bluuebunny/crossref_metadata_2025 huggingface dataset:
The Correlation between Transperineal Shear-Wave Elastography and Transabdominal Ultrasound When Assessing Pelvic Floor Function in Nulliparous Women
Authors: Do Yerim , Lim Youngeun , Lee Soohyun , Lee Haneul
Published: September 2023

Pelvic floor muscles (PFMs) play a crucial role in maintaining pelvic organ support and continence. However, pelvic floor dysfunction (PFD), often resulting from insufficient PFM control, poses a substantial global health challenge for women. This study aims to explore the relationship between levator ani muscle elasticity when assessed through transperineal shear-wave elastography (SWE) and bladder base displacement, quantified using transabdominal ultrasonography (TAUS), as a means to comprehensively evaluate PFM function. A total of 42 nulliparous women participated in this study. Participants received instructions on proper PFM contractions using Kegel exercises. Levator ani muscle elasticity was assessed both at rest and during contractions using transperineal SWE, while bladder base displacement was simultaneously measured through TAUS. Repeated measures demonstrated strong intraclass correlation coefficients of 0.906 at rest and 0.687 during contractions for levator ani muscle elasticity. The mean elasticity values were 24.7 ± 4.5 kPa at rest and 62.1 ± 10.4 kPa during contractions. Additionally, the mean bladder base displacement was 7.2 ± 2.5 mm, and the normalized bladder base displacement via body mass index was 0.3 ± 0.1 mm. Significantly, a moderate correlation was identified between the PFM function, represented by the difference in levator ani elasticity during contractions and resting, and bladder base displacement (r = 0.486, p = 0.001). These findings underscore the potential utility of transperineal SWE as a reliable and noninvasive method to assess levator ani muscle elasticity and, consequently, PFM function. In conclusion, this study sheds light on the interplay between PFM elasticity and bladder base displacement, offering insights into PFM function assessments. The observed correlation suggests the clinical relevance of SWE in providing valuable information for treatment planning in PFD. These findings contribute to a deeper understanding of PFM dynamics, ultimately aiding in the effective management of PFD among women.
One-Stage Detection without Segmentation for Multi-Type Coronary Lesions in Angiography Images Using Deep Learning
Authors: Wu Hui , Zhao Jing , Li Jiehui , Zeng Yan , Wu Weiwei , Zhou Zhuhuang , Wu Shuicai , Xu Liang , Song Min , Yu Qibin , Song Ziwei , Chen Lin
Published: September 2023

It is rare to use the one-stage model without segmentation for the automatic detection of coronary lesions. This study sequentially enrolled 200 patients with significant stenoses and occlusions of the right coronary and categorized their angiography images into two angle views: The CRA (cranial) view of 98 patients with 2453 images and the LAO (left anterior oblique) view of 176 patients with 3338 images. Randomization was performed at the patient level to the training set and test set using a 7:3 ratio. YOLOv5 was adopted as the key model for direct detection. Four types of lesions were studied: Local Stenosis (LS), Diffuse Stenosis (DS), Bifurcation Stenosis (BS), and Chronic Total Occlusion (CTO). At the image level, the precision, recall, mAP@0.1, and mAP@0.5 predicted by the model were 0.64, 0.68, 0.66, and 0.49 in the CRA view and 0.68, 0.73, 0.70, and 0.56 in the LAO view, respectively. At the patient level, the precision, recall, and F1scores predicted by the model were 0.52, 0.91, and 0.65 in the CRA view and 0.50, 0.94, and 0.64 in the LAO view, respectively. YOLOv5 performed the best for lesions of CTO and LS at both the image level and the patient level. In conclusion, the one-stage model without segmentation as YOLOv5 is feasible to be used in automatic coronary lesion detection, with the most suitable types of lesions as LS and CTO.
A Rare Axillary Lymph Node Metastasis on 18F-FDG PET/CT for Staging in a Patient with Common Bile Duct Cancer
Authors: Lee Yeongjoo , Won Hye Sung , Seo Kyung Jin , Na Sae Jung
Published: September 2023

Distant metastasis of cholangiocarcinoma is most commonly diagnosed in the liver; however, it can also be found in the lungs, distant lymph nodes, bones, and brain. Distant lymph node metastasis outside the abdominal region without concurrent abdominal metastasis is exceedingly rare in extrahepatic cholangiocarcinoma. Herein, we present interesting 18F-FDG PET/CT images of a 49-year-old male patient with common bile duct cancer. In this case, the patient, who was scheduled for surgery, unexpectedly showed axillary lymph node metastasis on a preoperative 18F-FDG PET scan, which was subsequently confirmed via histological examination. Although such cases are exceptionally rare, this accurate diagnosis prompted a modification of the treatment plan, leading to a positive therapeutic response.
A Deep Learning Approach with Extensive Sentiment Analysis for Quantitative Investment
Authors: Li Wang , Hu Chaozhu , Luo Youxi
Published: September 2023

