bluuebunny/crossref_metadata_2025 huggingface dataset:
Beeswax Alcohol Prevents Low-Density Lipoprotein Oxidation and Demonstrates Antioxidant Activities in Zebrafish Embryos and Human Subjects: A Clinical Study
Authors: Cho Kyung-Hyun , Baek Seung-Hee , Nam Hyo-Seon , Bahuguna Ashutosh , López-González Luis Ernesto , Rodríguez-Cortina Iván , Illnait-Ferrer José , Fernández-Travieso Julio César , Molina-Cuevas Vivian , Pérez-Guerra Yohani , Oyarzabal Yera Ambar , Mendoza-Castaño Sarahi
Published: January 2024

Oxidative stress is one of the primary instigators of the onset of various human ailments, including cancers, cardiovascular diseases, and dementia. Particularly, oxidative stress severely affects low-density lipid & protein (LDL) oxidation, leading to several detrimental health effects. Therefore, in this study, the effect of beeswax alcohol (BWA) was evaluated in the prevention of LDL oxidation, enhancement of paraoxonase 1 (PON-1) activity of high-density lipid & protein (HDL), and zebrafish embryo survivability. Furthermore, the implication of BWA consumption on the oxidative plasma variables was assessed by a preliminary clinical study on middle-aged and older human subjects (n = 50). Results support BWA augmentation of PON-1 activity in a dose-dependent manner (10–30 μM), which was significantly better than the effect exerted by coenzyme Q10 (CoQ10). Moreover, BWA significantly curtails LDL/apo-B oxidation evoked by CuSO4 (final 0.5 μM) and a causes a marked reduction in lipid peroxidation in LDL. The transmission electron microscopy (TEM) analysis revealed a healing effect of BWA towards the restoration of LDL morphology and size impaired by the exposure of Cu2+ ions (final 0.5 μM). Additionally, BWA counters the toxicity induced by carboxymethyllysine (CML, 500 ng) and rescues zebrafish embryos from development deformities and apoptotic cell death. A completely randomized, double-blinded, placebo-controlled preliminary clinical study on middle- and older-aged human subjects (n = 50) showed that 12 weeks of BWA (100 mg/day) supplementation efficiently diminished serum malondialdehyde (MDA) and total hydroperoxides and enhanced total antioxidant status by 25%, 27%, and 22%, respectively, compared to the placebo-control and baseline values. Furthermore, the consumption of BWA did not exhibit any noteworthy changes in physical variables, lipid profile, glucose levels, and biomarkers pertinent to kidney and liver function, thus confirming the safety of BWA for consumption. Conclusively, in vitro, BWA prevents LDL oxidation, enhances PON-1 activity in HDL, and positively influences oxidative variables in human subjects.
Effect of Different Air Oven Temperatures on Chemical, Physical, and Microbial Properties of Dried Bio-Yoghurt Product
Authors: Jaafar Fatimah Eesee , Rubaiy Hassan Hadi Mehdi Al , Niamah Alaa Kareem
Published: January 2024

The aim of this study was to compare the physical, chemical, and microbiological features of bio-yoghurt that had been air-oven-dried at three temperatures (40, 50, and 60 °C) to those of fresh bio-yoghurt. The results showed that drying bio-yoghurt at 40–60 °C decreased the number of probiotic starter bacteria in dried yoghurt products compared to fresh bio-yoghurt. The dried yoghurt’s moisture, protein, fat, carbohydrate, and ash contents were 4.16–4.55%, 38.22–40.02%, 1.33–1.43%, 47.94–49.45%, and 6.37–6.55%, respectively. The pH and total acidity levels of dried yoghurt were within acceptable ranges at various temperatures and storage durations. At different temperatures, the viscosity values of the products decreased by 620–550 cp; however, the hygroscopicity values remained constant. During a 90-day storage period, the dried yoghurt product’s physical, chemical, and microbiological characteristics remained within acceptable levels. Using a drying temperature of 40–50 °C kept the number of live bacteria below acceptable ranges during storage periods. Lactobacillus acidophilus counts were 6.75 and 6.70 log CFU/g, respectively, whereas Bifidobacterium bifidum numbers were 6.66 and 6.08 log CFU/g, respectively. In conclusion, drying bio-yoghurt in an air oven at 40–50 °C provided a dried product with a high number of viable probiotic bacteria and satisfactory physicochemical characteristics after 3 months.
Safety and Efficacy of GLP-1 Receptor Agonists in Type 2 Diabetes Mellitus with Advanced and End-Stage Kidney Disease: A Systematic Review and Meta-Analysis
Authors: Krisanapan Pajaree , Sanpawithayakul Kanokporn , Pattharanitima Pattharawin , Thongprayoon Charat , Miao Jing , Mao Michael A. , Suppadungsuk Supawadee , Tangpanithandee Supawit , Craici Iasmina M. , Cheungpasitporn Wisit
Published: January 2024

