bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of an Electrodeficient Dipyridylbenzene-like Terdentate Ligand: Cyclometallating Ligand for Highly Emitting Iridium(III) and Platinum(II) Complexes
Authors: Lanoë Pierre-Henri , Philouze Christian , Loiseau Frédérique
Published: July 2023

Cyclometallated iridium(III) and platinum(II) complexes are intensely used in optoelectronics for their photophysical properties and ability to convert excitons from singlet to triplet state, thus improving the device efficiency. In this contribution, we report the multi-steps synthesis of an electrodeficient dipyridylbenzene-like terdentate ligand [N^C^N], namely 2′,6′-dimethyl-2,3′:5′,2″-terpyridine (6), with 18% overall yield. Compound 6 has been employed to synthesize two phosphorescent complexes of platinum(II) and iridium(III), namely compounds 7 and 8, respectively. Both complexes have been characterized by NMR and high resolution mass spectrometry, and demonstrate high luminescence quantum yields in a deaerated solution at room temperature, with 18% and 61% for 7 and 8, respectively. If the iridium(III) complex displays similar emission properties to [Ir(dpyx)(ppy)Cl] (dpyx = 3,5-dimethyl-2,6-dipyridylbenzene and ppy = 2- phenylpyridine), the platinum(II) derivative, with λem = 470 nm, is a rare example of a fluorine atom-free blue emitting [N^C^N]PtCl complex.
Biomaterial Drug Delivery Systems for Prominent Ocular Diseases
Authors: Sapowadia Avin , Ghanbariamin Delaram , Zhou Libo , Zhou Qifa , Schmidt Tannin , Tamayol Ali , Chen Yupeng
Published: July 2023

Ocular diseases, such as age-related macular degeneration (AMD) and glaucoma, have had a profound impact on millions of patients. In the past couple of decades, these diseases have been treated using conventional techniques but have also presented certain challenges and limitations that affect patient experience and outcomes. To address this, biomaterials have been used for ocular drug delivery, and a wide range of systems have been developed. This review will discuss some of the major classes and examples of biomaterials used for the treatment of prominent ocular diseases, including ocular implants (biodegradable and non-biodegradable), nanocarriers (hydrogels, liposomes, nanomicelles, DNA-inspired nanoparticles, and dendrimers), microneedles, and drug-loaded contact lenses. We will also discuss the advantages of these biomaterials over conventional approaches with support from the results of clinical trials that demonstrate their efficacy.
Pharmaceutical Strategies to Improve Druggability of Potential Drug Candidates in Nonalcoholic Fatty Liver Disease Therapy
Authors: Amatya Reeju , Lee Donghee , Min Kyoung Ah , Shin Meong Cheol
Published: July 2023

Nonalcoholic fatty liver disease (NAFLD) has become globally prevalent and is the leading cause of chronic liver disease. Although NAFLD is reversible without medical intervention in the early stage, the condition could be sequentially worsened to nonalcoholic steatohepatitis (NASH) and, eventually, cirrhosis and hepatic cancer. The progression of NAFLD is related to various factors such as genetics, pre-disposed metabolic disorders, and immunologic factors. Thankfully, to date, there have been accumulating research efforts and, as a result, different classes of potent drug candidates have been discovered. In addition, there have also been various attempts to explore pharmaceutical strategies to improve the druggability of drug candidates. In this review, we provided a brief overview of the drug candidates that have undergone clinical trials. In the latter part, strategies for developing better drugs are discussed.
Effectiveness and Safety of Glucosamine in Osteoarthritis: A Systematic Review
Authors: Vo Nam Xuan , Le Ngan Nguyen Hoang , Chu Trinh Dang Phuong , Pham Huong Lai , Dinh Khang Xuan An , Che Uyen Thi Thuc , Ngo Thanh Thi Thanh , Bui Tien Thuy
Published: July 2023

Knee osteoarthritis is the most popular type of osteoarthritis that causes extreme pain in the elderly. Currently, there is no cure for osteoarthritis. To lessen clinical symptoms, glucosamine was suggested. The primary goal of our systematic review study is to evaluate the effectiveness and safety of glucosamine based on recent studies. Electronic databases such as PubMed, Scopus, and Cochrane were used to assess the randomized controlled trial (RCT). From the beginning through March 2023, the papers were checked, and if they fulfilled the inclusion criteria, they were then examined. The Western Ontario and McMaster Universities Osteoarthritis (WOMAC) and Visual Analog Scale (VAS) scales were considered the main outcome measures. A total of 15 studies were selected. Global pain was significantly decreased in comparison to placebo, as measured by the VAS index, with an overall effect size of standardized mean difference (SMD) of −7.41 ([95% CI] 14.31, 0.51). The WOMAC scale confirmed that pain, stiffness, and physical function had improved, however the effects were insufficient. A statistical update also revealed that there were no reports of serious medication interactions or significant adverse events. To summarize, glucosamine is more effective than a placebo at reducing pain in knee osteoarthritis patients. In long-term treatment, oral glucosamine sulfate 1500 mg/day is believed to be well tolerated.
Real-Time Exploration on Buildup Dynamics of Diode-Pumped Passively Mode-Locked Nd:YVO4 Laser with SESAM
Authors: Cheng Pin-Wen , Hsu Yu-Hsin , Chang Xiu-Wei , Liang Hsing-Chih , Chen Yung-Fu
Published: July 2023

