bluuebunny/crossref_metadata_2025 huggingface dataset:
Association of the Timeless Gene with Prognosis and Clinical Characteristics of Human Lung Cancer
Authors: Ye Jishi , Chen Jingli , Wang Juan , Xia Zhongyuan , Jia Yifan
Published: November 2022

(1) Background: As the most common malignant tumor type worldwide, it is necessary to identify novel potential prognostic biomarkers to improve the poor prognosis of lung cancer. The Timeless gene, a circadian rhythm-related gene, is associated with several types of cancer. However, studies analyzing the clinical significance of the Timeless gene in patients with lung cancer are currently limited. (2) Methods: In the present study, the expression levels and prognostic potential of the Timeless gene and its co-expressed genes in different subtypes of lung cancer were explored using multiple bioinformatics approaches. The correlations between the Timeless gene and its co-expressed genes were validated using A549 and NCI-H226 cells by transfecting them with expression vectors and analyses using Western blot and reverse transcription-quantitative PCR. (3) Results: The Oncomine and GEPIA database analyses indicated that the expression of the Timeless gene was significantly higher in lung cancer as compared to that in the normal tissue. Using the UALCAN database, significant differences in Timeless gene expression were determined among different stages of lung cancer and between genders. A Kaplan–Meier plotter analysis indicated that high expression of the Timeless gene was associated with poor overall survival (OS) and progression-free survival (PFS) of patients with lung cancer. In the cBioPortal and GEPIA database analyses, extra spindle pole bodies like 1 (ESPL1) was the top correlated gene of Timeless in patients with lung cancer. Similar to the Timeless gene, high expression of the ESPL1 gene was also associated with poor OS and PFS. Of note, overexpression of the Timeless gene increased the expression level of ESPL1 at both the mRNA and protein levels. (4) Conclusion: The present study explored the clinical significance of the Timeless gene and its correlated gene ESPL1 in patients with lung cancer, thereby providing a potential therapeutic target for lung cancer.
A New SMAD4 Splice Site Variant in a Three-Generation Italian Family with Juvenile Polyposis Syndrome
Authors: Micolonghi Caterina , Piane Maria , Germani Aldo , Sadeghi Soha , Libi Fabio , Savio Camilla , Fabiani Marco , Mancini Rita , Ranieri Danilo , Pizzuti Antonio , Corleto Vito Domenico , Parisi Pasquale , Visco Vincenzo , Di Nardo Giovanni , Petrucci Simona
Published: November 2022

Juvenile polyposis syndrome (JPS) is an autosomal dominant disorder characterized by hyperplastic polyps in the upper and lower gastrointestinal (GI) tract with a high risk of developing GI cancers. We have described a three-generation Italian family with all the spectrum of SMAD4 phenotype. A multigene panel test was performed on the genomic DNA of the proband by next-generation sequencing, including genes related to hereditary GI tumor syndromes. Molecular analysis revealed the presence of the c.1140-2A>G substitution in the SMAD4 gene, a novel splice variant that has never been described before. Our family is remarkable in that it illustrates the variable expressivity of the SMAD4 phenotype within the same family. The possibility of phenotype variability should also be considered within family members carrying the same mutation. In JPS, a timely genetic diagnosis allows clinicians to better manage patients and to provide early surveillance and intervention for their asymptomatic mutated relatives in the early decades of life.
Very High Yield of Urgent Small-Bowel Capsule Endoscopy for Ongoing Overt Suspected Small-Bowel Bleeding Irrespective of the Usual Predictive Factors
Authors: Estevinho Maria Manuela , Pinho Rolando , Rodrigues Adélia , Ponte Ana , Afecto Edgar , Correia João , Freitas Teresa
Published: November 2022

Evidence for an urgent approach to ongoing overt suspected small-bowel bleeding (SSBB) is scarce. We aimed to analyze our series of urgent small-bowel capsule endoscopies (SBCEs) for ongoing overt SSBB and to identify factors associated with positive findings and outcomes. A retrospective study of all SBCEs performed in the first 48 h after admission for overt SSBB between January 2006 and February 2022 was performed. Descriptive and inferential analyses (univariate and multivariable) were performed. Eighty-three urgent SBCEs were performed for overt SSBB. Patients were mostly men (69.2%, median age 68) and were followed for a median of 58.2 months (range 5–176). The diagnostic yield was 80.7%; in 60.2%, blood was detected in the small bowel (SB), while in 50.6%, a bleeding lesion was identified, mostly angioectasia. Patients with diabetes mellitus or taking NSAIDs were more prone to present SB findings, yet the explanatory power was low. Endoscopic or surgical treatments were performed in 28.9% and 19.3%, respectively, with the “non-conservative” therapeutic yield being 56.6%. Rebleeding occurred in 20.5% and was associated in the multivariable analysis with the female gender and anticoagulants use. This cohort of urgent SBCE, the largest from a European center, reinforces the usefulness of SBCE for ongoing overt SSBB management. This prompt performance of this procedure is highly effective, regardless of patients’ features.
CD8 Encephalitis: A Diagnostic Dilemma
Authors: Sharma Rohan , Spradley Thomas , Campbell Morgan , Biyani Shubham , Singhal Pulkit , Elkhider Hisham , Nalleballe Krishna , Gokden Murat , Kumar Manoj , Kapoor Nidhi
Published: November 2022