Background and Objectives: Limited evidence exists regarding the safety and efficacy of glucagon-like peptide-1 receptor agonists (GLP-1RAs) in type 2 diabetes mellitus (T2DM) patients with advanced chronic kidney disease (CKD) or end-stage kidney disease (ESKD). Thus, we conducted a systematic review and meta-analysis to assess the safety and efficacy of GLP-1RAs in T2DM patients with advanced CKD and ESKD. Materials and Methods: We performed a systematic literature search in MEDLINE, EMBASE, and Cochrane database until 25 October 2023. Included were clinical trials and cohort studies reporting outcomes of GLP-1RAs in adult patients with T2DM and advanced CKD. Outcome measures encompassed mortality, cardiovascular parameters, blood glucose, and weight. Safety was assessed for adverse events. The differences in effects were expressed as odds ratios with 95% confidence intervals (CIs) for dichotomous outcomes and the weighted mean difference or standardized mean difference (SMD) with 95% confidence intervals for continuous outcomes. The Risk of Bias In Non-randomized Studies—of Interventions (ROBIN-I) tool was used in cohort and non-randomized controlled studies, and the Cochrane Risk of Bias (RoB 2) tool was used in randomized controlled trials (RCTs). The review protocol was registered in the International Prospective Register of Systematic Reviews (CRD 42023398452) and received no external funding. Results: Eight studies (five trials and three cohort studies) consisting of 27,639 patients were included in this meta-analysis. No difference was observed in one-year mortality. However, GLP-1RAs significantly reduced cardiothoracic ratio (SMD of −1.2%; 95% CI −2.0, −0.4) and pro-BNP (SMD −335.9 pmol/L; 95% CI −438.9, −232.8). There was no significant decrease in systolic blood pressure. Moreover, GLP-1RAs significantly reduced mean blood glucose (SMD −1.1 mg/dL; 95% CI −1.8, −0.3) and increased weight loss (SMD −2.2 kg; 95% CI −2.9, −1.5). In terms of safety, GLP-1RAs were associated with a 3.8- and 35.7-time higher risk of nausea and vomiting, respectively, but were not significantly associated with a higher risk of hypoglycemia. Conclusions: Despite the limited number of studies in each analysis, our study provides evidence supporting the safety and efficacy of GLP-1RAs among T2DM patients with advanced CKD and ESKD. While gastrointestinal side effects may occur, GLP-1RAs demonstrate significant improvements in blood glucose control, weight reduction, and potential benefit in cardiovascular outcomes.
Optimal Configuration of Heterogeneous Swarm for Cooperative Detection with Minimum DOP Based on Nested Cones
Authors: Yu Ruihang , Liu Yilin , Meng Yangtao , Guo Yan , Xiong Zhiming , Jiang Pengfei
Published: January 2024

When unmanned platforms perform precise target detection, the configuration of detection nodes will significantly impact accuracy. Aiming to obtain the minimum dilution of precision (DOP), this paper innovatively proposes an optimal detection configuration design method focused on the heterogeneous unmanned cooperative swarm based on the nested cone model. The proposed method first divides the swarm into different groups according to the performances of platforms and then uses a conical nested configuration to arrange the placement of each node independently. The paper considers the problem of the inaccurate prior position of the target and replaces the single-point DOP with the average DOP on the prior region of the target as the optimization objective. Considering the unavoidable positioning errors in engineering practice, this paper provides the optimal configuration of the detection group (DG) and anchor group (AG) in the swarm to reduce the impact caused by positioning errors of detection nodes. We set a certain swarm consisting of 3 types of platforms to design the configuration by simulation experiments and find the optimal parameters for nested cones to realize accurate detection.
Factors Influencing University Teachers’ Technological Integration
Authors: Nagy Judit T. , Dringó-Horváth Ida
Published: January 2024

The extent and effectiveness of digitalization are influenced by a variety of factors, which are worth studying both separately and together, looking at how they affect each other. Typically, researched aspects in the context of education are institutional support, teachers’ beliefs about using digital tools, digital competence in teaching, technostress, self-efficacy, and the extent of digital tool use. The present study aims to center around the final aspect. It examines the separate influencing factors of information and communications technology (hereafter, ICT) use within a complex model, with the help of partial least squares structural equation modeling. The study was based on a survey of university lecturers (n = 116) at a university in Hungary that has six different training locations and five faculties. It was conducted by using an online questionnaire. To summarize the identified correlations, it can be concluded that digital competence in teaching, collegial support, ICT self-efficacy and ICT perception play a significant role in the use of technology. The effects detailed in the results can contribute to the effective digitalization of higher education institutions in several practical ways.
Injury as a Result of Children and Adolescent Labor—An Association with Ethnicity and Peripherality: A Retrospective Cohort Study Based on the Israeli Trauma Registry
Authors: Savitsky Bella , Radomislensky Irina , Katorza Eldad , Kaim Arielle
Published: January 2024