The buildup dynamics of diode-pumped passively mode-locked solid-state laser is thoroughly explored using the real-time measurement with temporal sampling rate of up to 40 GHz. A concise cavity is developed to ensure the transient dynamics purely arising from the gain medium and saturable absorber. Experimental results reveal that the laser output in the buildup process exhibits numerous passively Q-switched pulses followed with a damped relaxation oscillation prior to the stable mode locking. Furthermore, it is confirmed that the laser output has already displayed single clean mode-locked pulses inside the first several Q-switched envelopes before stepping into the stage of relaxation oscillation. The present real-time exploration is expected to provide important information for practical applications with temporal modulation of the pump intensity.
EERZ (Effective Equilibrium Reaction Zone) Model of Gas-Slag-Metal Reactions in the Application of Unconstrained Al-Ni-Cr-Co-Cu Metal Powders in Submerged Arc Welding: Model and 3D Slag SEM Evidence
Authors: Coetsee Theresa , De Bruin Frederik
Published: July 2023

The scope of this work is to improve the SAW process understanding and present an improved description of the SAW process in terms of gas-slag-metal reactions with alloy powder and Al powder additions. The scope does not include the materials properties of the weld metal. The latter may easily be optimised in the future by changing the weld metal chemistry once the process reactions of different element powders in SAW are understood. Aluminium as de-oxidiser element was applied to SAW to lower the oxygen partial pressure in the process. The results show the Al-Ni-Cr-Co-Cu alloyed weld metal total oxygen content was reduced to 257 ppm O, compared to the base case weld metal at 499 ppm O, made with the same flux and no metal powder additions. Thus, the aluminium that was added as a de-oxidiser element to the SAW process effectively lowered the original flux-induced partial oxygen pressure, both in the arc cavity and at the interface of the molten flux–weld pool phases. This partial oxygen pressure lowering effect of Al also prevents oxidation of Cr, preventing loss of Cr to the slag. Carbon steel was alloyed to 3.9% Al, 4.8% Ni, 4.9% Cr, 4.8% Co, 4.7% Cu at 62% Al yield, 76% Ni yield, 77% Cr yield, 75% Co yield, 74% Cu yield. SEM (scanning electron microscope) work on the three-dimensional (3D) post-weld slag sample show dome cavities with 3D rounded structures embedded in the dome cavity walls, as well as shards and nano-strands on the dome cavity walls. The 3D structures indicate vapour formation and re-condensation of oxy-fluorides. The novel application of the EERZ (effective equilibrium reaction zone) model simulates the mass transfer effects in the SAW process. This model is novel because it is the first model used to calculate the gas-slag-metal phase chemistry changes in SAW as a function of welding time. The novel SAW process modification of adding Al de-oxidiser powder with alloying element powders of the unique combination of Co-Cr-Co-Ni-Al was successfully applied. The results confirm that the gas phase and its reactions must be included in the interpretation and modelling of SAW process metallurgy.
Research on a New Method of Track Turnout Identification Based on Improved Yolov5s
Authors: Chen Renxing , Lv Jintao , Tian Haotian , Li Zhensen , Liu Xuan , Xie Yongjun
Published: July 2023

The modern tram track automatic cleaning car is a crucial equipment in urban rail transportation systems, effectively removing trash, dust, and other debris from the slotted tracks of trams. However, due to the complex and variable structure of turnouts, the cleaning car often requires assistance in accurately detecting their positions. Consequently, the cleaning car needs help in adequately cleaning or bypassing turnouts, which adversely affects cleaning effectiveness and track maintenance quality. This paper presents a novel method for tracking turnout identification called PBE-YOLO based on the improved yolov5s framework. The algorithm enhances yolov5s by optimizing the lightweight backbone network, improving feature fusion methods, and optimizing the regression loss function. The proposed method is trained using a dataset of track turnouts collected through field shots on modern tram lines. Comparative experiments are conducted to analyze the performance of the improved lightweight backbone network, as well as performance comparisons and ablation experiments for the new turnout identification method. Experimental results demonstrate that the proposed PBE-YOLO method achieves a 52.71% reduction in model parameters, a 4.60% increase in mAP@0.5(%), and a 3.27% improvement in precision compared to traditional yolov5s. By improving the track turnout identification method, this paper enables the automatic cleaning car to identify turnouts’ positions accurately. This enhancement leads to several benefits, including increased automation levels, improved cleaning efficiency and quality, reduced reliance on manual intervention, and mitigation of collision risks between the cleaning car and turnouts.
Zeolite-Containing Co Catalysts for Fischer–Tropsch Synthesis with Tailor-Made Molecular-Weight Distribution of Hydrocarbons
Authors: Sineva Lilia , Mordkovich Vladimir , Asalieva Ekaterina , Smirnova Valeria
Published: July 2023