CD8+ encephalitis is a subacute encephalopathy associated with HIV infection. Pathophysiology is thought to be auto-reactive CD8+ cells attacking on HIV infected CD4+ cells and ‘viral escape’ phenomena (replication of CD8+ cells in CSF). We present a case of a 45-year-old man with well controlled HIV who developed CD8 encephalitis following Herpes simplex encephalitis. He had persistent encephalopathy for several weeks with status epilepticus and agitated delirium, and diagnosis remained elusive until a brain biopsy confirmed the diagnosis.
Dual-Energy Computed Tomography-Based Iodine Concentration Estimation for Evaluating Choroidal Malignant Melanoma Response to Treatment: Optimization and Primary Validation
Authors: Tsuchiya Hiroki , Tachibana Yasuhiko , Kishimoto Riwa , Omatsu Tokuhiko , Hotta Eika , Tanimoto Katsuyuki , Wakatsuki Masaru , Obata Takayuki , Tsuji Hiroshi
Published: November 2022

Contrast-enhanced imaging for choroidal malignant melanoma (CMM) is mostly limited to detecting metastatic tumors, possibly due to difficulties in fixing the eye position. We aimed to (1) validate the appropriateness of estimating iodine concentration based on dual-energy computed tomography (DECT) for CMM and optimize the calculation parameters for estimation, and (2) perform a primary clinical validation by assessing the ability of this technique to show changes in CMM after charged-particle radiation therapy. The accuracy of the optimized estimate (eIC_optimized) was compared to an estimate obtained by commercial software (eIC_commercial) by determining the difference from the ground truth. Then, eIC_optimized, tumor volume, and CT values (80 kVp, 140 kVp, and synthesized 120 kVp) were measured at pre-treatment and 3 months and 1.5–2 years after treatment. The difference from the ground truth was significantly smaller in eIC_optimized than in eIC_commercial (p < 0.01). Tumor volume, CT values, and eIC_optimized all decreased significantly at 1.5–2 years after treatment, but only eIC_commercial showed a significant reduction at 3 months after treatment (p < 0.01). eIC_optimized can quantify contrast enhancement in primary CMM lesions and has high sensitivity for detecting the response to charged-particle radiation therapy, making it potentially useful for treatment monitoring.
Update on Dental Luting Materials
Authors: Leung Gary Kwun-Hong , Wong Amy Wai-Yee , Chu Chun-Hung , Yu Ollie Yiru
Published: November 2022

A dental luting material aids in the retention and stability of indirect restorations on the prepared tooth structure. In dentistry, clinicians are using a wide range of luting materials for the cementation of indirect restorations. Zinc oxide eugenol and non-eugenol cements, zinc phosphate cement, zinc polycarboxylate cement, glass ionomer cement and resin cements are common dental cements used in dentistry. Each luting material or cement possesses unique properties and clinical implications. An ideal luting cement should be biocompatible, insoluble, resistant to thermal and chemical assaults, antibacterial, aesthetic, simple and easy to use. It should have high strength properties under tension, shear and compression to resist stress at the restoration–tooth interface, as well as adequate working and setting times. So far, no luting material possesses all of these properties of an ideal cement. Scientists have been modifying the conventional luting cements to improve the material’s clinical performance and developing novel materials for clinical use. To achieve the best clinical outcome, clinicians should update their knowledge and gain a good understanding of the luting materials so that they can make a wise clinical decision on the material selection and obtain an insight into the development of luting cements. Therefore, the objective of this study is to provide a discussion on the physical, chemical, adhesive and aesthetic properties of common luting materials. The clinical indications of these luting materials are suggested based on their properties. In addition, overviews of the modification of the conventional luting materials and the newly developed luting materials are provided.
Retention Factors in STEM Education Identified Using Learning Analytics: A Systematic Review
Authors: Li Chunping , Herbert Nicole , Yeom Soonja , Montgomery James
Published: November 2022

Student persistence and retention in STEM disciplines is an important yet complex and multi-dimensional issue confronting universities. Considering the rapid evolution of online pedagogy and virtual learning environments, we must rethink the factors that impact students’ decisions to stay or leave the current course. Learning analytics has demonstrated positive outcomes in higher education contexts and shows promise in enhancing academic success and retention. However, the retention factors in learning analytics practice for STEM education have not been fully reviewed and revealed. The purpose of this systematic review is to contribute to this research gap by reviewing the empirical evidence on factors affecting student persistence and retention in STEM disciplines in higher education and how these factors are measured and quantified in learning analytics practice. By analysing 59 key publications, seven factors and associated features contributing to STEM retention using learning analytics were comprehensively categorised and discussed. This study will guide future research to critically evaluate the influence of each factor and evaluate relationships among factors and the feature selection process to enrich STEM retention studies using learning analytics.
Training and Preparing Tomorrow’s Workforce for the Fourth Industrial Revolution
Authors: Bühler Michael Max , Jelinek Thorsten , Nübel Konrad
Published: November 2022

