bluuebunny/crossref_metadata_2025 huggingface dataset:
The Participation of Teachers in Greece in Outdoor Education Activities and the Schools’ Perceptions of the Benefits to Students
Authors: Chrysomalidou Anastasia , Takos Ioannis , Spiliotis Ioannis , Xofis Panteleimon
Published: July 2024

International research highlights the potentially valuable contribution of outdoor education to the healthy development and proper holistic education of students. Among the various benefits that students gain from participating in outdoor activities are the mitigation of symptoms of Attention Deficit Hyperactivity Disorder (ADHD), improved respiration, memory improvement, skills development and others. Despite the well-documented contribution of such activities to children’s wellbeing, there is an increasing trend of younger children lacking contact with nature. The current study investigates to what extent teachers in Greece, at schools where students aged 6–18 attend, provide opportunities for outdoor activities to their students. Furthermore, it investigates the teacher’s perceptions of the benefits the students gain from such activities, based on their personal experience and the experience of other co-teachers in their school. The results presented in this study indicate that the percentage of teachers who choose outdoor activities during the educational process in Greece is rather low, although they identify that such activities provide significant benefits to students. Based on the perceptions of teachers regarding the mental, cognitive and physical benefits that students gain from outdoor activities a positive association was found between the participation of students in such activities and these benefits. Therefore, this study reveals that it is of significant importance to increase the number of opportunities for students’ participation in outdoor learning activities, by supporting teachers, creating learning communities with them and empowering them to provide more outdoor learning opportunities.
Introducing Security Mechanisms in OpenFog-Compliant Smart Buildings
Authors: Martín Toral Imanol , Calvo Isidro , Villar Eneko , Gil-García Jose Miguel , Barambones Oscar
Published: July 2024

Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes the use of free open source (FOS) technologies and has been identified for use in smart buildings. However, smart building systems may present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms in this domain is critical but not trivial. It complicates the design and operation of the applications, increasing the cost of the deployed systems. In addition, difficulties may arise in finding qualified cybersecurity personnel. OpenFog identifies the security requirements of the applications, although it does not describe clearly how to implement them. This article presents a scalable architecture, based on the OpenFog reference architecture, to provide security by design in buildings of different sizes. It adopts FOS technologies over low-cost IoT devices. Moreover, it presents guidelines to help developers create secure applications, even if they are not security experts. It also proposes a selection of technologies in different layers to achieve the security dimensions defined in the X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, based on low-cost smart nodes, was deployed in the Faculty of Engineering of Vitoria-Gasteiz to illustrate the implementation of the presented approach. The operation of the IEQ system was analyzed using software tools frequently used to find vulnerabilities in IoT applications. The use of state-of-the-art security mechanisms such as encryption, certificates, protocol selection and network partitioning/configuration in the OpenFog-based architecture improves smart building security.
TA-Quatro: Soft Error-Resilient and Power-Efficient SRAM Cell for ADC-Less Binary Weight and Ternary Activation In-Memory Computing
Authors: Nguyen Thanh-Dat , Le Minh-Son , Pham Thi-Nhan , Chang Ik-Joon
Published: July 2024

Some applications, such as satellites, require ultralow power and high-radiation resilience. We developed a12Tsoft error-resilient SRAM cell, TA-Quatro, to deliver in-memory computing (IMC) for those applications. Based on our TA-Quatro cell, we implemented an IMC circuit to support binary weights and ternary activations in a single SRAM cell. Our simulation under 28 nm FD-SOI technology demonstrates that the TA-Quatro IMC circuit maintains good IMC stability at a scaled supply of 0.7Vand achieves ternary activation without needing analog-to-digital converters. These advancements significantly enhance the power efficiency of the proposed IMC circuit compared to state-of-the-art works.
Microwave Corona Breakdown Suppression of Microstrip Coupled-Line Filter Using Lacquer Coating
Authors: Ye Ming , Hu Shaoguang , Wang Rui , Zhang Yong , He Yongning
Published: July 2024

Due to its potential harm to space payload, microwave corona breakdown of microstrip circuits has attracted much attention. This work describes an efficient way to suppress corona breakdown. Since the corona breakdown threshold is determined by the highest electric field intensity at the surface of microstrip circuits, lacquer coating with a thickness of tens of microns is sprayed on top of microstrip circuits. The applied dielectric coating is used to move the discharge location away from the circuit’s surface, which is equivalent to reducing the highest electric field intensity on the interface of solid/air of the circuit and thus results in a higher breakdown threshold. Two designs of a classic coupled-line bandpass filter were used for verification. Corona experimental results at 2.5 GHz show that in the low-pressure range of interest (100 to 4500 Pa), a 5.3 dB improvement of the microwave corona breakdown threshold can be achieved for a filter with a narrowest gap of 0.2 mm, while its electrical performances like insertion loss and Q-factor are still acceptable. A threshold improvement prediction method is also presented and validated.
Benchmarking Time-Frequency Representations of Phonocardiogram Signals for Classification of Valvular Heart Diseases Using Deep Features and Machine Learning
Authors: Chambi Edwin M. , Cuela Jefry , Zegarra Milagros , Sulla Erasmo , Rendulich Jorge
Published: July 2024

