bluuebunny/crossref_metadata_2025 huggingface dataset:
A γ-Glutamyl Transpeptidase (GGT)-Triggered Charge Reversal Drug-Delivery System for Cervical Cancer Treatment: In Vitro and In Vivo Investigation
Authors: Fu Jingxin , Lu Likang , Li Manzhen , Guo Yaoyao , Han Meihua , Guo Yifei , Wang Xiangtao
Published: April 2023

Neutral/negatively charged nanoparticles are beneficial to reduce plasma protein adsorption and prolong their blood circulation time, while positively charged nanoparticles easily transverse the blood vessel endothelium into a tumor and easily penetrate the depth of the tumor via transcytosis. Γ-Glutamyl transpeptidase (GGT) is overexpressed on the external surface of endothelial cells of tumor blood vessels and metabolically active tumor cells. Nanocarriers modified by molecules containing γ-glutamyl moieties (such as glutathione, G-SH) can maintain a neutral/negative charge in the blood, as well as can be easily hydrolyzed by the GGT enzymes to expose the cationic surface at the tumor site, thus achieving good tumor accumulation via charge reversal. In this study, DSPE-PEG2000-GSH (DPG) was synthesized and used as a stabilizer to generate paclitaxel (PTX) nanosuspensions for the treatment of Hela cervical cancer (GGT-positive). The obtained drug-delivery system (PTX-DPG nanoparticles) was 164.6 ± 3.1 nm in diameter with a zeta potential of −9.85 ± 1.03 mV and a high drug-loaded content of 41.45 ± 0.7%. PTX-DPG NPs maintained their negative surface charge in a low concentration of GGT enzyme (0.05 U/mL), whereas they showed a significant charge-reversal property in the high-concentration solution of GGT enzyme (10 U/mL). After intravenous administration, PTX-DPG NPs mainly accumulated more in the tumor than in the liver, achieved good tumor-targetability, and significantly improved anti-tumor efficacy (68.48% vs. 24.07%, tumor inhibition rate, p < 0.05 in contrast to free PTX). This kind of GGT-triggered charge-reversal nanoparticle is promising to be a novel anti-tumor agent for the effective treatment of such GGT-positive cancers as cervical cancer.
Responsible Innovation in Plant Breeding: The Case of Hybrid Potato Breeding
Authors: Stemerding Dirk , Beumer Koen , Edelenbosch Rosanne , Swart Jac. A. A. , de Vries Michiel E. , ter Steeg Emily , Almekinders Conny J. M. , Lindhout Pim , van Dijk Luuk C. M. , Struik Paul C.
Published: April 2023

As an emerging innovation, hybrid potato breeding raises high expectations about faster variety development and clean true potato seed as a new source of planting material. Hybrid breeding could, therefore, substantially contribute to global food security and other major sustainable development goals. However, its success will not only depend on the performance of hybrid potato in the field, but also on a range of complex and dynamic system conditions. This article is based on a multidisciplinary project in which we have studied the innovation dynamics of hybrid potato breeding and explored how these dynamics may shape the future of hybrid potato. Inspired by the approach of responsible innovation, we closely involved key players in the Dutch and international potato sector and other relevant actors in thinking about these potato futures. An important and recurrent theme in our work is the tension between the predominant commercial innovation dynamics in plant breeding and promises to respond to the global challenges of food security, agrobiodiversity and climate change. In this article, we, therefore, discuss responsible innovation strategies in (hybrid) potato breeding, which may help to bridge this tension and finally reflect on the implications for the field of plant breeding in general.
Current Progress and Future Prospect of Wheat Genetics Research towards an Enhanced Nitrogen Use Efficiency
Authors: Zhao Yun , Islam Shahidul , Alhabbar Zaid , Zhang Jingjuan , O’Hara Graham , Anwar Masood , Ma Wujun
Published: April 2023

To improve the yield and quality of wheat is of great importance for food security worldwide. One of the most effective and significant approaches to achieve this goal is to enhance the nitrogen use efficiency (NUE) in wheat. In this review, a comprehensive understanding of the factors involved in the process of the wheat nitrogen uptake, assimilation and remobilization of nitrogen in wheat were introduced. An appropriate definition of NUE is vital prior to its precise evaluation for the following gene identification and breeding process. Apart from grain yield (GY) and grain protein content (GPC), the commonly recognized major indicators of NUE, grain protein deviation (GPD) could also be considered as a potential trait for NUE evaluation. As a complex quantitative trait, NUE is affected by transporter proteins, kinases, transcription factors (TFs) and micro RNAs (miRNAs), which participate in the nitrogen uptake process, as well as key enzymes, circadian regulators, cross-talks between carbon metabolism, which are associated with nitrogen assimilation and remobilization. A series of quantitative genetic loci (QTLs) and linking markers were compiled in the hope to help discover more efficient and useful genetic resources for breeding program. For future NUE improvement, an exploration for other criteria during selection process that incorporates morphological, physiological and biochemical traits is needed. Applying new technologies from phenomics will allow high-throughput NUE phenotyping and accelerate the breeding process. A combination of multi-omics techniques and the previously verified QTLs and molecular markers will facilitate the NUE QTL-mapping and novel gene identification.
Three-Dimensional Stress Fields in Thick Orthotropic Plates with Sharply Curved Notches under In-Plane and Out-of-Plane Shear
Authors: Pontefisso Alessandro , Pastrello Matteo , Zappalorto Michele
Published: April 2023

