bluuebunny/crossref_metadata_2025 huggingface dataset:
Phase-Selective Epitaxy of Trigonal and Orthorhombic Bismuth Thin Films on Si (111)
Authors: Jalil Abdur Rehman , Hou Xiao , Schüffelgen Peter , Bae Jin Hee , Neumann Elmar , Mussler Gregor , Plucinski Lukasz , Grützmacher Detlev
Published: July 2023

Over the past three decades, the growth of Bi thin films has been extensively explored due to their potential applications in various fields such as thermoelectrics, ferroelectrics, and recently for topological and neuromorphic applications, too. Despite significant research efforts in these areas, achieving reliable and controllable growth of high-quality Bi thin-film allotropes has remained a challenge. Previous studies have reported the growth of trigonal and orthorhombic phases on various substrates yielding low-quality epilayers characterized by surface morphology. In this study, we present a systematic growth investigation, enabling the high-quality growth of Bi epilayers on Bi-terminated Si (111) 1 × 1 surfaces using molecular beam epitaxy. Our work yields a phase map that demonstrates the realization of trigonal, orthorhombic, and pseudocubic thin-film allotropes of Bi. In-depth characterization through X-ray diffraction (XRD) techniques and scanning transmission electron microscopy (STEM) analysis provides a comprehensive understanding of phase segregation, phase stability, phase transformation, and phase-dependent thickness limitations in various Bi thin-film allotropes. Our study provides recipes for the realization of high-quality Bi thin films with desired phases, offering opportunities for the scalable refinement of Bi into quantum and neuromorphic devices and for revisiting technological proposals for this versatile material platform from the past 30 years.
Phosphate Deficiency: A Tale from the End of PILNCR2
Authors: Upadhyay Santosh Kumar
Published: July 2023

A deficiency in inorganic phosphate (Pi) induces the expression of miRNA399 and the accumulation of its target Pi transporters (PHT1s) mRNA, which is contrary to the goal of miRNA-mediated gene regulation. Recently, a novel mechanism of RNA/RNA-duplex formation between the transcripts of a Pi deficiency-induced long non-coding RNA (PILNCR2) and PHT1s has been reported, which prevents the binding and cleavage of miRNA399 to PHT1 mRNAs, thereby providing tolerance of Pi-deficient conditions. Moreover, the way in which ribosomes move through the RNA/RNA-duplex for the translation of PHT1 transporter proteins remains elusive.
Blood Microbiota Profile Is Associated with the Responsiveness of Postprandial Lipemia to Platycodi radix Beverage: A Randomized Controlled Trial in Healthy Subjects
Authors: Kang Seunghee , Lee Inhye , Park Soo-yeon , Kim Ji Yeon , Kim Youjin , Choe Jeong-Sook , Kwon Oran
Published: July 2023

Prolonged postprandial hyperlipidemia may cause the development of cardiovascular diseases. This study explored whether postprandial triglyceride-rich lipoprotein (TRL) clearance responsiveness to Platycodi radix beverage (PR) is associated with changes in blood microbiota profiles. We conducted an 8-week randomized controlled clinical trial involving normolipidemic adults with low fruit and vegetable intakes. Participants underwent an oral fat tolerance test and 16S amplicon sequencing analysis of blood microbiota. Using the Qualitative Interaction Trees, we identified responders as those with higher baseline dietary fat intake (>38.5 g/day) and lipoprotein lipase levels (>150.6 ng/mL), who showed significant reductions in AUC for triglyceride (TG) and chylomicron-TG after the oral fat tolerance test. The LEfSe analysis showed differentially abundant blood microbiota between responders and non-responders. A penalized logistic regression algorithm was employed to predict the responsiveness to intervention on the TRL clearance based on the background characteristics, including the blood microbiome. Our findings suggest that PR intake can modulate postprandial TRL clearance in adults consuming higher fat intake over 38.5 g/day and low fruit and vegetable intake through shared links to systemic microbial signatures.
A Double-Blind, Randomized, Placebo-Controlled Trial of the Effect of 1-Kestose on Defecation Habits in Constipated Kindergarten Children: A Pilot Study
Authors: Takahashi Mayuko , Kadota Yoshihiro , Shiko Yuki , Kawasaki Yohei , Sakurai Kenichi , Mori Chisato , Shimojo Naoki
Published: July 2023

Constipation is common in children and can significantly affect quality of life. Prebiotics are reportedly helpful for constipation in adults, but few studies have examined their use in young children. In this study, the effect of 1-kestose (kestose), which has excellent bifidobacterial growth properties, on constipation in kindergarten children (n = 11) was compared with that of maltose (n = 12) in a randomized, double-blind study. Three grams of kestose per day for 8 weeks did not affect stool properties, but significantly increased the number of defecations per week (Median; 3 → 4 times/week, p = 0.017, effect size = 0.53). A significant decrease in Intestinibacter, a trend toward increased bifidobacteria, and a trend toward decreased Clostridium sensu stricto were observed after kestose ingestion, while concentrations of short-chain fatty acids in stools were unchanged.
The Footprint of Microbiome in Pediatric Asthma—A Complex Puzzle for a Balanced Development
Authors: Lupu Ancuta , Jechel Elena , Mihai Cristina Maria , Mitrofan Elena Cristina , Fotea Silvia , Starcea Iuliana Magdalena , Ioniuc Ileana , Mocanu Adriana , Ghica Dragos Catalin , Popp Alina , Munteanu Dragos , Sasaran Maria Oana , Salaru Delia Lidia , Lupu Vasile Valeriu
Published: July 2023