Recently, deep-learning-based quantitative investment is playing an increasingly important role in the field of finance. However, due to the complexity of the stock market, establishing effective quantitative investment methods is facing challenges from various aspects because of the complexity of the stock market. Existing research has inadequately utilized stock news information, overlooking significant details within news content. By constructing a deep hybrid model for comprehensive analysis of historical trading data and news information, complemented by momentum trading strategies, this paper introduces a novel quantitative investment approach. For the first time, we fully consider two dimensions of news, including headlines and contents, and further explore their combined impact on modeling stock price. Our approach initially employs fundamental analysis to screen valuable stocks. Subsequently, we built technical factors based on historical trading data. We then integrated news headlines and content summarized through language models to extract semantic information and representations. Lastly, we constructed a deep neural model to capture global features by combining technical factors with semantic representations, enabling stock prediction and trading decisions. Empirical results conducted on over 4000 stocks from the Chinese stock market demonstrated that incorporating news content enriched semantic information and enhanced objectivity in sentiment analysis. Our proposed method achieved an annualized return rate of 32.06% with a maximum drawdown rate of 5.14%. It significantly outperformed the CSI 300 index, indicating its applicability to guiding investors in making more effective investment strategies and realizing considerable returns.
A Multi-Strategy Crazy Sparrow Search Algorithm for the Global Optimization Problem
Authors: Jiang Xuewei , Wang Wei , Guo Yuanyuan , Liao Senlin
Published: September 2023

A multi-strategy crazy sparrow search algorithm (LTMSSA) for logic-tent hybrid chaotic maps is given in the research to address the issues of poor population diversity, slow convergence, and easily falling into the local optimum of the sparrow search algorithm (SSA). Firstly, the LTMSSA employs an elite chaotic backward learning strategy and an improved discoverer-follower ratio factor to improve the population’s quality and diversity. Secondly, the LTMSSA updates the positions of discoverers and followers by the crazy operator and the Lévy flight strategy to expand the selection range of target following individuals. Finally, during the algorithm’s optimization search, the LTMSSA introduces the tent hybrid and Corsi variable perturbation strategies to improve the population’s ability to jump out of the local optimum. Different types and dimensions of test functions are used as performance benchmark functions to test the performance of the LTMSSA with SSA variants and other algorithms. The simulation results show that the LTMSSA can jump out of the optimal local solution, converge faster, and have higher accuracy. Its overall performance is better than the other seven algorithms, and the LTMSSA can find smaller optimal values than other algorithms in the welded beam and reducer designs. The results confirm that the LTMSSA is an effective aid for computationally complex practical tasks, provides high-quality solutions, and outperforms other algorithms.
Soft Error Simulation of Near-Threshold SRAM Design for Nanosatellite Applications
Authors: Artola Laurent , Ruard Benjamin , Forest Julien , Hubert Guillaume
Published: September 2023

This paper presents the benefit of the near-threshold design of random-access memory (SRAM) design to reduce software errors during very low-power operations in nanosatellites. The near-threshold design is based on an optimization of the use of the Schmitt trigger structure for a 45 nm technology. The results of the soft error susceptibility of the optimized design are compared to a standard 6T SRAM cell. These two designs are modeled and validated by comparing the results with experimental measurements of both static noise margin (SNM) and single event upset (SEU). The optimized circuit reduces the multiple upsets occurrence from 95% down to 14%. Based on the use of simulation tools, the paper demonstrates that the near-threshold design of SRAM is an excellent candidate for the radiation point of view for agile nanosatellites. The results computed for the near-threshold SRAM device demonstrate an improvement of a factor of up to 25 of the soft error rate (SER) in a GEO orbit.
YOLO v7-ECA-PConv-NWD Detects Defective Insulators on Transmission Lines
Authors: Zhang Jianrui , Wei Xia , Zhang Linxuan , Yu Libin , Chen Yannan , Tu Meiqi
Published: September 2023

This paper proposes an enhanced YOLO v7-based method for detecting insulator defects in transmission lines, addressing the challenges of low accuracy and high leakage rates caused by complex backgrounds and electric poles alongside varying sizes of insulator targets in the image. Firstly, to address the issue of background interference and improve the importance of insulator features, a lightweight attention mechanism named Efficient Channel Attention (ECA) was introduced. With the incorporation of ECA, this model could effectively suppress background noise and provide more focus to insulator regions, thus enhancing its ability to detect insulator defects accurately. Secondly, a partial convolution (PConv) approach was employed in the backbone network instead of conventional convolution, which learned some important channels. This substitution improved both the network model’s accuracy and the training speed. Finally, the Normalized Wasserstein Distance (NWD) prevented insulator features from being lost during pre-feature extraction, which reduced the leakage rate and improved the detection accuracy of small target insulators and defective insulators. The experimental results demonstrate that the improved YOLO v7 network model achieved an average detection accuracy (mAP) of 98.1%, recall of 93.7%, and precision of 96.8% on the TISLTR dataset. On the FISLTR dataset, the average detection accuracy (mAP) for flashover insulators was 93%, with a recall of 92.3% and precision of 87.1%. The average detection accuracy (mAP) for broken insulators was 92.2%, with a recall of 90.3% and a precision of 95.2%. These metrics demonstrate significant improvements in both datasets, highlighting the proposed algorithms’ strong generalization capability and practicable potential to detect insulator targets.
Anomaly Detection Methods for Industrial Applications: A Comparative Study
Authors: Panza Maria Antonietta , Pota Marco , Esposito Massimo
Published: September 2023

