bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing IoT Network Security: Unveiling the Power of Self-Supervised Learning against DDoS Attacks
Authors: Almaraz-Rivera Josue Genaro , Cantoral-Ceballos Jose Antonio , Botero Juan Felipe
Published: October 2023

The Internet of Things (IoT), projected to exceed 30 billion active device connections globally by 2025, presents an expansive attack surface. The frequent collection and dissemination of confidential data on these devices exposes them to significant security risks, including user information theft and denial-of-service attacks. This paper introduces a smart, network-based Intrusion Detection System (IDS) designed to protect IoT networks from distributed denial-of-service attacks. Our methodology involves generating synthetic images from flow-level traffic data of the Bot-IoT and the LATAM-DDoS-IoT datasets and conducting experiments within both supervised and self-supervised learning paradigms. Self-supervised learning is identified in the state of the art as a promising solution to replace the need for massive amounts of manually labeled data, as well as providing robust generalization. Our results showcase that self-supervised learning surpassed supervised learning in terms of classification performance for certain tests. Specifically, it exceeded the F1 score of supervised learning for attack detection by 4.83% and by 14.61% in accuracy for the multiclass task of protocol classification. Drawing from extensive ablation studies presented in our research, we recommend an optimal training framework for upcoming contrastive learning experiments that emphasize visual representations in the cybersecurity realm. This training approach has enabled us to highlight the broader applicability of self-supervised learning, which, in some instances, outperformed supervised learning transferability by over 5% in precision and nearly 1% in F1 score.
The Effect of a Smartphone App with an Accelerometer on the Physical Activity Behavior of Hospitalized Patients: A Randomized Controlled Trial
Authors: Dijk-Huisman Hanneke C. van , Senden Rachel , Smeets Maud H. H. , Marcellis Rik G. J. , Magdelijns Fabienne J. H. , Lenssen Antoine F.
Published: October 2023

Inactive behavior is common in hospitalized patients. This study investigated the effectiveness of using a smartphone app with an accelerometer (Hospital Fit) in addition to usual care physiotherapy on increasing patients’ physical activity (PA) behavior. A randomized controlled trial was performed at Maastricht University Medical Centre. Patients receiving physiotherapy while hospitalized at the department of Pulmonology or Internal Medicine were randomized to usual care physiotherapy or using Hospital Fit additionally. Daily time spent walking, standing, and upright (standing/walking) (min) and daily number of postural transitions were measured with an accelerometer between the first and last treatment. Multiple linear regression analysis was performed to determine the association between PA behavior and Hospital Fit use, corrected for functional independence (mILAS). Seventy-eight patients were included with a median (IQR) age of 63 (56–68) years. Although no significant effects were found, a trend was seen in favor of Hospital Fit. Effects increased with length of use. Corrected for functional independence, Hospital Fit use resulted in an average increase of 27.4 min (95% CI: −2.4–57.3) standing/walking on day five and 29.2 min (95% CI: −6.4–64.7) on day six compared to usual care. Hospital Fit appears valuable in increasing PA in functionally independent patients.
Diagnosis of Alzheimer’s Disease Based on Accelerated Mirror Descent Optimization and a Three-Dimensional Aggregated Residual Network
Authors: Tu Yue , Lin Shukuan , Qiao Jianzhong , Zhang Peng , Hao Kuankuan
Published: October 2023

Alzheimer’s disease (AD), a neuropsychiatric disorder, continually arises in the elderly. To date, no targeted medications have been developed for AD. Early and fast diagnosis of AD plays a pivotal role in identifying potential AD patients, enabling timely medical interventions, and mitigating disease progression. Computer-aided diagnosis (CAD) becomes possible with the burgeoning of deep learning. However, the existing CAD models for processing 3D Alzheimer’s disease images usually have the problems of slow convergence, disappearance of gradient, and falling into local optimum. This makes the training of 3D diagnosis models need a lot of time, and the accuracy is often poor. In this paper, a novel 3D aggregated residual network with accelerated mirror descent optimization is proposed for diagnosing AD. First, a novel unbiased subgradient accelerated mirror descent (SAMD) optimization algorithm is proposed to speed up diagnosis network training. By optimizing the nonlinear projection process, our proposed algorithm can avoid the occurrence of the local optimum in the non-Euclidean distance metric. The most notable aspect is that, to the best of our knowledge, this is the pioneering attempt to optimize the AD diagnosis training process by improving the optimization algorithm. Then, we provide a rigorous proof of the SAMD’s convergence, and the convergence of SAMD is better than any existing gradient descent algorithms. Finally, we use our proposed SAMD algorithm to train our proposed 3D aggregated residual network architecture (ARCNN). We employed the ADNI dataset to train ARCNN diagnostic models separately for the AD vs. NC task and the sMCI vs. pMCI task, followed by testing to evaluate the disease diagnostic outcomes. The results reveal that the accuracy can be improved in diagnosing AD, and the training speed can be accelerated. Our proposed method achieves 95.4% accuracy in AD diagnosis and 79.9% accuracy in MCI diagnosis; the best results contrasted with several state-of-the-art diagnosis methods. In addition, our proposed SAMD algorithm can save about 19% of the convergence time on average in the AD diagnosis model compared with the gradient descent algorithms, which is very momentous in clinic.
DeepVision: Enhanced Drone Detection and Recognition in Visible Imagery through Deep Learning Networks
Authors: Al Dawasari Hassan J. , Bilal Muhammad , Moinuddin Muhammad , Arshad Kamran , Assaleh Khaled
Published: October 2023

