bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancements in EEG Emotion Recognition: Leveraging Multi-Modal Database Integration
Authors: Roshdy Ahmed , Karar Abdullah , Kork Samer Al , Beyrouthy Taha , Nait-ali Amine
Published: March 2024

This paper addresses the limitations of relying solely on facial expressions for emotion recognition by proposing an advanced approach that emphasizes continuous monitoring of electroencephalography (EEG) signals. Recognizing the potential for deception in facial expressions, our study leverages the growing interest in EEG signals, tapping into advancements in deep learning and machine learning. By optimizing the configuration of EEG electrodes, our approach enhances the accuracy of emotion classification systems, offering a streamlined solution. The proposed multi-input system refines EEG-based emotion recognition efficiency and integrates facial expression analysis to enhance overall system effectiveness. Through the application of brain heat map topographies and facial expression recognition, our system, employing just nine electrodes, outperforms basic emotion recognition setups. Experimental results validate that combining facial expression analysis with EEG signals provides a more comprehensive and accurate understanding of human emotions. This innovative approach holds significance across various sectors, including healthcare, psychology, and human–computer interaction. The paper introduces a novel multi-input system approach, collaboratively fusing two powerful deep learning algorithms: two Convolutional Neural Networks (CNNs). The proposed EEG-based CNN algorithm achieves an efficiency of 87.43%, rising to 91.21% when integrated with the DeepFace CNN. The seamless integration of facial expressions and brain topographies enables the system to efficiently harness abundant information from both modalities, ensuring a thorough comprehension of human emotions. By capitalizing on the combined advantages of analyzing facial expressions and EEG-derived brain topography, this avant-garde technique substantially improves both precision and efficiency in emotion recognition systems. This enhancement establishes a foundation for the introduction of innovative applications across a spectrum of fields.
Optical Coherence Tomography as a Biomarker in the Differential Diagnosis between Parkinson’s Disease and Atypical Parkinsonian Syndromes: A Narrative Review
Authors: Karatzetzou Stella , Parisis Dimitrios , Ioannidis Serafeim , Afrantou Theodora , Ioannidis Panagiotis
Published: March 2024

Parkinsonism may be a clinical manifestation of a wide range of disease entities, and still poses a great diagnostic challenge. In an attempt to provide further insight into the differential diagnosis of PD versus progressive supranuclear palsy (PSP), multiple system atrophy (MSA), corticobasal degeneration (CBD), and Lewy body dementia (LBD), several biomarkers have been investigated, yielding inconclusive results, OCT being among them. The present review aims to explore the potential diagnostic value of evaluating retinal parameters through OCT implementation among patients presenting with a Parkinsonian syndrome, with an emphasis on effective differentiation between distinct syndromes. Having reviewed all the available literature published within the last decade, neurodegeneration seems to be paralleled with degeneration and alterations of the retina that may be quantified by OCT. Specific patterns of structural changes within the retina may provide valuable information on the underlying pathology, thus highlighting the role of OCT as a diagnostic tool within this group of patients. Although still not utilized in clinical practice, OCT, if further explored and validated, may significantly enhance overall Parkinsonism care.
Extending UWOC System Applications through Photon Transmission Dynamics Study in Harbor Waters
Authors: Chang Chang , Han Xiaotian , Li Guangying , Li Peng , Nie Wenchao , Liao Peixuan , Li Cong , Wang Wei , Xie Xiaoping
Published: March 2024

Underwater wireless optical communication (UWOC) in harbor waters can facilitate real-time monitoring underwater instruments for environmental monitoring, underwater inspection, and maintenance tasks. This study delves into the complex dynamics of UWOC in four distinct harbor waters. The research employs Monte Carlo method incorporated with Fournier–Forand scattering phase function for simulating photon transmission. Key parameters such as the Transmitted full divergence angle, received aperture, and Field of View (FOV) are meticulously evaluated for their impact on power loss and time delay spread. Notably, the normalized power loss and time delay spread are found to be more significantly affected by communication distance than water quality, and the traditional Beer–Lambert law is ineffective in harbor water. The power loss of Harbor II, III, and IV are found to be 14.00 dB, 31.59 dB, and 41.59 dB lower than that of Harbor I, and the time delay spread of Harbor II, III, and IV is 30.56%, 9.67%, and 0.49% times that of the Harbor I under certain conditions. In addition, increasing the received aperture and FOV, particularly over longer distance, make little contribution to reduce the power loss and mitigate the time delay spread. Based on the fixed transmitted full divergence angle, the most applicable received FOV range is 1–3.2 rad, and the most ideal received aperture is 0.15–0.4 m. Under these conditions, the variation in normalized power loss is less than 2 dB. Additionally, the time delay spread remains within the same order of magnitude with the attenuation length (AL) held constant. These conclusions hold substantial technical relevance for the engineering design of UWOC systems in harbor waters.
Electrically Equivalent Head Tissue Materials for Electroencephalogram Study on Head Surrogates
Authors: Daru Richie Ranaisa , Rabby Monjur Morshed , Ko Tina , Shinglot Yukti , Raihan Rassel , Adnan Ashfaq
Published: March 2024