Anomaly detection (AD) algorithms can be instrumental in industrial scenarios to enhance the detection of potentially serious problems at a very early stage. Of course, the “Industry 4.0” revolution is fostering the implementation of intelligent data-driven decisions in industry based on increasingly efficient machine learning (ML) algorithms. Most well-known AD methods use a supervised learning approach focusing on fault classification. They assume the availability of labeled data for both normal and anomalous classes. However, in many industrial environments, a labeled set of anomalous data instances is more challenging to obtain than a labeled set of normal data. Hence, this work implements an unsupervised approach based on two different methods using a typical benchmark bearing-fault dataset. The first method relies on the manual extraction of typical vibration metrics provided as input to an ML algorithm. The second one is based on a deep learning (DL) approach, automatically learning latent representation from raw data. The performance metrics demonstrate that both approaches can distinguish the state of a bearing from normal to faulty. DL methodology proves a higher accuracy rate in recognizing faults and a better ability to provide information about the fault size.
Model Predictive Secondary Frequency Control for Islanded Microgrid under Wind and Solar Stochastics
Authors: Zhao Zhongwei , Zhang Xiangyu , Zhong Cheng
Published: September 2023

As microgrids are the main carriers of renewable energy sources (RESs), research on them has been receiving more attention. When considering the increase in the penetration of renewable energy sources/distributed generators (DGs) in microgrids, their low inertia and high stochastic power disturbance pose more challenges for frequency control. To address these challenges, this paper proposes a model predictive control (MPC) secondary control that incorporates an unknown input observer and where RESs/DGs use a deloading virtual synchronous generator (VSG) control to improve the system’s inertia. An unknown input observer is employed to estimate the system states and random power disturbance from the RESs/DGs and load to improve the effect of the predictive control. The distributed restorative power of each DG is obtained by solving the quadratic programming (QP) optimal problem with variable constraints. The RESs/DGs are given priority to participate in secondary frequency control due to the proper weighting factors being set. An islanded microgrid model consisting of multiple photovoltaic and wind power sources was built. The simulation results demonstrate that the proposed method improves the system frequency, restoration speed, and reduces frequency deviations compared with the traditional secondary control method.
Forecasting of Energy Balance in Prosumer Micro-Installations Using Machine Learning Models
Authors: Popławski Tomasz , Dudzik Sebastian , Szeląg Piotr
Published: September 2023

It is indisputable that power systems are being transformed around the world to increase the use of RES and reduce the use of fossil fuels in overall electricity production. This year, the EU Parliament adopted the Fit for 55 package, which should significantly reduce the use of fossil fuels in the energy balance of EU countries while increasing the use of RES. At the end of 2022, the total number of prosumer installations in Poland amounted to about one million two hundred thousand. Such a high saturation of prosumer micro-installations in the power system causes many threats resulting from their operation. These threats result, among others, from the fact that photovoltaics are classified as unstable sources and the expected production of electricity from such installations is primarily associated with highly variable weather conditions and is only dependent on people to a minor extent. Currently, there is a rapid development of topics related to forecasting the volume of energy production from unstable sources such as wind and photovoltaic power plants. This issue is being actively developed by research units around the world. Scientists use a whole range of tools and models related to forecasting techniques, from physical models to artificial intelligence. According to our findings, the use of machine learning models has the greatest chance of obtaining positive prognostic effects for small, widely distributed prosumer installations. The present paper presents the research results of two energy balance prediction algorithms based on machine learning models. For forecasting, we proposed two regression models, i.e., regularized LASSO regression and random forests. The work analyzed scenarios taking into account both endogenous and exogenous variables as well as direct multi-step forecasting and recursive multi-step forecasting. The training was carried out on real data obtained from a prosumer micro-installation. Finally, it was found that the best forecasting results are obtained with the use of a random forest model trained using a recursive multi-step method and an exogenous scenario.
Research on the Modulation and Control Strategy for a Novel Single-Phase Current Source Inverter
Authors: Zhang Yi , Yang Tao , Miao Yiru
Published: September 2023

Compared to the voltage source inverter, the current source inverter (CSI) can boost voltage and improve filtering performance. However, the DC side of CSI is not a real current source, and the DC input current comprises a DC power supply and an inductor. In the switching process, the DC-link inductor is charged or discharged and is in an uncontrollable state. This paper proposes a novel CSI topology containing five switching tubes and a modulation strategy based on the hysteresis control strategy of the DC-link current. Due to the conduction and switching loss being positive to the DC-link current, the calculation method for the least reference value of the DC-link current is derived to meet power requirements. By constructing a virtual axis, we then present the control strategy of the output voltage in a two-phase rotating reference frame. Finally, we carry out the simulation and experiment are to validate the proposed topology, modulation, and control strategy.
Effects of Prescribed Burning on Surface Dead Fuel and Potential Fire Behavior in Pinus yunnanensis in Central Yunnan Province, China
Authors: Wang Jin , Hong Ruicheng , Ma Cheng , Zhu Xilong , Xu Shiying , Tang Yanping , Li Xiaona , Yan Xiangxiang , Wang Leiguang , Wang Qiuhua
Published: September 2023

