bluuebunny/crossref_metadata_2025 huggingface dataset:
Clonal Myeloid Dysplasia Following CAR T-Cell Therapy: Chicken or the Egg?
Authors: Vainstein Vladimir , Avni Batia , Grisariu Sigal , Kfir-Erenfeld Shlomit , Asherie Nathalie , Nachmias Boaz , Auman Shlomtzion , Saban Revital , Zimran Eran , Assayag Miri , Filanovsky Kalman , Horowitz Netanel A. , Lebel Eyal , Shaulov Adir , Gur Michal , Rosenbluh Chaggai , Krichevsky Svetlana , Stepensky Polina , Gatt Moshe E.
Published: July 2023

Multiple myeloma (MM) is characterized by recurrent relapses. Consequently, patients receive multiple therapy lines, including alkylating agents and immune modulators, which have been associated with secondary malignancies such as myelodysplastic syndrome (MDS). Anti-B-cell maturation antigen (BCMA) chimeric antigen receptor T cell (CART) therapy is efficacious in patients with relapsed/refractory (R/R) MM. However, the long-term complications, particularly MDS, are not well understood. Whether CART therapy causes or promotes MDS has not been thoroughly investigated. In this study, we explored the causal relationship between MDS and CART therapy. We retrospectively examined the prevalence of MDS-related morphological and mutational changes before and after administration of CART therapy in five patients. Among them, four developed MDS after CART therapy, while one had pre-existing MDS prior to CART. None of the four patients who developed post-CART MDS showed morphological MDS changes prior to CART therapy. However, all four patients exhibited molecular alterations associated with MDS in their pre-CART as well as post-CART therapy bone marrow. No new mutations were observed. Our findings provide initial evidence suggesting that anti-BCMA CART therapy in MM may promote expansion of pre-existing MDS clones rather than causing development of new clones.
The Coagulopathy of Acute Promyelocytic Leukemia: An Updated Review of Pathophysiology, Risk Stratification, and Clinical Management
Authors: Hermsen Jack , Hambley Bryan
Published: July 2023

Acute promyelocytic leukemia (APL) has a well-established mechanism and a long-term prognosis that exceeds that of any other acute leukemia. These improving outcomes are due, in part, to all-trans retinoic acid (ATRA) and arsenic trioxide (ATO), two targeted and highly active agents in this disease. However, there remains a considerable morbidity and mortality risk in APL secondary to clinically significant hemorrhagic and/or thrombotic events. Prevention and treatment of these coagulopathic complications remain significant impediments to further progress in optimizing outcomes for patients with APL. Moreover, the relative rarity of APL hinders adequately powered randomized controlled trials for evaluating APL coagulopathy management strategies. This review draws from peer-reviewed works falling between initial descriptions of APL in 1957 and work published prior to January 2023 and provides an updated overview of the pathophysiology of hemorrhagic and thrombotic complications in APL, outlines risk stratification parameters, and compiles current clinical best practices. An improved understanding of the pathophysiologic mechanisms driving hemorrhage and thrombosis along with the completion of well-designed trials of management strategies will assist clinicians in developing interventions that mitigate these devastating complications in an otherwise largely curable disease.
Methods for Evaluating the Efficacy of Medical Castration: A Systematic Review
Authors: Aguilar Adriana , Planas Jacques , Trilla Enrique , Morote Juan
Published: July 2023

Measuring serum testosterone determination during medical castration is recommended by prostate cancer (PCa) guidelines to assess its efficacy and define castration resistance. It has been suggested that other biochemical compounds, such as free testosterone or luteinising hormone (LH), could also assess castration efficacy. We aimed to analyse the current evidence for serum biochemical compounds that could be appropriate candidates for evaluating medical castration efficacy. A systematic review was conducted after two investigators independently searched the literature in the PubMed, Cochrane Library, and EMBASE databases published between January 1980 and February 2023. Their searches used the medical subject headings ‘prostatic neoplasms’, ‘testosterone and androgen antagonists’, ‘gonadotropin-releasing hormone/analogues and derivatives’, ‘free testosterone’, and ‘luteinising hormone’. Studies were selected according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses criteria, and their eligibility was based on the Participants, Intervention, Comparator, and Outcome strategy. The search was limited to original articles published in English. Among the 6599 initially identified titles, 15 original studies analysing the clinical impact of serum testosterone levels in PCa patients undergoing androgen deprivation therapy (ADT) were selected for evidence acquisition. The risk of bias in individual studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 tool. All selected studies used immunoassays to measure serum testosterone, although only methods based on liquid or gas chromatography and mass spectrometry are recommended to measure low testosterone concentrations. The reported series were not uniform in clinical stage, ADT types, and the time or number of serum testosterone measurements. Only some studies found low serum testosterone levels (<20 or <32 ng/dL) associated with greater survival free of biochemical progression and castration resistance. We conclude that little current evidence justifies the measurement of serum testosterone during ADT using no appropriate methods. No reported longitudinal studies have examined the clinical impact of serum testosterone measured using liquid chromatography with tandem mass spectrometry (LC-MSMS), free testosterone, or LH in PCa patients undergoing medical castration. We conclude that well-designed longitudinal studies examining the clinical impact of serum testosterone measured with LC-MSMS, serum-free testosterone, and LH on biochemical progression and castration resistance in PCa patients undergoing neo-adjuvant castration in radiation therapy or continuous castration are needed.
HIPEC in Ovarian Cancer Is the Future… and Always Will Be? Results from a Spanish Multicentric Survey
Authors: González Gil Alida , Cerezuela Fernández-de Palencia Álvaro , Gómez Ruiz Álvaro Jesús , Gil Gómez Elena , López Hernández Francisco , Nieto Ruiz Aníbal , Martínez Jerónimo , Marhuenda Iván , Cascales Campos Pedro Antonio
Published: July 2023

