bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural and Spectroscopic Effects of Li+ Substitution for Na+ in LixNa1−xCaLa0.5Er0.05Yb0.45(MoO4)3 Upconversion Scheelite-Type Phosphors
Authors: Lim Chang Sung , Aleksandrovsky Aleksandr , Molokeev Maxim , Oreshonkov Aleksandr , Atuchin Victor
Published: February 2023

New triple molybdates LixNa1−xCaLa0.5(MoO4)3:Er3+0.05/Yb3+0.45 (x = 0, 0.05, 0.1, 0.2, 0.3) were manufactured successfully using the microwave-assisted sol-gel-based technique (MAS). Their room-temperature crystal structures were determined in space group I41/a by Rietveld analysis. The compounds were found to have a scheelite-type structure. In Li-substituted samples, the sites of big cations were occupied by a mixture of (Li, Na, La, Er, Yb) ions, which provided a linear cell volume decrease with the Li content increase. The increased upconversion (UC) efficiency and Raman spectroscopic properties of the phosphors were discussed in detail. The mechanism of optimization of upconversion luminescence upon Li content variation was shown to be due to the control of excitation/energy transfer channel, while the control of luminescence channels played a minor role. The UC luminescence maximized at lithium content x = 0.05. The mechanism of UC optimization was shown to be due to the control of excitation/energy transfer channel, while the control of luminescence channels played a minor role. Over the whole spectral range, the Raman spectra of LixNa1−xCaLa0.5(MoO4)3 doped with Er3+ and Yb3+ ions were totally superimposed with the luminescence signal of Er3+ ions, and increasing the Li+ content resulted in the difference of Er3+ multiple intensity. The density functional theory calculations with the account for the structural disorder in the system of Li, Na, Ca, La, Er and Yb ions revealed the bandgap variation from 3.99 to 4.137 eV due to the changing of Li content. It was found that the direct electronic transition energy was close to the indirect one for all compounds. The determined chromaticity points (ICP) of the LiNaCaLa(MoO4)3:Er3+,Yb3+ phosphors were in good relation to the equal-energy point in the standard CIE (Commission Internationale de L’Eclairage) coordinates.
Stereotactic Radiation for Oligometastatic and Oligoprogressive Stage IV Breast Cancer: A Case-Based Review
Authors: Freedman Gary M. , Jones Joshua A. , Taunk Neil K.
Published: February 2023

For decades, the distant progression of breast cancer has been the purview of systemic therapy alone or with low to moderate-dose radiation therapy intended for the palliation of symptomatic metastases. However, for decades there have been anecdotes of long-term disease-free survival with more aggressive local treatment of one or more metastases. The hypothesis of oligometastases is that the treatment of a clinically limited number of distant metastases can change the natural history of stage IV breast cancer. The advance in the technology of stereotactic body radiation (SBRT) has made it more possible to offer a non-invasive, yet potentially disease-modifying, metastases-directed ablative treatment in place of surgery or a palliative radiation regimen. Although there are promising local control and survival outcomes in phase I/II trials, there is still a lack of phase III evidence of ablative SBRT results showing any change in the natural history of metastatic breast cancer. Limited oligometastases may call for an ablative approach with SBRT when definitive long-term local control is needed for the best palliation against symptomatic progression in challenging locations. Some oligometastases that have progression on a certain systemic regimen, while others remain stable or in remission, may also be treated with SBRT in the hopes of prolonging the use of that regimen. Whether SBRT should represent the standard management for stage IV breast cancer of a limited number or of limited progression requires confirmation by phase III data. This review will discuss the data from key clinical trials as it applies to decision making in typical clinical cases considered for potentially ablative SBRT for oligometastases or oligoprogression.
Is a Modified Actin the Key to Toxin Resistance in the Nudibranch Chromodoris? A Biochemical and Molecular Approach
Authors: Hertzer Cora , Undap Nani , Papu Adelfia , Bhandari Dhaka , Aatz Stefan , Kehraus Stefan , Kaligis Fontje , Bara Robert , Schäberle Till , Wägele Heike , König Gabriele
Published: February 2023

Five Chromodoris species from North Sulawesi, Indonesia, were investigated for their sequestration of marine natural products. The cytotoxic 2-thiazolidinone macrolide latrunculin A (LatA) was the major metabolite in all examined Chromodoris species, as well as in one of the associated sponges Cacospongia mycofijiensis (Kakou, Crews & Bakus, 1987), supporting a dietary origin of LatA. Furthermore, LatA was secreted with the mucus trail, suggesting a possible use in short-range chemical communication. MALDI MS-Imaging revealed an accumulation of LatA throughout the mantle tissue, mucus glands, and especially in vacuoles of the mantle dermal formations (MDFs). Cytotoxicity of the isolated LatA was tested in HEK-293 cells, confirming that LatA targets the actin cytoskeleton. In vivo toxicity experiments with the sacoglossan Elysia viridis (Montagu, 1804) showed 100% mortality, but 100% survival of Chromodoris specimens, demonstrating resistance to LatA. A novel actin isoform was detected in all investigated Chromodoris species with two amino acid substitutions at the ‘nucleotide binding’ cleft, the binding site of LatA. These are suggested to cause insensitivity against LatA, thus enabling the storage of the toxin within the body for the slugs’ own defense.
Molecular Diagnosis and Cancer Prognosis—A Concise Review
Authors: Thenrajan Thatchanamoorthy , Alwarappan Subbiah , Wilson Jeyaraj
Published: February 2023