The review is dedicated to the topical field of research aimed at creating catalysts combining several types of active sites. At the same time, the composition of Fischer–Tropsch synthesis (FTS) products can be controlled by changing the strength and concentration of the active sites and inter-site distances. A comparative analysis of the literature data allows to formulate the main principles of catalytic particles formation active in FTS and acid-catalyzed transformations of hydrocarbons: (1) the presence of weak Bronsted acid sites to control the cracking depth, (2) an availability of Bronsted acid sites for re-adsorption hydrocarbons and (3) weak Co-zeolite interaction to reduce methane formation.
Technological Advances to Rescue Temporary and Ephemeral Wetlands: Reducing Their Vulnerability, Making Them Visible
Authors: Jiménez-Melero Raquel , Bohorquez Patricio , González-Planet Inmaculada , Pérez-Latorre Francisco José , Parra Gema
Published: July 2023

Mediterranean temporary ponds are a priority habitat according to the Natura 2000 network of the European Union, and complete inventories of these ecosystems are therefore needed. Their small size, short hydroperiod, or severe disturbance make these ponds undetectable by most remote sensing systems. Here we show, for the first time, that the distributed hydrologic model IBER+ detects ephemeral and even extinct wetlands by fully exploiting the available digital elevation model and resolving many microtopographic features at drainage basin scales of about 1000 km2. This paper aims to implement a methodology for siting flood-prone areas that can potentially host a temporary wetland, validating the results with historical orthophotos and existing wetlands inventories. Our model succeeds in dryland endorheic catchments of the Upper Guadalquivir Basin: it has detected 89% of the previously catalogued wetlands and found four new unknown wetlands. In addition, we have found that 24% of the detected wetlands have disappeared because of global change. Subsequently, environmental managers could use the proposed methodology to locate wetlands quickly and cheaply. Finding wetlands would help monitor their conservation and restore them if needed.
Investigation of the Vertical Distribution Characteristics and Microphysical Properties of Summer Mineral Dust Masses over the Taklimakan Desert Using an Unmanned Aerial Vehicle
Authors: Zhou Xiaowen , Zhou Tian , Fang Shuya , Han Bisen , He Qing
Published: July 2023

Investigating the vertical distribution of mineral dust masses and their microphysical properties is crucial for accurately assessing the climate effects of dust. However, there are limited studies related to relevant in situ observations over dust source areas. In this study, the near-surface vertical characteristics (within 500 m a.g.l) of dust mass concentrations in five size fractions (PMs: TSP, PM10, PM4, PM2.5, and PM1) were investigated using an unmanned aerial vehicle (UAV) in Tazhong (TZ) in the Taklimakan Desert (TD) in July 2021. To the best of our knowledge, the vertical profiles of particle number concentration (PNC), effective radius (Reff), and volume concentration (Cv) were obtained for the first time by UAV over the TD. Four scenarios of clear sky, floating dust, blowing sand, and dust storm were selected based on the classification criteria for PMs. The PMs, PNC, Reff, and Cv decreased with height for all scenarios. From clear-sky to dust-storm scenarios PMs, PNC, Reff, and Cv in the column gradually increased. Reff (Cv) increased from 1.15 μm (0.08 μm3/μm2) to 4.53 μm (0.74 μm3/μm2). The diurnal variations of PMs, PNC, and Reff (Cv) revealed a unimodal pattern, with the peak occurring between 13:00 and 16:00, due to the evolution of wind speed and the atmospheric boundary layer in TZ. Unexpectedly, among the three postprecipitation scenarios (P1, P2, and P3), the PNC of P2 was smaller than those of P1 and P3. The Reff (Cv) for P2 was similar to or greater than that for dust storms, which may be associated with moist dust particles on the ground surface being carried into the air by wind. These investigations add to our understanding of the mineral dust vertical characteristics over the source area, and provide a meaningful reference for colocated lidar inversion and dust simulations.
Recent Advances and Challenges in Schumann Resonance Observations and Research
Authors: Liu Jinlai , Huang Jianping , Li Zhong , Zhao Zhengyu , Zeren Zhima , Shen Xuhui , Wang Qiao
Published: July 2023

The theoretical development of Schumann Resonances has spanned more than a century as a form of global natural electromagnetic resonances. In recent years, with the development of electromagnetic detection technology and the improvement in digital processing capabilities, the connection between Schumann Resonances and natural phenomena, such as lightning, earthquakes, and Earth’s climate, has been experimentally and theoretically demonstrated. This article is a review of the relevant literature on Schumann Resonance observation experiments, theoretical research over the years, and a prospect based on space-based observations. We start with the theoretical background and the main content on Schumann Resonances. Then, observations and the identification of Schumann Resonance signals based on ground and satellite data are introduced. The research and related applications of Schumann Resonances signals are summarized in terms of lightning, earthquakes, and atmosphere. Finally, the paper presents a brief study of Schumann Resonances based on the China Seismo-Electromagnetic Satellite (CSES) and preliminary ideas about how to improve the identification and application of space-based Schumann Resonances signals.
Spectral–Temporal Transformer for Hyperspectral Image Change Detection
Authors: Li Xiaorun , Ding Jigang
Published: July 2023

