bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis, Antimicrobial and Antibiofilm Activities, and Molecular Docking Investigations of 2-(1H-Indol-3-yl)-1H-benzo[d]imidazole Derivatives
Authors: Mendogralo Elena Y. , Nesterova Larisa Y. , Nasibullina Ekaterina R. , Shcherbakov Roman O. , Myasnikov Danil A. , Tkachenko Alexander G. , Sidorov Roman Y. , Uchuskin Maxim G.
Published: October 2023

The treatment of many bacterial and fungal infections remains a problem due to increasing antibiotic resistance and biofilm formation by pathogens. In the present article, a methodology for the chemoselective synthesis of 2-(1H-indol-3-yl)-1H-benzo[d]imidazole derivatives is presented. We report on the antimicrobial activity of synthesized 2-(1H-indol-3-yl)-1H-benzo[d]imidazoles with significant activity against Staphylococcus aureus ATCC 25923, Staphylococcus aureus ATCC 43300 (MRSA), Mycobacterium smegmatis (mc(2)155/ATCC 700084), and Candida albicans ATCC 10231. High activity against staphylococci was shown by indolylbenzo[d]imidazoles 3ao and 3aq (minimum inhibitory concentration (MIC) < 1 µg/mL) and 3aa and 3ad (MIC 3.9–7.8 µg/mL). A low MIC was demonstrated by 2-(1H-indol-3-yl)-1-methyl-1H-benzo[d]imidazole (3ag) against M. smegmatis and against C. albicans (3.9 µg/mL and 3.9 µg/mL, respectively). 2-(5-Bromo-1H-indol-3-yl)-6,7-dimethyl-1H-benzo[d]imidazole (3aq) showed a low MIC of 3.9 µg/mL against C. albicans. Compounds 3aa, 3ad, 3ao, and 3aq exhibited excellent antibiofilm activity, inhibiting biofilm formation and killing cells in mature biofilms. Molecular docking analysis identified three potential interaction models for the investigated compounds, implicating (p)ppGpp synthetases/hydrolases, FtsZ proteins, or pyruvate kinases in their antibacterial action mechanism.
Gut Microbiota Composition in Patients with Neurodegenerative Disorders (Parkinson’s and Alzheimer’s) and Healthy Controls: A Systematic Review
Authors: Heravi Fatemah Sadeghpour , Naseri Kaveh , Hu Honghua
Published: October 2023

This systematic review aims to provide a comprehensive understanding of the current literature regarding gut microbiota composition in patients with Parkinson’s disease (PD) and Alzheimer’s disease (AD) compared to healthy controls. To identify the relevant studies, a thorough search of PubMed, Medline, and Embase was conducted following the PRISMA guidelines. Out of 5627 articles, 73 studies were assessed for full-text eligibility, which led to the inclusion of 42 studies (26 PD and 16 AD studies). The risk of bias assessment showed a medium risk in 32 studies (20 PD studies and 12 AD studies), a low risk in 9 studies (5 PD studies and 4 AD studies), and 1 PD study with a high risk. Among the PD studies, 22 out of 26 studies reported a different gut microbiota composition between the PD cases and the healthy controls, and 15 out of 16 AD studies reported differences in gut microbiota composition between the AD cases and the healthy controls. The PD and AD studies consistently identified the phyla Bacteroidetes, Firmicutes, and Proteobacteria as prevalent in the gut microbiota in both the healthy groups and the case groups. Microbial dysbiosis was specifically characterized in the PD studies by a high abundance of Akkermansia, Verrucomicrobiaceae, Lachnospiraceae, and Ruminococcaceae in the cases and a high abundance of Blautia, Coprococcus, Prevotellaceae, and Roseburia in the controls. Similarly, Bacteroides and Acidobacteriota were abundant in the AD cases, and Acidaminococcaceae, Firmicutes, Lachnospiraceae, and Ruminiclostridium were abundant in the AD controls. The microbial signature assessment showed the association of several microbial taxa, including Akkermansia, Lachnospiraceae, Verrucomicrobiaceae, Bifidobacterium, Ruminococcacea, and Verrucomicrobia with PD and Ruminococcaceae, Bacteroides, and Actinobacteria with AD. The microbial diversity evaluations in the PD and AD studies indicated comparable alpha diversity in some groups and distinct gut microbiota composition in others, with consistent beta diversity differences between the cases and the controls across multiple studies. The bacterial signatures identified in this study that are associated with PD and AD may offer promising prospects for efficient management and treatment approaches.
Radiometals in Imaging and Therapy: Highlighting Two Decades of Research
Authors: Sharma Shalini , Pandey Mukesh K.
Published: October 2023

The present article highlights the important progress made in the last two decades in the fields of molecular imaging and radionuclide therapy. Advancements in radiometal-based positron emission tomography, single photon emission computerized tomography, and radionuclide therapy are illustrated in terms of their production routes and ease of radiolabeling. Applications in clinical diagnostic and radionuclide therapy are considered, including human studies under clinical trials; their current stages of clinical translations and findings are summarized. Because the metalloid astatine is used for imaging and radionuclide therapy, it is included in this review. In regard to radionuclide therapy, both beta-minus (β−) and alpha (α)-emitting radionuclides are discussed by highlighting their production routes, targeted radiopharmaceuticals, and current clinical translation stage.
Bispecific Antibodies in Lung Cancer: A State-of-the-Art Review
Authors: Khosla Atulya Aman , Jatwani Karan , Singh Rohit , Reddy Aswanth , Jaiyesimi Ishmael , Desai Aakash
Published: October 2023

