bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Metallic Iron and Ferrates in Water and Wastewater Treatment for Cr(VI) and Organic Contaminants Removal
Authors: Samiotis Georgios , Stimoniaris Adam , Ristanis Ilias , Kemmou Liana , Mavromatidou Charoula , Amanatidou Elisavet
Published: March 2023

Iron species can act as electron donors, electron acceptors or serve as a sorbent to co-precipitate contaminants. These properties, along with its relatively low cost as a material, make iron an ideal compound for environmental applications in the removal of pollutants from water and wastewater. This study assesses the use of metallic iron as a reductant for the removal of toxic Cr(VI) from aqueous solutions, as well as the use of hexavalent iron (ferrates) for the removal of organic compounds, turbidity and biological contaminants from water and wastewater. Laboratory-scale experiments show that the Cr(VI) removal efficiency of metallic iron filling materials, such as scrap iron fillings, via reduction to Cr(III) and the subsequent precipitation/filtration of aggregates can reach values over 99.0%. Moreover, the efficiency of ferrates, in situ synthesized via a low-cost Fe0/Fe0 electrochemical cell, in the removal of organic compounds, turbidity and biological contaminants from high-strength industrial wastewater, biologically treated wastewater and natural water can also reach values over 99.0%. The results showed that iron species can be applied in low-cost and environmentally friendly technologies for natural water remediation and wastewater treatment. Furthermore, the study showed that the challenge of an iron material’s surface passivation, as well as of ferrates’ procurement cost and stability, can be resolved via the application of ultrasounds and via in situ ferrate electrosynthesis.
Gender Pension Gap in EU Countries: A Between-Group Inequality Approach
Authors: Abatemarco Antonio , Lagomarsino Elena , Russolillo Maria
Published: March 2023

Pension entitlements are influenced by individual career paths and labor market conditions, which often result in gender-based disparities. Women face several challenges during their working lives, such as late entry into the labor market, the gender pay gap, discontinuous working careers, and early retirement due to family caregiving, which lead to lower pension incomes. This paper investigates the gender pension gap in nine European Union countries from 2004 to 2020. Our study adopts a non-parametric estimation strategy that utilizes additively decomposable inequality measures to provide a more informative perspective on gender inequality. We aim to demonstrate that this approach surpasses the standard gender gap in pension index in capturing between-gender inequality in societies. Employing data from the SHARE database, we find that gender inequality in the studied countries is decreasing on average, with a convergence trend observed from 2011 onwards. This study contributes to a more comprehensive understanding of the gender pension gap phenomenon, which is crucial for developing effective policy responses in a welfare perspective.
Special Issue on Advances in Industrial Robotics and Intelligent Systems
Authors: Moreira António Paulo , Neto Pedro , Vidal Félix
Published: March 2023

Robotics and intelligent systems are intricately connected, each exploring their respective capabilities and moving towards a common goal [...]
Mass Balance of the Antarctic Ice Sheet in the Early 21st Century
Authors: Yang Tian , Liang Qi , Zheng Lei , Li Teng , Chen Zhuoqi , Hui Fengming , Cheng Xiao
Published: March 2023

Mass loss from the Antarctic Ice Sheet (AIS) is an important contributor to global sea level rise. To examine the recent ice loss, we estimated the mass budget of the AIS from 2000 to 2020 using multiple ice velocity datasets, state-of-the-art ice thickness datasets, and extended surface mass balance (SMB) records. The AIS lost mass at an average rate of −89 ± 99 Gt/yr over the study period. The East Antarctic Ice Sheet (EAIS) showed a slightly positive mass balance, while the West Antarctic Ice Sheet (WAIS) experienced a significant acceleration in mass loss. The ice discharge from the AIS increased from 1792 ± 47 Gt/yr in 2000 to 1940 ± 37 Gt/yr in 2017–2020, with the increase in the discharge from the WAIS being three to four times higher than that from the EAIS. Moreover, the average mass balance for 2017–2020 was −99 ± 93 Gt/yr, slightly more negative than the average for the early 21st Century. During this recent period, the ice discharge decreased in the East Indian Ocean sector, in contrast to its rapid increase from 2000 to 2013–2017. However, the discharge in the Amundsen Sea sector still greatly increased from 2013–2017 to 2017–2020. Overall, our results are in agreement with recent mass balance estimates for the AIS based on gravimetry and altimetry. Our assessments of the recent AIS mass balance with the mass budget method (input-output method) will contribute to the understanding of ice dynamic processes and provide insights into the stability of the AIS.
MFGFNet: A Multi-Scale Remote Sensing Change Detection Network Using the Global Filter in the Frequency Domain
Authors: Yuan Shiying , Zhong Ruofei , Li Qingyang , Dong Yaxin
Published: March 2023