Heart sounds and murmur provide crucial diagnosis information for valvular heart diseases (VHD). A phonocardiogram (PCG) combined with modern digital processing techniques provides a complementary tool for clinicians. This article proposes a benchmark different time–frequency representations, which are spectograms, mel-spectograms and cochleagrams for obtaining images, in addition to the use of two interpolation techniques to improve the quality of the images, which are bicubic and Lanczos. Deep features are extracted from a pretrained model called VGG16, and for feature reduction, the Boruta algorithm is applied. To evaluate the models and obtain more precise results, nested cross-validation is used. The best results achieved in this study were for the cochleagram with 99.2% accuracy and mel-spectogram representation with the bicubic interpolation technique, which reached 99.4% accuracy, both having a support vector machine (SVM) as a classifier algorithm. Overall, this study highlights the potential of time–frequency representations of PCG signals combined with modern digital processing techniques and machine learning algorithms for accurate diagnosis of VHD.
Decentralized Retrofit Model Predictive Control of Inverter-Interfaced Small-Scale Microgrids
Authors: Shojaee Milad , Azizi S. Mohsen
Published: July 2024

In recent years, small-scale microgrids have become popular in the power system industry because they provide an efficient electrical power generation platform to guarantee autonomy and independence from the power grid, which is a critical feature in cases of catastrophic events or remote areas. On the other hand, due to the short distances among multiple distribution generation systems in small-scale microgrids, the interconnection couplings among them increase significantly, which jeopardizes the stability of the entire system. Therefore, this work proposes a novel method to design decentralized robust controllers based on a retrofit model predictive control scheme to tackle the issue of instability due to the short distances among generation systems. In this approach, the retrofit model predictive controller receives the measured feedback signal from the interconnection current and generates a control command signal to limit the interconnection current to prevent instability. To design a retrofit controller, only the model of a robust closed-loop system, as well as an interconnection line, is required. The model predictive control signal is added in parallel to the control signal from the existing robust voltage source inverter controller. Simulation results demonstrate the superior performance of the proposed technique as compared with the virtual impedance and retrofit linear quadratic regulator techniques (benchmarks) with respect to peak-load demand, plug-and-play capability, nonlinear load, and inverter efficiency.
Improved 3D Object Detection Based on PointPillars
Authors: Kong Weiwei , Du Yusheng , He Leilei , Li Zejiang
Published: July 2024

Despite the recent advancements in 3D object detection, the conventional 3D point cloud object detection algorithms have been found to exhibit limited accuracy for the detection of small objects. To address the challenge of poor detection of small-scale objects, this paper adopts the PointPillars algorithm as the baseline model and proposes a two-stage 3D target detection approach. As a cutting-edge solution, point cloud processing is performed using Transformer models. Additionally, a redefined attention mechanism is introduced to further enhance the detection capabilities of the algorithm. In the first stage, the algorithm uses PointPillars as the baseline model. The central concept of this algorithm is to transform the point cloud space into equal-sized columns. During the feature extraction stage, when the features from all cylinders are transformed into pseudo-images, the proposed algorithm incorporates attention mechanisms adapted from the Squeeze-and-Excitation (SE) method to emphasize and suppress feature information. Furthermore, the 2D convolution of the traditional backbone network is replaced by dynamic convolution. Concurrently, the addition of the attention mechanism further improves the feature representation ability of the network. In the second phase, the candidate frames generated in the first phase are refined using a Transformer-based approach. The proposed algorithm applies channel weighting in the decoder to enhance channel information, leading to improved detection accuracy and reduced false detections. The encoder constructs the initial point features from the candidate frames for encoding. Meanwhile, the decoder applies channel weighting to enhance the channel information, thereby improving the detection accuracy and reducing false detections. In the KITTI dataset, the experimental results verify the effectiveness of this method in small objects detection. Experimental results show that the proposed method significantly improves the detection capability of small objects compared with the baseline PointPillars. In concrete terms, in the moderate difficulty detection category, cars, pedestrians, and cyclists average precision (AP) values increased by 5.30%, 8.1%, and 10.6%, respectively. Moreover, the proposed method surpasses existing mainstream approaches in the cyclist category.
A New Mitigation Method against DRDoS Attacks Using a Snort UDP Module in Low-Specification Fog Computing Environments
Authors: Kang Ho-Seok , Kim KangTae , Kim Sung-Ryul
Published: July 2024