Ovarian cancer is the leading cause of death due to gynecological tumors in the female population. Despite optimal first-line treatment, including cytoreduction and platinum-based systemic chemotherapy, recurrences are frequent. The use of hyperthermic intraperitoneal chemotherapy (HIPEC) has been criticized, especially because of the lack of randomized controlled trials (RCTs) with convincing results to support the use of HIPEC in patients with ovarian cancer with peritoneal dissemination. In 2018, the clinical trial published by Van Driel et al. reported improved outcomes in favor of HIPEC treatment with cisplatin. In this study, we conducted a national survey within the Spanish group of peritoneal surgical oncology (Grupo Español de Cirugía Oncológica Peritoneal, GECOP) to explore the impact of the results of this RCT on clinical practice. A total of 33 groups completed the survey. Routine clinical practice was not changed in 28 of the 33 groups (85%) based on the results of the Van Driel trial. Despite the results of this RCT, most groups considered that more RCTs are needed and that, in the future, HIPEC may become the standard of care. In conclusion, the results from RCTs evaluating HIPEC treatment in patients with ovarian cancer has not been transferred to clinical practice.
Diagnosis, Management and Theragnostic Approach of Gastro-Entero-Pancreatic Neuroendocrine Neoplasms
Authors: Piscopo Leandra , Zampella Emilia , Pellegrino Sara , Volpe Fabio , Nappi Carmela , Gaudieri Valeria , Fonti Rosa , Vecchio Silvana Del , Cuocolo Alberto , Klain Michele
Published: July 2023

Gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NENs) constitute an ideal target for radiolabeled somatostatin analogs. The theragnostic approach is able to combine diagnosis and therapy by the identification of a molecular target that can be diagnosed and treated with the same radiolabeled compound. During the last years, advances in functional imaging with the introduction of somatostatin analogs and peptide receptor radionuclide therapy, have improved the diagnosis and treatment of GEP-NENs. Moreover, PET/CT imaging with 18F-FDG represents a complementary tool for prognostic evaluation of patients with GEP-NENs. In the field of personalized medicine, the theragnostic approach has emerged as a promising tool in diagnosis and management of patients with GEP-NENs. The aim of this review is to summarize the current evidence on diagnosis and management of patients with GEP-NENs, focusing on the theragnostic approach.
Investigation of CrB as a Potential Gas Sensor for Fault Detection in Eco-Friendly Power Equipment
Authors: Tan Xiangyu , Na Zhimin , Zhuo Ran , Wang Dibo , Zhang Yifan , Wu Peng
Published: July 2023

With the development of two-dimensional materials such as graphene, transition metal dichalcogenides (TMDs), MXenes and MBenes, these materials have received extensive attention from scholars in the field of gas sensing due to their unique and superior properties. Based on first-principles calculations, the adsorption energy, charge transfer, density of states and deformation charge density of CrB, an MBene successfully synthesized under laboratory conditions, were investigated for the adsorption of the decomposition components (CF4, C3F6 and COF2) of an insulating medium, C4F7N. The calculation results revealed strong chemisorption with an adsorption energy as high as −3.336 eV between CrB and COF2, as well as physical adsorption with CF4 and C3F6. However, the excessive interaction strength makes it difficult for COF2 molecules to escape from the binding of the CrB substrate, making CrB more suitable as an adsorbent to remove COF2 gas. Compared with COF2 and CF4, CrB has appropriate adsorption energy and charge transfer for C3F6 adsorption, and its theoretical recovery performance is acceptable, indicating its potential as a sensor for detecting C3F6.
Nickel Tetrasulfonated Phthalocyanine Decorated with AuNP as a Double Sensorial Platform: SERS and Electrochemical
Authors: Martin Cibely Silva , Kavazoi Henry Seitiro , Miyazaki Celina Massumi , Alessio Priscila , Constantino Carlos José Leopoldo
Published: July 2023