Deep-Learning-based (DL-based) approaches have achieved remarkable performance in hyperspectral image (HSI) change detection (CD). Convolutional Neural Networks (CNNs) are often employed to capture fine spatial features, but they do not effectively exploit the spectral sequence information. Furthermore, existing Siamese-based networks ignore the interaction of change information during feature extraction. To address this issue, we propose a novel architecture, the Spectral–Temporal Transformer (STT), which processes the HSI CD task from a completely sequential perspective. The STT concatenates feature embeddings in spectral order, establishing a global spectrum–time-receptive field that can learn different representative features between two bands regardless of spectral or temporal distance, thereby strengthening the learning of temporal change information. Via the multi-head self-attention mechanism, the STT is capable of capturing spectral–temporal features that are weighted and enriched with discriminative sequence information, such as inter-spectral correlations, variations, and time dependency. We conducted experiments on three HSI datasets, demonstrating the competitive performance of our proposed method. Specifically, the overall accuracy of the STT outperforms the second-best method by 0.08%, 0.68%, and 0.99% on the Farmland, Hermiston, and River datasets, respectively.
Coupling the Relationship between Land Subsidence and Groundwater Level, Ground Fissures in Xi’an City Using Multi-Orbit and Multi-Temporal InSAR
Authors: Zhang Xing , Cheng Zhengfeng , Xu Bei , Gui Rong , Hu Jun , Yang Changjiang , Yang Qiuhong , Xiong Tao
Published: July 2023

The Xi’an region of China has been suffering from groundwater depletion, ground fissure hazards, and surface subsidence for a long time. Due to the complex tectonics and frequent human and natural activities, land deformation in the region is aggravated, posing a threat to infrastructure and human life. This study adopted the multi-orbit and multi-temporal InSAR technology to measure multi-dimensional displacements and time-series displacements in Xi’an City. Through the multi-dimensional deformation verification, it was found that the control of groundwater flow direction by ground fissures is the cause of horizontal deformation. On the contrary, the flow direction of groundwater from west to east was inferred using multi-dimensional deformation. Further analysis was performed by calculating the deformation gradient of the cumulative deformation to obtain differential land subsidence and angular distortions, and it was quantitatively determined that the threshold for the generation of ground fissures caused by differential subsidence is 1/500. Then, through the mutual verification of the time series data and the groundwater level, a positive correlation was obtained. However, due to the inconsistent geological conditions and soil layers at the monitoring positions of Well 2 and Well 3, the lag time was 64 days and 4 days, respectively. Finally, the relationship between the surface deformation and the groundwater in the sustained uplift areas was explored. The Well 1 groundwater-level data with a monitoring period of 22 years and the corresponding monitoring points’ time series data were modeled; it was concluded that, in the future, the groundwater level will continue to rise and surface deformation will mainly increase, without a slowing trend. Therefore, research on the impact of surface uplift on infrastructure should be strengthened. By quantifying the relationship between land subsidence, ground fissures, and the groundwater level in Xi’an, the results of this study provide a reference for groundwater monitoring and management.
Industry 5 and the Human in Human-Centric Manufacturing
Authors: Briken Kendra , Moore Jed , Scholarios Dora , Rose Emily , Sherlock Andrew
Published: July 2023

Industry 4 (I4) was a revolutionary new stage for technological progress in manufacturing which promised a new level of interconnectedness between a diverse range of technologies. Sensors, as a point technology, play an important role in these developments, facilitating human–machine interaction and enabling data collection for system-level technologies. Concerns for human labour working in I4 environments (e.g., health and safety, data generation and extraction) are acknowledged by Industry 5 (I5), an update of I4 which promises greater attention to human–machine relations through a values-driven approach to collaboration and co-design. This article explores how engineering experts integrate values promoted by policy-makers into both their thinking about the human in their work and in their writing. This paper demonstrates a novel interdisciplinary approach in which an awareness of different disciplinary epistemic values associated with humans and work guides a systematic literature review and interpretive coding of practice-focussed engineering papers. Findings demonstrate evidence of an I5 human-centric approach: a high value for employees as “end-users” of innovative systems in manufacturing; and an increase in output addressing human activity in modelling and the technologies available to address this concern. However, epistemic publishing practices show that efforts to increase the effectiveness of manufacturing systems often neglect worker voice.
Non-Destructive Imaging of Defects Using Non-Cooperative 5G Millimeter-Wave Signals
Authors: Vakalis Stavros , Colon-Berrios Jorge R. , Chen Daniel , Nanzer Jeffrey A.
Published: July 2023

Recent developments in fifth-generation (5G) wireless communications networks are creating an increasingly crowded electromagnetic environment at microwave (3–30 GHz) and millimeter-wave (30–300 GHz) frequencies. Radiation at these bands can provide non-destructive testing of defects and shielded structures using non-ionizing signals. In an actual building setting where 5G millimeter-wave communications signals are present, passive imaging of the radiation that is propagating through a wall defect can take place by means of interferometric processing without emitting additional signals in an already-crowded spectrum. We investigate the use of millimeter-wave interferometric imaging of defects in building walls and shielded structures by capturing the transmission of 5G millimeter-wave signals through the defects. We experimentally explore the ability to image defects by capturing the transmission of 38 GHz signals through materials using a 24-element interferometric receiving array.
Efficient-Lightweight YOLO: Improving Small Object Detection in YOLO for Aerial Images
Authors: Hu Mengzi , Li Ziyang , Yu Jiong , Wan Xueqiang , Tan Haotian , Lin Zeyu
Published: July 2023