In this paper, an analytical solution for the stress fields in the close neighbourhoods of radiused notches in thick orthotropic plates under shear loading and twisting is provided. In the first step, the equations of the three-dimensional theory of elasticity are successfully reduced to two uncoupled equations in two-dimensional space. Later, the 3D stress field solution for orthotropic plates with radiused notches is presented and its degree of accuracy is discussed by comparing theoretical results and numerical data from 3D FE analyses. The solution proposed can be satisfactorily used to characterise the stress field in plates made with polymeric composite materials, such as fibre-reinforced polymers and natural composites.
Polycaprolactone Electrospun Nanofiber Membrane with Skin Graft Containing Collagen and Bandage Containing MgO Nanoparticles for Wound Healing Applications
Authors: Nikfarjam Sadegh , Aldubaisi Yaqeen , Swami Vivek , Swami Vinay , Xu Gang , Vaughan Melville B. , Wolf Roman F. , Khandaker Morshed
Published: April 2023

The objective of this study was to create a nanofiber-based skin graft with an antimicrobial bandage that could accelerate the healing of an open wound while minimizing infection. To this end, we prepared a bi-layer construct where the top layer acts as bandage, and the bottom layer acts as a dermal equivalent graft. A collagen (CG) gel was combined without and with an electrospun polycaprolactone (PCL) membrane to prepare CG and CG-PCL dermal equivalent constructs. The antibacterial properties of PCL with and without an antibacterial agent (MgO nanoparticles) against Staphylococcus aureus (ATCC 6538) was also examined. Human dermal fibroblasts were cultured in each construct to make the dermal equivalent grafts. After culturing, keratinocytes were plated on top of the tissues to allow growth of an epidermis. Rheological and durability tests were conducted on in vitro dermal and skin equivalent cultures, and we found that PCL significantly affects CG-PCL graft biological and mechanical strength (rheology and durability). PCL presence in the dermal equivalent allowed sufficient tension generation to activate fibroblasts and myofibroblasts in the presence of transforming growth factor-beta. During culture of the skin equivalents, optical coherence tomography (OCT) showed layers corresponding to dermal and epidermal compartments in the presence or absence of PCL; this was confirmed after fixed specimens were histologically sectioned and stained. MgO added to PCL showed antibacterial activity against S. aureus. In vivo animal studies using a rat skin model showed that a polycaprolactone nanofiber bandage containing a type I collagen skin graft has potential for wound healing applications.
Interfacial Polymerization on Polyethersulfone Ultrafiltration Membrane to Prepare Nanofiltration Layers for Dye Separation
Authors: Liu Lulu , Wu Weilin , Jin Xiaogang , Luo Xiong , Wu Lili
Published: April 2023

Nanofiltration membranes are of great significance to the treatment of dye wastewater. Interfacial polymerization is a widely used method to fabricate nanofiltration membranes. In this study, the interaction of tannic acid-assisted polyethylene polyamine (PEPA) with terephthalaldehyde (TPAL) was performed on PES ultrafiltration membranes using novel nitrogen-rich amine monomers and relatively less reactive aldehyde-based monomers. A new nanofiltration membrane ((T-P-T)/PES) was prepared by interfacial polymerization. Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy, and scanning electron microscopy were used to analyze the elemental composition, bonding state, and surface morphology of the membrane surface. The effects of the PEPA deposition time, TPAL concentration, interfacial reaction time, and curing time on the nanofiltration layer were investigated. The modified membrane, prepared under optimal conditions, showed strong dye separation ability. The permeation of the modified membrane could reach 68.68 L·m−2·h−1·bar−1, and the rejection of various dyes was above 99%. In addition, the (T-P-T)/PES membrane showed good stability during long-term dye separation.
Effect of Extruder Type in the Interface of PLA Layers in FDM Printers: Filament Extruder Versus Direct Pellet Extruder
Authors: Pagés-Llobet Antoni , Espinach Francesc X. , Julián Fernando , Oliver-Ortega Helena , Méndez José Alberto
Published: April 2023

FDM (Fused Deposition Modeling) is one of the most used and industrially applied additive manufacturing processes due to its fast prototyping and manufacturing, simplicity, and low cost of the equipment. However, the mechanical properties of the printed products have a large dependence on orientation and interface strength between layers which is mainly related to the thermal union obtained. This thermal union has a large dependence on the melting and cooling down process. Additionally, the materials used must be extruded in a continuous filament before their use, which limits the materials used. However, a pellet extruder could be used directly in the printing equipment, avoiding filament extrusion. In this work, specimens of PLA (Poly(lactic acid)) with different bead orientations have been produced via filament or pellet extrusion to compare the effect of the different melting processes in the manufacturing methodology. Pellet extruded specimens showed higher infill and mechanical properties. These results were related to better adhesion between layers due to the longer melting and cooling process. The result was confirmed using DSC and XRD techniques, where a higher crystallinity was observed. A bicomponent specimen (50% pellet–50% filament) was prepared and tested, showing higher mechanical results than expected, which was, again, due to the better thermal union obtained in the pellet extruder.
Biodegradable Polycaprolactone Fibers with Silica Aerogel and Nanosilver Particles Produce a Coagulation Effect
Authors: Ayvazoğlu Büşra Şengel , Ceylan Muhammet , Turan Aybüke A. Isbir , Yılmaz Elif Burcu
Published: April 2023