Considered to be of greater complexity than the human genome itself, the microbiome, the structure of the body made up of trillions of bacteria, viruses, and fungi, has proven to play a crucial role in the context of the development of pathological processes in the body, starting from various infections, autoimmune diseases, atopies, and culminating in its involvement in the development of some forms of cancer, a diagnosis that is considered the most disabling for the patient from a psychological point of view. Therefore, being a cornerstone in the understanding and optimal treatment of a multitude of ailments, the body’s microbiome has become an intensively studied subject in the scientific literature of the last decade. This review aims to bring the microbiome–asthma correlation up to date by classifying asthmatic patterns, emphasizing the development patterns of the microbiome starting from the perinatal period and the impact of pulmonary dysbiosis on asthmatic symptoms in children. Likewise, the effects of intestinal dysbiosis reflected at the level of homeostasis of the internal environment through the intestine–lung/vital organs axis, the circumstances in which it occurs, but also the main methods of studying bacterial variability used for diagnostic purposes and in research should not be omitted. In conclusion, we draw current and future therapeutic lines worthy of consideration both in obtaining and maintaining remission, as well as in delaying the development of primary acute episodes and preventing future relapses.
Intakes of Added Sugars, with a Focus on Beverages and the Associations with Micronutrient Adequacy in US Children, Adolescents, and Teens (NHANES 2003–2018)
Authors: Ricciuto Laurie , Fulgoni Victor L. , Gaine P. Courtney , Scott Maria O. , DiFrancesco Loretta
Published: July 2023

Added sugars intake from sweetened beverages among children, adolescents, and teens is a public health concern. This study examined the relationships between added sugars intake from specific types of beverages with added sugars and from the rest of the diet (excluding beverages with added sugars) and micronutrient adequacy among US children, adolescents, and teens. Data from eight consecutive 2 y cycles of NHANES were combined (2003–04 through 2017–18), and regression analysis was conducted to test for trends in quantiles of added sugars intake from each beverage source (soft drinks, fruit drinks, sport and energy drinks, coffee and tea, and flavored milk) and the rest of the diet (excluding those beverages) and micronutrient adequacy among children (2–8 y) and adolescents and teens (9–18 y). Among those aged 2–8 y, higher added sugars from flavored milk were associated with lower percentages below the estimated average requirement (EAR) for calcium. Among those aged 9–18 y, higher added sugars from soft drinks or coffee and tea were associated with higher percentages below the EAR for magnesium and vitamins A and C. In contrast, higher added sugars from fruit drinks or flavored milk were associated with lower percentages below the EAR (higher percentages above the adequate intake (AI)) for vitamin C (fruit drinks) and calcium, magnesium, phosphorus, vitamin A, and potassium (flavored milk). Regarding the rest of the diet, higher added sugars were associated with lower percentages below the EAR (higher percentages above the AI) for most micronutrients examined. The results suggest that the relationship between added sugars intake and micronutrient adequacy depends on the added sugar sources and their nutrient composition. Continued monitoring of sweetened beverage consumption, including beverage type, and the association with added sugars intake, micronutrient adequacy, and diet quality is warranted, given the changes in consumption and product development over time.
Exposure to Biological Fluids in Dental Practice—Narrative Review on Appropriate Risk Assessment to Guide Post-Exposure Management
Authors: Săndulescu Mihai , Nicolescu Mihnea Ioan , Funieru Cristian , Şahin Gülşen Özkaya , Săndulescu Oana
Published: July 2023

Accidental exposure to blood or other biological fluids is a common occurrence in dentistry, and its post-exposure management is a key component of infection prevention and control programs designed to prevent the transmission of blood-borne pathogens such as hepatitis B and C viruses (HBV, HCV) and human immunodeficiency virus (HIV). This narrative review aims to comprehensively review the risk assessment process for each of these pathogens at all steps of the epidemiological process, i.e., source–exposure route–receptive person, in order to provide a better understanding of the delicate differences that influence the transmission risk and that drive the individualized post-exposure management.
Renoprotective Effect of Chrysanthemum coronarium L. Extract on Adenine-Induced Chronic Kidney Disease in Mice
Authors: Kim Yi-Seul , Lee Ae-Sin , Hur Haeng-Jeon , Lee Sang-Hee , Na Hyun-Jin , Sung Mi-Jeong
Published: July 2023