Bispecific antibodies have emerged as a promising class of therapeutics in the field of oncology, offering an innovative approach to target cancer cells while sparing healthy tissues. These antibodies are designed to bind two different antigens, enabling them to bridge immune cells with cancer cells, resulting in enhanced tumor cell killing and improved treatment responses. This review article summarizes the current landscape of bispecific antibodies in lung cancer, including their mechanisms of action, clinical development, and potential applications in other solid tumor malignancies. Additionally, the challenges and opportunities associated with their use in the clinic are discussed, along with future directions for research and development in this exciting area of cancer immunotherapy.
Optimization of Statin-Loaded Delivery Nanoparticles for Treating Chronic Liver Diseases by Targeting Liver Sinusoidal Endothelial Cells
Authors: Gil Mar , Khouri Lareen , Raurell Imma , Rafael Diana , Andrade Fernanda , Abasolo Ibane , Schwartz Simo , Martínez-Gómez María , Salcedo María Teresa , Pericàs Juan Manuel , Hide Diana , Wei Mingxing , Metanis Norman , Genescà Joan , Martell María
Published: October 2023

In this study, we developed functionalized polymeric micelles (FPMs) loaded with simvastatin (FPM-Sim) as a drug delivery system to target liver sinusoidal endothelial cells (LSECs) for preserving liver function in chronic liver disease (CLD). Polymeric micelles (PMs) were functionalized by coupling peptide ligands of LSEC membrane receptors CD32b, CD36 and ITGB3. Functionalization was confirmed via spectroscopy and electron microscopy. In vitro and in vivo FPM-Sim internalization was assessed by means of flow cytometry in LSECs, hepatocytes, Kupffer and hepatic stellate cells from healthy rats. Maximum tolerated dose assays were performed in healthy mice and efficacy studies of FPM-Sim were carried out in bile duct ligation (BDL) and thioacetamide (TAA) induction rat models of cirrhosis. Functionalization with the three peptide ligands resulted in stable formulations with a greater degree of in vivo internalization in LSECs than non-functionalized PMs. Administration of FPM-Sim in BDL rats reduced toxicity relative to free simvastatin, albeit with a moderate portal-pressure-lowering effect. In a less severe model of TAA-induced cirrhosis, treatment with FPM-CD32b-Sim nanoparticles for two weeks significantly decreased portal pressure, which was associated with a reduction in liver fibrosis, lower collagen expression as well as the stimulation of nitric oxide synthesis. In conclusion, CD32b-FPM stands out as a good nanotransporter for drug delivery, targeting LSECs, key inducers of liver injury.
Antimutagenicity and Antioxidant Activity of Castanea sativa Mill. Bark Extract
Authors: Gasperini Sofia , Greco Giulia , Angelini Sabrina , Hrelia Patrizia , Fimognari Carmela , Lenzi Monia
Published: October 2023

Castanea sativa Mill. (Cs), a plant traditionally employed in nutrition and to treat various respiratory and gastrointestinal infections, possesses cancer chemopreventive characteristics. In particular, Cs bark extract previously demonstrated antiproliferative and pro-apoptotic activities against a leukemic lymphoblastic cell line. Starting from this evidence, the aim of this paper was to investigate the possibility to affect also the earlier phases of the carcinogenic process by evaluating Cs bark extract’s antimutagenic properties, in particular using the “In Vitro Mammalian Cell Micronucleus Test” on TK6 cells performed by flow cytometry. For this purpose, since an ideal chemopreventive agent should be virtually nontoxic, the first step was to exclude the extract’s genotoxicity. Afterwards, the antimutagenic effect of the extract was evaluated against two known mutagens, the clastogen mitomycin C (MMC) and the aneugen vinblastine (VINB). Our results indicate that Cs bark extract protected cells from MMC-induced damage (micronuclei frequency fold increase reduction from 2.9 to 1.8) but not from VINB. Moreover, we demonstrated that Cs bark extract was a strong antioxidant and significantly reduced MMC-induced ROS levels by over 2 fold. Overall, our research supports the assumption that Cs bark extract can counteract MMC mutagenicity by possibly scavenging ROS production.
The Impact of Silver Nanoparticle-Induced Photothermal Therapy and Its Augmentation of Hyperthermia on Breast Cancer Cells Harboring Intracellular Bacteria
Authors: Liu Sijia , Phillips Spencer , Northrup Scott , Levi Nicole
Published: October 2023

