Removal from Natural Waters by Fe(III) Coagulation at Neutral pH Values and Comparison with the Conventional Fe(II)-H2O2 Fenton Process
Authors: Koutzaris Stefanos , Xanthopoulou Maria , Laskaridis Asterios , Katsoyiannis Ioannis A.
Published: December 2022

Arsenic is a naturally occurring contaminant in waters, which is toxic and adversely affects human health. Therefore, treatment of water for arsenic removal is very important production of safe drinking water. Coagulation using Fe(III) salts is the most frequently applied technology for arsenic removal, but is efficient mostly for As(V) removal. As(III) removal usually requires the application of a pre-oxidation step, which is mainly conducted by chemical or biological means. In this study, we show that Fe(III) coagulation in the presence of H2O2 can be a very efficient treatment process for As(III) removal, which has been never been shown before in the literature. The results showed that addition of 8.7–43.7 mM hydrogen peroxide to Fe(III) coagulation process was able to increase the effectiveness of As(III) removal in synthetic groundwater by 15–20% providing residual concentrations well below the regulatory limit of 10 μg/L from initial As(III) concentrations of 100 μg/L, at pH 7. The enhanced coagulation process was affected by the solution pH. The removal efficiency substantially declined at alkaline pH values (pH > 8). Addition of EDTA in the absence of H2O2 had a strong inhibiting effect where the As(III) removal was almost zero when 88.38 μΜ EDTA were used. Radical quenching experiments with 50, 100 and 200 mM DMSO, methanol and 2-propanol in the H2O2-coagulation process had a slightly adverse effect on the removal efficiency. This is considered as indicative of an adsorption/oxidation of As(III) process onto or very near the surface of iron oxide particles, formed by the hydrolysis of Ferric iron ions. In practice, the results suggest that addition of H2O2 increases the As(III) removal efficiency for Fe(III) coagulation systems. This is an important finding because the pre-oxidation step can be omitted with the addition of H2O2 while treating water contaminated with As(III).