Chronic kidney disease (CKD) gradually leads to loss of renal function and is associated with inflammation and fibrosis. Chrysanthemum coronarium L., a leafy vegetable, possesses various beneficial properties, including anti-oxidative, anti-inflammatory, and antiproliferative effects. In this study, we investigated the renoprotective effect of Chrysanthemum coronarium L. extract (CC) on adenine (AD)-induced CKD in mice. CKD was induced by feeding mice with an AD diet (0.25% w/w) for 4 weeks. Changes in renal function, histopathology, inflammation, and renal interstitial fibrosis were analyzed. The adenine-fed mice were characterized by increased blood urea nitrogen, serum creatinine, and histological changes, including inflammation and fibrosis; however, these changes were significantly restored by treatment with CC. Additionally, CC inhibited the expression of the inflammatory markers, monocyte chemoattractant protein-1, interleukins-6 and -1β, intercellular adhesion molecule-1, and cyclooxygenase 2. Moreover, CC suppressed the expression of the fibrotic markers, type IV collagen, and fibronectin. Furthermore, CC attenuated the expression of profibrotic genes (tumor growth factor-β and α-smooth muscle actin) in AD-induced renal injury mice. Thus, our results suggest that CC has the potential to attenuate AD-induced renal injury and might offer a new option as a renoprotective agent or functional food supplement to manage CKD.
Stable Gastric Pentadecapeptide BPC 157—Possible Novel Therapy of Glaucoma and Other Ocular Conditions
Authors: Sikiric Predrag , Kokot Antonio , Kralj Tamara , Zlatar Mirna , Masnec Sanja , Lazic Ratimir , Loncaric Kristina , Oroz Katarina , Sablic Marko , Boljesic Marta , Antunovic Marko , Sikiric Suncana , Strbe Sanja , Stambolija Vasilije , Beketic Oreskovic Lidija , Kavelj Ivana , Novosel Luka , Zubcic Slavica , Krezic Ivan , Skrtic Anita , Jurjevic Ivana , Boban Blagaic Alenka , Seiwerth Sven , Staresinic Mario
Published: July 2023

Recently, stable gastric pentadecapeptide BPC 157 therapy by activation of collateral pathways counteracted various occlusion/occlusion-like syndromes, vascular, and multiorgan failure, and blood pressure disturbances in rats with permanent major vessel occlusion and similar procedures disabling endothelium function. Thereby, we revealed BPC 157 cytoprotective therapy with strong vascular rescuing capabilities in glaucoma therapy. With these capabilities, BPC 157 therapy can recover glaucomatous rats, normalize intraocular pressure, maintain retinal integrity, recover pupil function, recover retinal ischemia, and corneal injuries (i.e., maintained transparency after complete corneal abrasion, corneal ulceration, and counteracted dry eye after lacrimal gland removal or corneal insensitivity). The most important point is that in glaucomatous rats (three of four episcleral veins cauterized) with high intraocular pressure, all BPC 157 regimens immediately normalized intraocular pressure. BPC 157-treated rats exhibited normal pupil diameter, microscopically well-preserved ganglion cells and optic nerve presentation, normal fundus presentation, nor- mal retinal and choroidal blood vessel presentation, and normal optic nerve presentation. The one episcleral vein rapidly upgraded to accomplish all functions in glaucomatous rats may correspond with occlusion/occlusion-like syndromes of the activated rescuing collateral pathway (azygos vein direct blood flow delivery). Normalized intraocular pressure in glaucomatous rats corresponded to the counteracted intra-cranial (superior sagittal sinus), portal, and caval hypertension, and aortal hypotension in occlusion/occlusion-like syndromes, were all attenuated/eliminated by BPC 157 therapy. Furthermore, given in other eye disturbances (i.e., retinal ischemia), BPC 157 instantly breaks a noxious chain of events, both at an early stage and an already advanced stage. Thus, we further advocate BPC 157 as a therapeutic agent in ocular disease.
Enhancing Oral Bioavailability and Brain Biodistribution of Perillyl Alcohol Using Nanostructured Lipid Carriers
Authors: Peczek Samila Horst , Tartari Ana Paula Santos , Zittlau Isabella Camargo , Diedrich Camila , Machado Christiane Schineider , Mainardes Rubiana Mara
Published: July 2023

Perillyl alcohol (POH), a bioactive monoterpenoid derived from limonene, shows promise as an antitumor agent for brain tumor treatment. However, its limited oral bioavailability and inadequate brain distribution hinder its efficacy. To address these challenges, this study developed nanostructured lipid carriers (NLCs) loaded with POH to improve its brain biodistribution. The NLCs prepared using hot homogenization exhibited an average diameter of 287 nm and a spherical morphology with a polydispersity index of 0.143. High encapsulation efficiency of 99.68% was achieved. X-ray diffraction analyses confirmed the semicrystalline state of POH-loaded NLCs. In vitro release studies demonstrated a biphasic release profile. Stability studies in simulated gastric and intestinal fluids confirmed their ability to withstand pH variations and digestive enzymes. In vivo pharmacokinetic studies in rats revealed significantly enhanced oral bioavailability of POH when encapsulated in the NLCs. Biodistribution studies showed increased POH concentration in brain tissue with NLCs compared with free POH, which was distributed more in non-target tissues such as the liver, lungs, kidneys, and spleen. These findings underscore the potential of NLCs as effective delivery systems for enhancing oral bioavailability and brain biodistribution of POH, providing a potential therapeutic strategy for brain tumor treatment.
Using the Aqueous Phase Produced from Hydrothermal Carbonization Process of Brown Seaweed to Improve the Growth of Phaseolus vulgaris
Authors: Spagnuolo Damiano , Bressi Viviana , Chiofalo Maria Teresa , Morabito Marina , Espro Claudia , Genovese Giuseppa , Iannazzo Daniela , Trifilò Patrizia
Published: July 2023

