bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostic Procedures for Inflammatory Bowel Disease: Laboratory, Endoscopy, Pathology, Imaging, and Beyond
Authors: Hong Seung Min , Baek Dong Hoon
Published: July 2024

Diagnosing inflammatory bowel disease (IBD) can often be challenging, and differentiating between Crohn’s disease and ulcerative colitis can be particularly difficult. Diagnostic procedures for IBD include laboratory tests, endoscopy, pathological tests, and imaging tests. Serological and stool tests can be easily performed in an outpatient setting and provide critical diagnostic clues. Although endoscopy is an invasive procedure, it offers essential diagnostic information and allows for tissue biopsy and therapeutic procedures. Video capsule endoscopy and device-assisted enteroscopy are endoscopic procedures used to evaluate the small bowel. In addition to endoscopy, magnetic resonance imaging, computed tomography, and ultrasound (US) are valuable tools for small bowel assessment. Among these, US is noninvasive and easily utilized, making its use highly practical in daily clinical practice. Endoscopic biopsy aids in the diagnosis of IBD and is crucial for assessing the histological activity of the disease, facilitating a thorough evaluation of disease remission, and aiding in the development of treatment strategies. Recent advances in artificial intelligence hold promise for enhancing various aspects of IBD management, including diagnosis, monitoring, and precision medicine. This review compiles current procedures and promising future tools for the diagnosis of IBD, providing comprehensive insights.
Cholecystocutaneous Fistula
Authors: Tustumi Francisco , da Costa Filha Giane Prata , Gnipper Cirillo Guilherme Carvalhal
Published: July 2024

This image article presents an 88-year-old indigenous woman with a history of several episodes of abdominal pain, for which she went to numerous different hospitals in the countryside, was always treated with analgesics, and then discharged. After a long time, the patient eventually was evaluated with magnetic resonance imaging. The test revealed a displaced gallbladder with thickened walls, multiple stones, and a fistulous tract extending to the skin. This case underscores the significant challenges faced by patients in regions with limited healthcare access, highlighting the impact of delayed diagnosis and inadequate management on patient outcomes.
Dynamic Perviousness Has Predictive Value for Clot Fibrin Content in Acute Ischemic Stroke
Authors: Anagnostakou Vania , Toth Daniel , Bertalan Gergely , Müller Susanne , Reimann Regina R. , Epshtein Mark , Madjidyar Jawid , Thurner Patrick , Schubert Tilman , Wegener Susanne , Kulcsar Zsolt
Published: July 2024

Dynamic perviousness is a novel imaging biomarker, with clot density measurements at multiple timepoints to allow longer contrast to thrombus interaction. We investigated the correlations between dynamic perviousness and clot composition in the setting of acute ischemic stroke. Thirty-nine patients with large vessel occlusion (LVO) undergoing mechanical thrombectomy (MT) were analyzed. Patients received a three-phase CT imaging pre-thrombectomy and histopathological analysis of retrieved clots. Clot densities for every phase and change in densities between phases were calculated, leading to four patterns of dynamic perviousness: no contrast uptake, early contrast uptake with and without washout and late uptake. Clots were categorized into three groups based on dominant histologic composition: red blood cell (RBC)-rich, fibrin/platelet-rich and mixed. Clot composition was correlated with dynamic perviousness using the Kruskal–Wallis test and Pearson’s correlation analysis. The dynamic perviousness categories showed a significant difference between fibrin-rich clots when compared to RBC-rich plus mixed groups. The uptake without washout category had significantly fewer fibrin clots compared to the uptake with washout (p = 0.036), and nearly significantly fewer fibrin clots when compared to the no uptake category (p = 0.057). Contrast uptake with different patterns of contrast washout showed significant differences of the likelihood for fibrin-rich clots.
Hematological Malignancies in Older Patients: Focus on the Potential Role of a Geriatric Assessment Management
Authors: Caserta Santino , Cancemi Gabriella , Loreta Silverio , Allegra Alessandro , Stagno Fabio
Published: July 2024

Geriatric assessment management is a multidimensional tool used to evaluate prognosis for clinical outcomes and targets for interventions in older adults with cancer receiving chemotherapy. In this review, we evaluated the possible application of geriatric assessment management (GAM) in hematological malignancies. In older patients with Diffuse Large B Cell Lymphoma, GAM might be helpful in both predicting planned hospital admissions and improving quality of life. In chronic myeloid leukemia, the Charlson Comorbidity Index demonstrates how comorbidities could affect treatment compliance and overall outcomes. In multiple myeloma, the application of different scores such as the International Myeloma Working Group Frailty Index and the Revised Myeloma Comorbidity Index can identify frail patients who need suitable interventions in treatment plan (reducing drug dose or changing treatment). Therefore, including GAM in the management plan of older patients with hematological malignancies may direct and optimize cancer care.
How AI and Robotics Will Advance Interventional Radiology: Narrative Review and Future Perspectives
Authors: Zhang Jiaming , Fang Jiayi , Xu Yanneng , Si Guangyan
Published: July 2024