Poly-ε-caprolactone (PCL) is a biodegradable aliphatic polyester that can be used in the field of biomaterials. Electrospinning is the name given to the process of producing micro and nanoscale fibers using electrostatically charged polymeric solutions under certain conditions. Almost all synthetic and naturally occurring polymers can undergo electrospinning using suitable solvents or mixtures prepared in certain proportions. In this study, silica aerogels were obtained by the sol-gel method. PCL-silica aerogel fibers were synthesized by adding 0.5, 1, 2, and 4% ratios in the PCL solution. Blood contact analysis was performed on the produced fibers with UV-VIS. According to the results obtained, 0.5, 1, 2, and 4% nano-silver were added to the fiber-containing 4% aerogel. Then, SEM-EDS and FTIR analyses were performed on all fibers produced. Antimicrobial tests were performed on fibers containing nano-silver. As a result, high-performance blood coagulation fibers were developed using PCL with aerogel, and an antimicrobial effect was achieved with nano-silver particles. It is thought that the designed surface will be preferred in wound dressing and biomaterial in tissue engineering, as it provides a high amount of cell adhesion with a small amount of blood and contains antimicrobial properties.
Optimization of a Mucoadhesive Vaginal Gel Containing Clotrimazole Using a D-Optimal Experimental Design and Multivariate Analysis
Authors: Dinte Elena , Iovanov Rares Iuliu , Bodoki Andreea Elena , Colosi Ioana Alina , Colosi Horatiu Alexandru , Tosa Nicoleta , Vostinaru Oliviu , Tomuta Ioan
Published: April 2023

The aim of this study was to develop a suitable clotrimazole (CLT)-loaded mucoadhesive vaginal gel (CLT-MVG) for topical applications in vaginal candidiasis. Ten CLT-MVG formulations were prepared, consisting of mixtures of acid polyacrylic (Carbopol 940) and polyethene oxides, Sentry Polyox WSRN 1105 or 750, according to an experimental D-optimal design, and CLT was suspended at a ratio of 1%. The prepared CLT-MVG formulations were studied in vitro, and the formulation containing Carbopol 940 0.89% combined with PEO 1105 1.39% was identified with the optimal rheological and in vitro bioadhesion properties, ensuring the prolonged release of CLT, with a similarity factor greater than 50, indicating dissolution profile similarity for three batches of the optimized formulation. This optimized formulation showed a pH in the tolerance range, and an adequate ex vivo mucoadhesion time, while the FT-IR studies revealed no interactions between the excipients and CLT. The microscopic analysis identified a mean particle size of suspended CLT of 5.24 ± 0.57 μm. The in vitro antifungal activity of the optimized formulation was tested on twenty strains of Candida albicans and proved to be better compared to a marketed clotrimazole preparation, showing a greater inhibition effect (p < 0.05). The optimized formulation could be a good candidate for the local treatment of vaginal mycosis.
Polyketone-Based Anion-Exchange Membranes for Alkaline Water Electrolysis
Authors: Racchi Ottavia , Baldassari Rebecca , Araya-Hermosilla Esteban , Mattoli Virgilio , Minei Pierpaolo , Pozio Alfonso , Pucci Andrea
Published: April 2023

Anion-exchange membranes (AEMs) are involved in a wide range of applications, including fuel cells and water electrolysis. A straightforward method for the preparation of efficient AEMs consists of polymer functionalization with robust anion-exchange sites. In this work, an aliphatic polyketone was functionalized with 1-(3-aminopropyl)imidazole through the Paal–Knorr reaction, with a carbonyl (CCO %) conversion of 33%. The anion-exchange groups were generated by the imidazole quaternization by using two different types of alkyl halides, i.e., 1,4-iodobutane and 1-iodobutane, with the aim of modulating the degree of crosslinking of the derived membrane. All of the membranes were amorphous (Tg ∼ 30 °C), thermally resistant up to 130 °C, and had a minimum Young’s modulus of 372 ± 30 MPa and a maximum of 86 ± 5 % for the elongation at break for the least-crosslinked system. The ionic conductivity of the AEMs was determined at 25 °C by electrochemical impedance spectroscopy (EIS), with a maximum of 9.69 mS/cm, i.e., comparable with that of 9.66 mS/cm measured using a commercially available AEM (Fumasep-PK-130). Future efforts will be directed toward increasing the robustness of these PK-based AEMs to meet all the requirements needed for their application in electrolytic cells.
Correction: Karpova et al. A Feature of the Crystalline and Amorphous Structure of Ultra Thin Fibers Based on Poly(3-hydroxybutyrate) (PHB) Containing Minor Concentrations of Hemin and a Complex of Tetraphenylporphyrin with Iron. Polymers 2022, 14, 4055
Authors: Karpova Svetlana , Varyan Ivetta , Olkhov Anatoly , Tyubaeva Polina , Popov Anatoly
Published: April 2023