Drones are increasingly capturing the world’s attention, transcending mere hobbies to revolutionize areas such as engineering, disaster aid, logistics, and airport protection, among myriad other fascinating applications. However, there is growing concern about the risks that they pose to physical infrastructure, particularly at airports, due to potential misuse. In recent times, numerous incidents involving unauthorized drones at airports disrupting flights have been reported. To solve this issue, this article introduces an innovative deep learning method proposed to effectively distinguish between drones and birds. Evaluating the suggested approach with a carefully assembled image dataset demonstrates exceptional performance, surpassing established detection systems previously proposed in the literature. Since drones can appear extremely small compared to other aerial objects, we developed a robust image-tiling technique with overlaps, which showed improved performance in the presence of very small drones. Moreover, drones are frequently mistaken for birds due to their resemblances in appearance and movement patterns. Among the various models tested, including SqueezeNet, MobileNetV2, ResNet18, and ResNet50, the SqueezeNet model exhibited superior performance for medium area ratios, achieving higher average precision (AP) of 0.770. In addition, SqueezeNet’s superior AP scores, faster detection times, and more stable precision-recall dynamics make it more suitable for real-time, accurate drone detection than the other existing CNN methods. The proposed approach has the ability to not only detect the presence or absence of drones in a particular area but also to accurately identify and differentiate between drones and birds. The dataset utilized in this research was obtained from a real-world dataset made available by a group of universities and research institutions as part of the 2020 Drone vs. Bird Detection Challenge. We have also tested the performance of the proposed model on an unseen dataset, further validating its better performance.
The Design of a Low-Noise, High-Speed Readout-Integrated Circuit for Infrared Focal Plane Arrays
Authors: Mu Yusong , Zhao Zilong , Chen Chong , Yuan Di , Wang Jing , Gao Hansong , Chi Yaodan
Published: October 2023

This paper describes the design of a low-noise, high-speed readout-integrated circuit for use in InGaAs infrared focal plane arrays, and analyzes the working principle and noise index of the pixel circuit in detail. The design fully considers the dynamic range, noise, and power consumption of the pixel circuit in which a capacitance transimpedance amplifier structure is adopted as the input stage circuit, and chip fabrication via an XFAB 0.18 µm CMOS process is successfully realized. The ROIC adopts monolithic integration and implements various functions, such as windowing, subsampling, and different integration and readout modes. The ROIC reached an array scale of 32 × 32, a frame rate of 100 Hz, and a readout rate of 20 Mbps with an analog power consumption of less than 52 mW. The measurement results show that the input reference noise can be reduced to 143 e- via the CDS, and the fully customized scheme has certain advantages in the research of high-performance ROICs.
Testing the Uniformity of Surface Resistance on Large-Format Transparent Heating Glass
Authors: Flaga Stanisław , Dominik Ireneusz , Szybiński Marek
Published: October 2023

The design of a glazing package containing heating glass can make a window a radiator simultaneously. For such bulky glass to act as an effective radiator simultaneously, it should be possible to provide a constant temperature over the entire surface. The continuous surface temperature of the glass depends on the uniformity of the surface resistance of the resistive layer. This paper will demonstrate the testing of heating glass parameters using a specialised apparatus. The research will mainly focus on measuring the value and distribution of the surface resistance of the transparent heating layer. A thermographic study will verify the results. As the heating glass will be subjected to a toughening process, the effect of the toughening process parameters on the degradation of the transparent heating film will be investigated.
Heterogeneity Analysis of Industrial Structure Upgrading on Eco-Environmental Quality from a Spatial Perspective: Evidence from 11 Coastal Provinces in China
Authors: Zhai Xiaohang , Chen Zhe , Tan Chunlan , Li Guangliang
Published: October 2023