The most significant technical challenges of current aerial image object-detection tasks are the extremely low accuracy for detecting small objects that are densely distributed within a scene and the lack of semantic information. Moreover, existing detectors with large parameter scales are unsuitable for aerial image object-detection scenarios oriented toward low-end GPUs. To address this technical challenge, we propose efficient-lightweight You Only Look Once (EL-YOLO), an innovative model that overcomes the limitations of existing detectors and low-end GPU orientation. EL-YOLO surpasses the baseline models in three key areas. Firstly, we design and scrutinize three model architectures to intensify the model’s focus on small objects and identify the most effective network structure. Secondly, we design efficient spatial pyramid pooling (ESPP) to augment the representation of small-object features in aerial images. Lastly, we introduce the alpha-complete intersection over union (α-CIoU) loss function to tackle the imbalance between positive and negative samples in aerial images. Our proposed EL-YOLO method demonstrates a strong generalization and robustness for the small-object detection problem in aerial images. The experimental results show that, with the model parameters maintained below 10 M while the input image size was unified at 640 × 640 pixels, the APS of the EL-YOLOv5 reached 10.8% and 10.7% and enhanced the APs by 1.9% and 2.2% compared to YOLOv5 on two challenging aerial image datasets, DIOR and VisDrone, respectively.
CoSOV1Net: A Cone- and Spatial-Opponent Primary Visual Cortex-Inspired Neural Network for Lightweight Salient Object Detection
Authors: Ndayikengurukiye Didier , Mignotte Max
Published: July 2023

Salient object-detection models attempt to mimic the human visual system’s ability to select relevant objects in images. To this end, the development of deep neural networks on high-end computers has recently achieved high performance. However, developing deep neural network models with the same performance for resource-limited vision sensors or mobile devices remains a challenge. In this work, we propose CoSOV1net, a novel lightweight salient object-detection neural network model, inspired by the cone- and spatial-opponent processes of the primary visual cortex (V1), which inextricably link color and shape in human color perception. Our proposed model is trained from scratch, without using backbones from image classification or other tasks. Experiments on the most widely used and challenging datasets for salient object detection show that CoSOV1Net achieves competitive performance (i.e., Fβ=0.931 on the ECSSD dataset) with state-of-the-art salient object-detection models while having a low number of parameters (1.14 M), low FLOPS (1.4 G) and high FPS (211.2) on GPU (Nvidia GeForce RTX 3090 Ti) compared to the state of the art in lightweight or nonlightweight salient object-detection tasks. Thus, CoSOV1net has turned out to be a lightweight salient object-detection model that can be adapted to mobile environments and resource-constrained devices.
Improvement of Fault Ride-Through Capability of Grid Connected Wind Turbine Based on a Switched Reluctance Generator Using a Dynamic Voltage Restorer
Authors: AlGhamdi Saeed A.
Published: July 2023

This paper presents an improvement to the fault ride-through (FRT) capabilities for a wind turbine that employs a switched reluctance generator (SRG) using a dynamic voltage restorer (DVR). The wind turbine may be disconnected from the grid by voltage sag, swell, and faulty line voltage in the grid. To improve the stator voltage of an SRG during grid failures, the DVR is applied to inject voltage at the point of common coupling (PCC) into the grid voltage. A control strategy for the DVR based on fuzzy logic controller (FLC) is proposed in this study to improve the FRT capability and meet the grid codes while avoiding the disconnection of the turbine from the grid. MATLAB/SIMULINK simulation validated the effectiveness and performance of this approach under three test cases: balanced sag, unbalanced sag, and a single line-to-ground fault. In addition, the total harmonic distortions utilizing different controllers were compared in sag mode. Furthermore, the simulation results exhibited significant improvement in transient and steady-state response, thus verifying the effectiveness of the control strategy compared to traditional methods.
The Effects of System Pressure on Low-Carbon Innovation in Firms: A Case Study from China
Authors: Jiang Yuguo , Ampaw Enock Mintah , Wu Hongyan , Zhao Lan
Published: July 2023

With the signing and implementation of the Paris Agreement, low-carbon models have become the general trend for future development. In this context, many countries have successively introduced relevant low-carbon systems within their companies. These systems bring a lot of pressure on traditional manufacturing enterprises. This study deeply explores the influential mechanism of system pressure on the theory of low-carbon innovation of enterprises. It analyzed 328 questionnaires from 107 enterprises in China by using theoretical models based on the upper echelons theory and the dynamic capability theory. The results of the study indicate that (1) system pressure significantly promotes enterprises’ low-carbon innovation; (2) low-carbon dynamic capability mediates between system pressure and enterprise low-carbon innovation; (3) executives’ low-carbon awareness positively moderates the relationship between system pressure and low-carbon dynamic capability; (4) executive low-carbon awareness moderates the intermediary role of low-carbon dynamic capability between system pressure and enterprise low-carbon innovation. Theoretically, this study deepens empirical studies on system pressure and enterprise low-carbon innovation. This study contributes to the application of the upper echelons theory, dynamic ability theory and enterprise behavior theory in the field of low-carbon research. In view of this, this study intends to serve as a reference material for future low-carbon innovation-related research and a guide for the low-carbon management of enterprises.
Grain Size Characteristics of Surface Sediments and Their Migration Trends in the Nearshore Waters of East Guangdong
Authors: Wang Hongbing , Wu Yuxi , Wan Xiaoming , Xia Lu , Wang Si
Published: July 2023