Current cloud computing expects to face huge traffic costs, data loads, and high latency due to the explosion of data from devices as the IoT and 5G technology evolve. Fog computing has emerged to overcome these issues. It deploys small fog servers at the edge of the network to process critical data in real time while sending the remaining secondary tasks to the central cloud, instead of sending massive amounts of data to the cloud. With the rise in fog computing, among traditional security threats, distributed denial-of-service (DDoS) attacks have become the major threat to availability. This is especially true for fog computing, where real-time processing is critical; there are many fog servers, and the processing power is relatively low. Distributed reflection denial-of-service (DRDoS), one of the frequently used DDoS attack techniques, is an amplification attack that can be used on a small or large scale. It is widely used in attack tools due to its easy configuration. This study analyzes the characteristics of fog computing, the characteristics of DRDoS attacks, and the advantages and disadvantages of existing countermeasures. Based on these analyses, this study proposes a model that could effectively mitigate attacks even on low-specification fog servers by combining a modified Snort module with reduced functionality, simple pattern matching, and filtering distribution using Anycast. This mitigation algorithm has a simple structure rather than a complex filtering structure. To achieve this goal, this study virtually implemented the corresponding fog IoT environment. In spite of its simple structure, it proved that the fog server could secure availability even under DRDoS attacks by implementing and validating the mitigation model.
Improved Design of a SiC MOSFET Gate Drive with Crosstalk Suppression Capability
Authors: Hao Jiade , Meng Runquan , Guo Zhuoyan
Published: July 2024

For high-frequency switching applications, silicon carbide (SiC) devices are more suitable than silicon-based devices, which is conducive to improving the efficiency and power density of power electronic equipment. However, as the switching frequency increases, the influence of parasitic parameters on the switching characteristics of devices becomes increasingly apparent. When SiC metal-oxide-semiconductor field-effect transistors (MOSFETs) are applied in bridge circuits, the crosstalk problem easily occurs with the complementary conduction of upper and lower transistors, which seriously limits the promotion of SiC MOSFETs. However, the existing crosstalk suppression drive circuit tends to increase the switching loss, switching delay, and control complexity; therefore, a gate drive with crosstalk suppression capability is proposed. In this paper, the gate drive has two features: a negative voltage to shut down the SiC MOSFET; and an adjustment of the gate-source equivalent impedance. To accomplish this goal, the mechanism of crosstalk voltage generation is analyzed. Furthermore, the operation principle of the gate drive is analyzed, and the parameters of the gate drive are designed. Eventually, the proposed gate drive is verified by an LTspice simulation and experimental platform. The results prove that the gate drive can suppress the crosstalk voltage without affecting the switching speed.
Expert System for Extracting Hidden Information from Electronic Documents during Outgoing Control
Authors: Tan Lingling , Yi Junkai
Published: July 2024

For confidential and sensitive electronic documents within enterprises and organizations, failure to conduct proper checks before sending can easily lead to incidents such as security degradation. Sensitive information transmission has become one of the main ways of internal data leakage. However, existing methods or systems cannot extract hidden data and do not support mining the binary structure of hidden information in files. In this paper, an expert system for mining electronic document hidden information is designed for various office documents, compressed files, and image files. This system can quickly mine various forms of concealment in more than 40 common types of electronic documents and extract hidden information, such as file type tampering, encryption concealment, structure concealment, redundant data concealment, etc. Additionally, feature information in the binary structure of the document is extracted to form a feature information base. Subsequently, an expert knowledge base is constructed. Finally, a hidden information mining engine is designed using the knowledge base to realize the security control of corresponding outgoing files with good expansibility and integration. By controlling the exit of documents through scanning for sensitive information contained within them, the security level contents can be obtained effectively, avoiding data leakage by technical means while also facilitating forensics. The actual test result proves that this system can quickly mine various means used to conceal information, extract their respective information, and provide a fast, practical diagnostic way for outgoing control over these electronic documents.
Developing a Symbiotic Fermented Milk Product with Microwave-Treated Hawthorn Extract
Authors: Utebaeva Aidana , Gabrilyants Eleonora , Abish Zhansaya
Published: July 2024

The rising interest in functional foods has increased the use of probiotics and prebiotics in fermented dairy products to enhance gut health. This study focuses on developing a symbiotic fermented milk product using Lactobacillus acidophilus and Bifidobacterium bifidum activated with hawthorn extract as a prebiotic. Three versions of the product were tested: a control and two variants with B. bifidum activated with 10−5 g/cm3 and 10−10 g/cm3 hawthorn extract, respectively. Key characteristics such as microbiological safety, sensory properties, amino acid profile, vitamin and mineral content, antioxidant capacity, and nutritional values were evaluated. Results showed that products enriched with hawthorn extract had favorable sensory properties and sustained high levels of lactic acid bacteria while being free of pathogens. Product 1 based on L. acidophilus and enriched with B. bifidum activated with hawthorn extract at a concentration of 10−5 g/cm3 demonstrated significant increases in L. acidophilus (24.1%) and B. bifidum (14.7%) after 7 days compared to the control. Both enriched products exhibited slower titratable acidity increases and higher viscosities over 14 days, indicating better preservation and texture stability. Product 1 was notably enriched with essential amino acids, vitamins, and minerals, alongside enhanced antioxidant properties due to increased flavonoid content. The technology developed ensures probiotic viability at 109–1010 CFU/cm3 after 14 days, making it viable for dairy production.
Plant-Based Meat Analogues and Consumer Interest in 3D-Printed Products: A Mini-Review
Authors: Miller Owen , Scarlett Christopher J. , Akanbi Taiwo O.
Published: July 2024