Background: Working children and adolescents face a heightened risk of work-related injuries. This research aimed to assess the rate of hospitalizations resulting from work-related injuries among children and adolescents in Israel, with a specific focus on disadvantaged populations. Methods: This nationwide retrospective cohort study utilized The Israeli National Trauma Registry (INTR). It included 642 children and adolescents aged 13–17 hospitalized due to work-related injuries from 2015–2022. Results: Arab children had over five times the risk of hospitalization due to work-related injuries compared to Jewish (RR = 5.5, 95% CI: 4.7–7.4). Despite the 2018 law prohibiting young people from entering this type of work, the most common type of work leading to hospitalization was construction, accounting for 40.2% of Arab and 11.9% of Jewish injuries (p < 0.001). After adjustment, road traffic accidents and falls presented the highest odds of at least severe injury. Arabs had three times significantly higher odds of at least moderate injury compared to Jews. Conclusions: Prioritizing the creation of safe job opportunities for Arab teenagers is imperative. Strict enforcement measures, particularly within the construction industry, especially among Arab youth and during night shifts, are essential. These initiatives should focus on establishing secure and sustainable employment opportunities for children and young individuals, effectively reducing the risks associated with hazardous labor practices. In addition, the implementation of educational programs in the school curriculum covering essential aspects of youth employment is vital.
A Residual Network with Efficient Transformer for Lightweight Image Super-Resolution
Authors: Yan Fengqi , Li Shaokun , Zhou Zhiguo , Shi Yonggang
Published: January 2024

In recent years, deep learning approaches have achieved remarkable results in the field of Single-Image Super-Resolution (SISR). To attain improved performance, most existing methods focus on constructing more-complex networks that demand extensive computational resources, thereby significantly impeding the advancement and real-world application of super-resolution techniques. Furthermore, many lightweight super-resolution networks employ knowledge distillation strategies to reduce network parameters, which can considerably slow down inference speeds. In response to these challenges, we propose a Residual Network with an Efficient Transformer (RNET). RNET incorporates three effective design elements. First, we utilize Blueprint-Separable Convolution (BSConv) instead of traditional convolution, effectively reducing the computational workload. Second, we propose a residual connection structure for local feature extraction, streamlining feature aggregation and accelerating inference. Third, we introduce an efficient transformer module to enhance the network’s ability to aggregate contextual features, resulting in recovered images with richer texture details. Additionally, spatial attention and channel attention mechanisms are integrated into our model, further augmenting its capabilities. We evaluate the proposed method on five general benchmark test sets. With these innovations, our network outperforms existing efficient SR methods on all test sets, achieving the best performance with the fewest parameters, particularly in the area of texture detail enhancement in images.
Voltage and Current Sensor Fault Diagnosis Method for Traction Rectifier in High-Speed Trains
Authors: Yu Yunjun , Song Yunquan , Tao Hongwei , Hu Jiawen
Published: January 2024

The traction rectifier plays a key role in high-speed trains. Unexpected failure often occurs in the sensors of the rectifier, which may affect the control performance of the electric traction rectifier and even cause serious deterioration to high-speed trains. A sensor fault diagnosis method is presented in this paper, considering three kinds of common fault types. It can not only locate the sensor fault, but also identify fault types. Based on the influences of the sensor faults, the fault diagnosis thresholds can be calculated quantitatively. No additional hardware is required. First, the model of the rectifier is established, and the estimator is built. The current residuals with different faults can be obtained. Next, residuals are analyzed and features are acquired. Then, diagnosis functions are constructed, which are used for fault location and fault type identification. Finally, the feasibility and effectiveness of the method have been confirmed by the experimental results.
Attention-Mechanism-Based Face Feature Extraction Model for WeChat Applet on Mobile Devices
Authors: Xiao Jianyu , Zhou Hongyang , Lei Qigong , Liu Huanhua , Xiao Zunlong , Huang Shenxi
Published: January 2024

Face recognition technology has been widely used with the WeChat applet on mobile devices; however, facial images are captured on mobile devices and then transmitted to a server for feature extraction and recognition in most existing systems. There are significant security risks related to personal information leakage with these transmissions. Therefore, we propose a face recognition framework for the WeChat applet in which face features are extracted in WeChat by the proposed Face Feature Extraction Model based on Attention Mechanism (FFEM-AM), and only the extracted features are transmitted to the server for recognition. In order to balance the prediction accuracy and model complexity, the structure of the proposed FFEM-AM is lightweight, and Efficient Channel Attention (ECA) was introduced to improve the prediction accuracy. The proposed FFEM-AM was evaluated using a self-built database and the WeChat applet on mobile devices. The experiments show that the prediction accuracy of the proposed FFEM-AM was 98.1%, the running time was less than 100 ms, and the memory cost was only 6.5 MB. Therefore, this demonstrates that the proposed FFEM-AM has high prediction accuracy and can also be deployed with the WeChat applet.
Design of a Ka-Band Heterogeneous Integrated T/R Module of Phased Array Antenna
Authors: Zeng Qinghua , Chen Zhengtian , He Mengyun , Wang Song , Liu Xiao , Xu Haitao
Published: January 2024