The development of materials for multiple applications is a challenge in the fields of technology and materials science. In this work, screen-printed carbon electrodes (SPCEs) were modified with an electropolymerized nickel tetrasulfonated phthalocyanine film (polymeric-NiTsPc = p-NiTsPc) decorated with gold nanoparticles (AuNP). The modified SPCEs were applied as a sensing platform for analysis via electrochemical and surface-enhanced Raman scattering (SERS) spectroscopy. The SPCEs modification was based on the potential cycling firstly in a NiTsPc solution and then in an AuHCl4 solution, with the fast formation of spherical AuNP through the p-NiTsPc film surface. The modified electrode based on SPCE/p-NiTsPc/AuNP showed a synergetic effect in voltammetric measurements in [Fe(CN)6]3−/[Fe(CN)6]4− probe as well as an electrocatalytic effect in the presence of dopamine. The calibration curve towards dopamine detection presented a linear range from 1 to 10 μmol/L with a limit of detection of 0.73 μmol/L. The spectroelectrochemistry measurements combining SERS and the applied potential of −60 mV showed that the SPCE/p-NiTsPc/AuNP and SPCE/AuNP can be powerfully used as a dual sensing platform for dopamine detection. In the case of SPCE/p-NiTsPc/AuNP, p-NiTsPc plays an important role in facilitating electron transfer during the electrochemical reaction, while AuNP is crucial for obtaining SERS signals for dopamine detection.
Preparation of Hierarchical Co/Beta Catalyst and Its Application in Hydrogenation of CO to Aviation Kerosene
Authors: Zhai Yanliang , Zhang Wanli , Lu Xianggang , Wang Jun , Zhang Jian , Ma Lili , Zhang Zhixiang , Li Zhijun
Published: July 2023

Due to the increasing depletion of petroleum resources, the production route of non-oil-based aviation kerosene has been paid more and more attention. In this regard, the process of preparing aviation kerosene from syngas (CO and H2) is one of the most promising industrial alternative fuel production routes. The traditional syngas-to-aviation kerosene catalyst uses iron-based and cobalt-based catalysts, which is a complex process with a high cost. In this work, a hierarchical Co/Beta metal-zeolite bifunctional catalyst prepared via the melting method is reported, which can directly and highly selectively produce an aviation kerosene component from syngas (CO and H2). Compared with the catalyst prepared via the impregnation method, the Co/Beta catalyst prepared via the melting method has smaller, more highly dispersed Co metal active species and more suitable acid properties, the conversion of CO can reach 34.6%, and the selectivity of the C8-C16 aviation kerosene component can reach 40.2%, which provides a new idea for the industrial production of aviation kerosene.
Energy-Efficient Control of a Gas Turbine Power Generation System
Authors: Al-Shami Marwan , Mohamed Omar , Abu Elhaija Wejdan
Published: July 2023

Gas turbines are used in the energy sectors as propulsion and power generation technologies. Despite technological advances in power generation and the emergence of numerous energy resources, gas turbine technology remains important due to its flexibility in load demand following, dynamical behavior, and the ability to work on different fuels with minor design changes. However, there would be no ambitious progress for gas turbines without reliable modeling and simulation. This paper describes a novel approach for modeling, identifying, and controlling a running gas turbine power plant. A simplified nonlinear model structure composed of s-domain transfer functions and nonlinear blocks represented by rate limiters, saturations, and look-up tables has been proposed. The model parameters have been optimized to fit real-world data. The verified model was then used to design a multiple PI/PD control to regulate the gas turbine via the inlet guide vane and fuel vales. The aim is to raise and stabilize the compressor’s differential pressure or pressure ratio, as well as raise the set-point of the temperature exhausted from the combustion turbine; as a result, energy efficiency has been improved by an average of 237.16 MWh saving in energy (or 8.96% reduction in fuel consumption) for a load range of 120 MW to 240 MW.
Complete Hydatidiform Mole with Lung Metastasis and Coexisting Live Fetus: Unexpected Twin Pregnancy Mimicking Placenta Accreta
Authors: Jung Hera
Published: July 2023

Twin pregnancy with a complete hydatidiform mole and coexisting fetus (CHMCF) is an exceedingly rare condition with an incidence of about 1 in 20,000–100,000 pregnancies. It can be detected by prenatal ultrasonography and an elevated maternal serum beta-human chorionic gonadotropin (BhCG) level. Herein, the author reports a case of CHMCF which was incidentally diagnosed through pathologic examination without preoperative knowledge. The 41-year-old woman, transferred due to preterm labor, delivered a female baby by cesarean section at 28 + 5 weeks of gestation. Clinically, the surgeon suspected placenta accreta on the surgical field, and the placental specimen was sent to the pathology department. On gross examination, focal vesicular and cystic lesions were identified separately from the normal-looking placental tissue. The pathologic diagnosis was CHMCF and considering the fact that placenta accreta was originally suspected, invasive hydatidiform mole was not ruled out. After radiologic work-up, metastatic lung lesions were detected, and methotrexate was administered in six cycles at intervals of every two weeks. The author presents the clinicopathological features of this unexpected CHMCF case accompanied by pulmonary metastasis, compares to literature review findings, and emphasizes the meticulous pathologic examination.
Multimodal Spatiotemporal Deep Learning Framework to Predict Response of Breast Cancer to Neoadjuvant Systemic Therapy
Authors: Verma Monu , Abdelrahman Leila , Collado-Mesa Fernando , Abdel-Mottaleb Mohamed
Published: July 2023