We call for a paradigm shift in engineering education. We are entering the era of the Fourth Industrial Revolution (“4IR”), accelerated by Artificial Intelligence (“AI”). Disruptive changes affect all industrial sectors and society, leading to increased uncertainty that makes it impossible to predict what lies ahead. Therefore, gradual cultural change in education is no longer an option to ease social pain. The vast majority of engineering education and training systems, which have remained largely static and underinvested for decades, are inadequate for the emerging 4IR and AI labour markets. Nevertheless, some positive developments can be observed in the reorientation of the engineering education sector. Novel approaches to engineering education are already providing distinctive, technology-enhanced, personalised, student-centred curriculum experiences within an integrated and unified education system. We need to educate engineering students for a future whose key characteristics are volatility, uncertainty, complexity and ambiguity (“VUCA”). Talent and skills gaps are expected to increase in all industries in the coming years. The authors argue for an engineering curriculum that combines timeless didactic traditions such as Socratic inquiry, mastery-based and project-based learning and first-principles thinking with novel elements, e.g., student-centred active and e-learning with a focus on case studies, as well as visualization/metaverse and gamification elements discussed in this paper, and a refocusing of engineering skills and knowledge enhanced by AI on human qualities such as creativity, empathy and dexterity. These skills strengthen engineering students’ perceptions of the world and the decisions they make as a result. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent collaborators who navigate increasingly complex multistakeholder ecosystems.
How Do Prospective Teachers Address Pupils’ Ideas during School Practices?
Authors: Valverde Pérez Magdalena , Esteve-Guirao Patricia , Banos-González Isabel
Published: November 2022

This paper assesses the coherence between the conceptions of prospective teachers about pupils’ ideas and how these are used in their educational proposals for primary school classrooms. For this purpose, three dimensions were analysed: The nature, utilisation, and change of ideas. In addition, two instruments were used: A questionnaire, to find out what prospective teachers think about pupils’ ideas, and the educational proposals they designed during their school practices. For the latter, qualitative content analysis was used to establish four levels according to the didactic approach on which they base the consideration of pupils’ ideas: Transmissive or the construction of ideas. The results show that, in all three dimensions, the conception of pupils’ ideas consistent with the construction of ideas orientation dominates. Nevertheless, their educational proposals do not show this orientation since the majority designed traditional educational proposals (Levels 1 and 2). Thus, there is no correlation between their conceptions about pupils’ ideas and how these are considered in their proposals. Besides, this analysis shows that an inadequate interpretation of the nature of pupils’ ideas could strongly condition how these ideas are considered in the teaching and learning process. The educational implications of these results in initial teacher training are discussed.
Higher Education Future in the Era of Digital Transformation
Authors: Akour Mohammad , Alenezi Mamdouh
Published: November 2022

A significant number of educational stakeholders are concerned about the issue of digitalization in higher educational institutions (HEIs). Digital skills are becoming more pertinent throughout every context, particularly in the workplace. As a result, one of the key purposes for universities has shifted to preparing future managers to address issues and look for solutions, including information literacy as a vital set of skills. The research of educational technology advances in higher education is now being discussed and debated, with various laws, projects, and tactics being offered. Digital technology has been a part of the lives of today’s children from the moment they are born. There are still many different types of digital divisions that exist in our society, and they affect the younger generation and their digital futures. Today’s students do not have the same level of preparation for the technology-rich society they will have. Universities and teaching should go through a significant digital transformation to fulfill the demands of today’s generation and the fully digitized world they will be living in. The COVID-19 pandemic has quickly and unexpectedly compelled HEIs and the educational system to engage in such a shift. In this study, we investigate the digital transformation brought about by COVID-19 in the fundamental education of the younger generation. Additionally, the study investigates the various digital divides that have emerged and been reinforced, as well as the potential roadblocks that have been reported along the way. In this paper, the study suggests that research into information management must better address students, their increasingly digitalized everyday lives, and basic education as key focus areas.
A Decade of Short Videos for Foreign Language Teaching and Learning: A Review
Authors: Zhang Yidi , Lucas Margarida , Pedro Luís
Published: November 2022

This literature review focuses on the use of short videos for foreign language (FL) teaching and learning from 2013 to 2022, a research area that has been attracting growing attention. The results were classified according to three categories based on the scope of the short videos in research: (1) short videos as a medium, (2) short videos as an intervention, and (3) short videos as the central focus of studies. Such a categorization enabled us to determine that short videos have become an independent research term in the field of FL teaching and learning and to describe current trends in this field. The intrinsic characteristics of short videos in current educational and multimedia environments are discussed, namely, the reasons why short videos are used in the classroom, as well as the potential of short videos as a learning resource created by young students and as an open educational resource (OER). Finally, we consider the differences between short videos and traditional audiovisual resources to highlight their innovative contributions to FL teaching and learning.
Perceptions of Behaviors Associated with ASD in Others: Knowledge of the Diagnosis Increases Empathy and Improves Perceptions of Warmth and Competence
Authors: Nestorowich Deven L. , Lupien Shannon P. , Madaus Knapp Vicki
Published: November 2022