Upgrading the industrial structure and improving the quality of the ecological environment are important strategic steps to realize the modernization of China. Based on the panel data of 11 provinces (municipalities) in China’s coastal areas from 2010 to 2019, this paper uses the spatial Dubin model and the threshold effect model to study the impact of industrial structure upgrading on eco-environmental quality. The results show that the influence of industrial structure upgrading on ecological environment quality has a positive “U”-shaped distribution. Based on the spatial econometric model, it is found that the rationalization of industrial structure and the optimization of industrial structure have spatial spillover effects on the ecological environment quality, and the influence of the rationalization of industrial structure and the optimization of industrial structure on the ecological environment quality of the surrounding area is positive “U”-shaped and inverted “U”-shaped, respectively. Based on the threshold model, it is found that industrial structure rationalization has a small effect on the ecological environment’s quality when the degree of scientific and technological innovation is low. When scientific and technological innovation reaches a certain threshold, industrial structure rationalization has a significant effect on the quality of the ecological environment. In addition, from a regional perspective, the influence of industrial structure rationalization in the East China Sea and the South China Sea and industrial optimization in the Bohai-Yellow Seas on the eco-environmental quality of the surrounding areas has a positive “U”-shaped distribution, while the influence of the optimization of industrial structure in the South China Sea on the eco-environmental quality of the surrounding areas has an inverted “U”-shaped curve on the left side.
Acute Ecotoxicity Potential of Untreated Tannery Wastewater Release in Arequipa, Southern Peru
Authors: Tejada-Meza Kevin , Arenazas-Rodríguez Armando , Garcia-Chevesich Pablo A. , Flores-Farfan Carmen , Morales-Paredes Lino , Romero-Mariscal Giuliana , Ticona-Quea Juana , Vanzin Gary , Sharp Jonathan O.
Published: October 2023

The centralized Rio Seco Industrial Park (RSIP) tannery collective in the Southern Peruvian city of Arequipa releases untreated tannery wastewater into a proximal creek that is a tributary of the Chili River. As industrial leather tanning wastewater contains high concentrations of metal(loid)s, salts, dyes, and organics, this complex mixture could exert a myriad of toxicological effects on the surrounding ecosystem. The RSIP effluent was analyzed to quantify the acute ecotoxicity and ecotoxicological status of this untreated industrial wastewater at multiple trophic levels with the following bioindicators: the floating macrophyte Lemna minor, invertebrates Daphnia magna and Physa venustula, and the amphibian Xenopus laevis. A physicochemical characterization of the RSIP effluent revealed a highly contaminated waste stream. In addition to chromium (10.4 ± 0.4 mg/L) and other toxic metals, the water harbored extremely high concentrations of total dissolved solids (67,770 ± 15,600 mg/L), biochemical oxygen demand (1530 ± 290 mg/L) and total nitrogen (490 ± 10 mg/L). The toxicological responses of certain bioindicator species tested were evaluated after exposure to 0, 1.5, 3.0, and 4.5% untreated tannery wastewater blended with dechlorinated tap water. L. minor experienced a significant decrease in the number of fronds, wet weight, and dry weight at the lowest blended wastewater of 1.5%. Bioassays with D. magna showed the effect on neonatal mortality with a calculated LC50 of 1.1% for 48 h. Bioassays with P. venustula embryos showed high sensitivity to diluted effluent with complete mortality at 3.0% wastewater and above. Finally, X. laevis showed a high sensitivity to the dilutions with an LC50 of 1.6 for embryos and 1.8% for tadpoles. Although RSIP wastewater contains many potentially toxic components, chromium and total dissolved solids, with a major contribution from sodium, are best correlated with acute toxicity variables. This suggests that conductivity or analogous measurements could provide a rapid and affordable forensic tool to query acute ecosystem pressures. Collectively, the results indicate that the release of untreated tannery wastewater from RSIP can exert pronounced acute impacts across trophic levels with the need for treatment or dilution to below 1% of total flow. As the assays addressed acute toxicity, the necessary treatment and/or dilution to mitigate chronic effects is likely much lower. In conclusion, untreated RSIP tannery wastewaters represent an ecological risk to downstream aquatic ecosystems; this needs to be addressed to prevent current and future environmental consequences.
Integration of Water Resources Management Strategies in Land Use Planning towards Environmental Conservation
Authors: Kalogiannidis Stavros , Kalfas Dimitrios , Giannarakis Grigoris , Paschalidou Maria
Published: October 2023

Water resources management is a critical component of environmental conservation and sustainable development. This study examines the integration of water resources management strategies into land use planning and its impact on environmental conservation, with a focus on the case of Greece. This study employed a quantitative research methodology using a cross-sectional survey research design. The target population consisted of environmental experts in Greece, and a sample of 278 participants was selected based on the Krejcie and Morgan table for sample size determination. Data were collected through an online survey questionnaire, and the statistical analysis was conducted using SPSS version 23. The relationships between the study variables were examined through regression analysis. The findings support the hypotheses, demonstrating the importance of integrating water resources management strategies into land use planning to achieve both sustainable development and environmental conservation. This paper discusses various strategies and approaches that can be adopted to effectively manage water resources while considering the impacts of land use decisions on the environment. Better public awareness and better enforcement of water conservation rules result from this integration, which makes it possible for land use authorities and water management agencies to collaborate more effectively. This study acknowledges the need for strategic planning and cooperation between water management and land use authorities to address the growing challenges of water resources management and environmental protection. Emphasizing stakeholder participation, adaptive management, and continuous monitoring can lead to successful outcomes and a more resilient and sustainable future.
In Vitro Propagation of Several Valuable Selections of Robinia pseudoacacia L. as a Fast and Sustainable Source for Wood Production
Authors: Budău Ruben , Bei Mariana , Onet Cristian , Agud Eliza , Mintas Olimpia Smaranda , Timofte Adrian Ioan , Rosan Cristina Adriana , Laslo Vasile , Vicas Simona Ioana
Published: October 2023

