bluuebunny/crossref_metadata_2025 huggingface dataset:
Insights into Flexible Bioinspired Fins for Unmanned Underwater Vehicle Systems through Deep Learning
Authors: Zhou Brian , Viswanath Kamal , Geder Jason , Sharma Alisha , Lee Julian
Published: July 2024

The last few decades have led to the rise of research focused on propulsion and control systems for bio-inspired unmanned underwater vehicles (UUVs), which provide more maneuverable alternatives to traditional UUVs in underwater missions. Recent work has explored the use of time-series neural network surrogate models to predict thrust and power from vehicle design and fin kinematics. We expand upon this work, creating new forward neural network models that encapsulate the effects of the material stiffness of the fin on its kinematic performance, thrust, and power, and are able to interpolate to the full spectrum of kinematic gaits for each material. Notably, we demonstrate through testing of holdout data that our developed forward models capture the thrust and power associated with each set of parameters with high resolution, enabling highly accurate predictions of previously unseen gaits and thrust and FOM gains through proper materials and kinematics selection. As propulsive efficiency is of utmost importance for flapping-fin UUVs in order to extend their range and endurance for essential operations, a non-dimensional figure of merit (FOM), derived from measures of propulsive efficiency, is used to evaluate different fin designs and kinematics and allow for comparison with other bio-inspired platforms. We use the developed FOM to analyze optimal gaits and compare the performance between different fin materials. The forward model demonstrates the ability to capture the highest thrust and FOM with good precision, which enables us to improve thrust generation by 83.89% and efficiency by 137.58% with proper fin stiffness and kinematics selection, allowing us to improve material selection for bio-inspired fin design.
Two Acceleration-Layer Configuration Amendment Schemes of Redundant Robot Arms Based on Zhang Neurodynamics Equivalency
Authors: Tang Zanyu , Mao Mingzhi , Zhang Yunong , Tan Ning
Published: July 2024

Two innovative acceleration-layer configuration amendment (CA) schemes are proposed to achieve the CA of constrained redundant robot arms. Specifically, by applying the Zhang neurodynamics equivalency (ZNE) method, an acceleration-layer CA performance indicator is derived theoretically. To obtain a unified-layer inequality constraint by transforming from angle-layer and velocity-layer constraints to acceleration-layer constraints, five theorems and three corollaries are theoretically derived and rigorously proved. Then, together with the unified acceleration-layer bound constraint, an enhanced acceleration-layer CA scheme specially considering three-layer time-variant physical limits is proposed, and a simplified acceleration-layer CA scheme considering three-layer time-invariant physical limits is also proposed. The proposed CA schemes are finally formulated in the form of standard quadratic programming and are solved by a projection neurodynamics solver. Moreover, comparative simulative experiments based on a four-link planar arm and a UR3 spatial arm are performed to verify the efficacy and superiority of the proposed CA schemes. At last, physical experiments are conducted on a real Kinova Jaco2 arm to substantiate the practicability of the proposed CA schemes.
Task-Motion Planning System for Socially Viable Service Robots Based on Object Manipulation
Authors: Jeon Jeongmin , Jung Hong-ryul , Pico Nabih , Luong Tuan , Moon Hyungpil
Published: July 2024

This paper presents a software architecture to implement a task-motion planning system that can improve human-robot interactions by including social behavior when social robots provide services related to object manipulation to users. The proposed system incorporates four main modules: knowledge reasoning, perception, task planning, and motion planning for autonomous service. This system adds constraints to the robot motions based on the recognition of the object affordance from the perception module and environment states from the knowledge reasoning module. Thus, the system performs task planning by adjusting the goal of the task to be performed, and motion planning based on the functional aspects of the object, enabling the robot to execute actions consistent with social behavior to respond to the user’s intent and the task environment. The system is verified through simulated experiments consisting of several object manipulation services such as handover and delivery. The results show that, by using the proposed system, the robot can provide different services depending on the situation, even if it performs the same tasks. In addition, the system demonstrates a modular structure that enables the expansion of the available services by defining additional actions and diverse planning modules.
Behavioral, Functional Imaging, and Neurophysiological Outcomes of Transcranial Direct Current Stimulation and Speech-Language Therapy in an Individual with Aphasia
Authors: Ashaie Sameer A. , Hernandez-Pavon Julio C. , Houldin Evan , Cherney Leora R.
Published: July 2024

Speech-language therapy (SLT) is the most effective technique to improve language performance in persons with aphasia. However, residual language impairments remain even after intensive SLT. Recent studies suggest that combining transcranial direct current stimulation (tDCS) with SLT may improve language performance in persons with aphasia. However, our understanding of how tDCS and SLT impact brain and behavioral relation in aphasia is poorly understood. We investigated the impact of tDCS and SLT on a behavioral measure of scripted conversation and on functional connectivity assessed with multiple methods, both resting-state functional magnetic resonance imaging (rs–fMRI) and resting-state electroencephalography (rs–EEG). An individual with aphasia received 15 sessions of 20-min cathodal tDCS to the right angular gyrus concurrent with 40 min of SLT. Performance during scripted conversation was measured three times at baseline, twice immediately post-treatment, and at 4- and 8-weeks post-treatment. rs–fMRI was measured pre-and post-3-weeks of treatment. rs–EEG was measured on treatment days 1, 5, 10, and 15. Results show that both communication performance and left hemisphere functional connectivity may improve after concurrent tDCS and SLT. Results are in line with aphasia models of language recovery that posit a beneficial role of left hemisphere perilesional areas in language recovery.
Maintaining Cognitive Performance at the Expense of Gait Speed for Asymptomatic Concussed Athletes: A Novel Dual-Task and Post-Exercise Assessment
Authors: Lavoie Gabriel , Bolduc Mathieu , Sicard Veronik , Lepore Franco , Ellemberg Dave
Published: July 2024