With the recent advent of smart wearable sensors for monitoring brain activities in real-time, the scopes for using Electroencephalograms (EEGs) and Magnetoencephalography (MEG) in mobile and dynamic environments have become more relevant. However, their application in dynamic and open environments, typical of mobile wearable use, poses challenges. Presently, there is limited clinical data on using EEG/MEG as wearables. To advance these technologies at a time when large-scale clinical trials are not feasible, many researchers have turned to realistic phantom heads to further explore EEG and MEG capabilities. However, to achieve translational results, such phantom heads should have matching geometric features and electrical properties. Here, we have designed and fabricated multilayer chopped carbon fiber–PDMS reinforced composites to represent phantom head tissues. Two types of phantom layers are fabricated, namely seven-layer and four-layer systems with a goal to achieve matching electrical conductivities in each layer. Desired electrical conductivities are obtained by varying the weight fraction of the carbon fibers in PDMS. Then, the prototype system was calibrated and tested with a 32-electrode EEG cap. The test results demonstrated that the phantom effectively generates a variety of scalp potential patterns, achieved through a finite number of internal dipole generators within the phantom sample. This innovative design holds potential as a valuable test platform for assessing wearable EEG technology as well as developing an EEG analysis process.
New Summation and Integral Representations for 2-Variable (p,q)-Hermite Polynomials
Authors: Raza Nusrat , Fadel Mohammed , Du Wei-Shih
Published: March 2024

In this paper, we introduce and study new features for 2-variable (p,q)-Hermite polynomials, such as the (p,q)-diffusion equation, (p,q)-differential formula and integral representations. In addition, we establish some summation models and their (p,q)-derivatives. Certain parting remarks and nontrivial examples are also provided.
Fuzzy Decision-Making and Resource Management Model of Performance Evaluation Indices
Authors: Chen Kuen-Suan , Hsieh Tsung-Hua , Chang Chia-Pao , Yao Kai-Chao , Huang Tsun-Hung
Published: March 2024

The Performance Evaluation Matrix (PEM) is an excellent decision-making tool for assessment and resource management. Satisfaction Index and Importance Index are two important evaluation indicators of construction and PEM. Managers can decide whether the service item needs to be improved based on the Satisfaction Index of the service item. When resources are limited, managers can determine the priority of improving the service item based on the Importance Index. In order to avoid the risk of misjudgment caused by sample errors and meet the needs of enterprises’ rapid decision-making, this study proposed a fuzzy test built on the confidence intervals of the above two key indicators to decide whether essential service items should be improved and determine the priority of improvement. Since the fuzzy test was relatively complex, this study further came up with fuzzy evaluation values and fuzzy evaluation critical values of service items following fuzzy testing rules. Besides, evaluation rules were established to facilitate industrial applications. This approach can be completed with any common word processing software, so it is relatively convenient in application and easy to manage. Finally, an application example was presented in this paper to explain the applicability of the proposed approach.
On Proximity Spaces Constructed on Rough Sets
Authors: Baek Jong Il , Abbas S. E. , Hur Kul , Ibedou Ismail
Published: March 2024

Based on equivalence relation R on X, equivalence class [x] of a point and equivalence class [A] of a subset represent the neighborhoods of x and A, respectively. These neighborhoods play the main role in defining separation axioms, metric spaces, proximity relations and uniformity structures on an approximation space (X,R) depending on the lower approximation and the upper approximation of rough sets. The properties and the possible implications of these definitions are studied. The generated approximation topology τR on X is equivalent to the generated topologies associated with metric d, proximity δ and uniformity U on X. Separated metric spaces, separated proximity spaces and separated uniform spaces are defined and it is proven that both are associating exactly discrete topology τR on X.
Developing Preventative Strategies to Mitigate Thermal Runaway in NMC532-Graphite Cylindrical Cells Using Forensic Simulations
Authors: Holloway Justin , Maharun Muinuddin , Houmadi Irma , Remy Guillaume , Piper Louis , Williams Mark A. , Loveridge Melanie J.
Published: March 2024

The ubiquitous deployment of Li-ion batteries (LIBs) in more demanding applications has reinforced the need to understand the root causes of thermal runaway. Herein, we perform a forensic simulation of a real-case failure scenario, using localised heating of Li(Ni0.5Mn0.3Co0.2)O2 versus graphite 18650 cylindrical cells. This study determined the localised temperatures that would lead to venting and thermal runaway of these cells, as well as correlating the gases produced as a function of the degradation pathway. Catastrophic failure, involving melting (with internal cell temperatures exceeding 1085 °C), deformation and ejection of the cell componentry, was induced by locally applying 200 °C and 250 °C to a fully charged cell. Conversely, catastrophic failure was not observed when the same temperatures were applied to the cells at a lower state of charge (SOC). This work highlights the importance of SOC, chemistry and heat in driving the thermal failure mode of Ni-rich LIB cells, allowing for a better understanding of battery safety and the associated design improvements.
Effect of Aging Path on Degradation Characteristics of Lithium-Ion Batteries in Low-Temperature Environments
Authors: Zhang Zhizu , Ji Changwei , Liu Yangyi , Wang Yanan , Wang Bing , Liu Dianqing
Published: March 2024