Individuals with Autism Spectrum Disorder (ASD) often exhibit atypical social behaviors that some may perceive as odd or discomforting. Given that ASD is largely invisible, it may be difficult to understand why a person is displaying these atypical behaviors, leading to less favorable attitudes. The current study aimed to examine if having an explanation for an individual exhibiting behaviors associated with ASD could improve perceptions of warmth and competence, as well as the amount of empathy felt towards the individual. Participants (n = 82) were presented with a scenario involving two people, one of whom exhibited behaviors consistent with ASD. ASD diagnosis information was manipulated, such that half of the participants were told that the target was diagnosed with ASD, and the other half were given no diagnostic information. Afterwards, participants rated the target. Results indicated that having an explanation for the ASD-related behaviors led to higher ratings of warmth and competence and greater feelings of empathy. Furthermore, empathy mediated the relationship between having the diagnostic information and target ratings. Thus, having an explanation for someone’s behavior may lead to greater feelings of empathy and improve perceptions and understanding. This has important implications for improving education and awareness about behaviors associated with ASD as well as for making the decision of whether or not to disclose one’s diagnosis.
Overview of Machine Learning and Deep Learning Approaches for Detecting Shockable Rhythms in AED in the Absence or Presence of CPR
Authors: Dahal Kamana , Ali Mohd. Hasan
Published: November 2022

Sudden Cardiac Arrest (SCA) is one of the leading causes of death worldwide. Therefore, timely and accurate detection of such arrests and immediate defibrillation support for the victim is critical. An automated external defibrillator (AED) is a medical device that diagnoses the rhythms and provides electric shocks to SCA patients to restore normal heart rhythms. Machine learning and deep learning-based approaches are popular in AEDs for detecting shockable rhythms and automating defibrillation. There are some works in the literature for reviewing various machine learning (ML) and deep learning (DL) algorithms for shockable ECG signals in AED. Starting in 2017 and beyond, different DL algorithms were proposed for the AED. This paper provides an overview of AED, including its circuit diagram and application to SCA patients. It also presents the most up-to-date ML and DL approaches for detecting shockable rhythms in AEDs without cardiopulmonary resuscitation (CPR) or during CPR. It also provides a performance comparison of these approaches and discusses other researchers’ results that lay the foundation for researchers to delve in-depth. Furthermore, the research gaps and recommendations for future research provided in this review paper will be helpful to the researchers, scientists, and engineers in conducting further research in this critical field.
Deep Learning Approach for Automatic Segmentation and Functional Assessment of LV in Cardiac MRI
Authors: Bhan Anupama , Mangipudi Parthasarathi , Goyal Ayush
Published: November 2022

The early diagnosis of cardiovascular diseases (CVDs) can effectively prevent them from worsening. The source of the disease can be effectively detected through analysis with cardiac magnetic resonance imaging (CMRI). The segmentation of the left ventricle (LV) in CMRI images plays an indispensable role in the diagnosis of CVDs. However, the automated segmentation of LV is a challenging task, as it is confused with neighboring regions in the cardiac MRI. Deep learning models are effective in performing such complex segmentation because of the high performing convolutional neural networks (CNN). However, since segmentation using CNN involves the pixel-level classification of the image, it lacks the contextual information that is highly desirable in analyzing medical images. In this research, we propose a modified U-Net model to accurately segment the LV using context-enabled segmentation. The proposed model achieves the automatic segmentation and quantitative assessment of LV. The proposed model achieves the state-of-the-art accuracy by effectively utilizing various hyperparameters, such as batch size, batch normalization, activation function, loss function and dropout. Our method demonstrated a statistical significance in the endo- and epicardial walls with a dice score of 0.96 and 0.93, respectively, an average perpendicular distance of 1.73 and percentage of good contours of 96.22 were achieved. Furthermore, a high positive correlation of 0.98 between the clinical parameters, such as ejection fraction, end diastolic volume (EDV), end systolic volume (ESV) and gold standard was obtained.
Research on the Determination Method of Aircraft Flight Safety Boundaries Based on Adaptive Control
Authors: Wang Miaosen , Xue Yuan , Wang Kang
Published: November 2022

Icing is one of the main external environmental factors causing loss of control (LOC) in aircraft. To ensure safe flying in icy conditions, modern large aircraft are all fitted with anti-icing systems. Although aircraft anti-icing technology is becoming more sophisticated as research continues to expand and deepen, the scope of protection provided by anti-icing systems based on existing anti-icing technology is still relatively limited, and in practice, it is difficult to avoid flying with ice even when the anti-icing system is switched on. Therefore, it is necessary to consider providing additional safety strategies in addition to the anti-icing system, i.e., to consider icing safety from the aerodynamic, stability, and control points of view during the aircraft design phase, and to build a complete ice-tolerant protection system combining aerodynamic design methods, flight control strategies and implementation equipment. Based on the modern control theory of adaptive control, this paper presents a new method of envelope protection in icing situations based on a case study of icing, which has the advantages of strong real-time performance and good robustness, and has high engineering application value.
An Event Matching Energy Disaggregation Algorithm Using Smart Meter Data
Authors: Liaqat Rehan , Sajjad Intisar Ali
Published: November 2022

