bluuebunny/crossref_metadata_2025 huggingface dataset:
The Cardiorenal Effects of Piper amalago Are Mediated by the Nitric Oxide/Cyclic Guanosine Monophosphate Pathway and the Voltage-Dependent Potassium Channels
Authors: Monteiro Luciane M. , Klider Lislaine M. , Marques Aline A. M. , Farago Paulo V. , Emiliano Janaína , Souza Roosevelt I. C. , dos Santos Ariany C. , dos Santos Vera L. P. , Wang Mei , Cassemiro Nadla S. , Silva Denise B. , Khan Ikhlas A. , Gasparotto Junior Arquimedes , Manfron Jane
Published: November 2023

Piper amalago L. is used in Brazilian traditional medicine to treat inflammation, chest pain, and anxiety. This study aimed to investigate the safety and the renal and cardiovascular effects of the volatile oil (VO) and the aqueous (AE) and hydroalcoholic (HE) extracts from P. amalago. The gas chromatography-mass spectrometry analyses identified 47 compounds in the VO, with β-cyclogermacrene, spathulenol, β-phellandrene, and α-pinene standing out. Among the 47 compounds also found in AE and HE by liquid chromatography-mass spectrometry, glycosylated flavones, organic acids, amino acids, and amides were highlighted. Some examples of these compounds are methoxy-methylenedioxy cis-cinnamoyl pyrrolidine, methoxy-methylenedioxy trans-cinnamoyl pyrrolidine, and cyclobutene-2,4-bis-(1,3-benzodioxol-5-methoxy-6-yl)-1,3-dicarboxapyrrolidide. The acute toxicity experiments were conducted on female rats (n = 5). The cardiorenal assays (n = 8) and evaluations of vasodilatory effects on the mesenteric vascular bed (n = 5) were conducted on male rats. In either extract or VO, there were no mortality or changes in relative weights or histopathological analysis of the organs. Urinary volume and renal electrolyte excretion were elevated significantly during repeated dose 7-day treatment with different preparations from P. amalago. None of the preparations induced hypotension or changes in cardiac electrical activity. Only HE promoted significant vasodilatory effects in rats’ isolated mesenteric vascular beds. These effects were completely abolished in the presence of L-NAME plus 4-aminopyridine. Therefore, P. amalago leaves are safe and present diuretic activity after acute and repeated dose administration over 7 days. Moreover, the HE induced significant vasodilator response in rats’ mesenteric vascular beds by NO/cGMP pathway and voltage-dependent K+ channels activation.
Analysis of the Physical Characteristics of an Anhydrous Vehicle for Compounded Pediatric Oral Liquids
Authors: Banov Daniel , Liu Yi , Ip Kendice , Shan Ashley , Vu Christine , Zdoryk Oleksandr , Bassani August S. , Carvalho Maria
Published: November 2023

The paucity of suitable drug formulations for pediatric patients generates a need for customized, compounded medications. This research study was set out to comprehensively analyze the physical properties of the new, proprietary anhydrous oral vehicle SuspendIt® Anhydrous, which was designed for compounding pediatric oral liquids. A wide range of tests was used, including sedimentation volume, viscosity, droplet size after dispersion in simulated gastric fluid, microscopic examination and content uniformity measurements to evaluate the properties of the anhydrous vehicle. The results showed that the vehicle exhibited consistent physical properties under varying conditions and maintained stability over time. This can be attributed to the unique blend of excipients in its formulation, which not only maintain its viscosity but also confer thixotropic behavior. The unique combination of viscous, thixotropic and self-emulsifying properties allows for rapid redispersibility, sedimentation stability, accurate dosing, potential drug solubility, dispersion and promotion of enhanced gastrointestinal distribution and absorption. Furthermore, the vehicle demonstrated long-term sedimentation stability and content uniformity for a list of 13 anhydrous suspensions. These results suggest that the anhydrous oral vehicle could serve as a versatile base for pediatric formulation, potentially filling an important gap in pediatric drug delivery. Future studies can further investigate its compatibility, stability and performance with other drugs and in different clinical scenarios.
Transferrin-Bearing, Zein-Based Hybrid Lipid Nanoparticles for Drug and Gene Delivery to Prostate Cancer Cells
Authors: Maeyouf Khadeejah , Sakpakdeejaroen Intouch , Somani Sukrut , Meewan Jitkasem , Ali-Jerman Hawraa , Laskar Partha , Mullin Margaret , MacKenzie Graeme , Tate Rothwelle J. , Dufès Christine
Published: November 2023