Breast cancer can harbor intracellular bacteria, which may have an impact on metastasis and therapeutic responses. Silver nanoparticles are FDA-approved for their antimicrobial potential, plus they have pleiotropic benefits for eradicating cancer cells. In the current work we synthesized photothermal silver nanoparticles (AgNPs) with an absorption at 800 nm for heat generation when exposed to near-infrared laser irradiation. Breast cell lines MCF 10A, MCF7, and MDA MB 231 were infected with Pseudomonas aeruginosa, and their response to AgNPs, heat, or photothermal therapy (PTT) was evaluated. The results demonstrate that the application of a brief heating of cells treated with AgNPs offers a synergistic benefit in killing both infected and non-infected cells. Using 10 µg/mL of AgNPs plus laser stimulation induced a temperature change of 12 °C, which was sufficient for reducing non-infected breast cells by 81–94%. Infected breast cells were resistant to PTT, with only a reduction of 45–68%. In the absence of laser stimulation, 10 µg/mL of AgNPs reduced breast cell populations by 10–65% with 24 h of exposure. This concentration had no impact on the survival of planktonic bacteria with or without laser stimulation, although infected breast cells had a 42–90% reduction in intracellular bacteria. Overall, this work highlights the advantages of AgNPs for the generation of heat, and to augment the benefits of heat, in breast cancer cells harboring intracellular infection.
Callus Type, Growth Regulators, and Phytagel on Indirect Somatic Embryogenesis of Coffee (Coffea arabica L. var. Colombia)
Authors: Avila-Victor Consuelo Margarita , Arjona-Suárez Enrique de Jesús , Iracheta-Donjuan Leobardo , Valdez-Carrasco Jorge Manuel , Gómez-Merino Fernando Carlos , Robledo-Paz Alejandrina
Published: October 2023

Coffee is a crop of global relevance. Indirect somatic embryogenesis has allowed plants of different coffee genotypes to be massively regenerated. The culture medium composition can affect the calli characteristics that are generated and their ability to form somatic embryos. This research aimed to determine the influence of the type of callus, growth regulators, and phytagel concentration on the embryogenic capacity of the Colombia variety. Leaf explants were cultured on Murashige and Skoog medium with 2,4-dichlorophenoxyacetic acid (2,4-D) (0.5–1.0 mg L−1), benzylaminopurine (BAP, 1.0 mg L−1), and phytagel (2.3–5.0 g L−1). The explants generated two types of calli: friable (beige, soft, watery, easy disintegration, polyhedral parenchyma cells) and compact (white, hard, low water content, difficult disintegration, elongated parenchyma cells). About 68% of the total callus generated was compact; this type of callus produced a greater number of embryos (71.3) than the friable one (29.2). The number of differentiated embryos was significantly affected by the concentration of phytagel; higher concentrations (5.0 g L−1) resulted in larger quantities (73.7). The highest number of embryos (127.47) was obtained by combining 1.0 mg L−1 2,4-D, 1.0 mg L−1 BAP, 5.0 g L−1 phytagel, and compact callus.
Quantification of Urban Greenspace in Shenzhen Based on Remote Sensing Data
Authors: Bai Yu , Liu Menghang , Wang Weimin , Xiong Xiangyun , Li Shenggong
Published: October 2023

Rapid urbanization has led to the expansion of Shenzhen’s built-up land and a substantial reduction in urban greenspace (UG). However, the changes in UG in Shenzhen are not well understood. Here, we utilized long-time-series land cover data and the Normalized Difference Vegetation Index (NDVI) as a proxy for greenspace quality to systematically analyze changes in the spatio-temporal pattern and the exposure and inequality of UG in Shenzhen. The results indicate that the UG area has been decreasing over the years, although the rate of decrease has slowed in recent years. The UG NDVI trend exhibited some seasonal variations, with a noticeable decreasing trend in spring, particularly in the eastern part of Shenzhen. Greenspace exposure gradually increased from west to east, with Dapeng and Pingshan having the highest greenspace exposure regardless of the season. Over the past two decades, inequality in greenspace exposure has gradually decreased during periods of urban construction in Shenzhen, with the fastest rate of decrease in spring and the slowest rate of decrease in summer. These findings provide a scientific basis for a better understanding of the current status of UG in Shenzhen and promote the healthy development of the city. Additionally, this study provides scientific evidence and insights for relevant decision-making institutions.
Evaluating the Uncertainty in Coherence-Change-Detection-Based Maps of Torrential Sediment Transport in Arid Environments
Authors: Botey i Bassols Joan , Bedia Carmen , Cuevas-González María , Valdivielso Sonia , Crosetto Michele , Vázquez-Suñé Enric
Published: October 2023

InSAR coherence-change detection (CCD) is a promising remote sensing technique that is able to map areas affected by torrential sediment transport triggered by flash floods in arid environments. CCD maps the changes in the interferometric coherence between synthetic aperture radar images (InSAR coherence), a parameter that measures the stability of the radar signal between two different SAR images, i.e., data acquisitions. In arid environments, such changes are mainly due to changes in the surface. However, the residual effect of other factors on the InSAR coherence cannot be completely excluded. Therefore, CCD-based maps contain the uncertainty of whether the detected changes are actual changes in the observed surface or just errors related to those residual effects. Thus, in this paper, the results of four CCD mapping methods, with different degrees of complexity and sensitivity to the different factors affecting the InSAR coherence, are compared in order to evaluate the existence of the errors and their importance. The obtained CCD maps are also compared with changes in satellite optical images and a field campaign. The results lead to the conclusion that CCD maps are reliable in the identification of the zones affected by sediment transport, although the precision in the delimitation of the affected area remains an open issue. However, highly rugged relief areas still require a thorough analysis of the results in order to discard the geometric effects related to the perpendicular baseline.
Evidence of Widespread Volcanic Activity near Hebrus Valles on Mars Revealed by SHARAD
Authors: Nerozzi Stefano , Christoffersen Michael S. , Holt John W. , Hamilton Christopher W.
Published: October 2023