Typical usage scenarios for energy storage and electric vehicles (EVs) require lithium-ion batteries (LIBs) to operate under extreme conditions, including varying temperatures, high charge/discharge rates, and various depths of charge and discharge, while also fulfilling vehicle-to-grid (V2G) interaction requirements. This study empirically investigates the impact of ambient temperature, charge/discharge rate, and charge/discharge cut-off voltage on the capacity degradation rate and internal resistance growth of 18,650 commercial LIBs. The charge/discharge rate was found to have the most significant influence on these parameters, particularly the charging rate. These insights contribute to a better understanding of the risks associated with low-temperature aging and can aid in the prevention or mitigation of safety incidents.
Dense Multi-Scale Graph Convolutional Network for Knee Joint Cartilage Segmentation
Authors: Chadoulos Christos , Tsaopoulos Dimitrios , Symeonidis Andreas , Moustakidis Serafeim , Theocharis John
Published: March 2024

In this paper, we propose a dense multi-scale adaptive graph convolutional network (DMA-GCN) method for automatic segmentation of the knee joint cartilage from MR images. Under the multi-atlas setting, the suggested approach exhibits several novelties, as described in the following. First, our models integrate both local-level and global-level learning simultaneously. The local learning task aggregates spatial contextual information from aligned spatial neighborhoods of nodes, at multiple scales, while global learning explores pairwise affinities between nodes, located globally at different positions in the image. We propose two different structures of building models, whereby the local and global convolutional units are combined by following an alternating or a sequential manner. Secondly, based on the previous models, we develop the DMA-GCN network, by utilizing a densely connected architecture with residual skip connections. This is a deeper GCN structure, expanded over different block layers, thus being capable of providing more expressive node feature representations. Third, all units pertaining to the overall network are equipped with their individual adaptive graph learning mechanism, which allows the graph structures to be automatically learned during training. The proposed cartilage segmentation method is evaluated on the entire publicly available Osteoarthritis Initiative (OAI) cohort. To this end, we have devised a thorough experimental setup, with the goal of investigating the effect of several factors of our approach on the classification rates. Furthermore, we present exhaustive comparative results, considering traditional existing methods, six deep learning segmentation methods, and seven graph-based convolution methods, including the currently most representative models from this field. The obtained results demonstrate that the DMA-GCN outperforms all competing methods across all evaluation measures, providing DSC=95.71% and DSC=94.02% for the segmentation of femoral and tibial cartilage, respectively.
Intersections of Fibrodysplasia Ossificans Progressiva and Traumatic Heterotopic Ossification
Authors: Juan Conan , Bancroft Alec C. , Choi Ji Hae , Nunez Johanna H. , Pagani Chase A. , Lin Yen-Sheng , Hsiao Edward C. , Levi Benjamin
Published: March 2024

Heterotopic ossification (HO) is a debilitating pathology where ectopic bone develops in areas of soft tissue. HO can develop as a consequence of traumatic insult or as a result of dysregulated osteogenic signaling, as in the case of the orphan disease fibrodysplasia ossificans progressiva (FOP). Traumatic HO (tHO) formation is mediated by the complex interplay of signaling between progenitor, inflammatory, and nerve cells, among others, making it a challenging process to understand. Research into the pathogenesis of genetically mediated HO (gHO) in FOP has established a pathway involving uninhibited activin-like kinase 2 receptor (ALK2) signaling that leads to downstream osteogenesis. Current methods of diagnosis and treatment lag behind pre-mature HO detection and progressive HO accumulation, resulting in irreversible decreases in range of motion and chronic pain for patients. As such, it is necessary to draw on advancements made in the study of tHO and gHO to better diagnose, comprehend, prevent, and treat both.
RETRACTED: Alhakamy et al. Optimized Ellagic Acid–Ca Pectinate Floating Beads for Gastroprotection against Indomethacin-Induced Gastric Injury in Rats. Biomolecules 2020, 10, 1006
Authors: Alhakamy Nabil A. , Badr-Eldin Shaimaa M. , Ahmed Osama A. A. , Halwani Abdulrahman A. , Aldawsari Hibah M. , El-Moselhy Mohamed A. , Anter Aliaa , Sharkawi Sara S. , Sultan Muhammad H. , Madkhali Osama A. A. , Bakhrebah Muhammed A. , Alomary Mohammad N. , Abdulaal Wesam H. , Fahmy Usama A.
Published: March 2024

The journal retracts the article, “Optimized Ellagic Acid–Ca Pectinate Floating Beads for Gastroprotection against Indomethacin-Induced Gastric Injury in Rats” [...]
Proteome-Wide Mendelian Randomization and Colocalization Analysis Identify Therapeutic Targets for Knee and Hip Osteoarthritis
Authors: Zou Mingrui , Shao Zhenxing
Published: March 2024