Addition of an Author [...]
Technological Modernizations in the Industry 5.0 Era: A Descriptive Analysis and Future Research Directions
Authors: Alojaiman Bader
Published: April 2023

Unexpected instances have posed challenges to production lines over the last few years. The latest COVID-19 global epidemic is one notable example. In addition to its social impact, the virus has destroyed the traditional industrial production system. Industry 4.0 requires adapting to changing prerequisites with adaptability. However, the next movement, Industry 5.0, has emerged in recent years. Industry 5.0 takes a more coordinated approach than Industry 4.0, with increased collaboration among humans and machines. With a human-centered strategy, Industry 5.0 improves Industry 4.0 for greater sustainability and resilience. The concept of Industry 4.0 is the interconnection via cyber-physical systems. Industry 5.0, also associated with systems enabled by Industry 4.0, discusses the relationship between “man and machine,” called robots or cobots. This paper discusses the industry 5.0 possibilities, the restrictions, and future analysis potentials. Industry 5.0 is a new paradigm change that tends to bring negotiated settlement because it places less prominence on technology and assumes that the possibilities for advancement are predicated on collaboration between humans and machines. This paper aims to examine the potential implementations of Industry 5.0. Once the current progress and problem were discovered, the previous research on the investigated topic was reviewed, research limitations were found, and the systematic analysis procedure was developed. The classifications of industry 5.0 and the sophisticated technology required for this industry revolution are the first subjects of discussion. There is additional discussion of the application domains enabled by Industry 5.0, such as healthcare, supply chain, production growth, cloud industrial production, and so on. The research also included challenges and problems investigated in this paper to understand better the issues caused by organizations among some robotic systems and individuals on the production lines.
Design of a RGB-Arduino Device for Monitoring Copper Recovery from PCBs
Authors: Morell Joan , Escobet Antoni , Dorado Antonio David , Escobet Teresa
Published: April 2023

The mobile phone industry, one of the fastest advancing sectors in production over the last few decades, has been associated with a high e-waste generation rate. Simultaneously, a high demand for the production of new electronic equipment has led to the scarcity of certain metals. In this context, many recent studies have focused on recovering certain metals from e-waste through the use of bioprocesses. Such recovery processes are based on the action of microorganisms that produce Fe(III) as an oxidant, in order to leach the copper contained in printed circuit boards. During the oxidation-reduction reaction between Fe(III) and metallic Cu, the color of the solution evolves from an initial reddish color, due to Fe(III), to a bluish-green color, due to the oxidized Cu. In this work, a hardware-software prototype is developed, through which the concentrations of the key analytes—Fe(III) and Cu(II)—can be determined in real time by monitoring the color of the solution. This is achieved through the use of a non-invasive system, taking into account the aggressiveness of the solutions used for the bioprocessing of electronic components. In the work presented herein, the evolution of the solution color during the bioprocessing of two different types of waste (i.e., electric cable and mobile phones) is analyzed and then compared with the results obtained for pure metallic copper. The results are validated through comparison of the predicted results with the outcomes of conventional procedures, including offline sampling and analysis of Cu(II) and Fe(III) through atomic absorption and UV-VIS spectroscopy, respectively. The developed monitoring system allows an algorithm to be designed that can fit the evolution of analyte concentrations without the need for sampling or the use of complex, tedious, and expensive analytic techniques. It is also worth noting that the monitoring system is not in direct contact with the solution (which is highly aggressive for the processing of electronic equipment), making the system more durable than classic sensors that must be submerged in the solution. The real-time nature of the obtained information allows for the development of control actions and for corrective measures to be taken without affecting the biomass involved in the process.
Analysis of the Characteristics and Causes of Land Degradation and Development in Coastal China (1982–2015)
Authors: Huang Ya , Li Guiping , Zhao Yong , Yang Jing , Li Yanping
Published: April 2023

Land degradation and development (LDD) is one of the important ecological issues in coastal China. This study analyzed the temporal and spatial changes of the LDD process in coastal China from 1982 to 2015 using the LDD index constructed from normalized NDVI and GPP data. The study also quantitatively evaluated the relative contributions of climate and human factors to LDD and explored their impact on LDD. The study’s findings indicate that coastal regions in China experienced a marked increase in land development during the study period, with 62.47% of the regions displaying a growth trend and only 7.03% exhibiting signs of land degradation. The impact of climate change on the change in LDD processes was limited, while human activities were the main driving force, with their impact becoming increasingly apparent over time. Human activities were the dominant contributor to the change in LDD in most regions, accounting for over 60% of the change. Fast urbanization led to a notable decrease in cropland, wetland, shrub, and grassland, with a substantial proportion of the affected cropland transformed into impervious surfaces, accounting for 91.31% of the total cropland conversion. These findings deepen our understanding of the LDD process and its driving factors in coastal China, providing valuable insights for developing effective policy interventions and implementing successful land restoration plans in the region.
An Autonomous Global Star Identification Algorithm Based on the Fast MST Index and Robust Multi-Order CCA Pattern
Authors: Zhu Zijian , Ma Yuebo , Dan Bingbing , Liu Enhai , Zhu Zifa , Yi Jinhui , Tang Yuping , Zhao Rujin
Published: April 2023