There is an increasing trend in forest production towards planting rapid-growing trees as attractive, environmentally friendly energy sources. This study aimed to establish an alternative to the traditional propagation of a number of selections of Robinia pseudoacacia L. by developing an in vitro culture protocol. This study’s topic is of great importance, and it reflects an ongoing concern at the University of Oradea’s Faculty of Environmental Protection’s sustainable research program. The explants from four forms (called S1, S2, S3, and S4), selected for their phenotypic characteristics, were inoculated on four culture media (Murashige–Skoog (MS), Anderson, Chée–Pool, and Driver and Kuniyuki Woody (DKW)) with the same phytohormonal balance. DKW medium proved to be the better support of morphogenic activity, and it was further tested under different phytohormonal balances. Different results were observed depending on the hormone content in the DKW environment. In the presence of 0.5 mg/L benzylaminopurine (BAP) and 0.04 mg/L aminoisobutyric acid (AIB), 91.5% of the explants developed an average of 4.45 ± 0.18 shoots, whereas the average upper shoot height (3.82 cm) was recorded on DKW medium with 0.5 mg/L BAP and 0.04 mg/L α-naphthaleneacetic acid (NAA). Auxin, 0.05 mg/L AIB, promoted root production (5.27 ± 0.15 roots/explant), while 0.1 mg/L NAA promoted root length. In conclusion, the S4 selection produced the greatest outcomes of all environmental variables in terms of both the number of shoots and their heights.
Physical, Rheological, and Anti-Ultraviolet Aging Performance of Layered Double Hydroxides + Styrene Block Copolymer-Modified Asphalt Binders
Authors: Song Yu , Wu Shaopeng , Chen Anqi , Li Yuanyuan
Published: October 2023

To determine the preparation parameters of layered double hydroxides (LDHs) + styrene butadiene styrene block copolymer (SBS)-modified asphalt binders (MABs) in engineering applications and identify the structure of LDHs used in asphalt modification, this paper investigated the physical, rheological, and UV aging resistance of LDHs + SBS MABs under various preparation parameters. Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), scanning electron microscopy (SEM), and an ultraviolet-visible spectrophotometer (UV-vis) were used to characterize the structure and UV resistance of LDHs and D-LDHs (dissolving from LDHs + SBS MABs). The mechanical properties of LDHs + SBS MABs were studied based on penetration, ductility, softening point, and rotational viscosity tests. The rheological performance and UV aging resistance of LDHs + SBS MABs were assessed using the bending beam rheometer (BBR) test, direct tensile test (DTT), dynamic shear rheometer (DSR) test, and FTIR. The results demonstrated that the crystal and chemical structures of LDHs remain unchanged before and after use in asphalt modification. The optimal preparation parameters of LDHs + SBS MABs were as follows: a preparation temperature of 170 °C, a shearing time of 60 min, and a shearing rate of 4000 r/min. The high-temperature performance of LDHs + SBS MABs improved significantly with LDHs added, and the low-temperature performance slightly decreased. The viscosity of LDHs + SBS MABs with 4 wt% LDHs at 135 °C was 1.920 Pa·s, which was 47.4% higher than that of SBS MABs. The DTT results indicated that SBS MABs have the highest fracture energy (FE) value of 4873 J/m2, showing the best low-temperature cracking resistance. In comparison, the FE values of MABs doped with 3 wt% and 4 wt% LDHs are 4518 J/m2 and 4248 J/m2, respectively, just 7.3% and 12.8% lower than that of ABs without LDHs. The complex modulus aging index (CMAI) of MABs doped with 4% LDHs is 14.3%, which is 15.9% lower than that of SBS MABs, indicating that the anti-ultraviolet aging performance of LDHs + SBS MABs has been improved. FTIR analysis demonstrated that the relative content of C=O (RCC) and S=O (RCS) of LDHs + SBS MABs decreased drastically compared with SBS MABs, indicating that the UV aging resistance of LDHs + SBS MABs was largely enhanced. Furthermore, the segregation test result of 3wt% LDHs + SBS-modified asphalt is 0.3 °C, showing the best compatibility with asphalt.
GEECO: Green Data Centers for Energy Optimization and Carbon Footprint Reduction
Authors: Mondal Sudipto , Faruk Fashat Bin , Rajbongshi Dibosh , Efaz Mohammad Masum Khondhoker , Islam Md. Motaharul
Published: October 2023