Osteoarthritis (OA) is a common degenerative disease. Although some biomarkers and drug targets of OA have been discovered and employed, limitations and challenges still exist in the targeted therapy of OA. Mendelian randomization (MR) analysis has been regarded as a reliable analytic method to identify effective therapeutic targets. Thus, we aimed to identify novel therapeutic targets for OA and investigate their potential side effects based on MR analysis. In this study, two-sample MR, colocalization analysis, summary-data-based Mendelian randomization (SMR) and Mendelian randomization phenome-wide association study (MR-PheWAS) were conducted. We firstly analyzed data from 4907 plasma proteins to identify potential therapeutic targets associated with OA. In addition, blood expression quantitative trait loci (eQTLs) data sources were used to perform additional validation. A protein–protein interaction (PPI) network was also constructed to delve into the interactions among identified proteins. Then, MR-PheWASs were utilized to assess the potential side effects of core therapeutic targets. After MR analysis and FDR correction, we identified twelve proteins as potential therapeutic targets for knee OA or hip OA. Colocalization analysis and additional validation supported our findings, and PPI networks revealed the interactions among identified proteins. Finally, we identified MAPK3 (OR = 0.855, 95% CI: 0.791–0.923, p = 6.88 × 10−5) and GZMK (OR = 1.278, 95% CI: 1.131–1.444, p = 8.58 × 10−5) as the core therapeutic targets for knee OA, and ITIH1 (OR = 0.847, 95% CI: 0.784–0.915, p = 2.44 × 10−5) for hip OA. A further MR phenome-wide association study revealed the potential side effects of treatments targeting MAPK3, GZMK, and ITIH1. This comprehensive study indicates twelve plasma proteins with potential roles in knee and hip OA as therapeutic targets. This advancement holds promise for the progression of OA drug development, and paves the way for more efficacious treatments of OA.
Regenerative Therapy for Corneal Scarring Disorders
Authors: Chandran Christine , Santra Mithun , Rubin Elizabeth , Geary Moira L. , Yam Gary Hin-Fai
Published: March 2024

The cornea is a transparent and vitally multifaceted component of the eye, playing a pivotal role in vision and ocular health. It has primary refractive and protective functions. Typical corneal dysfunctions include opacities and deformities that result from injuries, infections, or other medical conditions. These can significantly impair vision. The conventional challenges in managing corneal ailments include the limited regenerative capacity (except corneal epithelium), immune response after donor tissue transplantation, a risk of long-term graft rejection, and the global shortage of transplantable donor materials. This review delves into the intricate composition of the cornea, the landscape of corneal regeneration, and the multifaceted repercussions of scar-related pathologies. It will elucidate the etiology and types of dysfunctions, assess current treatments and their limitations, and explore the potential of regenerative therapy that has emerged in both in vivo and clinical trials. This review will shed light on existing gaps in corneal disorder management and discuss the feasibility and challenges of advancing regenerative therapies for corneal stromal scarring.
Ectopic Expression of Neurod1 Is Sufficient for Functional Recovery following a Sensory–Motor Cortical Stroke
Authors: Livingston Jessica M. , Lee Tina T. , Enbar Tom , Daniele Emerson , Phillips Clara M. , Krassikova Alexandra , Bang K. W. Annie , Kortebi Ines , Donville Brennan W. , Ibragimov Omadyor S. , Sachewsky Nadia , Lozano Casasbuenas Daniela , Olfat Arman , Morshead Cindi M.
Published: March 2024

Stroke is the leading cause of adult disability worldwide. The majority of stroke survivors are left with devastating functional impairments for which few treatment options exist. Recently, a number of studies have used ectopic expression of transcription factors that direct neuronal cell fate with the intention of converting astrocytes to neurons in various models of brain injury and disease. While there have been reports that question whether astrocyte-to-neuron conversion occurs in vivo, here, we have asked if ectopic expression of the transcription factor Neurod1 is sufficient to promote improved functional outcomes when delivered in the subacute phase following endothelin-1-induced sensory–motor cortex stroke. We used an adeno-associated virus to deliver Neurod1 from the short GFAP promoter and demonstrated improved functional outcomes as early as 28 days post-stroke and persisting to at least 63 days post-stroke. Using Cre-based cell fate tracking, we showed that functional recovery correlated with the expression of neuronal markers in transduced cells by 28 days post-stroke. By 63 days post-stroke, the reporter-expressing cells comprised ~20% of all the neurons in the perilesional cortex and expressed markers of cortical neuron subtypes. Overall, our findings indicate that ectopic expression of Neurod1 in the stroke-injured brain is sufficient to enhance neural repair.
Metaheuristic-Based Feature Selection Methods for Diagnosing Sarcopenia with Machine Learning Algorithms
Authors: Lee Jaehyeong , Yoon Yourim , Kim Jiyoun , Kim Yong-Hyuk
Published: March 2024

This study explores the efficacy of metaheuristic-based feature selection in improving machine learning performance for diagnosing sarcopenia. Extraction and utilization of features significantly impacting diagnosis efficacy emerge as a critical facet when applying machine learning for sarcopenia diagnosis. Using data from the 8th Korean Longitudinal Study on Aging (KLoSA), this study examines harmony search (HS) and the genetic algorithm (GA) for feature selection. Evaluation of the resulting feature set involves a decision tree, a random forest, a support vector machine, and naïve bayes algorithms. As a result, the HS-derived feature set trained with a support vector machine yielded an accuracy of 0.785 and a weighted F1 score of 0.782, which outperformed traditional methods. These findings underscore the competitive edge of metaheuristic-based selection, demonstrating its potential in advancing sarcopenia diagnosis. This study advocates for further exploration of metaheuristic-based feature selection’s pivotal role in future sarcopenia research.
Detection of Parasites in the Field: The Ever-Innovating CRISPR/Cas12a
Authors: Li Xin , Dang Zhisheng , Tang Wenqiang , Zhang Haoji , Shao Jianwei , Jiang Rui , Zhang Xu , Huang Fuqiang
Published: March 2024