In traditional image processing, the Fourier transform is often used to transform an image from the spatial domain to the frequency domain, and frequency filters are designed from the perspective of the frequency domain to sharpen or blur the image. In the field of remote sensing change detection, deep learning is beginning to become a mainstream tool. However, deep learning can still refer to traditional methodological ideas. In this paper, we designed a new convolutional neural network (MFGFNet) in which multiple global filters (GFs) are used to capture more information in the frequency domain, thus sharpening the image boundaries and better preserving the edge information of the change region. In addition, in MFGFNet, we use CNNs to extract multi-scale images to enhance the effects and to better focus on information about changes in different sizes (multi-scale combination module). The multiple pairs of enhancements are fused by the difference method and then convolved and concatenated several times to obtain a better difference fusion effect (feature fusion module). In our experiments, the IOUs of our network for the LEVIR-CD, SYSU, and CDD datasets are 0.8322, 0.6780, and 0.9101, respectively, outperforming the state-of-the-art model and providing a new perspective on change detection.
Socioeconomic and Climate Effects on Changes in Wetlands in China during a Three-Decade Period of Rapid Growth
Authors: Ge Ying , Sklenička Petr , Chen Zhongbing
Published: March 2023

China has experienced dramatic economic growth and social development, especially in the period between 1978 and 2008. The biodiversity and the socioeconomic sustainability in China were under threat, and the loss of wetlands was a significant aspect of ecological deterioration in the country at that time. However, the driving factors for the loss of wetlands are not well understood, probably due to a lack of accurate country-scale data. This study analyzes the changes in China’s wetland area between 1978 and 2008 (1978, 1990, 2000, and 2008) and the interchange between different wetland types from 1990 to 2000. We select 29 socioeconomic parameters (per capita GDP, primary industry added value, secondary industry ratio, total population, arable land, pesticide use, aquatic products, railway mileage, domestic wastewater, urban sewage treatment capacity, etc.) and three meteorological parameters (annual temperature, annual precipitation, and annual sunshine) to analyze the driving forces of changes in wetlands. The factor analysis based on these parameters shows that two factors can explain 65.8% of the total variation from the data, while eight parameters can explain 59.7%. Furthermore, multiple linear regression analysis reveals that five factors are of great significance in explaining wetland change in China, which are annual temperature (p < 0.001), inland waterway mileage (p < 0.001), urban land acquisition (p = 0.01), secondary industry ratio (p = 0.014), and railway mileage (p = 0.02). In conclusion, climate change (especially temperature) and inland waterway mileage are the primary factors for changes in the wetlands in China, and other socioeconomic indicators, especially from industrial and construction factors, also play an important role in changes in wetlands during China’s rapid economic development. In order to enhance wetland conservation efforts in China, we recommend prioritizing efforts to mitigate climate change on wetlands, promoting sustainable development policies, restoring and creating wetlands in urban areas, and utilizing advanced technologies to obtain accurate data.
Assessment of Machine and Deep Learning Approaches for Fault Diagnosis in Photovoltaic Systems Using Infrared Thermography
Authors: Boubaker Sahbi , Kamel Souad , Ghazouani Nejib , Mellit Adel
Published: March 2023

Nowadays, millions of photovoltaic (PV) plants are installed around the world. Given the widespread use of PV supply systems and in order to keep these PV plants safe and to avoid power losses, they should be carefully protected, and eventual faults should be detected, classified and isolated. In this paper, different machine learning (ML) and deep learning (DL) techniques were assessed for fault detection and diagnosis of PV modules. First, a dataset of infrared thermography images of normal and failure PV modules was collected. Second, two sub-datasets were built from the original one: The first sub-dataset contained normal and faulty IRT images, while the second one comprised only faulty IRT images. The first sub-dataset was used to develop fault detection models referred to as binary classification, for which an image was classified as representing a faulty PV panel or a normal one. The second one was used to design fault diagnosis models, referred to as multi-classification, where four classes (Fault1, Fault2, Fault3 and Fault4) were examined. The investigated faults were, respectively, failure bypass diode, shading effect, short-circuited PV module and soil accumulated on the PV module. To evaluate the efficiency of the investigated models, convolution matrix including precision, recall, F1-score and accuracy were used. The results showed that the methods based on deep learning exhibited better accuracy for both binary and multiclass classification while solving the fault detection and diagnosis problem in PV modules/arrays. In fact, deep learning techniques were found to be efficient for the detection and classification of different kinds of defects with good accuracy (98.71%). Through a comparative study, it was confirmed that the DL-based approaches have outperformed those based on ML-based algorithms.
Comparison of Canopy Height Metrics from Airborne Laser Scanner and Aerial/Satellite Stereo Imagery to Assess the Growing Stock of Hemiboreal Forests
Authors: Goldbergs Grigorijs
Published: March 2023

