bluuebunny/crossref_metadata_2025 huggingface dataset:
Short-Term Outcomes of XEN45 Standalone versus Combined with Phacoemulsification in Open-Angle Glaucoma Patients: A Retrospective Study
Authors: Pirani Vittorio , Virgili Francesco , Ramovecchi Vincenzo
Published: December 2023

The XEN45 is a minimally invasive glaucoma surgery device commonly used in clinical practice. This retrospective study included consecutive patients with open-angle glaucoma who underwent a XEN45 implant with mitomycin C, either alone or in combination with phacoemulsification, between June 2015 and March 2021. The primary end point was the mean change in intraocular pressure (IOP) from the baseline to month 6. A total of 677 eyes, 395 (58.3%) in the XEN alone group and 282 (41.7%) in the XEN+Phaco group, were included in this study. The preoperative IOP was significantly lowered from 28.7 ± 8.6 mmHg and 25.4 ± 6.9 mmHg to 13.5 ± 5.0 mmHg and 13.5 ± 4.1 mmHg at month 6 in the XEN solo and XEN+Phaco groups, respectively, with p < 0.0001 each. The mean (95% confidence interval) number of ocular hypotensive medications was significantly reduced from 3.3 (3.2–3.4) to 0.2 (0.1–0.2) and from 3.1 (2.9–3.2) to 0.2 (0.1–0.2) in the XEN solo and XEN+Phaco groups, respectively, with p < 0.0001 each. Needling was performed in 228 (33.7%) eyes. Conclusions: the XEN implant significantly reduces both IOP and the number of ocular hypotensive medications. IOP lowering was higher in the XEN solo group than in the XEN+Phaco one, although such a difference was only evident during the first month after surgery.
The Investigation of the Production of Salt-Added Polyethylene Oxide/Chitosan Nanofibers
Authors: Varnaitė-Žuravliova Sandra , Savest Natalja , Baltušnikaitė-Guzaitienė Julija , Abraitienė Aušra , Krumme Andres
Published: December 2023

The influence of different concentrations of salt-added polyethylene oxide (PEO) on the spinnability of chitosan (CS)/PEO + NaCl blends that could be used as a component part of filters for water treatment or nanofiber membranes as well as for medical applications was investigated in this study. The morphological properties of manufactured nanofibers were analyzed as well. It was determined that an increase of PEO concentration resulted mostly in thin and round nanofibers formed during electrospinning, but the manufacturing process became complex, because many wet fibers reached the collector while spinning. Also, it was noticed that the salt was not dissolved completely in the polymer solutions and some crystals were seen in the SEM images of manufactured fiber mats. However, the addition of salt resulted in lower viscosity and better conductivity of solution and fiber mats as well. The opposite effect was observed as the concentration of PEO was increased. The orientation of produced nanofibers as well as their diameter were analyzed with commercially available software. It was determined that the results obtained by software and microscopically are repeatable. The difference among the results of diameter calculated with software and taken by microscope varied from 0% to approximately 12%. The FTIR analyses indicated that alterations in polymer concentrations or the addition of salt did not induce any discernible changes in the chemical composition or nature of the materials under investigation. The sodium chloride present in the solutions enhanced electrical properties and increased conductivity values more than 50 times for PEO solutions and six times for CS/PEO blend solutions, compared to conductivity values of solutions without salt. To assess the thermal characteristics of the PEO/CS blend nanofibers, measurements using a differential scanning calorimeter (DSC) to determine melting (Tm) and crystallization (Tc) temperatures, as well as specific heat capacities were conducted. These parameters were derived from the analysis of endothermic and exothermic peaks observed in the DSC data. It showed that all produced nanofibers were semicrystalline.
Design and Evaluation of an Adjustable Compliant Constant-Force Microgripper
Authors: He Jiahang , Liu Yinong , Yang Chunbiao , Tong Zongdi , Wang Guangwei
Published: December 2023

Precise control of the manipulating force within an appropriate range is crucial to prevent potential damage to the operating object. However, achieving accurate force control through force feedback is challenging in micro-scale applications. This study presents the design of a quasi-zero stiffness-compliant constant-force microgripper with adjustable force output. The parameters of the constant-force mechanism are designed using a model-based optimization method. By utilizing this mechanism, a compliant microgripper capable of providing adjustable constant-force output is developed to overcome the limitation of traditional grippers that offer only a single constant force. Finite element analysis is performed to simulate the behavior and verify the stability of the constant-force output. Furthermore, an experimental platform is constructed to validate the mechanical properties of the developed microgripper. The experimental results demonstrate that the automatically optimized structural parameters enable the microgripper to achieve the desired constant-force value of 2 N with an adjustable range of 0.15 N. These findings provide a further basis for the application and promotion of compliant constant-force structures.
Fabrication and Polishing Performance of Diamond Self-Sharpening Gel Polishing Disk
Authors: Xu Lanxing , Feng Kaiping , Zhao Liang , Lyu Binghai
Published: December 2023