Seaweeds are considered a biomass for third-generation biofuel, and hydrothermal carbonization (HTC) is a valuable process for efficiently disposing of the excess of macroalgae biomass for conversion into multiple value-added products. However, the HTC process produces a liquid phase to be disposed of. The present study aims to investigate the effects of seed-priming treatment with three HTC-discarded liquid phases (namely AHL180, AHL240, and AHL300), obtained from different experimental procedures, on seed germination and plant growth and productivity of Phaseolus vulgaris L. To disentangle the osmotic effects from the use of AHL, isotonic solutions of polyethylene glycol (PEG) 6000 have also been tested. Seed germination was not affected by AHL seed-priming treatment. In contrast, PEG-treated samples showed significantly lower seed germination success. AHL-treated samples showed changes in plant biomass: higher shoot biomass was recorded especially in AHL180 samples. Conversely, AHL240 and AHL300 samples showed higher root biomass. The higher plant biomass values recorded in AHL-treated samples were the consequence of higher values of photosynthesis rate and water use efficiency, which, in turn, were related to higher stomatal density. Recorded data strongly support the hypothesis of the AHL solution reuse in agriculture in the framework of resource management and circular green economy.
Carbon Storage in Different Compartments in Eucalyptus Stands and Native Cerrado Vegetation
Authors: Ribeiro Fabiana Piontekowski , Gatto Alcides , Oliveira Alexsandra Duarte de , Pulrolnik Karina , Valadão Marco Bruno Xavier , Araújo Juliana Baldan Costa Neves , Carvalho Arminda Moreira de , Ferreira Eloisa Aparecida Belleza
Published: July 2023

This study evaluated Carbon (C) storage in different compartments in eucalyptus stands and native Cerrado vegetation. To determine C above ground, an inventory was carried out in the areas where diameter at breast height (DBH), diameter at base height (Db), and total tree height (H) were measured. In the stands, the rigorous cubage was made by the direct method, and in the native vegetation, it was determined by the indirect method through an allometric equation. Roots were collected by direct method using circular monoliths to a depth of 60 cm and determined by the volume of the cylinder. Samples were collected up to 100 cm deep to estimate C stock in the soil. All samples collected directly had C determined using the CHNS elemental analyzer. Gas samples were collected using a manually closed chamber, and the gas concentration was determined by gas chromatography. The results indicate high C storage in the studied areas > 183.99 Mg ha−1, could contribute to CO2 mitigation > 674.17 Mg ha−1. In addition to low emissions (<1 kg ha−1 yr−1) for the three evaluated areas, with no statistical difference in relation to the Global Warming Potential. Concerning the native cerrado vegetation conversion, the “4-year-old eucalyptus stand” seemed to restore the original soil carbon stocks in the first-meter depth, regardless of some losses that might have occurred right after establishment. Conversely, a significant loss of carbon in the soil was observed due to the alternative setting, where similar natural land was converted into agriculture, mostly soybean, and then, years later, turned into the “6-year-old eucalyptus stand” (28.43 Mg ha−1). Under this study, these mixed series of C baselines in landscape transitions have reflected on unlike C dynamics outcomes, whereas at the bottom line, total C stocks were higher in the younger forest (4-year-old stand). Therefore, our finding indicates that we should be thoughtful regarding upscaling carbon emissions and sequestration from small-scale measurements to regional scales
Effects of Centrifugation on the Oxidative Stability and Antioxidant Profile of Cold-Pressed Rapeseed Oil during Storage
Authors: Dordevic Dani , Gablo Natalia , Dordevic Janickova Simona , Tremlova Bohuslava
Published: July 2023

The recognition and growing consumption of cold-pressed rapeseed oil (CPRO) is due to by its unique, health-promoting properties; it is a rich source of omega-3 fatty acids and antioxidants. Nevertheless, the high content of unsaturated fatty acids and plant tissue particles makes CPRO more susceptible to oxidation. These pro-oxidant plant particles can be eliminated via centrifugation, thus improving the quality and stability of CPRO. Therefore, we aimed to determine whether the clarification of CPRO via centrifugation affects its quality parameters, pigment and phenolic profile, and antioxidant properties. These characteristics were analyzed and compared between centrifuged CPRO and CPRO clarified via natural decantation. Changes were monitored for 6 months of oil storage at 22 °C. Based on the results, no changes in the oxidation profile were found between centrifuged CPRO and decantated CPRO. When the storage is longer than 1 month, centrifugation is more beneficial with regard to delaying hydrolytic deterioration, while decantation provides slightly better pigment and polyphenol profiles. We did not observe that centrifugation improved the oil’s antioxidant properties. Further research should be continued to establish the effects of centrifugation on CPRO quality, including parameters such as rapeseed quality, maturity degree, varieties, and stricter storage conditions.
Biophysical Variable Retrieval of Silage Maize with Gaussian Process Regression and Hyperparameter Optimization Algorithms
Authors: Akbari Elahe , Boloorani Ali Darvishi , Verrelst Jochem , Pignatti Stefano , Neysani Samany Najmeh , Soufizadeh Saeid , Hamzeh Saeid
Published: July 2023