Our goal was to evaluate persisting deficits in gait and executive functioning in asymptomatic athletes with a history of concussion using a novel approach combining a dual-task paradigm and post-exercise exertion. Thirty-eight athletes aged 17 to 25 years old participated in the study, including 18 with a history of concussion. The dual-task paradigm required walking continuously at a predetermined self-paced target speed of 6.5 km/h while executing a complex switch task. Athletes completed two conditions, each on separate days: (1) dual task alone and (2) dual task following 20 min of running on a non-motorized treadmill. The statistical analyses revealed a significant reduction in gait speed exclusively for athletes with a history of concussion and only following the post-exercise condition (p = 0.008). These findings suggest that although asymptomatic concussed athletes maintain a cognitive performance comparable to non-concussed athletes, this appears to be achieved at the expense of gait speed. Our results underscore the importance of incorporating gait assessments and post-exercise exertion into concussion evaluation protocols in both research and clinical settings.
Male Body Odor Affects Emotional State, LH, and Cortisol Secretion in Women of Different Age Groups
Authors: Laktionova Tatiana , Kvasha Ilya , Voznessenskaya Vera
Published: July 2024

Hormone changes across women’s menstrual cycles may lead to changes in their perceptions of chemical signals and their hormonal responses to these cues. The aim of the present study was to determine the role of menstrual cycle phase in the response to extracts of male axillary secretions (EMAS) in women. We tested healthy reproductive age and premenopausal women (n = 29). An EMAS/control solution was applied once every two hours during either the follicular or luteal phase, at which point saliva samples for luteinizing hormone (LH) and cortisol monitoring were collected. LH and cortisol concentrations were analyzed using the enzyme immunoassay (EIA) technique. Positive and Negative Affect Schedule (PANAS) and Visual Analogue Scales (VAS) scores were used to assess the participants’ moods. For the first time, we showed that EMAS may produce opposite effects on LH secretion depending on the menstrual cycle phase of the recipient. We observed a significant increase in the number of LH peaks (p = 0.0447) and their amplitudes (p = 0.0469) when EMAS was applied during the follicular phase, while the same application in the luteal phase lowered the amplitudes of LH peaks (p = 0.0382). For the first time, we showed that EMAS application increased salivary cortisol levels in reproductive age women relative to premenopausal women (p = 0.0032). PANAS scores revealed changes in positive and negative affect after EMAS application. Our data indicate the significance of the menstrual cycle phase for EMAS’ effects on LH secretion and mood, but not on cortisol secretion in women.
Study of the Dynamic Reaction Mechanism of the Cable-Stayed Tube Bridge under Earthquake Action
Authors: Zhu Xiyu , Jiang Yuzhu , Weng Guangyuan
Published: July 2024

In order to explore the failure mode of the cable-stayed pipe bridge under earthquake action, taking the structural system of an oil and gas pipeline–cable-stayed pipe bridge as the research object, the full-scale finite element calculation model of the cable-stayed pipe bridge–oil and gas pipeline structural system as well as the finite element calculation model considering the additional mass of the oil and gas medium and the fluid–structure interaction effect were established by using ANSYS Workbench finite element software. The stress and displacement of the cable under the earthquake action were analyzed in the time history, as were the response characteristics of the cable when subjected to both methods. The calculation results show that the overall failure of the pipeline is basically the same under the two methods. Compared with the additional mass method, the solution for the fluid–structure coupling method can be derived through a comprehensive analysis of the flow field and structure, respectively, avoiding the sudden change caused by model simplification or calculation error so that the analysis results can better simulate the actual situation. In summary, the fluid–structure interaction method enables a more precise prediction of the dynamic response of the structure, and the findings of this research can provide a theoretical foundation and technical guidance for optimizing the seismic performance of cable-stayed pipe bridges.
Evaluation of a Novel Lateral Emitting Laser Fiber for Near-Infrared Photoimmunotherapy
Authors: Suzuki Motofumi , Kobayashi Hisataka , Hanaoka Hirofumi
Published: July 2024