Star identification plays a key role in spacecraft attitude measurement. Currently, most star identification algorithms tend to perform well only in a scene without noise and are highly sensitive to noise. To solve this problem, this paper proposes a star identification algorithm based on the maximum spanning tree (MST) index and multi-order continuous cycle angle (CCA) intended for the lost-in-space mode. In addition, a neighboring star selection method named dynamic eight-quadrant (DEQ) is developed. First, the DEQ method is used to select high-confidence neighboring stars for the main star. Then, the star image is regarded as a graph, and the Prim algorithm is employed to construct the MST pattern for each guide star, which is then combined with the K vector index to perform the main star candidate search. Finally, the Jackard similarity voting for the multi-order CCA of the main star is used to identify the main star, and the global neighboring star identification is conducted by the multi-order CCA of neighboring stars. The simulated and real star images test results show that compared with five mainstream algorithms, when the position noise is 1 pixel, the number of false stars is five, the magnitude noise is 0.5, and the identification accuracy of the proposed algorithm is higher than 98.5%. Therefore, the proposed algorithm has excellent anti-noise ability in comparison to other algorithms.
Efficient Point Cloud Object Classifications with GhostMLP
Authors: Lai Hawking , Law K. L. Eddie
Published: April 2023

Efficient models capable of handling large numbers of data points in point cloud research are in high demand in computer vision. Despite recent advancements in 3D classification and segmentation tasks in point cloud processing, the deep learning PointNeXt and PointMLP models are plagued with heavy computation requirements with limited efficiencies. In this paper, a novel GhostMLP model for point clouds is thus introduced. It takes the advantages of the GhostNet design modules and uses them to replace the MLP layers in the existing PointMLP model. The resulting GhostMLP architecture achieves superior classification performance with lower computation requirements. Compared to the PointMLP, GhostMLP maintains sustainable performance with fewer parameters and lower FLOPs computations. Indeed, it outperforms PointMLP on the ScanObjectNN dataset, achieving 88.7% overall accuracy and 87.6% mean accuracy with only 6 million parameters and 7.2 GFLOPs—about half the resources required by PointMLP. At the same time, GhostMLP-S is introduced as a lightweight version which also outperforms PointMLP in performance. GhostMLP completes faster training and inference with GPU and is the best-performing method that does not require any extra training data in the ScanObjectNN benchmark. Efficient point cloud analysis is essential in computer vision, and we believe that GhostMLP has the potential to become a powerful tool for large-scale point cloud analysis.
A Reference-Free Method for the Thematic Accuracy Estimation of Global Land Cover Products Based on the Triple Collocation Approach
Authors: Chen Pengfei , Huang Huabing , Shi Wenzhong , Chen Rui
Published: April 2023

Global land cover (GLC) data are an indispensable resource for understanding the relationship between human activities and the natural environment. Estimating their classification accuracy is significant for studying environmental change and sustainable development. With the rapid emergence of various GLC products, the lack of high-quality reference data poses a severe risk to traditional accuracy estimation methods, in which reference data are always required. Thus, meeting the needs of large-scale, fast evaluation for GLC products becomes challenging. The triple collocation approach (TCCA) is originally applied to assess classification accuracy in earthquake damage mapping when ground truth is unavailable. TCCA can provide unbiased accuracy estimation of three classification systems when their errors are conditionally independent. In this study, we extend the idea of TCCA and test its performance in the accuracy estimation of GLC data without ground reference data. Firstly, to generate two additional classification systems besides the original GLC data, a k-order neighbourhood is defined for each assessment unit (i.e., geographic tiles), and a local classification strategy is implemented to train two classifiers based on local samples and features from remote sensing images. Secondly, to reduce the uncertainty from complex classification schemes, the multi-class problem in GLC is transformed into multiple binary-class problems when estimating the accuracy of each land class. Building upon over 15 million sample points with remote sensing features retrieved from Google Earth Engine, we demonstrate the performance of our method on WorldCover 2020, and the experiment shows that screening reliable sample points during training local classifiers can significantly improve the overall estimation with a relative error of less than 4% at the continent level. This study proves the feasibility of estimating GLC accuracy using the existing land information and remote sensing data, reducing the demand for costly reference data in GLC assessment and enriching the assessment approaches for large-scale land cover data.
Occlusion Handling for Mobile AR Applications in Indoor and Outdoor Scenarios
Authors: Alfakhori Muhammad , Sardi Barzallo Juan Sebastián , Coors Volker
Published: April 2023