Hebrus Valles is an outflow channel system in the plain-forming terrains of southeastern Utopia Planitia, Mars. These terrains may have formed through a combination of liquid water and volcanic processes, yet their nature, subsurface structure, and composition remain unclear. We investigate these terrains by mapping subsurface reflectors across 540 Shallow Radar (SHARAD) profiles and applying two complementary loss tangent inversion techniques. We find moderate loss tangent values across some subregions of Granicus Valles and Hyblaeus Fossae (tan δ = 0.0162 ± 0.0004 and tan δ = 0.019 ± 0.002, respectively), suggesting the presence of basaltic lava flows. We interpret non-detections in the other flows in Granicus Valles to be due to the presence of radar-lossy materials formed through aqueous processes, which supports the hypothesized occurrence of lahars in this region. A small area near Hebrus Valles exhibits subsurface reflectors with low to moderate loss tangents (tan δ = 0.010 ± 0.003), suggesting the presence of pristine lava flows or sedimentary materials capped by lava flows. We also find a widespread occurrence of very low-loss tangent materials near Hyblaeus Dorsa (tan δ = 0.0045 ± 0.0002), which may represent a lobe of the Medusae Fossae Formation or similar high-porosity materials buried underneath a lava flow. Together, these findings suggest that volcanic activity played a central role in the formation of terrains across the broader Hebrus Valles region.
Development of a Novel, Ecologically Friendly Generation of pH-Responsive Alginate Nanosensors: Synthesis, Calibration, and Characterisation
Authors: Alwraikat Abdalaziz , Jaradat Abdolelah , Marji Saeed M. , Bayan Mohammad F. , Alomari Esra’a , Naser Abdallah Y. , Alyami Mohammad H.
Published: October 2023

Measurement of the intracellular pH is particularly crucial for the detection of numerous diseases, such as carcinomas, that are characterised by a low intracellular pH. Therefore, pH-responsive nanosensors have been developed by many researchers due to their ability to non-invasively detect minor changes in the pH of many biological systems without causing significant biological damage. However, the existing pH-sensitive nanosensors, such as the polyacrylamide, silica, and quantum dots-based nanosensors, require large quantities of organic solvents that could cause detrimental damage to the ecosystem. As a result, this research is aimed at developing a new generation of pH-responsive nanosensors comprising alginate natural polymers and pH-sensitive fluorophores using an organic, solvent-free, and ecologically friendly method. Herein, we successfully synthesised different models of pH-responsive alginate nanoparticles by varying the method of fluorophore conjugation. The synthesised pH nanosensors demonstrated a low MHD with a relatively acceptable PDI when using the lowest concentration of the cross-linker Ca+2 (1.25 mM). All the pH nanosensors showed negative zeta potential values, attributed to the free carboxylate groups surrounding the nanoparticles’ surfaces, which support the colloidal stability of the nanosensors. The synthesised models of pH nanosensors displayed a high pH-responsiveness with various correlations between the pH measurements and the nanosensors’ fluorescence signal. In summation, pH-responsive alginate nanosensors produced using organic, solvent-free, green technology could be harnessed as potential diagnostics for the intracellular and extracellular pH measurements of various biological systems.
Few-Shot Learning for WiFi Fingerprinting Indoor Positioning
Authors: Ma Zhenjie , Shi Ke
Published: October 2023

In recent years, deep-learning-based WiFi fingerprinting has been intensively studied as a promising technology for providing accurate indoor location services. However, it still demands a time-consuming and labor-intensive site survey and suffers from the fluctuation of wireless signals. To address these issues, we propose a prototypical network-based positioning system, which explores the power of few-shot learning to establish a robust RSSI-position matching model with limited labels. Our system uses a temporal convolutional network as the encoder to learn an embedding of the individual sample, as well as its quality. Each prototype is a weighted combination of the embedded support samples belonging to its position. Online positioning is performed for an embedded query sample by simply finding the nearest position prototype. To mitigate the space ambiguity caused by signal fluctuation, the Kalman Filter estimates the most likely current RSSI based on the historical measurements and current measurement in the online stage. The extensive experiments demonstrate that the proposed system performs better than the existing deep-learning-based models with fewer labeled samples.
TinyFallNet: A Lightweight Pre-Impact Fall Detection Model
Authors: Koo Bummo , Yu Xiaoqun , Lee Seunghee , Yang Sumin , Kim Dongkwon , Xiong Shuping , Kim Youngho
Published: October 2023

Falls represent a significant health concern for the elderly. While studies on deep learning-based preimpact fall detection have been conducted to mitigate fall-related injuries, additional efforts are needed for embedding in microcomputer units (MCUs). In this study, ConvLSTM, the state-of-the-art model, was benchmarked, and we attempted to lightweight it by leveraging features from image-classification models VGGNet and ResNet while maintaining performance for wearable airbags. The models were developed and evaluated using data from young subjects in the KFall public dataset based on an inertial measurement unit (IMU), leading to the proposal of TinyFallNet based on ResNet. Despite exhibiting higher accuracy (97.37% < 98.00%) than the benchmarked ConvLSTM, the proposed model requires lower memory (1.58 MB > 0.70 MB). Additionally, data on the elderly from the fall data of the FARSEEING dataset and activities of daily living (ADLs) data of the KFall dataset were analyzed for algorithm validation. This study demonstrated the applicability of image-classification models to preimpact fall detection using IMU and showed that additional tuning for lightweighting is possible due to the different data types. This research is expected to contribute to the lightweighting of deep learning models based on IMU and the development of applications based on IMU data.
Drift Error Compensation Algorithm for Heterodyne Optical Seawater Refractive Index Monitoring of Unstable Signals
Authors: Zhang Shiwen , Li Liyan , Liu Yuliang , Zhou Yan
Published: October 2023