By collecting surface sediment samples from 158 stations in the near-shore waters of eastern Guangdong, grain size analysis and grain size parameter calculations were performed to explore the characteristics and migration trends of surface sediments in the area. The analysis of the grain size results showed that the surface sediments in the nearshore waters of east Guangdong could be classified into nine sediment types, mainly including seven types of gravel sand ((g)S), gravel muddy sand ((g)mS), gravelly mud ((g)M), sand (S), silty sand (zS), sandy silt (sZ) and silt (Z). The relative percentages of gravel, sand, silt and mud were 0.7%, 40.56%, 46.7% and 12.04%, respectively. The average grain size varied from −2φ to 8φ, with an average of 4.94φ. The selection coefficient ranged from 0.44 to 3.78, with an average value of 1.8. The skewness distribution ranged from −0.34 to 0.67, with an average value of 0.07. By extracting and analyzing the spatial distribution information of grain size in the study area, using the Gao–Collins migration trend analysis method and incorporating dynamic factors such as tidal currents and waves, the transport direction and trend of surface sediments in the study area could be analyzed and inferred. The results show that the surface sediment migration trend was significant, migration on the north side of Nan’ao Island was in an east-to-west direction, and the sediment of Yifeng River was mainly deposited to the sand spout at the mouth of Lianyang River. After southward transport from the Houjiang waterway, the migration was mainly southeastward and the trend was quite significant until the 20 m isobath, where the trend gradually decreased. The sediments of the Rongjiang River were mainly deposited outside the mouth of Niutian Yang and Rongjiang River, and the surface sediments of Guang’ao Bay and Haimen Bay migrated in the northwest–southeast direction. After the 30 m isobath, the southeast corner of the study area migrated in the southeast–south direction. This sediment transport pattern revealed by the grain size migration trend is in good agreement with the physical and hydrodynamic conditions of the study area and provides an important reference for decisions regarding port dredging and waterway management in the area.
Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation
Authors: Bouchekara Houssem R. E. H. , Sha’aban Yusuf A. , Shahriar Mohammad S. , Abdullah Saad M. , Ramli Makbul A.
Published: July 2023

In this paper, a small-scale PV/Wind/Diesel Hybrid Microgrid System (HMS) for the city of Yanbu, Saudi Arabia is optimally designed, considering the uncertainties of renewable energy resources and battery degradation. The optimization problem is formulated as a multi-objective one with two objective functions: the Loss of Power Supply Probability (LPSP) and the Cost of Electricity (COE). An Improved Decomposition Multi-Objective Evolutionary Algorithm (IMOEAD) is proposed and applied to solve this problem. In this approach, different decomposition schemes are combined effectively to achieve better results than the classical MOEA/D approach. Twelve case studies are investigated based on different scenarios and different numbers of houses (5 and 10 houses). Each time, the suggested approach produced a set of solutions that formed a Pareto front (PF). Considering a variety of parameters, the optimal compromise option can be selected by the designer from the PF.
Industry 4.0 Technologies Promote Micro-Level Circular Economy but Neglect Strong Sustainability in Textile Industry
Authors: Oliveira Neto Geraldo Cardoso de , Pinto Luiz Fernando Rodrigues , de Silva Dirceu , Rodrigues Flavio Luiz , Flausino Fabio Richard , Oliveira Douglas Eldo Pereira de
Published: July 2023

Large textile industries are deploying Industry 4.0 Technologies (I4.0T) aiming to develop a micro-level circular economy (CECP), considering cleaner production practices as a strategic tool. However, due to the environmental impact generated by the textile industry, it has not yet achieved Strong Sustainability (SS), denoting an important path to be pursued by managers and shareholders in view of meeting the 2030 agenda. With this, the objective of this study is to evaluate whether the adoption of I4.0T promotes CECP-driving SS actions in large textile industries located in Brazil. A survey was the research method adopted, and for data analysis, structural equation modeling was used to test the hypotheses and Pearson correlation between variables. It was concluded that the adoption of I4.0T promotes CECP. However, they neglect SS actions. Facilitators for CECP practices were big data, augmented reality, and autonomous robots. In terms of SS, I4.0T has a low impact on increasing resource consumption efficiency, reusing waste as input in other processes, and increasing access to commodities. This research contributes to the linking I4.0T, CECP, and SS theory. Moreover, with the dissemination of knowledge to managers about the I4.0T that generates the CECP, it is possible to develop sustainable strategies in operations. However, to move in this direction, it is essential that there is a collective effort of the government, companies, and society, starting by raising awareness about the importance of SS in the textile sector.
The Effect of Digitalization on Youth Unemployment for EU Countries: Treat or Threat?
Authors: Başol Oğuz , Sevgi Hüseyin , Yalçın Esin Cumhur
Published: July 2023