Gene therapy holds great promise for treating prostate cancer unresponsive to conventional therapies. However, the lack of delivery systems that can transport therapeutic DNA and drugs while targeting tumors without harming healthy tissues presents a significant challenge. This study aimed to explore the potential of novel hybrid lipid nanoparticles, composed of biocompatible zein and conjugated to the cancer-targeting ligand transferrin. These nanoparticles were designed to entrap the anti-cancer drug docetaxel and carry plasmid DNA, with the objective of improving the delivery of therapeutic payloads to prostate cancer cells, thereby enhancing their anti-proliferative efficacy and gene expression levels. These transferrin-bearing, zein-based hybrid lipid nanoparticles efficiently entrapped docetaxel, leading to increased uptake by PC-3 and LNCaP cancer cells and significantly enhancing anti-proliferative efficacy at docetaxel concentrations exceeding 1 µg/mL. Furthermore, they demonstrated proficient DNA condensation, exceeding 80% at polymer–DNA weight ratios of 1500:1 and 2000:1. This resulted in increased gene expression across all tested cell lines, with the highest transfection levels up to 11-fold higher than those observed with controls, in LNCaP cells. These novel transferrin-bearing, zein-based hybrid lipid nanoparticles therefore exhibit promising potential as drug and gene delivery systems for prostate cancer therapy.
Quantitative Analysis of a Pilot Transwell Barrier Model with Automated Sampling and Mathematical Modeling
Authors: Tárnoki-Zách Júlia , Bősze Szilvia , Czirók András
Published: November 2023

In the preclinical phase of drug development, it is necessary to determine how the active compound can pass through the biological barriers surrounding the target tissue. In vitro barrier models provide a reliable, low-cost, high-throughput solution for screening substances early in the drug candidate development process, thus reducing more complex and costly animal studies. In this pilot study, the transport properties of TB501, an antimycobacterial drug candidate, were characterized using an in vitro barrier model of VERO E6 kidney cells. The compound was delivered into the apical chamber of the transwell insert, and its concentration passing through the barrier layer was measured through the automated sampling of the basolateral compartment, where media were replaced every 30 min for 6 h, and the collected samples were stored for further spectroscopic analysis. The kinetics of TB501 concentration obtained from VERO E6 transwell cultures and transwell membranes saturated with serum proteins reveal the extent to which the cell layer functions as a diffusion barrier. The large number of samples collected allows us to fit a detailed mathematical model of the passive diffusive currents to the measured concentration profiles. This approach enables the determination of the diffusive permeability, the diffusivity of the compound in the cell layer, the affinity of the compound binding to the cell membrane as well as the rate by which the cells metabolize the compound. The proposed approach goes beyond the determination of the permeability coefficient and offers a more detailed pharmacokinetic characterization of the transwell barrier model. We expect the presented method to be fruitful in evaluating other compounds with different chemical features on simple in vitro barrier models. The proposed mathematical model can also be extended to include various forms of active transport.
Cohesive Zone Modeling of the Interface Fracture in Full-Thermoplastic Hybrid Composites for Lightweight Application
Authors: Giusti Ruggero , Lucchetta Giovanni
Published: November 2023

With the increasing demand for lightweight and high-performance materials in the automotive and aerospace industries, full-thermoplastic hybrid composites have emerged as a pivotal solution, offering enhanced mechanical properties and design flexibility. This work aims to numerically model the fracture strength in full-thermoplastic hybrid composites made by forming and overmolding organosheets. The mode I fracture was investigated by modeling the behavior of T-joint specimens under a tensile test following the cohesive zone modeling (CZM) approach. The sample was designed to replicate the connection between the laminate and the overmolded part. Double cantilever beam (DCB) specimens were manufactured with organosheets and tested to mode I opening to determine the interlaminar fracture toughness. The fracture toughness out of the mode I test with DCB specimens was used to define the CZM parameters that describe the traction-separation law. Later, due to the particular geometry of the T-join specimens that under tensile load work close to pure mode I, the cohesive parameters were determined by inverse analysis, i.e., calibrating the theoretical models to match experimental results. The fracture resistance T-joint specimens appeared dependent on the fiber-bridging phenomenon during the delamination. In particular, the presence of fiber-bridging visible from the experimental results has been replicated by virtual analyses, and it is observed that it leads to a higher energy value before the interface’s complete breakage. Moreover, a correspondence between the mode I fracture toughness of the DCB specimen and T-joint specimens was observed.
Ionenes as Potential Phase Change Materials with Self-Healing Behavior
Authors: Arriaza-Echanes Carolina , Velázquez-Tundidor María V. , Angel-López Alejandro , Norambuena Ángel , Palay Francisco E. , Terraza Claudio A. , Tundidor-Camba Alain , Ortiz Pablo A. , Coll Deysma
Published: November 2023

Ionenes are poly(ionic liquids) (PILs) comprising a polymer backbone with ionic groups along the structure. Ionenes as solid–solid phase change materials are a recent research field, and some studies have demonstrated their potential in thermal dissipation into electronic devices. Eight ionenes obtained through Menshutkin reactions were synthesized and characterized. The analysis of the thermal tests allowed understanding of how the thermal properties of the polymers depend on the aliphatic nature of the dihalogenated monomer and the carbon chain length. The TGA studies concluded that the ionenes were thermally stable with T10% above 420 °C. The DSC tests showed that the prepared ionenes presented solid–solid transitions, and no melting temperature was appreciated, which rules out the possibility of solid–liquid transitions. All ionenes were soluble in common polar aprotic solvents. The hydrophilicity of the synthesized ionenes was studied by the contact angle method, and their total surface energy was calculated. Self-healing behavior was preliminarily explored using a selected sample. Our studies show that the prepared ionenes exhibit properties that make them potential candidates for applications as solid–solid phase change materials.
Projection Micro-Stereolithography to Manufacture a Biocompatible Micro-Optofluidic Device for Cell Concentration Monitoring
Authors: Saitta Lorena , Cutuli Emanuela , Celano Giovanni , Tosto Claudio , Sanalitro Dario , Guarino Francesca , Cicala Gianluca , Bucolo Maide
Published: November 2023