The refractive index measurement of seawater has proven significance in oceanography, while an optical heterodyne interferometer is an important, highly accurate, tool used for seawater refractive index measurement. However, for practical seawater refractive index measurement, the refractive index of seawater needs to be monitored for long periods of time, and the influence of drift error on the measurement results for these cases cannot be ignored. This paper proposes a drift error compensation algorithm based on wavelet decomposition, which can adaptively separate the background from the signal, and then calculate the frequency difference to compensate for the drift error. It is suitable for unstable signals, especially signals with large differences between the beginning and the end, which is common in actual seawater refractive index monitoring. The authors identify that the primary cause of drift error is the frequency instability of the acousto-optic frequency shifter (AOFS), and the actual frequency difference was measured through experimentation. The frequency difference was around 0.1 Hz. Simulation experiments were designed to verify the effectiveness of the algorithm, and the standard deviation of the optical length of the results was on the scale of 10−8 m. Liquid refractive index measurement experiments were carried out in a laboratory, and the measurement error was reduced from 36.942% to 0.592% after algorithm processing. Field experiments were carried out regarding seawater refractive index monitoring, and the algorithm-processing results are able to match the motion of the target vehicle. The experimental data were processed with different algorithms, and, according to the comparison of the results, the proposed algorithm performs better than other existing drift error elimination algorithms.
Dynamic Response Study of Piezoresistive Ti3C2-MXene Sensor for Structural Impacts
Authors: Srivatsa Shreyas , Sieber Paul , Hofer Céline , Robert André , Raorane Siddhesh , Marciszko-Wiąckowska Marianna , Grabowski Krzysztof , Nayak M. M. , Chatzi Eleni , Uhl Tadeusz
Published: October 2023

MXenes are a new family of two-dimensional (2D) nanomaterials. They are inorganic compounds of metal carbides/nitrides/carbonitrides. Titanium carbide MXene (Ti3C2-MXene) was the first 2D nanomaterial reported in the MXene family in 2011. Owing to the good physical properties of Ti3C2-MXenes (e.g., conductivity, hydrophilicity, film-forming ability, elasticity) various applications in wearable sensors, energy harvesters, supercapacitors, electronic devices, etc., have been demonstrated. This paper presents the development of a piezoresistive Ti3C2-MXene sensor followed by experimental investigations of its dynamic response behavior when subjected to structural impacts. For the experimental investigations, an inclined ball impact test setup is constructed. Stainless steel balls of different masses and radii are used to apply repeatable impacts on a vertical cantilever plate. The Ti3C2-MXene sensor is attached to this cantilever plate along with a commercial piezoceramic sensor, and their responses for the structural impacts are compared. It is observed from the experiments that the average response times of the Ti3C2-MXene sensor and piezoceramic sensor are 1.28±0.24μs and 31.19±24.61μs, respectively. The fast response time of the Ti3C2-MXene sensor makes it a promising candidate for monitoring structural impacts.
Six-Lead Electrocardiography Enables Identification of Rhythm and Conduction Anomalies of Patients in the Telemedicine-Based, Hospital-at-Home Setting: A Prospective Validation Study
Authors: Sharabi Adam , Abutbul Eli , Grossbard Eitan , Martsiano Yonatan , Berman Aya , Kassif-Lerner Reut , Hakim Hila , Liber Pninit , Zoubi Anram , Barkai Galia , Segal Gad
Published: October 2023

Background: The hospital-at-home (HAH) model is a viable alternative for conventional in-hospital stays worldwide. Serum electrolyte abnormalities are common in acute patients, especially in those with many comorbidities. Pathologic changes in cardiac electrophysiology pose a potential risk during HAH stays. Periodical electrocardiogram (ECG) tracing is therefore advised, but few studies have evaluated the accuracy and efficiency of compact, self-activated ECG devices in HAH settings. This study aimed to evaluate the reliability of such a device in comparison with a standard 12-lead ECG. Methods: We prospectively recruited consecutive patients admitted to the Sheba Beyond Virtual Hospital, in the HAH department, during a 3-month duration. Each patient underwent a 12-lead ECG recording using the legacy device and a consecutive recording by a compact six-lead device. Baseline patient characteristics during hospitalization were collected. The level of agreement between devices was measured by Cohen’s kappa coefficient for inter-rater reliability (Ϗ). Results: Fifty patients were included in the study (median age 80 years, IQR 14). In total, 26 (52%) had electrolyte disturbances. Abnormal D-dimer values were observed in 33 (66%) patients, and 12 (24%) patients had elevated troponin values. We found a level of 94.5% raw agreement between devices with regards to nine of the options included in the automatic read-out of the legacy device. The calculated Ϗ was 0.72, classified as a substantial consensus. The rate of raw consensus regarding the ECG intervals’ measurement (PR, RR, and QT) was 78.5%, and the calculated Ϗ was 0.42, corresponding to a moderate level of agreement. Conclusion: This is the first report to our knowledge regarding the feasibility of using a compact, six-lead ECG device in the setting of an HAH to be safe and bearing satisfying agreement level with a legacy, 12-lead ECG device, enabling quick, accessible arrythmia detection in this setting. Our findings bear a promise to the future development of telemedicine-based hospital-at-home methodology.
An Approach for Easy Detection of Buried FRP Composite/Non-Metallic Pipes Using Ground-Penetrating Radar
Authors: Kavi Jonas , Halabe Udaya B.
Published: October 2023

