bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of an ultrasensitive microfluidic assay for the analysis of Glial fibrillary acidic protein (GFAP) in blood
Authors: Fazeli Badrieh , Huss André , Gómez de San José Nerea , Otto Markus , Tumani Hayrettin , Halbgebauer Steffen
Published: April 2023

Introduction: A rapid and reliable detection of glial fibrillary acidic protein (GFAP) in biological samples could assist in the diagnostic evaluation of neurodegenerative disorders. Sensitive assays applicable in the routine setting are needed to validate the existing GFAP tests. This study aimed to develop a highly sensitive and clinically applicable microfluidic immunoassay for the measurement of GFAP in blood.

Methods: A microfluidic GFAP assay was developed and validated regarding its performance. Subsequently, serum and cerebrospinal fluid (CSF) of Alzheimer’s disease (AD), Multiple Sclerosis (MS) and control patients were analyzed with the established assay, and levels were compared to the commercial GFAP Simoa discovery kit.

Results: The developed GFAP assay showed a good performance with a recovery of 85% of spiked GFAP in serum and assay variations below 15%. The established assay was highly sensitive with a calculated lower limit of quantification and detection of 7.21 pg/mL and 2.37 pg/mL, respectively. GFAP levels were significantly increased in AD compared to control patients with advanced age (p = 0.002). However, GFAP levels revealed no significant increase in MS compared to control patients in the same age range (p = 0.140). Furthermore, serum GFAP levels evaluated with the novel microfluidic assay strongly correlated with Simoa concentrations (r = 0.88 (95% CI: 0.81–0.93), p < 0.0001).

Conclusion: We successfully developed a sensitive and easy-to-use microfluidic assay to measure GFAP in blood. Furthermore, we could confirm previous findings of elevated GFAP levels in AD by applying the assay in a cohort of clinically characterized patients.
Transcranial direct current stimulation impairs updating of avoidance-based associative learning
Authors: van ’t Wout-Frank Mascha , Garnaat Sarah L. , Faucher Christiana R. , Arulpragasam Amanda R. , Cole Julia E. , Philip Noah S. , Burwell Rebecca D.
Published: April 2023

Introduction

Exposure-based psychotherapies for the treatment of anxiety- and fear-based disorders rely on “corrective” associative learning. Namely the repeated confrontation with feared stimuli in the absence of negative outcomes allows the formation of new, corrected associations of safety, indicating that such stimuli no longer need to be avoided. Unfortunately, exposure-facilitated corrective learning tends to be bound by context and often poorly generalizes. One brain structure, the prefrontal cortex, is implicated in context-guided behavior and may be a relevant target for improving generalization of safety learning. Here, we tested whether inhibition of the left prefrontal cortex causally impaired updating of context-bound associations specifically or, alternatively, impaired updating of learned associations irrespective of contextual changes. Additionally, we tested whether prefrontal inhibition during corrective learning influenced subsequent generalization of associations to a novel context.

Methods

In two separate experiments, participants received either 10 min of 2 mA cathodal transcranial direct current stimulation (tDCS) over EEG coordinate F3 (Experiment 1 n = 9, Experiment 2 n = 22) or sham stimulation (Experiment 1 n = 10, Experiment 2 n = 22) while previously learned associations were reversed in the same or a different context from initial learning. Next, to assess generalization of learning, participants were asked to indicate which of the previously seen images they preferred in a novel, never seen before context.

Results

Results indicate that tDCS significantly impaired reversal irrespective of context in Experiment 2 only. When taking learning rate across trials into account, both experiments suggest that participants who received sham had the greatest learning rate when reversal occurred in a different context, as expected, whereas participants who received active tDCS in this condition had the lowest learning rate. However, active tDCS was associated with preferring the originally disadvantageous, but then neural stimulus after stimulus after reversal occurred in a different context in Experiment 1 only.

Discussion

These results support a causal role for the left prefrontal cortex in the updating of avoidance-based associations and encourage further inquiry investigating the use of non-invasive brain stimulation on flexible updating of learned associations.
Bridging event-related potentials with behavioral studies in motor learning
Authors: Deng Xueqian , Yang Chen , Xu Jingyue , Liufu Mengzhan , Li Zina , Chen Juan
Published: April 2023

Behavioral approaches and electrophysiology in understanding human sensorimotor systems have both yielded substantial advancements in past decades. In fact, behavioral neuroscientists have found that motor learning involves the two distinct processes of the implicit and the explicit. Separately, they have also distinguished two kinds of errors that drive motor learning: sensory prediction error and task error. Scientists in electrophysiology, in addition, have discovered two motor-related, event-related potentials (ERPs): error-related negativity (ERN), and feedback-related negativity (FRN). However, there has been a lack of interchange between the two lines of research. This article, therefore, will survey through the literature in both directions, attempting to establish a bridge between these two fruitful lines of research.
Adjuvant chemotherapy is associated with an overall survival benefit regardless of age in ER+/HER2- breast cancer pts with 1-3 positive nodes and oncotype DX recurrence score 20 to 25: an NCDB analysis
Authors: Stabellini Nickolas , Cao Lifen , Towe Christopher W. , Luo Xun , Amin Amanda L. , Montero Alberto J.
Published: April 2023

Background

The RxPONDER trial found that among breast cancer patients with estrogen receptor positive (ER+) breast cancer, 1-3 positive axillary nodes, and a recurrence score of ≤25, only pre-menopausal women benefitted from adjuvant chemoendocrine therapy; postmenopausal women with similar characteristic did not benefit from adjuvant chemotherapy. We aimed to replicate the RxPonder trial using a larger patient cohort with real world data to determine whether a RS threshold existed where adjuvant chemotherapy was beneficial regardless of age.