Current approaches to breast cancer therapy include neoadjuvant systemic therapy (NST). The efficacy of NST is measured by pathologic complete response (pCR). A patient who attains pCR has significantly enhanced disease-free survival progress. The accurate prediction of pCR in response to a given treatment regimen could increase the likelihood of achieving pCR and prevent toxicities caused by treatments that are not effective. Th early prediction of response to NST can increase the likelihood of survival and help with decisions regarding breast-conserving surgery. An automated NST prediction framework that is able to precisely predict which patient undergoing NST will achieve a pathological complete response (pCR) at an early stage of treatment is needed. Here, we propose an end-to-end efficient multimodal spatiotemporal deep learning framework (deep-NST) framework to predict the outcome of NST prior or at an early stage of treatment. The deep-NST model incorporates imaging data captured at different timestamps of NST regimens, a tumor’s molecular data, and a patient’s demographic data. The efficacy of the proposed work is validated on the publicly available ISPY-1 dataset, in terms of accuracy, area under the curve (AUC), and computational complexity. In addition, seven ablation experiments were carried out to evaluate the impact of each design module in the proposed work. The experimental results show that the proposed framework performs significantly better than other recent methods.
Unravelling Peritoneal Carcinomatosis Using Cross-Sectional Imaging Modalities
Authors: Veron Sanchez Ana , Bennouna Ilias , Coquelet Nicolas , Cabo Bolado Jorge , Pinilla Fernandez Inmaculada , Mullor Delgado Luis A. , Pezzullo Martina , Liberale Gabriel , Gomez Galdon Maria , Bali Maria A.
Published: July 2023

Peritoneal carcinomatosis (PC) refers to malignant epithelial cells that spread to the peritoneum, principally from abdominal malignancies. Until recently, PC prognosis has been considered ill-fated, with palliative therapies serving as the only treatment option. New locoregional treatments are changing the outcome of PC, and imaging modalities have a critical role in early diagnosis and disease staging, determining treatment decision making strategies. The aim of this review is to provide a practical approach for detecting and characterizing peritoneal deposits in cross-sectional imaging modalities, taking into account their appearances, including the secondary complications, the anatomical characteristics of the peritoneal cavity, together with the differential diagnosis with other benign and malignant peritoneal conditions. Among the cross-sectional imaging modalities, computed tomography (CT) is widely available and fast; however, magnetic resonance (MR) performs better in terms of sensitivity (92% vs. 68%), due to its higher contrast resolution. The appearance of peritoneal deposits on CT and MR mainly depends on the primary tumour histology; in case of unknown primary tumour (3–5% of cases), their behaviour at imaging may provide insights into the tumour origin. The timepoint of tumour evolution, previous or ongoing treatments, and the peritoneal spaces in which they occur also play an important role in determining the appearance of peritoneal deposits. Thus, knowledge of peritoneal anatomy and fluid circulation is essential in the detection and characterisation of peritoneal deposits. Several benign and malignant conditions show similar imaging features that overlap those of PC, making differential diagnosis challenging. Knowledge of peritoneal anatomy and primary tumour histology is crucial, but one must also consider clinical history, laboratory findings, and previous imaging examinations to achieve a correct diagnosis. In conclusion, to correctly diagnose PC in cross-sectional imaging modalities, knowledge of peritoneal anatomy and peritoneal fluid flow characteristics are mandatory. Peritoneal deposit features reflect the primary tumour characteristics, and this specificity may be helpful in its identification when it is unknown. Moreover, several benign and malignant peritoneal conditions may mimic PC, which need to be considered even in oncologic patients.
Patient Blood Management after Hematopoietic Stem Cell Transplantation in a Pediatric Setting: Starting Low and Going Lower
Authors: Del Fante Claudia , Mortellaro Cristina , Recupero Santina , Giorgiani Giovanna , Agostini Annalisa , Panigari Arianna , Perotti Cesare , Zecca Marco
Published: July 2023

Despite the substantial transfusion requirements, there are few studies on the optimal transfusion strategy in pediatric patients undergoing hematopoietic stem cell transplantation (HSCT). Our study aimed to retrospectively analyze red blood cell (RBC) and platelet (PLT) transfusion practices during the first 100 days after HSCT at the pediatric hematology/oncology unit of our hospital between 2016 and 2019, due to a more restrictive approach adopted after 2016. We also evaluated the impact on patient outcomes. A total of 146 consecutive HSCT patients were analyzed. In patients without hemorrhagic complications, the Hb threshold for RBC transfusions decreased significantly from 2016 to 2017 (from 7.8 g/dL to 7.3 g/dL; p = 0.010), whereas it remained the same in 2017, 2018, and 2019 (7.3, 7.2, and 7.2 g/dL, respectively). Similarly, the PLT threshold decreased significantly from 2016 to 2017 (from 18,000 to 16,000/μL; p = 0.026) and further decreased in 2019 (15,000/μL). In patients without severe hemorrhagic complications, the number of RBC and PLT transfusions remained very low over time. No increase in 100-day and 180-day non-relapse mortality or adverse events was observed during the study period. No patient died due to hemorrhagic complications. Our preliminary observations support robust studies enrolling HSCT patients in patient blood management programs.
Contribution of Dynamic and Genetic Tests for Short Stature Diagnosing: A Case Report
Authors: Biagetti Betina , Valenzuela Irene , Campos-Martorell Ariadna , Campos Berta , Hernandez Sara , Giralt Marina , Díaz-Troyano Noelia , Iniesta-Serrano Emilio , Yeste Diego , Simó Rafael
Published: July 2023