The central element of a phased array antenna that performs beam electrical scanning, as well as signal transmission and reception, is the transceiver (T/R) module. Higher standards have been set for the integration, volume, power consumption, stability, and environmental adaptability of T/R modules due to the increased operating frequency of phased array antennas, the variability of application platforms, and the diversified development of system functions. Device-based multichannel T/R modules are the key to realizing low-profile Ka-band phased array antenna microsystem architecture. The design and implementation of a low-profile, high-performance, and highly integrated Ka-band phased array antenna T/R module are examined in this paper. Additionally, a dependable Ka-band four-channel T/R module based on Si/GaAs/Low Temperature Co-fired Ceramic (LTCC), applying multi-material heterogeneous integration architecture, is proposed and fabricated. The chip architecture, transceiver link, LTCC substrates, interconnect interface, and packaging are all taken into consideration when designing the T/R module. When compared to a standard phased array antenna, the module’s profile shrunk from 40 mm to 8 mm, and its overall dimensions are only 10.8 mm × 10 mm × 3 mm. It weighs 1 g, and with the same specs, the single channel volume was reduced by 95%. The T/R module has an output power of ≥26 dBm for single-channel transmission, an efficiency of ≥25%, and a noise factor of ≤4.4 dB. When compared to T/R modules based on System-on-Chip (SOC) devices, the RF performance has significantly improved, as seen by an increase in single channel output power and a decrease in the receiving noise factor. This work lays a foundation for the devitalization and engineering application of T/R modules in highly reliable application scenarios.
The Effect of Feature Selection on the Accuracy of X-Platform User Credibility Detection with Supervised Machine Learning
Authors: Abid-Althaqafi Nahid R. , Alsalamah Hessah A.
Published: January 2024

In the era of digital information, online platforms play a crucial role in shaping public opinion. However, the extensive spread of misinformation and fake news poses a significant challenge, largely fueled by non-credible users. Detecting user credibility is vital for ensuring the reliability of information on these platforms. This study employs supervised machine learning algorithms, leveraging key user features to enhance credibility detection. Feature selection methods, specifically SelectKBest and correlation-based algorithms, are explored for their impact on X-Platform user credibility detection. Utilizing various classifiers, including support vector machine, logistic regression, and XGBoost, experiments are conducted on the ArPFN dataset, which is a labeled, balanced, publicly available dataset. The evaluation includes measures like accuracy, precision, recall, and F1-score to assess efficiency. This research considers feature categories and selection methods with SML to detect their impact on the accuracy of X-Platform user credibility detection, making this research a reference for researchers and practitioners working in the field of SML, feature engineering, and social media analysis. We aim to advance the field’s understanding of effective strategies for mitigating the spread of fake news. The novelty of this study lies in the comprehensive exploration of feature selection methods and their influence on credibility detection, contributing valuable insights for future research in this domain.
Risk-Based System-Call Sequence Grouping Method for Malware Intrusion Detection
Authors: Vyšniūnas Tolvinas , Čeponis Dainius , Goranin Nikolaj , Čenys Antanas
Published: January 2024

Malware intrusion is a serious threat to cybersecurity; that is why new and innovative methods are constantly being developed to detect and prevent it. This research focuses on malware intrusion detection through the usage of system calls and machine learning. An effective and clearly described system-call grouping method could increase the various metrics of machine learning methods, thereby improving the malware detection rate in host-based intrusion-detection systems. In this article, a risk-based system-call sequence grouping method is proposed that assigns riskiness values from low to high based on function risk value. The application of the newly proposed grouping method improved classification accuracy by 23.4% and 7.6% with the SVM and DT methods, respectively, compared to previous results obtained on the same methods and data. The results suggest the use of lightweight machine learning methods for malware attack can ensure detection accuracy comparable to deep learning methods.
Optimal Weighted Modulus: A Secure and Large-Capacity Data-Hiding Algorithm for High Dynamic Range Images
Authors: Hsieh Ku-Sung , Wang Chung-Ming
Published: January 2024

This paper presents an optimal weighted modulus (OWM) algorithm able to conceal secret messages in a high dynamic range image encoded via the RGBE format, consisting of the red, green, blue, and exponent channels. In contrast to current state-of-the-art schemes, which mainly employ limited and vulnerable homogeneous representations, our OWM scheme exploits four channels and an embedding weight to conceal secret messages, thereby offering more embedding capacities and undetectability against steganalytic tools. To reduce the impact on the luminance variation, we confine the maximal change incurred in the exponent channel when embedding secret messages. In addition, we propose an SEC scheme to eliminate the pixel saturation problem, even though a pixel contains values close to the boundary extreme. As a result, the stego images produced not only exhibit high quality but also comply with the RGBE encoding format, making them able to resist malicious steganalytic detection. The experimental results show that our scheme offers larger embedding rates, between 2.8074 and 5.7549 bits per pixel, and the average PSNR value for twelve tone-mapped images is over 48 dB. In addition, the HDR VDP 3.0 metric demonstrates the high fidelity of stego HDR images, where the average Q value is close to the upper bound of 10.0. Our scheme can defeat RS steganalytic attacks and resist image compatibility attacks. A comparison result confirms that our scheme outperforms six current state-of-the-art schemes.
Improving the Precision of Image Search Engines with the Psychological Intention Diagram
Authors: Wu Meng-Qian Alexander , Wu Fan , Lin Wen-Bin
Published: January 2024

With the increase in the amount of images online, the whole Internet is becoming an image database. Since there are so many available images, it is difficult for users to find the desired images. Unlike text search engines, image search engines cannot fully recognize the visual meaning of an image. In addition, it is difficult to obtain the desired images from the keywords provided by the user, since a keyword may contain multiple meanings. To solve these problems, this paper proposes a psychological intention diagram of past users, if inquiring using a keyword, to predict the images that these users want. Based upon the novel psychological diagram, this paper proposes a search engine that analyzes images in the sequential probing of the current user if he/she inquires after the same keywords as previous users. Moreover, this paper also constructs a psychological intention diagram of the designers of the web pages containing the keyword. This type of psychological intention diagram is used when a query is not issued by past users. To the best of our knowledge, this paper is the first one considering the psychological viewpoint of users and web designers in guiding the retrieval of the search engine. The experimental results show that the proposed image search engine has high precision; therefore, the method of providing images can help users to find their desired image more easily.
Determination of Ozone Concentration Levels in Urban Environments Using a Laser Spectroscopy System
Authors: Petrus Mioara , Popa Cristina , Bratu Ana-Maria
Published: January 2024

