bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing a Multivariate Agro‐Meteorological Index to Improve Capturing Onset and Persistence of Droughts Utilizing Vapor Pressure Deficit and Soil Moisture
Authors: Zeraati Masoud , Farahmand Alireza , Asghari Keyvan , Behrangi Ali
Published: June 2024

Drought is associated with adverse environmental and societal impacts across various regions. Therefore, drought monitoring based on a single variable may lead to unreliable information, especially about the onset and persistence of drought. Previous studies show vapor pressure deficit (VPD) data can detect drought onset earlier than other drought indicators such as precipitation. On the other hand, soil moisture (SM) is a robust indicator for assessing drought persistence. This study introduces a nonparametric multivariate drought index Vapor Pressure Deficit Soil moisture standardized Drought Index (VPDSDI) which is developed by combining VPD with SM information. The performance of the multivariate index in terms of drought onset detection is compared with the Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) for six major drought events across the United States including three rapidly developing drought events (this term refers to flash droughts that develop on monthly scales) and three conventional drought events. Additionally, the performance of the proposed index in detecting drought persistence is compared with the Standardized Soil moisture Index (SSI), which is an agricultural drought index. Results indicate the multivariate index detects drought onset always earlier than SPI for conventional events, but VPDSDI detects drought onset earlier than or about the same time as SPEI for rapidly developing droughts. In terms of persistence, VPDSDI detects persistence almost identical to SSI for both rapidly developing and conventional drought events. The results also show that combining VPD with SM reduces the high variability of VPD and produces a smoother index which improves the onset and persistence detection of drought events leveraging VPD and SM information.
AttUnet_R_SFT: A Novel Network to Explore the Application of Complex Terrain Information in Satellite Precipitation Estimating
Authors: Zhang Lu , Zhou Zeming , Guan Jiping , Gao Yanbo , Zhang Lifeng , Kader Movlan
Published: June 2024

Accurate rainfall measurement with a precise spatial and temporal resolution is essential for making informed decisions during disasters and conducting scientific studies, particularly in regions characterized by intricate terrain and limited coverage of automated weather stations. Retrieval of precipitation with satellite is currently the most effective means to obtain precipitation over large‐scale areas. The key to enhancing the accuracy of precipitation estimation and forecasting in regions with complex terrain lies in effectively integrating satellite data with topographic information. This paper introduces a deep learning approach called AttUnet_R_SFT that utilizes high temporal, spatial, and spectral resolution data obtained from the Fengyun 4A satellite, and incorporates the Deep Spatial Feature Transform (SFT) layer to incorporate geographical data for estimating half‐hourly precipitation in northeastern China. We assess it by compared to operational near‐real‐time satellite precipitation products demonstrated to be successful in estimating precipitation and baseline deep learning models. According to the experimental findings, the AttUnet_R_SFT model outperforms practical precipitation products and baseline deep learning models in both identifying and estimating precipitation. The main enhancement of the model performance is shown in the windward slope of the Greater Khingan Mountains as a result of the successful incorporation of geographical data. Hence, the suggested framework holds the capability to function as a superior and dependable satellite‐derived precipitation estimation solution in regions characterized by intricate terrain and infrequent rainfall. The findings of this study indicate that the utilization of deep learning algorithms for satellite precipitation estimation shows potential as a fruitful avenue for further research.
Leveraging Machine Learning Approaches to Predict Organic Carbon Abundance in Mars‐Analog Hypersaline Lake Sediments
Authors: Nichols Floyd , Pontefract Alexandra , Masterson Andrew L. , Thompson Mia L. , Carr Christopher E. , Tuccillo Mia T. , Osburn Magdalena R.
Published: June 2024

Modern advancements in laboratory and instrumental techniques in astrobiology have improved our life detection capabilities on both Earth and beyond. These advancements have also increased the complexity of data often resulting in data sets that are characterized by complex and non‐linear relationships. Machine learning methods are underutilized in astrobiology; however, these methods are extremely effective at revealing structure and patterns in complex data sets when paired with the right algorithms. Here, we employ a series of classification and regression algorithms to predict the abundance of organic carbon (OC) from X‐ray fluorescence (XRF) heavy element (>Mg) data in dynamic Mars‐analog hypersaline lake sediments. More specifically, we constructed models using the random forest, k‐nearest neighbors (KNN), support vector machine, and logistic regression algorithms. Overall, our trained models showed good performance with predicting the abundance of OC, with accuracies from 80% to 94%. Machine learning approaches such as classification and regression algorithms offer insight into complex data while providing agnostic insights, ultimately creating a more efficient search for OC. We applied our trained model on XRF data from Martian soil using rover‐based (PIXL) and orbital (Odyssey) data sets to produce probability predictions of OC abundance. Our predictions show a high probability that OC abundance is low which is comparable to OC data from recently landed missions. These results highlight the potential for predictive machine learning models to be trained on data from analog environments on Earth and then applied to extraterrestrial targets, ultimately, improving life detection efforts.
MEMS reservoir computing system with stiffness modulation for multi-scene data processing at the edge
Authors: Guo Xiaowei , Yang Wuhao , Xiong Xingyin , Wang Zheng , Zou Xudong
Published: June 2024