Quantification of vegetation biophysical variables such as leaf area index (LAI), fractional vegetation cover (fCover), and biomass are among the key factors across hydrological, agricultural, and irrigation management studies. The present study proposes a kernel-based machine learning algorithm capable of performing adaptive and nonlinear data fitting so as to generate a suitable, accurate, and robust algorithm for spatio-temporal estimation of the three mentioned variables using Sentinel-2 images. To this aim, Gaussian process regression (GPR)–particle swarm optimization (PSO), GPR–genetic algorithm (GA), GPR–tabu search (TS), and GPR–simulated annealing (SA) hyperparameter-optimized algorithms were developed and compared against kernel-based machine learning regression algorithms and artificial neural network (ANN) and random forest (RF) algorithms. The accuracy of the proposed algorithms was assessed using digital hemispherical photography (DHP) data and destructive measurements performed during the growing season of silage maize in agricultural fields of Ghale-Nou, southern Tehran, Iran, in the summer of 2019. The results on biophysical variables against validation data showed that the developed GPR-PSO algorithm outperformed other algorithms under study in terms of robustness and accuracy (0.917, 0.931, 0.882 using R2 and 0.627, 0.078, and 1.99 using RMSE in LAI, fCover, and biomass of Sentinel-2 20 m, respectively). GPR-PSO also possesses the unique ability to generate pixel-based uncertainty maps (confidence level) for prediction purposes (i.e., estimated uncertainty level <0.7 in LAI, fCover, and biomass, for 96%, 98%, and 71% of the total study area, respectively). Altogether, GPR-PSO appears to be the most suitable option for mapping biophysical variables at the local scale using Sentinel-2 images.
A Super-Resolution Algorithm Based on Hybrid Network for Multi-Channel Remote Sensing Images
Authors: Li Zhen , Zhang Wenjuan , Pan Jie , Sun Ruiqi , Sha Lingyu
Published: July 2023

In recent years, the development of super-resolution (SR) algorithms based on convolutional neural networks has become an important topic in enhancing the resolution of multi-channel remote sensing images. However, most of the existing SR models suffer from the insufficient utilization of spectral information, limiting their SR performance. Here, we derive a novel hybrid SR network (HSRN) which facilitates the acquisition of joint spatial–spectral information to enhance the spatial resolution of multi-channel remote sensing images. The main contributions of this paper are three-fold: (1) in order to sufficiently extract the spatial–spectral information of multi-channel remote sensing images, we designed a hybrid three-dimensional (3D) and two-dimensional (2D) convolution module which can distill the nonlinear spectral and spatial information simultaneously; (2) to enhance the discriminative learning ability, we designed the attention structure, including channel attention, before the upsampling block and spatial attention after the upsampling block, to weigh and rescale the spectral and spatial features; and (3) to acquire fine quality and clear texture for reconstructed SR images, we introduced a multi-scale structural similarity index into our loss function to constrain the HSRN model. The qualitative and quantitative comparisons were carried out in comparison with other SR methods on public remote sensing datasets. It is demonstrated that our HSRN outperforms state-of-the-art methods on multi-channel remote sensing images.
Locality Preserving Property Constrained Contrastive Learning for Object Classification in SAR Imagery
Authors: Wang Jing , Tian Sirui , Feng Xiaolin , Zhang Bo , Wu Fan , Zhang Hong , Wang Chao
Published: July 2023

Robust unsupervised feature learning is a critical yet tough task for synthetic aperture radar (SAR) automatic target recognition (ATR) with limited labeled data. The developing contrastive self-supervised learning (CSL) method, which learns informative representations by solving an instance discrimination task, provides a novel method for learning discriminative features from unlabeled SAR images. However, the instance-level contrastive loss can magnify the differences between samples belonging to the same class in the latent feature space. Therefore, CSL can dispel these targets from the same class and affect the downstream classification tasks. In order to address this problem, this paper proposes a novel framework called locality preserving property constrained contrastive learning (LPPCL), which not only learns informative representations of data but also preserves the local similarity property in the latent feature space. In LPPCL, the traditional InfoNCE loss of the CSL models is reformulated in a cross-entropy form where the local similarity of the original data is embedded as pseudo labels. Furthermore, the traditional two-branch CSL architecture is extended to a multi-branch structure, improving the robustness of models trained with limited batch sizes and samples. Finally, the self-attentive pooling module is used to replace the global average pooling layer that is commonly used in most of the standard encoders, which provides an adaptive method for retaining information that benefits downstream tasks during the pooling procedure and significantly improves the performance of the model. Validation and ablation experiments using MSTAR datasets found that the proposed framework outperformed the classic CSL method and achieved state-of-the-art (SOTA) results.
Contextual Cluster-Based Glow-Worm Swarm Optimization (GSO) Coupled Wireless Sensor Networks for Smart Cities
Authors: Ramesh P. S. , Srivani P. , Mahdal Miroslav , Sivaranjani Lingala , Abidin Shafiqul , Kagi Shivakumar , Elangovan Muniyandy
Published: July 2023