The rapid advancement of artificial intelligence (AI) and robotics has led to significant progress in various medical fields including interventional radiology (IR). This review focuses on the research progress and applications of AI and robotics in IR, including deep learning (DL), machine learning (ML), and convolutional neural networks (CNNs) across specialties such as oncology, neurology, and cardiology, aiming to explore potential directions in future interventional treatments. To ensure the breadth and depth of this review, we implemented a systematic literature search strategy, selecting research published within the last five years. We conducted searches in databases such as PubMed and Google Scholar to find relevant literature. Special emphasis was placed on selecting large-scale studies to ensure the comprehensiveness and reliability of the results. This review summarizes the latest research directions and developments, ultimately analyzing their corresponding potential and limitations. It furnishes essential information and insights for researchers, clinicians, and policymakers, potentially propelling advancements and innovations within the domains of AI and IR. Finally, our findings indicate that although AI and robotics technologies are not yet widely applied in clinical settings, they are evolving across multiple aspects and are expected to significantly improve the processes and efficacy of interventional treatments.
Circulating IgG Fragments for Gastric Cancer and Esophageal Cancer
Authors: Goufman Eugene I. , Tikhonova Nataliia B. , Aleksankin Andrey P. , Gershkovich Karina B. , Stepanov Alexander A. , Stepanova Irina I. , Mikhaleva Liudmila M. , Nizyaeva Natalia V. , Kovaleva Olga V. , Alferov Alexander A. , Kuzmin Yury B. , Kushlinskii Nikolay E.
Published: July 2024

Blood serum of patients with gastric (n = 68) and esophageal (n = 43) cancer was assessed for proteolytic fragments of IgG. Serum samples of 20 healthy donors were used as a control. We analyzed indicators of hemostasis (prothrombin time, fibrinogen, plasminogen activity, a2-antiplasmin activity, protein C activity) in blood plasma and the level of total IgG in the blood serum. The median IgG-LysK of healthy donors was lower than in esophageal cancer and in patients with gastric cancer. ROC-analysis showed high sensitivity (91%) and specificity (85%) in the group with esophageal cancer but 68% and 85%, respectively, in patients with gastric cancer. Analysis of false negatives IgG-LysK in cancer patients showed that most patients had an advanced stage of cancer accompanied by metastases. Total IgG in the plasma of patients with false-negative IgG-LysK values was 30% lower than in samples with positive values, while the level of a2-antiplasmin was increased and the prothrombin time was shorter. These changes in blood homeostasis may be the reason for an increase in the proportion of false-negative values of the IgG-LysK coefficient. Circulatory IgG-LysK levels increase in the early stages of such cancers as gastric and esophageal cancers. Thus, when used in a panel with other more specific markers for these pathologies, this indicator can significantly increase the early detection of cancer.
BRAF Detection in FNAC Combined with Semi-Quantitative 99mTc-MIBI Technique and AI Model, an Economic and Efficient Predicting Tool for Malignancy in Thyroid Nodules
Authors: Teodoriu Laura , Ungureanu Maria-Christina , Matei Mioara , Grierosu Irena , Saviuc Alexandra Iuliana , Wael Jalloul , Ivanov Iuliu , Dragos Loredana , Danila Radu , Cristian Velicescu , Costandache Mihai-Andrei , Iftene Adrian , Preda Cristina , Stefanescu Cipriana
Published: July 2024

Background: Technology allows us to predict a histopathological diagnosis, but the high costs prevent the large-scale use of these possibilities. The current liberal indication for surgery in benign thyroid conditions led to a rising frequency of incidental thyroid carcinoma, especially low-risk papillary micro-carcinomas. Methods: We selected a cohort of 148 patients with thyroid nodules by ultrasound characteristics and investigated them by fine needle aspiration cytology (FNAC)and prospective BRAF collection for 70 patients. Also, we selected 44 patients with thyroid nodules using semi-quantitative functional imaging with an oncological, 99mTc-methoxy-isobutyl-isonitrile (99mTc-MIBI) radiotracer. Results: Following a correlation with final histopathological reports in patients who underwent thyroidectomy, we introduced the results in a machine learning program (AI) in order to obtain a pattern. For semi-quantitative functional visual pattern imaging, we found a sensitivity of 33%, a specificity of 66.67%, an accuracy of 60% and a negative predicting value (NPV) of 88.6%. For the wash-out index (WOind), we found a sensitivity of 57.14%, a specificity of 50%, an accuracy of 70% and an NPV of 90.06%.The results of BRAF in FNAC included 87.50% sensitivity, 75.00% specificity, 83.33% accuracy, 75.00% NPV and 87.50% PPV. The prevalence of malignancy in our small cohort was 11.4%. Conclusions: We intend to continue combining preoperative investigations such as molecular detection in FNAC, 99mTc-MIBI scanning and AI training with the obtained results on a larger cohort. The combination of these investigations may generate an efficient and cost-effective diagnostic tool, but confirmation of the results on a larger scale is necessary.
Intraocular Epithelial Ingrowth after Traumatic and Surgical Corneal Injuries
Authors: Heinzelmann Joana , Stoica Sergiu , Vogt Alexander Ruben , Hecht Sabine , Viestenz Anja , Viestenz Arne
Published: July 2024