A diamond gel polishing disk with self-sharpening ability is proposed to solve the problem of glazing phenomenon in the gel polishing disks. Aluminum nitride (AlN) powder with silica sol film coating (A/S powder) is added to the polishing disk, and a specific solution is used to dissolve the A/S powder during polishing, forming a pore structure on the polishing disk. To realize the self-sharpening process, the dissolution property of the A/S powder is analyzed. The effect of A/S powder content on the friction and wear performance and the polishing performance of 4H-SiC wafers are investigated. Results showed that the friction coefficient of the polishing disk with 9 wt% A/S powder content is the most stable. The surface roughness Ra of 2.25 nm can be achieved, and there is no obvious glazing phenomenon on the polishing disk after polishing. The surface roughness of the 4H-SiC wafer is reduced by 38.8% compared with that of the polishing disk with no A/S powder addition after rough polishing, and the 4H-SiC wafer then obtained a damage-free surface with a Ra less than 0.4 nm after fine polishing by chemical mechanical polishing (CMP).
A Comprehensive Examination of Vegan Lifestyle in Italy
Authors: Stenico Annachiara , Zarantonello Diana , Vittadello Fabio , Kob Michael
Published: December 2023

The popularity of veganism and plant-based diets is rapidly increasing worldwide, including in Italy, where more individuals and families are adopting this lifestyle. However, medical and health professionals often lack the necessary knowledge and are skeptical about this diet despite the scientific evidence. It is important for them to provide support and expertise to those following this diet. The survey evaluated various aspects of the lifestyle of Italian vegans living in Italy and abroad, including food frequency, vitamin and mineral supplementation, relationship with medical and health professionals, and perceived difficulties in daily life. The emphasis was on potentially critical aspects for those following this dietary choice. A cross-sectional survey was conducted in Italy between March and April 2022. A questionnaire was distributed through social media platforms such as Instagram, Facebook, and Telegram, and 2180 Italian adults who follow a vegan diet completed it. The survey found that most of the vegan population surveyed were female, showed a greater sensitivity to ethical issues, were aware of the need for vitamin B12 supplementation, and followed healthy-eating guidelines. It is evident that despite the increasing popularity of plant-based diets, many medical and health professionals remain cautious and hesitant to recommend them.
Subclinical Hypothyroidism in Patients with Obesity and Metabolic Syndrome: A Narrative Review
Authors: Biondi Bernadette
Published: December 2023

The literature on the connection between obesity, metabolic syndrome, and subclinical hypothyroidism is critically analyzed in this narrative review. These conditions are frequently observed among adult populations and various studies and meta-analyses have assessed their association. The prevalence of subclinical hypothyroidism in obese individuals is higher than in non-obese subjects and this trend is more pronounced in unhealthy obesity phenotypes. However, the diagnosis and treatment of subclinical hypothyroidism can be difficult in obese patients. Exaggerated body fat is linked to thyroid hypoechogenicity as evident through ultrasonography and euthyroid obese people have greater TSH, FT3, and FT3/FT4 ratios than non-obese individuals in a euthyroid condition. Moreover, a reduced expression of the TSH receptor and altered function of deiodinases has been found in the adipose tissue of obese patients. Current data do not support the necessity of a pharmacological correction of the isolated hyperthyrotropinemia in euthyroid obese patients because treatment with thyroid hormone does not significantly improve weight loss and the increase in serum TSH can be reversible after hypocaloric diet or bariatric surgery. On the other hand, obesity is linked to elevated leptin levels. Inflammation can raise the risk of Hashimoto thyroiditis, which increases the likelihood that obese patients will experience overt or subclinical hypothyroidism. Both metabolic syndrome and subclinical hypothyroidism are associated with atherosclerosis, liver and kidney disease. Hence, the association of these two illnesses may potentiate the adverse effects noted in each of them. Subclinical hypothyroidism should be identified in patients with obesity and treated with appropriate doses of L-thyroxine according to the lean body mass and body weight. Randomized controlled trials are necessary to verify whether treatment of thyroid deficiency could counteract the expected risks.
The Role of Gut Microbiota and Leaky Gut in the Pathogenesis of Food Allergy
Authors: Poto Remo , Fusco William , Rinninella Emanuele , Cintoni Marco , Kaitsas Francesco , Raoul Pauline , Caruso Cristiano , Mele Maria Cristina , Varricchi Gilda , Gasbarrini Antonio , Cammarota Giovanni , Ianiro Gianluca
Published: December 2023

Food allergy (FA) is a growing public health concern, with an increasing prevalence in Western countries. Increasing evidence suggests that the balance of human gut microbiota and the integrity of our intestinal barrier may play roles in the development of FA. Environmental factors, including industrialization and consumption of highly processed food, can contribute to altering the gut microbiota and the intestinal barrier, increasing the susceptibility to allergic sensitization. Compositional and functional alterations to the gut microbiome have also been associated with FA. In addition, increased permeability of the gut barrier allows the translocation of allergenic molecules, triggering Th2 immune responses. Preclinical and clinical studies have highlighted the potential of probiotics, prebiotics, and postbiotics in the prevention and treatment of FA through enhancing gut barrier function and promoting the restoration of healthy gut microbiota. Finally, fecal microbiota transplantation (FMT) is now being explored as a promising therapeutic strategy to prevent FA in both experimental and clinical studies. In this review article, we aim to explore the complex interplay between intestinal permeability and gut microbiota in the development of FA, as well as depict potential therapeutic strategies.
Diet Quality and Mortality among Chinese Adults: Findings from the China Health and Nutrition Survey
Authors: Zheng Jiali , Zhu Tianren , Li Fangyu , Wu Han , Jiang Shuo , Shivappa Nitin , Hébert James R. , Li Xiaoguang , Li Yan , Wang Hui
Published: December 2023