Prescribed burning is a widely used fuel management employed technique to mitigate the risk of forest fires. The Pinus yunnanensis Franch. forest, which is frequently prone to forest fires in southwestern China, serves as a prime example for investigating the effects of prescribed burning on the flammability of surface dead fuel. This research aims to establish a scientific foundation for managing dead fuel in forests, as well as fire prevention and control strategies. Field data was collected from P. yunnanensis forests located in central Yunnan Province in 2021 and 2022. The study implemented a randomized complete block design with two blocks and three treatments: an unburned control (UB), one year after the prescribed burning (PB1a), and three years after the prescribed burning (PB3a). These treatments were evaluated based on three indices: surface dead-bed structure, physicochemical properties, and potential fire behavior parameters. To analyze the stand characteristics of the sample plots, a paired t-test was conducted. The results indicated no significant differences in the stand characteristics of P. yunnanensis following prescribed burning (p > 0.05). Prescribed burning led to a significant decrease in the average surface dead fuel load from 10.24 t/ha to 3.70 t/ha, representing a reduction of 63.87%. Additionally, the average fire−line intensity decreased from 454 kw/m to 190 kw/m, indicating a decrease of 58.15%. Despite prescribed burning, there were no significant changes observed in the physical and chemical properties of dead fuels (p > 0.05). However, the bed structure of dead fuels and fire behavior parameters exhibited a significant reduction compared with the control sample site. The findings of this study provide essential theoretical support for the scientific implementation of prescribed burning programs and the accurate evaluation of ecological and environmental effects post burning.
Functional and Antioxidant Evaluation of Two Ecotypes of Control and Grafted Tree Tomato (Solanum betaceum) at Different Altitudes
Authors: Coyago-Cruz Elena , Guachamin Aida , Méndez Gabriela , Moya Melany , Martínez Aníbal , Viera William , Heredia-Moya Jorge , Beltrán Elena , Vera Edwin , Villacís Michael
Published: September 2023

Tree tomato (Solanum betaceum) is susceptible to nematode attack; for this reason, grafting is used as an alternative to reduce this impact. In this study, the bioactive compounds of the fruit (shell, pulp, and seed jelly) of two tree tomato ecotypes (‘giant orange’ and ‘giant purple’) were evaluated in both control and grafted plants grown at different altitudes (2010–2250, 2260–2500, 2510–2750 and 2760–3000 masl). Commercial quality, vitamin C, organic acids, phenolics, carotenoids and antioxidant activity were determined by microextraction and quantified by liquid chromatography (RRLC) or spectrophotometry (microplate reader). The results showed high concentrations of vitamin C, organic acids and antioxidant activity in the seed jelly, organic acids in the pulp and phenolic compounds, carotenoids, and antioxidant activity in the shell. The main phenolics were ferulic acid, caffeic acid and luteolin, while the main carotenoids were lutein, B-cryptoxanthin and B-carotene. Multivariate analysis showed that tree tomato quality was mainly influenced by altitude and fruit part and that grafting positively affected soluble solids for both ecotypes and all altitudes.
Assessment of the Fruit Chemical Characteristics and Antioxidant Activity of Different Mulberry Cultivars (Morus spp.) in Semi-Arid, Sandy Regions of China
Authors: Sun Zhiyu , Zhou Yongbin , Zhu Wenxu , Yin You
Published: September 2023

As a traditional cash crop with ecological and nutritional values, mulberry is gradually expanding its consumption worldwide due to its great regional adaptability and superior health functions. The widespread interest in nutrients has led to a growing need to explore in depth the health benefits of mulberries. Many studies are actively being conducted to investigate the adaptability of the diversity of mulberries in different applications. This study systematically investigated the physicochemical properties and antioxidant activity of four mulberry genotypes cultivated in China’s semi-arid sandy regions to better understand the composition and health-promoting potential of this super crop. Chemical composition identification was identified via HPLC and antioxidant activity was further determined via DPPH and FRAP. The moisture, crude protein, ash, soluble solids, phenolics, anthocyanins, and flavonoids contents of mulberry were comparatively analyzed. The study revealed that the four mulberry genotypes showed significant differences in quality and content of the analyzed characteristics. The greatest antioxidant activity was found in Shensang 1, which had the most soluble solids (17%) and the highest amounts of free sugar (fructose: 5.14% and glucose: 5.46%). Ji’an had the most minerals (K: 2.35 mg/g, Ca: 2.27 mg/g, and Fe: 467.32 mg/kg) and it also contained chlorogenic acid, which has the potential to be turned into a natural hypoglycemic agent. PCA and Pearson correlation analysis indicated that the antioxidant activity was closely related to the chemical contents of total phenols, flavonoids, anthocyanins, and soluble sugars. If the antioxidant activity and nutrient content of the developed plants are considered, Shen Sang 1 is the most favorable variety. This finding can be used to support the widespread cultivation of mulberries to prevent desertification as well as to promote the development of the mulberry industry.
Kombucha Fermentation of Olympus Mountain Tea (Sideritis scardica) Sweetened with Thyme Honey: Physicochemical Analysis and Evaluation of Functional Properties
Authors: Geraris Kartelias Ioannis , Karantonis Haralabos Christos , Giaouris Efstathios , Panagiotakopoulos Ioannis , Nasopoulou Constantina
Published: September 2023