When producing an engaging augmented reality (AR) user experience, it is crucial to create AR content that mimics real-life objects’ behavior to the greatest extent possible. A critical aspect to achieve this is ensuring that the digital objects conform to line-of-sight rules and are either partially or completely occluded, just like real-world objects would be. The study explores the concept of utilizing a pre-existing 3D representation of the physical environment as an occlusion mask that governs the rendering of each pixel. Specifically, the research aligns a Level of Detail (LOD) 1 building model and a 3D mesh model with their real-world counterparts and evaluates the effectiveness of occlusion between the two models in an outdoor setting. Despite the mesh model containing more detailed information, the overall results do not show improvement. In an indoor scenario, the researchers leverage the scanning capability of HoloLens 2.0 to create a pre-scanned representation, which helps overcome the limited range and delay of the mesh reconstruction.
MEMS Shielded Capacitive Pressure and Force Sensors with Excellent Thermal Stability and High Operating Temperature
Authors: Ghanam Muhannad , Goldschmidtboeing Frank , Bilger Thomas , Bucherer Andreas , Woias Peter
Published: April 2023

In this paper, we present an innovative manufacturing process for the production of capacitive pressure and force sensors with excellent thermal stability for high-temperature applications. The sensors, which are manufactured from a stack of two silicon chips mounted via with gold–silicon (Au-Si) or aluminum–silicon (Al-Si) eutectic bonding, are shielded, miniaturized, and allow an operating temperature of up to 500 °C. Compared to conventional methods, the greatest benefit of the manufacturing process is that different sensor dimensions can be produced in the same batch for a wide measuring range, from mN to kN. The characterization of the realized sensors shows a high linearity and a low temperature drift of 99.992% FS and −0.001% FS/K at 350 °C, as well as a nonlinearity of 0.035% FS and a temperature drift of −0.0027% FS/K at 500 °C.
Evolution of Hybrid LiFi–WiFi Networks: A Survey
Authors: Besjedica Toni , Fertalj Krešimir , Lipovac Vlatko , Zakarija Ivona
Published: April 2023

Given the growing number of devices and their need for internet access, researchers are focusing on integrating various network technologies. Concerning indoor wireless services, a promising approach in this regard is to combine light fidelity (LiFi) and wireless fidelity (WiFi) technologies into a hybrid LiFi and WiFi network (HLWNet). Such a network benefits from LiFi’s distinct capability for high-speed data transmission and from the wide radio coverage offered by WiFi technologies. In this paper, we describe the framework for the HWLNet architecture, providing an overview of the handover methods used in HLWNets and presenting the basic architecture of hybrid LiFi/WiFi networks, optimization of cell deployment, relevant modulation schemes, illumination constraints, and backhaul device design. The survey also reviews the performance and recent achievements of HLWNets compared to legacy networks with an emphasis on signal to noise and interference ratio (SINR), spectral and power efficiency, and quality of service (QoS). In addition, user behaviour is discussed, considering interference in a LiFi channel is due to user movement, handover frequency, and load balancing. Furthermore, recent advances in indoor positioning and the security of hybrid networks are presented, and finally, directions of the hybrid network’s evolution in the foreseeable future are discussed.
Leveraging ChatGPT to Aid Construction Hazard Recognition and Support Safety Education and Training
Authors: Uddin S M Jamil , Albert Alex , Ovid Anto , Alsharef Abdullah
Published: April 2023

Proper hazard recognition is fundamental to effective safety management in construction workplaces. Nevertheless, poor hazard recognition levels are a widespread and persistent problem in the construction industry. For example, recent investigations have demonstrated that a significant number of workplace hazards often remain unrecognized in construction workplaces. These unrecognized workplace hazards often remain unmanaged and can potentially translate into devastating and unexpected safety incidents. Therefore, interventions targeted at improving hazard recognition levels are foundational to enhancing safety management in construction workplaces. The main objective of the current investigation was to examine if ChatGPT, a language model recently launched by OpenAI, can aid hazard recognition when integrated into the curriculum of students pursuing a career in the construction industry. The investigation was carried out as an experimental effort with 42 students enrolled in the construction program at a major state university in the United States. First, prior to the introduction of ChatGPT as an intervention, the pre-intervention hazard recognition ability of the students was measured. Next, ChatGPT and its capabilities were introduced to the students in a classroom setting. Guidance was also offered on how the students could leverage ChatGPT to aid hazard recognition efforts. Finally, the post-intervention hazard recognition ability of the students was measured and compared against their earlier performance. The result suggests that ChatGPT can be leveraged to improve hazard recognition levels. Accordingly, integrating ChatGPT as part of safety education and training can yield benefits and prepare the next generation of construction professionals for industry success.
M-StruGAN: An Automatic 2D-Plan Generation System under Mixed Structural Constraints for Homestays
Authors: Gao Xiaoni , Guo Xiangmin , Lo Tiantian
Published: April 2023