The association between diet quality and all-cause mortality in Chinese population is unclear. We aimed to study the associations of three a priori diet quality indices—including the Diet Quality Index-International (DQI-I), Chinese Healthy Eating Index (CHEI), and energy-adjusted Dietary Inflammatory Index (E-DII)—and their included components with all-cause mortality. We used baseline data from the 2004, 2006, 2009, and 2011 waves of the China Health and Nutrition Survey (CHNS). We used a multivariable-adjusted Cox model to examine the associations between DQI-I, CHEI, and E-DII with all-cause mortality. During a mean of 7 years of follow-up, a total of 461 deaths occurred among 12,914 participants. For DQI-I, there were significant inverse associations with mortality for the variety score (HRQ4 vs. Q1 = 0.69, 95%CI = 0.52–0.92) and overall balance score (HR>0 vs. 0 = 0.81, 95%CI = 0.66–0.91). The adequacy score of CHEI was associated with 40% less risk of all-cause mortality (HRQ4 vs. Q1 = 0.60, 95%CI = 0.43–0.84). E-DII was not associated with mortality. An estimated 20.1%, 13.9%, and 31.3% of total mortality would be averted if the DQI-I variety score, DQI-I overall balance score, and CHEI adequacy score improved from the bottom to the top quartile, respectively. Improving diet quality, especially improving diet variety and adequacy, and having a more balanced diet may reduce all-cause mortality in Chinese adults.
Active Compounds of Panax ginseng in the Improvement of Alzheimer’s Disease and Application of Spatial Metabolomics
Authors: Zhang Meng , Niu Huazhou , Li Qingqing , Jiao Lili , Li Hui , Wu Wei
Published: December 2023

Panax ginseng C.A. Meyer (P. ginseng) is one of the more common traditional Chinese medicines (TCMs). It contains numerous chemical components and exhibits a range of pharmacological effects. An enormous burden is placed on people’s health and life by Alzheimer’s disease (AD), a neurodegenerative condition. Recent research has shown that P. ginseng’s chemical constituents, particularly ginsenosides, have a significant beneficial impact on the prevention and management of neurological disorders. To understand the current status of research on P. ginseng to improve AD, this paper discusses the composition of P. ginseng, its mechanism of action, and its clinical application. The pathogenesis of AD includes amyloid beta protein (Aβ) generation and aggregation, tau protein hyperphosphorylation, oxidant stress, neuroinflammation, mitochondrial damage, and neurotransmitter and gut microbiota disorders. This review presents the key molecular mechanisms and signaling pathways of the active ingredients in P. ginseng involved in improving AD from the perspective of AD pathogenesis. A P. ginseng-related signaling pathway network was constructed to provide effective targets for the treatment of AD. In addition, the application of spatial metabolomics techniques in studying P. ginseng and AD is discussed. In summary, this paper discusses research perspectives for the study of P. ginseng in the treatment of AD, including a systematic and in-depth review of the mechanisms of action of the active substances in P. ginseng, and evaluates the feasibility of applying spatial metabolomics in the study of AD pathogenesis and pharmacological treatment.
Pharmacological Advances for Treatment in Hypertension
Authors: Gasparotto Junior Arquimedes
Published: December 2023

Hypertension plays a significant role in the development of cardiovascular disease and renal diseases, which can heighten the likelihood of experiencing related conditions like myocardial infarction, stroke, and heart failure [...]
Molecular Marvels: Small Molecules Paving the Way for Enhanced Gene Therapy
Authors: Hasselbeck Sebastian , Cheng Xinlai
Published: December 2023

In the rapidly evolving landscape of genetic engineering, the advent of CRISPR-Cas technologies has catalyzed a paradigm shift, empowering scientists to manipulate the genetic code with unprecedented accuracy and efficiency. Despite the remarkable capabilities inherent to CRISPR-Cas systems, recent advancements have witnessed the integration of small molecules to augment their functionality, introducing new dimensions to the precision and versatility of gene editing applications. This review delves into the synergy between CRISPR-Cas technologies based specifically on Cas9 and small-molecule drugs, elucidating the pivotal role of chemicals in optimizing target specificity and editing efficiency. By examining a diverse array of applications, ranging from therapeutic interventions to agricultural advancements, we explore how the judicious use of chemicals enhances the precision of CRISPR-Cas9-mediated genetic modifications. In this review, we emphasize the significance of small-molecule drugs in fine-tuning the CRISPR-Cas9 machinery, which allows researchers to exert meticulous control over the editing process. We delve into the mechanisms through which these chemicals bolster target specificity, mitigate off-target effects, and contribute to the overall refinement of gene editing outcomes. Additionally, we discuss the potential of chemical integration in expanding the scope of CRISPR-Cas9 technologies, enabling tailored solutions for diverse genetic manipulation challenges. As CRISPR-Cas9 technologies continue to evolve, the integration of small-molecule drugs emerges as a crucial avenue for advancing the precision and applicability of gene editing techniques. This review not only synthesizes current knowledge but also highlights future prospects, paving the way for a deeper understanding of the synergistic interplay between CRISPR-Cas9 systems and chemical modulators in the pursuit of more controlled and efficient genetic modifications.
Potency and Powder X-ray Diffraction (PXRD) Evaluation of Levothyroxine Sodium Tablets under Ambient, Accelerated, and Stressed Conditions
Authors: Okezue Mercy A. , Byrn Stephen R. , Probost Josiah , Lucas Madison , Clase Kari L.
Published: December 2023