Near-infrared photoimmunotherapy (NIR-PIT) is a new cancer therapy that uses NIR light and conjugates of a tumor-targeting monoclonal antibody and phthalocyanine dye. In clinical practice, frontal and cylindrical diffusers are the only options for NIR illumination. However, illumination in a narrow space is technically difficult with such diffusers. Therefore, we evaluated a lateral illumination system using a lateral emitting laser (LEL) fiber. The LEL fiber illuminated a certain area in a lateral direction. NIR-PIT with an LEL fiber reduced luciferase activity in a light-dose-dependent manner in A431-GFP-luc cells in vitro and significantly suppressed tumor proliferation in a xenograft mouse model. To evaluate the usefulness of the LEL fiber in the illumination of a narrow space, a tumor was illuminated from the inside of a cylinder, mimicking a narrow space, and the fluorescence intensity in the tumor was monitored. In the frontal diffuser, NIR light was unevenly delivered and little light reached a distal tumor area from the illuminated side. By contrast, the LEL fiber allowed a uniform illumination of the entire tumor, and a loss of fluorescence was observed even in distal areas. These findings suggested that the LEL fiber can be used for NIR-PIT and is suitable for NIR light illumination in a narrow space.
Advances in Image-Guided Ablation Therapies for Solid Tumors
Authors: Campbell Warren A. , Makary Mina S.
Published: July 2024

Image-guided solid tumor ablation methods have significantly advanced in their capability to target primary and metastatic tumors. These techniques involve noninvasive or percutaneous insertion of applicators to induce thermal, electrochemical, or mechanical stress on malignant tissue to cause tissue destruction and apoptosis of the tumor margins. Ablation offers substantially lower risks compared to traditional methods. Benefits include shorter recovery periods, reduced bleeding, and greater preservation of organ parenchyma compared to surgical intervention. Due to the reduced morbidity and mortality, image-guided tumor ablation offers new opportunities for treatment in cancer patients who are not candidates for resection. Currently, image-guided ablation techniques are utilized for treating primary and metastatic tumors in various organs with both curative and palliative intent, including the liver, pancreas, kidneys, thyroid, parathyroid, prostate, lung, breast, bone, and soft tissue. The invention of new equipment and techniques is expanding the criteria of eligible patients for therapy, as now larger and more high-risk tumors near critical structures can be ablated. This article provides an overview of the different imaging modalities, noninvasive, and percutaneous ablation techniques available and discusses their applications and associated complications across various organs.
Sequential Endoluminal Gemcitabine and Cabazitaxel with Intravenous Pembrolizumab as a Bladder-Preserving Strategy for Docetaxel-Unresponsive Non-Muscle Invasive Urothelial Carcinoma Following Transurethral Resection of Bladder Tumor
Authors: McElree Ian M. , Packiam Vignesh T. , Steinberg Ryan L. , Hougen Helen Y. , Mott Sarah L. , Abou Chakra Mohamad , Zakharia Yousef , O’Donnell Michael A.
Published: July 2024

Growing evidence suggests that many patients with high-risk non-muscle invasive urothelial carcinoma (NMIUC) can undergo bladder-sparing management with salvage intravesical therapies. However, inherent or developed disease resistance, particularly after multiple lines of prior salvage therapy, implores the continued pursuit of new treatment combinations. Herein, we describe the outcomes of 26 patients (31 treated units; 24 lower tract, 7 upper tract) with high-risk NMIUC treated with sequential intravesical gemcitabine and cabazitaxel with concomitant intravenous pembrolizumab (GCP) at the University of Iowa from August 2020 to February 2023. Median (IQR) follow-up was 30 (IQR: 17–35) months. Treated units had a history of high-risk NMIUC with a median of four prior endoluminal inductions. Overall, 87% of units presented with CIS or positive urine cytology. The 1- and 2-year recurrence-free survival was 77% (CI: 58–88%) and 52% (CI: 30–70%), respectively. The 2-year progression-free and cancer-specific survival was 70% (CI: 44–85%) and 96% (CI: 75–99%), respectively. In total, 22/26 (85%) patients reported any adverse event and 5/26 (19%) reported a grade ≥3 adverse event; however, all patients tolerated a full induction course. These results suggest that GCP is an effective and tolerable treatment option for patients with recurrent high-risk NMIUC.
The Novel Cytokine Interleukin-41/Meteorin-like Is Reduced in Diffuse Systemic Sclerosis
Authors: Freedman Paul , Schock Bettina , O’Reilly Steven
Published: July 2024

Systemic sclerosis (SSc) is an autoimmune connective tissue disease with a triad of features that include vascular abnormalities, inflammation and skin and lung fibrosis. At the core of the disease is the activation of myofibroblasts from quiescent fibroblasts and this can be modified by various cytokines. IL-41 is a recently described cytokine that was initially characterised as an adipokine as it was highly expressed in adipocytes and adipose tissue. However, it has recently been identified as being widely expressed and has immunomodulatory functions. This study examined the circulating levels of IL-41 and its expression in skin biopsies. We demonstrated significantly reduced levels of IL-41 in diffuse SSc that was also mirrored in the skin of SSc patients. AMPK has been proposed as a downstream target of IL-41, so we also measure mammalian target of rapamycin in skin and found that this is elevated in SSc patients. We speculate that IL-41 maybe an antifibrotic cytokine and its reduction may facilitate the activation of fibroblasts.
Markers of Dermal Fibroblast Subpopulations for Viable Cell Isolation via Cell Sorting: A Comprehensive Review
Authors: Łuszczyński Krzysztof , Soszyńska Marta , Komorowski Michał , Lewandowska Paulina , Zdanowski Robert , Sobiepanek Anna , Brytan Marek , Malejczyk Jacek , Lutyńska Anna , Ścieżyńska Aneta
Published: July 2024