In urban areas, there has been a recent rise in ground-level ozone. Given its toxicity to both humans and the environment, the investigation of ozone pollution demands attention and should not be overlooked. Therefore, we conducted a study on ozone concentration in three distinct locations within the city of Magurele, Romania. This investigation considered variations in both structure and location during the spring and summer seasons, specifically at a breathing level of 1.5 m above the ground. Our analysis aimed to explore the impact of different locations and meteorological variables on ozone levels. The three measurement points were strategically positioned in diverse settings: within the city, in a forest, and within an industrial area. For these measurements, we used a laser spectroscopy system to determine the system’s sensitivity and selectivity and the influence of humidity in the detection of ozone in ambient air, which is a mixture of trace gases and water vapor. During the March–August campaign, the mean values in the three measuring points were 24.45 ± 16.44 ppb, 11.96 ± 3.80 ppb, and 95.01 ± 37.11 ppb. The peak concentrations of ozone were observed during the summer season. A diurnal analysis revealed that the atmospheric ozone levels were higher in the latter part of the day compared to the earlier part. These measurements suggest that the atmospheric temperature plays a significant role in tropospheric ozone production. Additionally, meteorological variables such as wind speed and direction were found to influence the ozone concentration. Remarkably, despite substantial traffic, the ozone levels remained consistently low throughout the entire period within the forested area. This observation may suggest the remarkable ability of trees to mitigate pollution levels.
A Suitable HPLC-MS/MS Methodology for the Detection of Oxytetracycline, Enrofloxacin, and Sulfachloropyridazine Residues in Lettuce Plants
Authors: Yévenes Karina , Ibáñez María José , Pokrant Ekaterina , Flores Andrés , Maturana Matías , Maddaleno Aldo , Cornejo Javiera
Published: January 2024

Oxytetracycline (OTC), enrofloxacin (EFX), and sulfachloropyridazine (SCP) are critically important antimicrobials (AMs) in both human and veterinary medicine, where they are widely used in farm animals. Lettuce has become a matrix of choice for studying the presence of residues of these AMs in plants, as the concentrations of residues detected in lettuce can range from ng to mg. While several analytical methodologies have been developed for the purpose of detecting AMs in lettuce, these currently do not detect both the parent compound and its active metabolites or epimers, such as in the case of ciprofloxacin (CFX) and 4-epi-oxitetracycline (4-epi-OTC), which also pose a risk to public health and the environment due to their AM activity. In light of this situation, this work proposes an analytical method that was developed specifically to allow for the detection of OTC, 4-epi-OTC, EFX, CFX, and SCP in a lettuce matrix. This method uses acetonitrile, methanol, 0.5% formic acid, and McIlvaine-EDTA buffer as extraction solvents, and dispersive solid-phase extraction (dSPE) for the clean-up. The analytes were detected using a liquid chromatography technique coupled to mass spectrometry (HPLC-MS/MS). Parameters such as the specificity, linearity, recovery, precision, limit of detection, and limit (LOD) of quantification (LOQ) were calculated according to the recommendations established in the European Union decision 2021/808/EC and VICH GL2: Validation of analytical procedures. The LOQ for the analytes OTC, 4-epi-OTC, CFX, and SCP was 1 μg·kg−1, whereas for EFX, it was 5 μg·kg−1 dry weight. All calibration curves showed a coefficient of determination (R2) of >0.99. The recovery levels ranged from 93.0 to 110.5% and the precision met the acceptance criteria, with a coefficient of variation of ≤14.02%. Therefore, this methodology allows for the precise and reliable detection and quantification of these analytes. The analysis of commercial samples confirmed the suitability of this method.
Advances in the Use of Beneficial Microorganisms to Improve Nutritional and Functional Properties of Fermented Foods
Authors: De Bellis Palmira , Rizzello Carlo Giuseppe
Published: January 2024

The World Health Organization [...]
Physicochemical, Sensory, and Nutritional Properties of Foods Affected by Processing and Storage Series II
Authors: Martínez Sidonia , Carballo Javier
Published: January 2024

Food processing has several different purposes [...]
Nondestructive and Rapid Screening of Aflatoxin-Contaminated Single Peanut Kernels Using Field-Portable Spectroscopy Instruments (FT-IR and Raman)
Authors: Yao Siyu , Miyagusuku-Cruzado Gonzalo , West Megan , Nwosu Victor , Dowd Eric , Fountain Jake , Giusti M. Monica , Rodriguez-Saona Luis E.
Published: January 2024