Energy disaggregation algorithms disintegrate aggregate demand into appliance-level demands. Among various energy disaggregation approaches, non-intrusive load monitoring (NILM) algorithms requiring a single sensor have gained much attention in recent years. Various machine learning and optimization-based NILM approaches are available in the literature, but bulk training data and high computational time are their respective drawbacks. Considering these drawbacks, we devised an event matching energy disaggregation algorithm (EMEDA) for NILM of multistate household appliances using smart meter data. Having limited training data, K-means clustering was employed to estimate appliance power states. These power states were accumulated to generate an event database (EVD) containing all combinations of appliance operations in their various states. Prior to matching, the test samples of aggregate demand events were decreased by event-driven data compression for computational effectiveness. The compressed test events were matched in the sorted EVD to assess the contribution of each appliance in the aggregate demand. To counter the effects of transient spikes and/or dips that occurred during the state transition of appliances, a post-processing algorithm was also developed. The proposed approach was validated using the low-rate data of the Reference Energy Disaggregation Dataset (REDD). With better energy disaggregation performance, the proposed EMEDA exhibited reductions of 97.5 and 61.7% in computational time compared with the recent smart event-based optimization and optimization-based load disaggregation approaches, respectively.
Fog Computing: Strategies for Optimal Performance and Cost Effectiveness
Authors: Alraddady Sara , Soh Ben , AlZain Mohammed A. , Li Alice S.
Published: November 2022

The proliferation of IoT devices has amplified the challenges for cloud computing, causing bottleneck congestion which affects the delivery of the required quality of service. For some services that are delay sensitive, response time is extremely critical to avoid fatalities. Therefore, Cisco presented fog computing in 2012 to overcome such limitations. In fog computing, data processing happens geographically close to the data origin to reduce response time and decrease network and energy consumption. In this paper, a new fog computing model is presented, in which a management layer is placed between the fog nodes and the cloud data centre to manage and control resources and communication. This layer addresses the heterogeneity nature of fog computing and complex connectivity that are considered challenges for fog computing. Sensitivity analysis using simulation is conducted to determine the efficiency of the proposed model. Different cluster configurations are implemented and evaluated in order to reach the optimal clustering method. The results show that the management layer improves QoS, with less bandwidth consumption and execution time.
Efficient Decoder for Turbo Product Codes Based on Quadratic Residue Codes
Authors: Dong Jie , Li Yong , Liu Rui , Guo Taolin , Lau Francis C. M.
Published: November 2022

In this letter, we study turbo product codes with quadratic residue codes (called QR-TPCs) as the component codes. We propose an efficient decoder based on Chase-II algorithm with two convergence conditions for the iterative decoding of QR-TPCs. For each row and column, the Chase-II decoder will stop immediately when one of the conditions is met. The simulation results show that the proposed algorithm has a lower computational complexity compared with existing decoding methods. Moreover, a comparison with 5G low-density parity-check codes shows that the proposed turbo product codes have better performance for short code lengths.
Attributation Analysis of Reinforcement Learning-Based Highway Driver
Authors: Pankiewicz Nikodem , Kowalczyk Paweł
Published: November 2022

While machine learning models are powering more and more everyday devices, there is a growing need for explaining them. This especially applies to the use of deep reinforcement learning in solutions that require security, such as vehicle motion planning. In this paper, we propose a method for understanding what the RL agent’s decision is based on. The method relies on conducting a statistical analysis on a massive set of state-decisions samples. It indicates which input features have an impact on the agent’s decision and the relationships between the decisions, the significance of the input features, and their values. The method allows us to determine whether the process of making a decision by the agent is coherent with human intuition and what contradicts it. We applied the proposed method to the RL motion planning agent which is supposed to drive a vehicle safely and efficiently on a highway. We find out that making such an analysis allows for a better understanding of the agent’s decisions, inspecting its behavior, debugging the ANN model, and verifying the correctness of the input values, which increases its credibility.
Optimising Health Emergency Resource Management from Multi-Model Databases
Authors: Arias Juan C. , Cubillas Juan J. , Ramos Maria I.
Published: November 2022

The health care sector is one of the most sensitive sectors in our society, and it is believed that the application of specific and detailed database creation and design techniques can improve the quality of patient care. In this sense, better management of emergency resources should be achieved. The development of a methodology to manage and integrate a set of data from multiple sources into a centralised database, which ensures a high quality emergency health service, is a challenge. The high level of interrelation between all of the variables related to patient care will allow one to analyse and make the right strategic decisions about the type of care that will be needed in the future, efficiently managing the resources involved in such care. An optimised database was designed that integrated and related all aspects that directly and indirectly affected the emergency care provided in the province of Jaén (city of Jaén, Andalusia, Spain) over the last eight years. Health, social, economic, environmental, and geographical information related to each of these emergency services was stored and related. Linear and nonlinear regression algorithms were used: support vector machine (SVM) with linear kernel and generated linear model (GLM), and the nonlinear SVM with Gaussian kernel. Predictive models of emergency demand were generated with a success rate of over 90%.
Adaptive Kernel Density Estimation for Traffic Accidents Based on Improved Bandwidth Research on Black Spot Identification Model
Authors: Ge Huimin , Dong Lei , Huang Mingyue , Zang Wenkai , Zhou Lijun
Published: November 2022