The markets for plant-based meat analogues (PBMAs) are growing worldwide, showing the increasing consumer demand for and acceptance of these new products. Three-dimensional (3D) food printing is a new technology with huge potential for printing products customised to suit consumers’ wants and needs. There is a broad acceptance from consumers regarding the safety and desirability of consuming food products that are produced using 3D printing. As this is a new technology, consumers must be provided with relevant information from a trusted source, with further research needing to be conducted within the context of the identified market and culture. By embracing the strength of customisation of 3D printing and coupling this with the global demand for plant-based products, 3D printed PBMAs could be a future challenger to the currently popular production method of extrusion. Therefore, this article reviews consumer interests in PBMAs and summarises opportunities for using 3D printing technology to produce plant-based meat analogues.
Consumer Awareness, Perceptions and Avoidance of Ultra-Processed Foods: A Study of UK Adults in 2024
Authors: Robinson Eric , Cummings Jenna R. , Gough Thomas , Jones Andrew , Evans Rebecca
Published: July 2024

Background: Ultra-processed food (UPF) is currently not included in most countries’ dietary guidance. However, there may be growing public interest and consumer avoidance of UPF due to media reporting of studies on the negative health outcomes associated with UPFs. Methods: We surveyed 2386 UK adults (M age = 45 years, 50% female) during February–April 2024. Participants completed measures on awareness of the term UPF, whether the UPF status of foods affects their dietary decision-making, and confidence in identifying UPFs. Participants categorised a list of 10 foods (5 UPFs and 5 non-UPFs) as UPF vs. not, before rating whether information about studies linking UPF to worse health impacts on their negative affect and acts as a deterrent to consuming UPFs. Results: Most participants (73%) were aware of the term UPF and 58% reported that their food choices are determined by whether they believe a food is ultra-processed or not. Participants with the highest income and education levels were most likely to report both being aware of, and, avoiding consuming UPFs. Most participants could not accurately categorise whether foods were UPFs. Some sociodemographic groups (e.g., higher education levels) were more likely to accurately categorise UPFs but were also more likely to incorrectly believe that non-UPFs were UPFs. Participants tended to report that UPF-health risk information increases negative affect and acts as a deterrent to consuming UPFs. Conclusions: In this study, a large number of UK adults reported avoiding consuming UPFs. This was particularly pronounced among those with the highest education and income levels.
Analyzing the Effects of Rapid and Natural Cooling Techniques on the Quality of Hand-Shaken Green Tea Beverages
Authors: Chen Yuan-Ke , Song Tuzz-Ying , Chang Chi-Yu , Sheu Shiann-Cherng , Chen Chih-Wei
Published: July 2024

This study compared the quality of hand-shaken green tea prepared through rapid and natural cooling methods. Cooling is crucial in preserving green tea’s flavor, aroma, and nutritional components. In the rapid cooling method, green tea is freshly brewed at an initial temperature of 95 °C for 25 min, and then rapidly cooled to 18 °C for 25 min. Conversely, the natural cooling method involves brewing tea at the same initial temperature and time, but allowing it to cool gradually to 30 °C over approximately 4–5 h at room temperature. This study’s findings indicate that the rapid cooling method produced green tea with a more vibrant color and improved clarity versus the natural cooling method. Sensory analysis revealed that the taste and aroma of the hand-shaken green tea prepared using rapid cooling were perceived to be more refreshing and invigorating. However, the natural cooling method preserved a higher level of chemical components, including individual catechin caffeine, total polyphenol, soluble solids, reducing sugar, and total tannins. The essential amino acid content of the rapidly and naturally cooled green tea infusions was 6.85 and 13.55 μg/mL, respectively. The γ-Aminobutyric acid (GABA) content was 439.82 and 457.31 μg/mL, respectively. This study’s findings suggest that rapid cooling during the preparation of hand-shaken green tea enhances its overall quality. The vibrant color, improved clarity, refreshing taste, and invigorating aroma make it a preferable choice for tea enthusiasts who seek an enhanced sensory experience and excellent quality.
The Effect of Lactiplantibacillus plantarum SHY130 and Konjac Glucomannan on the Physicochemical, Antioxidant, and Sensory Properties of Stirred Yogurt
Authors: He Penglin , Wang Yufei , Yang Jing , Suo Huayi , Song Jiajia
Published: July 2024

The impact of konjac glucomannan (KGM)-based synbiotics on yogurt quality is not well understood. This study investigated the effects of a synbiotic mixture of KGM and the selected probiotic Lactiplantibacillus plantarum SHY130 on the physicochemical, antioxidant, and sensory properties of yogurt. The results showed that KGM significantly promoted the growth of Lactiplantibacillus plantarum SHY130. The synbiotics dramatically enhanced the count of lactic acid bacteria in yogurt during the 14 days of storage. Texture analysis indicated that the synbiotic supplement had no impact on springiness and cohesiveness but resulted in notable reductions in hardness, gumminess, and chewiness. The synbiotics did not significantly affect the water-holding capacity and syneresis. While the synbiotics initially decreased yogurt viscosity, it increased with storage time. Furthermore, the synbiotics significantly improved the yogurt’s antioxidant capacity. Additionally, the supplementation of the synbiotics did not adversely affect sensory properties, although the synbiotics containing 0.02% KGM negatively impacted overall acceptability. Overall, these findings elucidate the effects of KGM-based synbiotics on yogurt quality, providing a foundation for developing novel synbiotic yogurt products.
Characterization of Meat Metabolites and Lipids in Shanghai Local Pig Breeds Revealed by LC–MS-Based Method
Authors: Gao Jun , Sun Lingwei , Tu Weilong , Cao Mengqian , Zhang Shushan , Xu Jiehuan , He Mengqian , Zhang Defu , Dai Jianjun , Wu Xiao , Wu Caifeng
Published: July 2024