A nondestructive and rapid classification approach was developed for identifying aflatoxin-contaminated single peanut kernels using field-portable vibrational spectroscopy instruments (FT-IR and Raman). Single peanut kernels were either spiked with an aflatoxin solution (30 ppb–400 ppb) or hexane (control), and their spectra were collected via Raman and FT-IR. An uHPLC-MS/MS approach was used to verify the spiking accuracy via determining actual aflatoxin content on the surface of randomly selected peanut samples. Supervised classification using soft independent modeling of class analogies (SIMCA) showed better discrimination between aflatoxin-contaminated (30 ppb–400 ppb) and control peanuts with FT-IR compared with Raman, predicting the external validation samples with 100% accuracy. The accuracy, sensitivity, and specificity of SIMCA models generated with the portable FT-IR device outperformed the methods in other destructive studies reported in the literature, using a variety of vibrational spectroscopy benchtop systems. The discriminating power analysis showed that the bands corresponded to the C=C stretching vibrations of the ring structures of aflatoxins were most significant in explaining the variance in the model, which were also reported for Aspergillus-infected brown rice samples. Field-deployable vibrational spectroscopy devices can enable in situ identification of aflatoxin-contaminated peanuts to assure regulatory compliance as well as cost savings in the production of peanut products.
Estimating In Vitro Protein Digestion and Protein Digestibility Corrected Amino Acid Score of Chicken Breasts Affected by White Striping and Wooden Breast Abnormalities
Authors: Srimarut Yanee , Phanphuet Apinya , Trithavisup Thanatorn , Rattanawongsa Wachiraya , Saenmuangchin Rattaporn , Klamchuen Annop , Malila Yuwares
Published: January 2024

An understanding regarding impacts of growth-related myopathies, i.e., white striping (WS) and wooden breast (WB), on the quality of dietary protein from cooked chicken breast is still limited. This study aimed at comparing protein content and in vitro protein digestion and estimating the in vitro protein digestibility corrected amino acid score (PDCAAS) of cooked chicken meat exhibiting different abnormality levels (i.e., normal, WS, and WS + WB). The results show that the WS + WB samples exhibited lower protein content, greater cooking loss, and greater lipid oxidation than those of normal samples (p < 0.05). No differences in protein carbonyls or the myofibril fragmentation index were found (p ≥ 0.05). Cooked samples were hydrolyzed in vitro using digestive enzyme mixtures that subsequently mimicked the enzymatic reactions in oral, gastric, and intestinal routes. The WS + WB samples exhibited greater values of free NH2 and degree of hydrolysis than the others at all digestion phases (p < 0.05), suggesting a greater proteolytic susceptibility. The in vitro PDCAAS of the WS + WB samples was greater than that of the other samples for pre-school children, school children, and adults (p < 0.05). Overall, the findings suggest that the cooked chicken breast with the WS + WB condition might provide greater protein digestibility and availability than WS and normal chicken breasts.
Boosting Purnica granatum L. Seed Oil Yield: An Adaptive Neuro-Fuzzy Interference System Fuels SC-CO2 Extraction Breakthrough
Authors: Pao-la-or Padej , Marungsri Boonruang , Chirinang Pornariya , Posridee Kakanang , Oonsivilai Ratchadaporn , Oonsivilai Anant
Published: January 2024

This study used supercritical fluid extraction to successfully enhance the conditions for extracting oil from pomegranate seeds. To determine the optimal extraction conditions for maximizing pomegranate oil yield, the researchers employed a Box–Behnken design experimental strategy, involving three parameters with three levels each: extraction pressure, extraction temperature, and extraction time. To determine the optimal optimization conditions, the Response Surface Method (RSM) and the Artificial Neural Fuzzy Intelligent System (ANFIS) were also used. The results revealed a strong correlation with the experimental data, demonstrating that both strategies were helpful in optimizing the extraction process. The ideal extraction parameters, according to this study, were an extraction pressure of 40 MPa, an extraction temperature of 55 °C, and an extraction time of 120 min with a CO2 flow rate of 21.3 L/h.
2023: The Best Year Ever for Future Pharmacology (and Even Better Years to Come)
Authors: Schifano Fabrizio
Published: January 2024

The end of any year provides an opportunity to reflect on the past, and in particular, the past twelve months [...]
A Systematic Patent Review of Connected Vehicle Technology Trends
Authors: Bridgelall Raj
Published: January 2024

Governments and manufacturers anticipate that connected vehicle deployments will reduce accidents, optimize traffic flow, and enhance the driving experience. Although extensive studies focus on the technical aspects of connected vehicles, a gap exists in systematically analyzing the invention trends shaping the field. Insights into these trends is a strategic imperative for policymakers, researchers, and investors alike. This study presents a systematic patent review (SPR) as a robust and adaptable methodological framework for patent analysis. Adapted from the established systematic literature review (SLR), the SPR offers detailed insights into both the thematic and temporal trajectories of innovation in any technology field. The SPR identifies 220 U.S. patents from 2018 to 2022 and classifies them into specific objective categories such as computing resources, cybersecurity, and driving safety, among others. The study notes an increasing focus on driving safety and secure wireless communications, which aligns with broader goals of enhancing safety and situational awareness in transportation. Both the methodological framework and findings address an existing gap in the literature, guide future research, policymaking, and investment in the field of connected vehicles.
Crosslinked Gel Polymer Electrolyte from Trimethylolpropane Triglycidyl Ether by In Situ Polymerization for Lithium-Ion Batteries
Authors: Jin Lei , Lim Hyunmin , Bae Wansu , Song Subeen , Joo Kijong , Jang Hohyoun , Kim Whangi
Published: January 2024