Intraocular epithelial ingrowth is a rare but serious complication of eye surgery or trauma. The diagnosis is challenging but can be aided by techniques such as anterior optical coherence tomography (AS-OCT). This study aimed to compare clinical and histopathological diagnostic data to evaluate the accuracy of AS-OCT. This retrospective analysis focused on patients presenting with suspected epithelial invasion between 2017 and 2022. Clinical data and histopathological findings were analyzed for diagnostic confirmation. Immunohistochemistry using the corneal-specific marker cytokeratin 3 and the conjunctival-specific marker cytokeratin 13 helped to identify the type of invading epithelial cells. Statistical analysis was used to evaluate the effectiveness of AS-OCT for diagnosis. This study included 51 patients who underwent keratoplasty or enucleation. Sixteen cases (31%) of epithelial ingrowth were histologically confirmed. The most common type was the cystic form (82%). Enucleation was required in 25% of patients, mainly due to diffuse epithelial invasion. Immunohistochemistry revealed a conjunctival origin in 82% of the infiltrated cells. AS-OCT showed a sensitivity of 78% and a specificity of 26% in detecting hyperreflective structures associated with epithelial invasion. This study highlights the diverse manifestations of epithelial ingrowth and the need for improved diagnostic techniques, with AS-OCT showing promising results but requiring further validation to avoid misdiagnosis.
Attention-Based Deep Learning Approach for Breast Cancer Histopathological Image Multi-Classification
Authors: Aldakhil Lama , Alhasson Haifa , Alharbi Shuaa
Published: July 2024

Breast cancer diagnosis from histopathology images is often time consuming and prone to human error, impacting treatment and prognosis. Deep learning diagnostic methods offer the potential for improved accuracy and efficiency in breast cancer detection and classification. However, they struggle with limited data and subtle variations within and between cancer types. Attention mechanisms provide feature refinement capabilities that have shown promise in overcoming such challenges. To this end, this paper proposes the Efficient Channel Spatial Attention Network (ECSAnet), an architecture built on EfficientNetV2 and augmented with a convolutional block attention module (CBAM) and additional fully connected layers. ECSAnet was fine-tuned using the BreakHis dataset, employing Reinhard stain normalization and image augmentation techniques to minimize overfitting and enhance generalizability. In testing, ECSAnet outperformed AlexNet, DenseNet121, EfficientNetV2-S, InceptionNetV3, ResNet50, and VGG16 in most settings, achieving accuracies of 94.2% at 40×, 92.96% at 100×, 88.41% at 200×, and 89.42% at 400× magnifications. The results highlight the effectiveness of CBAM in improving classification accuracy and the importance of stain normalization for generalizability.
Cone-Beam Computed Tomography (CBCT)-Based Diagnosis of Dental Bone Defects
Authors: Alshomrani Faisal
Published: July 2024

Cone Beam Computed Tomography (CBCT) has completely changed the way that bone disorders are diagnosed and treated, especially in the dental and maxillofacial domains. This article examines the diverse applications of computed tomography (CBCT) in the diagnosis and treatment of facial trauma, including mandibular, dentoalveolar, and other facial fractures, as well as bone abnormalities like dislocations and fractures. CBCT is useful for a wide range of dental conditions and greatly improves diagnostic accuracy in periodontics, orthodontics, endodontics, and dental implantology. Additionally, a comparison between CBCT and conventional imaging methods was conducted, emphasizing the latter’s inferior 3D imaging capabilities, allowing for more precise treatment planning and better patient outcomes with CBCT. Although CBCT has many benefits, it also has some drawbacks, such as requiring specific training for accurate interpretation, cost considerations, and a higher radiation exposure than with traditional dental X-rays. In order to optimize benefits and reduce risks, the conclusion highlights CBCT’s revolutionary influence on clinical practice while arguing for its prudent and responsible application.
The Impact of Intraoperative Glucagon on the Diagnostic Accuracy of Intraoperative Cholangiogram for the Diagnosis of Choledocholithiasis: Experience from a Large Tertiary Care Center
Authors: Mittal Nitish , Ali Faisal S. , Machado Antonio Pizuorno , Ngo Sean , Shatila Malek , DaVee Tomas , Thosani Nirav , Wadhwa Vaibhav
Published: July 2024

A proportion of patients who undergo intraoperative cholangiogram (IOC) do not have bile duct stones at the time of endoscopic retrograde cholangiopancreatography (ERCP), either due to the spontaneous passage of stones or a false-positive IOC. Glucagon has been utilized as an inexpensive tool to allow the passage of micro-choledocholithiasis to the duodenum and resolve filling defects caused by stones or air bubbles. The purpose of our study is to understand the change in diagnostic accuracy of IOC to detect choledocholithiasis with intraoperative glucagon. We conducted a retrospective study at a tertiary care center on adult patients who underwent laparoscopic cholecystectomy with IOC. The diagnostic accuracy of IOC was assessed before and after the administration of intravenous glucagon. Of 1455 patients, 374 (25.7%) received intraoperative glucagon, and 103 of these 374 patients (27.5%) showed resolution of the filling defect with the passage of contrast to the duodenum. Pre- and post-glucagon administration comparison showed enhancement in specificity from 78% to 83%, an increase in positive predictive value from 67.3% to 72.4%, and an improvement in the diagnostic accuracy of IOC from 81.5% to 84.3%. Our findings suggest that intraoperative glucagon administration carries the potential to reduce the rate of false-positive IOCs, thereby reducing the performance of unnecessary ERCPs.
Resuscitation and Forensic Factors Influencing Outcome in Penetrating Cardiac Injury
Authors: Aumaitre Astrid , Delteil Clémence , Tuchtan Lucile , Piercecchi-Marti Marie-Dominique , Gainnier Marc , Carvelli Julien , Boussen Salah , Bruder Nicolas , Heireche Fouzia , Florant Thibault , Gaillat Françoise , Lagier David , Porto Alizée , Velly Lionel , Simeone Pierre
Published: July 2024