Levothyroxine tablets, although highly prescribed in the United States, have been one of the most frequently recalled products. Because of the importance of the medication, several efforts have been put in place by the United States Food and Drug Administration (US FDA) to control the quality of levothyroxine tablets available to patients using the drug. The choice of excipients used in the formulation has been shown to impact the hygroscopicity and microenvironment, and ultimately the stability of the levothyroxine tablets formulations. Based on information generated from the US FDA Enforcement Report database, one of the main reasons for recalls is the low potency of different batches of the product. The yearly product recall trends for levothyroxine formulations were determined using the FDA Enforcement Report database. Three brands of levothyroxine tablets were selected with excipient lists similar to those products that have been historically recalled. The samples were placed at ambient (~23 °C), accelerated stability (40 °C/75% RH), and stress (50 °C/75% RH) conditions for up to 6 months. Sample potencies were determined at 0, 1.5, 3, and 6 months using the methods for assay and impurities in the United States Pharmacopeia (USP) monograph for levothyroxine tablets. Additional sample monitoring was conducted by overlaying the initial powder X-ray diffractograms (PXRD) of the samples from 0 months with the patterns generated thereafter. There has been a decline in the number of levothyroxine tablets recalled over the years. The highest numbers of recalls were recorded in the years 2013 [33] and 2020 [23]; no recalls occurred in the years 2019 and 2022. All of the brands evaluated met the USP 95.0–105.0% assay requirements at 1.5 months under accelerated conditions; only one of the brands complied at 3 months. Under ambient conditions, two brands were stable at 6 months, with borderline assay results. For stability, levothyroxine was found in microgram quantities in the formulations and PXRD could not detect changes at these low levels. However, we found some distinguishing data for samples under stress conditions.
First In Vivo Applicational Data of Foam-Based Intrathoracic Chemotherapy (FBiTC) in a Swine Model
Authors: Khosrawipour Carolina , Nicpoń Jakub , Kiełbowicz Zdzisław , Prządka Przemysław , Liszka Bartłomiej , Zielinski Kacper , Khosrawipour Veria , Li Shiri , Lau Hien , Kulas Joanna , Diakun Agata , Kielan Wojciech , Mikolajczk-Martinez Agata , Chabowski Mariusz
Published: December 2023

Background: For decades, both intraperitoneal and pleural chemotherapy (IPC) have been delivered as a liquid solution. Recent studies suggest that foam carriers outperform liquid carriers for locoregional chemotherapy. For the first time, this study aims to evaluate the feasibility, safety, and characteristics of foam-based intrathoracic chemotherapy (FBiTC) in an in vivo setting. Methods: In this study, contrast-enhanced FBiTC with doxorubicin was delivered via video-assisted thoracoscopy (VAT) in three swine under general anesthesia. Intraoperative and postoperative parameters, blood analyses, vital signs, and anesthesiologic data were collected. Additionally, an intraoperative computer tomography (CT) scan was performed, and histological tissue sections were collected and further analyzed using fluorescence microscopy. Results: FBiTC was delivered without major complications. End-tidal capnometry detected increased CO2 levels with reduced peripheral oxygen saturation and increased blood pressure and heart rate. No major intra- or postoperative complications were observed. CT scans confirmed a multidirectional distribution pattern of foam. Postoperative laboratory workup did not reveal any critical changes in hemoglobin, white blood count, or platelets. There was no evidence of critical kidney impairment or liver function. Fluorescence microscopy of tissue specimen detected doxorubicin in pleural tissues. Discussion: Our preliminary results are encouraging and indicate that FBiTC is feasible. However, to consider a possible clinical application, further studies are required to investigate the pharmacologic, pharmacodynamic, and physical properties of FBiTC and to ensure the safety of the overall procedure regarding oxygenation levels and capnography parameters.
A Dialogic Theology of Migration: Martin Buber and Eugen Rosenstock-Huessy
Authors: Maor Zohar
Published: December 2023