The rapid and accurate identification of parasites is crucial for prompt therapeutic intervention in parasitosis and effective epidemiological surveillance. For accurate and effective clinical diagnosis, it is imperative to develop a nucleic-acid-based diagnostic tool that combines the sensitivity and specificity of nucleic acid amplification tests (NAATs) with the speed, cost-effectiveness, and convenience of isothermal amplification methods. A new nucleic acid detection method, utilizing the clustered regularly interspaced short palindromic repeats (CRISPR)-associated (Cas) nuclease, holds promise in point-of-care testing (POCT). CRISPR/Cas12a is presently employed for the detection of Plasmodium falciparum, Toxoplasma gondii, Schistosoma haematobium, and other parasites in blood, urine, or feces. Compared to traditional assays, the CRISPR assay has demonstrated notable advantages, including comparable sensitivity and specificity, simple observation of reaction results, easy and stable transportation conditions, and low equipment dependence. However, a common issue arises as both amplification and cis-cleavage compete in one-pot assays, leading to an extended reaction time. The use of suboptimal crRNA, light-activated crRNA, and spatial separation can potentially weaken or entirely eliminate the competition between amplification and cis-cleavage. This could lead to enhanced sensitivity and reduced reaction times in one-pot assays. Nevertheless, higher costs and complex pre-test genome extraction have hindered the popularization of CRISPR/Cas12a in POCT.
APOEε4 Carriers Exhibit Objective Cognitive Deficits: A Cross-Sectional Study in a Single Center Trial
Authors: Zeng Yanfang , Du Wenying , Zhang Mingkai , Walker Ariel , Han Ying , Ding Yuchuan
Published: March 2024

Objective: To explore the association between the apolipoprotein E (APOE) genotype and objectively assessed cognitive function. Methods: In this cross-sectional study, 537 participants underwent a neuropsychological assessment for cognitive function and blood testing for APOE genotype. Based on cognitive test results, participants were stratified into two cohorts: Cognitively Unimpaired participants (CU) and Cognitively Impaired participants (CI). The CI group was further divided into Mild Cognitive Impairment (MCI) and Alzheimer’s Disease (AD). Furthermore, we conducted age stratification, categorizing participants into three age groups: age 1: <65 years, age 2: 65–75 years, and age 3: >75 years. We assessed the disparities in cognitive function associated with ε4 carrier status across different age brackets. Plasma amyloid-β levels were measured in a cohort of 294 participants to investigate potential interactions involving ε4 carrier status, diagnosis, sex, or plasma markers. Results: The APOE genotypic distribution among the 537 participants was characterized as follows: ε2/ε2 (5 participants), ε2/ε3 (67), ε2/ε4 (13), ε3/ε3 (330), ε3/ε4 (113), and ε4/ε4 (9). Allele frequencies were: ε3 at 78.21%, ε4 at 13.41%, and ε2 at 8.38%. Notably, the ε4 carrier frequency was markedly elevated in the AD group at 81.8% when compared to MCI at 32.8% and CU at 21.3% (p < 0.05). Within the Cognitively Unimpaired (CU) cohort, the sole discernible contrast between ε4+ and ε4− emerged in STT-B (p < 0.05). Within the CI group, ε4 carriers showed statistically poorer scores as compared to non-ε4 carriers in several cognitive tests (p < 0.05). Age stratification result revealed that, among ε4 carriers, cognitive function scores within the age 3 group were significantly inferior to those of age 1 and age 2 groups (p < 0.05). Plasma amyloid-β detection was applied to the 294 participants. We tested plasma amyloid-β (Aβ42) and plasma amyloid-β (Aβ40) levels and calculated the Aβ42/Aβ40 ratio. We found that among female ε4 carriers, both Aβ42 and the Aβ42/Aβ40 ratio were notably lower than their male counterparts (p < 0.05). Conclusions: The ε3/ε3 was the most prevalent among participants, succeeded by ε3/ε4 and ε2/ε3. The least prevalent were ε2/ε4, ε4/ε4, and ε2/ε2 genotypes. The ε3 was predominant, followed by the ε4 and ε2. Individuals with the ε4 allele exhibited significant cognitive impairment, with an especially high prevalence in AD group at 81.8%. The study unveils a pronounced correlation between the ε4 allele and cognitive deficits, implying its potential role in the advancement and severity of cognitive disorders, notably Alzheimer’s disease. Cognitive function declines with age in individuals carrying the ε4, and women are more affected by ε4.
Immersive Virtual Reality for Treatment of Unilateral Spatial Neglect via Eye-Tracking Biofeedback: RCT Protocol and Usability Testing
Authors: Martino Cinnera Alex , Verna Valeria , Marucci Matteo , Tavernese Aurora , Magnotti Luisa , Matano Alessandro , D’Acunto Chiara , Paolucci Stefano , Morone Giovanni , Betti Viviana , Tramontano Marco
Published: March 2024