Background: Cardiac injury caused by a sharp object is a medical and surgical therapeutic challenge. Mortality risk factors have been identified but there are major discrepancies in the literature. The aim of this study was to analyse the management of victims of penetrating cardiac injuries before and after admission to hospital and the anatomical characteristics of these injuries in order to facilitate diagnosis of the most critical patients. Methods: To carry out this study, we conducted a retrospective analytical study with epidemiological data on victims of penetrating cardiac injuries. We included two types of patients, with those who underwent autopsy in our institution after death from sharp injury to the heart or great vessels and those who survived with treatment in the emergency department or intensive care unit between January 2015 and February 2022. Results: We included 30 autopsied patients and 12 survivors aged between 18 and 73 years. Higher mortality was associated with prehospital or in-hospital cardiorespiratory arrest (OR = 4, CI [1.71–9.35]), preoperative mechanical ventilation (OR = 10, CI [1.53–65.41]), preoperative catecholamines (OR = 7, CI [1.12–6.29]), preoperative and perioperative adrenaline (OR = 13, CI [1.98–85.46] and [1.98–85.46]), penetrating cardiac injury (OR = 14, CI [2.10–93.22]), multiple cardiac injuries (OR = 1.5, CI [1.05–2.22]) and an Organ Injury Scaling of the American Association for the Surgery of Trauma (AAST-OIS) score of 5 (OR = 2.9, CI [1.04–8.54]; p = 0.0329) with an AUC-ROC curve value of 0.708 (CI [0.543–0.841]). Conclusions: This study identified risk mortality factors in penetrating cardiac injury patients. These findings can help improve the diagnosis and management of these patients. The AAST-OIS score may be a good tool to diagnose critical patients.
Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance
Authors: Ros Seyha , Tam Prohim , Song Inseok , Kang Seungwoo , Kim Seokhoon
Published: July 2024

Network functions virtualization (NFV) has become the platform for decomposing the sequence of virtual network functions (VNFs), which can be grouped as a forwarding graph of service function chaining (SFC) to serve multi-service slice requirements. NFV-enabled SFC consists of several challenges in reaching the reliability and efficiency of key performance indicators (KPIs) in management and orchestration (MANO) decision-making control. The problem of SFC fault tolerance is one of the most critical challenges for provisioning service requests, and it needs resource availability. In this article, we proposed graph neural network (GNN)-based deep reinforcement learning (DRL) to enhance SFC fault tolerance (GRL-SFT), which targets the chain graph representation, long-term approximation, and self-organizing service orchestration for future massive Internet of Everything applications. We formulate the problem as the Markov decision process (MDP). DRL seeks to maximize the cumulative rewards by maximizing the service request acceptance ratios and minimizing the average completion delays. The proposed model solves the VNF management problem in a short time and configures the node allocation reliably for real-time restoration. Our simulation result demonstrates the effectiveness of the proposed scheme and indicates better performance in terms of total rewards, delays, acceptances, failures, and restoration ratios in different network topologies compared to reference schemes.
RDF Stream Taxonomy: Systematizing RDF Stream Types in Research and Practice
Authors: Sowiński Piotr , Szmeja Paweł , Ganzha Maria , Paprzycki Marcin
Published: July 2024

Over the years, RDF streaming has been explored in research and practice from many angles, resulting in a wide range of RDF stream definitions. This variety presents a major challenge in discussing and integrating streaming systems due to a lack of a common language. This work attempts to address this critical research gap by systematizing RDF stream types present in the literature in a novel taxonomy. The proposed RDF Stream Taxonomy (RDF-STaX) is embodied in an OWL 2 DL ontology that follows the FAIR principles, making it readily applicable in practice. Extensive documentation and additional resources are provided to foster the adoption of the ontology. Three use cases for the ontology are presented with accompanying competency questions, demonstrating the usefulness of the resource. Additionally, this work introduces a novel nanopublications dataset, which serves as a collaborative, living state-of-the-art review of RDF streaming. The results of a multifaceted evaluation of the resource are presented, testing its logical validity, use case coverage, and adherence to the community’s best practices, while also comparing it to other works. RDF-STaX is expected to help drive innovation in RDF streaming by fostering scientific discussion, cooperation, and tool interoperability.
NLOCL: Noise-Labeled Online Continual Learning
Authors: Cheng Kan , Ma Yongxin , Wang Guanglu , Zong Linlin , Liu Xinyue
Published: July 2024