Fibroblasts are among the most abundant cell types in the human body, playing crucial roles in numerous physiological processes, including the structural maintenance of the dermis, production of extracellular matrix components, and mediation of inflammatory responses. Despite their importance, fibroblasts remain one of the least characterized cell populations. The advent of single-cell analysis techniques, particularly single-cell RNA sequencing (scRNA-seq) and fluorescence-activated cell sorting (FACS), has enabled detailed investigations into fibroblast biology. In this study, we present an extensive analysis of fibroblast surface markers suitable for cell sorting and subsequent functional studies. We reviewed over three thousand research articles describing fibroblast populations and their markers, characterizing and comparing subtypes based on their surface markers, as well as their intra- and extracellular proteins. Our detailed analysis identified a variety of distinct fibroblast subpopulations, each with unique markers, characteristics dependent on their location, and the physiological or pathophysiological environment. These findings underscore the diversity of fibroblasts as a cellular population and could lead to the development of novel diagnostic and therapeutic tools.
APOE4 Increases Energy Metabolism in APOE-Isogenic iPSC-Derived Neurons
Authors: Budny Vanessa , Knöpfli Yannic , Meier Debora , Zürcher Kathrin , Bodenmann Chantal , Peter Siri L. , Müller Terry , Tardy Marie , Cortijo Cedric , Tackenberg Christian
Published: July 2024

The apolipoprotein E4 (APOE4) allele represents the major genetic risk factor for Alzheimer’s disease (AD). In contrast, APOE2 is known to lower the AD risk, while APOE3 is defined as risk neutral. APOE plays a prominent role in the bioenergetic homeostasis of the brain, and early-stage metabolic changes have been detected in the brains of AD patients. Although APOE is primarily expressed by astrocytes in the brain, neurons have also been shown as source for APOE. However, the distinct roles of the three APOE isoforms in neuronal energy homeostasis remain poorly understood. In this study, we generated pure human neurons (iN cells) from APOE-isogenic induced pluripotent stem cells (iPSCs), expressing either APOE2, APOE3, APOE4, or carrying an APOE knockout (KO) to investigate APOE isoform-specific effects on neuronal energy metabolism. We showed that endogenously produced APOE4 enhanced mitochondrial ATP production in APOE-isogenic iN cells but not in the corresponding iPS cell line. This effect neither correlated with the expression levels of mitochondrial fission or fusion proteins nor with the intracellular or secreted levels of APOE, which were similar for APOE2, APOE3, and APOE4 iN cells. ATP production and basal respiration in APOE-KO iN cells strongly differed from APOE4 and more closely resembled APOE2 and APOE3 iN cells, indicating a gain-of-function mechanism of APOE4 rather than a loss-of-function. Taken together, our findings in APOE isogenic iN cells reveal an APOE genotype-dependent and neuron-specific regulation of oxidative energy metabolism.
Critical Review on Advanced Cooling Strategies in Friction Stir Processing for Microstructural Control
Authors: Patel Md Saad , Immanuel R. Jose , Rahaman Ariful , Khan Mohammad Faseeulla , Jouiad Mustapha
Published: July 2024

Friction stir processing (FSP) stands as an effective approach designed for grain refinement and site-specific microstructural modification. The evolving microstructure during FSP is determined by various variables out of which rate of sample cooling is the key parameter. More often, FSP is conducted in naturally flowing air; however, a large number of studies are conducted by researchers across the world; stressing the importance of additional sample cooling strategy for tailoring the material microstructure. Such strategies vary not only in terms of the cooling medium used but also with regard to various other compliant conditions that must be fulfilled for the cooling process to make them successful and economically viable. This work critically reviews the most prevalent methods practiced by various researchers and industries for controlled sample cooling during and after FSP. The underlying mechanisms; advantages; disadvantages; and limitations of each procedure along with the resulting microstructure and material performances are discussed and recommendations are provided
Using the ClinFIT COVID-19 Instrument to Assess the Functional Impairments Specific to Post-COVID-19 Patients in Romania
Authors: Ursescu Clara , Teodoru Gigi , Bucurica Sandica , Nica Remus Iulian , Lazăr Ștefan Dragoș , Popescu Marius Nicolae , Ciobanu Ileana , Berteanu Mihai
Published: July 2024