At present, the total length of accident blackspot accounts for 0.25% of the total length of the road network, while the total number of accidents that occurred at accident black spots accounts for 25% of the total number of accidents on the road network. This paper describes a traffic accident black spot recognition model based on the adaptive kernel density estimation method combined with the road risk index. Using the traffic accident data of national and provincial trunk lines in Shanghai and ArcGIS software, the recognition results of black spots were compared with the recognition results of the accident frequency method and the kernel density estimation method, and the clustering degree of recognition results of adaptive kernel density estimation method were analyzed. The results show that: the accident prediction accuracy index values of the accident frequency method, kernel density estimation method, and traffic accident black spot recognition model were 14.39, 16.36, and 18.25, respectively, and the lengths of the traffic accident black spot sections were 184.68, 162.45, and 145.57, respectively, which means that the accident black spot section determined by the accident black spot recognition model was the shortest and the number of traffic accidents identified was the largest. Considering the safety improvement budget of 20% of the road length, the adaptive kernel density estimation method could identify about 69% of the traffic accidents, which was 1.13 times and 1.27 times that of the kernel density estimation method and the accident frequency method, respectively.
Regulation of Polyhomeotic Condensates by Intrinsically Disordered Sequences That Affect Chromatin Binding
Authors: Kapur Ibani , Boulier Elodie L. , Francis Nicole J.
Published: November 2022

The Polycomb group (PcG) complex PRC1 localizes in the nucleus in condensed structures called Polycomb bodies. The PRC1 subunit Polyhomeotic (Ph) contains an oligomerizing sterile alpha motif (SAM) that is implicated in both PcG body formation and chromatin organization in Drosophila and mammalian cells. A truncated version of Ph containing the SAM (mini-Ph) forms phase-separated condensates with DNA or chromatin in vitro, suggesting that PcG bodies may form through SAM-driven phase separation. In cells, Ph forms multiple small condensates, while mini-Ph typically forms a single large nuclear condensate. We therefore hypothesized that sequences outside of mini-Ph, which are predicted to be intrinsically disordered, are required for proper condensate formation. We identified three distinct low-complexity regions in Ph based on sequence composition. We systematically tested the role of each of these sequences in Ph condensates using live imaging of transfected Drosophila S2 cells. Each sequence uniquely affected Ph SAM-dependent condensate size, number, and morphology, but the most dramatic effects occurred when the central, glutamine-rich intrinsically disordered region (IDR) was removed, which resulted in large Ph condensates. Like mini-Ph condensates, condensates lacking the glutamine-rich IDR excluded chromatin. Chromatin fractionation experiments indicated that the removal of the glutamine-rich IDR reduced chromatin binding and that the removal of either of the other IDRs increased chromatin binding. Our data suggest that all three IDRs, and functional interactions among them, regulate Ph condensate size and number. Our results can be explained by a model in which tight chromatin binding by Ph IDRs antagonizes Ph SAM-driven phase separation. Our observations highlight the complexity of regulation of biological condensates housed in single proteins.
Probiotic Properties of Lactobacillus fermentum InaCC B1295 Encapsulated by Cellulose Microfiber from Oil Palm Empty Fruit Bunches
Authors: Pato Usman , Yusmarini  , Riftyan Emma , Rossi Evy , Hidayat Rahmad , Anjani Sandra Fitri , Riadi Nabila , Octaviani Ika Nur , Agrina  , Syukri Daimon , Surono Ingrid Suryanti
Published: November 2022

This study aims at an in vitro characterization of the acid and bile tolerance of Lactobacillus fermentum InaCC B1295 (LFB1295) encapsulated with hydrogel cellulose microfibers (CMF) from oil palm empty fruit bunches (OPEFBs). The viability at different storage temperatures was assessed. The experimental design used in this research was an in vitro trial. The microencapsulated probiotic was stored at 25 °C and 4 °C for 28 days. LFB1295 encapsulated with cellulose microfiber hydrogel from OPEFB showed a stable viability of probiotic bacteria at pH 2 and 0.5% (m/v) oxgall. In addition, the microencapsulation maintained the viability at 25 °C and 4 °C at 0, 14, and 28 days. The characterization of the encapsulant CMF-OPEFB showed that the thickness of CMF was in the range of 5–15 μm, and XRD patterns showed that CMF was of the cellulose I type with a crystallinity index of 77.08%. Based on its resistance to hydrogen peroxide, ability to scavenge DPPH radicals, and activity in scavenging hydroxyl radicals, LFB1295 encapsulated with CMF hydrogel of OPEFB exhibits antioxidant properties as good as the scavenging ability of DPPH radicals with IC50 of 36.880, 188.530, and 195.358 µg/mL, respectively, during storage for 0, 14, and 28 days at room and refrigerated temperature. Furthermore, hydroxyl radicals (HR)-scavenging activity showed an increased inhibition along with the increasing concentration of the Fenton reaction and decreasing concentration of cell-free supernatant (CFS) during storage time. In vitro safety tests, including hemolytic activity, biogenic amines, cytolysin, and gelatinase production, showed that the encapsulated LFB1295 was safe to use as a probiotic. The results of the inhibitory activity against hydrogen peroxide LFB1295 show that the higher the concentration of H2O2, the lower the inhibition value during 28 days of storage. Based on the storage temperature, the inhibition of LAB against H2O2 based on different storage temperatures showed a better level of the inhibition at cold temperatures compared to at room temperature.
Understanding the Development of Heterocyclic Aromatic Amines in Fried Bacon and in the Remaining Oil after Pan-Frying in Five Different Vegetable Oils
Authors: Du Hongzhen , Wang Ziyi , Li Yuexin , Liu Qian , Chen Qian , Kong Baohua
Published: November 2022