Cloud computing has revolutionized data storage, processing, and access in modern data center operations. Conventional data centers use enormous amounts of energy for server operation, power supply, and cooling. The processors produce heat while processing the data and therefore increase the center’s carbon footprint, and the rising energy usage and carbon emissions caused by data centers pose serious environmental challenges. Under these circumstances, energy-efficient green data centers are being used as a phenomenal source of sustainable modernization. This study proposes the implementation of the Green Energy Efficiency and Carbon Optimization (GEECO) model for enhancing energy usage. Within the data center, the GEECO model dynamically adjusts workload distribution and task assignment to balance performance and manage service-level reconciliation. The ability to identify possibilities for energy optimization and carbon emission reduction is possible through real-time monitoring of energy usage and workload demand. The results revealed a considerable increase in energy efficiency, with significant decreases in energy usage and related costs. The GEECO model provides a significant improvement in energy consumption and carbon emission reduction for the different introduced scenarios. This model’s introduction to practical application would be made possible by these improvements in the quantitative results. The approach of this study also has a positive impact on the environment by reducing carbon emissions. The resilience and practicality of the solution are also analyzed, highlighting the probability of widespread adoption and its associated improvements in the advancement of sustainable cloud computing.
The Mitigation of Phytopathogens in Wheat under Current and Future Climate Change Scenarios: Next-Generation Microbial Inoculants
Authors: Campos-Avelar Ixchel , Montoya-Martínez Amelia C. , Villa-Rodríguez Eber D. , Valenzuela-Ruiz Valeria , Ayala Zepeda Marisol , Parra-Cota Fannie Isela , de los Santos Villalobos Sergio
Published: October 2023

Wheat production worldwide faces numerous challenges linked to climate change, exponential population growth, nutrient depletion in agricultural soils, and the increasing threat of phytopathogen occurrence. The application of beneficial microorganisms is a promising strategy for crop management as it favorizes nutrient uptake, improves soil fertility, and increases plant resilience. Therefore, this approach facilitates the transition to more sustainable agricultural practices while reducing the dependence on agrochemicals. The valuable beneficial impacts of bioinoculant application include the enrichment of agricultural soils’ ecosystems by restoring microbial populations and interactions that have been lost through the years due to decades of intensive agricultural practices and the massive application of pesticides. Furthermore, beneficial microorganisms constitute a remarkable tool for combating biotic threats, specifically fungal pathogens, whose proliferation and emergence are predicted to increase due to global warming. To optimize their beneficial impact, bioinoculant development requires an extensive study of microbial interactions with plants and their surrounding ecosystem, to improve their composition, mode of action, and stability through application. The use of innovative tools, such as omic sciences, facilitates the elucidation of these mechanisms. Finally, bioprospection and bioformulation must be consciously executed to guarantee the application and persistence of adapted microorganisms and/or their bioactive molecules.
Servicescape Effects on Hotel Guests’ Willingness to Pay Premiums at Different Stages of Pandemic: A Multi-Phase Study
Authors: Fan Alei , Kline Sheryl F. , Liu Yiran , Byrd Karen
Published: October 2023

Drawing on servicescape theory, this research investigates guests’ perceptions of and responses to the protection and prevention practices launched by hotels at different stages of the pandemic. The research finds that hotel guests’ general response-efficacy beliefs positively influence their perception of the effectiveness of the protection and prevention practices adopted in hotels’ physical and social servicescapes, and such positive relationships also show a significant increase from 2020 to 2021. The servicescape effects’ downstream results show that hotel guests are willing to pay premium prices for safety servicescapes manifested as protection and prevention practices implemented at the private space or related to employees. This research sheds light on servicescape theory by deconstructing the overall hotel servicescape concept into multiple dimensions, particularly in a health threat situation such as the pandemic, and empirically examining each dimension’s effects on guests’ monetary response at different timepoints. From a practical perspective, this study provides managerial insights into which servicescape dimensions warrant operational investments by hotels.
Microplastics in Sandy Beaches of Puerto Vallarta in the Pacific Coast of Mexico
Authors: Mejía-Estrella Ixchel Alejandra , Peña-Montes Carolina , Peralta-Peláez Luis Alberto , Del Real Olvera Jorge , Sulbarán-Rangel Belkis
Published: October 2023

In this research, the abundance and physical and chemical characteristics of microplastics (MPs) in coastal sediments from three beaches of Puerto Vallarta in Mexico were investigated. The objective of characterizing and finding MPs in sand is to generate information that is useful to manage macroplastic waste, prevent its additional generation, and thus reduce environmental pollution and achieve sustainable development. The MPs were classified according to their physical characteristics such as color, size, and shape under a stereoscopic microscope, and their wear and surface were observed using a scanning electron microscope. The chemical composition of the most representative types of polymers were detected by Fourier-transform infrared spectroscopy. It can be observed that Los Muertos beach presents the highest number of MPs (97.5 particles/m2) followed by Boca de Tomates beach (69.75 particles/m2) and Oro beach (28.75 particles/m2). The differences found between the beaches are attributed to the tourist influx and proximity to the mouth of a river. In total, 37% of MPs were white, followed by 19% yellow, and 11% transparent. The shape distribution of microplastics of sizes < 5 mm and 1 mm was fragmented, the greatest abundance was microfibers, microfragments, and microfilms for MPs between <1 mm and 1 µm, and these corresponded to polyester, polyethylene, cellophane, and polystyrene, respectively.
Systematic Insights into a Textile Industry: Reviewing Life Cycle Assessment and Eco-Design
Authors: Fonseca Ana , Ramalho Edgar , Gouveia Ana , Henriques Rita , Figueiredo Filipa , Nunes João
Published: October 2023