Introduction: The COVID-19 pandemic has led to approximately 3.5 million cases in Romania, causing systemic inflammation and over 200 symptoms affecting various body systems. This complexity has challenged rehabilitation systems, necessitating personalized plans tailored to each patient’s illness stage and impairment level. The ISPRM-developed ClinFIT COVID-19 instrument, aligned with the ICF categories, assists in assessing patients during acute, post-acute, and long-term phases. Objective: This study aimed to evaluate and assess functional impairments in post-COVID-19 patients in Romania, with a secondary goal of generating rehabilitation directions. Methods: Data were collected from patients at two Bucharest medical centers, including those with persistent symptoms post-acute phase. Participants were assessed using the adapted ClinFIT COVID-19 instrument, and descriptive statistics were applied. Conclusions: Findings revealed diverse functional impairments in physical, psychological, and social domains among post-COVID-19 patients, with severe impairments more common in those with long-term COVID-19. Complete impairment in complex movement and paid work was noted, affecting one-third of salaried employees and forcing some to retire. In the acute phase, the most frequent functional impairments were sleep, attention, pain sensation, and exercise tolerance functions. In contrast, the most severely affected functions were exercise tolerance and mobility joint functions. Age did not positively correlate with any of the analyzed functions. In the post-acute phase, sleep, energy, and drive functions remained the most frequently affected functions, while the most severely affected was, by far, the moving around function. In the post-acute period, respiratory and respiratory muscle functions strongly correlated with all tasks related to physical activity. In the long COVID-19 phase, remunerative employment was the most severely affected function, while attention functions remained the most frequently affected, similar to the acute phase. The ClinFIT COVID-19 instrument effectively captured these impairments, underscoring the need for comprehensive rehabilitation strategies.
Functional Improvement at One Year in Fibrotic Interstitial Lung Diseases—Prognostic Value of Baseline Biomarkers and Anti-Inflammatory Therapies
Authors: Shao Guangyu , Thöne Paul , Kaiser Bernhard , Lamprecht Bernd , Lang David
Published: July 2024

Background: The clinical spectrum of fibrotic interstitial lung diseases (ILDs) is highly heterogeneous. We aimed to evaluate the prognostic value of widely available baseline biomarkers for the improvement of lung function in patients with fibrotic ILDs. Methods: This registry-based study included 142 patients with fibrotic ILDs as defined by the presence of reticulation, traction bronchiectasis or honeycombing on initial high-resolution computed tomography (HRCT). Functional improvement at 1 year was defined as a relative increase of 5% in forced vital capacity (FVC) or of 10% in diffusion capacity for carbon monoxide (DLCO). The prognostic value of baseline biomarkers was evaluated for all patients and the subgroup with anti-inflammatory treatment. Results: At one year, 44 patients showed improvement while 73 showed disease progression. Multivariate analyses found prognostic significance for age < 60 years (OR 5.4; 95%CI 1.9–15.4; p = 0.002), lactate dehydrogenase (LDH) >250 U/L (OR 2.5; 95%CI 1.1–5.8; p = 0.043) and blood monocyte count < 0.8 G/L (OR 3.5; 95%CI 1.1–11.3; p = 0.034). In 84 patients undergoing anti-inflammatory treatment, multivariate analysis revealed age < 60 years (OR 8.5 (95%CI 2.1–33.4; p = 0.002) as the only significant variable. Conclusion: Younger age, a higher LDH and lower blood monocyte count predicted functional improvement in fibrotic ILD patients, while in those treated with anti-inflammatory drugs, only age had significant implications.
The Surviving, Not Thriving, Photoreceptors in Patients with ABCA4 Stargardt Disease
Authors: De Bruyn Hanna , Johnson Megan , Moretti Madelyn , Ahmed Saleh , Mujat Mircea , Akula James D. , Glavan Tomislav , Mihalek Ivana , Aslaksen Sigrid , Molday Laurie L. , Molday Robert S. , Berkowitz Bruce A. , Fulton Anne B.
Published: July 2024

Stargardt disease (STGD1), associated with biallelic variants in the ABCA4 gene, is the most common heritable macular dystrophy and is currently untreatable. To identify potential treatment targets, we characterized surviving STGD1 photoreceptors. We used clinical data to identify macular regions with surviving STGD1 photoreceptors. We compared the hyperreflective bands in the optical coherence tomographic (OCT) images that correspond to structures in the STGD1 photoreceptor inner segments to those in controls. We used adaptive optics scanning light ophthalmoscopy (AO-SLO) to study the distribution of cones and AO-OCT to evaluate the interface of photoreceptors and retinal pigment epithelium (RPE). We found that the profile of the hyperreflective bands differed dramatically between patients with STGD1 and controls. AO-SLOs showed patches in which cone densities were similar to those in healthy retinas and others in which the cone population was sparse. In regions replete with cones, there was no debris at the photoreceptor-RPE interface. In regions with sparse cones, there was abundant debris. Our results raise the possibility that pharmaceutical means may protect surviving photoreceptors and so mitigate vision loss in patients with STGD1.
Determining Diagnostic Sensitivity: A Comparison of Rose Bengal Test, Coombs Gel Test, ELISA and Bacterial Culture in Brucellosis Diagnosis—Analyzing Clinical Effectiveness in Light of Inflammatory Markers
Authors: Barkay Orçun , Karakeçili Faruk , Binay Umut Devrim , Akyüz Sümeyye
Published: July 2024