Cancer is a complicated disease. Globally, it is one of the major causes for morbidity and mortality. A critical challenge associated with it is the difficulty to accurately diagnose it at an early stage. The malignancy due to multistage and heterogeneity that result from genetic and epigenetic modifications poses critical challenge to diagnose and monitor the progress at an early stage. Current diagnostic techniques normally suggest invasive biopsy procedure that can cause further infections and bleeding. Therefore, noninvasive diagnostic methods with high accuracy, safety and earliest detection are the needs of the hour. Herein, we provide a detailed review on the advanced methodologies and protocols developed for the detection of cancer biomarkers based on proteins, nucleic acids and extracellular vesicles. Furthermore, existing challenges and the improvements essential for the rapid, sensitive and noninvasive detection have also been discussed.
The Role of Genetic Testing in Patients with Heritable Thoracic Aortic Diseases
Authors: Monda Emanuele , Lioncino Michele , Verrillo Federica , Rubino Marta , Caiazza Martina , Mauriello Alfredo , Guarnaccia Natale , Fusco Adelaide , Cirillo Annapaola , Covino Simona , Altobelli Ippolita , Diana Gaetano , Palmiero Giuseppe , Dongiglio Francesca , Natale Francesco , Cesaro Arturo , Bossone Eduardo , Russo Maria Giovanna , Calabrò Paolo , Limongelli Giuseppe
Published: February 2023

Heritable thoracic aortic disease (HTAD) is a term used to define a large group of disorders characterized by the occurrence of aortic events, mainly represented by aneurysm or dissection. These events generally involve the ascending aorta, although the involvement of other districts of the aorta or peripheral vessels may occur. HTAD can be classified as non-syndromic if the disorder is limited to the aorta, and syndromic when associated with extra-aortic features. About 20–25% of patients with non-syndromic HTAD exhibit a family history of aortic disease. Thus, a careful clinical evaluation of the proband and the first-degree family members is required to differentiate familial and sporadic cases. Genetic testing is essential since it allows confirmation of the etiological diagnosis of HTAD (particularly in patients with a significant family history) and may guide family screening. In addition, genetic diagnosis significantly impacts patients’ management since the different conditions significantly differ with respect to natural history and treatment strategies. The prognosis in all HTADs is determined by the progressive dilation of the aorta, potentially leading to acute aortic events, such as dissection or rupture. Moreover, the prognosis varies according to the underlying genetic mutations. This review aims to describe the clinical characteristics and natural history of the most common HTADs, with particular emphasis on the role of genetic testing in risk stratification and management.
IoT-Enabled Classification of Echocardiogram Images for Cardiovascular Disease Risk Prediction with Pre-Trained Recurrent Convolutional Neural Networks
Authors: Balakrishnan Chitra , Ambeth Kumar V. D.
Published: February 2023

Cardiovascular diseases currently present a key health concern, contributing to an increase in death rates worldwide. In this phase of increasing mortality rates, healthcare represents a major field of research, and the knowledge acquired from this analysis of health information will assist in the early identification of disease. The retrieval of medical information is becoming increasingly important to make an early diagnosis and provide timely treatment. Medical image segmentation and classification is an emerging field of research in medical image processing. In this research, the data collected from an Internet of Things (IoT)-based device, the health records of patients, and echocardiogram images are considered. The images are pre-processed and segmented, and then further processed using deep learning techniques for classification as well as forecasting the risk of heart disease. Segmentation is attained via fuzzy C-means clustering (FCM) and classification using a pretrained recurrent neural network (PRCNN). Based on the findings, the proposed approach achieves 99.5% accuracy, which is higher than the current state-of-the-art techniques.
Diagnostic and Prognostic Roles of C-Reactive Protein, Procalcitonin, and Presepsin in Acute Kidney Injury Patients Initiating Continuous Renal Replacement Therapy
Authors: Han Suyeon , Kim Moo-Jun , Ko Ho-Joon , Lee Eu-Jin , Kim Hae-Ri , Jeon Jae-Wan , Ham Young-Rok , Na Ki-Ryang , Lee Kang-Wook , Lee Song-I. , Choi Dae-Eun , Park Heyrim
Published: February 2023