About one-third of stroke survivors present unilateral spatial neglect (USN) that negatively impacts the rehabilitation outcome. We reported the study protocol and usability results of an eye-tracking (ET) biofeedback immersive virtual reality (iVR) protocol. Healthy controls and stroke patients with and without USN underwent a single session of the three iVR tasks. The system usability scale (SUS), adverse events (AEs), and ET data were collected and analyzed via parametric analysis. Twelve healthy controls (six young adults and six older adults) and seven patients with a diagnosis of single ischemic stroke (four without USN and three with confirmed diagnosis of USN) completed the usability investigation. SUS results showed good acceptability of the system for healthy controls and stroke patients without USN. ET results showed a lower performance for patients with USN concerning healthy controls and stroke patients without USN, in particular in the exploration of the left visual field. The results showed that the proposed iVR-ET biofeedback protocol is a safe and well-tolerated technique in patients with USN. The real-time feedback can induce a performance response supporting its investigation such as a treatment approach.
Understanding the Interplay between Wellness Motivation, Engagement, Satisfaction, and Destination Loyalty
Authors: Ahn Young-joo , Kim Katie Bokyun
Published: March 2024

Increased awareness of negative psychological symptoms and the negative impact of the pandemic has led to a rising demand for wellness-related travel experiences. There is a need for research on tourists’ experiential and reflective engagement in order to maximize positive outcomes such as overall satisfaction, positive WOM, and recommendations. These positive outcomes are crucial for attracting tourists and strengthening destinations’ brands. As there are few empirical studies, research on the effects of engagement on satisfaction and behavioral intentions is necessary. This study aimed to examine the relationships between wellness motivation, engagement, satisfaction, and destination loyalty among wellness tourists. It also aimed to examine the mediating effects of two engagement factors, experiential and reflective engagement, between wellness motivation and positive outcomes. A total of 319 respondents were used for the analysis, and structural equation modeling (SEM) was conducted. The results found that wellness motivation is composed of six wellness motivation components, namely physical motivation, transcendence, relaxation, social motivation, self-esteem, and escape, each representing first-order factors. Wellness motivation is positively associated with reflective and experiential engagement. Engagement positively affects satisfaction and destination loyalty. This study provides several implications, theoretically and practically.
Seismic Performance Evaluation of Reinforced Concrete Building Structure Retrofitted with Self-Centering Disc-Slit Damper and Conventional Steel Slit Damper
Authors: Naeem Asad , Koichi Kusunoki , Lee Joohno
Published: March 2024

To meet the recent requirements of low-damage design, there is a growing need to retrofit building structures with a self-centering dissipation system. This system serves a dual purpose: reducing lateral drift and providing supplemental damping to enhance the seismic performance of buildings. This research focuses on assessing the efficiency in seismic response of structures retrofitted with an innovative self-centering hysteretic damper called a Self-Centering Disc Slit Damper (SC-DSD). The SC-DSD consists of four slit dampers and pre-compressed Belleville disc springs that provide self-centering and energy dissipation capabilities. This study investigates the SC-DSD’s working mechanism, theoretical formulation, and design method of SC-DSD dampers for their application in multistory building structures. A reinforced concrete (RC) structure is selected as a case study building that is retrofitted with SC-DSDs and conventional slit dampers. Subsequent seismic performance assessments are conducted using detailed pushover to evaluate the global behavior and capacity of the structure used for the design of the damping system. Nonlinear time history analysis is performed to simulate the dynamic behavior of the retrofitted structure under a variety of seismic excitations. This analysis considers a range of ground motion records to capture different intensity levels and frequency content. Comparing these analyses reveals that the designed SC-DSDs effectively reduce seismic responses while minimizing residual displacement up to 95% when contrasted with both the bare structure and the structure retrofitted with conventional steel slit dampers.
Series–Parallel System Analysis and Reliability Research of Grid Structures Considering Adaptive Dynamic Bounding Threshold
Authors: Zhang Limei , Yi Tao , Du Qiuyue
Published: March 2024

There are many bars in grid structures, and their topological relationships are complex, so the workload of calculations involved in researching their reliability is large. In this paper, based on the geometric topological relationship within a grid structure, a series–parallel system analysis of the structure is carried out by means of node analysis, constraint grade division, and hierarchical combination analysis, and the series–parallel analysis results for the structure are used to judge the failure of the structure. In order to avoid the problem of missing important components due to unreasonable selection of the bounding threshold when identifying failed components, an adaptive dynamic bounding threshold method with high accuracy is introduced. The failure probability value of the failure path is calculated using the direct numerical integration method, and the reliability of the whole structure is obtained. Finally, the validity of this method is verified using an example of a square pyramid grid structure. The results show that the method is feasible for series–parallel system analysis, structural failure judgment, and reliability analysis of a grid structure.
Design Decision Support for Healthcare Architecture: A VR-Integrated Approach for Measuring User Perception
Authors: Yang Tianyi , White Marcus , Lipson-Smith Ruby , Shannon Michelle M. , Latifi Mehrnoush
Published: March 2024

Changing the physical environment of healthcare facilities can positively impact patient outcomes. Virtual reality (VR) offers the potential to understand how healthcare environment design impacts users’ perception, particularly among those with brain injuries like stroke, an area with limited research. In this study, our objective was to forge a new pathway in healthcare environment research by developing a comprehensive, six-module ‘user-centered’ design decision support approach, utilizing VR technology. This innovative method integrated patient engagement, architectural design principles, BIM prototyping, and a sophisticated VR user interface to produce realistic and immersive healthcare scenarios. Forty-four stroke survivors participated, experiencing 32 VR scenarios of in-patient bedrooms, followed by interactive in-VR questions and semi-structured interviews. The results of the approach proved to be comparatively efficient and feasible, provided a high level of immersion and presence for the participants, and effectively elicited extremely rich quantifiable response data, which revealed distinct environmental preferences. Our novel approach to understanding end-user responses to stroke rehabilitation architecture demonstrates potential to inform user-centered evidence-based design decisions in healthcare, to improve user experiences and health outcomes in other healthcare populations and environments.
Study on Axial Compression Performance of Corroded Reinforced Concrete Columns Strengthened by Concrete Canvas and Carbon Fiber Reinforced Plastic under Secondary Corrosion
Authors: Li Fengge , Chen Chen , Xiang Zehui
Published: March 2024