Methods

The National Cancer Database (NCDB) was queried for women with ER+, human epidermal growth factor receptor 2 (HER2) negative breast cancer, 1-3 positive axillary nodes, and RS ≤25 who received endocrine (ET) only or chemo-endocrine therapy (CET). Cox regression interaction was explored between CET and age as a surrogate for menopausal status.

Results

The final analytic cohort included 28,427 eligible women: 7,487 (26.3%) received adjuvant CET and 20,940 (73.7%) ET. In the entire cohort, RS had a normal distribution, with a median score of 14. After correcting for demographic and clinical variables, a threshold effect was observed with RS >20 being associated with a significantly inferior overall survival (OS) (P value range: < 0.001-0.019). In women with RS of 20-25, CET was associated with a significant improvement in OS compared to ET alone, regardless of age (age <=50: HR = 0.334, P=0.002; age>50: HR=0.521, P=0.019).

Conclusion

Among women with ER+/HER2- breast cancer with 1–3 positive nodes, and a RS of 20-25—in contrast to the RxPONDER trial—we observed that CET was associated with an OS benefit in women regardless of age.
A large ectopic hepatocellular carcinoma with adrenal infiltration: a rare case report
Authors: Yang Yongjun , Lu Qiang , Li Zonglin , Wang Chen , Li Yuanwei
Published: April 2023

Ectopic hepatocellular carcinoma (EHCC) originates from the ectopic liver, which refers to a liver organ or tissue unrelated to surrounding tissues. EHCC is a rare disease that lacks specific clinical signs, and preoperative diagnosis is often difficult. In a 61-year-old male patient with positive hepatitis B virus antibody, abdominal contrast-enhanced computed tomography scan showed a large heterogenously enhancing mass both on arterial and portal venous phase imaging arising from the right adrenal gland. Similar enhancement features were seen on magnetic resonance imaging. Serum potassium, aldosterone, cortisol, and plasma metanephrines were normal. The tumor markers of serum alpha-fetoprotein and alpha-fetoprotein-L3% were increased to 23.69 ng/mL and 82.1%, respectively. Exploratory laparotomy was performed and operative findings showed that the retroperitoneal tumor was disconnected from the right kidney and the liver, but invaded the right adrenal gland. Immunohistochemical examination showed that Arginase-1 was positive expression, and the retroperitoneal tumor was finally diagnosed as EHCC. We report a rare EHCC with adrenal infiltration that is difficult to diagnose preoperatively and mimics a retroperitoneal tumor or adrenal tumor, and we present a review of the literature on EHCC case reports.
miRNome of Child A hepatocellular carcinoma in Egyptian patients
Authors: EL-shqnqery Hend E. , Mohamed Rania Hassan , Samir Omar , Ayoub Islam , El-Sayed Wael M. , Sayed Ahmed A.
Published: April 2023

Introduction

Hepatocellular carcinoma (HCC) has different etiologies that contribute to its heterogeneity. In regards to the number of HCC patients, Egypt ranks third in Africa and fifteenth worldwide. Despite significant advancements in HCC diagnosis and treatment, the precise biology of the tumor is still not fully understood, which has a negative impact on patient outcomes.

Methods

Advances in next-generation sequencing (NGS) have increased our knowledge of the molecular complexity of HCC.

Results & discussion

In this research, 16 HCC and 6 tumor adjacent tissues (control) of Child A Egyptian patients were successfully profiled for the expression profile of miRNAs by NGS. Forty-one differentially expressed miRNAs (DEMs) were found by differential expression analysis, with 31 being upregulated and 10 being downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was then conducted on these differentially expressed miRNAs revealing that Sensitivity and specificity analysis showed that hsa-miR-4488, hsa-miR-3178, and hsa-miR-3182 were unique miRNAs as they are expressed in HCC tissues only. These miRNAs were all highly involved in AMPK signaling pathways. However, hsa-miR-214-3p was expressed in control tissues about eight times higher than in cancer tissues and was most abundant in “pathways in cancer and PI3K-Akt signaling pathway” KEGG terms. As promising HCC diagnostic markers, we here suggest hsa-miR-4488, hsa-miR-3178, hsa-miR-3182, and hsa-miR-214-3p. We further urge future research to confirm these markers' diagnostic and prognostic potential as well as their roles in the pathophysiology of HCC.
A synthetic peptide from Sipunculus nudus promotes bone formation via Estrogen/MAPK signal pathway based on network pharmacology
Authors: Wang Peiran , Feng Zhenhui , Chen Siyu , Liang Yingye , Hou Haiyan , Ouyang Qianqian , Yu Hui , Ye Hua , Cai Lei , Qi Yi , Wu Kefeng , Luo Hui
Published: April 2023