In this work, a 3D printed biocompatible micro-optofluidic (MoF) device for two-phase flow monitoring is presented. Both an air–water bi-phase flow and a two-phase mixture composed of micrometric cells suspended on a liquid solution were successfully controlled and monitored through its use. To manufacture the MoF device, a highly innovative microprecision 3D printing technique was used named Projection Microstereolithography (PμSL) in combination with the use of a novel 3D printable photocurable resin suitable for biological and biomedical applications. The concentration monitoring of biological fluids relies on the absorption phenomenon. More precisely, the nature of the transmission of the light strictly depends on the cell concentration: the higher the cell concentration, the lower the optical acquired signal. To achieve this, the microfluidic T-junction device was designed with two micrometric slots for the optical fibers’ insertion, needed to acquire the light signal. In fact, both the micro-optical and the microfluidic components were integrated within the developed device. To assess the suitability of the selected biocompatible transparent resin for optical detection relying on the selected working principle (absorption phenomenon), a comparison between a two-phase flow process detected inside a previously fully characterized micro-optofluidic device made of a nonbiocompatible high-performance resin (HTL resin) and the same made of the biocompatible one (BIO resin) was carried out. In this way, it was possible to highlight the main differences between the two different resin grades, which were further justified with proper chemical analysis of the used resins and their hydrophilic/hydrophobic nature via static water contact angle measurements. A wide experimental campaign was performed for the biocompatible device manufactured through the PμSL technique in different operative conditions, i.e., different concentrations of eukaryotic yeast cells of Saccharomyces cerevisiae (with a diameter of 5 μm) suspended on a PBS (phosphate-buffered saline) solution. The performed analyses revealed that the selected photocurable transparent biocompatible resin for the manufactured device can be used for cell concentration monitoring by using ad hoc 3D printed micro-optofluidic devices. In fact, by means of an optical detection system and using the optimized operating conditions, i.e., the optimal values of the flow rate FR=0.1 mL/min and laser input power P∈{1,3} mW, we were able to discriminate between biological fluids with different concentrations of suspended cells with a robust working ability R2=0.9874 and Radj2=0.9811.
Sīrah Philosophy: A Modern Trajectory for Sīrah Studies
Authors: Sertkaya Suleyman
Published: November 2023

Prophet Muhammad is a central figure in Islam. Systematic exploration of his life and biography as a central discourse for sīrah studies remains timeless and relevant. This has made his life a focal point for study among Muslim and Western scholars for centuries, resulting in the emergence of fresh approaches in modern times. This paper delves into the concept of “sīrah philosophy,” which is vigorously advocated by Fethullah Gülen, a prominent Muslim scholar, as a novel and essential perspective for sīrah studies in modern times. Gülen’s amalgamation of the Prophet’s life and contemporary challenges underscores the enduring significance of sīrah in guiding modern discourse. Sīrah philosophy, at its core, provides a framework rooted in the Prophet’s life to draw inspiration for addressing contemporary issues. The article unpacks the practical application of sīrah philosophy through the Hudaybiya incident, a pivotal moment in the Prophet’s life during his time in Medina. From conflict resolution and peacebuilding to interfaith dialogue, Gülen’s approach leverages sīrah to propose solutions for complex contemporary problems, offering a dynamic way to engage with present-day predicaments. In essence, this article emphasises how sīrah, as envisioned by Muslim scholars like Gülen, transcends historical and contextual boundaries, enriching present-day discourse. As sīrah studies evolve, this pioneering exploration of a modern trajectory fosters a deeper appreciation of the Prophet’s legacy, facilitating comprehensive understanding for diverse audiences. This article argues that this approach is groundbreaking and innovative, paving the way for new perspectives to read and interpret sīrah in a contemporary world for a modern audience.
Infrared Small-Target Detection Based on Background-Suppression Proximal Gradient and GPU Acceleration
Authors: Hao Xuying , Liu Xianyuan , Liu Yujia , Cui Yi , Lei Tao
Published: November 2023

Patch-based methods improve the performance of infrared small target detection, transforming the detection problem into a Low-Rank Sparse Decomposition (LRSD) problem. However, two challenges hinder the success of these methods: (1) The interference from strong edges of the background, and (2) the time-consuming nature of solving the model. To tackle these two challenges, we propose a novel infrared small-target detection method using a Background-Suppression Proximal Gradient (BSPG) and GPU parallelism. We first propose a new continuation strategy to suppress the strong edges. This strategy enables the model to simultaneously consider heterogeneous components while dealing with low-rank backgrounds. Then, the Approximate Partial Singular Value Decomposition (APSVD) is presented to accelerate solution of the LRSD problem and further improve the solution accuracy. Finally, we implement our method on GPU using multi-threaded parallelism, in order to further enhance the computational efficiency of the model. The experimental results demonstrate that our method out-performs existing advanced methods, in terms of detection accuracy and execution time.
A Heterogeneity-Enhancement and Homogeneity-Restraint Network (HEHRNet) for Change Detection from Very High-Resolution Remote Sensing Imagery
Authors: Wang Biao , He Ao , Wang Chunlin , Xu Xiao , Yang Hui , Wu Yanlan
Published: November 2023