Martin Buber (1878–1965) and Eugen Rosenstock-Huessy (1888–1973) were influential theologians and intellectuals known for their heterodox theologies and for their visions of a society based on dialogue. Both experienced migration. Buber emigrated during his teens from Vienna to Galicia, then, after his marriage, from Vienna to Germany, and finally from Germany to Palestine in 1938. Rosenstock-Huessy, a Christian theologian of Jewish origin, fled Germany in the wake of the Nazi rise to power in 1933. Independently and in different contexts, these thinkers employed their theologies in the 1930s and 1940s, advocating for immigration against the prevailing ideas of nativism and developing an (embryonic) theory and praxis of dialogic integration. Both sought to replace the popular totalistic and intolerant melting-pot ideology. This essay explores Buber’s and Rosenstock-Huessy’s approaches to immigration and its reception, the influence of their immigration experiences, and the relation to their approaches to other aspects of their thought. It explores the nativist theological approaches they opposed and the anti-nativism that might have inspired them. Finally, this essay examines the novelty of their approaches; while their theological advocacy of immigration was unique only in their times, their dialogical approach to integration stands out, even with regard to the contemporary multicultural approach, due to its theological edge.
Parallelized Inter-Image k-Means Clustering Algorithm for Unsupervised Classification of Series of Satellite Images
Authors: Han Soohee , Lee Jeongho
Published: December 2023

As the volume of satellite images increases rapidly, unsupervised classification can be utilized to swiftly investigate land cover distributions without prior knowledge and to generate training data for supervised (or deep learning-based) classification. In this study, an inter-image k-means clustering algorithm (IIkMC), as an improvement of the native k-means clustering algorithm (kMC), was introduced to obtain a single set of class signatures so that the classification results could be compatible among multiple images. Because IIkMC was a computationally intensive algorithm, parallelized approaches were deployed, using multi-cores of a central processing unit (CPU) and a graphics processing unit (GPU), to speed up the process. kMC and IIkMC were applied to a series of images acquired in a PlanetScope mission. In addition to the capability of the inter-image compatibility of the classification results, IIkMC could settle the problem of incomplete segmentation and class canceling revealed in kMC. Based on CPU parallelism, the speed of IIkMC improved, becoming up to 12.83 times better than sequential processing. When using a GPU, the speed improved up to 25.53 times, rising to 39.00 times with parallel reduction. From the results, it was confirmed IIkMC provided more reliable results than kMC, and its parallelism could facilitate the overall inspection of multiple images.
Detection of Rubber Tree Powdery Mildew from Leaf Level Hyperspectral Data Using Continuous Wavelet Transform and Machine Learning
Authors: Cheng Xiangzhe , Feng Yuyun , Guo Anting , Huang Wenjiang , Cai Zhiying , Dong Yingying , Guo Jing , Qian Binxiang , Hao Zhuoqing , Chen Guiliang , Liu Yixian
Published: December 2023

Powdery mildew is one of the most significant rubber tree diseases, with a substantial impact on the yield of natural rubber. This study aims to establish a detection approach that coupled continuous wavelet transform (CWT) and machine learning for the accurate assessment of powdery mildew severity in rubber trees. In this study, hyperspectral reflectance data (350–2500 nm) of healthy and powdery mildew-infected leaves were measured with a spectroradiometer in a laboratory. Subsequently, three types of wavelet features (WFs) were extracted using CWT. They were as follows: WFs dimensionally reduced by the principal component analysis (PCA) of significant wavelet energy coefficients (PCA-WFs); WFs extracted from the top 1% of the determination coefficient between wavelet energy coefficients and the powdery mildew disease class (1%R2-WFs); and all WFs at a single decomposition scale (SS-WFs). To assess the detection capability of the WFs, the three types of WFs were input into the random forest (RF), support vector machine (SVM), and back propagation neural network (BPNN), respectively. As a control, 13 optimal traditional spectral features (SFs) were extracted and combined with the same classification methods. The results revealed that the WF-based models all performed well and outperformed those based on SFs. The models constructed based on PCA-WFs had a higher accuracy and more stable performance than other models. The model combined PCA-WFs with RF exhibited the optimal performance among all models, with an overall accuracy (OA) of 92.0% and a kappa coefficient of 0.90. This study demonstrates the feasibility of combining CWT with machine learning in rubber tree powdery mildew detection.
OEGR-DETR: A Novel Detection Transformer Based on Orientation Enhancement and Group Relations for SAR Object Detection
Authors: Feng Yunxiang , You Yanan , Tian Jing , Meng Gang
Published: December 2023

Object detection in SAR images has always been a topic of great interest in the field of deep learning. Early works commonly focus on improving performance on convolutional neural network frameworks. More recent works continue this path and introduce the attention mechanisms of Transformers for better semantic interpretation. However, these methods fail to treat the Transformer itself as a detection framework and, therefore, lack the development of various details that contribute to the state-of-the-art performance of Transformers. In this work, we first base our work on a fully multi-scale Transformer-based detection framework, DETR (DEtection TRansformer) to utilize its superior detection performance. Secondly, to acquire rotation-related attributes for better representation of SAR objects, an Orientation Enhancement Module (OEM) is proposed to facilitate the enhancement of rotation characteristics. Then, to enable learning of more effective and discriminative representations of foreground objects and background noises, a contrastive-loss-based GRC Loss is proposed to preserve patterns of both categories. Moreover, to not restrict comparisons exclusively to maritime objects, we have also developed an open-source labeled vehicle dataset. Finally, we evaluate both detection performance and generalization ability on two well-known ship datasets and our vehicle dataset. We demonstrated our method’s superior performance and generalization ability on both datasets.
Radar Emitter Signal Intra-Pulse Modulation Open Set Recognition Based on Deep Neural Network
Authors: Yuan Shibo , Li Peng , Wu Bin
Published: December 2023