The tripeptide Leu-Pro-Lys (LPK), derived from the Sipunculus nudus protein, was synthesized and studied to investigate its potential protective effect on bone formation. The effect and mechanism of LPK were analyzed through network pharmacology, bioinformatics, and experimental pharmacology. The study found that LPK at concentrations of 25 μg/mL and 50 μg/mL significantly increased ALP activity and mineralization in C3H10 cells. LPK also increased the expression of COL1A1 and promoted bone formation in zebrafish larvae. Network pharmacology predicted 148 interaction targets between LPK and bone development, and analysis of the protein-protein interaction network identified 13 hub genes, including ESR1, MAPK8, and EGFR, involved in bone development. Through KEGG enrichment pathways analysis, it was determined that LPK promotes bone development by regulating endocrine resistance, the relaxin signaling pathway, and the estrogen signaling pathway. Molecular docking results showed direct interactions between LPK and ESR1, MAPK8, and MAPK14. Additional verification experiments using western blot assay revealed that LPK significantly upregulated the expression of genes related to bone formation, including COL1A1, OPG, RUNX2, ESR1, phosphorylated MAPK14, and phosphorylated MAPK8 in C3H10 cells. These results suggest that LPK promotes bone formation by activating the estrogen/MAPK signaling pathway.
Variant biomarker discovery using mass spectrometry-based proteogenomics
Authors: Reilly Luke , Seddighi Sahba , Singleton Andrew B. , Cookson Mark R. , Ward Michael E. , Qi Yue A.
Published: April 2023

Genomic diversity plays critical roles in risk of disease pathogenesis and diagnosis. While genomic variants—including single nucleotide variants, frameshift variants, and mis-splicing isoforms—are commonly detected at the DNA or RNA level, their translated variant protein or polypeptide products are ultimately the functional units of the associated disease. These products are often released in biofluids and could be leveraged for clinical diagnosis and patient stratification. Recent emergence of integrated analysis of genomics with mass spectrometry-based proteomics for biomarker discovery, also known as proteogenomics, have significantly advanced the understanding disease risk variants, precise medicine, and biomarker discovery. In this review, we discuss variant proteins in the context of cancers and neurodegenerative diseases, outline current and emerging proteogenomic approaches for biomarker discovery, and provide a comprehensive proteogenomic strategy for detection of putative biomarker candidates in human biospecimens. This strategy can be implemented for proteogenomic studies in any field of enquiry. Our review timely addresses the need of biomarkers for aging related diseases.
Construct validity of the Danish version of the Work Rehabilitation Questionnaire (WORQ)—sensitivity and specificity of the objectively tested physical capacity items
Authors: Verpe Ida Skovborg , Thygesen Katrine Baltzer , Escorpizo Reuben , Mortensen Ole Steen , Korshøj Mette
Published: April 2023

Objective

The aim of this study was to examine the construct validity of the Danish version of the Work Rehabilitation Questionnaire (WORQ) and to compare the physical capacity items of WORQ to objective, standardized measures of physical capacity and selected SF-36 physical items.

Methods

The study took place at a job center in Holbæk municipality, and 40 clients of working age were enrolled. Participants completed the interviewer-administered version of WORQ, selected SF-36 items, and underwent objective, physical capacity testing, including a 30-s sit-to-stand-test, a hand-grip-strength test, and a 6-min walk test to estimate cardiorespiratory fitness. Correlations between variables were assessed using Spearman's correlation. Further, cross tabulations and chi-square tests were conducted, and sensitivity, specificity, positive predictive values (PPVs), and negative predictive values (NPVs) were calculated.

Results

We found a moderate to strong correlation between WORQ and SF-36 items and a weak to moderate correlation between physical capacity items of WORQ and objectively tested physical capacity measures. On the basis of cross tabulations, calculations yielded overall higher NPVs than PPVs, whereas sensitivity and specificity varied more, with not one parameter being overall better than the other.

Conclusion

We found evidence of construct validity of the WORQ-Danish. However, our study might also raise a question as to whether objective physical capacity tests are the gold standard for evaluating functioning. Our results are promising, and we suggest further investigations of the screening capabilities of WORQ, alongside other legacy measures or instruments, both self-reported and objective physical measures, to complement information—where specific answers to specific questions trigger work-related actions or interventions
Association of Work Schedules With Nurse Turnover: A Cross-Sectional National Study
Authors: Bae Sung-Heui
Published: April 2023

Objective: To examine the relationship of work schedules with nurse turnover across various work settings.

Methods: A cross-sectional study design was used with data collected from 17,046 nurses who participated in the 2018 National Sample Survey of Registered Nurses in the U.S. Multivariate logistic regression was used to examine the effects of work hours and overtime on nurse turnover.