Continual learning (CL) from infinite data streams has become a challenge for neural network models in real-world scenarios. Catastrophic forgetting of previous knowledge occurs in this learning setting, and existing supervised CL methods rely excessively on accurately labeled samples. However, the real-world data labels are usually misled by noise, which influences the CL agents and aggravates forgetting. To address this problem, we propose a method named noise-labeled online continual learning (NLOCL), which implements the online CL model with noise-labeled data streams. NLOCL uses an empirical replay strategy to retain crucial examples, separates data streams by small-loss criteria, and includes semi-supervised fine-tuning for labeled and unlabeled samples. Besides, NLOCL combines small loss with class diversity measures and eliminates online memory partitioning. Furthermore, we optimized the experience replay stage to enhance the model performance by retaining significant clean-labeled examples and carefully selecting suitable samples. In the experiment, we designed noise-labeled data streams by injecting noisy labels into multiple datasets and partitioning tasks to simulate infinite data streams realistically. The experimental results demonstrate the superior performance and robust learning capabilities of our proposed method.
Rail Surface Defect Detection Based on Dual-Path Feature Fusion
Authors: Zhong Yinfeng , Chen Guorong
Published: July 2024

With the rapid development of rail transit, the workload of track maintenance has increased, making the intelligent identification of rail surface defects crucial for improving detection efficiency. To address issues such as low defect detection accuracy, the loss of feature information due to single-path architecture backbones, and insufficient information interaction in existing rail defect detection methods, we propose a rail surface defect detection method based on dual-path feature fusion (DPF). This method initially employs a dual-path structure to separately extract low-level and high-level features. It then utilizes a combination of attention mechanisms and feature fusion techniques to integrate these features. By doing so, it preserves richer information and enhances detection accuracy and robustness. The experimental results demonstrate that the comprehensive performance of the proposed model is superior to mainstream algorithms.
Symmetrical Multilevel High Voltage-Gain Boost Converter Control Strategy for Photovoltaic Systems Applications
Authors: Touré Mohamed Lamine , Camara Mamadou Baïlo , Dakyo Brayima
Published: July 2024

This paper proposes a Symmetric High Voltage-Gain (SHVG) boost converter control for photovoltaic system applications. The concept is based on a multilevel boost converter configuration, which presents an advantage compared to a classic boost converter such as the ability to transfer a high amount of power with less stress on the power electronics components in the high voltage-gain conditions. This advantage allows the power losses in the converter to be reduced. A mathematical-based voltage model of the PV system using variable series resistance depending on solar irradiance and the temperature is proposed. This model is connected to an SHVG boost converter to supply the load’s power. A control strategy of the DC-bus voltage with maximum power point tracking (MPPT) from the PV system using PI controllers is developed. The contributions of the paper are focused on the SHVG operating analysis with the passive components’ sizing, and the DC-bus voltage control with maximum power point tracking of the PV systems in dynamic operating conditions. The performances of the proposed control are evaluated through simulations, where the results are interesting for high-power photovoltaic applications.
Advances in Brain-Inspired Deep Neural Networks for Adversarial Defense
Authors: Li Ruyi , Ke Ming , Dong Zhanguo , Wang Lubin , Zhang Tielin , Du Minghua , Wang Gang
Published: July 2024

Deep convolutional neural networks (DCNNs) have achieved impressive performance in image recognition, object detection, etc. Nevertheless, they are susceptible to adversarial attacks and interferential noise. Adversarial attacks can mislead DCNN models by manipulating input data with small perturbations, causing security risks to intelligent system applications. Comparatively, these small perturbations have very limited perceptual impact on humans. Therefore, the research on brain-inspired adversarial robust models has gained increasing attention. Beginning from the adversarial attack concepts and schemes, we present a review of the conventional adversarial attack and defense methods and compare the advantages and differences between brain-inspired robust neural networks and the conventional adversarial defense methods. We further review the existing adversarial robust DCNN models, including methods inspired by the early visual systems and supervised by neural signals. Representative examples have validated the efficacy of brain-inspired methods for designing adversarial robust models, which may benefit the further research and development of brain-inspired robust deep convolutional neural networks and the intelligent system applications.
A Deep Reinforcement Learning Algorithm for Trajectory Planning of Swarm UAV Fulfilling Wildfire Reconnaissance
Authors: Demir Kubilay , Tumen Vedat , Kosunalp Selahattin , Iliev Teodor
Published: July 2024

Wildfires have long been one of the critical environmental disasters that require a careful monitoring system. An intelligent system has the potential to both prevent/extinguish the fire and deliver urgent requirements postfire. In recent years, unmanned aerial vehicles (UAVs), with the ability to detect missions in high-risk areas, have been gaining increasing interest, particularly in forest fire monitoring. Taking a large-scale area involved in a fire into consideration, a single UAV is often insufficient to accomplish the task of covering the whole disaster zone. This poses the challenge of multi-UAVs optimum path planning with a key focus on limitations such as energy constraints and connectivity. To narrow down this issue, this paper proposes a deep reinforcement learning-based trajectory planning approach for multi-UAVs that permits UAVs to extract the required information within the disaster area on time. A target area is partitioned into several identical subareas in terms of size to enable UAVs to perform their patrol duties over the subareas. This subarea-based arrangement converts the issue of trajectory planning into allowing UAVs to frequently visit each subarea. Each subarea is initiated with a risk level by creating a fire risk map optimizing the UAV patrol route more precisely. Through a set of simulations conducted with a real trace of the dataset, the performance outcomes confirmed the superiority of the proposed idea.
SPECE: Subject Position Encoder in Complex Embedding for Relation Extraction
Authors: Wu Shangjia , Guo Zhiqiang , Huang Xiaofeng , Zhang Jialiang , Ni Yingfang
Published: July 2024