Electrolytes play a critical role in battery performance. They are associated with an increased risk of safety issues. The main challenge faced by many researchers is how to balance the physical and electrical properties of electrolytes. Gel polymer electrolytes (GPEs) have received increasing attention due to their satisfactory properties of ionic conductivity, mechanical stability, and safety. Herein, we develop a gel network polymer electrolyte (GNPE) to address the challenge mentioned earlier. This GNPE was formed by tri-epoxide monomer and bis(fluorosulfonyl)imide lithium salt (LiFSI) via an in situ cationic polymerization under mild thermal conditions. The obtained GNPE exhibited a relatively high ionic conductivity (σ) of 2.63 × 10−4 S cm−1, lithium transference number (tLi+, 0.58) at room temperature (RT), and intimate electrode compatibility with LiFePO4 and graphite. The LiFePO4/GNPE/graphite battery also showed a promising cyclic performance at RT, e.g., a suitable discharge specific capacity of 127 mAh g−1 and a high Coulombic efficiency (>97%) after 100 cycles at 0.2 C. Moreover, electrolyte films showed good mechanical stability and formed the SEI layer on the graphite anode. This study provides a facile method for preparing epoxy-based electrolytes for high-performance lithium-ion batteries (LIBs).
Engagement with mHealth Alcohol Interventions: User Perspectives on an App or Chatbot-Delivered Program to Reduce Drinking
Authors: Sedotto Robyn N. M. , Edwards Alexandra E. , Dulin Patrick L. , King Diane K.
Published: January 2024

Research suggests participant engagement is a key mediator of mHealth alcohol interventions’ effectiveness in reducing alcohol consumption among users. Understanding the features that promote engagement is critical to maximizing the effectiveness of mHealth-delivered alcohol interventions. The purpose of this study was to identify facilitators and barriers to mHealth alcohol intervention utilization among hazardous-drinking participants who were randomized to use either an app (Step Away) or Artificial Intelligence (AI) chatbot-based intervention for reducing drinking (the Step Away chatbot). We conducted semi-structured interviews from December 2019 to January 2020 with 20 participants who used the app or chatbot for three months, identifying common facilitators and barriers to use. Participants of both interventions reported that tracking their drinking, receiving feedback about their drinking, feeling held accountable, notifications about high-risk drinking times, and reminders to track their drinking promoted continued engagement. Positivity, personalization, gaining insight into their drinking, and daily tips were stronger facilitator themes among bot users, indicating these may be strengths of the AI chatbot-based intervention when compared to a user-directed app. While tracking drinking was a theme among both groups, it was more salient among app users, potentially due to the option to quickly track drinks in the app that was not present with the conversational chatbot. Notification glitches, technology glitches, and difficulty with tracking drinking data were usage barriers for both groups. Lengthy setup processes were a stronger barrier for app users. Repetitiveness of the bot conversation, receipt of non-tailored daily tips, and inability to self-navigate to desired content were reported as barriers by bot users. To maximize engagement with AI interventions, future developers should include tracking to reinforce behavior change self-monitoring and be mindful of repetitive conversations, lengthy setup, and pathways that limit self-directed navigation.
Dyslipidemia Is Positively Associated with Chronic Low Back Pain in Korean Women: Korean National Health and Nutrition Examination Survey 2010–2012
Authors: Kim Sunmin , Lee Seon-Mi
Published: January 2024

Background: This study aimed to evaluate the association between chronic low back pain (CLBP) and chronic diseases, such as hypertension, diabetes, and dyslipidemia. Methods: This study was a retrospective analysis using data from the Korea National Health and Nutrition Examination Survey (KNHANES) between 2010–2012 and included women who answered a questionnaire in the KNHANES asking whether they had low back pain for ≥3 months. Participants were divided into non-CLBP and CLBP groups. For statistical analysis, the Student’s t-test, chi-square test, Fisher’s exact test, and logistic regression analysis were performed using SPSS. Results: Of 5961 participants, the non-CLBP group comprised 4098 women and the CLBP group comprised 1863. Adjusted logistic regression model revealed that dyslipidemia was positively associated with CLBP (odds ratio, 1.32; 95% confidence interval, 1.140, 1.530; p < 0.001). However, hypertension and diabetes were not associated with CLBP. Conclusions: Our results suggest that proper treatment of dyslipidemia may contribute to lowering the risk of CLBP later in life.
Development and Effectiveness of a Rapid Cycle Deliberate Practice Neonatal Resuscitation Simulation Program: A Quasi-Experimental Study
Authors: Yang Sun-Yi , Oh Yun-Hee
Published: January 2024