Results: Longer weekly work hours increased nurse turnover (OR = 1.104, 95% confidence interval [CI] = 1.006–1.023). A non-linear relationship was observed between overtime and turnover. Compared with nurses with no overtime, the turnover for nurses working 1–11 h overtime per week decreased (OR = 0.893, 95% CI = 0.798–0.999). When nurses worked ≥12 h, turnover increased (OR = 1.260, 95% CI = 1.028–1.545). Earning from the primary nursing position decreased turnover among nurses working in hospitals, other inpatient settings, and clinics. Job satisfaction decreased turnover.

Conclusion: To prevent nurse turnover, it is important to monitor and regulate nurses’ working hours at institutional and government levels. Government support and policy implementations can help prevent turnover.
Prognostic role of pretreatment skeletal muscle index in gastric cancer patients: A meta-analysis
Authors: He Xiaohong , Zhou Sicheng , Li Hongjun , Gou Yue , Jia Dan
Published: April 2023

Background: The association between pretreatment skeletal muscle index (SMI) and long-term survival of gastric cancer patients remains unclear up to now. The aim of this meta-analysis was to identify the prognostic value of pretreatment SMI in gastric cancer.

Methods: The PubMed, EMBASE and Web of Science electronic databases were searched up to 5 June 2022 for relevant studies. The primary outcome was overall survival (OS) and the second outcomes were disease-free survival (DFS) and cancer-specific survival (CSS). The hazard ratios (HRs) and 95% confidence intervals (CIs) were combined to assess the relationship between pretreatment SMI and survival of gastric cancer patients. All statistical analyses were conducted by STATA 15.0 software.

Results: A total of 31 retrospective studies involving 12,434 patients were enrolled in this meta-analysis. The pooled results demonstrated that lower pretreatment was significantly associated with poorer OS (HR = 1.53, p < 0.001). Besides, lower pretreatment SMI was also related with worse DFS (HR = 1.39, p < 0.001) and CSS (HR = 1.96, p < 0.001).

Conclusion: Pretreatment SMI was significantly associated with prognosis of gastric cancer patients and lower SMI predicted worse survival. However, more prospective high-quality studies are still needed to verify our findings.
Classification of Fresh and Frozen-Thawed Beef Using a Hyperspectral Imaging Sensor and Machine Learning
Authors: Park Seongmin , Hong Suk-Ju , Kim Sungjay , Ryu Jiwon , Roh Seungwoo , Kim Ghiseok
Published: April 2023

The demand for safe and edible meat has led to the advancement of freeze-storage techniques, but falsely labeled thawed meat remains an issue. Many methods have been proposed for this purpose, but they all destroy the sample and can only be performed in the laboratory by skilled personnel. In this study, hyperspectral image data were used to construct a machine learning (ML) model to discriminate between freshly refrigerated, long-term refrigerated, and thawed beef meat samples. With four pre-processing methods, a total of five datasets were prepared to construct an ML model. The PLS-DA and SVM techniques were used to construct the models, and the performance was highest for the SVM model applying scatter correction and the RBF kernel function. These results suggest that it is possible to construct a prediction model to distinguish between fresh and non-fresh meat using the spectra obtained by purifying hyperspectral image data cubes, which can be a rapid and non-invasive method for routine analyses of the meat storage state.
Sensory and Biological Activity of Medlar (Mespilus germanica) and Quince ‘Nivalis’ (Chaenomeles speciosa): A Comperative Study
Authors: Żołnierczyk Anna K. , Pachura Natalia , Bąbelewski Przemysław , Taghinezhad Ebrahim
Published: April 2023

This research investigates the potential health benefits of extracts from the seeds, peels, and pulps of quince, medlar, and bletting medlar fruits. Our study reveals that the polyphenol content is higher in the skin than in the flesh of the fruits tested, with the highest concentration found in the skin of fresh medlar fruits (1148 mg GAE/100 gDM). The extracts from medlar and quince show the highest antioxidant activity (ABTS, DPPH, and FRAP tests), while the pulp of bletting medlars exhibits the highest inhibition ability against α-amylase (53.7% at a concentration of 10 mg/mL). The analysis of fatty acids in the tested samples indicates the presence of nine major fatty acids, with linoleic acid being the most abundant (716–1878 mg/100 g of biomass). Analysis of sterols in the tested material shows five main phytosterols, with β-sitosterol being the most commonly studied and recommended phytosterol. The highest amount of phytosterols is found in the lipid fraction of the quince seeds (1337.1 mg/100 g of biomass). Therefore, we suggest that fruit peel extracts can be utilised as a natural source of antioxidants and as an alternative treatment for carbohydrate uptake disorders. However, it is important to note that bletting medlar loses a significant amount of polyphenols and antioxidant activity after the bletting process. This article also describes the sensory analysis process, which is a valuable tool for evaluating the quality of food products. Our study evaluates the attributes and preferences of the fruits of quince, medlar, and bletting medlar using a nine-point hedonic scale. The results show that quince is the highest-rated fruit in terms of aroma, colour, and overall acceptability (7.3, 7.0, and 4.2, respectively) while bletting medlar is the least preferred fruit. The article concludes that sensory analysis can aid in the development of new products and recipes that meet consumer preferences. In general, the study suggests that both fruit peel extracts and sensory analysis are important tools for assessing product quality and developing products that meet consumers’ preferences.
Seed Treatment with Calcium Carbonate Containing Bacillus amyloliquefaciens PMB05 Powder Is an Efficient Way to Control Black Rot Disease of Cabbage
Authors: Hsiao Chia-Yu , Blanco Sabrina Diana , Peng An-Li , Fu Ju-Yin , Chen Bo-Wei , Luo Min-Chia , Xie Xing-Yu , Lin Yi-Hsien
Published: April 2023