For reducing the high mortality rate of severe acute kidney injury (AKI) patients initiating continuous renal replacement therapy (CRRT), diagnosing sepsis and predicting prognosis are essential. However, with reduced renal function, biomarkers for diagnosing sepsis and predicting prognosis are unclear. This study aimed to assess whether C-reactive protein (CRP), procalcitonin, and presepsin could be used to diagnose sepsis and predict mortality in patients with impaired renal function initiating CRRT. This was a single-center, retrospective study involving 127 patients who initiated CRRT. Patients were divided into sepsis and non-sepsis groups according to the SEPSIS-3 criteria. Of the 127 patients, 90 were in the sepsis group and 37 were in the non-sepsis group. Cox regression analysis was performed to determine the association between the biomarkers (CRP, procalcitonin, and presepsin) and survival. CRP and procalcitonin were superior to presepsin for diagnosing sepsis. Presepsin was closely related to the estimated glomerular filtration rate (eGFR) (r = −0.251, p = 0.004). These biomarkers were also evaluated as prognostic markers. Procalcitonin levels ≥3 ng/mL and CRP levels ≥31 mg/L were associated with higher all-cause mortality using Kaplan–Meier curve analysis. (log-rank test p = 0.017 and p = 0.014, respectively). In addition, procalcitonin levels ≥3 ng/mL and CRP levels ≥31 mg/L were associated with higher mortality in univariate Cox proportional hazards model analysis. In conclusion, a higher lactic acid, sequential organ failure assessment score, eGFR, and a lower albumin level have prognostic value to predict mortality in patients with sepsis initiating CRRT. Moreover, among these biomarkers, procalcitonin and CRP are significant factors for predicting the survival of AKI patients with sepsis-initiating CRRT.
Auto-Detection of Motion Artifacts on CT Pulmonary Angiograms with a Physician-Trained AI Algorithm
Authors: Dasegowda Giridhar , Bizzo Bernardo C. , Kaviani Parisa , Karout Lina , Ebrahimian Shadi , Digumarthy Subba R. , Neumark Nir , Hillis James M. , Kalra Mannudeep K. , Dreyer Keith J.
Published: February 2023

Purpose: Motion-impaired CT images can result in limited or suboptimal diagnostic interpretation (with missed or miscalled lesions) and patient recall. We trained and tested an artificial intelligence (AI) model for identifying substantial motion artifacts on CT pulmonary angiography (CTPA) that have a negative impact on diagnostic interpretation. Methods: With IRB approval and HIPAA compliance, we queried our multicenter radiology report database (mPower, Nuance) for CTPA reports between July 2015 and March 2022 for the following terms: “motion artifacts”, “respiratory motion”, “technically inadequate”, and “suboptimal” or “limited exam”. All CTPA reports were from two quaternary (Site A, n = 335; B, n = 259) and a community (C, n = 199) healthcare sites. A thoracic radiologist reviewed CT images of all positive hits for motion artifacts (present or absent) and their severity (no diagnostic effect or major diagnostic impairment). Coronal multiplanar images from 793 CTPA exams were de-identified and exported offline into an AI model building prototype (Cognex Vision Pro, Cognex Corporation) to train an AI model to perform two-class classification (“motion” or “no motion”) with data from the three sites (70% training dataset, n = 554; 30% validation dataset, n = 239). Separately, data from Site A and Site C were used for training and validating; testing was performed on the Site B CTPA exams. A five-fold repeated cross-validation was performed to evaluate the model performance with accuracy and receiver operating characteristics analysis (ROC). Results: Among the CTPA images from 793 patients (mean age 63 ± 17 years; 391 males, 402 females), 372 had no motion artifacts, and 421 had substantial motion artifacts. The statistics for the average performance of the AI model after five-fold repeated cross-validation for the two-class classification included 94% sensitivity, 91% specificity, 93% accuracy, and 0.93 area under the ROC curve (AUC: 95% CI 0.89–0.97). Conclusion: The AI model used in this study can successfully identify CTPA exams with diagnostic interpretation limiting motion artifacts in multicenter training and test datasets. Clinical relevance: The AI model used in the study can help alert technologists about the presence of substantial motion artifacts on CTPA, where a repeat image acquisition can help salvage diagnostic information.
CSF Aβ42 and Aβ42/Aβ40 Ratio in Alzheimer’s Disease and Frontotemporal Dementias
Authors: Constantinides Vasilios C. , Paraskevas George P. , Boufidou Fotini , Bourbouli Mara , Pyrgelis Efstratios-Stylianos , Stefanis Leonidas , Kapaki Elisabeth
Published: February 2023