Reservoir computing (RC) is a bio-inspired neural network structure which can be implemented in hardware with ease. It has been applied across various fields such as memristors, and electrochemical reactions, among which the micro-electro-mechanical systems (MEMS) is supposed to be the closest to sensing and computing integration. While previous MEMS RCs have demonstrated their potential as reservoirs, the amplitude modulation mode was found to be inadequate for computing directly upon sensing. To achieve this objective, this paper introduces a novel MEMS reservoir computing system based on stiffness modulation, where natural signals directly influence the system stiffness as input. Under this innovative concept, information can be processed locally without the need for advanced data collection and pre-processing. We present an integrated RC system characterized by small volume and low power consumption, eliminating complicated setups in traditional MEMS RC for data discretization and transduction. Both simulation and experiment were conducted on our accelerometer. We performed nonlinearity tuning for the resonator and optimized the post-processing algorithm by introducing a digital mask operator. Consequently, our MEMS RC is capable of both classification and forecasting, surpassing the capabilities of our previous non-delay-based architecture. Our method successfully processed word classification, with a 99.8% accuracy, and chaos forecasting, with a 0.0305 normalized mean square error (NMSE), demonstrating its adaptability for multi-scene data processing. This work is essential as it presents a novel MEMS RC with stiffness modulation, offering a simplified, efficient approach to integrate sensing and computing. Our approach has initiated edge computing, enabling emergent applications in MEMS for local computations.
An acoustofluidic device for the automated separation of platelet-reduced plasma from whole blood
Authors: Ma Zhehan , Xia Jianping , Upreti Neil , David Emeraghi , Rufo Joseph , Gu Yuyang , Yang Kaichun , Yang Shujie , Xu Xiangchen , Kwun Jean , Chambers Eileen , Huang Tony Jun
Published: June 2024

Separating plasma from whole blood is an important sample processing technique required for fundamental biomedical research, medical diagnostics, and therapeutic applications. Traditional protocols for plasma isolation require multiple centrifugation steps or multiunit microfluidic processing to sequentially remove large red blood cells (RBCs) and white blood cells (WBCs), followed by the removal of small platelets. Here, we present an acoustofluidic platform capable of efficiently removing RBCs, WBCs, and platelets from whole blood in a single step. By leveraging differences in the acoustic impedances of fluids, our device generates significantly greater forces on suspended particles than conventional microfluidic approaches, enabling the removal of both large blood cells and smaller platelets in a single unit. As a result, undiluted human whole blood can be processed by our device to remove both blood cells and platelets (>90%) at low voltages (25 Vpp). The ability to successfully remove blood cells and platelets from plasma without altering the properties of the proteins and antibodies present creates numerous potential applications for our platform in biomedical research, as well as plasma-based diagnostics and therapeutics. Furthermore, the microfluidic nature of our device offers advantages such as portability, cost efficiency, and the ability to process small-volume samples.
Monolithic integrated optoelectronic chip for vector force detection
Authors: Feng Jiansong , Wang Zhongqi , Zhanghu Mengyuan , Zhang Xu , Shen Yong , Yang Jing , Li Zhibin , Chen Bin , Wang Taihong , Chen Xiaolong , Liu Zhaojun
Published: June 2024

Sensors with a small footprint and real-time detection capabilities are crucial in robotic surgery and smart wearable equipment. Reducing device footprint while maintaining its high performance is a major challenge and a significant limitation to their development. Here, we proposed a monolithic integrated micro-scale sensor, which can be used for vector force detection. This sensor combines an optical source, four photodetectors, and a hemispherical silicone elastomer component on the same sapphire-based AlGaInP wafer. The chip-scale optical coupling is achieved by employing the laser lift-off techniques and the flip-chip bonding to a processed sapphire substrate. This hemispherical structure device can detect normal and shear forces as low as 1 mN within a measurement range of 0–220 mN for normal force and 0–15 mN for shear force. After packaging, the sensor is capable of detecting forces over a broader range, with measurement capabilities extending up to 10 N for normal forces and 0.2 N for shear forces. It has an accuracy of detecting a minimum normal force of 25 mN and a minimum shear force of 20 mN. Furthermore, this sensor has been validated to have a compact footprint of approximately 1.5 mm2, while maintaining high real-time response. We also demonstrate its promising potential by combining this sensor with fine surface texture perception in the fields of compact medical robot interaction and wearable devices.
Prevalence of obesity and associated sociodemographic and lifestyle factors in Ecuadorian children and adolescents
Authors: López-Gil José Francisco , Chen Sitong , López-Bueno Rubén , Gutiérrez-Espinoza Hector , Duarte Junior Miguel Angelo , Galan-Lopez Pablo , Palma-Gamiz José Luis , Smith Lee
Published: June 2024

Background

Given the increasing prevalence of obesity in young people in Ecuador, there is a need to understand the factors associated with this condition. The aim of this study was to assess the prevalence of obesity in Ecuadorian children and adolescents aged 5–17 years and identify its associated sociodemographic and lifestyle factors.