The meat of local livestock breeds often has unique qualities and flavors. In this study, three Shanghai native pig breeds (MSZ, SWT, and SHB) exhibited better meat quality traits than globalized commercial pig breeds (DLY). Subsequently, metabolomic and lipidomic differences in the longissimus dorsi (L) and gluteus (T) muscles of the Shanghai native pig breeds and DLY pig breed were compared using liquid chromatography–mass spectrometry (LC–MS). The results demonstrated that the metabolites mainly consisted of (28.16%) lipids and lipid-like molecules, and (25.87%) organic acids and their derivatives were the two most dominant groups. Hundreds of differential expression metabolites were identified in every compared group, respectively. One-way ANOVA was applied to test the significance between multiple groups. Among the 20 most abundant differential metabolites, L-carnitine was significantly different in the muscles of the four pig breeds (p-value = 7.322 × 10−11). It was significantly higher in the L and T muscles of the two indigenous black pig breeds (MSZ and SWT) than in the DLY pigs (p-value < 0.001). Similarly, lipidomic analysis revealed the PA (18:0/18:2) was significantly more abundant in the muscle of these two black breeds than that in the DLY breed (p-value < 0.001). These specific metabolites and lipids might influence the meat quality and taste properties and lead to customer preferences. Therefore, this study provided insights into the characterization of meat metabolites and lipids in Shanghai native pig breeds.
Optimization of the Microwave-Assisted Extraction of Caffeine from Roasted Coffee Beans
Authors: Savić Ivan M. , Savić Gajić Ivana M. , Gajić Dragoljub G.
Published: July 2024

This study aimed to develop a fast procedure for caffeine extraction from roasted coffee beans. The microwave-assisted extraction was carried out in the microwave oven with an operating frequency of 2450 MHz. The response surface methodology based on a Box–Behnken design was used to model and optimize the extraction process. Among the analyzed extraction parameters (factors), the influence of extraction time (2–6 min), liquid-to-solid ratio (5–15 mL/g), and microwave power (336–595 W) were considered, while the yield of extracted caffeine was observed as the response of the system. Water was used as the solvent of choice for the extraction of caffeine. The optimum conditions were as follows: extraction time, 2 min; liquid-to-solid ratio, 15 mL/g; and microwave power, 500 W. In this optimized condition, the expected extraction yield of caffeine was 1.01 g/100 g dry weight (value confirmed by experimental assays). The total energy consumed of 1.7 kWh/100 g of purified caffeine indicated a more energy-efficient procedure by about 1200–15,000 times than the reported procedures. This study showed that caffeine can be quantitatively extracted from roasted coffee beans through a green approach and that the isolated caffeine has a high purity degree, which was confirmed by the UHPLC-ESI-MS/MS method. With this quality, isolated caffeine could be further used as an active ingredient in the food industry, while for pharmaceutical purposes, it must be further purified.
Evaluation of Gel Coating Performance in Extending the Shelf Life of Egg: The Role of Surface Area and Initial Weight
Authors: Pham Thanh Tung , Nguyen Lien Le Phuong , Baranyai László , Dam Mai Sao , Ha Nga Thi Thanh , Varga-Tóth Adrienn , Dalmadi István , Németh Csaba , Friedrich László Ferenc
Published: July 2024

This work investigated the impact of chicken egg size, including surface area and initial weight, on the effectiveness of cassava starch-based gel coating during storage at room temperature. The quality of a total of 540 fresh eggs in four different sizes (S, M, L and XL) was evaluated over a 4-week storage period at 25 ± 1 °C (60–65% RH). In this research, images from a scanning electron microscope revealed that the coatings maintained their integrity across all egg sizes, effectively covering pores and cracks throughout storage. The application of gel coating reduced weight loss and preserved the Haugh unit and yolk index, extending freshness by 1–2 weeks compared with uncoated eggs at 25 °C. The results indicated that the performance of the coating varied with egg size. Statistical analysis revealed that the surface area and initial weight of the egg significantly impacted the effectiveness of the coating in preserving quality (p < 0.001). Eggs with larger surface areas exhibited a reduced protective effect of the coating, resulting in higher weight loss and lower retention of Haugh unit and yolk index compared with the coated eggs with smaller surface areas. The coating application was more effective in preserving the Haugh unit of eggs with higher initial weights. Overall, the surface area and the initial weight of the egg should be considered as key factors to ensure optimal coating performance.
Conchas, Coloring Books, and Oxnard: Using Critical Race Counterstorytelling as a Framework to Create a Social Justice Coloring Book
Authors: Gonzalez Martín Alberto
Published: July 2024