The cluster technique involves the creation of clusters and the selection of a cluster head (CH), which connects sensor nodes, known as cluster members (CM), to the CH. The CH receives data from the CM and collects data from sensor nodes, removing unnecessary data to conserve energy. It compresses the data and transmits them to base stations through multi-hop to reduce network load. Since CMs only communicate with their CH and have a limited range, they avoid redundant information. However, the CH’s routing, compression, and aggregation functions consume power quickly compared to other protocols, like TPGF, LQEAR, MPRM, and P-LQCLR. To address energy usage in wireless sensor networks (WSNs), heterogeneous high-power nodes (HPN) are used to balance energy consumption. CHs close to the base station require effective algorithms for improvement. The cluster-based glow-worm optimization technique utilizes random clustering, distributed cluster leader selection, and link-based routing. The cluster head routes data to the next group leader, balancing energy utilization in the WSN. This algorithm reduces energy consumption through multi-hop communication, cluster construction, and cluster head election. The glow-worm optimization technique allows for faster convergence and improved multi-parameter selection. By combining these methods, a new routing scheme is proposed to extend the network’s lifetime and balance energy in various environments. However, the proposed model consumes more energy than TPGF, and other protocols for packets with 0 or 1 retransmission count in a 260-node network. This is mainly due to the short INFO packets during the neighbor discovery period and the increased hop count of the proposed derived pathways. Herein, simulations are conducted to evaluate the technique’s throughput and energy efficiency.
Enabling Trust and Security in Digital Twin Management: A Blockchain-Based Approach with Ethereum and IPFS
Authors: Onwubiko Austine , Singh  Raman , Awan  Shahid , Pervez Zeeshan , Ramzan  Naeem
Published: July 2023

The emergence of Industry 5.0 has highlighted the significance of information usage, processing, and data analysis when maintaining physical assets. This has enabled the creation of the Digital Twin (DT). Information about an asset is generated and consumed during its entire life cycle. The main goal of DT is to connect and represent physical assets as close to reality as possible virtually. Unfortunately, the lack of security and trust among DT participants remains a problem as a result of data sharing. This issue cannot be resolved with a central authority when dealing with large organisations. Blockchain technology has been proposed as a solution for DT information sharing and security challenges. This paper proposes a Blockchain-based solution for digital twin using Ethereum blockchain with performance and cost analysis. This solution employs a smart contract for information management and access control for stakeholders of the digital twin, which is secure and tamper-proof. This implementation is based on Ethereum and IPFS. We use IPFS storage servers to store stakeholders’ details and manage information. A real-world use-case of a production line of a smartphone, where a conveyor belt is used to carry different parts, is presented to demonstrate the proposed system. The performance evaluation of our proposed system shows that it is secure and achieves performance improvement when compared with other methods. The comparison of results with state-of-the-art methods showed that the proposed system consumed fewer resources in a transaction cost, with an 8% decrease. The execution cost increased by 10%, but the cost of ether was 93% less than the existing methods.
Willingness to Prepare for Disasters among Individuals with Disabilities: An Essential Component for Building Disaster Resiliency
Authors: Kyne Dean
Published: July 2023

This study focuses on exploring the factors influencing individuals’ preparedness for disasters. Drawing upon the protection motivation theory (PMT) and the prototype willingness model (PWM), a conceptual framework was proposed to investigate the determinants of willingness to prepare for disasters and its impact on disaster preparedness. Data was collected through an online survey, involving 377 participants with disabilities and medical special needs residing in the Rio Grande Valley (RGV). The collected data was analyzed using generalized structural equation modeling (GSEM) to examine the associations among the selected study variables. The findings indicate that both coping appraisal and threat appraisal significantly influence individuals’ willingness to prepare for disasters, which, in turn, has a notable impact on disaster preparedness. Recognizing the significance of disaster preparedness in building resilience and effectively responding to and recovering from disasters, it is crucial to acknowledge the importance of the willingness component in these efforts to cope effectively with future extreme events.
Discovering the Sustainable Innovation Service Process of Organizational Environment, Information Sharing and Satisfaction: The Moderating Roles of Pressure
Authors: Liu Chih-Hsing , La Quoc Phong , Ng Yen-Ling , Mamengko Rullyana Puspitaningrum
Published: July 2023

Sustainability issues have been highly impacted during the pandemic period, and issues of sustainability are receiving increasing attention and have been embedded in tourism and hospitality management. To follow customer changes and sustainability requirements, employee behavior is a significant determinant of organizations’ sustainable service innovation. Data were collected from 454 restaurant employees to confirm the proposed hypothesis and investigate the organization of sustainable service innovation processes. The results showed that organizational environments may encourage employees to engage in information sharing and satisfaction to enhance sustainable service innovation through achievement and improvement. Further, this study also asserts that pressure is a critical attribute that moderates the relationship between achievement and improvement for sustainable service innovation. Theoretical and managerial implications are also introduced and discussed.
Life-LCA: Impacts of a German Human Being in the Old Adulthood Stage
Authors: Bossek David , Rudolph Caroline , Bach Vanessa , Finkbeiner Matthias
Published: July 2023