Black rot disease is a serious bacterial disease that harms vegetable crops of the Brassica genus (especially cabbage plants) worldwide. The causal agent, Xanthomonas campestris pv. campestris (Xcc), is a seed-borne pathogen that primarily infects seedlings. Previous studies suggest that the bacterial strain, Bacillus amyloliquefaciens PMB05, can intensify the plant immune responses of cabbage against black rot disease and reduce disease occurrence. In plant immunity, several reactions occur during a pathogen attack, but the elevation of calcium ion concentration in plant cells is essential in the induction of plant defense responses. Therefore, this study aims to investigate whether disease control of black rot disease in cabbage plants can be improved by integrating calcium carbonate in the formulation for preparing B. amyloliquefaciens PMB05. Firstly, we found the addition of calcium carbonate in the formulation revealed to have significantly increased the cell and endospore populations of B. amyloliquefaciens PMB05 in the fermentation liquids. To increase the convenience of disease control in the field, these fermentation liquids were converted to powder form for subsequent analysis. Results revealed that the grown seedlings from seeds, mixed with PMB05 powders, significantly intensified plant immune responses and improved black rot disease control. We further compared distinct seed treatments using one PMB05 powder to evaluate its feasibility in field application. The results demonstrated that the disease control efficacy and yield of cabbage were significantly improved in the seed treatment with the powder (SD-160C2) to 56.46% and 5.91%, respectively, at 10 weeks post transplanting. Interestingly, the seed treatment combined with a calcium-containing commercial fertilizer spraying treatment did not increase the control efficacy of black rot disease, but it significantly increased the weight of cabbages after harvest. We concluded that the seed treatment with calcium carbonate-containing Bacillus amyloliquefaciens PMB05 powder is an efficient way to control black rot disease in cabbage.
Using Genetic Programming to Identify Characteristics of Brazilian Regions in Relation to Rural Credit Allocation
Authors: Araújo Adolfo Vicente , Mota Caroline , Siraj Sajid
Published: April 2023

Rural credit policies have a strong impact on food production and food security. The attribution of credit policies to agricultural production is one of the main problems preventing the guarantee of agricultural expansion. In this work, we conduct family typology analysis applied to a set of research data to characterize different regions. Through genetic programming, a model was developed using user-defined terms to identify the importance and priority of each criterion used for each region. Access to credit results in economic growth and provides greater income for family farmers, as observed by the results obtained in the model for the Sul region. The Nordeste region indicates that the cost criterion is relevant, and according to previous studies, the Nordeste region has the highest number of family farming households and is also the region with the lowest economic growth. An important aspect discovered by this research is that the allocation of rural credit is not ideal. Another important aspect of the research is the challenge of capturing the degree of diversity across different regions, and the typology is limited in its ability to accurately represent all variations. Therefore, it was possible to characterize how credit is distributed across the country and the main factors that can influence access to credit.
Knowledge Tracing Model and Student Profile Based on Clustering-Neural-Network
Authors: Xia Jianghua , Wang Han , Zhuge Qingfeng , Sha Edwin Hsing-Mean
Published: April 2023

Knowledge tracing models based on deep neural networks are currently widely studied to enhance personalized learning. However, to ensure the practical deployment of DNN-based KT models, prediction accuracy, training efficiency, and interpretability should be greatly improved. In this paper, we observe that the prediction accuracy of KT models can be improved by clustering the features of both students and questions. Based on this observation, a distributed KT scheme is proposed: (1) it classifies both students and questions based on clustering technology to reduce the interaction between different feature data to improve the prediction accuracy; (2) models for different classifications are trained in parallel in this distributed deployment architecture to improve the training efficiency; (3) the combination of a students’ knowledge state matrix and an RPa-LLM model is designed to display the knowledge status of students in the learning process, which can be used to build students’ portraits, thus improving the interpretability of the model. Real educational data are collected to conduct experiments. The results show that the proposed scheme improves both prediction accuracy and training efficiency by 4.08% and 67.28%, respectively, compared to the baseline methods. Furthermore, the proposed method maintains the interpretability of KT models, making it suitable for practical deployment.
Characterization of Thermal Properties of Ruby Chocolate Using DSC, PDSC and TGA Methods
Authors: Ostrowska-Ligęza Ewa , Dolatowska-Żebrowska Karolina , Brzezińska Rita , Wirkowska-Wojdyła Magdalena , Bryś Joanna , Piasecka Iga , Górska Agata
Published: April 2023