This study implemented kombucha fermentation of Olympus Mountain tea (Sideritis scardica) sweetened with honey (OMTWH) in order to investigate the potential for producing a novel beverage with functional properties. The increase in the total count of bacteria and yeast suggests that the OMTWH acts as a viable substrate for supporting the proliferation of the microorganisms of the Kombucha symbiotic culture. The fermentation resulted in a reduction in pH and increased total titratable acidity. After fermentation, a statistically significant increase in the vitamins C, B1, B2, B6, B7, and B12 content was observed (p < 0.05). Total phenolics and antioxidant activity of the fermented beverage was significantly enhanced, as assessed by the method of Folin–Ciocalteu and ABTS assay, respectively. Results revealed that OMTWH had a potent inhibitory activity of α-amylase, α-glucosidase, acetylcholinesterase, and butyrylcholinesterase; OMTWH fermented with a kombucha consortium exhibited even higher inhibition. Hence, the process of kombucha fermentation can convert OMTWH into a novel beverage with enhanced functional properties.
The Role of Hemp (Cannabis sativa L.) as a Functional Food in Vegetarian Nutrition
Authors: Rizzo Gianluca , Storz Maximilian Andreas , Calapai Gioacchino
Published: September 2023

Recently, there has been a renewed interest in Cannabis sativa and its uses. The recreational use of inflorescences as a source of THC has led to the legal restriction of C. sativa cultivation to limit the detrimental effects of psychotropic substance abuse on health. However, this has also limited the cultivation of textile/industrial varieties with a low content of THC used for textile and nutritional purposes. While previously the bans had significantly penalized the cultivation of C. sativa, today many countries discriminate between recreational use (marijuana) and industrial and food use (hemp). The stalks of industrial hemp (low in psychotropic substances) have been used extensively for textile purposes while the seeds are nutritionally versatile. From hemp seeds, it is possible to obtain flours applicable in the bakery sector, oils rich in essential fatty acids, proteins with a high biological value and derivatives for fortification, supplementation and nutraceutical purposes. Hemp seed properties seem relevant for vegetarian diets, due to their high nutritional value and underestimated employment in the food sector. Hemp seed and their derivatives are a valuable source of protein, essential fatty acids and minerals that could provide additional benefit to vegetarian nutrition. This document aims to explore the information available in the literature about hemp seeds from a nutritional point of view, highlighting possible beneficial effects for humans with particular attention to vegetarian nutrition as a supplemental option for a well-planned diet.
Volatiles of All Native Juniperus Species Growing in Greece—Antimicrobial Properties
Authors: Fotiadou Evgenia , Panou Evgenia , Graikou Konstantia , Sakellarakis Fanourios-Nikolaos , Chinou Ioanna
Published: September 2023

Juniper (Juniperus L., Cupressaceae Bartlett) trees are of high commercial value, as their essential oils are widely applied in the food and cosmetic industries due to their bioactivities. The genus Juniperus comprises eight species in Greece, and in the current work, we report the chemical analyses of their volatiles (GC-MS) obtained from the leaves and cones of all indigenous species found in the country, as well as their antimicrobial properties. The studied species were J. oxycedrus L., J. excelsa M. Bieb., J. foetidissima Willd., J. communis L., J. macrocarpa Sibth. & Sm., J. turbinata Guss., J. sabina L. and J. drupacea Labill., and a total of 164 constituents were identified. Monoterpenes, followed by sesquiterpenes, appeared as the dominant compounds in all investigated species. Most of the studied essential oils belonged to the α-pinene chemotype, with amounts of α-cedrol, sabinene, limonene and myrcene among the abundant metabolites, except for J. sabina, which belonged to the sabinene chemotype. Through antimicrobial tests, it was observed that the essential oils of most of the cones showed better activity compared with the respective leaves. The essential oils of the cones of J. foetidissima, J. communis and J. turbinata showed the strongest activity against the tested microorganisms. Additionally, in these three species, the content of thujone, which is a toxic metabolite found in essential oils of many Juniperus species, was considerably low. Taking into consideration the chemical profile, safety and antimicrobial activity, these three Greek Juniperus species seemed to provide the most promising essential oils for further exploitation in the food and cosmetics industries.
Evaluation of the Effect of Preharvest Melatonin Spraying on Fruit Quality of ‘Yuluxiang’ Pear Based on Principal Component Analysis
Authors: Zhao Liangliang , Yan Shuai , Wang Yufei , Xu Gongxun , Zhao Deying
Published: September 2023