Background: Alzheimer’s disease dementia (ADD) may manifest with atypical phenotypes, resembling behavioral variant frontotemporal dementia (bvFTD) and corticobasal syndrome (CBS), phenotypes which typically have an underlying frontotemporal lobar degeneration with tau proteinopathy (FTLD-tau), such as Pick’s disease, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), or FTLD with TDP-43 proteinopathy (FTLD-TDP). CSF biomarkers total and phosphorylated tau (τT and τP-181), and amyloid beta with 42 and 40 amino acids (Aβ42 and Aβ40) are biomarkers of AD pathology. The primary aim of this study was to compare the diagnostic accuracy of Aβ42 to Aβ42/Aβ40 ratio in: (a) differentiating ADD vs. frontotemporal dementias; (b) patients with AD pathology vs. non-AD pathologies; (c) compare biomarker ratios and composite markers to single CSF biomarkers in the differentiation of AD from FTD; Methods: In total, 263 subjects were included (ADD: n = 98; bvFTD: n = 49; PSP: n = 50; CBD: n = 45; controls: n = 21). CSF biomarkers were measured by commercially available ELISAs (EUROIMMUN). Multiple biomarker ratios (Aβ42/Aβ40; τT/τP-181; τT/Aβ42; τP-181/Aβ42) and composite markers (t-tau: τT/(Aβ42/Aβ40); p-tau: τP-181/(Aβ42/Aβ40) were calculated. ROC curve analysis was performed to compare AUCs of Aβ42 and Aβ42/Aβ40 ratio and relevant composite markers between ADD and FTD, as defined clinically. BIOMARKAPD/ABSI criteria (abnormal τT, τP-181 Aβ42, and Aβ42/Aβ40 ratio) were used to re-classify all patients into AD pathology vs. non-AD pathologies, and ROC curve analysis was repeated to compare Aβ42 and Aβ42/Aβ40; Results: Aβ42 did not differ from Aβ42/Aβ40 ratio in the differentiation of ADD from FTD (AUCs 0.752 and 0.788 respectively; p = 0.212). The τT/Aβ42 ratio provided maximal discrimination between ADD and FTD (AUC:0.893; sensitivity 88.8%, specificity 80%). BIOMARKAPD/ABSI criteria classified 60 patients as having AD pathology and 211 as non-AD. A total of 22 had discrepant results and were excluded. Aβ42/Aβ40 ratio was superior to Aβ42 in the differentiation of AD pathology from non-AD pathology (AUCs: 0.939 and 0.831, respectively; p < 0.001). In general, biomarker ratios and composite markers were superior to single CSF biomarkers in both analyses. Conclusions: Aβ42/Aβ40 ratio is superior to Aβ42 in identifying AD pathology, irrespective of the clinical phenotype. CSF biomarker ratios and composite markers provide higher diagnostic accuracy compared to single CSF biomarkers.
Pressure Pain Thresholds and Central Sensitization in Relation to Psychosocial Predictors of Chronicity in Low Back Pain
Authors: Steinmetz Anke , Hacke Franziska , Delank Karl-Stefan
Published: February 2023

(1) Background: Peripheral, as well as central, sensitization have been described in chronic low back pain (cLBP). The purpose of this study is to investigate the influence of psychosocial factors on the development of central sensitization. (2) Methods: This prospective study investigated local and peripheral pressure pain thresholds and their dependence on psychosocial risk factors in patients with cLBP receiving inpatient multimodal pain therapy. Psychosocial factors were assessed using the Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ). (3) Results: A total of 90 patients were included in the study, 61 (75.4% women, 24.6% men) of whom had significant psychosocial risk factors. The control group consisted of 29 patients (62.1% women, 37.9% men). At baseline, patients with psychosocial risk factors showed significantly lower local and peripheral pressure pain thresholds, suggesting central sensitization, compared to the control group. Sleep quality, measured by the Pittsburgh Sleep Quality Index (PSQI), was also correlated with altered PPTs. After multimodal therapy, all participants reported increased local pain thresholds compared to at admission, independent of psychosocial chronification factors. (4) Conclusions: Psychosocial chronicity factors measured using the ÖMPSQ have a significant influence on pain sensitization in cLBP. A 14-day multimodal pain therapy increased local, but not peripheral, pressure pain thresholds.
Management of Non-Melanoma Skin Cancer: Radiologists Challenging and Risk Assessment
Authors: Russo Gaetano Maria , Russo Anna , Urraro Fabrizio , Cioce Fabrizio , Gallo Luigi , Belfiore Maria Paola , Sangiovanni Angelo , Napolitano Stefania , Troiani Teresa , Verolino Pasquale , Sica Antonello , Brancaccio Gabriella , Briatico Giulia , Nardone Valerio , Reginelli Alfonso
Published: February 2023

Basal cell carcinoma, squamous cell carcinoma, and Merkel cell carcinoma are the three main types of nonmelanoma skin cancers and their rates of occurrence and mortality have been steadily rising over the past few decades. For radiologists, it is still difficult to treat patients with advanced nonmelanoma skin cancer. Nonmelanoma skin cancer patients would benefit greatly from an improved diagnostic imaging-based risk stratification and staging method that takes into account patient characteristics. The risk is especially elevated among those who previously received systemic treatment or phototherapy. Systemic treatments, including biologic therapies and methotrexate (MTX), are effective in managing immune-mediated diseases; however, they may increase susceptibility to NMSC due to immunosuppression or other factors. Risk stratification and staging tools are crucial in treatment planning and prognostic evaluation. PET/CT appears more sensitive and superior to CT and MRI for nodal and distant metastasis as well as in surveillance after surgery. The patient treatment response improved with advent and utilization of immunotherapy and different immune-specific criteria are established to standardized evaluation criteria of clinical trials but none of them have been utilized routinely with immunotherapy. The advent of immunotherapy has also arisen new critical issues for radiologists, such as atypical response pattern, pseudo-progression, as well as immune-related adverse events that require early identification to optimize and improve patient prognosis and management. It is important for radiologists to have knowledge of the radiologic features site of the tumor, clinical stage, histological subtype, and any high-risk features to assess immunotherapy treatment response and immune-related adverse events.
A Novel Proposal for Deep Learning-Based Diabetes Prediction: Converting Clinical Data to Image Data
Authors: Aslan Muhammet Fatih , Sabanci Kadir
Published: February 2023