As a crucial component of many natural language processing tasks, extracting entities and relations transforms unstructured text information into structured data, providing essential support for constructing knowledge graphs (KGs). However, current entity relation extraction models often prioritize the extraction of richer semantic features or the optimization of relation extraction methods, overlooking the significance of positional information and subject characteristics in this task. To solve this problem, we introduce the subject position-based complex exponential embedding for entity relation extraction model (SPECE). The encoder module of this model ingeniously combines a randomly initialized dilated convolutional network with a BERT encoder. Notably, it determines the initial position of the predicted subject based on semantic cues. Furthermore, it achieves a harmonious integration of positional encoding features and textual features through the adoption of the complex exponential embedding method. The experimental outcomes on both the NYT and WebNLG datasets reveal that, when compared to other baseline models, our proposed SPECE model demonstrates significant improvements in the F1 score on both datasets. This further validates its efficacy and superiority.
5G Enabled Dual Vision and Speech Enhancement Architecture for Multimodal Hearing-Aids
Authors: Ni Xianpo , Cen Yang , Tyagi Tushar , Enemali Godwin , Arslan Tughrul
Published: July 2024

This paper presents the algorithmic framework for a multimodal hearing aid (HA) prototype designed on a Field Programmable Gate Array (FPGA), specifically the RFSOC4*2 AMD FPGA, and evaluates the transmitter performance through simulation studies. The proposed architecture integrates audio and video inputs, processes them using advanced algorithms, and employs the 5G New Radio (NR) communication protocol for uploading the processed signal to the cloud. The core transmission utilizes Orthogonal Frequency Division Multiplexing (OFDM), an algorithm that effectively multiplexes the processed signals onto various orthogonal frequencies, enhancing bandwidth efficiency and reducing interference. The design is divided into different modules such as Sound reference signal (SRS), demodulation reference signal (DMRS), physical broadcast channel (PBCH), and physical uplink shared channel (PUSCH). The modulation algorithm has been optimized for FPGA parallel processing capabilities, making it better suited for the hearing aid requirements for low latency. The optimized algorithm achieves a transmission time of only 4.789 ms and uses fewer hardware resources, enhancing performance in a cost-effective and energy-efficient manner.
Analysis of Factors Influencing Fire Accidents in Commercial Complexes Based on WSR-DEMATEL-ISM Model
Authors: Qin Rongshui , Shi Chenchen , Yu Tao , Ding Chao , Ren Xin , Xiao Junfeng
Published: July 2024

Commercial complexes integrate various business formats, and a fire outbreak can lead to widespread, continuous, and chain-reaction social disturbances, including severe casualties, economic losses, and social impacts. To deeply explore the characteristics and influencing factors of fire accidents in urban commercial complexes in China, this study first analyzed fire accident cases in commercial complexes that occurred from 2002 to 2022. Using mathematical statistics, the analysis examined the year and month of the accidents, their severity, and their causes to identify key risk factors associated with fire hazards in urban commercial complexes. Subsequently, based on the WSR methodology, an index system for assessing the influencing factors of fire accidents in commercial complexes was constructed, encompassing four aspects: personnel, equipment, environment, and management, including 11 cause indicators and 9 outcome indicators. Then, the Decision Experiment and Evaluation Laboratory Method (DEMATEL) was used to quantitatively analyze the relationships among influencing factors, combined with Interpretative Structural Modeling (ISM) to perform a hierarchical categorization of the factors and identify those critically influencing commercial complex fires. This research indicates that critical influencing factors include inadequate regulations, insufficient fire safety inspections, inadequate safety training, careless use of fire during operations, inadequate government supervision, illegal renovations, unimplemented corporate fire safety responsibilities, and poor routine maintenance and management. These results provide a theoretical reference for effectively preventing and controlling fires in commercial complexes.
Properties of Chitin and Its Regenerated Hydrogels from the Insect Zophobas morio Fed Citrus Biomass or Polystyrene
Authors: Guangorena Zarzosa Guillermo Ignacio , Kobayashi Takaomi
Published: July 2024

The potential of insects as a recycling tool has recently attracted attention. In this study, chitin was extracted with 1 M HCl for 24 h at 20 °C, followed by 1 M NaOH for 5 h at 90 °C, and bleached with 2.5% v/v NaOCl for 2 h at 20 °C from Zophobas morio (ZM) insects fed citrus waste biomass (OP) or polystyrene foam (PS). The highest survival rate was found in the OP group. The properties of the resulting chitin material are reported, as well as the preparation of hydrogels using a DMAc/LiCl solvent. All chitins obtained were α-chitin. The degrees of deacetylation, crystallinity, molecular weight, and solubility in DMAc/LiCl were similar between the PS and biomass feeds, and they showed similar viscosities in the DMAc/LiCl solution. All hydrogels obtained had similar properties and viscoelastic behavior, indicating that the resultant chitins and their hydrogels from ZM were similar between those fed with citrus biomass and those fed with PS.
Monitoring and Cause Analysis of Land Subsidence along the Yangtze River Utilizing Time-Series InSAR
Authors: Chen Yuanyuan , Guo Lin , Xu Jia , Yang Qiang , Wang Hao , Zhu Chenwei
Published: July 2024