Unemployment affects approximately 73 million young people, representing 17.9% of the global youth workforce in 2022. Although there are several policies to prevent youth unemployment, digitalization seems to be one of the strongest. This research focuses on the impact of the Digital Economy and Society Index (DESI) on youth unemployment in 27 European countries from 2018 to 2021. For the research, the “Digital Economy and Society Index” was measured with four sub-dimensions. These were “connectivity”, “digital public services”, “human capital”, and “digital technology integration”. Additionally, “Youth Unemployment” was measured with three sub-dimensions. These included the “long-term youth unemployment rate”, “not in education, employment, or training rate”, and “youth unemployment rate”. The analyses were conducted using SmartPLS 4 and the results showed that the DESI reduces youth unemployment each year. According to the findings, the indicators of DESI can be an effective strategy for combating youth unemployment in European countries.
Sustainable Composites: A Review with Critical Questions to Guide Future Initiatives
Authors: Hubbe Martin A.
Published: July 2023

Composites, which have become very common in mass-produced items, have the potential to outperform similar materials made from any one of their individual components. This tutorial review article considers published studies that shine a light on what is required for such structures to earn the name “sustainable”. The focus is on a series of questions that deal with such issues as the carbon footprint, other life-cycle impacts, durability, recyclability without major loss of value, reusability of major parts, and the practical likelihood of various end-of-life options. To achieve the needed broader impacts of limited research dollars, it is important that researchers choose their research topics carefully. Among a great many possible options for preparing truly eco-friendly composite materials, it will be important to focus attention on the much smaller subset of technologies that have a high probability of commercial success and large-scale implementation.
AI and Digital Transformation in Higher Education: Vision and Approach of a Specific University in Vietnam
Authors: Quy Vu Khanh , Thanh Bui Trung , Chehri Abdellah , Linh Dao Manh , Tuan Do Anh
Published: July 2023

The Fourth Industrial Revolution is opening up new opportunities and challenges for all industries, professions, and fields, aiming to bring humanity more optimal tools and services. During the Fourth Industrial Revolution, digital transformation has been one of the most critical problems. Artificial Intelligence (AI) and the Internet of Things (IoT) are two technologies that have the potential to cause the biggest breakout to evolve in the educational domain. In recent years, digital transformation has seen implementation across all sectors, including education, healthcare, agriculture, transportation, and other smart ecosystems. Among those areas, education, especially higher education, is among the most challenging due to the diversity in training programs, duration, and subjects. The Internet of Things makes it possible to create smart and ubiquitous learning environments, while artificial intelligence can completely transform the way we learn and teach. In this paper, we present the digital transformation process in higher education in Vietnam and internationally and analyze some characteristics of Vietnamese higher education in the digital transformation process. Moreover, we present the vision, approach, and challenges to digital transformation at universities of low- and middle-income countries from the perspective of the Hung Yen University of Technology and Education in Vietnam.
Adaption and Tolerance in Built Environment—An Evaluation of Environmental Sensation, Acceptance and Overall Indoor Environmental Quality (IEQ) in a Subtropical Region
Authors: Tsang Tsz-Wun , Mui Kwok-Wai , Wong Ling-Tim
Published: July 2023

The relationship between environmental sensations and acceptance in the indoor environment has yet to be fully explored or quantified. This study is the first in the literature that examines these relationships in thermal comfort, indoor air quality, aural comfort, visual comfort, and overall indoor environmental quality (IEQ). Using a regional IEQ database, the relationship between occupants’ sensation and acceptance of individual environmental aspects was investigated. The results suggest that building occupants had high tolerances towards indoor air quality and aural and visual discomforts, while cold sensations tended to elicit environmental discomfort. Furthermore, the study developed machine learning models with imbalanced data treatment to predict overall IEQ acceptance based on both sensation and acceptance of individual IEQ domains. These models accounted for the influence of environmental adaptation and tolerance on overall IEQ satisfaction determination. They accurately predicted unseen data, indicating high model generalizability and robustness. Overall, the study has practical implications for improving building performance and provides insights to better understand the relationship between environmental sensations and occupants’ acceptance, which should be considered in building design and operation.
A Study on the Spatial-Temporal Evolution and Problem Area Identification of High-Quality Urban Development in the Central Region
Authors: Zhao Meilin , Zhang Rui , Liu Hong , Zhang Xiaoyi , Wang Yue
Published: July 2023