Diabetes, one of the most common diseases worldwide, has become an increasingly global threat to humans in recent years. However, early detection of diabetes greatly inhibits the progression of the disease. This study proposes a new method based on deep learning for the early detection of diabetes. Like many other medical data, the PIMA dataset used in the study contains only numerical values. In this sense, the application of popular convolutional neural network (CNN) models to such data are limited. This study converts numerical data into images based on the feature importance to use the robust representation of CNN models in early diabetes diagnosis. Three different classification strategies are then applied to the resulting diabetes image data. In the first, diabetes images are fed into the ResNet18 and ResNet50 CNN models. In the second, deep features of the ResNet models are fused and classified with support vector machines (SVM). In the last approach, the selected fusion features are classified by SVM. The results demonstrate the robustness of diabetes images in the early diagnosis of diabetes.
Delay of Dental Care: An Exploratory Study of Procrastination, Dental Attendance, and Self-Reported Oral Health
Authors: Steinvik Lene M. , Svartdal Frode , Johnsen Jan-Are K.
Published: February 2023

Delay of dental care is a problem for dental public health. The present study explored the relationship between procrastination and dental attendance, focusing on delay in seeking dental care. This hypothetical relation was compared to other avoidance-related factors affecting dental attendance. In addition, an inquiry into the reasons for delaying dental care was conducted. Students (n = 164) answered an internet-based questionnaire on socio-demographic factors, dental health, dental attendance, delay of dental care, reasons for the delay, procrastination (IPS), dental anxiety (MDAS), perceived stress (PSS) and oral health self-efficacy (OHSES). The study found no significant relation between procrastination and delay in dental care. However, procrastination was related differently to past, present, and future dental attendance and seemed to relate to oral health behavior. Delay of dental care was associated with higher dental anxiety and lower oral health self-efficacy. The cost of dental care was the most frequently given reason for the delay of dental care. Further research on the delay of dental care and dental attendance is warranted in understanding the behavior, implementing interventions, and improving the utilization of public dental care.
Trajectory Planning for Multiple UAVs and Hierarchical Collision Avoidance Based on Nonlinear Kalman Filters
Authors: Hematulin Warunyu , Kamsing Patcharin , Torteeka Peerapong , Somjit Thanaporn , Phisannupawong Thaweerath , Jarawan Tanatthep
Published: February 2023

Fully autonomous trajectory planning for multiple unmanned aerial vehicles (UAVs) is significant for building the next generation of the logistics industry without human control. This paper presents a method to enable multiple UAVs to fly in the same trajectory without collision. It benefits several applications, such as smart cities and transfer goods, during the COVID-19 pandemic. Different types of nonlinear state estimation are deployed to test the position estimation of drones by treating the information from AirSim as offline dynamic data. The obtained global positioning system sensor data and magnetometer sensor data are determined as the measurement model. The experiment in the simulation is separated into (1) the localization state, (2) the rendezvous state, in which the proposed rendezvous strategy is presented by using the relation between velocity and displacement through the setting area, and (3) the full mission state, which combines both the localization and rendezvous states. The localization state results show the best RMSE in the case of full GPS available at 0.21477 m and 0.25842 m in the case of a GPS outage during a period of time by implementing the ensemble Kalman filter. Similarly, the ensemble Kalman filter performs well with an RMSE of 0.5112414 m in the rendezvous state and demonstrates exceptional performance in the full mission state. Moreover, the experiment is implemented in a real-world situation with some basic drone kits as proof that the proposed rendezvous strategy can truly operate.
A Pedestrian Detection Network Model Based on Improved YOLOv5
Authors: Li Ming-Lun , Sun Guo-Bing , Yu Jia-Xiang
Published: February 2023

Advanced object detection methods always face high algorithmic complexity or low accuracy when used in pedestrian target detection for the autonomous driving system. This paper proposes a lightweight pedestrian detection approach called the YOLOv5s-G2 network to address these issues. We apply Ghost and GhostC3 modules in the YOLOv5s-G2 network to minimize computational cost during feature extraction while keeping the network’s capability of extracting features intact. The YOLOv5s-G2 network improves feature extraction accuracy by incorporating the Global Attention Mechanism (GAM) module. This application can extract relevant information for pedestrian target identification tasks and suppress irrelevant information, improving the unidentified problem of occluded and small targets by replacing the GIoU loss function used in the bounding box regression with the α-CIoU loss function. The YOLOv5s-G2 network is evaluated on the WiderPerson dataset to ensure its efficacy. Our proposed YOLOv5s-G2 network offers a 1.0% increase in detection accuracy and a 13.2% decrease in Floating Point Operations (FLOPs) compared to the existing YOLOv5s network. As a result, the YOLOv5s-G2 network is preferable for pedestrian identification as it is both more lightweight and more accurate.
Analysis and Optimization of a General Linking Matrix for JSCC Scheme Based on Double LDPC Codes
Authors: Chen Qiwang , Xu Zhiping , Wu Huihui , Cai Guofa
Published: February 2023