Background: Brucellosis is a zoonotic infectious disease. It is estimated that the number of cases reported today is much less than the actual number. We still have difficulty in diagnosing the disease and its organ involvement. In this sense, new approaches that can be useful in clinical practice are required, and we aimed to evaluate this situation in our study. Methods: 171 of 213 patients followed in our center between January 2021 and April 2024 were included in the study. A total of 150 patients were included in the study as a control group. Rose Bengal test (RBT), Coombs gel test (CGT), enzyme-linked immunosorbent assay (ELISA), and automated blood culture were used for diagnosing brucellosis. Complete blood count, sedimentation, C-reactive protein, and biochemical parameters were obtained. Inflammation markers such as neutrophil–lymphocyte ratio, platelet–lymphocyte ratio, systemic immune-inflammation index, and systemic inflammation response index were calculated. Results: The most successful results in the diagnosis were ELISA (89.4%), RBT (88.3%), CGT (83%), and blood culture (34.8%). For diagnosing sacroiliitis and spondylodiscitis, instead of resorting to expensive methods like magnetic resonance, a combination of ELISA positivity with elevated acute phase reactants and inflammatory markers could be significantly instructive. Conclusions: Optimizing diagnostic algorithms and exploring novel diagnostic approaches, such as inflammatory markers, hold promise for improving diagnosis and management.
Corrective Evaluation of Response Capabilities of Flexible Demand-Side Resources Considering Communication Delay in Smart Grids
Authors: Liu Ying , Liu Chuan , Tao Jing , Liu Shidong , Wang Xiangqun , Zhang Xi
Published: July 2024

With the gradual increase in the proportion of new energy sources in the power grid, there is an urgent need for more flexible resources to participate in short-term regulation. The impact of communication network channel quality will continue to magnify, and factors such as communication latency may directly affect the efficiency and effectiveness of resource regulation. In this context of a large number of flexible demand-side resources accessing the grid, this article proposes a bidirectional channel delay measurement method based on MQTT (Message Queuing Telemetry Transport). It can effectively evaluate the real-time performance of communication links, considering that resources mainly access the grid through the public network. Subsequently, focusing on two typical types of resources on the demand side, namely, split air conditioners and central air conditioners, this article proposes an assessment method for correcting the response capabilities of air conditioning resources considering communication latency. Experimental simulations are conducted, and the results demonstrate that under given communication conditions, this method can more accurately estimate the response capability of air conditioners. This provides a basis for formulating more reasonable scheduling strategies, avoiding excessive or insufficient resource regulation caused by communication issues, and aiding the power grid in achieving precise scheduling.
A Self-Sovereign Identity Privacy-Preserving Scheme for Logistics Transportation Based on One-Time-Use Tokens
Authors: Sun Nigang , Zhu Chenyang , Liu Yining
Published: July 2024

The advancement of the logistics industry has fostered the enhancement of operational efficacy within the socioeconomic domain. However, the current inevitable privacy leaks in the process of logistics transportation have seriously affected the development of the industry, which led to a crisis of consumer trust and even caused economic recession. This paper proposes a self-sovereign identity privacy protection scheme tailored specifically for logistics transportation contexts. First, the scheme entails furnishing users with one-time-use tokens while establishing decentralized identities capable of concealing identity information and ensuring the secure transmission of data. Furthermore, the scheme integrates fuzzy identity-based encryption to encrypt identity information, thereby guaranteeing the confidentiality and integrity of logistics user identities along with their associated data. Compared with other schemes, this scheme exhibits superior security in the realm of logistics transportation. Its targeted encryption technology and self-sovereignty strategies address the critical issue of privacy leakage, thereby safeguarding consumer privacy rights and interests while facilitating the sustainable development of the logistics industry.
Multi-Frequency Spectral–Spatial Interactive Enhancement Fusion Network for Pan-Sharpening
Authors: Tang Yunxuan , Li Huaguang , Xie Guangxu , Liu Peng , Li Tong
Published: July 2024

The objective of pan-sharpening is to effectively fuse high-resolution panchromatic (PAN) images with limited spectral information and low-resolution multispectral (LR-MS) images, thereby generating a fused image with a high spatial resolution and rich spectral information. However, current fusion techniques face significant challenges, including insufficient edge detail, spectral distortion, increased noise, and limited robustness. To address these challenges, we propose a multi-frequency spectral–spatial interaction enhancement network (MFSINet) that comprises the spectral–spatial interactive fusion (SSIF) and multi-frequency feature enhancement (MFFE) subnetworks. The SSIF enhances both spatial and spectral fusion features by optimizing the characteristics of each spectral band through band-aware processing. The MFFE employs a variant of wavelet transform to perform multiresolution analyses on remote sensing scenes, enhancing the spatial resolution, spectral fidelity, and the texture and structural features of the fused images by optimizing directional and spatial properties. Moreover, qualitative analysis and quantitative comparative experiments using the IKONOS and WorldView-2 datasets indicate that this method significantly improves the fidelity and accuracy of the fused images.
A Pseudo-Differential LNA with Noise Improvement Techniques for Concurrent Multi-Band GNSS Applications
Authors: Eghtesadi Minoo , Mosavi Mohammad Reza , Ragonese Egidio
Published: July 2024