I am from Oxnard, California, a predominantly Latinx city that is stereotyped as “too hood”, “too ghetto”, or “crime-infested” because of its low-income Brown people. Such negative narratives are so commonplace that they become believable, but we can challenge these oppressive narratives using critical race counterstorytelling. There are multiple ways to tell a story, and I pride myself in producing counterstories that are accessible and enjoyable to mi gente. So, to encourage stay-at-home practices and empower my own community during the COVID-19 pandemic, I created a social justice coloring book with the help of artistic friends and local Oxnard Latinx artists. In collaboration with Chingon Bakery, a local panaderia in Oxnard, we delivered over 500 FREE conchas and coloring books to the Oxnard community during the height of the COVID-19 pandemic. In this creative piece, I explain why counterstorytelling, as a framework, served as the foundation for this coloring book and I include several examples of the coloring pages. Additionally, I discuss how and why this coloring book has proven to be a tool for cultural empowerment in my community. Ultimately, I argue that artistic representations of counterstories are necessary in the struggle to challenge and dismantle systems of oppression.
Rare Variants of the SMN1 Gene Detected during Neonatal Screening
Authors: Akhkiamova Maria , Polyakov Aleksander , Marakhonov Andrey , Voronin Sergey , Saifullina Elena , Vafina Zulfiia , Michalchuk Kristina , Braslavskaya Svetlana , Chukhrova Alena , Ryadninskaya Nina , Kutsev Sergey , Shchagina Olga
Published: July 2024

During the expanded neonatal screening program conducted in 2023, we analyzed samples obtained from 1,227,130 out of 1,256,187 newborns in the Russian Federation in order to detect 5q spinal muscular atrophy (5q SMA). Within the 253-sample risk group formed based on the results of the first screening stage, 5 samples showed a discrepancy between the examination results obtained via various screening methods and quantitative MLPA (used as reference). The discrepancy between the results was caused by the presence of either a c.835-18C>T intronic variant or a c.842G>C p.(Arg281Thr) missense variant in the SMN1 gene, both of which are located in the region complementary to the sequences of annealing probes for ligation and real-time PCR. Three newborns had the c.835-18C>T variant in a compound heterozygous state with a deletion of exons 7–8 of the SMN1 gene, one newborn with two copies of the SMN1 gene had the same variant in a heterozygous state, and one newborn had both variants—c.835-18C>T and c.842G>C p.(Arg281Thr)—in a compound heterozygous state. Additional examination was carried out for these variants, involving segregation analysis in families, carriage analysis in population cohorts, and RNA analysis. Based on the obtained results, according to the ACMG criteria, the c.835-18C>T intronic variant should be classified as likely benign, and the c.842G>C p.(Arg281Thr) missense substitution as a variant of uncertain clinical significance. All five probands are under dynamic monitoring. No 5q SMA symptoms were detected in these newborns neonatally or during a 1-year follow-up period.
The Relationship between Adolescent Dating Violence and Risky Health Behavioral Outcomes
Authors: Saini Neha , Smith Shamya N. , Wongpaiboon Manasicha , Crowther Vanessa B. , Buxbaum Sarah , Tawk Rima
Published: July 2024

Dating violence is a serious public health issue among adolescents due to the detrimental short- and long-term consequences. The purpose of this study is to examine the relationship between adolescent dating violence (ADV) and adverse health behavioral outcomes related to substance abuse, mental health, and select risky health behaviors such as feeling unsafe, school performance, and inadequate sleep within the state of Florida. This study used data from the 2015 Youth Risk Behavior Survey (YRBS). The high school students represented a weighted total of 542,818 (n = 4301). Logistic regression analyses, stratified by gender, examined the relationship between ADV and health risk behaviors after adjusting for race and grade. Proportions of ADV were as follows: 3.1% of students reported being abused both physically and sexually; 3.4% reported being abused only physically; 3.9% reported being abused only sexually; and 89.6% were uninvolved. ADV was associated with almost all the health risk behavior outcomes studied, with a few exceptions. Experiencing both kinds of abuse held the highest odds ratio among the four mutually exclusive categories of ADV. The findings from this study could be helpful in identifying youths who demonstrate warning signs of ADV abuse and thus could provide opportunities for targeted preventive interventions.
Unlocking Rapid and User-Friendly Strategies to Improve Horticultural Crop Qualities
Authors: Sharma Diksha , Ruhil Bhumi , Dubey Anubhav , Jain Divya , Bhatia Deepika , Koubouris Georgios
Published: July 2024