Melatonin (MT), an indoleamine compound, has a pleiotropic effect on plant growth and development and can regulate the quality of tree fruit. Systematic research on the effect of preharvest MT spraying on pear fruit quality and technical solutions for MT application to regulate pear fruit quality are still lacking. Thus, here we aimed to evaluate the effects of different spraying times, concentrations, and exogenous MT application times on ‘Yuluxiang’ pear fruit quality. Our results showed that the single fruit weight and vertical and horizontal diameters of pear fruit sprayed with MT twice at 30 and 90 d after full bloom were the largest, and the red and green values of the treatment were the highest. MT-treated pears had higher contents of total soluble solids, soluble sugar, sucrose, sorbitol, fructose, and glucose and lower contents of titratable acid, malic acid, and citric acid. Moreover, exogenous MT treatment increased the pear peel strength. Based on the principal component analysis of 10 fruit quality indices, the suitable periods for MT spraying on ‘Yuluxiang’ pears were 30 and 90 d after full bloom, the suitable concentration was 100 μmol/L, and the suitable number of times was two. This study provides a theoretical reference for optimizing MT application and improving pear fruit quality.
Biocontrol Efficacy of Metschnikowia spp. Yeasts in Organic Vineyards against Major Airborne Diseases of Table Grapes in the Field and in Postharvest
Authors: Lombardo Monia Federica , Panebianco Salvina , Restuccia Cristina , Cirvilleri Gabriella
Published: September 2023

The aim of this work was to evaluate the efficacy of two antagonistic yeasts, Metschnikowia pulcherrima strain MPR3 and M. fructicola strain NRRL Y-27328 (commercial product NOLI), applied in addition to the “on-farm biological treatments” (BIO) carried out during the production season, for the containment of powdery mildew and grey mould diseases on organic table grapes ‘Italia’. The yeast strains were applied in the field three times, and their efficacy was evaluated during the production season and under postharvest conditions. Overall, M. pulcherrima MPR3 combined with BIO treatments reduced disease incidence caused by Erysiphe necator and disease incidence and severity caused by Botrytis cinerea with values between 67.8% and 86.2%, showing higher efficacy than BIO treatments applied alone and in combination with NOLI. Field treatments based on BIO+MPR3 maintained their performance also during fruit storage, protecting grape berries from grey mould development to a greater extent than the other treatments (disease reduction of about 98%). Thus, the presence of M. pulcherrima MPR3 seems to improve disease management both in the field and in postharvest environments, without negative impacts on grape microbial communities. These findings highlight the potential of M. pulcherrima MPR3 as a promising alternative strategy for disease control in organic vineyards and in postharvest, providing sustainable solutions to improve food quality and safety.
Multipronged Approach to Profiling Metabolites in Beta vulgaris L. Dried Pulp Extracts Using Chromatography, NMR and Other Spectroscopy Methods
Authors: Fiadorwu Joshua , Subedi Kiran , Todd Daniel , Basti Mufeed M.
Published: September 2023

Beetroot (Beta vulgaris L.) is known for being a rich source of phytochemicals, minerals and vitamins. This study aims to show how the combination of extraction/chromatography/mass spectrometry and NMR offers an efficient way to profile metabolites in the extracts of beetroot. Such combination may lead to the identification of more nutritional or medicinal compounds in natural products, and it is essential for our ongoing investigation to study the selective adsorption/desorption of these metabolites’ on/off nanoparticles. The aqueous and organic extracts underwent analyses using UV-vis spectroscopy; GC-MS; LC-MS; 1H, 13C, 31P, TOCSY, HSQC, and selective TOCSY NMR experiments. Polar Extract: The two forms of betalain pigment were identified by UV-vis and LC MS. Fourteen amino acids, sucrose, and other compounds, among which is riboflavin, were identified by LC-MS. Two-dimensional TOCSY showed the spin coupling correlations corresponding to some of these compounds. The HSQC spectrum showed 1H/13C spin correlation in sucrose, confirming its high abundance in beetroot. Organic Extract: GC-MS data enabled the identification of several compounds including six fatty acid methyl esters (FAME) with higher than, on average, 90% similarity score. Selective TOCSY NMR data showed the spin coupling pattern corresponding to oleic, linoleic, and linolenic fatty acids. 31P NMR spectra indicate that phospholipids exist in both the organic and aqueous phase.
Effect of Heat Treatment on Protein Self-Digestion in Ruminants’ Milk
Authors: Leite Juliana A. S. , Montoya Carlos A. , Maes Evelyne , Hefer Charles , Cruz Raul A. P. A. , Roy Nicole C. , McNabb Warren C.
Published: September 2023

This study investigated whether heat treatments (raw, 63 °C for 30 min, and 85 °C for 5 min) affect protein hydrolysis by endogenous enzymes in the milk of ruminants (bovine, ovine, and caprine) using a self-digestion model. Self-digestion consisted of the incubation for six hours at 37 °C of the ruminants’ milk. Free amino group concentration was measured by the o-phthaldialdehyde method, and peptide sequences were identified by chromatography-mass spectrometry. Results showed that heat treatments prior to self-digestion decreased the free NH2 by 59% in bovine milk heated at 85 °C/5 min, and by 44 and 53% in caprine milk heated at 63 °C/30 min and 85 °C/5 min, respectively. However, after self-digestion, only new free amino groups were observed for the raw and heated at 63 °C/30 min milk. β-Casein was the most cleaved protein in the raw and heated at 63 °C/30 min bovine milk. A similar trend was observed in raw ovine and caprine milk. Self-digestion increased 6.8-fold the potential antithrombin peptides in the bovine milk heated at 63 °C/30 min. Enhancing bioactive peptide abundance through self-digestion has potential applications in the industry for functional products. Overall, heat treatments affected the free amino groups according to the species and heat treatment applied, which was reflected in the varying degrees of cleaved peptide bonds and peptides released during self-digestion.
Three-Dimensional Printing Parameter Optimization for Salmon Gelatin Gels Using Artificial Neural Networks and Response Surface Methodology: Influence on Physicochemical and Digestibility Properties
Authors: Carvajal-Mena Nailín , Tabilo-Munizaga Gipsy , Saldaña Marleny D. A. , Pérez-Won Mario , Herrera-Lavados Carolina , Lemus-Mondaca Roberto , Moreno-Osorio Luis
Published: September 2023