This study compared the canopy height model (CHM) performance obtained from large-format airborne and very high-resolution satellite stereo imagery (VHRSI), with airborne laser scanning (ALS) data, for growing stock (stand volume) estimation in mature, dense Latvian hemiboreal forests. The study used growing stock data obtained by ALS-based individual tree detection as training/reference data for the image-based and ALS CHM height metrics-based growing stock estimators. The study only compared the growing stock species-specific area-based regression models which are based solely on tree/canopy height as a predictor variable applied to regular rectangular 0.25 and 1 ha plots and irregular forest stands. This study showed that ALS and image-based (IB) height metrics demonstrated comparable effectiveness in growing stock prediction in dense closed-canopy forests. The relative RMSEs did not exceed 20% of the reference mean values for all models. The best relative RMSEs achieved were 13.6% (IB) and 15.7% (ALS) for pine 0.25 ha plots; 10.3% (IB) and 12.1% (ALS) for pine 1 ha plots; 16.4% (IB) and 12.2% (ALS) for spruce 0.25 ha plots; 17.9% (IB) and 14.2% (ALS) for birch 0.25 ha plots; 15.9% (IB) and 18.9% (ALS) for black alder 0.25 ha plots. This research suggests that airborne imagery and, accordingly, image-based CHMs collected regularly can be an efficient solution for forest growing stock calculations/updates, in addition to a traditional visual forest inventory routine. However, VHRSI can be the fastest and cheapest solution for monitoring forest growing stock changes in vast and dense forestland under optimal data collection parameters.
A Novel Cipher-Based Data Encryption with Galois Field Theory
Authors: Hazzazi Mohammad Mazyad , Attuluri Sasidhar , Bassfar Zaid , Joshi Kireet
Published: March 2023

Both the act of keeping information secret and the research on how to achieve it are included in the broad category of cryptography. When people refer to “information security,” they are referring to the study and use of methods that make data transfers harder to intercept. When we talk about “information security,” this is what we have in mind. Using private keys to encrypt and decode messages is a part of this procedure. Because of its vital role in modern information theory, computer security, and engineering, cryptography is now considered to be a branch of both mathematics and computer science. Because of its mathematical properties, the Galois field may be used to encrypt and decode information, making it relevant to the subject of cryptography. The ability to encrypt and decode information is one such use. In this case, the data may be encoded as a Galois vector, and the scrambling process could include the application of mathematical operations that involve an inverse. While this method is unsafe when used on its own, it forms the foundation for secure symmetric algorithms like AES and DES when combined with other bit shuffling methods. A two-by-two encryption matrix is used to protect the two data streams, each of which contains 25 bits of binary information which is included in the proposed work. Each cell in the matrix represents an irreducible polynomial of degree 6. Fine-tuning the values of the bits that make up each of the two 25-bit binary data streams using the Discrete Cosine Transform (DCT) with the Advanced Encryption Standard (AES) Method yields two polynomials of degree 6. Optimization is carried out using the Black Widow Optimization technique is used to tune the key generation in the cryptographic processing. By doing so, we can produce two polynomials of the same degree, which was our original aim. Users may also use cryptography to look for signs of tampering, such as whether a hacker obtained unauthorized access to a patient’s medical records and made any changes to them. Cryptography also allows people to look for signs of tampering with data. Indeed, this is another use of cryptography. It also has the added value of allowing users to check for indications of data manipulation. Users may also positively identify faraway people and objects, which is especially useful for verifying a document’s authenticity since it lessens the possibility that it was fabricated. The proposed work achieves higher accuracy of 97.24%, higher throughput of 93.47%, and a minimum decryption time of 0.0047 s.
Unsupervised Learning Methods for Data-Driven Vibration-Based Structural Health Monitoring: A Review
Authors: Eltouny Kareem , Gomaa Mohamed , Liang Xiao
Published: March 2023

Structural damage detection using unsupervised learning methods has been a trending topic in the structural health monitoring (SHM) research community during the past decades. In the context of SHM, unsupervised learning methods rely only on data acquired from intact structures for training the statistical models. Consequently, they are often seen as more practical than their supervised counterpart in implementing an early-warning damage detection system in civil structures. In this article, we review publications on data-driven structural health monitoring from the last decade that relies on unsupervised learning methods with a focus on real-world application and practicality. Novelty detection using vibration data is by far the most common approach for unsupervised learning SHM and is, therefore, given more attention in this article. Following a brief introduction, we present the state-of-the-art studies in unsupervised-learning SHM, categorized by the types of used machine-learning methods. We then examine the benchmarks that are commonly used to validate unsupervised-learning SHM methods. We also discuss the main challenges and limitations in the existing literature that make it difficult to translate SHM methods from research to practical applications. Accordingly, we outline the current knowledge gaps and provide recommendations for future directions to assist researchers in developing more reliable SHM methods.
An Edge-Filtered Optical Fiber Interrogator for Thermoplastic Polymer Analysis
Authors: Backmann Vincent , Dorner Felix , Drechsler Klaus
Published: March 2023