A key component of the joint source-channel coding (JSCC) scheme based on double low-density parity-check (D-LDPC) codes is the introduction of a linking matrix between the source LDPC code and channel LDPC code, by which the decoding information including the source redundancy and channel state information can be transferred iteratively. However, the linking matrix is a fixed one-to-one mapping, i.e., an identity matrix in a conventional D-LDPC code system, which may not take full advantage of the decoding information. Therefore, this paper introduces a general linking matrix, i.e., a non-identity linking matrix, connecting the check nodes (CNs) of the source LDPC code and the variable nodes (VNs) of the channel LDPC code. Further, the encoding and decoding algorithms of the proposed D-LDPC coding system are generalized. A joint extrinsic information transfer (JEXIT) algorithm is derived for calculating the decoding threshold of the proposed system with a general linking matrix. In addition, several general linking matrices are optimized with the aid of the JEXIT algorithm. Finally, the simulation results demonstrate the superiority of the proposed D-LDPC coding system with general linking matrices.
Testing the Validity of the Quantity Theory of Money on Sectoral Data: Non-Linear Evidence from South Africa
Authors: Mndebele Siyabonga , Tewari Devi Datt , Ilesanmi Kehinde Damilola
Published: February 2023

Purpose: The purpose of this study is to test the validity of the quantity theory of money (QTM) on South African sectoral data. The rationale of this study and its necessity for South Africa as the case study is that, although aggregate inflation may lie within the target range, inflation at a sectoral level, particularly in the food and transport sector, is still a matter of concern in South Africa. Methodology/approach: This study employed the Non-linear Autoregressive Distributed Lagged model (NARDL) to assess potential asymmetries in the effect of money supply to differentiate between the effects of contractional and expansional episodes on inflation at the sectoral level. Quarterly time series data spanning from 2002Q2 to 2021Q2 was utilised for the estimation. Ultimately, the causal effect amongst the variables is examined by employing the Pairwise Granger Causality test. Findings: The results suggest that in the short run, the effect of monetary policy shocks is very weak. On the other hand, in the long run, both negative and positive shocks in the money supply push inflation at the sectoral level in the opposite directions, and positive shocks (expansionary monetary policy) have a greater effect than negative shocks, which renders the QTM invalid in South Africa. The sectoral response was found to be heterogeneous in the long run, and this was also backed by the results of the Granger Causality test and the dynamic multipliers. Asymmetry in the effect of the money supply is assessed in some of the sectors only in the long run. Practical implications: Based on the results, this study confirms great discrepancies in sectoral responses. Therefore, aggregate inflation may not be a good indicator of the inflation path in South Africa, as it may underestimate sectoral variations. Originality/value: The originality of this study lies on testing the validity of the QTM on inflation at the sectoral level in the South African context using a non-linear approach to assess potential asymmetry between the effects of expansionary and contractionary episodes of monetary policy shocks.
Mentoring Postsecondary Students with Intellectual Disabilities: Faculty and Staff Mentor Perspectives
Authors: Heron Laura M. , Agarwal Rumi , Burke Shanna L.
Published: February 2023

As the number of inclusive postsecondary education (IPSE) programs in the United States increases, a greater number of young adults with an intellectual disability (ID) are attending college. To ensure students with IDs have the same opportunity to succeed in the postsecondary education environment as their peers without disabilities, it is critical that research is conducted to explore the support mechanisms that contribute to successful outcomes for this population. To address existing gaps in the literature, the present study involved a qualitative investigation of the experiences of faculty and staff mentors who formally mentored students with ID over the course of one academic year. Four themes provided unique insights into (1) the activities that were undertaken by faculty and staff mentors to help students meet their academic, employment, independent living, and personal development goals; (2) common challenge areas related to the mentoring program and dyad partnerships; (3) areas of student growth; and, finally, (4) how impactful the mentoring experience was for faculty and staff mentors. By providing a timely and novel contribution to the mentoring literature, the findings from this study can inform the development of mentoring programs within IPSE settings that will promote positive postsecondary outcomes for students with IDs.
Web-Conferencing Systems (WCS): Individual, Group or Full-Class Teacher Education Format?
Authors: Nagovitsyn Roman Sergeevich , Valeeva Roza Alexeevna , Latypova Liliia Agzamovna
Published: February 2023

Web-conferencing systems (WCS) are gaining momentum in the implementation of distance learning for young people, especially during and after the spread of COVID-19. In this regard, it seems urgent to identify technologies for distance learning education that correspond to modern teacher education to the fullest and are effective, user-friendly and convenient for all subjects of the educational process. This experiment revealed the most popular formats of communication for long-distance students in the implementation of future teachers’ professional training by means of video conferencing on the Zoom platform. The analysis of the implementation of various formats of interaction based on the questionnaire of research participants demonstrated a positive trend in the level of user expectations from educational interaction, technical preferences and students’ attitude to distance learning by means of web-conferencing. The implementation of distance learning using web-conferencing in group and full-class formats of interaction made it possible to increase social presence through the interactive cooperation of the students with each other and with the teacher in the educational and social context. These formats enhance social and cognitive interaction, thus developing key competencies in future teachers related to the ability to implement effective communication when working in a teaching team. It causes an increase in educational efficiency level and is critical, since it allows information to be obtained through interaction with each other and with the content presented on the screen. Thereby, educational distance communication with the help of web-conferencing should be considered as a new form of social and educational communication in the implementation of professional training rather than as a technical non-traditional tool for teacher education.
Digital University: A Study of Students’ Experiences and Expectations in the Post-COVID Era
Authors: Chodak Katarzyna , Ciesielski Piotr , Grysztar Dominika , Kurasińska Amelia , Makeeva Olga , Prygiel Paulina , Żabicki Michał
Published: February 2023