The Rapid Cycle Deliberate Practice (RCDP) simulation during neonatal resuscitation program (NRP) training provides in-event feedback for each simulation step, repeats the simulation from the beginning, and undergoes a continuous improvement process. It also offers after-event debriefing that involves follow-up discussion and reflection after completing simulations. These two methods differ in the timing and frequency of feedback application, and there may be differences in the effectiveness of neonatal resuscitation training. A quasi-experimental simulation study with a pre- and post-test design was used; the experimental group received RCDP simulation NRP training, based on the self-determination theory, while the control group received an after-event debriefing, following the NRP scenario. The experimental group displayed significantly improved clinical decision-making skills compared with the control group. When responding to emergencies involving high-risk newborns, we found that RCDP simulation during NRP training and better preparation for neonatal resuscitation among nursing students improved outcomes for newborns.
Oral Adverse Events Associated with BRAF and MEK Inhibitors in Melanoma Treatment: A Narrative Literature Review
Authors: Basilicata Michele , Terrano Vincenzo , D'Aurelio Alessandro , Bruno Giovanni , Troiani Teresa , Bollero Patrizio , Napolitano Stefania
Published: January 2024

Background: Melanoma cancer represents the most lethal type of skin cancer originating from the malignant transformation of melanocyte cells. Almost 50% of melanomas show the activation of BRAF mutations. The identification and characterization of BRAF mutations led to the development of specific drugs that radically changed the therapeutic approach to melanoma. Methods: We conducted a narrative review of the literature according to a written protocol before conducting the study. This article is based on previously conducted studies. We identified articles by searching electronic databases (Medline, Google Scholar and PubMed). We used a combination of “melanoma”, “Braf-Mek inhibitors”, “ targeted therapy” and “oral side effects”. Results: Eighteen studies were reported in this article showing the relationship between the use of targeted therapy in melanoma cancer and the development of oral side effects, such as mucositis, hyperkeratosis and cellular proliferation. Conclusion: Targeted therapy plays an important role in the treatment of melanoma cancer, showing a notable increase in response rate, prolonged progression-free survival and overall survival in BRAF-mutated melanoma patients. Oral side effects represent a common finding over the course of treatment. However, these adverse effects can be easily managed in a multidisciplinary approach involving collaboration between medical oncologists and dental doctors.
Death Anxiety in Caregivers of Chronic Patients
Authors: Quevedo-Blasco Raúl , Díaz-Román Amparo , Vega-García Alberto
Published: January 2024

This study aimed to determine the extent to which caregivers of patients with chronic illnesses experience death anxiety, and which variables from caregivers and patients might potentially be related to their death anxiety. It also aimed to compare the levels of death anxiety between patients and caregivers. Web of Science, Scopus, PubMed, Psychology Database, Cochrane, and Google Scholar were searched for original studies available until December 2022 that quantitatively addressed death anxiety in family and informal caregivers of individuals with chronic illnesses. The methodological quality of the included studies was assessed, and a meta-analysis was conducted using Hedges’ g as the effect size index and the DerSimonian–Laird method to analyze differences between patients and caregivers in death anxiety. The results of the 11 included studies showed moderate levels of death anxiety in caregivers, and the meta-analysis (k = 7; 614 patients and 586 caregivers) revealed non-significant differences between the death anxiety experienced by patients and caregivers (pooled Hedges’ g = −0.03, 95% CI = −0.29 to 0.25, p = 0.802). Some sociodemographic and psychological factors (e.g., gender, depression, and anxiety) might be related to the death anxiety experienced, but additional research is necessary to validate these findings.
Sharing Heritage through Open Innovation—An Attempt to Apply the Concept of Open Innovation in Heritage Education and the Reconstruction of Cultural Identity
Authors: Szromek Adam R. , Bugdol Marek
Published: January 2024

The topic of cultural heritage is the subject of many interdisciplinary studies. So far, these studies have focused on the issues of classifying particular types of heritage, their functions and benefits, components and determinants. However, relatively less attention was paid to the dimension of a methodical approach to education and rebuilding cultural identity through heritage. Meanwhile, generational changes, especially in the dimension of knowledge perception, indicate such a need. The aim of this article is to present the perspective of using open innovations in the transfer of cultural heritage used in shaping cultural identity and education. Our review and conceptual article is an attempt to draw attention to the problem of changes in the perception of cultural heritage by generations born in the era of the digital revolution and the need to take these changes into account in heritage education. Taking these conditions into account allowed the authors to develop a model for generating open innovation in the outside-in process and then to develop a model for making it available through the inside-out process. The role of education in this process was also emphasized.
Harmful Cyanobacterial Blooms: Going beyond the “Green” to Monitor and Predict HCBs
Authors: de Figueiredo Daniela R.
Published: January 2024

Under the Climate Change scenario, the occurrence of Harmful Cyanobacterial Blooms (HCBs) is an increasingly concerning problem. Particularly for inland freshwaters, that have human populations depending on them for consumption or recreation, HCBs can lead to serious ecological damages and socio-economic impacts, but also to health risks for local communities. From satellite imagery to molecular data, there is an increasing number of methodological approaches that can help improve the monitoring and prediction of cyanobacterial blooms. However, although each methodology has its own strengths and limitations, generally there is a lack of data addressing specific and intraspecific information, which has implications for the modelling and prediction of the real dynamics and toxicity of HCBs. The present review intends to make a quick overview on current approaches to monitor cyanobacterial blooms and provide a tier-based integrative perspective for their application. A transversal monitoring at a wide scale should be enhanced but cannot rely only on pigment levels but rather include the specific and intraspecific diversity information that can be obtained from modern molecular tools. This is crucial to achieve the effective prediction, monitoring and management of HCBs under their increasing occurrence and severity trends in freshwaters.