Existing methods for generating 2D plans based on intelligent systems usually require human-defined rules, and their operations are complex. GANs can solve these problems through independent research and learning. However, they only have generative design research based on a single constraint condition, and whether they can generate a qualified design scheme under many constraints is still unclear. Therefore, this paper develops the M-StruGAN generative model based on the structural design framework of a GAN. Its application research is extended to the 2D-plan layout generation of homestay based on the constraints of hybrid structures, and the feasibility of the method is comprehensively verified through three aspects: image synthesis quality assessment, scheme rationality assessment, and scheme design quality assessment. Experimental results show that the quality of the drawings generated by M-StruGAN is qualified, designers have a high degree of acceptance of the design results of M-StruGAN, and M-StruGAN completed the learning of the critical points of the 2D layout. Finally, through the human–computer interaction application of M-StruGAN, it can be found that compared with traditional design methods, M-StruGAN based on pix2pixHD has high-definition image quality, higher design efficiency, lower design cost, and more stable design quality.
A Methodological Literature Review of Acoustic Wildlife Monitoring Using Artificial Intelligence Tools and Techniques
Authors: Sharma Sandhya , Sato Kazuhiko , Gautam Bishnu Prasad
Published: April 2023

Artificial intelligence (AI) has become a significantly growing field in the environmental sector due to its ability to solve problems, make decisions, and recognize patterns. The significance of AI in wildlife acoustic monitoring is particularly important because of the vast amounts of data that are available in this field, which can be leveraged for computer vision and interpretation. Despite the increasing use of AI in wildlife ecology, its future in acoustic wildlife monitoring remains uncertain. To assess its potential and identify future needs, a scientific literature review was conducted on 54 works published between 2015 and March 2022. The results of the review showed a significant rise in the utilization of AI techniques in wildlife acoustic monitoring over this period, with birds (N = 26) gaining the most popularity, followed by mammals (N = 12). The most commonly used AI algorithm in this field was Convolutional Neural Network, which was found to be more accurate and beneficial than previous categorization methods in acoustic wildlife monitoring. This highlights the potential for AI to play a crucial role in advancing our understanding of wildlife populations and ecosystems. However, the results also show that there are still gaps in our understanding of the use of AI in wildlife acoustic monitoring. Further examination of previously used AI algorithms in bioacoustics research can help researchers better understand patterns and identify areas for improvement in autonomous wildlife monitoring. In conclusion, the use of AI in wildlife acoustic monitoring is a rapidly growing field with a lot of potential. While significant progress has been made in recent years, there is still much to be done to fully realize the potential of AI in this field. Further research is needed to better understand the limitations and opportunities of AI in wildlife acoustic monitoring, and to develop new algorithms that can improve the accuracy and usefulness of this technology.
Impact of Storage on Chemical Composition of Wheat and Efficiency of Its Utilization in Broilers
Authors: Anwar Urooj , Bilal Muhammad Qamar , Khalid Muhammad Farooq , Mustafa Riaz , Farooq Umar , Ashraf Muhammad , Munir Hassan , Riaz Muhammad , Hussain Mubasher , Hussain Munawar , Ayaz Chisti Muhammad Farhan , Rehman Abdul , Rahman Muhammad Aziz ur
Published: April 2023

This present study was designed to evaluate the effect of storage duration (1.5 years and 2.5 years storage) on wheat quality and the impact of the inclusion of stored wheat in the diet of broilers on performance, nutrient digestibility, and carcass parameters. A total of 560 one-day-old male broilers were randomly assigned to the 56 pens, and each pen had 10 birds. A corn-soybean-based diet was considered as the control diet and the other six dietary treatments were prepared by replacing corn of the corn-soybean diet with 50% and 100% replacement of fresh, 1.5-year stored, and 2.5-year stored wheat. The data of proximate composition of wheat represents that dry matter was improved (p < 0.05) and acid detergent fiber was decreased in 2.5-year-old wheat (p < 0.05). Performance parameters data represents that both in the starter phase and finisher phase, the replacement of corn with 50% and 100% fresh wheat in the diet significantly reduced the feed intake, nutrient digestibility, and body weight gain (p < 0.05), and 100% replacement of corn with fresh wheat resulted in higher FCR (p < 0.05). Based on the findings of this current study, it is concluded that the storage of wheat improves the performance of birds.
Digital Transformation to Help Carbon Neutrality and Green Sustainable Development Based on the Metaverse
Authors: Cao Weiran , Cai Zengjie , Yao Xu , Chen Lifeng
Published: April 2023

With the development of sustainable theory, environmental and resource issues have become one of the major challenges facing human society. As an important part of social economy, enterprises are also an important source of carbon emissions and environmental pollution. With the growth of the digital economy, digital technology has played an important role in improving economic efficiency. Digital transformation can not only enable enterprises to obtain and allocate resources more efficiently and reasonably, but can also provide a powerful driving force for the healthy development of the environment. This can improve the positive role and impact of enterprises on environmental development. Based on the overview of social carbon neutrality and green sustainable development goals, this paper made an in-depth study of digital transformation to help carbon neutrality and green sustainable development. In order to verify its effect, this paper took a medium-sized enterprise as the object, analyzed the growth of its economic and environmental benefits in the process of digital transformation, and compared it with the traditional development strategy. The empirical results showed that in the perspective of the Metaverse, the highest growth rate of environmental benefits of the enterprise would reach 19.6% every month in 2021. From this data, digital transformation based on the perspective of the Metaverse was more able to help carbon neutrality and green sustainable development.
AHP-EWM Based Model Selection System for Subsidence Area Research
Authors: Liang Ming , Yang Gen , Zhu Xiaojun , Cheng Hua , Zheng Liugen , Liu Hui , Dong Xianglin , Zhang Yanhai
Published: April 2023