Genetic tests have led to the discovery of many novel genetic variants related to growth failure, but the clinical significance of some results is not always easy to establish. The aim of this report is to describe both clinical phenotype and genetic characteristics in an adult patient with short stature associated with a homozygous variant in disintegrin and metalloproteinase with thrombospondin motifs type 17 gene (ADAMTS17) combined with a homozygous variant in the GH secretagogue receptor (GHS-R). The index case had severe short stature (SS) (−3.0 SD), small hands and feet, associated with eye disturbances. Genetic tests revealed homozygous compounds for ADAMTS17 responsible for Weill–Marchesani-like syndrome but a homozygous variant in GHS-R was also detected. Dynamic stimulation with an insulin tolerance test showed a normal elevation of GH, while the GH response to macimorelin stimulus was totally flattened. We show the implication of the GHS-R variant and review the molecular mechanisms of both entities. These results allowed us to better interpret the phenotypic spectrum, associated co-morbidities, its implications in dynamic tests, genetic counselling and treatment options not only to the index case but also for her relatives.
DroneNet: Rescue Drone-View Object Detection
Authors: Wang Xiandong , Yao Fengqin , Li Ankun , Xu Zhiwei , Ding Laihui , Yang Xiaogang , Zhong Guoqiang , Wang Shengke
Published: July 2023

Recently, the research on drone-view object detection (DOD) has predominantly centered on efficiently identifying objects through cropping high-resolution images. However, it has overlooked the distinctive challenges posed by scale imbalance and a higher prevalence of small objects in drone images. In this paper, to address the challenges associated with the detection of drones (DODs), we introduce a specialized detector called DroneNet. Firstly, we propose a feature information enhancement module (FIEM) that effectively preserves object information and can be seamlessly integrated as a plug-and-play module into the backbone network. Then, we propose a split-concat feature pyramid network (SCFPN) that not only fuses feature information from different scales but also enables more comprehensive exploration of feature layers with many small objects. Finally, we develop a coarse to refine label assign (CRLA) strategy for small objects, which assigns labels from coarse- to fine-grained levels and ensures adequate training of small objects during the training process. In addition, to further promote the development of DOD, we introduce a new dataset named OUC-UAV-DET. Extensive experiments on VisDrone2021, UAVDT, and OUC-UAV-DET demonstrate that our proposed detector, DroneNet, exhibits significant improvements in handling challenging targets, outperforming state-of-the-art detectors.
Distributed Optimization for Resource Allocation Problem with Dynamic Event-Triggered Strategy
Authors: Guo Feilong , Chen Xinrui , Yue Mengyao , Jiang Haijun , Chen Siyu
Published: July 2023

This study aims to unravel the resource allocation problem (RAP) by using a consensus-based distributed optimization algorithm under dynamic event-triggered (DET) strategies. Firstly, based on the multi-agent consensus approach, a novel one-to-all DET strategy is presented to solve the RAP. Secondly, the proposed one-to-all DET strategy is extended to a one-to-one DET strategy, where each agent transmits its state asynchronously to its neighbors. Furthermore, it is proven that the proposed two types of DET strategies do not have Zeno behavior. Finally, numerical simulations are provided to validate and illustrate the effectiveness of the theoretical results.
Unconditionally Stable System Incorporated Factorization-Splitting Algorithm for Blackout Re-Entry Vehicle
Authors: Wen Yi , Wang Junxiang , Xu Hongbing
Published: July 2023

A high-temperature plasma sheath is generated on the surface of the re-entry vehicle through the conversion of kinetic energy to thermal and chemical energy across a strong shock wave at the hypersonic speed. Such a condition results in the forming of a blackout which significantly affects the communication components. To analyze the re-entry vehicle at the hypersonic speed, an unconditionally stable system incorporated factorization-splitting (SIFS) algorithm is proposed in finite-difference time-domain (FDTD) grids. The proposed algorithm shows advantages in the entire performance by simplifying the update implementation in multi-scale problems. The plasma sheath is analyzed based on the modified auxiliary difference equation (ADE) method according to the integer time step scheme in the unconditionally stable algorithm. Higher order perfectly matched layer (PML) formulation is modified to simulate open region problems. Numerical examples are carried out to demonstrate the performance of the algorithm from the aspects of target characteristics and antenna model. From resultants, it can be concluded that the proposed algorithm shows considerable accuracy, efficiency, and absorption during the simulation. Meanwhile, plasma sheath significantly affects the communication and detection of the re-entry vehicle.
Interaction Information Guided Prototype Representation Rectification for Few-Shot Relation Extraction
Authors: Ma Xiaoqin , Qin Xizhong , Liu Junbao , Ran Wensheng
Published: July 2023

Few-shot relation extraction aims to identify and extract semantic relations between entity pairs using only a small number of annotated instances. Many recently proposed prototype-based methods have shown excellent performance. However, existing prototype-based methods ignore the hidden inter-instance interaction information between the support and query sets, leading to unreliable prototypes. In addition, the current optimization of the prototypical network only relies on cross-entropy loss. It is only concerned with the accuracy of the predicted probability for the correct label, ignoring the differences of other non-correct labels, which cannot account for relation discretization in semantic space. This paper proposes an attentional network of interaction information to obtain a more reliable relation prototype. Firstly, an inter-instance interaction information attention module is designed to mitigate prototype unreliability through interaction information between the support set and query set instances, utilizing category information hidden in the query set. Secondly, the similarity scalar, which is defined by the mixed features of the prototype and the relation and is added to the focal loss to improve the attention of hard examples. We conducted extensive experiments on two standard datasets and demonstrated the validity of our proposed model.
Civil Aviation Travel Question and Answer Method Using Knowledge Graphs and Deep Learning
Authors: Gong Weiguang , Guan Zheng , Sun Yuzhu , Zhu Zhuoning , Ye Shijie , Zhang Shaopu , Yu Pan , Zhao Huimin
Published: July 2023