Barely explored in the prior literature, ruby chocolate was investigated in this study to explore its thermal properties. The fatty acid composition of ruby chocolate (RC) fat was determined using gas chromatography. Differential scanning calorimetry (DSC) was successfully used to determine the melting behavior and polymorphic forms of the cocoa fat and milk fat present in the RC. The oxidative stability of the fat extracted from the RC was studied with the use of pressurized differential scanning calorimetry (PDSC). The thermal behavior of the chocolate and the fat were investigated using thermogravimetry (TGA). The thermal profile and characteristics of the RC showed how the parameters compared with those of dark and milk chocolate. The melting temperature of the RC obtained by DSC was more similar to that of milk chocolate than to that of dark chocolate. Regression analysis of the PDSC data for the fat extracted from the RC was characterized by very high correlation coefficients (>0.99). It was noticed there was no statistically significant difference between the values of the activation energy (Ea) of the oxidation process for the fat extracted from the RC, obtained by the means of maximum temperature (dynamic mode) and maximum induction time (isothermal mode).
HyperIO: A Hypervisor-Based Framework for Secure IO
Authors: Kiperberg Michael , Zaidenberg Nezer Jacob
Published: April 2023

Malware often attempts to steal input and output through human interface devices to obtain confidential information. We propose to use a thin hypervisor, called “HyperIO”, to realize a secure path between input and output devices using a partial implementation of device drivers. We apply our approach using two security systems built on HyperIO: FireSafe and ClipCrypt. FireSafe is a web browser extension which allows a remote web server to display and receive sensitive user information securely. ClipCrypt enables the user to securely enter and view their confidential information in commodity Windows applications.
Digital Rock Analysis on the Influence of Coarse Micro-Fractures on Petrophysical Properties in Tight Sandstone Reservoirs
Authors: Liu Lei , Yao Jun , Sun Hai , Zhang Lei , Zhang Kai
Published: April 2023

Tight sandstone reservoirs, as typical unconventional reservoirs, have attracted more and more attention worldwide. Compared to conventional reservoirs, the complex microscopic pore structures and micro-fractures of the tight reservoirs are developed, and fluid flow in the tight sandstone reservoir is very complicated. Therefore, studying the influence of fractures on the rock topological structure and the flow characteristics between micro-fractures and the matrix is critical to the development of tight sandstone reservoirs. In light of the intricate nature of micro-fractures, digital rock analysis technology is utilized to address this issue instead of traditional experimental methods. Firstly, the selected tight rock is scanned by X-ray computed tomography (XCT), and then the natural tight digital rock is reconstructed by filtering and binary segmentation. Secondly, micro-fracture with different shapes is added to the digital rock. Then, a pore network model extracted by the maximum ball method is adopted to conduct the flow simulation. The study finds that the distribution of pore throat radius changes with increasing fracture aperture and length and that the permeability and capillary pressure curves are influenced by fracture aperture and length in the direction of connectivity. The impact of micro-fracture dip angle on pore throat structure is significant with changes in permeability and fluid flow in different directions. Overall, the study emphasizes the importance of fracture aperture and length in determining the properties and behavior of tight sandstone reservoirs and highlights the usefulness of digital rock analysis technology in providing insights into complex microstructures.
A Visual Analytics Framework for Inter-Hospital Transfer Network of Stroke Patients
Authors: Kwak Kyuhan , Park Jinu , Song Hyunjoo
Published: April 2023

Effective inter-hospital coordination is crucial in improving the stroke treatment process and outcomes. The introduction of endovascular thrombectomy (EVT) further emphasized the importance of coordination. Although previous studies considered various clinical data besides stroke in terms of the network structure between hospitals, a majority of these studies performed only quantitative analyses instead of topological analyses. This study proposes a new framework (PatientFlow) for constructing a network based on stroke patient transfer data and performing exploratory analysis. The proposed framework can visualize the network structure among hospitals at the national level and analyze the detailed structure through dynamic queries. The hub-and-spoke structure for each cluster derived through community detection can be compared visually and analyzed quantitatively using network measures. Further, the relationship between regions can be analyzed by aggregating the transfer of patients by province. PatientFlow allows medical researchers to perform an exploratory analysis to understand the network at the national, provincial, and community levels with multiple coordinated views.
Assessment and Spatial Modelling of Agrochernozem Properties for Reclamation Measurements
Authors: Suleymanov Ruslan , Suleymanov Azamat , Zaitsev Gleb , Adelmurzina Ilgiza , Galiakhmetova Gulnaz , Abakumov Evgeny , Shagaliev Ruslan
Published: April 2023