Change detection (CD), a crucial technique for observing ground-level changes over time, is a challenging research area in the remote sensing field. Deep learning methods for CD have made significant progress in remote sensing intelligent interpretation. However, with very high-resolution (VHR) satellite imagery, technical challenges such as insufficient mining of shallow-level features, complex transmission of deep-level features, and difficulties in identifying change information features have led to severe fragmentation and low completeness issues of CD targets. To reduce costs and enhance efficiency in monitoring tasks such as changes in national resources, it is crucial to promote the practical implementation of automatic change detection technology. Therefore, we propose a deep learning approach utilizing heterogeneity enhancement and homogeneity restraint for CD. In addition to comprehensively extracting multilevel features from multitemporal images, we introduce a cosine similarity-based module and a module for progressive fusion enhancement of multilevel features to enhance deep feature extraction and the change information utilization within feature associations. This ensures that the change target completeness and the independence between change targets can be further improved. Comparative experiments with six CD models on two benchmark datasets demonstrate that the proposed approach outperforms conventional CD models in various metrics, including recall (0.6868, 0.6756), precision (0.7050, 0.7570), F1 score (0.6958, 0.7140), and MIoU (0.7013, 0.7000), on the SECOND and the HRSCD datasets, respectively. According to the core principles of change detection, the proposed deep learning network effectively enhances the completeness of target vectors and the separation of individual targets in change detection with VHR remote sensing images, which has significant research and practical value.
Continuous Tracking of Forest Disturbance and Recovery in the Greater Khingan Mountains from Annual Landsat Imagery
Authors: Ren Huixin , Ren Chunying , Wang Zongming , Jia Mingming , Yu Wensen , Liu Pan , Xia Chenzhen
Published: November 2023

Understanding accurate and continuous forest dynamics is of key importance for forest protection and management in the Greater Khingan Mountains (GKM). There has been a lack of finely captured and long-term information on forest disturbance and recovery since the mega-fire of 1987 which may limit the scientific assessment of the GKM’s vegetation conditions. Therefore, we proposed a rapid and robust approach to track the dynamics of forest disturbance and recovery from 1987 to 2021 using Landsat time series, LandTrendr, and random forests (RF) models. Furthermore, we qualified the spatial characteristics of forest changes in terms of burn severity, topography, and distances from roads and settlements. Our results revealed that the integrated method of LandTrendr and RF is well adapted to track forest dynamics in the GKM, with an overall accuracy of 0.86. From 1987 to 2021, forests in the GKM showed a recovery trend with a net increase of more than 4.72 × 104 ha. Over 90% of disturbances occurred between 1987 and 2010 and over 75% of recovery occurred between 1987 and 1988. Mildly burned areas accounted for 51% of forest disturbance and severely burned areas contributed to 45% of forest recovery. Forest changes tended to occur in zones with elevations of 400–650 m, slopes of less than 9°, and within 6 km of roads and 24 km of settlements. Temporal trends of forest disturbance and recovery were mainly explained by the implementation timelines of major forestry policies. Our results provide high-resolution and time-series information on forest disturbance and recovery in the GKM which could support scientific decisions on forest management and sustainable utilization.
Iterative-Based Impact Force Identification on a Bridge Concrete Deck
Authors: Rashidi Maria , Tashakori Shabnam , Kalhori Hamed , Bahmanpour Mohammad , Li Bing
Published: November 2023

Steel-reinforced concrete decks are prominently utilized in various civil structures such as bridges and railways, where they are susceptible to unforeseen impact forces during their operational lifespan. The precise identification of the impact events holds a pivotal role in the robust health monitoring of these structures. However, direct measurement is not usually possible due to structural limitations that restrict arbitrary sensor placement. To address this challenge, inverse identification emerges as a plausible solution, albeit afflicted by the issue of ill-posedness. In tackling such ill-conditioned challenges, the iterative regularization technique known as the Landweber method proves valuable. This technique leads to a more reliable and accurate solution compared with traditional direct regularization methods and it is, additionally, more suitable for large-scale problems due to the alleviated computation burden. This paper employs the Landweber method to perform a comprehensive impact force identification encompassing impact localization and impact time–history reconstruction. The incorporation of a low-pass filter within the Landweber-based identification procedure is proposed to augment the reconstruction process. Moreover, a standardized reconstruction error metric is presented, offering a more effective means of accuracy assessment. A detailed discussion on sensor placement and the optimal number of regularization iterations is presented. To automatedly localize the impact force, a Gaussian profile is proposed, against which reconstructed impact forces are compared. The efficacy of the proposed techniques is illustrated by utilizing the experimental data acquired from a bridge concrete deck reinforced with a steel beam.
Fluctuations in Upper and Lower Body Movement during Walking in Normal Pressure Hydrocephalus and Parkinson’s Disease Assessed by Motion Capture with a Smartphone Application, TDPT-GT
Authors: Iseki Chifumi , Suzuki Shou , Fukami Tadanori , Yamada Shigeki , Hayasaka Tatsuya , Kondo Toshiyuki , Hoshi Masayuki , Ueda Shigeo , Kobayashi Yoshiyuki , Ishikawa Masatsune , Kanno Shigenori , Suzuki Kyoko , Aoyagi Yukihiko , Ohta Yasuyuki
Published: November 2023