Methods

This cross-sectional study was conducted using data from the Encuesta Nacional de Salud y Nutrición (ENSANUT-2018). The final sample consisted of 11,980 participants who provided full information on the variables of interest.

Results

The prevalence of obesity was 12.7%. A lower odd of having obesity was observed for adolescents; for those with a breadwinner with an educational level in middle/high school or higher; for each additional day with 60 or more minutes of daily moderate-to-vigorous physical activity; and for those with greater daily vegetable consumption (one, two, or three or more servings). Conversely, there were greater odds of obesity in participants from families with medium, poor, and very poor wealth and those from the coast and insular region.

Conclusions

The high prevalence of obesity in Ecuadorian children and adolescents is a public health concern. Sociodemographic and lifestyle behavior differences in young people with obesity should be considered when developing specific interventions.

Impact

As the prevalence of obesity among children and adolescents increases in Latin America, with a particular focus on Ecuador, it becomes crucial to delve into the factors linked to this condition and identify the most successful strategies for its mitigation.

The elevated prevalence of obesity among young individuals in Ecuador raises significant public health concerns.

To develop targeted interventions, it is crucial to account for sociodemographic variables and lifestyle behaviors that contribute to obesity in this population.
SMAD4 depletion contributes to endocrine resistance by integrating ER and ERBB signaling in HR + HER2− breast cancer
Authors: Li Kang , Shu Dan , Li Han , Lan Ailin , Zhang Wenjie , Tan Zhaofu , Huang Man , Tomasi Maria Lauda , Jin Aishun , Yu Haochen , Shen Meiying , Liu Shengchun
Published: June 2024

Endocrine resistance poses a significant clinical challenge for patients with hormone receptor-positive and human epithelial growth factor receptor 2-negative (HR + HER2−) breast cancer. Dysregulation of estrogen receptor (ER) and ERBB signaling pathways is implicated in resistance development; however, the integration of these pathways remains unclear. While SMAD4 is known to play diverse roles in tumorigenesis, its involvement in endocrine resistance is poorly understood. Here, we investigate the role of SMAD4 in acquired endocrine resistance in HR + HER2− breast cancer. Genome-wide CRISPR screening identifies SMAD4 as a regulator of 4-hydroxytamoxifen (OHT) sensitivity in T47D cells. Clinical data analysis reveals downregulated SMAD4 expression in breast cancer tissues, correlating with poor prognosis. Following endocrine therapy, SMAD4 expression is further suppressed. Functional studies demonstrate that SMAD4 depletion induces endocrine resistance in vitro and in vivo by enhancing ER and ERBB signaling. Concomitant inhibition of ER and ERBB signaling leads to aberrant autophagy activation. Simultaneous inhibition of ER, ERBB, and autophagy pathways synergistically impacts SMAD4-depleted cells. Our findings unveil a mechanism whereby endocrine therapy-induced SMAD4 downregulation drives acquired resistance by integrating ER and ERBB signaling and suggest a rational treatment strategy for endocrine-resistant HR + HER2− breast cancer patients.
Associations of combined genetic and lifestyle risks with hypertension and home hypertension
Authors: Takase Masato , Hirata Takumi , Nakaya Naoki , Nakamura Tomohiro , Kogure Mana , Hatanaka Rieko , Nakaya Kumi , Chiba Ippei , Kanno Ikumi , Nochioka Kotaro , Tsuchiya Naho , Narita Akira , Metoki Hirohito , Satoh Michihiro , Obara Taku , Ishikuro Mami , Ohseto Hisashi , Uruno Akira , Kobayashi Tomoko , Kodama Eiichi N. , Hamanaka Yohei , Orui Masatsugu , Ogishima Soichi , Nagaie Satoshi , Fuse Nobuo , Sugawara Junichi , Kuriyama Shinichi , Tamiya Gen , Hozawa Atsushi , Yamamoto Masayuki ,   the ToMMo investigators
Published: June 2024

No study, to our knowledge, has constructed a polygenic risk score based on clinical blood pressure and investigated the association of genetic and lifestyle risks with home hypertension. We examined the associations of combined genetic and lifestyle risks with hypertension and home hypertension. In a cross-sectional study of 7027 Japanese individuals aged ≥20 years, we developed a lifestyle score based on body mass index, alcohol consumption, physical activity, and sodium-to-potassium ratio, categorized into ideal, intermediate, and poor lifestyles. A polygenic risk score was constructed with the target data (n = 1405) using publicly available genome-wide association study summary statistics from BioBank Japan. Using the test data (n = 5622), we evaluated polygenic risk score performance and examined the associations of combined genetic and lifestyle risks with hypertension and home hypertension. Hypertension and home hypertension were defined as blood pressure measured at a community-support center ≥140/90 mmHg or at home ≥135/85 mmHg, respectively, or self-reported treatment for hypertension. In the test data, 2294 and 2322 participants had hypertension and home hypertension, respectively. Both polygenic risk and lifestyle scores were independently associated with hypertension and home hypertension. Compared with those of participants with low genetic risk and an ideal lifestyle, the odds ratios for hypertension and home hypertension in the low genetic risk and poor lifestyle group were 1.94 (95% confidence interval, 1.34–2.80) and 2.15 (1.60–2.90), respectively. In summary, lifestyle is important to prevent hypertension; nevertheless, participants with high genetic risk should carefully monitor their blood pressure despite a healthy lifestyle.
Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease
Authors: Kilian Christoph , Ulrich Hanna , Zouboulis Viktor A. , Sprezyna Paulina , Schreiber Jasmin , Landsberger Tomer , Büttner Maren , Biton Moshe , Villablanca Eduardo J. , Huber Samuel , Adlung Lorenz
Published: June 2024

Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.
Extended-release ketamine tablets for treatment-resistant depression: a randomized placebo-controlled phase 2 trial
Authors: Glue Paul , Loo Colleen , Fam Johnson , Lane Hsien-Yuan , Young Allan H. , Surman Peter ,   BEDROC study investigators, Glozier Nick , Fitzgerald Paul , Liu Dennis , Sharma Shanthi , Grunfeld Jennifer , Barton David , Hopwood Malcolm , Miles Wayne , Williams Mike , Carson Simon , Fam Johnson , Tor Phern-Chern , Lane Hsien-Yuan , Chen Chun-Hsin , Huang Yu-Jui
Published: June 2024

Ketamine has rapid-onset antidepressant activity in patients with treatment-resistant major depression (TRD). The safety and tolerability of racemic ketamine may be improved if given orally, as an extended-release tablet (R-107), compared with other routes of administration. In this phase 2 multicenter clinical trial, male and female adult patients with TRD and Montgomery–Asberg Depression Rating Scale (MADRS) scores ≥20 received open-label R-107 tablets 120 mg per day for 5 days and were assessed on day 8 (enrichment phase). On day 8, responders (MADRS scores ≤12 and reduction ≥50%) were randomized on a 1:1:1:1:1 basis to receive double-blind R-107 doses of 30, 60, 120 or 180 mg, or placebo, twice weekly for a further 12 weeks. Nonresponders on day 8 exited the study. The primary endpoint was least square mean change in MADRS for each active treatment compared with placebo at 13 weeks, starting with the 180 mg dose, using a fixed sequence step-down closed test procedure. Between May 2019 and August 2021, 329 individuals were screened for eligibility, 231 entered the open-label enrichment phase (days 1–8) and 168 responders were randomized to double-blind treatment. The primary objective was met; the least square mean difference of MADRS score for the 180 mg tablet group and placebo was −6.1 (95% confidence interval 1.0 to 11.16, P = 0.019) at 13 weeks. Relapse rates during double-blind treatment showed a dose response from 70.6% for placebo to 42.9% for 180 mg. Tolerability was excellent, with no changes in blood pressure, minimal reports of sedation and minimal dissociation. The most common adverse events were headache, dizziness and anxiety. During the randomized phase of the study, most patient dosing occurred at home. R-107 tablets were effective, safe and well tolerated in a patient population with TRD, enriched for initial response to R-107 tablets. ClinicalTrials.gov registration: ACTRN12618001042235.
Prediction of hepatic metastasis in esophageal cancer based on machine learning
Authors: Wan Jun , Zeng Yukai
Published: June 2024

This study aimed to establish a machine learning (ML) model for predicting hepatic metastasis in esophageal cancer. We retrospectively analyzed patients with esophageal cancer recorded in the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2020. We identified 11 indicators associated with the risk of liver metastasis through univariate and multivariate logistic regression. Subsequently, these indicators were incorporated into six ML classifiers to build corresponding predictive models. The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. A total of 17,800 patients diagnosed with esophageal cancer were included in this study. Age, primary site, histology, tumor grade, T stage, N stage, surgical intervention, radiotherapy, chemotherapy, bone metastasis, and lung metastasis were independent risk factors for hepatic metastasis in esophageal cancer patients. Among the six models developed, the ML model constructed using the GBM algorithm exhibited the highest performance during internal validation of the dataset, with AUC, accuracy, sensitivity, and specificity of 0.885, 0.868, 0.667, and 0.888, respectively. Based on the GBM algorithm, we developed an accessible web-based prediction tool (accessible at https://project2-dngisws9d7xkygjcvnue8u.streamlit.app/) for predicting the risk of hepatic metastasis in esophageal cancer.
Correlation between normally aerated lung and respiratory system compliance at clinical high positive end-expiratory pressure in patients with COVID-19
Authors: Ogura Keishi , Nakayama Ryuichi , Bunya Naofumi , Katayama Shinshu , Yama Naoya , Goto Yuya , Sawamoto Keigo , Uemura Shuji , Narimatsu Eichi
Published: June 2024