This study aimed to optimize the 3D printing parameters of salmon gelatin gels (SGG) using artificial neural networks with the genetic algorithm (ANN-GA) and response surface methodology (RSM). In addition, the influence of the optimal parameters obtained using the two different methodologies was evaluated for the physicochemical and digestibility properties of the printed SGG (PSGG). The ANN-GA had a better fit (R2 = 99.98%) with the experimental conditions of the 3D printing process than the RSM (R2 = 93.99%). The extrusion speed was the most influential parameter according to both methodologies. The optimal values of the printing parameters for the SGG were 0.70 mm for the nozzle diameter, 0.5 mm for the nozzle height, and 24 mm/s for the extrusion speed. Gel thermal properties showed that the optimal 3D printing conditions affected denaturation temperature and enthalpy, improving digestibility from 46.93% (SGG) to 51.52% (PSGG). The secondary gel structures showed that the β-turn structure was the most resistant to enzymatic hydrolysis, while the intermolecular β-sheet was the most labile. This study validated two optimization methodologies to achieve optimal 3D printing parameters of salmon gelatin gels, with improved physicochemical and digestibility properties for use as transporters to incorporate high value nutrients to the body.
Epigenetic Findings in Twins with Esophageal Atresia
Authors: Błoch Michal , Gasperowicz Piotr , Gerus Sylwester , Rasiewicz Katarzyna , Lebioda Arleta , Skiba Pawel , Płoski Rafal , Patkowski Dariusz , Karpiński Pawel , Śmigiel Robert
Published: September 2023

Esophageal atresia (EA) is the most common malformation of the upper gastrointestinal tract. The estimated incidence of EA is 1 in 3500 births. EA is more frequently observed in boys and in twins. The exact cause of isolated EA remains unknown; a multifactorial etiology, including epigenetic gene expression modifications, is considered. The study included six pairs of twins (three pairs of monozygotic twins and three pairs of dizygotic twins) in which one child was born with EA as an isolated defect, while the other twin was healthy. DNA samples were obtained from the blood and esophageal tissue of the child with EA as well as from the blood of the healthy twin. The reduced representation bisulfite sequencing (RRBS) technique was employed for a whole-genome methylation analysis. The analyses focused on comparing the CpG island methylation profiles between patients with EA and their healthy siblings. Hypermethylation in the promoters of 219 genes and hypomethylation in the promoters of 78 genes were observed. A pathway enrichment analysis revealed the statistically significant differences in methylation profile of 10 hypermethylated genes in the Rho GTPase pathway, previously undescribed in the field of EA (ARHGAP36, ARHGAP4, ARHGAP6, ARHGEF6, ARHGEF9, FGD1, GDI1, MCF2, OCRL, and STARD8).
Evaluating the Financial Performances of the Publicly Held Healthcare Companies in Crisis Periods in Türkiye
Authors: Tengilimoğlu Dilaver , Tümer Tolga , Bennett Russell L. , Younis Mustafa Z.
Published: September 2023

The purpose of this study was to evaluate the financial performances of the publicly held healthcare companies in crisis periods in Türkiye. The 2018 economic crisis and the COVID-19 pandemic crisis were included in the study as the crisis periods. We collected the financial data of the publicly held healthcare companies and calculated three liquidity, three turnover, three leverage and three profitability ratios through ratio analysis to use as financial performance indicators. We then conducted Wilcoxon signed-rank tests and we performed separate analyses for the 2018 economic crisis and the COVID-19 pandemic crisis. The results of the analyses showed that there were no statistically significant differences between the publicly held healthcare companies’ liquidity, turnover, leverage, profitability ratios and thus their financial performances before the crises and after the crises. While the results are reassuring and give valuable insights to managers and policy makers to determine the areas that needs to be strengthened to be better prepared for possible future crises, our sample was limited. Therefore, this study presents an exploratory foundation for future studies which are needed to make a case for financial stability for the publicly held healthcare companies before and after the crisis periods.
Enhancing Spiritual Well-Being, Physical Activity, and Happiness in Hospitalized Older Adult Patients with Swallowing Difficulties: A Comparative Study of Thickeners and Swallowing Exercises
Authors: Kao Yu-Yin , Lai Yun-Ru , Huang Chiung-Yu , Tsai Meng-Yun , Kuo Ming-Chun , Chen Hsin-Wei , Lee Suey-Haur , Lee Chen-Hsiang
Published: September 2023