We aimed to capture the fluctuations in the dynamics of body positions and find the characteristics of them in patients with idiopathic normal pressure hydrocephalus (iNPH) and Parkinson’s disease (PD). With the motion-capture application (TDPT-GT) generating 30 Hz coordinates at 27 points on the body, walking in a circle 1 m in diameter was recorded for 23 of iNPH, 23 of PD, and 92 controls. For 128 frames of calculated distances from the navel to the other points, after the Fourier transforms, the slopes (the representatives of fractality) were obtained from the graph plotting the power spectral density against the frequency in log–log coordinates. Differences in the average slopes were tested by one-way ANOVA and multiple comparisons between every two groups. A decrease in the absolute slope value indicates a departure from the 1/f noise characteristic observed in healthy variations. Significant differences in the patient groups and controls were found in all body positions, where patients always showed smaller absolute values. Our system could measure the whole body’s movement and temporal variations during walking. The impaired fluctuations of body movement in the upper and lower body may contribute to gait and balance disorders in patients.
Joint Reconfiguration after Failure for Performing Emblematic Gestures in Humanoid Receptionist Robot
Authors: Jutharee Wisanu , Kaewkamnerdpong Boonserm , Maneewarn Thavida
Published: November 2023

This study proposed a strategy for a quick fault recovery response when an actuator failure problem occurred while a humanoid robot with 7-DOF anthropomorphic arms was performing a task with upper body motion. The objective of this study was to develop an algorithm for joint reconfiguration of the receptionist robot called Namo so that the robot can still perform a set of emblematic gestures if an actuator fails or is damaged. We proposed a gesture similarity measurement to be used as an objective function and used bio-inspired artificial intelligence methods, including a genetic algorithm, a bacteria foraging optimization algorithm, and an artificial bee colony, to determine good solutions for joint reconfiguration. When an actuator fails, the failed joint will be locked at the average angle calculated from all emblematic gestures. We used grid search to determine suitable parameter sets for each method before making a comparison of their performance. The results showed that bio-inspired artificial intelligence methods could successfully suggest reconfigured gestures after joint motor failure within 1 s. After 100 repetitions, BFOA and ABC returned the best-reconfigured gestures; there was no statistical difference. However, ABC yielded more reliable reconfigured gestures; there was significantly less interquartile range among the results than BFOA. The joint reconfiguration method was demonstrated for all possible joint failure conditions. The results showed that the proposed method could determine good reconfigured gestures under given time constraints; hence, it could be used for joint failure recovery in real applications.
Improving Automatic Smartwatch Electrocardiogram Diagnosis of Atrial Fibrillation by Identifying Regularity within Irregularity
Authors: Velraeds Anouk , Strik Marc , van der Zande Joske , Fontagne Leslie , Haissaguerre Michel , Ploux Sylvain , Wang Ying , Bordachar Pierre
Published: November 2023

Smartwatches equipped with automatic atrial fibrillation (AF) detection through electrocardiogram (ECG) recording are increasingly prevalent. We have recently reported the limitations of the Apple Watch (AW) in correctly diagnosing AF. In this study, we aim to apply a data science approach to a large dataset of smartwatch ECGs in order to deliver an improved algorithm. We included 723 patients (579 patients for algorithm development and 144 patients for validation) who underwent ECG recording with an AW and a 12-lead ECG (21% had AF and 24% had no ECG abnormalities). Similar to the existing algorithm, we first screened for AF by detecting irregularities in ventricular intervals. However, as opposed to the existing algorithm, we included all ECGs (not applying quality or heart rate exclusion criteria) but we excluded ECGs in which we identified regular patterns within the irregular rhythms by screening for interval clusters. This “irregularly irregular” approach resulted in a significant improvement in accuracy compared to the existing AW algorithm (sensitivity of 90% versus 83%, specificity of 92% versus 79%, p < 0.01). Identifying regularity within irregular rhythms is an accurate yet inclusive method to detect AF using a smartwatch ECG.
Manipulation Direction: Evaluating Text-Guided Image Manipulation Based on Similarity between Changes in Image and Text Modalities
Authors: Watanabe Yuto , Togo Ren , Maeda Keisuke , Ogawa Takahiro , Haseyama Miki
Published: November 2023