To investigate the effects of concrete canvas (CC) and carbon fiber reinforced plastic (CFRP) reinforcement on the mechanical properties of corroded reinforced concrete columns (compressive strength, flexure strength, strength of extension, and so on), 42 columns in four groups were designed and axial compression experiments were carried out. For the corroded reinforced concrete columns reinforced with CC and CFRP, the effects of initial corrosion rate (5%, 10%), secondary corrosion time (15 d, 30 d), number of CC layers (0, 1), and number of CFRP layers (1, 2, 3) on the failure morphology, load carrying capacity, and ductility of concrete columns were analyzed. The test results show that the properties of the single layer CC confined specimens are improved to a certain extent, and the ductility properties are enhanced. The properties of the CC–CFRP composite constrained specimens are greatly improved, the plastic deformation ability is enhanced, and the typical ductile damage characteristics are shown. The corrosion inhibition of CC for specimens with a theoretical corrosion rate lower than 20% showed an increasing trend, and the corrosion inhibition rate ranged from 23.0% to 31.2%. CC and CFRP restrain the concrete jointly, hindering the expansion inside the concrete, and the peak strain of the joint restraint specimen itself changes greatly, while the overall peak strain of the corrosion specimen is very small under the action of the joint steel bar. Finally, according to the existing peak stress–strain model and the experimental data in this paper, a peak stress–strain model suitable for corroded reinforced concrete columns is established. The established calculation model has a high accuracy, which provides a certain theoretical basis for subsequent research.
Flawed Institutional Structures: Project Managers Underutilized in Nigeria’s Construction Industry
Authors: Iroha Ebuka Valentine , Watanabe Tsunemi , Satoshi Tsuchiya
Published: March 2024

Many studies have been conducted on the poor performance of the construction industry. Nigeria’s construction industry has been linked to project delays and cost overruns, leading to many abandoned construction projects throughout the country. These issues are largely attributed to inadequate project management practices and the underutilization of project managers. To address these challenges, an institutional analysis was conducted to examine the factors, within the institutional framework of the Nigerian construction industry, that hinder the effective utilization of project managers and the implementation of project management practices. Data were collected from the previous literature and were supported by data collected through semi-structured interviews in Nigeria. The collected data were coded into a four-level framework for institutional analysis. This method was employed to analyze the interrelationships between the identified embedded factors, institutional laws and regulations, and construction organizations, and to understand how their influence results in the underutilization of project managers. Deviation analysis was conducted as an additional method to categorize the impacts of the embedded factors at each institutional level and to determine how these impacts contribute to the underutilization of project managers in the Nigerian construction industry (NCI). It was found that the system of the underutilization of project managers consists of two subsystems: underutilization and lowering commitment. For the former subsystem, corruption, political influence, religious and tribal discrimination, and organizational culture were found to adversely influence the institutional structure of the construction industry in Nigeria. These factors weaken the governance mechanisms within the industry, leading project managers to prioritize corrupt practices over project needs. The ineffectiveness of existing laws and regulations exacerbates the situation, supporting unfair working conditions and contributing to the underperformance of project managers. This result leads to development at the top of the latter subsystem, with minimal incentives and limited opportunities for career growth within construction organizations. The findings hold significant potential for addressing systemic issues in the Nigerian construction industry, particularly the underutilization of project managers and organizational support measures to improve project management practices and mitigate the adverse effects of corruption.
Histopathological Diagnosis of Primary Central Nervous System Lymphoma after Therapy with Corticosteroids or Anticoagulants
Authors: Feldheim Julia , Darkwah Oppong Marvin , Feldheim Jonas Alexander , Jabbarli Ramazan , Dammann Philipp , Uerschels Anne-Kathrin , Gembruch Oliver , Ahmadipour Yahya , Deuschl Cornelius , Junker Andreas , Sure Ulrich , Wrede Karsten Henning
Published: March 2024

In patients with primary central nervous system lymphoma (PCNSL), the choice of surgical strategy for histopathologic assessments is still controversial, particularly in terms of preoperative corticosteroid (CS) therapy. To provide further evidence for clinical decision-making, we retrospectively analyzed data from 148 consecutive patients who underwent surgery at our institution. Although patients treated with corticosteroids preoperatively were significantly more likely to require a second or third biopsy (p = 0.049), it was only necessary in less than 10% of the cases with preoperative (but discontinued) corticosteroid treatment. Surprisingly, diagnostic accuracy was significantly lower when patients were treated with anticoagulation or dual antiplatelet therapy (p = 0.015). Preoperative CSF sampling did not provide additional information but was associated with delayed surgery (p = 0.02). In conclusion, preoperative CS therapy can challenge the histological diagnosis of PCNSL. At the same time, our data suggest that preoperative CS treatment only presents a relative contraindication for early surgical intervention. If a definitive diagnosis cannot be made after the first surgical intervention, the timing of a repeat biopsy after the discontinuation of CS remains a case-by-case decision. The effect of anticoagulation and dual antiplatelet therapy on diagnostic accuracy might have been underestimated and should be examined closely in future investigations.
Radiomics-Based Classification of Tumor and Healthy Liver on Computed Tomography Images
Authors: Zossou Vincent-Béni Sèna , Gnangnon Freddy Houéhanou Rodrigue , Biaou Olivier , de Vathaire Florent , Allodji Rodrigue S. , Ezin Eugène C.
Published: March 2024