In 2020, the education process at universities started to be redefined, parting with the traditional face-to-face form. The article presents the conclusions of exploratory study conducted at the Jagiellonian University in Kraków (Poland) on the students’ experiences of remote education as well as their expectations for the future. The study was conducted in the form of an online survey addressed to the entire population of science recipients at the Jagiellonian University, around 800 respondents completed the questionnaire. The obtained results show that most students rate remote education relatively high, although there are statistically significant differences in specific questions (e.g., theoretical classes are more suitable for online learning than practical classes). The authors paid special attention to the differences in the attitudes of students depending on their characteristics, the approach to remote education differs, in particular, depending on the gender and field of study. Students of social and humanist faculties view remote education most positively, and science students opinions are mostly negative. It has also been observed that some students are uncritically satisfied with most aspects of distance learning (the so-called “Tiggers”), while others are strong supporters of face-to-face education, reluctant to accept any changes (so-called “Eeyores”), so regardless of the scope of pro-quality activities undertaken, both criticism and praise of remote education can be expected. The obtained results open the field for further studies that would allow to confirm the covariance of multidimensional characteristics of students and their attitudes towards the digital university, and on the other hand would allow planning activities aimed at different and perhaps mutually contradictory expectations of the recipients of education.
Social–Emotional Skills Correlate with Reading Ability among Typically Developing Readers: A Meta-Analysis
Authors: Yu Liyan , Yu Jane Jie , Tong Xiuhong
Published: February 2023

This meta-analysis examined the correlation between social–emotional skills and reading ability and identified possible moderators by synthesizing 285 correlations from 37 studies among 38 samples with 28,404 participants. Results showed a significantly positive correlation between social–emotional skills and reading ability among typically developing readers, r = 0.23, 95% CI [0.19, 0.28]. The moderation analysis revealed that, after controlling for types of social–emotional skills and grade level, the correlation between social–emotional skills and reading ability was moderated by the levels of reading (i.e., word reading vs. reading comprehension), β = 0.07, 95% CI [0.02, 0.11], t = 5.03, p < 0.05. Specifically, social–emotional skills had a significantly stronger correlation with reading comprehension than it with word reading. This work provides support for the lattice model of reading, suggesting that future research efforts are needed to examine the underlying mechanisms between social–emotional skills and reading ability.
Prolonged Grief Disorder and Symptoms of Anxiety and Depression among Bereaved Family Caregivers in the Context of Palliative Home Care
Authors: Sardella Alberto , Musetti Alessandro , Caponnetto Pasquale , Quattropani Maria C. , Lenzo Vittorio
Published: February 2023

Background: This study aimed to investigate the prevalence and the psychological comorbidity of PGD among bereaved family caregivers of palliative care cancer patients. We also examined the discriminant validity of two simple and reliable tools in correctly categorized individuals with PGD. Methods: A cross-sectional study was conducted with 157 bereaved participants (77.1% females, mean age = 43.50 ± 14.04 years, mean time since the loss = 3.59 years) recruited from three palliative home care services. These participants completed the Prolonged Grief Scale (PG-13) and the Hospital Anxiety and Depression Scale (HADS). Results: The prevalence of PGD within the sample was 4.46% (i.e., = 7/157). Participants scored higher than the cut-off on the PG-13 and the HADS-D. Symptoms of PGD were positively correlated with depression levels. The ROC curve analysis showed that the HADS-D was outstanding in categorizing individuals with prolonged grief disorder from those without PGD. A HADS-D score of ≥7.5 was able to categorize participants with a sensitivity of 0.90 and a specificity of 0.73. Conclusions: Overall, these results highlight the relationship between grief and depression symptoms and their exceptional discriminant validity among correctly identified individuals with PGD.
Passification-Based Robust Phase-Shift Control for Two-Rotor Vibration Machine
Authors: Andrievsky Boris , Zaitceva Iuliia , Barkana Itzhak
Published: February 2023

In this paper, the solution to the problem of robust control of the phase shift during rotation at a given speed of the unbalanced rotors for a two-rotor vibratory machine is presented. The solution to this problem is relevant for the development of vibration technologies (for example, a vibro-transportation of bulk materials). The proposed controller includes two proportional-integral (PI) rotor speed controllers with a cross-coupling, which receive signals with opposite signs from the phase shift controller. Unlike previous works, where a PI controller for phase shift control was also taken, including the adaptive controller with an implicit reference model (IRM), in the present paper, a relay-type signal controller with an integral component without a parametric adaptation is used. This approach allows, while maintaining robustness, to increase the operation speed and accuracy of the control process, avoiding at the same time the possible divergence of the tunable parameters due to the influence of noises and disturbances caused, among other things, by vibrations of the setup’s structural elements and measurement errors. For the control law design, the speed-gradient method was employed. For various types of reference phase-shift signals (constant, harmonic, chaotic), the results of extensive experimental studies performed on the mechatronic vibration setup and the simulations accomplished based on the results of identifying the parameters of the stand drive model are presented in the paper. The obtained results confirm the efficiency and robustness of the proposed algorithm and allow one to reveal the system performance properties.
Efficient Algorithms and Architectures for DSP Applications
Authors: Chiper Doru-Florin , Paleologu Constantin
Published: February 2023