The physicochemical properties of five vegetable oils (peanut, corn, rapeseed, sunflower seed, and soybean) and their impact on the development of heterocyclic aromatic amines (HAAs) in pan-fried bacon and in the remaining oil were investigated. Corn oil led to the lowest total free amino acids (FAAs) contents and glucose content of fried bacon (p < 0.05) and rapeseed oil led to the lowest creatine content of fried bacon (p < 0.05). Bacon fried in corn oil had the highest HAA contents (p < 0.05). The total HAA contents of the oils after frying were lowest in rapeseed and soybean oils (p < 0.05). The type of vegetable oil used affected the color of the fried bacon but not the flavor and taste (p < 0.05). To reduce the HAA concentrations of fried bacon, the type of vegetable oil should be considered.
The Effect of Spice Powders on Bioactive Compounds, Antioxidant Activity, Phenolic Components, Fatty Acids, Mineral Contents and Sensory Properties of “Keşkek”, Which Is a Traditional Food
Authors: Özcan Mehmet Musa
Published: November 2022

“Keşkek”, which is a dish of Western Anatolia, Thrace, the Eastern Anatolia Region, the Black Sea and Central Anatolia, is a traditional dish made mainly of split wheat and meat—although it varies according to the regions in Anatolia—which is usually made at weddings and holidays. In this study, the effects of thyme, coriander and cumin spices on the fat content, bioactive properties, phenolic component, fatty acid composition, mineral contents and sensory properties of “Keşkek” were investigated. The oil yields of “Keşkek” types were determined to be between 14.90 (control) and 21.20% (with cumin). Total phenolic and flavonoid contents of “Keşkek” types’ added spices were established as between 7.02 (control) and 77.10 mg/100 g Gallic Acid Equivalent (GAE) (with thyme) to 20.24 (control) and 132.14 mg quercetin equivalent (QE)/100 g (with thyme), respectively. Moreover, the antioxidant activity values of “Keşkek” samples varied between 0.04 (control) and 2.78 mmol Trolox Equivalent (TE)/kg (with thyme). Among these phenolic constituents, gallic acid was the most abundant, followed by catechin, rutin and 3,4-dihydroxybenzoic acid, in descending order. Oleic and linoleic acid contents of the “Keşkek” oils were detected between 25.51 (with thyme) and 30.58% (with cumin) to 38.28 (with cumin) and 48.49% (control), respectively. P, K, Mg and S were the major minerals of “Keşkek” samples. Considering the sensory characteristics of the “Keşkek” samples, “Keşkek” with thyme was appreciated, followed by “Keşkek” with cumin and “control and Keşkek” with coriander in decreasing order.
Factors Influencing Rooibos Tea Certification and Quality Control for Smallholder Farmers in South Africa
Authors: Liu Aijun , Ka Makhaya Siphiwe Charmaine , Osewe Maurice
Published: November 2022

This study aimed to identify factors that influence the decisions of rooibos farmers in South Africa to implement certification and quality assurance systems. The study was conducted in the Western Cape region of South Africa. A structured questionnaire was distributed to 300 farmers in the form of interviews. In addition, an analysis of previously published data was also used. Results showed that membership in an association, land tenure, rooibos tea farm size, and education level were the main determinants of implementing certifications and quality assurance systems. Membership in the association and land tenure significantly negatively affected the adoption of certification. In contrast, farm size and level of education, translating to knowledge of certification systems, tended to have a significant positive effect on adoption. Continuous education, awareness of the process of certification and quality assurance systems, and the formation of farmers’ support systems are recommended to improve the impact of smallholder rooibos farmers in the industry.
The Use of Saccharomyces cerevisiae Supplemented with Intracellular Magnesium Ions by Means of Pulsed Electric Field (PEF) in the Process of Bread Production
Authors: Pankiewicz Urszula , Zielińska Ewelina , Sobota Aldona , Wirkijowska Anna
Published: November 2022