Climatic changes and global warming affect the growth, development, and productivity of crops. In this review, we highlight the possible benefits of using innovative breeding techniques like clustered regularly interspaced short palindromic repeats (CRISPRs), exogenous phytohormone-like strigolactones (SLs), nanomaterials (NMs), and beneficial microbial endophytes to address the challenges in sustainable cultivation of horticultural crops. These applications are evaluated by examining how they affect different metabolic, morphological, and biochemical parameters in diverse crops. Endophytes are symbiotic microorganisms and can be used as nematicides for improving crop yield. With an emphasis on quality control, we examined the impacts of applying NMs, a novel family of phytohormones called SLs, and microbial endophytes on horticultural commodities. Furthermore, we reviewed the benefits of CRISPR for the editing of plant genomes, as well as how it affects gene expression and transcription factors to increase crop tolerance and yield. These innovations hold the potential to improve crop yield, quality, and resilience by acting as safe, natural components in biofertilizers and plant protection solutions. Gradually adopting these methods could decrease reliance on agrochemicals, thereby reducing their negative effects on biodiversity, soil fertility, and human health.
Upregulated Nuclear Expression of Soluble Epoxide Hydrolase Predicts Poor Outcome in Breast Cancer Patients: Importance of the Digital Pathology Approach
Authors: Montecillo-Aguado Mayra , Soca-Chafre Giovanny , Antonio-Andres Gabriela , Morales-Martinez Mario , Tirado-Rodriguez Belen , Rocha-Lopez Angelica G. , Hernandez-Cueto Daniel , Sánchez-Ceja Sandra G. , Alcala-Mota-Velazco Berenice , Gomez-Garcia Anel , Gutiérrez-Castellanos Sergio , Huerta-Yepez Sara
Published: July 2024

Breast cancer (BC) is the most common cancer in women, with incidence rates increasing globally in recent years. Therefore, it is important to find new molecules with prognostic and therapeutic value to improve therapeutic response and quality of life. The polyunsaturated fatty acids (PUFAs) metabolic pathway participates in various physiological processes, as well as in the development of malignancies. Although aberrancies in the PUFAs metabolic pathway have been implicated in carcinogenesis, the functional and clinical relevance of this pathway has not been well explored in BC. To evaluate the clinical significance of soluble epoxide hydrolase (EPHX2) expression in Mexican patients with BC using tissue microarrays (TMAs) and digital pathology (DP). Immunohistochemical analyses were performed on 11 TMAs with 267 BC samples to quantify this enzyme. Using DP, EPHX2 protein expression was evaluated solely in tumor areas. The association of EPHX2 with overall survival (OS) was detected through bioinformatic analysis in public databases and confirmed in our cohort via Cox regression analysis. Clear nuclear expression of EPHX2 was identified. Receiver operating characteristics (ROC) curves revealed the optimal cutoff point at 2.847062 × 10−3 pixels, with sensitivity of 69.2% and specificity of 67%. Stratification based on this cutoff value showed elevated EPHX2 expression in multiple clinicopathological features, including older age and nuclear grade, human epidermal growth factor receptor 2 (HER2) and triple negative breast cancer (TNBC) subtypes, and recurrence. Kaplan–Meier curves demonstrated how higher nuclear expression of EPHX2 predicts shorter OS. Consistently, multivariate analysis confirmed EPHX2 as an independent predictor of OS, with a hazard ratio (HR) of 3.483 and a 95% confidence interval of 1.804–6.724 (p < 0.001). Our study demonstrates for the first time that nuclear overexpression of EPHX2 is a predictor of poor prognosis in BC patients. The DP approach was instrumental in identifying this significant association. Our study provides valuable insights into the potential clinical utility of EPHX2 as a prognostic biomarker and therapeutic target in BC.
Correlation of Albumin, Red Cell Distribution Width and Other Biochemical and Hematological Parameters with Glycated Hemoglobin in Diabetic, Prediabetic and Non-Diabetic Patients
Authors: Ginoudis Argyrios , Ioannidou Stavroula , Tsakiroglou Georgia , Kazeli Konstantina , Vagdatli Eleni , Lymperaki Evgenia
Published: July 2024

Diabetes mellitus is a chronic metabolic disease that affects more than 10.5% of the world’s adult population. Biochemical and hematological parameters, such as albumin (ALB) and red cell distribution width (RDW), have been shown to be altered in diabetic patients. This study aimed to correlate hematological and biochemical parameters with glycated hemoglobin (HbA1c). A total of 777 adults (372 women and 405 men, aged 19–85 years) were divided into three groups: 218 participants with HbA1c < 5.7% (group A: non-diabetic), 226 with HbA1c ≥ 5.7% and <6.5% (group B: prediabetic) and 333 with HbA1c ≥ 6.5% (group C: diabetic). Biochemical and hematological parameters were compared among the three groups. An analysis of variance was performed to determine the correlations of the parameters among the groups. The ALB and sodium (Na) levels were significantly lower in group C than in groups A (ALB: 3.8 g/dL vs. 4.1 g/dL, p < 0.0001, Na: 138.4 mmol/L vs. 139.3 mmol/L, p < 0.001) and B (ALB: 3.8 g/dL vs. 4.0 g/dL, p < 0.0001, Na: 138.4 mmol/L vs. 139.6 mmol/L, p < 0.0001), whereas the RDW-standard deviation (RDW-SD) and urea were increased in group C as compared to group A (RDW: 45.8 vs. 43.9 fL, p < 0.0001, urea: 55.6 mg/dL vs. 38.5 mg/dL, p < 0.0001). The mean platelet volume (MPV) was increased in group C as compared to group A (9.3 fL vs. 9.1 fL, p < 0.05, respectively). Τhe increase in RDW-SD in group A as compared to B and C demonstrates the impact of hyperglycemia on red blood cells. Albumin and RDW might improve risk assessment for the development of diabetes. These results highlight the potential role of these parameters as an indication for prediabetes that would alert for measurement of HbA1c.
Transcriptome Reveals the Regulation of Exogenous Auxin Inducing Rooting of Non-Rooting Callus of Tea Cuttings
Authors: Wang Shuting , Wu Huanran , Zhang Yazhao , Sun Guodong , Qian Wenjun , Qu Fengfeng , Zhang Xinfu , Hu Jianhui
Published: July 2024