Life-LCA studies, which assess the environmental impacts of human beings, focused so far on the span from conception to 50 years. This case study extends the analysis to an “old adulthood stage”, including a retirement (65–75 years) and end-of-life phase (75–80 years), thus complementing the assessment gap in the life cycle of a human being. The Life-LCA method is applied to a fictional study object representing an average German adult using mainly secondary data. Over both life phases, impacts result in 1.2 × 102 t CO2-eq for climate change, 9 × 10−⁵ CTUh for human toxicity cancer, 2 × 10−3 CTUh for human toxicity non-cancer, 1.35 × 10⁰ kg Sb-eq for abiotic depletion for elements, and 1.55 × 10⁰ TJ for fossil fuels. Across all impact categories, “transport” is a hotspot, contributing 41% to GWP, followed by “Energy and water” (39%) and “food” (20%). For abiotic depletion for elements, “Electronics” shows a share of 50%. The “retirement phase” causes a higher environmental impact than the “EoL phase” across all impact categories due to restricted mobility with higher age. A study with primary data collection is suggested to check the plausibility of the results.
Spatial Differentiation and Driving Factors of Traditional Villages in Jiangsu Province
Authors: Zhang Qinghai , Wang Jiabei
Published: July 2023

Jiangsu Province, situated in the Yangtze River basin, has rich traditional village resources and a prominent position in economic development and cultural integration. This study focuses on the analysis of the variation distribution pattern of traditional villages in Jiangsu Province using six batches of traditional village directories with data until 2023 as research samples. By employing ANN, Voronoi graph analysis, and Moran’s I index, the researchers determined the spatial distribution characteristics of rural settlements. Additionally, kernel density and spatial autocorrelation techniques were used to further examine the spatial distribution patterns, and geographic detector detection was introduced. The results showed the following: (1) The spatial distribution of traditional village settlements in Jiangsu Province showed a significant clustering distribution that is mainly concentrated in central Jiangsu Province. (2) The driving factors reflected a strong symbiotic relationship of “air–water–soil–man”. The spatial distribution of traditional villages was mainly driven by the annual mean temperature and soil type. The interaction between factors was dominated by the enhancement relationship between the two factors. (3) According to the detection results of risk areas in the region, the average annual temperature was 17~17.6 °C, the annual precipitation was 133.0~145.7 billion m3, the average annual wind speed was 0.549~0.565 m/s, the GDP was 85,100~204,000 CNY/km−2, and the population density was 2.32~3.91 thousand/km−2. Arable land was the main type of area and was conducive to the gathering of traditional villages. The preservation of rural settlements should take into account the complex and diverse factors that affect their distribution. Additionally, it is crucial to tailor protection strategies to specific local conditions and conduct flexible research.
Numerical Analysis of Natural Ventilation on One Side of a Room with Two Different Opening Configurations
Authors: Fang Zhicheng , Wang Wanjiang , Chen Yanhui , Fan Hui , Dong Ruoqi , Pang Dongbing , Song Junkang
Published: July 2023

Single-side natural ventilation is a commonly used means of ventilation to effectively regulate the thermal environment in building interiors without any fossil energy consumption. To achieve most of the potential for the efficiency of single-side natural ventilation, research needs to be undertaken into the forces that drive single-side natural ventilation. This paper examines the single-side natural ventilation of a single vertical single opening (SSO) and a vertical double opening (SDO) in a freestanding building under wind and thermal pressure. The change in the trajectory of vortex shedding when the building is leeward as well as the frequency of vortex shedding in square buildings was investigated by large eddy simulation (LES), and computational fluid dynamics was used to analyze the difference in the air exchange rate of single-side natural ventilation of SSO and SDO in the windward and leeward conditions of the building. Both of these methods were used in conjunction with one another. According to the findings, the creation of vortices at SSO and SDO in the presence of low wind speeds reduces the ventilation effect of thermal pressure under windward circumstances. Consequently, the influence of thermal stress and wind stress ultimately cancel each other out, and this phenomenon finally disappears as the wind blowing from the outside of the structure increases. The shedding of vortices in the leeward state accomplishes a form of air supply pumping with a particular periodicity of airflow fluctuations in the lateral direction. The Strouhal number computed using the LES simulation acts in a manner consistent with the experimental findings.
Estimation of the Extent of the Vulnerability of Agriculture to Climate Change Using Analytical and Deep-Learning Methods: A Case Study in Jammu, Kashmir, and Ladakh
Authors: Malik Irtiqa , Ahmed Muneeb , Gulzar Yonis , Baba Sajad Hassan , Mir Mohammad Shuaib , Soomro Arjumand Bano , Sultan Abid , Elwasila Osman
Published: July 2023