Bread was supplemented with magnesium through an addition of yeasts subjected to the effect of PEF at optimised parameters to obtain the maximum bioaccumulation of magnesium in cells. Bread produced with the use of yeasts supplemented with magnesium by means of PEF was characterised by its highest content, at 39.3 mg/100 g, which was higher by 50% and 24%, respectively, compared to the control bread sample with an admixture of yeasts cultured without any addition of magnesium and with no PEF treatment and to the control bread sample with an admixture of yeasts cultured with an addition of magnesium but no PEF treatment. The addition of yeasts supplemented with magnesium using PEF in bread production did not cause any statistically significant changes in the chemical composition of any of the analysed samples. However, statistically significant changes were noted in the technological properties of breads produced with an admixture of yeasts supplemented with magnesium by means of PEF treatment. An increase of moisture to 54.03 ± 0.29% led to a reduction of the total baking loss. No statistically significant differences were noted in the bread volume in samples K1, K2, and P, varying from 239 to 269 cm3/100 g.
Analysis and Screening of Commercialized Protein Supplements for Sports Practice
Authors: Rodriguez-Lopez Paloma , Rueda-Robles Ascensión , Sánchez-Rodríguez Leticia , Blanca-Herrera Rosa María , Quirantes-Piné Rosa María , Borrás-Linares Isabel , Segura-Carretero Antonio , Lozano-Sánchez Jesús
Published: November 2022

Recent years have seen a rise in the popularity of the consumption of sports-related supplements. However, the hypothesis is raised that it is necessary to analyze the quality aspects of these supplements in relation to the information provided on the label, to avoid associated risks and obtain the greatest possible benefit from their consumption. Therefore, the aim of this study has been to carry out an analysis or screening of the protein supplements that are currently marketed in Spain. We analyzed the labels of 52 protein sports supplements available both in physical stores and online. The analysis consisted of addressing three relevant aspects considering the labeling: (a) the legislative framework in which the supplements are marketed, (b) the quality of the protein, and (c) the presence of other ingredients according to the specifications of the label. In the legislative context, there do not seem to be any specific regulations to guarantee consumer protection, which can lead to unfair practices and misleading advertising. Most of the supplements analyzed to comply with the requirements of their current regulations. However, claims about their benefits that are not allowed under European legislation have been found in some of them. Regarding composition and according to label information, the supplements have been found to provide a sufficient dose of protein in terms of recommended protein intake per serving. Regarding the presence of other ingredients and according to the information on the label, most of them, except for egg supplements, contain other ingredients. Colostrum was also found in one of the supplements evaluated. The conclusions of the study reveal that, due to a lack of knowledge or misleading advertising practices, supplements are often not used properly. The information provided is essential for both professionals and consumers to avoid the risks associated with consumption, such as unintentional doping, interactions between ingredients that reduce the quality of the supplement, and consumption of supplements inappropriately, among others.
Effects of Bacillus subtilis BSNK-5-Fermented Soymilk on the Gut Microbiota by In Vitro Fecal Fermentation
Authors: Gao Yaxin , Hou Lizhen , Hu Miao , Li Danfeng , Tian Zhiliang , Wen Wei , Fan Bei , Li Shuying , Wang Fengzhong
Published: November 2022

The gut microbiota of soymilk intervention is beneficial to maintaining human health. Bacillus subtilis fermented soymilk has brought much interest, due to its richness of thrombolytic nattokinase and the strain of potential probiotic properties. In this study, soymilk was fermented by B. subtilis BSNK-5, and the BSNK-5-fermented soymilk (SMF) on the production of short chain fatty acids (SCFAs) and the regulation of fecal microbiota was initially evaluated by in vitro fecal fermentation. SMF supplementation obviously increased the levels of SCFAs from 32.23 mM to 49.10 mM, especially acetic acid, propionic acid, and isobutyric acid. Additionally, SMF changed the composition and microbial diversity of gut microbiota. After 24 h of anaerobic incubation in vitro, SMF decreased the Firmicutes/Bacteroidota ratio favoring weight loss, increased Lachnospiraceae_UCG-004 and the other beneficial bacteria producing SCFAs, as well as suppressing pathogenic Streptococcus genus. These results revealed the potential use of BSNK-5-fermented soymilk as a potential candidate to promote gut health.
Structural Characteristics and Emulsifying Properties of Soy Protein Isolate Glycated with Galacto-Oligosaccharides under High-Pressure Homogenization
Authors: Xie Yitong , Liu Rongxu , Zhang Changge , Liu Danyi , Han Jianchun
Published: November 2022

This study explored the Maillard reaction process during the glycation of soy protein isolate (SPI) with galacto-oligosaccharides (GOSs) under high-pressure homogenization (HPH) and its effects on the emulsifying properties of SPI. SPI-GOS glycation under moderate pressure (80 MPa) significantly inhibited the occurrence and extent of the Maillard reaction (p < 0.05), but homogenization pressures in the range of 80–140 MPa gradually promoted this reaction. HPH caused a decrease in the surface hydrophobicity of the glycated protein, an increase in the abundance of free sulfhydryl groups, unfolding of the protein molecular structure, and the formation of new covalent bonds (C=O, C=N). Additionally, the particle size of emulsions created with SPI-GOS conjugates was reduced under HPH, thus improving the emulsifying properties of SPI. A reduction in particle size (117 nm), enhanced zeta potential (−23 mV), and uniform droplet size were observed for the emulsion created with the SPI-GOS conjugate prepared at 120 MPa. The conformational changes in the glycated protein supported the improved emulsification function. All results were significantly different (p < 0.05). The study findings indicate that HPH provides a potential method for controlling glycation and improving the emulsifying properties of SPI.