Radar emitter signal intra-pulse modulation recognition is important for modern electronic reconnaissance systems to analyze target radar systems. In the actual environment, the intra-pulse modulations of the sampled radar emitter signals contain not only the known types in the library but also the unknown types. Therefore, the existing recognition methods, which are based on a closed set, cannot recognize the unknown samples. In order to solve this problem, in this paper, we proposed a method for radar emitter signal intra-pulse modulation open set recognition. The proposed method could classify the known modulations and identify the unknown modulation by using an original deep neural network-based recognition model trained on a closed set, estimating the signal-to-noise ratio, and calculating the reconstruction loss by an encoder–decoder model. For a given sample, the original deep neural network-based recognition model will label it as a certain known class temporarily. By estimating the SNR of the sample and calculating the reconstruction loss by inputting the sample to the corresponding encoder–decoder model related to the temporary predicted known class, whether the sample belongs to the predicted temporary known class or the unknown class will be confirmed. Experiments were conducted with five different openness conditions. The experimental results indicate that the proposed method has good performance on radar emitter signal intra-pulse modulation open set recognition.
Assessment of the Impact of Pacific Inflow on Sea Surface Temperature Prior to the Freeze-Up Period over the Bering Sea
Authors: Wang Weibo , Wang Yu , Zhang Junpeng , Jing Chunsheng , Ding Rui
Published: December 2023

Warm water inflow from the Northeast Pacific has always been considered a crucial factor in early winter freeze-up in the Bering Sea. There is a strong correlation between changes in sea surface temperature (SST) on the eastern Bering Sea shelf and sea ice area in December. However, there is still limited research on the impact of Pacific inflow on SST on the eastern Bering Sea shelf, resulting in insufficient measurements of the impact of Pacific inflow on early freeze-up. In this article, the definition of marine heatwaves (MHW) is used to extract warm events (with a threshold of the 70th percentile) and cold events (with a threshold of the 30th percentile) from the eastern Bering Sea shelf in November. Self-organizing map (SOM) technology is utilized to classify extracted cold and warm events and the mixed-layer heat budget is ultimately used to explore the factors that generate and maintain these cold and warm events. Between 1993 and 2021, a total of 12 warm and 12 cold events are extracted and their cumulative intensity is found to be strongly correlated with the interannual variation in SST by 99.8%, indicating that these warm and cold events are capable of characterizing the interannual variation in SST. Among the 12 warm events, 9 of them can be attributed to abnormal warming of seawater before November and only 3 events are attributed to warm water inflow from the Northeast Pacific. During the development of warm events, there are only two events in which the warm inflow from the Northeast Pacific has a more profound regulatory effect on warm events in November. Moreover, both generation and regulatory factors of cold events are the net air–sea heat flux. Statistics indicate that the warm water inflow from the Northeast Pacific has a limited effect on SST on the eastern Bering Sea shelf during the early freeze-up period. Changes in local SST are more influenced by the residual heat before November and by local net air–sea heat flux. However, we highlight that long-term ocean heatwaves occurring in the Northeast Pacific can enlarge the residual heat of seawater in the eastern Bering Sea shelf before November, thereby impacting early freeze-up. The frequency of such events has significantly increased in the past decade, causing notable changes in the climate and ecosystem of the Bering Sea. Therefore, it is crucial to continue closely monitoring the occurrence and development of such events in the future.
Assessing CYGNSS Satellite Soil Moisture Data for Drought Monitoring with Multiple Datasets and Indicators
Authors: Hou Zhaolu , Pu Zhaoxia
Published: December 2023

Drought monitoring is crucial for various sectors, and soil moisture data play a pivotal role, especially in agricultural contexts. This study focuses on the recent CYGNSS Level 3 soil moisture data derived from the NASA Cyclone Global Navigation Satellite System (CYGNSS), notable for its wide coverage and rapid revisit times, yet underexplored in drought research. Spanning from 1 January 2018 to 31 December 2022, this research analyzed daily CYGNSS soil moisture data, comparing them with the ERA5, SMAP, and GLDAS-NOAH datasets. It was found that the average and standard deviation (std) of CYGNSS soil moisture exhibited spatial patterns largely similar to other datasets, although some regions showed discrepancies (std differences reached up to 0.05 in some regions). The correlation coefficients and RMSE values between CYGNSS and other datasets depended on climate and land cover types. Four drought indicators from different soil moisture datasets were compared with the improved monthly Standardized Precipitation Evapotranspiration Index (SPEI). The drought indicators based on CYGNSS data demonstrate the capacity to describe drought extent and intensity. The correlation coefficients between certain drought indicators obtained from CYGNSS and SPEI reached 0.27 for drought percentage and 0.16 for drought intensity. Further investigations with selected extreme drought cases revealed that the indicator from CYGNSS data is relatively weak, influenced by the selected regions, times, and drought indicators. The results of this study provide insights into the potential application of CYGNSS soil moisture data in drought monitoring, offering a foundation for future research and practical implementation with current and future improved products.
Characterization of the Fels Landslide (Alaska) Using Combined Terrestrial, Aerial, and Satellite Remote Sensing Data
Authors: Donati Davide , Stead Doug , Rabus Bernhard , Engelbrecht Jeanine , Clague John J. , Newman Stephen D. , Francioni Mirko
Published: December 2023