In this paper, a civil aviation travel question and answer (Q&A) method based on integrating knowledge graphs and deep learning technology is proposed to establish a highly efficient travel information Q&A platform and quickly and accurately obtain question information and give corresponding answers to passengers. In the proposed method, a rule-based approach is employed to extract triads from the acquired civil aviation travel dataset to construct a civil aviation travel knowledge graph. Then, the ELECTRA-BiLSTM-CRF model is constructed to recognize the entity, and an improved ALBERT-TextCNN model is used for intent classification. Finally, Cypher query templates are transformed into Cypher query statements and retrieved in the Neo4j database, and the query returns the result, which realizes a new civil aviation travel Q&A method. A self-built civil aviation dataset is selected to prove the effectiveness of the proposed method. The experimental results show that the proposed method based on integrating knowledge graphs and deep learning technology can achieve better Q&A results, and it has better generalization and high accuracy.
Tissue Ablation Using Irreversible Electrolytic Electroporation with Reduced Voltage
Authors: Kim Ki-Han , An Jinsu , Park Young-Jin , Park Jung-Hoon , Kim Hong Bae , Yi Jeong-Han , Kim Hyung-Sik
Published: July 2023

Thermal tissue ablation may damage surrounding healthy tissue and cause pain. In this study, tissue ablation with the sequential application of electrical energy-inducing irreversible electroporation (IRE) and electrolysis (EL) (IRE + EL = IREEL) was investigated. An IREEL device was designed to control five output pulse parameters: voltage level (VL), pulse width (PW), pulse interval (PI), pulse number (PN), and pulse tail time (PTT). IREEL experiments were conducted on vegetable tissue. The results indicated that by increasing the VL and PTT, the ablation area increased, whereas the impedance was reduced significantly. Almost no ablation area was observed when only EL or IRE at 500 V and 1000 V, respectively, were applied. The ablation area observed with IRE alone at 1500 V was defined as 100%. In the case of IREEL at 500 V and 1000 V, ablation was induced even with the use of micro-second level PTT, and ablation areas of 91% and 186% were achieved, respectively. For IREEL at a voltage of 1500 V, the ablation area expanded to 209% and the maximum temperature was 48.7 °C, whereas the temperature did not exceed 30 °C under other conditions. A change in pH was also observed in an agar-gel phantom experiment which was conducted to examine and confirm whether IREEL induced electrolysis. IREEL was able induce ablation at low voltages owing to the synergistic effect of applying IRE and EL sequentially. Moreover, the ablation areas at high voltages could be increased compared to the areas observed when IRE and EL were applied independently.
Research on Identity Authentication Scheme for UAV Communication Network
Authors: Xia Tao , Wang Menglin , He Jun , Lin Shaofeng , Shi Yongqi , Guo Liyuan
Published: July 2023

Unmanned aerial vehicles (UAV) play a vital role in many fields, such as agricultural planting, security patrol, emergency rescue, and so on. The development and implementation of these devices have become vital in terms of reachability and usability. Unfortunately, as drones become more widely used in various fields, they become more and more vulnerable to attacks and security threats, including, but not limited to, eavesdropping, man-in-the-middle attacks, and known session key attacks. In order to deal with these attacks and security threats and meet the needs of lightweight UAV communication, a secure and efficient authentication scheme is essential. To meet the security and lightweight requirements of an identity authentication scheme in a UAV communication network, this paper proposes an identity authentication scheme sdronelig based on an elliptic curve cryptosystem. The scheme realizes the mutual authentication and session key agreement configuration between the UAV and the ground station, and the authentication and key agreement between the UAVs can be realized with the help of the control station. The sdronelig authentication scheme is based on the ECDH key exchange protocol in the elliptic curve cryptography algorithm and adopts the MAC message authentication code technology and the method of pre-calculating part of the process. Under the premise of ensuring the security of the UAV communication network, the authentication efficiency is improved, the communication overhead and communication times are reduced, and the lightweight requirement of the UAV authentication scheme is met. Additionally, a formal verification tool is used to verify the security of the sdronelig scheme under the Dolev-Yao threat model, which is suitable for UAV networks. Finally, a detailed comparative study was conducted on security features, communication overhead, the number of communications, and computational overhead. The results show that the proposed sdronelig authentication scheme not only provides superior security features but also has better or comparable overhead compared to other existing authentication schemes.
An In-Phase/Quadrature Index Modulation-Aided Spread Spectrum Communication System for Underwater Acoustic Communication
Authors: Wei Yunlong , Quan Lingmiao , Xu Weikai , Wang Deqing , Wang Lin
Published: July 2023