The present paper deals with the determination of thermodynamic quantities of thermoplastic polymers by using an optical fiber interrogator. Typically, laboratory methods such as differential scanning calorimetry (DSC) or thermomechanical analysis (TMA) are a reliable state-of-the-art option for thermal polymer analysis. The related laboratory commodities for such methods are of high cost and are impractical for field applications. In this work, an edge-filter-based optical fiber interrogator, which was originally developed to detect the reflection spectrum of fiber Bragg grating sensors, is utilized for the detection of the boundary reflection intensities of the cleaved end of a standard telecommunication optical fiber (SMF28e). By means of the Fresnel equations, the temperature-dependent refractive index of thermoplastic polymer materials is measured. Demonstrated with the amorphous thermoplastic polymers polyetherimide (PEI) and polyethersulfone (PES), an alternative to DSC and TMA is presented as the glass transition temperatures and coefficients of thermal expansion are derived. A DSC alternative in the semi-crystalline polymer analysis with the absence of a crystal structure is shown as the melting temperature and cooling-rate-dependent crystallization temperatures of polyether ether ketone (PEEK) are detected. The proposed method shows that thermal thermoplastic analysis can be performed with a flexible, low-cost and multipurpose device.
Fiber Optic Temperature Sensor System Using Air-Filled Fabry–Pérot Cavity with Variable Pressure
Authors: Chowdhury Hasanur R. , Han Ming
Published: March 2023

We report a high-resolution fiber optic temperature sensor system based on an air-filled Fabry–Pérot (FP) cavity, whose spectral fringes shift due to a precise pressure variation in the cavity. The absolute temperature can be deduced from the spectral shift and the pressure variation. For fabrication, a fused-silica tube is spliced with a single-mode fiber at one end and a side-hole fiber at the other to form the FP cavity. The pressure in the cavity can be changed by passing air through the side-hole fiber, causing the spectral shift. We analyzed the effect of sensor wavelength resolution and pressure fluctuation on the temperature measurement resolution. A computer-controlled pressure system and sensor interrogation system were developed with miniaturized instruments for the system operation. Experimental results show that the sensor had a high wavelength resolution (<0.2 pm) with minimal pressure fluctuation (~0.015 kPa), resulting in high-resolution (±0.32 ℃) temperature measurement. It shows good stability from the thermal cycle testing with the maximum testing temperature reaching 800 ℃.
Quantifying States and Transitions of Emerging Postural Control for Children Not Yet Able to Sit Independently
Authors: Mellodge Patricia , Saavedra Sandra , Tran Poit Linda , Pratt Kristamarie A. , Goodworth Adam D.
Published: March 2023

Objective, quantitative postural data is limited for individuals who are non-ambulatory, especially for those who have not yet developed trunk control for sitting. There are no gold standard measurements to monitor the emergence of upright trunk control. Quantification of intermediate levels of postural control is critically needed to improve research and intervention for these individuals. Accelerometers and video were used to record postural alignment and stability for eight children with severe cerebral palsy aged 2 to 13 years, under two conditions, seated on a bench with only pelvic support and with additional thoracic support. This study developed an algorithm to classify vertical alignment and states of upright control; Stable, Wobble, Collapse, Rise and Fall from accelerometer data. Next, a Markov chain model was created to calculate a normative score for postural state and transition for each participant with each level of support. This tool allowed quantification of behaviors previously not captured in adult-based postural sway measures. Histogram and video recordings were used to confirm the output of the algorithm. Together, this tool revealed that providing external support allowed all participants: (1) to increase their time spent in the Stable state, and (2) to reduce the frequency of transitions between states. Furthermore, all participants except one showed improved state and transition scores when given external support.
Remote Sensing Low Signal-to-Noise-Ratio Target Detection Enhancement
Authors: Ma Tian J. , Anderson Robert J.
Published: March 2023

In real-time remote sensing application, frames of data are continuously flowing into the processing system. The capability of detecting objects of interest and tracking them as they move is crucial to many critical surveillance and monitoring missions. Detecting small objects using remote sensors is an ongoing, challenging problem. Since object(s) are located far away from the sensor, the target’s Signal-to-Noise-Ratio (SNR) is low. The Limit of Detection (LOD) for remote sensors is bounded by what is observable on each image frame. In this paper, we present a new method, a “Multi-frame Moving Object Detection System (MMODS)”, to detect small, low SNR objects that are beyond what a human can observe in a single video frame. This is demonstrated by using simulated data where our technology-detected objects are as small as one pixel with a targeted SNR, close to 1:1. We also demonstrate a similar improvement using live data collected with a remote camera. The MMODS technology fills a major technology gap in remote sensing surveillance applications for small target detection. Our method does not require prior knowledge about the environment, pre-labeled targets, or training data to effectively detect and track slow- and fast-moving targets, regardless of the size or the distance.
Review on Alzheimer Disease Detection Methods: Automatic Pipelines and Machine Learning Techniques
Authors: Shukla Amar , Tiwari Rajeev , Tiwari Shamik
Published: March 2023