Time-series monitoring of the land subsidence in the Yangtze River coastal area is crucial for maintaining river stability and early warning of disasters. This study employed PS-InSAR and SBAS-InSAR techniques to monitor the land subsidence along the Yangtze River in Nanjing, using a total of 42 Sentinel-1A images obtained between April 2015 and November 2021. The accuracy of both methods was compared and validated, while a comprehensive analysis was conducted to ascertain the spatial distribution characteristics and underlying causes of land subsidence. The maximum deviation between the two methods and six leveling point data did not exceed ±5 mm. Within the 5 km buffer zone on either side of the Yangtze River in Nanjing, four subsidence funnels were identified. Analysis of the factors contributing to land subsidence in this area indicates that underground engineering construction and operation, increasing ground building area, and geological condition all have certain correlations to the land subsidence. The results obtained through PS-InSAR and SBAS-InSAR technologies revealed a high degree of consistency in monitoring outcomes, and the latter method exhibited superior monitoring accuracy than the former one in this area. This study holds significant implications for guiding the scientific management of urban geohazards along the Yangtze River.
The Usefulness of Outpatient Cardiac Telemetry in Patients with Cryptogenic Stroke
Authors: Lasek-Bal Anetta , Konka Adam , Puz Przemysław , Boidol Joanna , Kosarz-Lanczek Katarzyna , Puz Agnieszka , Wagner-Kusz Anna , Tomasik Andrzej , Student Sebastian
Published: July 2024

Introduction: Atrial fibrillation (AF), apart from non-stenotic supracardiac atherosclerosis and neoplastic disease, is the leading cause of cryptogenic stroke, including embolic stroke of un-determined source (ESUS). The aim of our study was to determine the prevalence of AF in ESUS patients based on 30-day telemetric heart rate monitoring initiated within three months after stroke onset. Another aim was to identify factors that increase the likelihood of detecting subsequent AF among ESUS patients. Material and Methods: patients with first-ever stroke classified as per the ESUS definition were eligible for this study. All patients underwent outpatient 30-day telemetric heart rate monitoring. Results: In the period between 2020 and 2022, 145 patients were included. The mean age of all qualified patients was 54; 40% of eligible patients were female. Six patients (4.14%), mostly male patients (4 vs. 2), were diagnosed with AF within the study period. In each case, the diagnosis related to a patient whose stroke occurred in the course of large vessel occlusion. Episodes of AF were detected between day 1 and 25 after starting ECG monitoring. Out of the analyzed parameters that increase the probability of, A.F.; only supraventricular extrasystoles proved to be an independent factor regarding an increased risk of AF [OR 1.046, CI 95% 1.016–1.071, p-value < 0.01]. Conclusions: The use of telemetry heart rhythm monitoring in an outpatient setting can detect AF in 4% of ESUS patients who have undergone prior diagnostic procedures for cardiogenic embolism. Supraventricular extrasystoles significantly increases the likelihood of AF detection in patients with ESUS within three months following stroke. Comorbid coronary artery disease, diabetes and hypertension, rather than a single-factor clinical burden, increase the likelihood of AF detection in older ESUS patients. ESUS in the course of large vessel occlusion is probably associated with an increased likelihood of cardiogenic embolism.
Calcitriol in Sepsis—A Single-Centre Randomised Control Trial
Authors: Thampi Siddhant Jeevan , Basheer Aneesh , Thomas Kurien
Published: July 2024

Background/Objectives: Sepsis is a life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis is a significant cause of hospital admission and the leading reason for admission to the ICU and is associated with high mortality. Vitamin D has shown promising immunomodulatory effects by upregulating the antimicrobial peptide, cathelicidin. However, previous studies analysing the use of calcitriol in sepsis have shown variable results and did not utilise APACHE II (Acute Physiology and Chronic Health Evaluation II) scores as endpoints. This study evaluates the efficacy of intramuscular calcitriol in patients admitted to the ICU with sepsis, focusing on its impact on APACHE II scores. The primary aim was to determine if intramuscular calcitriol improved APACHE II scores from day 1 to day 7 or discharge from the ICU, whichever was earlier. Secondary outcomes included 28-day mortality, ventilator days, vasopressor days, ICU stay length, adverse events, and hospital-acquired infections in ICU patients. Methods: This was a triple-blinded phase III randomised control trial. A total of 152 patients with suspected sepsis were block-randomised to receive either intramuscular calcitriol (300,000 IU) (n = 76) or a placebo (n = 76). The trial was registered with the Clinical Trials Registry—India (CTRI No: CTRI 2019/01/17066) following ethics committee approval and was not funded. Results: There was no significant difference in APACHE II scores between the calcitriol and placebo groups from day 1 to day 7 (p = 0.382). There were no significant changes in 28-day mortality (14.4% vs. 17%, p = 0.65), number of days on a ventilator (5 vs. 5, p = 0.84), number of days on vasopressors (3 vs. 3, p = 0.98), length of ICU stay (10 days vs. 11 days, p = 0.78), adverse events (27.6% vs. 19.7%, p = 0.25), and hospital-acquired infections (17.1% vs. 15.8%, p = 0.82). Conclusions: There was no effect of intramuscular calcitriol in patients admitted to the ICU with sepsis.
Cataract Surgery in nAMD Patients Receiving Intravitreal Aflibercept Injections
Authors: Seredyka-Burduk Małgorzata , Liberski Slawomir , Malukiewicz Grażyna , Kocięcki Jarosław , Kaluzny Bartlomiej J.
Published: July 2024