The worldwide textile sector is one of the most polluting and consuming natural resource value chains. In recent years, trends have demonstrated a linear model driven by fast fashion, increasing the sustainability problems of this sector. The European market and industry are changing the paradigm and promoting some actions towards a sustainable value chain. This paper applies a systematic approach to reviewing scientific research, where Life Cycle Assessment (LCA) is implemented as a tool to understand the impacts considering a holistic life cycle framework, from raw materials to the end-of-life of textile products. The methodology and criteria applied resulted in 73 articles used for qualitative analysis, of which 39 met the criteria for quantitative analysis. The quantitative results reported in the studies were organized and presented by phase of the garment production life cycle (production of fiber, yarn, fabric, manufacturing, and recovery/end of life). From a cradle-to-gate perspective, wool yarn production, by worsted processing, was the material with the highest values (95.70 kg CO2 eq/kg) for climate change/global warming potential, closely followed by silk fabric (80.90 kg CO2 eq/kg). Extending to a cradle-to-grave boundary, polyester had the highest values for the previously mentioned category, reaching a potential release of 40.28 kg CO2 eq per kilogram of polyester textile. When data was available, the user phase predominantly contributed to climate change/global warming potential. Additionally, there were significant differences in maximum and minimum values for some of the materials, which were related to methodological considerations, database inventory, and frequency of use and care considered by the different authors. The study also addresses the considerations and limitations of diverse LCA impact assessment tools.
Acceptance of Digital Transformation: Evidence from Romania
Authors: Rusu Bogdan , Sandu Christiana Brigitte , Avasilcai Silvia , David Irina
Published: October 2023

The digital transformation (DT) implies designing products and services, to which digital technology is applied, that are adopted and used by customers. However, if people do not accept the new technologies embedded in the innovative products and services, DT will fail. Therefore, getting to know the determinant factors that affect acceptance is necessary, especially during economic turmoil that requires companies to become even more competitive. Moreover, Romania is lagging behind in its digital progress. The aim of this research is to draw upon a previous study on successful DT, analyze personal and social acceptance factors, and empirically verify whether they would affect DT in Romania. We identified from the literature the main factors (behavioral and innovative characteristics) affecting the DT acceptance attitude and adapted the theoretical model to the Romanian context. The study collected data from 123 persons using an online questionnaire and applied a structural equation model to test the theoretical model. The empirical results emphasize that the acceptance attitude of DT is positively associated with individuals’ behavioral factors and innovative characteristics. Moreover, DT acceptance attitude positively impacts both personal and social acceptance of DT. This research provides both theoretical and empirical contributions by adapting the theoretical DT model and testing it for the Romanian context, using personal and social acceptance. These findings are important for managers and policy makers that seek to transform their organizations.
Prediction of Heat and Cold Loads of Factory Mushroom Houses Based on EWT Decomposition
Authors: Zuo Hesen , Zheng Wengang , Wang Mingfei , Zhang Xin
Published: October 2023

Load forecasting has significant implications on optimizing the operation of air conditioning systems for industrial mushroom houses and energy saving. This research paper presents a novel approach for short-term load forecasting in mushroom houses, which face challenges in accurately modeling cold and heat loads due to the complex interplay of various factors, including climatic conditions, mushroom growth, and equipment operation. The proposed method combines empirical wavelet transform (EWT), hybrid autoregressive integrated moving average (ARIMA), convolutional neural network (CNN), and bi-directional long short-term memory (BiLSTM) with an attention mechanism (CNN-BiLSTM-Attention) to address these challenges. The first step of this method was to select input features via the Boruta algorithm. Then, the EWT method was used to decompose the load data of mushroom houses into four modal components. Subsequently, the Lempel–Ziv method was introduced to classify the modal components into high-frequency and low-frequency classes. CNN-BiLSTM-Attention and ARIMA prediction models were constructed for these two classes, respectively. Finally, the predictions from both classes were combined and reconstructed to obtain the final load forecasting value. The experimental results show that the Boruta algorithm selects key influential feature factors effectively. Compared to the Spearman and Pearson correlation coefficient methods, the mean absolute error (MAE) of the prediction results is reduced by 14.72% and 3.75%, respectively. Compared to the ensemble empirical mode decomposition (EEMD) method, the EWT method can reduce the decomposition reconstruction error by an order of magnitude of 103, effectively improving the accuracy of the prediction model. The proposed model in this paper exhibits significant advantages in prediction performance compared to the single neural network model, with the MAE, root mean square error (RMSE), and mean absolute percentage error (MAPE) of the prediction results reduced by 31.06%, 26.52%, and 39.27%, respectively.
Quality of Urban Water Services Provided to Users: Assessment System and the Portuguese Path through Four Generations, Lessons Learned and New Challenges
Authors: Cardoso Maria Adriana , Brito Rita Salgado , Silva Catarina , Rodrigues Susana , Rodrigues Rute , Costa Alexandra , Cardoso Joana , Jorge Catarina , Alegre Helena , Rosa Maria João
Published: October 2023