Alzheimer’s Disease (AD) is becoming increasingly prevalent across the globe, and various diagnostic and detection methods have been developed in recent years. Several techniques are available, including Automatic Pipeline Methods and Machine Learning Methods that utilize Biomarker Methods, Fusion, and Registration for multimodality, to pre-process medical scans. The use of automated pipelines and machine learning systems has proven beneficial in accurately identifying AD and its stages, with a success rate of over 95% for single and binary class classifications. However, there are still challenges in multi-class classification, such as distinguishing between AD and MCI, as well as sub-stages of MCI. The research also emphasizes the significance of using multi-modality approaches for effective validation in detecting AD and its stages.
Contributing to SDG Targets 4.5 and 5.5 during Physical Education Sessions: The Effect of a Collective Sports Intervention on Gender Attitudes
Authors: Martínez Lucía , García-Taibo Olalla , Ferriz-Valero Alberto , Baena-Morales Salvador
Published: March 2023

In recent years, the sustainability of the planet has been undermined. Education is the basis for raising awareness and is the engine for achieving attitudinal change among citizens. In terms of the social dimension, gender inequality is increasing, with it being common among children, and co-education aims to address this. Likewise, physical activity favors education and gender issues. Therefore, studying how physical education (PE) affects gender stereotypes can be analyzed in depth. This research analyzed whether a co-educational PE intervention improved students’ gender beliefs, eliminated inequalities in universal education, and promoted women’s full participation. For this purpose, 91 primary school pupils (42 females) completed the research. The mean age was 11.5 ± 0.7 years. A quasi-experimental, pre–post study was carried out with a control group and an experimental group. The sample was distributed by convenience among the pupils, using two instruments already used in other research studies: attitudes towards gender equality among primary school pupils and data collection on the internalization of gender stereotypes. For three weeks, the experimental group carried out a didactic intervention of four sessions of “Colpbol”, among others. In turn, the control group followed the PE sessions without methodological variations. To analyze the normality of the results, the Shapiro–Wilk test was used and was confirmed to be non-parametric. To measure the effect of the intervention, the Mann–Whitney and Wilcoxon U tests were used. The statistics showed that the improvement in the experimental group was slightly more significant than in the control group after the intervention, with a significance of 0.022 for the social behavior variable, with a significance of 0.05. These results show the relationship between PE, sustainable development, and gender equality, linking to SDG 4 and 5 and contributing to targets 4.5 and 5.5.
Low Job Market Integration of Skilled Immigrants in Canada: The Implication for Social Integration and Mental Well-Being
Authors: Raihan Mohammad M. H. , Chowdhury Nashit , Turin Tanvir C.
Published: March 2023

Skilled immigrants are critical assets to the social and economic dynamism of Canada. However, they are less likely to find employment matching their skillset due to a lack of inclusive post-immigration professional integration policies and support. They generally earn less and often live below the low-income cutoff relative to their Canadian-born counterparts. This paper aims to review the current situation of low job market integration (LJMI) of skilled immigrants in Canada and its implications on their social integration and mental well-being. Skilled immigrants continue to face disparities in getting desired jobs, despite having sufficient skills and credentials similar if not superior to that of Canadian-borns. Based on the existing literature, this study demonstrates that low job market integration limits skilled immigrants’ productivity, and they experience a lower level of social integration and deteriorated mental well-being. Therefore, initiatives from multidisciplinary and multisector stakeholders are necessary to improve skilled immigrants’ mental well-being by providing equal opportunities devoid of social exclusion and marginalization.
Falling off the Radar? Reaching Out to the Finnish Roma Community during the COVID-19 Pandemic
Authors: Stenroos Marko , Musta Laura , Skogberg Natalia
Published: March 2023

In this paper, we ask how the Finnish Roma community handled the challenging times of the COVID-19 pandemic, and how the information reached Roma communities. The previous studies indicate existing health inequalities between Finnish Roma and the general population. The point of departure for the article is crisis communication between Finnish Roma and national authorities. The themes of racialization, mistrust and Roma relying on peers as a source of information and support became apparent. From this setting, this article sheds light on the way of speaking, usage of language, (Finnish) as a social construction of ethnic identity and expression of (non)belonging. At the same time, the usage of languge and codeswitching reveals social stratifications among the Finnish Roma population. Findings indicate that subtle forms of exclusion of Roma prevail in Finland and are materialized as a “left alone mentality”. Consequently, Roma persons working as civil servants or NGO workers would potentially constitute a crucial link between health authorities and the Roma population. This link, however, should be constantly maintained. The study is a qualitative study and based on thematic interviews among Roma actors.
Effects of Malocclusion on Maximal Aerobic Capacity and Athletic Performance in Young Sub-Elite Athletes
Authors: El Ouali El Mokhtar , Zouhal Hassane , Bahije Loubna , Ibrahimi Azeddine , Benamar Bahae , Kartibou Jihan , Saeidi Ayoub , Laher Ismail , El Harane Sanae , Granacher Urs , Mesfioui Abdelhalem
Published: March 2023