Normally aerated lung tissue on computed tomography (CT) is correlated with static respiratory system compliance (Crs) at zero end-expiratory pressure. In clinical practice, however, patients with acute respiratory failure are often managed using elevated PEEP levels. No study has validated the relationship between lung volume and tissue and Crs at the applied positive end-expiratory pressure (PEEP). Therefore, this study aimed to demonstrate the relationship between lung volume and tissue on CT and Crs during the application of PEEP for the clinical management of patients with acute respiratory distress syndrome due to COVID-19. Additionally, as a secondary outcome, the study aimed to evaluate the relationship between CT characteristics and Crs, considering recruitability using the recruitment-to-inflation ratio (R/I ratio). We analyzed the CT and respiratory mechanics data of 30 patients with COVID-19 who were mechanically ventilated. The CT images were acquired during mechanical ventilation at PEEP level of 15 cmH2O and were quantitatively analyzed using Synapse Vincent system version 6.4 (Fujifilm Corporation, Tokyo, Japan). Recruitability was stratified into two groups, high and low recruitability, based on the median R/I ratio of our study population. Thirty patients were included in the analysis with the median R/I ratio of 0.71. A significant correlation was observed between Crs at the applied PEEP (median 15 [interquartile range (IQR) 12.2, 15.8]) and the normally aerated lung volume (r = 0.70 [95% CI 0.46–0.85], P < 0.001) and tissue (r = 0.70 [95% CI 0.46–0.85], P < 0.001). Multivariable linear regression revealed that recruitability (Coefficient = − 390.9 [95% CI − 725.0 to − 56.8], P = 0.024) and Crs (Coefficient = 48.9 [95% CI 32.6–65.2], P < 0.001) were significantly associated with normally aerated lung volume (R-squared: 0.58). In this study, Crs at the applied PEEP was significantly correlated with normally aerated lung volume and tissue on CT. Moreover, recruitability indicated by the R/I ratio and Crs were significantly associated with the normally aerated lung volume. This research underscores the significance of Crs at the applied PEEP as a bedside-measurable parameter and sheds new light on the link between recruitability and normally aerated lung.
Preliminary clinical and radiological evaluation of osteosynthesis using the Femoral Neck System (FNS) for subcapital fractures of the femur
Authors: Hernández-Naranjo Jose Manuel , Campuzano-Bitterling Borja , Renau-Cerrillo Marina , Vives-Barquiel Marian , Camacho-Carrasco María Pilar , Muñoz-Mahamud Ernesto
Published: June 2024

Addressing subcapital fractures of the femur poses a substantial clinical challenge, complicated by the diverse range of available osteosynthesis materials. This study is dedicated to a comprehensive analysis of the clinical and radiological implications linked with the implementation of the Femoral Neck System (FNS) in osteosynthesis procedures. A descriptive study was conducted involving patients who underwent osteosynthesis for subcapital fractures of the femur utilizing the FNS during the period from 2019 to 2022. The investigation encompassed various facets, including the classification of fractures according to the Garden and Pauwells classifications, criteria for achieving precise reduction based on the Garden criteria and Tip Apex Distance (TAD). At the one-year follow-up, factors such as fracture consolidation, loss of reduction, fracture collapse, complications, and functional outcomes were evaluated utilizing the Harris Hip Score (HHS) scale. The study cohort included a total of 26 patients, among whom 22 exhibited non-displaced subcapital femur fractures categorized as Garden I and II. Successful reduction was accomplished in 23 cases, in which 24 cases (92.3%) displayed a TAD measurement below 25 mm. According to the HHS, patients achieved an average score of 90.9 (ranging from 63 to 100) following the surgical intervention, with predominantly "excellent" and "good" outcomes. The outcomes derived from our investigation corroborate the viability of the Femoral Neck System (FNS) as a reliable option for osteosynthesis in femoral neck fractures. The results obtained are comparable to those achieved with other available implants, as highlighted by previous studies.
Antioxidant capacity and peptidomic analysis of in vitro digested Camelina sativa L. Crantz and Cynara cardunculus co-products
Authors: Lanzoni Davide , Grassi Scalvini Francesca , Petrosillo Elena , Nonnis Simona , Tedeschi Gabriella , Savoini Giovanni , Buccioni Arianna , Invernizzi Guido , Baldi Antonella , Giromini Carlotta
Published: June 2024

In recent decades, the food system has been faced with the significant problem of increasing food waste. Therefore, the feed industry, supported by scientific research, is attempting to valorise the use of discarded biomass as co-products for the livestock sector, in line with EU objectives. In parallel, the search for functional products that can ensure animal health and performances is a common fundamental goal for both animal husbandry and feeding. In this context, camelina cake (CAMC), cardoon cake (CC) and cardoon meal (CM), due valuable nutritional profile, represent prospective alternatives. Therefore, the aim of this work was to investigate the antioxidant activity of CAMC, CC and CM following in vitro digestion using 2,2′-azinobis-(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), Ferric reducing antioxidant power (FRAP) and oxygen radical absorbance capacity (ORAC) assays. Total phenolic content (TPC) and angiotensin converting enzyme (ACE) inhibitory activity, actively involved in modulating antioxidant properties, were also studied. Further, a peptidomic analysis was adopted to substantiate the presence of bioactive peptides after in vitro digestion. The results obtained confirmed an interesting nutritional profile of CAMC, CC and CM and relevant antioxidant and ACE inhibitory activities. In particular, considering antioxidant profile, CM and CC revealed a significantly higher (10969.80 ± 18.93 mg TE/100 g and 10451.40 ± 149.17 mg TE/100 g, respectively; p < 0.05) ABTS value than CAMC (9511.18 ± 315.29 mg TE/100 g); a trend also confirmed with the FRAP assay (306.74 ± 5.68 mg FeSO4/100 g; 272.84 ± 11.02 mg FeSO4/100 g; 103.84 ± 3.27 mg FeSO4/100 g, for CC, CM and CAMC, respectively). Similar results were obtained for TPC, demonstrating the involvement of phenols in modulating antioxidant activity. Finally, CAMC was found to have a higher ACE inhibitory activity (40.34 ± 10.11%) than the other matrices. Furthermore, potentially bioactive peptides associated with ACE inhibitory, anti-hypertensive, anti-cancer, antimicrobial, antiviral, antithrombotic, DPP-IV inhibitory and PEP-inhibitory activities were identified in CAMC. This profile was broader than that of CC and CM. The presence of such peptides corroborates the antioxidant and ACE profile of the sample. Although the data obtained report the important antioxidant profile of CAMC, CC, and CM and support their possible use, future investigations, particularly in vivo trials will be critical to evaluate and further investigate their effects on the health and performance of farm animals.
Comparison of tibial fracture plate length, placement, and fibular integrity effects on plate integrity through finite element analysis
Authors: Lee Byung Hoon , Kang Yeokyung , Cho Sung Ha , Moon Myung , Sim Jae Ang , Kim Jungsung
Published: June 2024