The characterization of landslides located in remote areas poses significant challenges due to the costs of reaching the sites and the lack of reliable subsurface data to constrain geological interpretations. In this paper, the advantages of combining field and remote sensing techniques to investigate the deformation and stability of rock slopes are demonstrated. The characterization of the Fels landslide, a large, slowly deforming rock slope in central Alaska, is described. Historical aerial imagery is used to highlight the relationship between glacier retreat and developing instability. Airborne laser scanning (ALS) and Structure-from-Motion (SfM) datasets are used to investigate the structural geological setting of the landslide, revealing a good agreement between structural discontinuities at the outcrop and slope scales. The magnitude, plunge, and direction of slope surface displacements and their changes over time are studied using a multi-temporal synthetic aperture radar speckle-tracking (SAR ST) dataset. The analyses show an increase in displacement rates (i.e., an acceleration of the movement) between 2010 and 2020. Significant spatial variations of displacement direction and plunge are noted and correlated with the morphology of the failure surface reconstructed using the vector inclination method (VIM). In particular, steeper displacement vectors were reconstructed in the upper slope, compared to the central part, thus suggesting a change in basal surface morphology, which is largely controlled by rock mass foliation. Through this analytical approach, the Fels landslide is shown to be a slow-moving, compound rockslide, the displacement of which is controlled by structural geological features and promoted by glacier retreat.
Two-Level Integrity-Monitoring Method for Multi-Source Information Fusion Navigation
Authors: Chen Rui , Zhao Long
Published: December 2023

To address the issue of integrity monitoring for a multi-source information fusion navigation system, a theoretical framework of two-level integrity monitoring is proposed. Firstly, at the system level, a system-integrity-monitoring method based on the Kalman filter weighted least-squares form is established to detect and isolate faulty navigation sources. Secondly, at the sensor level, considering the redundancy of the faulty navigation sources, this paper presents the design of a multi-mode comprehensive fault-detection method for non-redundant navigation sources. Additionally, an extended-dimension matrix optimized sensor-fault detection and verification method for redundant navigation sources is proposed. Finally, integrity risk allocation criteria are established based on the effectiveness of navigation sources to calculate the system protection level and trigger integrity alarms. The two-level integrity-monitoring method was tested on a multi-source information fusion navigation system integrated with an inertial navigation system (INS), global positioning system (GPS), BeiDou satellite navigation system (BDS), Doppler velocity log (DVL), barometric altimeter (BA), and terrain-aided navigation (TAN). Test results demonstrate that the proposed method can effectively isolate the faulty navigation source within 10 s. Furthermore, it can detect the faulty sensors within the faulty navigation sources, thereby enhancing the reliability and robustness of the multi-source information fusion navigation system.
Street Design Strategies Based on Spatial Configurations and Building External Envelopes in Relation to Outdoor Thermal Comfort in Arid Climates
Authors: Ben Ratmia Fatima Zahra , Ahriz Atef , Santi Giovanni , Bouzaher Soumia , Mahar Waqas Ahmed , Ben Ratmia Mohamed Akram Eddine , Matallah Mohamed Elhadi
Published: December 2023

Climate change patterns and expected extreme weather conditions drive urban design practices toward more effective adaptation strategies for the built environment. Biskra City, one of the largest urban areas in the Algerian Sahara territory, has suffered from unprecedented extreme weather patterns, specifically during the summer. This paper examined outdoor thermal comfort in the arid climates of Biskra, Algeria, during summer extreme conditions by investigating the impact of the height-to-width (H/W) ratio aspect and the north–south (N-S) and east–west (E-W) street orientations on pedestrian thermal comfort with the parameterization of external building envelopes using brick, concrete, adobe, and limestone materials. This study was conducted with ENVI-met 5.1.1 software, based on 24 parametric scenarios, to identify the most effective composition for outdoor thermal stress mitigation using the physiological equivalent temperature (PET) thermal index. Across all scenarios, the PET index values fluctuated between PETmin = 32.2 °C and PETmax = 60.6 °C at different hours. The coupling between the H/W ratio and street orientation as geometry factors and building envelope characteristics reveals six distinct categories of building materials, each with an impact on outdoor thermal comfort: (1) high cooling (60–100%), (2) medium cooling (40–60%), (3) low cooling (<40%), (4) high heating (60–100%), (5) medium heating (40–60%), and (6) low heating material (<40%). Therefore, in the N-S orientation, limestone walls can provide a cooling efficiency range from 85% to 100% throughout deep and shallow canyons. Contrary to this, brick walls can cause a heat retention range varying from 70% to 93% within the same canyons. When considering extreme summer conditions in arid climates, the results show that the most effective bioclimatic passive strategy that could be achieved is the E-W orientation, within H/W < 1, characterized by a high albedo building material.
Digital Data Management Practices for Effective Embodied Carbon Estimation: A Systematic Evaluation of Barriers for Adoption in the Building Sector
Authors: Jayathilaka Geeth , Thurairajah Niraj , Rathnasinghe Akila
Published: December 2023