Pipelines remain the safest means of transporting natural gas and petroleum products. Nonetheless, the pipeline infrastructure in the US is facing major challenges, especially in terms of corrosion of steel/metallic pipes and excavation damage of onshore pipelines (leading to oil spills, explosions, and deaths). Corrosion of metallic pipelines can be avoided by using non-corrosive materials such as plastic pipes for low-pressure applications and glass-fiber-reinforced polymer (GFRP) composite pipes for transporting high-pressure oil and natural gas. However, buried non-metallic pipelines are not easily detectable, which can lead to increased excavation damage during construction and rehabilitation work. Alternative strategies for making buried non-metallic pipes easily locatable using ground-penetrating radar (GPR) were investigated in this study. Results from this study have shown that using carbon fabric or an aluminum foil overlay on non-metallic pipes before burying in soil significantly increases the reflected GPR signal amplitude, thereby making it easier to locate such pipelines. The reflected GPR signal amplitude for pipe sections with carbon fabric or aluminum foil overlays was found to have increased by a factor of up to 4.5 over the control samples. The results also highlight the importance of selecting the appropriate antenna frequency for GPR surveys, since wet silt loam soil and clay significantly reduce the penetration depths of the radar signals produced by the GPR antennae.
A Stable, Efficient, and High-Precision Non-Coplanar Calibration Method: Applied for Multi-Camera-Based Stereo Vision Measurements
Authors: Zheng Hao , Duan Fajie , Li Tianyu , Li Jiaxin , Niu Guangyue , Cheng Zhonghai , Li Xin
Published: October 2023

Traditional non-coplanar calibration methods, represented by Tsai’s method, are difficult to apply in multi-camera-based stereo vision measurements because of insufficient calibration accuracy, inconvenient operation, etc. Based on projective theory and matrix transformation theory, a novel mathematical model is established to characterize the transformation from targets’ 3D affine coordinates to cameras’ image coordinates. Then, novel non-coplanar calibration methods for both monocular and binocular camera systems are proposed in this paper. To further improve the stability and accuracy of calibration methods, a novel circular feature points extraction method based on region Otsu algorithm and radial section scanning method is proposed to precisely extract the circular feature points. Experiments verify that our novel calibration methods are easy to operate, and have better accuracy than several classical methods, including Tsai’s and Zhang’s methods. Intrinsic and extrinsic parameters of multi-camera-systems can be calibrated simultaneously by our methods. Our novel circular feature points extraction algorithm is stable, and with high precision can effectively improve calibration accuracy for coplanar and non-coplanar methods. Real stereo measurement experiments demonstrate that the proposed calibration method and feature extraction method have high accuracy and stability, and can further serve for complicated shape and deformation measurements, for instance, stereo-DIC measurements, etc.
Towards the Structural Health Monitoring of Bridges Using Wireless Sensor Networks: A Systematic Study
Authors: Sonbul Omar S. , Rashid Muhammad
Published: October 2023

To perform a comprehensive assessment of important infrastructures (like bridges), the process of structural health monitoring (SHM) is employed. The development and implementation of SHM systems are generally based on wireless sensor networks (WSN) platforms. However, most of the WSN platforms are battery-powered, and therefore, have a limited battery lifetime. The power constraint is generally addressed by applying energy harvesting (EH) technologies. As a result, there exists a plethora of WSN platforms and EH techniques. The employment of a particular platform and technique are important factors during the development and implementation of SHM systems and depend upon various operating conditions. Therefore, there is a need to perform a systematic literature review (SLR) for WSN platforms and EH techniques in the context of SHM for bridges. Although state-of-the-art review articles present multiple angles of the field, there is a lack of an SLR presenting an in-depth comparative study of different WSN platforms and EH techniques. Moreover, a systematic analysis is also needed for the exploration of other design considerations such as inspection scale (global/local), response type (static/dynamic), and types of sensors. As a result, this SLR selects 46 articles (during 2007–2023), related to EH techniques and WSN platforms in SHM for bridges. The selected articles are classified into three groups: WSN platforms, energy harvesting techniques, and a combination of both. Subsequently, a comparative analysis of WSN platforms and EH techniques is made. Furthermore, the selected articles (total = 46) are also explored in terms of sensor type, inspection scale, and response type. As a result, 17 different sensor types are identified. This research is significant as it may facilitate the various stakeholders of the domain during the selection of appropriate WSN platforms, EH techniques, and related design issues.
Peptide-Functionalized Carbon Nanotube Chemiresistors: The Effect of Nanotube Density on Gas Sensing
Authors: Sim Daniel , Huang Tiffany , Kim Steve S.
Published: October 2023

Biorecognition element (BRE)-based carbon nanotube (CNT) chemiresistors have tremendous potential to serve as highly sensitive, selective, and power-efficient volatile organic compound (VOC) sensors. While many research groups have studied BRE-functionalized CNTs in material science and device development, little attention has been paid to optimizing CNT density to improve chemiresistor performance. To probe the effect of CNT density on VOC detection, we present the chemiresistor-based sensing results from two peptide-based CNT devices counting more than 60 different individual measurements. We find that a lower CNT density shows a significantly higher noise level and device-to-device variation while exhibiting mildly better sensitivity. Further investigation with SEM images suggests that moderately high CNT density with a stable connection of the nanotube network is desirable to achieve the best signal-to-noise ratio. Our results show an essential design guideline for tuning the nanotube density to provide sensitive and stable chemiresistors.
Intelligent Hierarchical Admission Control for Low-Earth Orbit Satellites Based on Deep Reinforcement Learning
Authors: Wei Debin , Guo Chuanqi , Yang Li
Published: October 2023