At present, text-guided image manipulation is a notable subject of study in the vision and language field. Given an image and text as inputs, these methods aim to manipulate the image according to the text, while preserving text-irrelevant regions. Although there has been extensive research to improve the versatility and performance of text-guided image manipulation, research on its performance evaluation is inadequate. This study proposes Manipulation Direction (MD), a logical and robust metric, which evaluates the performance of text-guided image manipulation by focusing on changes between image and text modalities. Specifically, we define MD as the consistency of changes between images and texts occurring before and after manipulation. By using MD to evaluate the performance of text-guided image manipulation, we can comprehensively evaluate how an image has changed before and after the image manipulation and whether this change agrees with the text. Extensive experiments on Multi-Modal-CelebA-HQ and Caltech-UCSD Birds confirmed that there was an impressive correlation between our calculated MD scores and subjective scores for the manipulated images compared to the existing metrics.
An Industry 5.0 Perspective on Feeding Production Lines
Authors: Chivilò Michele , Meneghetti Antonella
Published: November 2023

The emerging concept of Industry 5.0 is fostering companies to consider the three pillars of human-centricity, sustainability, and resilience. How such a new perspective can be effectively declined and practically guide the introduction of new technologies is a challenge to be addressed. This study proposes a framework to support companies when introducing new solutions to feed production lines by adopting an Industry 5.0 perspective. For each fundamental pillar, critical points to focus on have been highlighted and operational checklists have been developed to effectively support the analysis and implementation of new solutions. The application of the framework and related operational checklists to a case study regarding the integration of an Autonomous Mobile Robot system has proved its validity. Following the human-centricity checklist, full acceptance of the new technology by workers has been gained, together with a safer workplace. Energy savings for material handling and recycling have been supported about the sustainability pillar, while redundancy and backup systems have increased the resilience of the feeding system.
From Pixels to Sustainability: Trends and Collaborations in Remote Sensing for Advancing Sustainable Cities and Communities (SDG 11)
Authors: Ekmen Omer , Kocaman Sultan
Published: November 2023

Remote sensing data and methods have become indispensable for observing and modeling the Earth and have great potential for monitoring a substantial portion of the targets defined under the United Nations Sustainable Development Goals (SDGs). This study investigates remote sensing research on SDG 11 (sustainable cities and communities) from 2016 to 2023, highlighting the growing interest in the field. By evaluating a large number of selected articles (6820) using a specialized keyword selection strategy and various filters, a significant increase in publication frequency was observed. Remote Sensing and Sustainability were found to be the most relevant journals. A trend towards research addressing urban ecological quality, changes in land use patterns, and the impact of impervious surfaces was found in domain-specific citations. Semi-niche motor themes encompass deep learning, feature extraction, and semantic segmentation. Simultaneously, remote sensing, machine learning, and change detection serve as foundational motor themes, merging elements of both basic and motor themes. The introduction of new analytical methods (e.g., new indices), together with the use of open data and crowdsourcing, has gained great interest. While there has been a strong focus on land cover, urban expansion, and land surface temperature, the main gaps were identified in regional development, disaster, resilience, natural and cultural heritage, housing, and inclusiveness. The findings show the significance of remote sensing research and its practical applications for shaping urban policy, planning strategies, and sustainable urban development. By extracting research patterns using centrality and density analyses and identifying underexplored areas, valuable insights into relationships, significance, and developmental progress within SDG 11-related remote sensing research were gained and may contribute to future planning and informing policymaking decisions.
A Systematic Review of International and Internal Climate-Induced Migration in Africa
Authors: Ofori Desmond Oklikah , Bandauko Elmond , Kutor Senanu Kwasi , Odoi Amanda , Asare Akosua Boahemaa , Akyea Thelma , Arku Godwin
Published: November 2023

Academics and policymakers have been paying close attention to the impact of climate change on migration in recent years. This phenomenon piqued interest because the factors driving environmentally induced migration are complex and manifold. Noticeably, there has been considerable scholarship on climate change and migration in Africa. However, there has not been a concerted effort to periodically review the existing literature to systematically document the state of scholarship. Using a standardized systematic review procedures to analyze 22 peer-reviewed studies published between 2000 and 2022, we found that climate change impacts migration in many complex and multilayered forms. Beyond what has already been established in the literature on climate-related migration such as environmental effects on migration; migration as an adaptation strategy; and the influence of environmental and non-environmental factors on migration; we also found that (1) studies on climate-induced migration in Africa intensely focused on SSA, suggesting an uneven study of the region, (2) heavily affected people tend to be immobile, and (3) young people have high migration intentions due to harsh climate insecurities. These findings require urgent government and stakeholder attention. Specifically, there is a need for scholarship to interrogate the climate change–immobility nexus in order to design appropriate in situ or ex situ adaptation strategies to support lives and livelihoods.
Spatial Risk Assessment of the Effects of Obstacle Factors on Areas at High Risk of Geological Disasters in the Hengduan Mountains, China
Authors: Gao Haixin , Zhou Qiang , Niu Baicheng , Zhang Shengpeng , Zhi Zemin
Published: November 2023