A low-noise amplifier (LNA) design with the operation of concurrent dual-band for Global Navigation Satellite System (GNSS) receivers with single channel is presented in this work. This LNA structure has an inductively degenerated cascode architecture and is pseudo-differential, operating at two frequencies simultaneously (1.2 GHz and 1.57 GHz). Two noise reduction/cancellation techniques, using load capacitor and feedforward path, respectively, are proposed resulting in an excellent improvement in the noise figure (NF). The input matching circuit uses both series and parallel resonant components to enable concurrency. The adopted pseudo-differential structure results in input balun elimination. Inductively degenerated cascode topology provides both input impedance and optimum noise impedance matching. The soundness of the proposed approach has been demonstrated in a 0.18-µm CMOS technology by TSMC. Simulation results show that at 1.2 GHz and 1.57 GHz the LNA achieves −13 dB and −11 dB of input matching, 24.6 dB and 24.7 dB of gain, 1.47 dB and 1.43 dB of NF, respectively. The input-referred 1-dB compression point (IP1dB) is around −16 dBm, while the input-referred third-order intercept point (IIP3) achieves −2.2 dBm at 1.2 GHz and −0.6 dBm at 1.57 GHz. The LNA draws about 13 mA from a 1.8-V supply voltage.
Empirical Investigation of Multilayered Framework for Predicting Academic Performance in Open and Distance Learning
Authors: Adewale Muyideen Dele , Azeta Ambrose , Abayomi-Alli Adebayo , Sambo-Magaji Amina
Published: July 2024

Integrating artificial intelligence (AI) in open and distance learning (ODL) necessitates comprehensive frameworks to evaluate its educational implications. Existing models lack a robust multilayered analysis of AI’s impact on educational outcomes in ODL. This study introduces a Multilayered Process Framework designed to predict academic performance in ODL and enhance inclusivity, aligning with UNESCO’s 2030 educational goals. The current research employed structural equation modelling (SEM) to analyse the impact of AI adoption, focusing on the initial layers of the process framework. Preliminary validation of the SEM framework showed a good model fit, with a Chi-square/df ratio of 2.34, Root Mean Square Error of Approximation (RMSEA) of 0.045, and Comparative Fit Index (CFI) of 0.97, indicating the model’s effectiveness in capturing the complexities of AI impacts on student outcomes. This framework provides a structured, multilayered approach to understanding AI’s role in education, facilitating the development of equitable and accessible AI-driven educational technologies. It lays the foundational work for expanding research into predictive analytics with a support vector machine (SVM), aiming to universalise quality education and ensure global educational equity. This study highlights the practical implications for integrating AI in educational settings and suggests future research directions to enhance the adaptability and effectiveness of AI-driven educational interventions.
Explicitly Exploiting Implicit User and Item Relations in Graph Convolutional Network (GCN) for Recommendation
Authors: Xiao Bowen , Chen Deng
Published: July 2024

Most existing collaborative filtering-based recommender systems rely solely on available user–item interactions for user and item representation learning. Their performance often suffers significantly when interactions are sparse, as limited user and item interactions are insufficient for learning robust representations. To address this issue, recent research has explored additional information between users and items by leveraging the user–item bipartite graph. However, these methods have not fully exploited high-order neighborhood information, primarily using sampled interactions to enrich training data rather than integrating this information directly into representation learning. In this paper, we propose a novel model, EIR-GCN (Embedding Integration with Relational Graph Convolutional Network), which directly incorporates various types of collaborative relations, such as user–user and item–item interactions, into the embedding function for user preference modeling. Specifically, our model employs advanced graph convolutional network (GCN) techniques to integrate user–item, user–user, and item–item relations for comprehensive representation learning. EIR-GCN initially selects the most influential second-order neighbors from the user–item bipartite graph to form user–user and item–item connections. With these enriched connections, a message-passing method is adopted to learn node representations by aggregating messages from directly linked nodes, including first-order item neighbors and selected second-order user neighbors. Extensive experiments on several public datasets demonstrate that EIR-GCN outperforms strong baselines, including recent GCN-based models and those exploiting high-order information. Our results show that EIR-GCN achieves state-of-the-art performance and effectively addresses the sparsity issue, highlighting its robustness and efficacy in recommendation tasks.
Improved Facial Expression Recognition Algorithm Based on Local Feature Enhancement and Global Information Association
Authors: Chen Zixuan , Yan Lingyu , Wang Hairu , Adamyk Bogdan
Published: July 2024

Facial expression recognition is the key area of research in computer vision, enabling intelligent devices to understand human emotions and intentions. However, recognition of facial expressions in natural scenes presents challenges due to environmental factors like occlusion and pose variations. To address this, we propose a novel approach that combines local feature enhancement and global information correlation. This method allows the model to learn both local and global facial features along with contextual information. By enhancing salient local features and exploring multi-scale facial expression features, our model effectively mitigates the impact of occlusion and pose variations, improving recognition accuracy. Experimental results demonstrate that our adapted model outperforms alternative algorithms in recognizing facial expressions under challenging environments, achieving recognition accuracies of 85.07% and 99.35% on the RAF-DB and CK+ datasets, respectively.
Optimal Placement of Multiple Sources in a Mesh-Type DC Microgrid Using Dijkstra’s Algorithm
Authors: Boutros Fouad , Doumiati Moustapha , Olivier Jean-Christophe , Mougharbel Imad , Kanaan Hadi
Published: July 2024