Liver malignancies, particularly hepatocellular carcinoma and metastasis, stand as prominent contributors to cancer mortality. Much of the data from abdominal computed tomography images remain underused by radiologists. This study explores the application of machine learning in differentiating tumor tissue from healthy liver tissue using radiomics features. Preoperative contrast-enhanced images of 94 patients were used. A total of 1686 features classified as first-order, second-order, higher-order, and shape statistics were extracted from the regions of interest of each patient’s imaging data. Then, the variance threshold, the selection of statistically significant variables using the Student’s t-test, and lasso regression were used for feature selection. Six classifiers were used to identify tumor and non-tumor liver tissue, including random forest, support vector machines, naive Bayes, adaptive boosting, extreme gradient boosting, and logistic regression. Grid search was used as a hyperparameter tuning technique, and a 10-fold cross-validation procedure was applied. The area under the receiver operating curve (AUROC) assessed the performance. The AUROC scores varied from 0.5929 to 0.9268, with naive Bayes achieving the best score. The radiomics features extracted were classified with a good score, and the radiomics signature enabled a prognostic biomarker for hepatic tumor screening.
Pretreatment Circulating HPV16 DNA Viral Load Predicts Risk of Distant Metastasis in Patients with HPV16-Positive Oropharyngeal Cancer
Authors: Mazurek Agnieszka Maria , Jabłońska Iwona , Kentnowski Marek , Kacorzyk Urszula , Śnietura Mirosław , Rutkowski Tomasz Wojciech
Published: March 2024

Background: There are definite reasons to implement molecular diagnostics based on the measurement of human papillomavirus (HPV) DNA in liquid biopsy into clinical practice. It is a quick, repeatable, and health-safe test for cancer biomarkers in the blood. In this study, we investigated whether the circulating tumor-related HPV16 (ctHPV16) viral load (VL) in patients with oropharyngeal squamous cell carcinoma (OPSCC) was important for determining the risk of locoregional recurrence-free survival (LRFS), metastasis-free survival (MFS), and overall survival (OS). Methods: This study included 91 patients with ctHPV16-positive OPSCC who had been treated with radical radiotherapy and chemotherapy. The VL was measured using quantitative PCR (qPCR) and a probe specific for HPV16. Based on 10 years of follow-up, the 2-, 3-, 5-, and 9-year LRFS, MFS, and OS were estimated. Results: The 5-year actuarial LRFS, MFS, and OS rates of patients with ctHPV16-positive/OPSCC were 88%, 90%, and 81%, respectively. The VL was significantly higher in patients who subsequently developed distant metastases (DM) than in those who did not (VL 4.09 vs. 3.25; p = 0.009). In a Cox proportional hazards regression model for MFS, a higher ctHPV16 VL appeared to be a significant independent prognostic factor for the occurrence of DM (HR 2.22, p = 0.015). The ROC curve revealed a cutoff value of 3.556 for VL (p = 0.00001). Conclusions: A high VL before treatment indicates patients with a significant risk of DM, and should be used in OPSCC treatment stratification.
Mezigdomide—A Novel Cereblon E3 Ligase Modulator under Investigation in Relapsed/Refractory Multiple Myeloma
Authors: Hartley-Brown Monique A. , Mo Clifton C. , Nadeem Omar , Midha Shonali , Laubach Jacob P. , Richardson Paul G.
Published: March 2024

Mezigomide is an oral cereblon E3 ligase modulator (CELMoD) that is under clinical investigation in patients with relapsed/refractory (RR) multiple myeloma (MM). Like other CELMoD compounds, mezigdomide acts by altering the conformation of cereblon within the cullin 4A ring ligase–cereblon (CRL4CRBN) E3 ubiquitin ligase complex, thereby recruiting novel protein substrates for selective proteasomal degradation. These include two critical lymphoid transcription factors, Ikaros family zinc finger proteins 1 and 3 (IKZF1 and IKZF3), also known as Ikaros and Aiolos, which have important roles in the development and differentiation of hematopoietic cells, in MM pathobiology, and in suppressing the expression of interferon-stimulating genes and T-cell stimulation. Among the CELMoDs, mezigdomide has the greatest cereblon-binding potency, plus the greatest potency for the degradation of Ikaros and Aiolos and subsequent downstream antimyeloma effects. Preclinical studies of mezigdomide have demonstrated its anti-proliferative and apoptotic effects in MM, along with its immune-stimulatory effects and its synergistic activity with other antimyeloma agents, including in lenalidomide-/pomalidomide-resistant MM cell lines and mouse xenograft models. Early-phase clinical trial data indicate notable activity in heavily pretreated patients with RRMM, including those with triple-class-refractory disease, together with a tolerable and manageable safety profile. This review summarizes current preclinical and clinical findings with mezigdomide and its potential future roles in the treatment of MM.