In a multiple-sequences-spread-spectrum (MSSS) communication system, the transmitted signal is made up of superimposed cyclic shift sequences, each sequence carrying a symbol, so the data rate is inceased. In this context, we propose an in-phase/quadrature index modulation-aided MSSS system (MSSS-I/Q-IM), which achieves higher data rate and better bit-error-rate (BER) performance. The new system maps the additional bits to the cyclic shift length of the superimposed sequences of I/Q branches. The sequences in two branches carry the real and imaginary parts of the M-ary phase-shift-keying (MPSK) symbols, respectively. We derive the theoretical BER of the MSSS-I/Q-IM system over an additive white Gaussian noise (AWGN) channel. Then, the simulation experiments of the proposed system and MSSS system over an underwater acoustic channel are analyzed and compared. Finally, field experiments are carried out in the pool environment. The experiment results show that the proposed scheme can achieve higher data rate or better BER performance via adjusting the IM parameter. This is important for the time-variant underwater acoustic transmission environments.
Novel Heuristic Optimization Technique to Solve Economic Load Dispatch and Economic Emission Load Dispatch Problems
Authors: Singh Nagendra , Chakrabarti Tulika , Chakrabarti Prasun , Margala Martin , Gupta Amit , Praveen S. Phani , Krishnan Sivaneasan Bala , Unhelkar Bhuvan
Published: July 2023

The fundamental objective of economic load dispatch is to operate the available generating units such that the needed load demand satisfies the lowest generation cost and also complies with the various constraints. With proper power system operation planning using optimized generation limits, it is possible to reduce the cost of power generation. To fulfill the needs of such objectives, proper planning and economic load dispatch can help to plan the operation of the electrical power system. To optimize the economic load dispatch problems, various classical and new evolutionary optimization approaches have been used in research articles. Classical optimization techniques are outdated due to many limitations and are also unable to provide a global solution to the ELD problem. This work uses a new variant of particle swarm optimization techniques called modified particle swarm optimization, which is effective and efficient at finding optimum solutions for single as well as multi-objective economic load dispatch problems. The proposed MPSO is used to solve single and multi-objective problems. This work considers constraints like power balance and power generation limits. The proposed techniques are tested for three different case studies of ELD and EELD problems. (1) The first case is tested using the data of 13 generating unit systems along with the valve point loading effect; (2) the second case is tested using 15 generating unit systems along with the ramp rate limits; and (3) the third case is tested using the economic emission dispatch (EELD) as a multi-objective problem for 6 generating unit systems. The outcomes of the suggested procedures are contrasted with those of alternative optimization methods. The results show that the suggested strategy is efficient and produces superior optimization outcomes than existing optimization techniques.
Photoplethysmography in Wearable Devices: A Comprehensive Review of Technological Advances, Current Challenges, and Future Directions
Authors: Kim Kwang Bok , Baek Hyun Jae
Published: July 2023

Photoplethysmography (PPG) is an affordable and straightforward optical technique used to detect changes in blood volume within tissue microvascular beds. PPG technology has found widespread application in commercial medical devices, enabling measurements of oxygen saturation, blood pressure, and cardiac output; the assessment of autonomic nerve function; and the diagnosis of peripheral vascular disease. Recently, the growing demand for non-invasive, portable, cost-effective technology, along with advancements in small semiconductor components, has led to the integration of PPG into various wrist-worn wearable devices. Multiple sensor structures have been proposed and, through appropriate signal processing and algorithmic application, these wearable devices can measure a range of health indicators during daily life. This paper begins by addressing the market status of wrist-worn wearable devices, followed by an explanation of the fundamental principles underlying light operation and its interaction with living tissue for PPG measurements. Moving on to technological advancements, the paper addresses the analog front end for the measurement of the PPG signal, sensor configurations with multiple light emitters and receivers, the minimum sampling rate required for low-power systems, and the measurement of stress, sleep, blood pressure, blood glucose, and activity using PPG signals. Several challenges in the field are also identified, including selecting the appropriate wavelength for the PPG sensor’s light source, developing low-power interpolation methods to extract high-resolution inter-beat intervals at a low sampling rate, and exploring the measurement of physiological phenomena using multi-wavelength PPG signals simultaneously collected at the same location. Lastly, the paper presents future research directions, which encompass the development of new, reliable parameters specific to wearable PPG devices and conducting studies in real-world scenarios, such as 24-h long-term measurements.
Distributed Adaptive Fault-Tolerant Control for Leaderless/Leader–Follower Multi-Agent Systems against Actuator and Sensor Faults
Authors: Ye Zhengyu , Cheng Yuehua , Yu Ziquan , Jiang Bin
Published: July 2023

The faults of actuators and sensors can lead to abnormal operations or even system faults in multi-agent systems (MASs). To address this issue, this paper proposes an adaptive fault-tolerant control (FTC) algorithm for leaderless/leader–follower MASs against actuator and sensor faults. First, extended states integrating the fault components are constructed and the MAS is transformed into a descriptor system form. Then, a sliding-mode observer is designed for the transformed MAS. Based on the estimated MAS states and faults, adaptive FTC algorithms are developed, which update the control gains with the distributed tracking error. Finally, numerical simulations demonstrate that the proposed method can guarantee MAS stability against actuator and sensor faults.
Constructing Maps for Autonomous Robotics: An Introductory Conceptual Overview
Authors: Racinskis Peteris , Arents Janis , Greitans Modris
Published: July 2023