Traditional land-use systems can be modified under the conditions of climate change. Higher air temperatures and loss of productive soil moisture lead to reduced crop yields. Irrigation is a possible solution to these problems. However, intense irrigation may have contributed to land degradation. This research assessed the ameliorative potential of soil and produced large-scale digital maps of soil properties for arable plot planning for the construction and operation of irrigation systems. Our research was carried out in the southern forest–steppe zone (Southern Ural, Russia). The soil cover of the site is represented by agrochernozem soils (Luvic Chernozem). We examined the morphological, physicochemical and agrochemical properties of the soil, as well as its heavy metal contents. The random forest (RF) non-linear approach was used to estimate the spatial distribution of the properties and produce maps. We found that soils were characterized by high organic carbon content (SOC) and neutral acidity and were well supplied with nitrogen and potassium concentrations. The agrochernozem was characterized by favorable water–physical properties and showed good values for water infiltration and moisture categories. The contents of heavy metals (lead, cadmium, mercury, cobalt, zinc and copper) did not exceed permissible levels. The soil quality rating interpretation confirms that these soils have high potential fertility and are convenient for irrigation activities. The spatial distribution of soil properties according to the generated maps were not homogeneous. The results showed that remote sensing covariates were the most critical variables in explaining soil properties variability. Our findings may be useful for developing reclamation strategies for similar soils that can restore soil health and improve crop productivity.
Comparison between Eight-Axis Articulated Robot and Five-Axis CNC Gantry Laser Metal Deposition Machines for Fabricating Large Components
Authors: Maffia Simone , Chiappini Federico , Maggiani Gianluca , Furlan Valentina , Guerrini Massimo , Previtali Barbara
Published: April 2023

Laser metal deposition (LMD) is an additive manufacturing (AM) process capable of producing large components for the aerospace and oil and gas industries. This is achieved by mounting the deposition head on a motion system, such as an articulated robot or a gantry computer numerical control (CNC) machine, which can scan large volumes. Articulated robots are more flexible and less expensive than CNC machines, which on the other hand, are more accurate. This study compares two LMD systems with different motion architectures (i.e., an eight-axis articulated robot and a five-axis CNC gantry machine) in producing a large gas turbine axisymmetric component. The same process parameters were applied to both machines. The deposited components show no significant differences in geometry, indicating that the different performances in terms of accuracy of the two machines do not influence the outcome. The findings indicate that LMD can consistently produce large-scale axisymmetric metal components with both types of equipment. For such an application, the user has the option of using an articulated robot when flexibility and cost are essential, such as in a research context, or a CNC machine where ease of programming and process standardization are important elements, such as in an industrial environment.
A Triple Deep Image Prior Model for Image Denoising Based on Mixed Priors and Noise Learning
Authors: Hu Yong , Xu Shaoping , Cheng Xiaohui , Zhou Changfei , Hu Yufeng
Published: April 2023

Image denoising poses a significant challenge in computer vision due to the high-level visual task’s dependency on image quality. Several advanced denoising models have been proposed in recent decades. Recently, deep image prior (DIP), using a particular network structure and a noisy image to achieve denoising, has provided a novel image denoising method. However, the denoising performance of the DIP model still lags behind that of mainstream denoising models. To improve the performance of the DIP denoising model, we propose a TripleDIP model with internal and external mixed images priors for image denoising. The TripleDIP comprises of three branches: one for content learning and two for independent noise learning. We firstly use a Transformer-based supervised model (i.e., Restormer) to obtain a pre-denoised image (used as external prior) from a given noisy image, and then take the noisy image and the pre-denoised image as the first and second target image, respectively, to perform the denoising process under the designed loss function. We add constraints between two-branch noise learning and content learning, allowing the TripleDIP to employ external prior while enhancing independent noise learning stability. Moreover, the automatic stop criterion we proposed prevents the model from overfitting the noisy image and improves the execution efficiency. The experimental results demonstrate that TripleDIP outperforms the original DIP by an average of 2.79 dB and outperforms classical unsupervised methods such as N2V by an average of 2.68 dB and the latest supervised models such as SwinIR and Restormer by an average of 0.63 dB and 0.59 dB on the Set12 dataset. This can mainly be attributed to the fact that two-branch noise learning can obtain more stable noise while constraining the content learning branch’s optimization process. Our proposed TripleDIP significantly enhances DIP denoising performance and has broad application potential in scenarios with insufficient training datasets.
Effectiveness of Driving Simulators for Drivers’ Training: A Systematic Review
Authors: Alonso Francisco , Faus Mireia , Riera José V. , Fernandez-Marin Marcos , Useche Sergio A.
Published: April 2023

Although driving simulators could be commonly assumed as very useful technological resources for both novel and experienced drivers’ instruction under risk control settings, the evidence addressing their actual effectiveness seems substantially limited. Therefore, this study aimed to analyze the existing original literature on driving simulators as a tool for driver training/instruction, considering study features, their quality, and the established degree of effectiveness of simulators for these purposes. Methods: This study covered a final number of 17 empirical studies, filtered and analyzed in the light of the PRISMA methodology for systematic reviews of the literature. Results: Among a considerably reduced set of original research studies assessing the effectiveness of driving simulators for training purposes, most sources assessing the issue provided reasonably good insights into their value for improving human-based road safety under risk control settings. On the other hand, there are common limitations which stand out, such as the use of very limited research samples, infrequent follow-up of the training outcomes, and reduced information about the limitations targeted during the simulator-based training processes. Conclusions: Despite the key shortcomings highlighted here, studies have commonly provided empirical support on the training value of simulators, as well as endorsed the need for further evaluations of their effectiveness. The data provided by the studies included in this systematic review and those to be carried out in the coming years might provide data of interest for the development and performance improvement of specific training programs using simulators for driver instruction.
Investigating the Fracture Process and Tensile Mechanical Behaviours of Brittle Materials under Concentrated and Distributed Boundary Conditions
Authors: Liang Haozhe , Fang Xiaozu , Yu Xinlu , Fu Yingqian , Zhou Gangyi
Published: April 2023