Minimally invasive plate osteosynthesis is the most commonly used minimally invasive surgery technique for tibial fractures, possibly involving single or dual plate methods. Herein, we performed a finite element analysis to investigate plate strength according to the plate type, length, and presence of a fibula by constructing a three-dimensional tibia model. A thickness of 20 mm was cut 50 mm distal from the lateral plateau, and the ligaments were created. Plates were modeled with lengths of 150, 200, and 250 mm and mounted to the tibia. Screws were arranged to avoid overlapping in the dual plating. The von-Mises stress applied to the plates was measured by applying a load of 1 body weight. Dual plates showed the least stress with low displacement, followed by medial and lateral plates. As the plate length increased, the average stress gradually decreased, increasing plate safety. The difference in the influence of the fibula depending on the presence of proximal fibula osteotomy showed that the average stress increased by 35% following proximal fibula osteotomy in the D1(Plate type: Dual plate, Medial plate length: 150 mm, Lateral plate length: 200 mm, Non Proximal fibula osteotomy) and D1P(Plate type: Dual plate, Medial plate length: 150 mm, Lateral plate length: 200 mm, Proximal fibula osteotomy) models, confirming the necessity of the fibula model. There is no consensus guideline for treatment of this kind of fracture case. A single fracture plate can decrease the risk of skin damage, ligament damage, and wound infection, but because of its design, it cannot provide sufficient stability and satisfactory reduction of the condylar fragment, especially in cases of comminution or coronal fracture. So, these results will help clinicians make an informed choice on which plate to use in patients with tibial fractures.
Synthesis and characterization of aluminosilicate and zinc silicate from sugarcane bagasse fly ash for adsorption of aflatoxin B1
Authors: Niamnuy Chalida , Sungsinchai Sirada , Jarernsamrit Prapaporn , Devahastin Sakamon , Chareonpanich Metta
Published: June 2024

Sugarcane bagasse fly ash, a residual product resulting from the incineration of biomass to generate power and steam, is rich in SiO2. Sodium silicate is a fundamental material for synthesizing highly porous silica-based adsorbents to serve circular practices. Aflatoxin B1 (AFB1), a significant contaminant in animal feeds, necessitates the integration of adsorbents, crucial for reducing aflatoxin concentrations during the digestive process of animals. This research aimed to synthesize aluminosilicate and zinc silicate derived from sodium silicate based on sugarcane bagasse fly ash, each characterized by a varied molar ratio of aluminum (Al) to silicon (Si) and zinc (Zn) to silicon (Si), respectively. The primary focus of this study was to evaluate their respective capacities for adsorbing AFB1. It was revealed that aluminosilicate exhibited notably superior AFB1 adsorption capabilities compared to zinc silicate and silica. Furthermore, the adsorption efficacy increased with higher molar ratios of Al:Si for aluminosilicate and Zn:Si for zinc silicate. The N2 confirmed AFB1 adsorption within the pores of the adsorbent. In particular, the aluminosilicate variant with a molar ratio of 0.08 (Al:Si) showcased the most substantial AFB1 adsorption capacity, registering at 88.25% after an in vitro intestinal phase. The adsorption ability is directly correlated with the presence of surface acidic sites and negatively charged surfaces. Notably, the kinetics of the adsorption process were best elucidated through the application of the pseudo-second-order model, effectively describing the behavior of both aluminosilicate and zinc silicate in adsorbing AFB1.
Implementation and proficiency analysis of enhanced graph algorithm for DC microgrid applications
Authors: J Mohamed Abdullah , V Sumathi
Published: June 2024