Coal mining can create a variety of environmental, ecological, and land-use problems. Subsidence areas resulting from coal mining are a common and particularly difficult problem to manage. Despite much discussion in the academic literature as well as among local and international stakeholders, there is neither a uniform standard nor a universally accepted approach for selecting an appropriate governance model for a subsidence area. In particular, the lack of quantitative evaluation methods and excessive subjectivity represent key obstacles to the effective selection of governance models for subsidence areas. This paper proposes a selection framework for a coal mining subsidence governance model that integrates the analytic hierarchy process (AHP) and entropy weight method (EWM). The model comprehensively considers the settlement characteristics of the subsidence area, its geographic location, the water index, as well as the vegetation index. These variables are used as indicators to develop an evaluation framework upon which different subsidence zones can be quantitatively analyzed. The selection framework is demonstrated using examples from three subsidence areas in the Huainan and Huaibei mining areas in China, for which relevant data were collected and processed with the help of field surveys, remote sensing images, and subsidence prediction software. Applying the novel selection framework, the most suitable governance model for each subsidence area was obtained and determined to be consistent with the recommendations of an academic panel composed of multiple experts. The novel selection framework has high efficacy and potential to overcome the problem of subjectivity in the selection of governance models for coal mining subsidence areas. It is also envisaged that future incorporation of the selection framework into a user-friendly software package will significantly improve the efficiency with which suitable governance models for coal mining subsidence areas are selected.
pH Dynamics in Aquaponic Systems: Implications for Plant and Fish Crop Productivity and Yield
Authors: Wang Yi-Ju , Yang Teng , Kim Hye-Ji
Published: April 2023

The pH range of 7.0 to 7.2 is recommended to ensure reasonable nitrification rates in aquaponics; however, this range is conducive neither to nitrification, a critical process that occurs at pH 8.0, nor to plant growth. To determine the effects of pH in an aquaponic system, Swiss chard (Beta vulgaris L.), kale (Brassica oleracea L.), mustard green (Brassica juncea L.), cilantro (Coriandrum sativum L.), lettuce (Lactuca sativa L.), and arugula (Eruca vesicaria L.) were cultured with tilapia (Oreochromis niloticus) in 5-year-old coupled aquaponic systems at three pH levels, 6.0, 6.5, and 7.0, in comparison with hydroponics. Morphological and physiological growth parameters of vegetable and fish crops were measured regularly, and the ammonia-oxidizing bacteria (AOB) in the aquaponic system were analyzed by qPCR at the end of the production. This study found that feed conversion ratio, fish biomass, and copy number of AOB were not affected by different pH, but similar to hydroponic systems, lower pH in aquaponic systems increased fresh and dry mass and nutrient levels of all plant species tested. This study suggests that pH has a significant impact on plant performance and yield in both aquaponic and hydroponic systems and that, similar to hydroponics, a pH of 6 is desirable for aquaponic systems to improve plant crop yield without compromising nitrification activity and fish yield.
Numerical Simulation of the Ca(OH)2/CaO Thermochemical Heat Storage Process in an Internal Heating Fixed-Bed Reactor
Authors: Yan Jun , Jiang Lei , Zhao Changying
Published: April 2023

Using a Ca(OH)2/CaO thermochemical heat storage system is an effective way to promote the utilization of renewable energy. However, poor thermal conductivity restricts the application of a widely used fixed-bed reactor. To improve the heat storage rate, the internal heating mode, which heats the reactant via the internal heating tube instead of the external wall, was adopted, and the heat storage process in the fixed-bed reactor was investigated numerically. The results show that the number and location of tubes have a significant impact on heat storage performance. Compared with the external wall heating mode, the optimized scheme of six internal heating tubes can shorten the reaction time by 21.78%. The temperature and reaction extent distribution reveal that as the reaction proceeds, the optimized scheme has a higher temperature and reaction extent. Additionally, the effects of different conditions, such as solid particle porosity, wall temperature, outlet pressure, and solid particle size, were also analyzed. The study demonstrates that increases in solid particle porosity, wall temperature, and solid particle size as well as a decrease in outlet pressure can improve the heat storage rate.
Exploring Students’ Learning Habitus from Chinese Higher Vocational Colleges
Authors: Huang Junjun , Wei Shumin , He Zhen
Published: April 2023

Habitus is a concept from Bourdieu’s theories that plays a key role in explaining individuals’ behaviours. The social reputation and recognition of vocational education in modern China are declining, and vocational college students are bearing a negative stigma, although they have a positive learning behaviour toward academic education. The aim of this study was to examine those students’ previous life experiences, especially in the education field. The main research questions are as follows: (1) How does the individual’s experience construct his or her learning habitus? (2) How does their learning habitus change their learning behaviours? The findings show that the interaction between participants and their parents and teachers mainly leads to the construction of learning habitus, that is, to pursue the success of academic education. Even though they originate from the working class, with less cultural capital and poor academic performance, this does not mean that they have negative learning behaviours. Therefore, it is necessary to give objective and fair evaluations to higher vocational students and address educational inequity problems.