This research paper introduces an optimization methodology for the strategic electric sources’ placement at multiple positions in a DC islanded microgrid characterized by a mesh network, aiming to minimize line losses while considering minimal cable weight. The DC microgrid studied in this paper is composed of PV panels, batteries, a diesel generator, and 20 residential loads. Employing Dijkstra’s algorithm, a graph algorithm used in Google Maps, the study identifies the shortest path (resistance) between potential source nodes and various variable loads within a predefined electric distribution mesh network topology. This study focuses on active power considerations and offers valuable insights into the placement optimization of multiple sources’ positions in DC microgrid mesh networks. A key contribution of this paper lies in the ranking of source node positions based on minimal to maximal line losses, taking into consideration optimal cable weights, while using MATPOWER to validate sources’ ranking based on Dijkstra’s hypothesis. The research further includes a techno-economic study to assess the viability of sources’ placement at multiple positions within the mesh network, comparing it with the optimal placement scenario involving a single position for all sources. This methodology serves as a valuable resource for system designers and operators aiming to minimize line losses and optimize energy distribution in DC microgrids in a mesh topology.
Improved MTPA and MTPV Optimal Criteria Analysis Based on IPMSM Nonlinear Flux-Linkage Model
Authors: Fan Yingpeng , Ma Hongtai , Zhu Guoqing , Luo Jian
Published: July 2024

The use of interior permanent-magnet synchronous machines (IPMSMs) is prevalent in automotive and vehicle traction applications due to their high efficiency over a wide speed range. Given the high-power-density requirements of automotive IPMSMs, it is imperative to consider the effect of nonlinearities, such as saturation and cross-coupling, on the motor model. The aforementioned nonlinearities render conventional linear motor models incapable of accurately describing the operating characteristics of the IPMSM, including the maximum torque per ampere (MTPA) trajectory, the flux-weakening (FW) trajectory, and the maximum torque per volt (MTPV) trajectory. With respect to the linear motor model, the nonlinear flux-linkage model is gradually receiving attention from researchers. This modeling method represents the nonlinear behavior of the motor through the direct establishment of a bidirectional mapping relationship between flux-linkage and current. It is capable of naturally incorporating the effects of magnetic saturation and cross-coupling factors. However, the analysis of the current trajectory optimal criteria based on this model has not yet been reported. In this paper, the optimal criteria for the MTPA and MTPV current trajectories are analyzed based on the nonlinear flux-linkage model of IPMSMs. Firstly, the nonlinear flux-linkage model of the tested IPMSM is established by the experimental calibration method. The mathematical analytical expressions of the MTPA and MTPV optimal criteria are then analyzed by constructing and solving optimal problems with different objectives. Finally, the current command table applicable to actual motor control is constructed by calculating the current command for different operating conditions according to the optimal criteria proposed in this paper. The validity and feasibility of the optimal criteria proposed in this paper are verified through experimental tests on different operating conditions.
State-of-Charge Estimation for Lithium-Ion Battery Base on Adaptive Extended Sliding Innovation Filter
Authors: Wang Zhuo , Shen Jinrong , Xu Yang
Published: July 2024

Accurate State of Charge (SoC) estimation is pivotal in advancing battery technology. In order to enhance the precision of SoC estimation, this study introduces the 2RC equivalent circuit model for lithium batteries. The Adaptive Extended Sliding Innovation Filter (AESIF) algorithm merges the model’s predictive outcomes with observation results. However, further improvements are required for this algorithm to perform optimally in strong noise environments. By adapting to observation noise and utilizing PID control to adjust the sliding boundary layer, the algorithm can accommodate varying noise levels and control interference fluctuations within specific limits. This study enhances the AESIF algorithm in these areas, proposing an improved version (IAESIF) to elevate performance in strong noise environments and improve overall estimation accuracy. Comprehensive tests were conducted under diverse operational conditions and temperatures, with results indicating that, compared to the EKF and the AESIF algorithm in strong noise environments, the IAESIF algorithm demonstrates improved noise adaptation and overall estimation accuracy.
Evaluating the Impact of CO2 Capture on the Operation of Combined Cycles with Different Configurations
Authors: Savoldelli Elena , Ravelli Silvia
Published: July 2024

In order to reduce greenhouse gas emissions associated with power generation, the replacement of fossil fuels with renewables must be accompanied by the availability of dispatchable sources needed to balance electricity demand and production. Combined cycle (CC) power plants adopting post-combustion capture (PCC) can serve this purpose, ensuring near-zero CO2 emissions at the stack, as well as high efficiency and load flexibility. In particular, the chemical absorption process is the most established approach for industrial-scale applications, although widespread implementation is lacking. In this study, different natural gas combined cycle (NGCC) configurations were modeled to estimate the burden of retrofitting the capture process to existing power plants on thermodynamic performance. Simulations under steady-state conditions covered the widest possible load range, depending on the gas turbine (GT) model. Attention was paid to the net power loss and net efficiency penalty attributable to PCC. The former can be mitigated by lowering the GT air–fuel ratio to increase the CO2 concentration (XCO2) in the exhaust, thus decreasing the regeneration energy. The latter is reduced when the topping cycle is more efficient than the bottoming cycle for a given GT load. This is likely to be the case in the less-complex heat recovery units.