Cuttage is the main propagation method of tea plant cultivars in China. However, some tea softwood cuttings just form an expanded and loose callus at the base, without adventitious root (AR) formation during the propagation period. Meanwhile, exogenous auxin could promote the AR formation of tea plant cuttings, but the regulation mechanism has not yet explained clearly. We conducted this study to elucidate the regulatory mechanism of exogenous auxin-induced adventitious root (AR) formation of such cuttings. The transcriptional expression profile of non-rooting tea calluses in response to exogenous IBA and NAA was analyzed using ONT RNA Seq technology. In total, 56,178 differentially expressed genes (DEGs) were detected, and most of genes were significantly differentially expressed after 12 h of exogenous auxin treatment. Among these DEGs, we further identified 80 DEGs involved in the auxin induction pathway and AR formation. Specifically, 14 auxin respective genes (ARFs, GH3s, and AUX/IAAs), 3 auxin transporters (AUX22), 19 auxin synthesis- and homeostasis-related genes (cytochrome P450 (CYP450) and calmodulin-like protein (CML) genes), and 44 transcription factors (LOB domain-containing protein (LBDs), SCARECROW-LIKE (SCL), zinc finger protein, WRKY, MYB, and NAC) were identified from these DEGs. Moreover, we found most of these DEGs were highly up-regulated at some stage before AR formation, suggesting that they may play a potential role in the AR formation of tea plant cuttings. In summary, this study will provide a theoretical foundation to deepen our understanding of the molecular mechanism of AR formation in tea cuttings induced by auxin during propagation time.
Integrating Machine Learning in Geotechnical Engineering: A Novel Approach for Railway Track Layer Design Based on Cone Penetration Test Data
Authors: Bernard Matthieu
Published: July 2024

The cone penetration test (CPT) has emerged as a cost-effective and time-efficient method for assessing soil conditions relevant to railway track infrastructure. The geotechnical data obtained from the CPT serve as crucial input for asset managers in designing optimal sublayers and form layers for track renewal works. To properly assess the condition of soil layers, various soil behavior type charts and machine learning models based on CPT data have been published to help engineers classify soils into groups with similar properties. By understanding the properties of the soils, an optimal substructure can be designed to minimize extensive maintenance and reduce the risk of derailment. However, when analyzing multiple CPTs, the diversity and non-uniformity of subsoil characteristics pose challenges in designing a new optimal trackbed. This study presents an automated approach for recommending thicknesses of sublayers and form layers in railway tracks based on CPT data, employing machine learning algorithms. The proposed approach was tested using CPT data from the Belgian railway network and showed very good agreement with results from traditional soil investigation interpretations and layer design. A Random Forest classifier, fine-tuned through Bayesian optimization with a cross-validation technique and trained on 80% of the datasets, achieved an overall accuracy of 83% on the remaining 20%. Based on these results, we can conclude that the proposed model is highly effective at accurately designing sub-ballast layers using CPT data.
A Review Paper on Optical Coherence Tomography Evaluation of Coronary Calcification Pattern: Is It Relevant Today?
Authors: Onea Horea-Laurentiu , Olinic Maria , Lazar Florin-Leontin , Homorodean Calin , Ober Mihai Claudiu , Spinu Mihail , Achim Alexandru , Tataru Dan Alexandru , Olinic Dan Mircea
Published: July 2024

The process of coronary calcification represents one of the numerous pathophysiological mechanisms involved in the atherosclerosis continuum. Optical coherence tomography (OCT) represents an ideal imaging modality to assess plaque components, especially calcium. Different calcification patterns have been contemporarily described in both early stages and advanced atherosclerosis. Microcalcifications and spotty calcifications correlate positively with macrophage burden and inflammatory markers and are more frequently found in the superficial layers of ruptured plaques in acute coronary syndrome patients. More compact, extensive calcification may reflect a later stage of the disease and was traditionally associated with plaque stability. Nevertheless, a small number of culprit coronary lesions demonstrates the presence of dense calcified plaques. The purpose of the current paper is to review the most recent OCT data on coronary calcification and the interrelation between calcification pattern and plaque vulnerability. How different calcified plaques influence treatment strategies and associated prognostic implications is of great interest.