Oral pathologies can cause athletic underperformance. The aim of this study was to determine the effect of malocclusion on maximal aerobic capacity in young athletes with the same anthropometric data, diet, training mode, and intensity from the same athletics training center. Sub-elite track and field athletes (middle-distance runners) with malocclusion (experimental group (EG); n = 37; 21 girls; age: 15.1 ± 1.5 years) and without malocclusion (control group (CG); n = 13; 5 girls; age: 14.7 ± 1.9 years) volunteered to participate in this study. Participants received an oral diagnosis to examine malocclusion, which was defined as an overlapping of teeth that resulted in impaired contact between the teeth of the mandible and the teeth of the upper jaw. Maximal aerobic capacity was assessed using the VAMEVAL test (calculated MAS and estimated VO2max). The test consisted of baseline values that included the following parameters: maximum aerobic speed (MAS), maximal oxygen uptake (VO2max), heart rate frequency, systolic (SAP) and diastolic arterial pressure (DAP), blood lactate concentration (LBP), and post-exercise blood lactate assessment (LAP) after the performance of the VAMEVAL test. There were no statistically significant differences between the two study groups related to either anthropometric data (age: EG = 15.1 ± 1.5 vs. CC = 14.7 ± 1.9 years (p = 0.46); BMI: EG = 19.25 ± 1.9 vs. CC = 19.42 ± 1.7 kg/m2 (p = 0.76)) or for the following physical fitness parameters and biomarkers: MAS: EG = 15.5 (14.5–16.5) vs. CG = 15.5 (15–17) km/h (p = 0.47); VO2max: EG = 54.2 (52.5–58.6) vs. CG = 54.2 (53.4–59.5) mL/kg/min (p = 0.62) (IQR (Q1–Q3)); heart rate before the physical test: EG = 77.1 ± 9.9 vs. CG = 74.3 ± 14.0 bpm (p = 0.43); SAP: EG = 106.6 ± 13.4 vs. CG = 106.2 ± 14.8 mmHg (p = 0.91); DAP: EG = 66.7 ± 9.1 vs. CG = 63.9 ± 10.2 mmHg (p = 0.36); LBP: EG = 1.5 ± 0.4 vs. CG = 1.3 ± 0.4 mmol/L (p = 0.12); and LAP: EG = 4.5 ± 2.36 vs. CG = 4.06 ± 3.04 mmol/L (p = 0.60). Our study suggests that dental malocclusion does not impede maximal aerobic capacity and the athletic performance of young track and field athletes.
Effects of Rediset Additive on the Performance of WMA at Low, Intermediate, and High Temperatures
Authors: Alqahtani Majed A. , Bazuhair Rabeea W.
Published: March 2023

Utilizing polymers with asphalt mixtures is one solution to improving the performance of asphalt mixtures. Warm mixed asphalt (WMA) technology has begun to be widely used; however, hot mixed asphalt (HMA) is the most common paving procedure worldwide. HMA has some side effects, such as increasing emissions of exhaust gases, which lead to environmental pollution and air pollution and increasing energy consumption. Thus, utilizing WMA would help to improve asphalt mixture performance, reduce mixing and paving temperatures, reduce CO2 emissions, and save energy. In this study, two WMA additives (Sasobit (M1) and Rediset LQ-1200 (M2)) are used with the control HMA to investigate and evaluate the asphalt mixture’s performance and the effects of WMA additives. Rediset LQ-1200 is a new version of materials classified under chemical additives in WMA. The Sasobit and Rediset LQ-1200 dosages were 1.5 and 0.5 percent by binder weight, respectively. Different mixture and binder tests were utilized, such as penetration, DSR, BBR, IDT, CML, HLWT, and APA. To simulate long-term performance, laboratory conditions of single or combined effects were used. The results showed that M2 had more cracking resistance and durable performance with low rutting resistance, while M1 had more rutting resistance and less moisture suitability, with low cracking resistance and durability.
The Reconstruction of Post-War Cities—Proposing Integrated Conservation Plans for Aleppo’s Reconstruction
Authors: Dimelli Despina , Kotsoni Areti
Published: March 2023

The reconstruction of historic cities is a complicated challenge that has been faced using different principles diachronically. Historic cities that have suffered severe damage are areas that need to be replanned to preserve their urban characteristics and adjust to their residents’ needs. This paper aims to examine the principles of urban preservation according to the terms of Historic Urban Landscape (HUL) principles, which consider historic centers as living organisms that need to be adjusted to modern society’s needs. The examined case study is the historic center of Aleppo and its post-war reconstruction. The research focuses on the five physical elements below: the site’s morphology, geomorphology, and natural features; its built environment, historic or contemporary; its infrastructures; its open spaces and gardens; its land use patterns and “spatial organization”. It proposes policies and spatial forms for its reconstruction according to the HUL’s principles: more specifically, it proposes plans and strategies for the historic center’s regeneration in the fields of land uses, building regulations, transportation networks, and green public spaces, taking into account several factors: the inhabitants, the stakeholders, UNESCO’s regulations, and the cultural value of the built environment. Finally, it underlines the importance of community engagement for the city’s regeneration in terms of HUL.
Method to Model the Environmental Impacts of Aircraft Cabin Configurations during the Operational Phase
Authors: Keiser Dennis , Arenz Michael , Freitag Michael , Reiß Matthias
Published: March 2023