The Hengduan Mountains in China are known for their complex geological environment, which leads to frequent geological disasters that pose significant threats to the safety and economic and social development of the local population. In this study, we developed develop a multi-dimensional evaluation index system from the aspects of economy, society, ecology, and infrastructure, and the resilience inference measurement (RIM) model was developed to assess resilience to regional disasters. The clustering evaluation of exposure, damage, and recovery variables in four states was conducted by way of K-means clustering. The results of K-means clustering are confirmed by discriminant analysis, and the disaster resilience index was empirically verified once. At the same time, the obstacle factor was further analyzed with the obstacle degree model. The results indicate that there are 8 susceptible areas, 23 recovering areas, 27 resistant areas, and 7 usurper areas. The classification accuracy of the model is 95.4%. The disaster resilience of high-risk areas was found to be low, with “extremely poor” differentiation, where the majority of the areas had low resilience and only a minority had high resilience. A “high in the southeast and low in the northwest” spatial distribution was observed. High-resilience areas were “dotted” and mainly concentrated in core areas with a high population density and strong economic activity, while low-resilience areas had a pattern of “edge extension” and were mainly distributed in the transition zone between the Qinghai–Tibet and Yunnan Plateaus. There were clear differences in the barriers of disaster resilience among the 65 counties (cities). The economic barrier degree was found to be the largest barrier to disaster resilience, followed by ecological, social, and infrastructure barrier degrees. The main factors affecting the distribution of disaster resilience in the high-risk areas were topographic relief, proportion of female population, cultivated land area, industrial structure, number of industrial enterprises above a designated size, and drainage pipeline density in the built-up area. Additionally, primary barrier factors classify the 65 counties (cities) into three types: economic constraint, natural environment constraint, and population structure constraint.
Photocatalytic Degradation of Chlorinated Hydrocarbons: The By-Product of the Petrochemical Industry Using Ag-Cu/Graphite Bimetallic Carbon Nitride
Authors: Blall Elsayed G. , Toderas Monica , Ezzat Abbas A. , Abdou Hossam A. , Mahmoud Amira S. , Shokry Fathy
Published: November 2023

In this study, the author improved and modified g-C3N4 by doping it with the metals Ag and Cu, which changed the photochemical properties of g-C3N4, narrowed the band gap, and improved the photocatalytic performance regarding quantum efficiency. Organic hydrocarbons such as 1,2-dichloroethane (DCE) are very stable prepared materials produced as intermediates to obtain polyvinyl chloride, and the prepared photo-catalyst is an innovative method for extreme decomposition of chlorinated hydrocarbons. However, some significant results were obtained using different analysis techniques. X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR) showed that the addition of Ag and Cu-NPS partially altered the structure of pure graphitic carbon nitride (g-C3N4-Pure). Scanning electron microscopy (TEM) analysis revealed that the morphological features of Ag-Cu/g-C3N4 contain quantum dots of Ag and Cu nanoparticles in addition to 2d-g-C3N4. The better separation of the photo-generated charge carriers is attributed to better photoactivity in the case of 0.3 g Ag-Cu/g-C3N4 with a reaction time of less than 30 min. Furthermore, the Ag-Cu/g-C3N4 recycling experiment showed that the catalyst remained stable after three stages of the pyrolysis experimental cycle. Another clear indicator of DCE degradation is the measurement using the titration of the Cl ions released by the decomposition.
The Prevalence and Impact of Innovative CSR Strategies in Manufacturing Enterprises in the Silesian Voivodeship: A Multifaceted Analysis of Benefits, Challenges, and Market Adaptability
Authors: Wolniak Radosław , Sadłowska-Wrzesińska Joanna , Miciuła Ireneusz , Wojtaszek Henryk , Głuchowska-Wójcicka Maja , Skelnik Klaudia , Tylżanowski Roman , Nejman Żaneta
Published: November 2023

This article presents a comprehensive analysis of the occurrence of innovative solutions in accordance with CSR in various companies. It turns out that 71% of medium-sized enterprises (50–249 people) and 64% of smaller companies (10–49 people and up to 9 people) declare the introduction of innovative solutions in CSR strategies, which proves that innovations are not limited to large companies. A responsible approach to business can affect competitiveness and positive public perception. The implementation of a CSR strategy increases profits, improves image, increases customer loyalty, attracts media attention, and opens up new markets. The hindering factor is the additional cost of implementing CSR activities, insufficient knowledge and awareness of CSR, and unclear regulations and market conditions, as well as the need to adapt the organizational structure and culture. CSR strategies are important for the success of enterprises and society, and solving potential problems allows for effective introduction of responsible practices. In order to obtain the presented data, two research methods were used: an analysis of the international literature sources and a survey by manufacturing firms in the Silesian Voivodeship.
Analyzing and Optimizing the Emission Impact of Intersection Signal Control in Mixed Traffic
Authors: Fan Jieyu , Najafi Arsalan , Sarang Jokhio , Li Tian
Published: November 2023