In this study, concrete was selected to investigate the real-time splitting tensile mechanical and fracture behaviours of brittle materials using the Brazilian test under concentrated and distributed boundary conditions. The digital image correlation (DIC) method was adopted to evaluate the tensile strength and failure process in Brazilian tests using a high-resolution camera. The DIC results showed that the position of the crack initiation randomly occurred at the centre of a disc and at the boundary in Brazilian tests with concentrated loads (BTC). Comparatively, the crack initiated at the centre of discs in most Brazilian tests with distributed loads (BTD), as validated by the DIC results. Our results indicated that the average nominal tensile strength of specimens cracking at the boundary was larger than that of specimens cracking at the centre in the BTC, suggesting that the nominal tensile strength measured by the Brazilian test was related to the failure process of the discs. Moreover, this study demonstrated that the tensile strength measured by the Brazilian test was dependent on the boundary conditions. The equation recommended by the ISRM (International Society for Rock Mechanics) might slightly overestimate the tensile strength of brittle materials based on the pure elastic theory and hyperbolic-distributed loading conditions at the boundaries.
NGLSFusion: Non-Use GPU Lightweight Indoor Semantic SLAM
Authors: Wan Le , Jiang Lin , Tang Bo , Li Yunfei , Lei Bin , Liu Honghai
Published: April 2023

Perception of the indoor environment is the basis of mobile robot localization, navigation, and path planning, and it is particularly important to construct semantic maps in real time using minimal resources. The existing methods are too dependent on the graphics processing unit (GPU) for acquiring semantic information about the indoor environment, and cannot build the semantic map in real time on the central processing unit (CPU). To address the above problems, this paper proposes a non-use GPU for lightweight indoor semantic map construction algorithm, named NGLSFusion. In the VO method, ORB features are used for the initialization of the first frame, new keyframes are created by optical flow method, and feature points are extracted by direct method, which speeds up the tracking speed. In the semantic map construction method, a pretrained model of the lightweight network LinkNet is optimized to provide semantic information in real time on devices with limited computing power, and a semantic point cloud is fused using OctoMap and Voxblox. Experimental results show that the algorithm in this paper ensures the accuracy of camera pose while speeding up the tracking speed, and obtains a reconstructed semantic map with complete structure without using GPU.
Data Fusion-Based Structural Damage Identification Approach Integrating Fractal and RCPN
Authors: Fu Chun , Li Ming
Published: April 2023

In order to improve the identification accuracy of damage detection and evaluation based on the vibration response, this paper presents a structural damage identification method based on the fractal dimension, data fusion and a revised counter-propagation network (RCPN). Firstly, the fractal dimensions of the original signal response are extracted through data preprocessing. Secondly, the first-time fusion of data (i.e., the feature-level fusion) is carried out, after which these data are used as the input for the RCPN, to identify and decide the initial damage. Finally, the second-time data fusion (i.e., based on the decision results of the feature-level fusion) is carried out, leading to decision-level fusion. In order to verify the validity of the proposed method, a four-storey benchmark structure of ASCE is used for damage identification and comparison, using a single RCPN decision and the data fusion damage identification method, respectively. The results show that the proposed method is more accurate and reliable than the results of single RCPN decision and feature-level fusion decision, and has good noise resistance and robustness.
Correction: Schubert et al. Microencapsulation of Bacteriophages for the Delivery to and Modulation of the Human Gut Microbiota through Milk and Cereal Products. Appl. Sci. 2022, 12, 6299
Authors: Schubert Christina , Fischer Sabina , Dorsch Kathrin , Teßmer Lutz , Hinrichs Jörg , Atamer Zeynep
Published: April 2023

The authors would like to make the following corrections to this paper [...]
An Exploration of Robot-Mediated Tai Chi Exercise for Older Adults
Authors: Zheng Zhi , Oh Hyunkyoung , Mim Mayesha , Choi Wonchan , Lee Yura
Published: April 2023

In this fast-aging society, many older adults fail to meet the required level of exercise due to trainer shortages. Therefore, we developed a robot tutor to investigate the feasibility of robot-mediated exercise for older adults. Twenty older adults participated in an experimental study. A pre-exercise survey was used to assess their background. Each participant experienced a 30-min robot-led Tai Chi exercise followed by a post-exercise survey to evaluate the easiness of following the robot and expectations for future robot design. Participants’ Tai Chi performances were evaluated in terms of completion and accuracy. Associations between the surveys and the performance were also analyzed. All participants completed the study. Fifteen out of the twenty subjects had at least one chronic condition, and most practiced Tai Chi before the study but had never interacted with a robot. On average, the participants scored 93.09 and 85.21 out of 100 for movement completion and accuracy, respectively. Their initial movement accuracy was correlated with their attitude towards exercise. Most subjects reported that they could follow the robot’s movements and speeches well and were interested in using a robot tutor in the community. The study demonstrated the initial feasibility of robot-led Tai Chi exercise for older adults.