The entire aircraft industry is facing major challenges due to the formulated targets to reduce environmental emissions. For decision-makers, it is therefore of great importance to be able to compare the environmental impact of aircrafts. This includes the impact assessment of different aircraft-cabin configurations. Based on this motivation, this paper proposes a dynamic method for calculating those environmental impacts. To ensure a straightforward application, the method allows for the cabin configuration with the main cabin components. In addition, a specific mission profile can be defined and is considered in the calculations. The method follows the standardized life-cycle assessment framework. The first application of the method showed that there were large differences in the environmental impacts depending on the cabin configuration and that airlines can contribute to the achievement of sustainability goals with optimized cabin layouts.
Sensitivity Assessment of Boron Isotope as Indicator of Contaminated Groundwater for Hydraulic Fracturing Flowback Fluids Produced from the Dameigou Shale of the Northern Qaidam Basin
Authors: Zheng Zhaoxian , Zhang Yan , Li Bingyan
Published: March 2023

Hydrogeochemical processes occurring in contaminated groundwater and aquifer systems may reduce the sensitivity of boron isotopes as an indicator of hydraulic fracturing flowback fluids (HFFF) in groundwater. In this paper, based on the Chaiye-1 well (the first continental shale gas well in the northern Qaidam Basin), the hydrogeochemical processes affecting boron isotopes were analyzed in HFFF-contaminated Neogene (NG1 and NG2) and Quaternary (QG1) groundwater around the shale gas field. Then, a model for boron isotopes in HFFF-contaminated groundwater was constructed to assess the sensitivity of boron isotopes as an HFFF indicator. The results show that, limited by the range of pH values and saturation indices (SI) in HFFF-contaminated groundwater, the dissolution of alkali feldspar and precipitation of carbonate have little effect on the boron isotopes in shallow groundwater. For the NG2 aquifer system containing clay minerals, the δ11B of simulated contaminated groundwater (40.0–55.6‰) is always higher than that of the corresponding groundwater mixed conservatively (−6.4–55.6‰) due to preferential adsorption of boron isotopes onto clay minerals, indicating preferential adsorption would reduce the sensitivity of boron isotopes as an indicator of groundwater contamination from HFFF. For the scenario of HFFF contamination, when the mixing ratio of HFFF in contaminated groundwater increases by 5%, boron isotopes in Neogene (NG1 and NG2) and Quaternary (QG1) groundwater have detectable responses to HFFF contamination, suggesting δ11B is a sensitive indicator of HFFF contamination in shallow groundwater from the Dameigou Shale in the northern Qaidam Basin.
The Moderating Effect of a Golden Parachute on the Association between CSR and Firm Value: Does Gender-Driven Innovation Matter?
Authors: Okafor Collins E. , Ujah Nacasius U. , Cho Eunho , Okafor Winifred U. , James Kevin L.
Published: March 2023

We revisit the debate on whether a firm’s corporate social responsibility (CSR) activities enhance firm value. Research on related topics has produced mixed results suggesting a need to further investigate factors that directly or indirectly impact the CSR–firm value association. To this end, we examine if a firm’s adoption of a golden parachute (GP) moderates the relationship between CSR and firm value. We also investigate if diversity-based innovation as it pertains to the gender of executives reveals any difference in the CSR–firm value relation. Using a sample of 11,065 firm-year observations of publicly traded US firms from 2007 to 2016, we find that CSR activities are significantly and positively associated with firm value. More importantly, our study shows that for US firms that issue GPs, this severance pay strengthens this positive relationship, suggesting that CEOs with a GP engage in more value-enhancing innovative CSR projects than their counterparts without it. This finding supports the conflict resolution theory and the resource-based view of the firm. A test to examine if the gender of the corporate executives alters their behavior towards CSR when the GP protects them shows an inverse relationship between female executives and CSR–firm value association. This interesting finding lends credence to related theories suggesting that women in male-dominated fields may feel pressured to conform to the stereotype of women as less competent than men and may adopt traditionally masculine behaviors to counteract this stereotype. As they climb the corporate leadership ladder endowed with a GP, the stereotype threat may still prevail, adversely affecting the CSR–firm value outcomes. These results remain robust after a series of sensitivity tests.
What Can We Expect for the Development of Rural Areas in Europe?—Trends of the Last Decade and Their Opportunities for Rural Regeneration
Authors: Ahlmeyer Florian , Volgmann Kati
Published: March 2023

Rural areas in Europe have been undergoing structural change for years, resulting in strong functional differentiation and fragmentation into prosperous and structurally weak areas. Rural areas are as diverse as the challenges they face. Not only various megatrends but also social, economic, technological, ecological, and political trends influence and shape the development of rural areas. In order to understand the problems and causes of the current development of rural areas, this paper provides a differentiated trend analysis for rural areas at the European level. A content analysis of more than 70 EU-funded project reports on rural areas and rural development is carried out. The aim is to identify trends and their drivers over the last decade and to summarize opportunities and challenges for successful rural regeneration. These external and overarching trends, particularly in the context of a sustainable transition, renewable energies, the emergence of new technologies and growing awareness of environmental impacts, offer rural areas more opportunities than ever before. The interplay between external incentives (e.g., European Union policies) and endogenous regional development (e.g., local actors) is crucial for the successful exploitation of these opportunities for rural regeneration.
Differentiated Control of Large Spatial Environments: Air Curtain Grid System
Authors: Song Linye , Li Kaijun , Zhang Xinghui , Hua Jing , Zhang Cong
Published: March 2023