The central region is an important strategic area that encompasses the east and the west and connects the south and the north. Promoting high-quality urban development in the central region plays a positive role in comprehensively upgrading the central rising strategy and realizing coordinated regional development. Based on the measurement index system result of the level of high-quality urban development in the central region, this study describes the regional gap and its dynamic evolution through the Dagum Gini coefficient and the kernel density function. In addition, it analyzes the causes of the gap in high-quality development of cities in the central region from the perspective of problem area identification. The result shows that the overall high-quality development of cities in the central region is increasing, with high-level cities clustering around the core cities. The relative regional disparities continue to narrow, but the absolute differences tend to expand. The super-variable density tends to be the main source of the overall difference, and the high-quality development of cities in each region is positively spatial correlated with each other. At present, the lagging economic development and outcomes sharing are the main obstacles to the high-quality development of cities in the central region.
Analysis of E-Learning System Use Using Combined TAM and ECT Factors
Authors: Tawafak Ragad M. , Al-Rahmi Waleed Mugahed , Almogren Abeer S. , Al Adwan Muhammad Noor , Safori Amjad , Attar Razaz Waheeb , Habes Mohammed
Published: July 2023

The use of e-learning systems has become widespread in higher education institutions in Oman. However, understanding of factors that influence student acceptance and usage of these systems is lacking. This study combined the factors of the Technology Acceptance Model (TAM) and Expectation–Confirmation Theory (ECT) to examine the acceptance and use of e-learning systems by students in Omani HEIs. A survey was conducted with 220 students from Al-Buraimi University College in Oman to collect data on perceived usefulness, perceived ease of use, behavioral intention, and e-learning system use. A model was created by merging eight interactions between TAM, ECT, and seven variables. The results showed that perceived usefulness and ease of use were significant predictors of students’ intention to use e-learning systems, and behavioral intention had a direct effect on the actual use of e-learning systems. These findings provide valuable insights for e-learning system designers, developers, and educators in Oman and similar contexts to design and implement e-learning systems that meet student needs and expectations.
The Cornell COVID-19 Testing Laboratory: A Model to High-Capacity Testing Hubs for Infectious Disease Emergency Response and Preparedness
Authors: Laverack Melissa , Tallmadge Rebecca L. , Venugopalan Roopa , Sheehan Daniel , Ross Scott , Rustamov Rahim , Frederici Casey , Potter Kim S. , Elvinger François , Warnick Lorin D. , Koretzky Gary A. , Lawlis Robert , Plocharczyk Elizabeth , Diel Diego G.
Published: July 2023

The unprecedented COVID-19 pandemic posed major challenges to local, regional, and global economies and health systems, and fast clinical diagnostic workflows were urgently needed to contain the spread of SARS-CoV-2. Here, we describe the platform and workflow established at the Cornell COVID-19 Testing Laboratory (CCTL) for the high-throughput testing of clinical samples from the university and the surrounding community. This workflow enabled efficient and rapid detection and the successful control of SARS-CoV-2 infection on campus and its surrounding communities. Our cost-effective and fully automated workflow enabled the testing of over 8000 pooled samples per day and provided results for over 2 million samples. The automation of time- and effort-intensive sample processing steps such as accessioning and pooling increased laboratory efficiency. Customized software applications were developed to track and store samples, deconvolute positive pools, track and report results, and for workflow integration from sample receipt to result reporting. Additionally, quality control dashboards and turnaround-time tracking applications were built to monitor assay and laboratory performance. As infectious disease outbreaks pose a constant threat to both human and animal health, the highly effective workflow implemented at CCTL could be modeled to establish regional high-capacity testing hubs for infectious disease preparedness and emergency response.
Risk Assessment of the Possible Intermediate Host Role of Pigs for Coronaviruses with a Deep Learning Predictor
Authors: Jiang Shuyang , Zhang Sen , Kang Xiaoping , Feng Ye , Li Yadan , Nie Maoshun , Li Yuchang , Chen Yuehong , Zhao Shishun , Jiang Tao , Li Jing
Published: July 2023

Swine coronaviruses (CoVs) have been found to cause infection in humans, suggesting that Suiformes might be potential intermediate hosts in CoV transmission from their natural hosts to humans. The present study aims to establish convolutional neural network (CNN) models to predict host adaptation of swine CoVs. Decomposing of each ORF1ab and Spike sequence was performed with dinucleotide composition representation (DCR) and other traits. The relationship between CoVs from different adaptive hosts was analyzed by unsupervised learning, and CNN models based on DCR of ORF1ab and Spike were built to predict the host adaptation of swine CoVs. The rationality of the models was verified with phylogenetic analysis. Unsupervised learning showed that there is a multiple host adaptation of different swine CoVs. According to the adaptation prediction of CNN models, swine acute diarrhea syndrome CoV (SADS-CoV) and porcine epidemic diarrhea virus (PEDV) are adapted to Chiroptera, swine transmissible gastroenteritis virus (TGEV) is adapted to Carnivora, porcine hemagglutinating encephalomyelitis (PHEV) might be adapted to Primate, Rodent, and Lagomorpha, and porcine deltacoronavirus (PDCoV) might be adapted to Chiroptera, Artiodactyla, and Carnivora. In summary, the DCR trait has been confirmed to be representative for the CoV genome, and the DCR-based deep learning model works well to assess the adaptation of swine CoVs to other mammals. Suiformes might be intermediate hosts for human CoVs and other mammalian CoVs. The present study provides a novel approach to assess the risk of adaptation and transmission to humans and other mammals of swine CoVs.