Public water supply, urban wastewater and stormwater management, and urban waste management are structural public services, essential to well-being, public health, and the safety of populations as well as to economic activities and environmental protection. These services must be guided by principles of universal access, continuity and quality of service, and efficiency and fairness of applied tariffs. The main concern of the regulation of these services is the protection of the interests of the users through the promotion of the quality of the service provided by the water utilities and the guarantee of balance in the practiced tariffs, materialized in the principles of universality, equity, reliability, and cost-efficiency. The quality of the urban water services has been assessed by ERSAR (the Portuguese regulator) since 2004, when the first generation of the assessment system was developed, and has undergone three periodical critical revisions. The fourth generation, developed in 2021, entered in force in 2022. This paper presents the fourth generation of ERSAR’s system for assessing the quality of urban water services in Continental Portugal, focusing on the path followed and addressing the experience of its application over almost two decades, the lessons learned, and the new challenges for the water sector.
The Impact of Regional Socio-Economic Development on Spatial and Temporal Differences in the Distribution Pattern of Top-Tier Education in China
Authors: Chen Xiaoshuang , Yu Hao , Ding Mingli , Shu Huisheng
Published: October 2023

Regional socio-economics has multiple and far-reaching influences on the development of top-tier education, and the development of top-tier education also represents the strength and level of the regional socio-economics to a large extent. The present study investigates the spatial and temporal differences in the distribution pattern of doctoral disciplines of Chinese “double first-class” construction universities between 1996 and 2022 and the influence of regional socio-economics through two perspectives of economic regions and provinces. The study shows that there are differences in the development speed, scale, and level of top-tier education among different economic divisions and provinces, and the overall pattern of “fast in the east and slow in the west”, “more in the east and less in the west”, and “strong in the east and weak in the west” is unbalanced. At the same time, there is a high degree of concentration in different economic regions. The main reasons include the historical problem of the unbalanced allocation of China’s educational resources, as well as the uneven geographical distribution of relevant national policies, and the influence of regional socio-economic development differences, especially GDP and literacy rate. In terms of the influence mechanism, the development mindset of universities themselves, especially the strategy for talent cultivation and introduction, is the fundamental factor for the formation of the top-tier education development gap among different economic regions and provinces.
Effect of Hydraulic Structure on Mitigating Extreme Hydrological Conditions of a Small River in the Temperate Zone (Główna River, Central Europe)
Authors: Ptak Mariusz , Szyga-Pluta Katarzyna , Zhu Senlin , Osmanaj Lavdim , Sojka Mariusz
Published: October 2023

Water resources are of elementary economic and environmental importance, and the observed global transformations as well as regional environmental conditions necessitate activities aimed at providing an optimal amount of water at different levels. One such solution is hydrotechnical infrastructure that permits the precise control of the amount of water in the catchment. This paper presents results concerning changes in the water flow in the Główna River in Poland before (1955–1983) and after (1984–2021) the construction of the Kowalski Reservoir. In the former period, there were no changes in water flow, and the obtained results were not statistically significant (p 0.05). In the period after the construction of the reservoir, a decreasing trend in monthly flow was observed in December, April, July, September, and October. Moreover, a decrease in 1, 3, 7, and 90 day maximum flow was observed. For maximum 30 day flow, the changes were below the threshold of the adopted significance level. Moreover, minimum flow in the period after the construction of the reservoir showed no significant decreasing trend. In hydrological terms, the reservoir served its purpose by contributing to the stabilisation of the water flow. This information is important from the point of view of an increase in retention and corresponds with a broader programme conducted in the territory of Poland. In the context of the construction of further reservoirs, it is important to investigate the current range of changes in water circulation for objects of the type already functioning in the environment, constituting an actual point of reference.
Technology Enhanced Learning in Undergraduate Level Education: A Case Study of Students of Mass Communication
Authors: Tahat Dina Naser , Habes Mohammed , Tahat Khalaf , Pasha Saadia Anwar , Attar Razaz Waheeb , Al-Rahmi Waleed Mugahed , Alblehai Fahad
Published: October 2023

The incorporation of digital technology in education represents a substantial transformation in the realm of academia. In the present day, with new technology being readily available to both educators and students, educational institutions encourage their students to embrace it, enabling students facing geographical constraints to easily continue their education through internet-based learning. The primary objective of this study is to investigate the viewpoints of undergraduate students in the field of mass communication concerning the integration of Information and Communication Technology (ICT) in the UAE. Based on a Technology Acceptance Model (TAM), the data were gathered using structured questionnaires. Results revealed that knowledge sharing and accessibility are significant factors affecting the perceived ease of use and perceived usefulness among the undergraduate students. Further, perceived ease of use significantly affects perceived usefulness. Finally, both perceived ease of use and perceived usefulness remained as significant factors regarding ICT acceptance among the Emirati students. It is concluded that educational institutions must invest significantly in robust IT infrastructure. This step ensures that e-learning experiences are seamless and accessible to all students. Further, to address some students’ connectivity challenges, offering alternative access options or providing offline resources can be beneficial. Finally, the practical implications and limitations are discussed.
Research on the Closure and Remediation Processes of Mining Areas in Romania and Approaches to the Strategy for Heavy Metal Pollution Remediation
Authors: Radu Violeta Monica , Vîjdea Anca Marina , Ivanov Alexandru Anton , Alexe Veronica Elena , Dincă George , Cetean Valentina Maria , Filiuță Andra Elena
Published: October 2023