Integrating renewable energy generation with the conventional grid supports reduces carbon emissions in the atmosphere. Despite technical advancements in protection strategies, critical issues concerning renewable integration in microgrid structures require standardized solutions. The essential aspects that need to be concentrated during securing the grids are rapid fault interruption, false tripping and blinding of protection. This study proposes an innovative approach to enhance fault isolation speed through the implementation of a grid monitoring system (GMS) coupled with a fault identification method based on Kosaraju’s algorithm. This algorithm operates on the principles of overvoltage and overcurrent detection. The study assesses the efficacy of this approach by examining its integration with a Z-source circuit breaker and conducting tests on different fault types within a 13-bus system. Real-time simulations using Opal RT software are employed to experimentally validate the proposed methodology, ensuring its efficacy in fault interruption and isolation.
A new fuzzy method for investigating the effects of dam on aquifer: case study of Rudbal dam, south of Iran
Authors: Moradi Nazarpoor Sajjad , Rezaei Mohsen , Mali Fateme
Published: June 2024

Dam construction has some qualitative and quantitative effects on groundwater resources. This effect may be in the form of an increasing groundwater table or a changing groundwater system. In this paper, the effect of the Rodbal dam construction on the Darab aquifer was investigated. For this paper water table levels from observation wells and precipitation data was used. The study aims to analyse the behaviour of the water table during precipitation by employing a combination of the standardisation process, Fuzzy Inference System (FIS), and Root Mean Square Error (RMSE) calculations. Fuzzy logic involves the fuzzification of input data, transforming precise values into fuzzy sets. The effectiveness of the FIS is highlighted, particularly in determining the number of membership functions for inputs. The performance of the results is assessed using indicators such as RMSE and Coefficient of Determination (R2). The FIS showed a high level of effectiveness in performance assessment, exhibiting a 70% similarity between the fuzzy and Mann–Kendall methods. Nonetheless, the Fuzzy Purpose Method corresponded more closely with the observed data, indicating a more accurate reflection of reality. The findings indicate that for P3, P7, and P8, the results from the Mann–Kendall method do not show a discernible trend. Conversely, the proposed Fuzzy method accounts for changes in the behaviour of these piezometers.
Novel bilayer 2D V2O5 as a potential catalyst for fast photodegradation of organic dyes
Authors: Reshma P. R. , Prasad Arun K. , Dhara Sandip
Published: June 2024

Two-dimensional (2D) materials have recently drawn interest in various applications due to their superior electronic properties, high specific surface area, and surface activity. However, studies on the catalytic properties of the 2D counterpart of V2O5 are scarce. In the present study, the catalytic properties of 2D V2O5 vis-à-vis bulk V2O5 for the degradation of methylene blue dye are discussed for the first time. The 2D V2O5 catalyst was synthesized using a modified chemical exfoliation technique. A massive increase in the electrochemically active surface area of 2D V2O5 by one order of magnitude greater than that of bulk V2O5 was observed in this study. Simultaneously, ~ 7 times increase in the optical absorption coefficient of 2D V2O5 significantly increases the number of photogenerated electrons involved in the catalytic performance. In addition, the surface activity of the 2D V2O5 catalyst is enhanced by generating surface oxygen vacancy defects. In the current study, we have achieved ~ 99% degradation of 16 ppm dye using the 2D V2O5 nanosheet catalysts under UV light exposure with a remarkable degradation rate constant of 2.31 min−1, which is an increase of the order of 102 from previous studies using V2O5 nanostructures and nanocomposites as catalysts. Since the enhanced photocatalytic activity emerged from the surface and optical properties of the catalyst, the current study shows great promise for the future application of 2D V2O5 in photo- and electrocatalysis.
IRSEI-based monitoring of ecological quality and analysis of drivers in the Daling River Basin
Authors: Ge Jintao , Qian Cheng , Zhang Chao , Zhang Li , Song Weimin , Na Fuchao , Ma Hongwei , Guo Changlai , Jiang Shan
Published: June 2024

The Daling River Basin is an important ecological functional area in the western region of Liaoning with outstanding environmental problems. The monitoring of ecological and environmental quality in the basin and the analysis of driving factors are of great importance for the protection of the ecological environment and the improvement of economic quality. In this paper, the three periods of Landsat remote sensing images in 1995, 2010 and 2020 are used as the basic data, and platforms and technical means such as RS and GIS are used to decipher and extract the three periods of land use information, and to construct the land use type transfer matrix. The remote sensing ecological index (RSEI) was improved, and the principal component analysis method was applied to construct the improved remote sensing ecological index (IRSEI) model based on the greenness (NDVI), moisture (WET), heat (LST) and new dryness (N-NDBSI), so as to realize the dynamic monitoring of ecological and environmental quality in the study area. Based on the land use change, combined with the trend of improved remote sensing ecological index (IRSEI) of Daling River Basin, thus achieving the purpose of rapid and efficient dynamic monitoring of ecological quality of Daling River Basin from 1995 to 2020. A geoprobe model was then used to systematically assess the drivers of ecological quality in the catchment. The results show that the improved remote sensing ecological index (IRSEI) can efficiently and accurately obtain the spatial distribution pattern and temporal variation trend of IRSEI in the study area, which is more in line with the characteristics of indicators in this study area. The IRSEI in the study area showed an increasing trend from 1995 to 2020, from 0.4794 to 0.5615, and the proportion of benign ecological classes increased year by year during the period. Among the evaluation indicators, NDVI and N-NDBSI are the main factors affecting the environmental and ecological quality of the Daling River Basin, and the increase of vegetation cover, climate regulation and human activities have obvious promoting effects on the improvement of the ecological environment of the Daling River Basin. This study provides a scientific theoretical basis for the implementation of further ecological environmental protection measures.
Thunderstorm total lightning activity behavior associated with transmission line trip events of power system
Authors: Li Muzi , Cheng Si , Wang Jianguo , Cai Li , Fan Yadong , Cao Jinxin , Zhou Mi
Published: June 2024