Mapping the environment is a powerful technique for enabling autonomy through localization and planning in robotics. This article seeks to provide a global overview of actionable map construction in robotics, outlining the basic problems, introducing techniques for overcoming them, and directing the reader toward established research covering these problem and solution domains in more detail. Multiple levels of abstraction are covered in a non-exhaustive vertical slice, starting with the fundamental problem of constructing metric occupancy grids with Simultaneous Mapping and Localization techniques. On top of these, topological meshes and semantic maps are reviewed, and a comparison is drawn between multiple representation formats. Furthermore, the datasets and metrics used in performance benchmarks are discussed, as are the challenges faced in some domains that deviate from typical laboratory conditions. Finally, recent advances in robot control without explicit map construction are touched upon.
Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint
Authors: Xu Zequan , Wang Wei , Chi Yixiang , Li Kun , He Leiying
Published: July 2023

Path planning to generate an appropriate time sequence of positions for a complex trajectory is an open challenge in robotics. This paper proposes an optimization method with the integration of an improved ant colony algorithm and a high-order spline interpolation technique. The optimization process can be modelled as the travelling salesman problem. The greatest features of this method include: (1) automatic generation for complex trajectory and a new idea of selecting the nearest start point instead of using the traditional way of human operation; (2) an optimized motion sequence of the manipulator with the shortest length of the free-load path improves efficiency by nearly 65% and (3) trajectories both in Cartesian space and joint space are interpolated with good smoothness to reduce shocks and vibrations. Simulations and experiments are conducted to demonstrate the good properties of this method.
An Efficient Encryption Scheme with Fully Hidden Access Policy for Medical Data
Authors: Zhang Moli , Shao Feijiao , Zheng Ruijuan , Liu Muhua , Ji Zhihang
Published: July 2023

With the development of informatization, patient medical data are generally stored in the form of electronic medical records. Hospitals store a large amount of medical data on cloud servers, which can ensure the integrity and sharing of medical data. There are many problems when sharing medical data, the most important of which is the security of private data. The ciphertext-policy attribute-based encryption (CP-ABE) algorithm not only supports data encryption, but also supports data access control. The CP-ABE algorithm is applied to medical databases. Through the encryption of medical data and the fine-grained control of data owner access to medical data, the privacy security and sharing security of medical data are realized. However, the traditional CP-ABE algorithm also has problems for the data user regarding access policy privacy leakage and the low efficiency of medical data encryption and decryption. This paper proposes a secure and efficient encryption technique. Medical data are encrypted using a symmetric encryption algorithm, and the CP-ABE algorithm with a fully hidden access policy encrypts the symmetric key. To implement access policy hiding, it uses an attribute bloom filter (ABF) for all access structures. The solution also supports the outsourced decryption of medical data, which can improve the encryption and decryption efficiency of the technique. Finally, in this paper, it is demonstrated that the scheme is selectively chosen-plaintext attack secure (CPA-secure). The experimental results show that users have less computational consumption to obtain medical data.
A Knowledge Graph Embedding Based Service Recommendation Method for Service-Based System Development
Authors: Xie Fang , Zhang Yiming , Przystupa Krzysztof , Kochan Orest
Published: July 2023

Web API is an efficient way for Service-based Software (SBS) development, and mashup is a key technology which merges several web services to deal with the increasing complexity of software requirements and expedite the service-based system development. The efficient service recommendation method is vital for the software development. However, the existing methods often suffer from data sparsity or cold start issues, which should lead to bad effects. Currently, this paper starts with SBS development, and proposes a service recommendation method based on knowledge graph embedding and collaborative filtering (CF) technology. In our model, we first construct a refined knowledge graph using SBS-service co-invocation record and SBS and service related information to mine the potential semantics relationship between SBS and service. Then, we learn the SBS and service entities in the knowledge graph. These heterogeneous entities (SBS and service, etc.) are embedded into the low-dimensional space through the representation learning algorithms of Word2vec and TransR, and the distances between SBS and service vectors are calculated. The input of recommendation model is SBS requirement (target SBS), the similarities functional SBS set is extracted from knowledge graph, which can relieve the cold start problem. Meanwhile, the recommendation model uses CF to recommend service to target SBS. Finally, this paper verifies the effectiveness of method on the real-word dataset. Compared with the several state-of-the-art methods, our method has the best service hit rate and ranking quality.
Design and Implementation of EinStein Würfelt Nicht Program Monte_Alpha
Authors: Chen Chih-Hung , Chiu Sin-Yi , Lin Shun-Shii
Published: July 2023

The game of EinStein würfelt nicht involves an element of uncertainty due to die rolling, which poses a big challenge in the development of computer game programs. However, the intriguing nature of probabilistic elements has made this game popular in computer game competitions. This study aimed to develop a high-strength EinStein würfelt nicht program that utilizes an efficient bitboard representation for the game board as well as pre-established probability distribution tables and extensively uses bitwise operations to improve the efficiency of game tree expansion. Additionally, this study attempted to replace random simulation with an evaluation function to enhance the accuracy of the Upper Confidence bounds applied to Trees algorithm. Through this design, we improved the strength of our program, and we hope that this program will be able to achieve additional excellent results in future computer game tournaments.