Large public buildings (LPBs) are the main energy consumers in cities, and the air conditioning system contributes a large part. Supply air allocation by partition can avoid excessive regulation of the system. In spatially interconnected LPBs, thermal coupling relationships exist between different subzones. The convective heat transfer to the non-occupied zone increases the actual cooling/heating capacity of the air conditioning area. This paper applies the air curtain as an airflow barrier indoors, and the air curtain grid system (ACGS) is created by the combined operation of multiple air curtains, which aims to reduce the convective heat exchange between adjacent subzones. The computational fluid dynamics (CFD) model is established and simulated. The main conclusions are as follows: (1) For the scenarios addressed in this paper, the combination of a 60° diffuser air supply angle and 2 m/s air curtain velocity can reduce the convective load from the adjacent space by more than 50%. (2) It is recommended to install incomplete air curtains indoors, and a 50% air curtain coverage ratio can reduce 52% of the heat exchange. (3) The mathematical model of air infiltration/exfiltration under the combined operation of multiple air curtains is established and verified in ACGS. This paper provides a new approach to the air conditioning partition control of LPBs.
Partial Replacement of Cationic Starch by Cationic Hardwood Kraft Lignin Does Not Compromise Key Paper Properties
Authors: Pinto Patrícia I. F. , Pinto Paula C. R. , Evtuguin Dmitry V. , Liebner Falk
Published: March 2023

Competition issues with food industry have recently boosted the exploration of alternative solutions capable of replacing starch in papermaking to a certain extent. Covalent grafting of quaternary ammonium groups onto LignoBoost® Eucalyptus kraft lignin has recently shown promise in this regard as the cationic products feature excellent water solubility across the entire pH scale. Considering these suitable properties, cationic kraft lignin was applied and evaluated, for the first time, in the perspective of partial substitution of cationic starch in papermaking, using bleached Eucalyptus kraft pulp. Based on an assessment of key paper properties, such as mechanical (tensile, bursting, and tearing indexes), structural (roughness, capillarity rise, air resistance, internal strength, and water contact angle), and optical ones (brightness, opacity, and relative color change), it is safe to conclude that the partial replacement of conventional cationic starch by cationic lignin does not compromise these features. The results also show that properties can be fine-tuned by varying the degree of lignin derivatization, providing paper-specific solutions for replacing starch by lignin potentially available at large-scale at the pulp and paper industry, closing the loop within the circular economy concept.
Wind Energy and the Energy Transition: Challenges and Opportunities for Mexico
Authors: Magar Vanesa , Peña Alfredo , Hahmann Andrea Noemí , Pacheco-Rojas Daniel Alejandro , García-Hernández Luis Salvador , Gross Markus Sebastian
Published: March 2023

We present a review of wind energy development in Mexico, factors hampering this development, and proposals for solutions to address this hampering. This review is relevant in the context of climate change mitigation strategies and the achievement of the United Nations’ sustainable development goals. Wind energy can be harvested at competitive costs to solve society’s energy poverty and climate change problems. Firstly, we present the current wind energy installed capacity and wind power generation status globally and in Mexico and discuss why Mexico is lagging behind, particularly since 2020. Despite this lag, several state governors are still considering wind energy developments. The current economic context is then considered, with community wind energy as a solution forward for wind energy development, using a successful case study from the UK that has addressed energy poverty and provided an additional income source for an island community. Any community energy project using wind as its main energy resource relies on accurate wind energy assessment in its feasibility analysis. Thus, an evaluation of different wind energy atlases for Mexico was performed, which showed that models considering microscale processes could lead to a relative difference of more than 50% when compared to those that do not consider them. This led to the conclusion that microscale effects must be considered in wind energy characterization models. Furthermore, it is acknowledged that wind faces other challenges, such as the effect of future climate change scenarios, grid planning, and vulnerability and risk associated with tropical storms, which can be substantial in Mexico. Solutions are proposed in the form of possible wind power generation scenarios, planning and implementation of centralized and distributed transmission lines, and possible wind siting and technological choices to reduce the vulnerability and risk to tropical storms. Finally, we close with some future perspectives for researchers and decision-makers. The main conclusions are that sustainable growth can only be compatible with a transition to renewable sources of energy, energy community projects can address energy poverty and achieve sustainable development goals, wind energy feasibility studies need to include microscale effects, return of investment can be improved by siting the wind farms in regions of low vulnerability and risk to extreme events, and high-voltage transmission lines are crucial for sustainable development, even with the important role that distributed systems play. Finally, turbine growth and materials recycling, among other factors, must be considered when assessing the environmental impacts of wind farm decommissioning.