Low-Earth orbit (LEO) satellites have limited on-board resources, user terminals are unevenly distributed in the constantly changing coverage area, and the service requirements vary significantly. It is urgent to optimize resource allocation under the constraint of limited satellite spectrum resources and ensure the fairness of service admission control. Therefore, we propose an intelligent hierarchical admission control (IHAC) strategy based on deep reinforcement learning (DRL). This strategy combines the deep deterministic policy gradient (DDPG) and the deep Q network (DQN) intelligent algorithm to construct upper and lower hierarchical resource allocation and admission control frameworks. The upper controller considers the state features of each ground zone and satellite resources from a global perspective, and determines the beam resource allocation ratio of each ground zone. The lower controller formulates the admission control policy based on the decision of the upper controller and the detailed information of the users’ services. At the same time, a designed reward and punishment mechanism is used to optimize the decisions of the upper and lower controllers. The fairness of users’ services admissions in each ground zone is achieved as far as possible while ensuring the reasonable allocation of beam resources among zones. Finally, online decision-making and offline learning were combined, so that the controller could make full use of a large number of historical data to learn and generate intelligent strategies with stronger adaptive ability while interacting with the network environment in real time. A large number of simulation results show that IHAC has better performance in terms of a successful service admission rate, service drop rate, and fair resource allocation. Among them, the number of accepted services increased by 20.36% on average, the packet loss rate decreased by 17.56% on average, and the resource fairness increased by 17.16% on average.
A Scheme for Quantum Teleportation and Remote Quantum State Preparation of IoT Multiple Devices
Authors: Fu You , Li Dongfen , Hua Xiaoyu , Jiang Yangyang , Zhu Yonghao , Zhou Jie , Yang Xiaolong , Tan Yuqiao
Published: October 2023

With the continuous development of the Internet of Things (IoT) technology, the industry’s awareness of the security of the IoT is also increasing, and the adoption of quantum communication technology can significantly improve the communication security of various devices in the IoT. This paper proposes a scheme of controlled remote quantum state preparation and quantum teleportation based on multiple communication parties, and a nine-qubit entanglement channel is used to achieve secure communication of multiple devices in the IoT. The channel preparation, measurement operation, and unitary operation of the scheme were successfully simulated on the IBM Quantum platform, and the entanglement degree and reliability of the channel were verified through 8192 shots. The scheme’s application in the IoT was analyzed, and the steps and examples of the scheme in the secure communication of multiple devices in the IoT are discussed. By simulating two different attack modes, the effect of the attack on the communication scheme in the IoT was deduced, and the scheme’s high security and anti-interference ability was analyzed. Compared with other schemes from the two aspects of principle and transmission efficiency, it is highlighted that the advantages of the proposed scheme are that it overcomes the single fixed one-way or two-way transmission protocol form of quantum teleportation in the past and can realize quantum communication with multiple devices, ensuring both security and transmission efficiency.
A Signal Coordination Model for Long Arterials Considering Link Traffic Flow Characteristics
Authors: Wen Xiaoyue , Wang Dianhai , Jin Sheng , Qian Guomin , Zhu Yixuan
Published: October 2023

In order to improve the travel efficiency on a long arterial with massive signals, this paper proposed a mixed integer linear programming model, MaxBandLAM, to simultaneously optimize the arterial partition scheme and signal coordination schemes with the consideration of link traffic flow characteristics. The weighted sum of the two-way green bandwidths on links across the arterial was taken as its objective. The link volume to capacity rations were taken as the weights. The number of sub-zones, the allocation of signals and links, signal cycle, offset and phase sequence, the coordination speed, as well as the two-way green bandwidths of sub-zones and of links are the decision variables. A numerical test was carried out on a virtual arterial with twenty signals. The results indicate the scheme generated by the MaxBandLAM model can provide a more reasonable partition scheme and coordination schemes compared to those generated by Synchro and the models with no traffic flow characteristics of links consideration. For the scenario of dominating the main road through flows, the average delay, average stop number, and average travel speed at intersections for all-turning flows and main road through flows in the MaxBandLAM scheme, all performed well.
How Do Problem-Solving Demands Influence Employees’ Thriving at Work: An Explanation Based on Cognitive Appraisal
Authors: Ma Lulu , Ma Hongyu , Zhan Xiangping , Wang Yue
Published: October 2023

In globalized markets, it is important for companies to cultivate a thriving workforce that is motivated to grow and develop. Based on the transactional theory of stress, we discussed how the way people appraise their problem-solving demands, either as a challenge or a hindrance, impacts employees’ thriving at work. Data were collected from employees of a state-owned enterprise in China at two separate points with a 4-week interval. The results showed that problem-solving demands have a positive impact on employees’ thriving at work through challenge appraisal and a negative impact on employees’ thriving at work through hindrance appraisal. Additionally, we observed a moderated mediation effect in which organizational identity strengthened the positive effects of problem-solving demands on challenge appraisal, which in turn promoted employees’ thriving at work. The findings highlight the role of cognitive appraisal in interpreting employees’ responses to work stress.
The Isolation and Characterization of a Novel Group III-Classified Getah Virus from a Commercial Modified Live Vaccine against PRRSV
Authors: Gao Xintao , Li Jialei , Wu Tong , Dou Jinping , Zhang Wenrong , Jia Hong , Zhang Zhifang , Liu Xingjian , Li Yinü
Published: October 2023