In the new era of digital revolution, the digital sensors and embedded designs become cheaper and more present [...]
Secure Data Transmission of Electronic Health Records Using Blockchain Technology
Authors: Sonkamble Rahul Ganpatrao , Bongale Anupkumar M. , Phansalkar Shraddha , Sharma Abhishek , Rajput Shailendra
Published: February 2023

Electronic Health Records (EHR) serve as a solid documentation of health transactions and as a vital resource of information for healthcare stakeholders. EHR integrity and security issues, however, continue to be intractable. Blockchain-based EHR architectures, however, address the issues of integrity very effectively. In this work, we suggest a decentralized patient-centered healthcare data management (PCHDM) with a blockchain-based EHR framework to address issues of confidentiality, access control, and privacy of record. This patient-centric architecture keeps the patient at the center of control for secured storage of EHR data. It is effective in the storage environment with the interplanetary file system (IPFS) and blockchain technology. In order to control unauthorized users, the proposed secure password authentication-based key exchange (SPAKE) implements smart contract-based access control to EHR transactions and access policies. The experimental setup comprises four hyperledger fabric nodes with level DB database and IPFS off-chain storage. The framework was evaluated using the public hepatitis dataset, with parameters such as block creation time, transactional computational overhead with encryption key size, and uploading/downloading time with EHR size. The framework enables patient-centric access control of the EHR with the SPAKE encryption algorithm.
Revisiting Homophily Ratio: A Relation-Aware Graph Neural Network for Homophily and Heterophily
Authors: Huang Wei , Guan Xiangshuo , Liu Desheng
Published: February 2023

The graph neural network (GNN) is a type of powerful deep learning model used to process graph data consisting of nodes and edges. Many studies of GNNs have modeled the relationships between the edges and labels of nodes only by homophily/heterophily, where most/few nodes with the same label tend to have an edge between each other. However, this modeling method cannot describe the multiconnection mode on graphs where homophily can coexist with heterophily. In this work, we propose a transition matrix to describe the relationships between edges and labels at the class level. Through this transition matrix, we constructed a more interpretable GNN in a neighbor-predicting manner, measured the information that the edges can provide for the node classification task, and proposed a method to test whether the labels match the edges. The results show the improvement of the proposed method against state-of-the-art (SOTA) GNNs. We also obtain the following two results: (1) the poor performance of GNNs is highly relevant to the information of edges instead of heterophily, which is always considered the main factor resulting in the decline in performance; and (2) most benchmark heterophilic datasets exhibit the label-edge mismatch problem, leading them to become intractable
An Empirical Study of Segmented Linear Regression Search in LevelDB
Authors: Ramadhan Agung Rahmat , Choi Min-guk , Chung Yoojin , Choi Jongmoo
Published: February 2023

The purpose of this paper is proposing a novel search mechanism, called SLR (Segmented Linear Regression) search, based on the concept of learned index. It is motivated by our observation that a lot of big data, collected and used by previous studies, have a linearity property, meaning that keys and their stored locations show a strong linear correlation. This observation leads us to design SLR search where we apply segmentation into the well-known machine learning algorithm, linear regression, for identifying a location from a given key. We devise two segmentation techniques, equal-size and error-aware, with the consideration of both prediction accuracy and segmentation overhead. We implement our proposal in LevelDB, Google’s key-value store, and verify that it can improve search performance by up to 12.7%. In addition, we find that the equal-size technique provides efficiency in training while the error-aware one is tolerable to noisy data.
Mixed Reality in Undergraduate Mental Health Education: A Systematic Review
Authors: Rincon Esther , Rodriguez-Guidonet Irene , Andrade-Pino Paula , Monfort-Vinuesa Carlos
Published: February 2023

The landscape of Extended Reality (ER), which includes Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) is rapidly changing. However, despite the promising results from many randomized controlled trials (RCTs) developed on healthcare environments, there is a lack of standardization, specifically to determine their effectiveness in academic settings. To our best knowledge, this is the first systematic review addressing the efficacy of MR to enhance learning and skills acquisition in undergraduate mental health education. The purposes of this study were to review the scientific literature of those studies involving MR and undergraduate mental health education, to answer the two following questions: (1) Is MR useful to enhance the acquisition of knowledge and skill training in undergraduate mental health education, and (2) Which are the advantages and disadvantages that should be addressed to successfully develop MR in undergraduate mental health education? We conducted a systematic review of the peer-reviewed literature from EBSCO, Ovid, PubMed, and Scopus y WOS (Web of Science), following the PRISMA statements and using “mixed reality + education”, “mixed reality + student”, “mixed reality + undergraduate”, and “mixed reality + mental health”, as keywords. Those studies published between 2012 to present, in English or Spanish language, were reviewed. A total of 2608 records were retrieved, and only 6 publications met the inclusion criteria, and were finally included. MR training used was varied. There were no studies providing specific outcomes regarding the student’s acquired knowledge (theoretical concepts) after using MR. Several strengths and weaknesses of using MR with students were discussed. The results will be useful to develop innovative MR strategies to improve undergraduate mental health education, due to the lack of studies focused on this topic.