Climate stress poses a threat to the agricultural sector, which is vital for both the economy and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability is crucial. This study proposes a framework to estimate the impact climate stress on agriculture in terms of three objectives: assessing the regional vulnerability (exposure, sensitivity, and adaptive capacity), analysing the climate variability, and measuring agricultural performance under climatic stress. The vulnerability of twenty-two sub-regions in Jammu, Kashmir, and Ladakh is assessed using indicators to determine the collective susceptibility of the agricultural framework to climate change. An index-based approach with min–max normalization is employed, ranking the districts based on their relative performances across vulnerability indicators. This work assesses the impact of socio-economic and climatic indicators on the performance of agricultural growth using the benchmark Ricardian approach. The parameters of the agricultural growth function are estimated using a linear combination of socio-economic and exposure variables. Lastly, the forecasted trends of climatic variables are examined using a long short-term memory (LSTM)-based recurrent neural network, providing an annual estimate of climate variability. The results indicate a negative impact of annual minimum temperature and decreasing land holdings on agricultural GDP, while cropping intensity, rural literacy, and credit facilities have positive effects. Budgam, Ganderbal, and Bandipora districts exhibit higher vulnerability due to factors such as low literacy rates, high population density, and extensive rice cultivation. Conversely, Kargil, Rajouri, and Poonch districts show lower vulnerability due to the low population density and lower level of institutional development. We observe an increasing trend of minimum temperature across the region. The proposed LSTM synthesizes a predictive estimate across five essential climate variables with an average overall root mean squared error (RMSE) of 0.91, outperforming the benchmark ARIMA and exponential-smoothing models by 32–48%. These findings can guide policymakers and stakeholders in developing strategies to mitigate climate stress on agriculture and enhance resilience.
Community-Driven Insights into Fish Assemblage, Microhabitats, and Management Strategies in the Meghna River Basin of Bangladesh
Authors: Sultana Mst. Armina , Hussain Md. Ashraf , Schneider Petra , Nahiduzzaman Md. , Barman Benoy Kumar , Wahab Md. Abdul , Mozumder Mohammad Mojibul Hoque , Kunda Mrityunjoy
Published: July 2023

The present study aimed to delve into the local ecological knowledge of fisheries in the Meghna River Basin (MRB) of Bangladesh by exploring the insights and perspectives of local communities. A survey was administered among six fishing communities from five districts along the MRB between August 2015 and January 2016 to accumulate data for this study. The study sites were selected meticulously based on three crucial criteria: upstream river, coastal area, and fish sanctuaries, which covered three major rivers, namely the Meghna, Andharmanik, and Payra. The study employed participatory rural appraisal (PRA) tools, including 120 individual interviews using purposive sampling, 25 focus group discussions, and 36 key informant interviews. The study identified the ten most frequently caught fish species along with their temporal and spatial variation as reported by the respondents. Nine of these species fell into the least concern category, which indicate their stable population status. Meanwhile, six out of ten species cited as highly caught in the previous one to two decades belong to the threatened or near-threatened category. Findings also reveal that fishers are able to recognize important microhabitats of the study area and their significance for fish species. In addition, fishers identified the negative drivers of ecosystem degradation as well as suggested several management measures to address these challenges. The results of this study underscore the critical role of engaging with local communities and integrating their ecological knowledge into initiatives for the sustainable exploitation and conservation of aquatic resources in the MRB.
Machine-Learning-Based Sensor Design for Water Salinity Prediction: A Conceptual Approach
Authors: Mourched Bachar , Abdallah Mariam , Hoxha Mario , Vrtagic Sabahudin
Published: July 2023

This research paper introduces a sensor that utilizes a machine-learning model to predict water salinity. The sensor’s concept and design are established through a simulation software which enables accurate modeling and analysis. Operating on the principle of light transmission physics, the sensor employs data collected from the simulation software as input parameters to predict the salinity parameter, serving as the output. The results of the prediction model exhibit excellent performance, showcasing high accuracy with a coefficient of determination value of 0.999 and a mean absolute error of 0.074. These outcomes demonstrate the model’s ability, particularly the multi-layer perceptron model, to effectively predict salinity values for previously unseen input data. This performance underscores the model’s accuracy and its proficiency in handling unfamiliar input data, emphasizing its significance in practical applications.
RETRACTED: Ding et al. Study on Mechanical Properties of Soil Stabilization by Different Vegetation Roots on High Steep Slope. Sustainability 2023, 15, 2569
Authors: Ding Heng , Zhang Hong , Liu Bing , Huang Haiyun
Published: July 2023

The Journal retracts the article entitled “Study on Mechanical Properties of Soil Stabilization by Different Vegetation Roots on High Steep Slope” by Ding et al. [...]
An Evolutionary Analysis of Higher-Order Interaction Collaborative Innovation Networks in China’s New Energy Vehicle Industry
Authors: Yuan Yuan , Guo Jinli , Guo Zhaohua
Published: July 2023

As a manifestation of technological innovation achievements, patents reflect the frontier of technological development in the field. The aim of this research is to investigate the spatial evolution of patent collaboration networks and cooperation activities in the Chinese new energy vehicle (NEV) industry. We hypothesize that the higher-order collaboration networks will exhibit the formation of triangle groups centered around core nodes and the emergence of key edges indicating their importance. Key organizations and partners will play a significant role in shaping the future direction of cooperative innovation. The research utilizes data on collaboration patents in the NEV industry in China and constructs higher-order interaction collaboration innovation networks. The spatial evolution of networks and patent cooperation activities are examined using simplex methods. The results indicate that the generalized degree distribution of nodes and edges follows a power-law distribution. Two-dimensional simplex networks gradually form triangle clusters centered on core nodes and key edges. Large companies and research institutes prefer high-depth collaboration, while universities prefer high-breadth collaboration. Furthermore, the development of the new energy vehicle industry has gradually shifted from the eastern region to the central region. In the two-dimensional simplex network, Beijing and Jiangsu play a crucial role as key bridges in fostering stable and deep collaborations. The findings of this study shed light on the spatial evolution of patent collaboration networks and cooperation activities in the Chinese NEV industry. The identification of key organizations and partners, as well as the central positions of certain regions, provides valuable insights for innovation organizations in navigating innovation development and selecting collaboration partners.