As an epizootic causative agent, the Getah virus (GETV) can cause moderate illness in horses, lethal disease in foxes, and reproductive disorders and fetal death in pigs. Due to the wide range of hosts and multiple routes of transmission, GETV has become a growing potential threat to the global livestock industry, and even to public health. More attention and research on GETV are urgently needed. In this study, we successfully isolated a novel GETV strain, named BJ0304, from a commercial live vaccine against porcine reproductive and respiratory syndrome virus (PRRSV) and determined its growth kinetics. Then, genetic and phylogenetic analyses were performed. The results revealed that BJ0304 was clustered into Group III, and it was most related to the GETV-V1 strain based on the complete genome sequence. Furthermore, the pathogenicity of the isolate was assessed and found to be a low virulent strain in mice relative to its closest homolog GETV-V1. Finally, mutation and glycosylation analysis showed that a unique mutation (171 T > I) at one amino acid of E2, which affected the glycosylation of E2, may be associated with viral pathogenicity. In summary, the general characteristic of a novel Group III-classified GETV-BJ0304 isolated from commercial live PRRSV vaccine was defined and then mutation/glycosylation-related potential virulence factor was discussed. This study highlights the complexity of GETV transmission routes in swine and the need for more surveillance on commercial animal vaccines, contributes to the understanding of genetic characterization of clinical isolates, provides possible virulence factors in favor of unveiling the viral pathogenesis, and eventually lays the foundation for the prevention and control of GETV.
The Multi-Channel System of the Vietnamese Mekong Delta: Impacts on the Flow Dynamics under Relative Sea-Level Rise Scenarios
Authors: Le Hoang-Anh , Nguyen Thong , Gratiot Nicolas , Deleersnijder Eric , Soares-Frazão Sandra
Published: October 2023

The Mekong Delta has the world’s third-largest surface area. It plays an indisputable role in the economy and livelihoods of Vietnam and Cambodia, with repercussions at regional and global scales. During recent decades, the Vietnamese part of the Mekong Delta underwent profound human interventions (construction of dykes and multi-channel networks), which modified the hydrodynamic regime, especially cycles of field submersion. In this study, we first applied a full 2D numerical hydraulic model, TELEMAC-2D, to examine the effects of the complex channel and river networks on the spatial and temporal distribution of the flow in the 40,000 km2 of the Vietnamese Mekong Delta. Then, two scenarios of relative sea-level rise in 2050 and 2100 were implemented to simulate the future patterns of water fluxes in the delta. The results show that dykes and multi-channel networks would reduce the inundation area by 36% and lessen the peak water level by 15% and the discharge over the floodplains by 24%. Despite this protection, under a relative sea-level rise of 30 cm and 100 cm, the maximum flooded area could occupy about 69% and 85% of the whole delta in 2050 and 2100, respectively.
Groundwater Level Dynamic Impacted by Land-Cover Change in the Desert Regions of Tarim Basin, Central Asia
Authors: Wang Wanrui , Chen Yaning , Wang Weihua , Chen Yapeng , Hou Yifeng
Published: October 2023

Groundwater is essential to residents, ecology, agriculture, and industry. The depletion of groundwater impacted by climatic variability and intense human activities could threaten water, food, and socioeconomic security in arid regions. A thorough understanding of groundwater level dynamics and its response to land-cover change is necessary for groundwater management and ecosystem improvement, which are poorly understood in arid desert regions due to a scarcity of field monitoring data. In our study, spatiotemporal characteristics of groundwater level impacted by land-cover change and its relationship with vegetation were examined using 3-years in-situ monitoring data of 30 wells in the desert regions of Tarim Basin during 2019–2021. The results showed that the depth to groundwater level (DGL) exhibited obvious spatial and seasonal variations, and the fluctuation of DGL differed significantly among the wells. The cultivated land area increased by 1174.6, 638.0, and 732.2 km2 during 2000–2020 in the plains of Yarkand, Weigan-Kuqa, and Dina Rivers, respectively, mainly transferring from bare land and grassland. Annual average Normalized Difference Vegetation Index (NDVI) values increased with time during the period in the plains. DGL generally exhibited a weakly increasing trend from 2019 to 2021, mainly due to human activities. Land-cover change significantly affected the groundwater level dynamic. Generally, the groundwater system was in negative equilibrium near the oasis due to agricultural irrigation, was basically in dynamic equilibrium in the desert region, and was in positive equilibrium near the Tarim River Mainstream due to irrigation return water and streamflow. NDVI of natural desert vegetation was negatively correlated with DGL in the desert regions (R2 = 0.78, p < 0.05). Large-scale land reclamation and groundwater overexploitation associated with water-saving irrigation agriculture development have caused groundwater level decline in arid oasis-desert regions. Hence, controlling groundwater extraction intensity, strengthening groundwater monitoring, and promoting water-saving technology would be viable methods to sustainably manage groundwater and maintain the ecological environment in arid areas.