Swallowing difficulties often occur in older adult patients during acute hospitalization, leading to reduced nutritional intake, increased frailty, and various psychosocial challenges. This randomized controlled study aimed to assess the effects of two interventions, thickeners and swallowing exercises, on the spiritual well-being, physical activity, and happiness of older adult patients with swallowing difficulties during acute hospitalization from October 2019 to August 2020. Sample size calculation was performed using a conservative estimate approach, resulting in an estimate-required sample size of 42 participants. The sampling method was a random cluster sampling approach, with three ward rooms assigned to the thickeners group, swallowing exercises group and control group, respectively. Seventy-two participants were assigned to the intervention groups (thickeners or swallowing exercises) or the control group using a 1:1:1 stratified random assignment. Data were collected before and after the intervention, and matched samples were analyzed using t-tests, ANOVA, and generalized estimating equations for statistical analysis. Both intervention groups showed significant improvements in spiritual well-being (p < 0.001), physical activity (p < 0.001), and happiness (p < 0.001) compared to the control group. However, there were no significant differences between the intervention groups. Our findings suggest that interventions involving thickeners and swallowing exercises have positive effects on the spiritual well-being, physical activity, and happiness of older adult patients with swallowing difficulties during acute hospitalization and emphasize the importance of implementing these interventions to enhance the overall well-being and quality of life of this vulnerable patient population.
Comprehensive Genomic Analysis and Expression Profile of Hsp70 Gene Family Related to Abiotic and Biotic Stress in Cucumber
Authors: Zhou Zixian , Xiao Lingdi , Zhao Jindong , Hu Zhaoyang , Zhou Yuelong , Liu Shiqiang , Wu Hao , Zhou Yong
Published: September 2023

Heat shock protein 70 (Hsp70) is a class of HSPs involved in plant growth and development, stress response and regulation. The Hsp70 proteins exist widely in the plant world, but the detail information about Hsp70s is still unclear in cucumber. Based on the available cucumber genome, a total of 12 Hsp70 genes (CsHsp70-1 to CsHsp70-12) were identified in this study, and they were distributed among five out of seven chromosomes. The CsHsp70s were divided into four groups based on a phylogenetic analysis by using protein sequences from cucumber and other plants, and their conserved motifs were relatively conserved. Gene duplication analysis showed that segmental duplication is the main driving force of expansion in cucumber CsHsp70 genes. Promoter analysis of CsHsp70 genes showed that they contained many cis-acting elements involved in hormone and stress responses. Expression analysis by RNA-seq and qRT-PCR indicated that the expression of most CsHsp70 genes was associated with multiple biotic and abiotic stresses in cucumber. This study introduces the characteristics of cucumber CsHsp70 genes and the regulation of their expression levels in various abiotic and biotic stresses, which provided a basis for functional exploration and utilization of CsHsp70 genes in the future.
The Effect of Mindset and Breathing Exercises on Physical and Mental Health in Persons with Spinal Cord Injury—A Pilot Feasibility Study
Authors: de Groot Sonja , Ettema Frank W. L. , van Leeuwen Christel M. C. , Achterberg Wendy J. , Janssen Thomas W. J. , Hoekstra Sven P.
Published: September 2023

This study investigated the feasibility and efficacy of mindset and breathing exercises (Wim Hof Method (WHM)) on physical and mental health in persons with spinal cord injury (SCI). Ten individuals with SCI participated in this pilot study. These ten participants followed a 4-week WHM intervention, with one weekly group session in the rehabilitation center and daily practice at home using the WHM app. An in-person exit-interview was conducted post-intervention to collect qualitative information on participants’ experiences, regarding the feasibility and effects of the intervention. Furthermore, tests and questionnaires were administered pre- and post-intervention to assess physical and mental health outcomes. Adherence to the weekly in-person meetings was excellent and no adverse events occurred. Physical and mental health outcomes in this small sample size showed some pre–post differences. This pilot feasibility study provides preliminary evidence supporting the feasibility and efficacy of the WHM, including mindset and breathing exercises, on physical and mental health of people with SCI. These results warrant a randomized-controlled trial, including cold exposure, of this novel intervention in people with SCI.
Callous and Unemotional Traits as Precursors to the Development of Female Psychopathy
Authors: Cardoso Ana Raquel , Costa Maria João , Sani Ana Isabel , Moreira Diana
Published: September 2023

Objective: Conduct a systematic review concerning the literature that reflects whether the callous and unemotional traits present in childhood and/or adolescence are precursors in the development of female psychopathy in adulthood. Materials and Methods: A systematic review involved consulting three databases—EBSCO, the Web of Science, and PubMed—for peer-reviewed and quantitative studies within the period 2000–2023. Nine articles with quality of three and above were included. Results: The presence of callous and unemotional traits designates a group of youth that show characteristics associated with psychopathy, specifically when predicting a more severe and chronic pattern of antisocial behaviour. Children with high rates of callous and unemotional traits, who show symptoms of attention deficit hyperactivity disorder in combination with severe conduct problems, are most likely to show features associated with psychopathy. The multidimensional psychopathy construct is considered a better predictor of future and stable antisocial behaviour than the callous and unemotional traits alone model. Conclusions: According to the studies selected, the callous and unemotional traits in childhood seem to be precursors of female psychopathy in adulthood, but only because of the way they seem to enhance conduct problems, disruptive behaviour disorders, and, as a possible outcome, delinquency and antisocial traits, which may be precursors of future psychopathy.