The pervasive impact of industrialisation on our daily existence has precipitated carbon emissions that demand critical attention. Although international conventions and scholarly research have scrutinised carbon emission sources and reduction strategies, the integration of digital tools and databases for estimating embodied carbon emissions remains in an incipient phase. Consequently, this review study aims to seek to optimise opportunities for digital transformation and sustainable practices while addressing the digital carbon footprint in the building sector. Employing the PRISMA guidelines, we systematically analysed 59 publications amassed from Scopus and Web of Science databases. The study’s search parameters encompassed the analytical dimensions of “embodied carbon”, “emission data”, and “barriers to digital transformation”. Through this rigorous process, 32 salient challenges and barriers were synthesised, encapsulated within four overarching parameters: traceability, accuracy, auditability, and efficiency. At its core, this study’s primary objective resides in the evaluation of existing barriers and challenges within the realm of carbon emission estimation. By doing so, it aspires to proffer a cogent knowledge model capable of catalysing the development of digital methodologies and models that can, with a high degree of accuracy, assess the burgeoning digital carbon footprint within the expansive domain of the building sector.
Navigating the Delivery of Transit-Oriented Development: A Case Study of Private Developers in Riyadh
Authors: Alasmari Fawaz , Alarabi Sameeh
Published: December 2023

Transit-oriented development has gained global attention as a sustainable urban planning approach. However, its implementation in developing countries, particularly in the Middle East, remains underexplored. This study aims to investigate the challenges and opportunities facing private developers in Riyadh, Saudi Arabia, in the context of delivering TOD projects. Using a mixed-methods approach that combines survey data and interviews, the research explores four key dimensions: regulatory, structural, collective vision, and economic factors. The findings reveal a complex local environment characterized by both encouraging prospects and formidable challenges. Institutional coordination, procedural clarity, and timely approval emerge as critical challenges in the regulatory dimension. Land-related issues, including land amalgamation and fragmented ownership, are identified as significant structural obstacles. While there is general enthusiasm for TOD among private developers, the lack of effective public–private collaboration and a unified vision hampers progress. Economically, high initial investments and regulatory uncertainties are the main challenges, although there is cautious optimism for future profitability. Despite these challenges, the study unveiled policy implications for implementation and offered information for context-specific adaptive planning. The research contributes to the growing body of literature on TOD in developing countries and lays the groundwork for future multistakeholder studies.
Assessing Water Resource Sustainability in the Kabul River Basin: A Standardized Runoff Index and Reliability, Resilience, and Vulnerability Framework Approach
Authors: Sediqi Mohammad Naser , Komori Daisuke
Published: December 2023

The sustainability of water resources is fundamental for basin management, especially in regions where changing hydrological conditions due to climate extremes are prevalent. This study presents a comprehensive assessment of the Kabul River Basin (KRB) sustainability using the Standardized Runoff Index (SRI) as a runoff indicator. By integrating the concepts of reliability, resilience, and vulnerability (RRV), this research aims to provide a granular understanding of water sustainability within the basin. Utilizing future climate projections derived from the mean ensemble of Global Climate Models (GCMs) of Coupled Model Intercomparison Project Phase 6 (CMIP6) under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5), the Soil and Water Assessment Tool (SWAT) model simulated surface runoff for the KRB. Employing a grid-based approach, this study uncovers the internal variabilities within the basin, recognizing that individual grid points may present distinct water availability characteristics. Historical analysis indicated a decline in the KRB’s sustainability, attributed to increased vulnerability and reduced reliability and resilience. Future projections emphasize the basin’s susceptibility to runoff variations, particularly in downstream areas characterized by dense populations and intense agricultural activities. These findings accentuate the need for strategic water resource management within the KRB to address localized vulnerabilities and ensure sustainable water availability amidst climatic uncertainties.
Towards Green Innovation in Smart Cities: Leveraging Traffic Flow Prediction with Machine Learning Algorithms for Sustainable Transportation Systems
Authors: Tao Xingyu , Cheng Lan , Zhang Ruihan , Chan W. K. , Chao Huang , Qin Jing
Published: December 2023

The emergence of smart cities has presented the prospect of transforming urban transportation systems into more sustainable and environmentally friendly entities. A pivotal facet of achieving this transformation lies in the efficient management of traffic flow. This paper explores the utilization of machine learning techniques for predicting traffic flow and its application in supporting sustainable transportation management strategies in smart cities based on data from the TRAFFIC CENSUS of the Hong Kong Transport Department. By analyzing anticipated traffic conditions, the government can implement proactive measures to alleviate congestion, reduce fuel consumption, minimize emissions, and ultimately improve quality of life for urban residents. This study proposes a way to develop traffic flow prediction methods with different methodologies in machine learning with a comparison with other results. This research aims to highlight the importance of leveraging machine learning technology in traffic flow prediction and its potential impact on sustainable transportation systems for the green innovation paradigm. The findings of this research have practical implications for transportation planners, policymakers, and urban designers. The predictive models demonstrated can support decision-making processes, enabling proactive measures to optimize traffic flow, reduce emissions, and improve the overall sustainability of transportation systems.