Mining activities often generate important amounts of extractive waste, and, as a consequence, environmental impacts that affect all factors to a greater or lesser extent. Depending on a variety of variables, the impact can be permanent or temporary, reversible or irreversible, negative or positive. This study conducted research on the status of closure and remediation processes of mining areas in Romania, specifically in the counties of Maramureș, Suceava, Harghita, Alba, Hunedoara and Caraș-Severin. Furthermore, based on the type and level of pollution, the degree of application of remediation techniques for water and soil pollution in the investigated mining areas was studied. From the analysed information, it is evident that although the closure and remediation process started in Romania over 20 years ago, unfortunately, to this day, the technical projects, technical assistance, and execution of closure and remediation works have not yet completely solved the complex environmental issues in the mining sector. Most of the tailing ponds and waste piles of former mines continue to pose permanent specific risks to the environment and the population. This study concludes that the mining sector in Romania, although it has the necessary techniques and technologies for the ecological rehabilitation of degraded lands related to the Extractive Waste Facilities and the elimination of negative impacts on the environment and public health, has not yet been able to fully concretize its remediation efforts.
The Potential of Bio-Based Polylactic Acid (PLA) as an Alternative in Reusable Food Containers: A Review
Authors: O’Loughlin Jennie , Doherty Dylan , Herward Bevin , McGleenan Cormac , Mahmud Mehreen , Bhagabati Purabi , Boland Adam Neville , Freeland Brian , Rochfort Keith D. , Kelleher Susan M. , Fahy Samantha , Gaughran Jennifer
Published: October 2023

The biodegradable biopolymer polylactic acid (PLA) has been used in the recent past in single-use packaging as a suitable replacement for non-biodegradable fossil fuel-based plastics, such as polyethylene terephthalate (PET). Under FDA and EU regulations, lactic acid (LA), the building block of PLA, is considered safe to use as a food contact material. The mechanical, thermal, and barrier properties of PLA are, however, major challenges for this material. PLA is a brittle material with a Young’s modulus of 2996–3750 MPa and an elongation at break of 1.3–7%. PLA has a glass transition temperature (Tg) of 60 °C, exhibiting structural distortion at this temperature. The water permeability of PLA can lead to hydrolytic degradation of the material. These properties can be improved with biopolymer blending and composites. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV), for instance, increases the thermal stability of PLA while decreasing the water permeability by up to 59%. Polypropylene (PP) is one of the most common plastics in reusable food containers. This study will compare PLA-based blends and composites to the currently used PP as a sustainable alternative to fossil fuel-based plastics. The end-of-life options for PLA-based food containers are considered, as is the commercial cost of replacing PP with PLA.
Learning Effects of Augmented Reality and Game-Based Learning for Science Teaching in Higher Education in the Context of Education for Sustainable Development
Authors: Czok Valerie , Krug Manuel , Müller Sascha , Huwer Johannes , Weitzel Holger
Published: October 2023

In the course of digitalization, new technologies and innovations are continuously introduced to the educational sector. For instance, augmented reality (AR) is increasingly applied in science teaching in both school and higher education. Combining real and virtual content potentially enhances interactivity and understanding of the learning process. This teaching and learning approach can positively impact various learning outcomes, such as learning gains and motivation. This paper aims to investigate the positive learning effects of AR using a game-based AR learning environment: “Beat the Beast”. In line with the concept of an education for sustainable development (ESD) topic, microplastics, this learning environment follows an interdisciplinary approach, combining the subjects of biology, chemistry, and engineering. To determine and distinguish the effects of implementing the technology AR in science learning environments as well as the principles of game-based learning, we contrasted the learning environment into two factors: one with AR and one without AR and the other with a game and without a game. A quasi-experimental design with 203 pre-service teachers of the first semester of all subjects was chosen to evaluate the four different types of settings with questionnaires on motivation, technology acceptance, user engagement, cognitive load, computer self-efficacy, knowledge, and ESD outcomes in higher education. Our research demonstrates that although augmented reality (AR) imposes a relatively elevated cognitive load, it does not negatively affect learning effects. In spite of the increased cognitive load, learners in AR settings do not exhibit lesser knowledge acquisition compared to those in alternative environments. Moreover, our investigation highlights AR’s potential to amplify motivation and user engagement. Contrary to expectations, in the context of the selected subject matter and target audience, game-based adaptations of the educational environment fail to enhance learning outcomes. These versions actually underperform compared to other formats in both motivational and engagement metrics.