Background: To evaluate functional and anatomical outcomesof cataract surgery in neovascular age-related macular neovascularization (nAMD) eyes receiving anti-vascular endothelial growth factor (anti-VEGF) intravitreal injections in modified pro re nata (PRN) regimen. Materials and Methods: Sixty eyes of 60 nAMD patients, including 41 women (68.3%) and 19 men (31.7%) in an average age of 77.35 ± 6.41 years, under treatment with intravitreal aflibercept injections in modified PRN regimen with no signs of macular neovascularization (MNV) activity during two consecutive visits were included in this prospective, observational study. Best-corrected visual acuity (BCVA), central retinal thickness (CRT), as well as the number of anti-VEGF injections were monitored six months before and after phacoemulsification with intraocular lens (IOL) implantation. Further, the change of the abovementioned parameters was assessed during the six-month follow-up period for CRT and the number of injections, while the BCVA was monitored for 54 months. Results: BCVA measured on the first day after surgery (0.17 ± 0.19 logMAR) as well as in the six-month post-surgery (0.13 ± 0.16 logMAR) significantly improved compared to preop values (0.42 ± 0.20 logMAR). BCVA remains stable during the observational period. We found that both differences were statistically significant (p < 0.01). The mean CRT and the mean number of injections did not differ between the six-month pre- and post-surgical periods. Conclusions: We showed the beneficial effect of phacoemulsification in nAMD patients treated with anti-VEGF agents on visual outcomes in the short and long term. Cataract surgery in nAMD eyes treated with anti-VEGF injections does not increase the frequency of anti-VEGF injections and does not cause deterioration of the macular status.
Effects of Limbs’ Spasticity on Spinopelvic Alignment in Post-Stroke Patients: A Cross-Sectional Study
Authors: Bissolotti Luciano , Brojka Alice , Vezzoli Marika , Calza Stefano , Nicoli Federico , Romero-Morales Carlos , Villafañe Jorge Hugo
Published: July 2024

Objectives: This study aimed to determine the impacts of upper and lower limb (UL and LL) spasticity and impairment on spinal alignment in chronic post-stroke patients. Methods: A total of 45 consecutive chronic post-stroke patients, 18 women and 27 men, from 18 to 70 years old who presented post-stroke hemiparesis were recruited in this cross-sectional study. The clinical assessment included the Modified Ashworth Scale (UL-MAS and LL-MAS spasticity), Upper Limb Motricity Index (UL-MI), FAST-UL, and Five Times Sit-to-Stand Test (5T-STS); the Associated Reaction Rating Scale was used to measure associated reactions in the hemiparetic UL, the plumb line distance from the spinous process of C7 on the sagittal (PL-C7s) and frontal plane (Pl-C7f), the kyphosis apex (PL-AK), and the spinous process of L3 (PL-L3). Angular measures of spinal alignment were measured by a Bunnell scoliometer™ (angle of trunk rotation—ATR) and a gravity-dependent inclinometer (inclination at C7-T1 and T12-L1). Results: In chronic post-stroke patients, there was found to be an association between the 5T-STS and PL-C7f (β = 0.41, p = 0.05) and the angle of inclination at T12-L1 (β = 0.44, p = 0.01). The FAST-UL correlated with PL-C7f (β = −0.41, p = 0.05), while the UL-MI correlated with this last parameter (β = −0.36, p = 0.04) and the ATR (β = −0.31, p = 0.05). The UL-MAS showed correlation with the ATR (β = 0.38, p = 0.01). Conclusions: The results lead to the possibility that, in chronic post-stroke patients, spinal misalignment on the frontal and sagittal plane is associated both with strength impairment and UL spasticity. The improvement or restoration of spinopelvic parameters can take advantage of therapeutic interventions targeted at motor improvement and spasticity reduction of the hemiparetic side.
The Role of Heat Shock Protein 70 (HSP70) in the Pathogenesis of Ocular Diseases—Current Literature Review
Authors: Modrzejewska Monika , Zdanowska Oliwia
Published: July 2024

Heat shock proteins (HSPs) have been attracting the attention of researchers for many years. HSPs are a family of ubiquitous, well-characterised proteins that are generally regarded as protective multifunctional molecules that are expressed in response to different types of cell stress. Their activity in many organs has been reported, including the heart, brain, and retina. By acting as chaperone proteins, HSPs help to refold denatured proteins. Moreover, HSPs elicit inhibitory activity in apoptotic pathways and inflammation. Heat shock proteins were originally classified into several subfamilies, including the HSP70 family. The aim of this paper is to systematise information from the available literature about the presence of HSP70 in the human eye and its role in the pathogenesis of ocular diseases. HSP70 has been identified in the cornea, lens, and retina of a normal eye. The increased expression and synthesis of HSP70 induced by cell stress has also been demonstrated in eyes with pathologies such as glaucoma, eye cancers, cataracts, scarring of the cornea, ocular toxpoplasmosis, PEX, AMD, RPE, and diabetic retinopathy. Most of the studies cited in this paper confirm the protective role of HSP70. However, little is known about these molecules in the human eye and their role in the pathogenesis of eye diseases. Therefore, understanding the role of HSP70 in the pathophysiology of injuries to the cornea, lens, and retina is essential for the development of new therapies aimed at limiting and/or reversing the processes that cause damage to the eye.