Signalized intersections are one of the typical bottlenecks in urban transport systems that have reduced speeds and which have substantial vehicle emissions. This study aims to analyze and optimize the impacts of signal control on the emissions of mixed traffic flow (CO, HC, and NOx) containing both heavy- and light-duty vehicles at urban intersections, leveraging high-resolution field emission data. An OBEAS-3000 (Manufacturer: Xiamen Tongchuang Inspection Technology Co., Ltd., Xiamen, China.) vehicle emission testing device was used to collect microscopic operating characteristics and instantaneous emission data of different vehicle types (light- and heavy-duty vehicles) under different operating conditions. Based on the collected data, the VSP (Vehicle Specific Power) model combined with the VISSIM traffic simulation platform was used to quantitatively analyze the impact of signal control on traffic emissions. Heavy-duty vehicles contribute to most of the emissions regardless of the low proportion in the traffic flows. Afterward, a model is proposed for determining the optimal signal control at an intersection for a specific percentage of heavy-duty vehicles based on the conversion of emission factors of different types of vehicles. Signal control is also optimized based on conventional signal timing, and vehicle emissions are calculated. In the empirical analysis, the changes in CO, HC, and NOx emissions of light- and heavy-duty vehicles before and after conventional signal control optimization are quantified and compared. After the signal control optimization, the CO, HC, and NOx emissions of heavy-duty vehicles were reduced. The CO and HC emissions of light-duty vehicles were reduced, but the NOx emissions of light-duty vehicles remained unchanged. The emissions of vehicles after optimized signal control based on vehicle conversion factors are reduced more significantly than those after conventional optimized signal control. This study provides a scientific basis for developing traffic management measures for energy saving and emission reduction in transport systems with mixed traffic.
Process-Oriented Design Methodologies Inspired by Tropical Plants
Authors: McCormick Elizabeth L. , Cooper Elizabeth A. , Esfandiar Mahsa , Roberts MaryGrayson , Shields Lindsay
Published: November 2023

In light of the escalating climate crisis, there is a pressing need for a significant shift in how we design the built environment to effectively confront global challenges. Natural systems have inspired scientists, architects, and engineers for centuries; however, conventional biomimetic approaches often focus on superficial aspects, disregarding the underlying complexities. While this approach may lead to a more efficient outcome, it operates under the assumption that the organism functions exclusively within the confines of human knowledge, which are inherently limited by established epistemological and technological systems. This study advocates for a departure from conventional biomimetic approaches and asks the mechanisms of the biological system to inform the process of translation, as opposed to simply defining the outcome. By relinquishing control to material properties and dynamic processes of the biological analog, this study explores the generation of novel, bio-inspired dynamic formworks through non-linear fabrication processes. Specifically, it investigates the thermal properties of accessible building materials, enabling them to respond to environmental conditions without sophisticated technology or human intervention. By embracing chance and unpredictability, translated behaviors are granted the same influence as human intervention. Drawing inspiration from adaptive plant physiology, this research seeks to inspire innovative, climate-responsive methodological practices within broader architectural systems.
The Effects of Tourism Development on Eco-Environment Resilience and Its Spatio-Temporal Heterogeneity in the Yangtze River Economic Belt, China
Authors: Wang Kun , Chen Xiangtai , Lei Zhenxian , Zhao Songxin , Zhou Xiao
Published: November 2023

Tourism sustainability is a significant approach to forming a synergistic model of industry and ecology in ecologically vulnerable areas. Scientifically detecting the effect mechanism of tourism development on eco-environment resilience is important in achieving regional social-ecological system sustainability. In this work, empirical exploration is conducted on the tourism development index (TDI) and eco-environment resilience index (ERI) in the Yangtze River Economic Belt (YREB) to study the spatio-temporal heterogeneity of TDI’s effect on the ERI. The results indicate significant growth in the TDI in the YREB, with the formation of tourist clusters around Shanghai and Chongqing as the core. Although the ERI typically exhibits a declining trend, the rate of decline has notably slowed, forming a “high at the sides and low in the middle” spatial pattern. The TDI and ERI are spatially dependent in the YREB, with predominantly high-high (HH) and low-high (LH) clusters in Shanghai, Zhejiang, and Jiangsu. Conversely, upstream regions with strong eco-environmental foundations exhibit low-low (LL) and high-low (HL) clusters. In general, the TDI promotes the ERI, but there is significant spatio-temporal heterogeneity in the YREB. Positive impact regions are expanding, while negative impact regions are shrinking. These results could provide scientific evidence for differentiated classification and control policies in the YREB.
Continuous Dynamic Analysis Method and Case Verification of Cable Structure Based on Digital Twin
Authors: Wang Zeqiang , Li Mingming , Liu Zhansheng , Dezhkam Majid , Zhao Yifeng , Hu Yang
Published: November 2023

The safety and quality of cable structure construction necessitate a comprehensive analysis approach. However, conventional methods suffer from difficulties in the temporal and spatial integration of construction information and low efficiency in construction analysis. This study proposes a multi-dimensional digital twin model for cable structure construction to optimize conventional calculation methods. Firstly, this study proposes a continuous dynamic analysis method for cable structures based on the digital twin, which reveals the mechanism behind the continuous dynamic analysis of cable structures. Furthermore, a multidimensional digital twin model is established, and the model is continuously corrected using real-time data collected by sensors. The intrinsic constitution equation and equilibrium equation are also corrected to improve the finite element analysis method of the cable structure. An intelligent simulation system for cable structures was developed and effectively applied to actual cable structure construction scenarios. The same finite element analysis model was used to calculate all stages from lifting to tension forming. Construction information fusion ensured continuous dynamic analysis with an average calculation accuracy higher than 97%.