High-voltage transmission lines are susceptible targets for lightning strikes. It is an interesting topic how the trip event of transmission line is related to the area, location, and intensity of thunderstorms occurring at that time and that place. Based on total lightning observation containing intra-cloud and cloud-to-ground lightning, and transmission line trip information from relaying system of power system, 8 thunderstorms associated with the lightning strike trip of local transmission lines were selected in the Pearl River Delta (PRD) region. Analysis was conducted on the total lightning activity of each thunderstorm process, including the characteristics of total lightning counts and density, followed by the variations in total lightning activity before and after lightning strike trips. Further, our investigation encompassed the spatial and temporal evolution, charge structure, and kinematic parameters of thunderstorms. It was revealed that almost all lightning trips in this area emerged in close proximity to bodies of water, accompanied by a discernible reduction in thunderstorm cloud altitude during line trip occurrences. This paper aims to enhance the understanding of total lightning and thunderstorm activity behavior, thereby providing valuable insights for lightning disaster prevention and mitigation in the meteorological bureau and power system.
Probing chromatin condensation dynamics in live cells using interferometric scattering correlation spectroscopy
Authors: Hsiao Yi-Teng , Liao I-Hsin , Wu Bo-Kuan , Chu Hsueh-Ping Catherine , Hsieh Chia-Lung
Published: June 2024

Chromatin organization and dynamics play important roles in governing the regulation of nuclear processes of biological cells. However, due to the constant diffusive motion of chromatin, examining chromatin nanostructures in living cells has been challenging. In this study, we introduce interferometric scattering correlation spectroscopy (iSCORS) to spatially map nanoscopic chromatin configurations within unlabeled live cell nuclei. This label-free technique captures time-varying linear scattering signals generated by the motion of native chromatin on a millisecond timescale, allowing us to deduce chromatin condensation states. Using iSCORS imaging, we quantitatively examine chromatin dynamics over extended periods, revealing spontaneous fluctuations in chromatin condensation and heterogeneous compaction levels in interphase cells, independent of cell phases. Moreover, we observe changes in iSCORS signals of chromatin upon transcription inhibition, indicating that iSCORS can probe nanoscopic chromatin structures and dynamics associated with transcriptional activities. Our scattering-based optical microscopy, which does not require labeling, serves as a powerful tool for visualizing dynamic chromatin nano-arrangements in live cells. This advancement holds promise for studying chromatin remodeling in various crucial cellular processes, such as stem cell differentiation, mechanotransduction, and DNA repair.
Operationalizing climate risk in a global warming hotspot
Authors: Boyce Daniel G. , Tittensor Derek P. , Fuller Susanna , Henson Stephanie , Kaschner Kristin , Reygondeau Gabriel , Schleit Kathryn E. , Saba Vincent , Shackell Nancy , Stanley Ryan R. E. , Worm Boris
Published: June 2024

Climate change is a looming threat to marine life, creating an urgent need to develop climate-informed conservation strategies. The Climate Risk Index for Biodiversity was designed to assess the climate risk for marine species in a manner that supports decision-making. Yet, its regional application remains to be explored. Here, we use it to evaluate climate risk for ~2000 species in the northwest Atlantic Ocean, a marine warming hotspot, to explore its capacity to inform climate-considered fisheries management. Under high emissions, harvested species, especially those with the highest economic value, have a disproportionate risk of projected exposure to hazardous climate conditions but benefit the most from emission mitigation. By mapping critical risk areas for 90 fish stocks, we pinpoint locations likely to require additional intervention, such as in the southern Gulf of St. Lawrence for Atlantic cod. Finally, we demonstrate how evaluating climate risk geographically and understanding how it arises can support short- and long-term fisheries management and conservation objectives under climate change.
Sleep quality mediates the association between chronotype and mental health in young Indian adults
Authors: Chauhan Satyam , Pandey Rakesh , Vakani Krupa , Norbury Ray , Ettinger Ulrich , Kumari Veena
Published: June 2024

There is increasing recognition of ‘higher preference for eveningness’ as a potential independent risk factor for poor mental health. To examine the chronotype-mental health relationship while also quantifying the potential roles of poor sleep quality, relevant personality traits, and childhood trauma, we assessed 282 young adults (18–40 years; 195 females) residing in North India, between January and March 2023 (to control for seasonal variation), using self-report measures of diurnal preference, sleep patterns, mental health (depression, anxiety, and stress), personality traits (extraversion, neuroticism, schizotypy, and impulsivity), and childhood trauma. The results showed a significant association between eveningness and poor mental health but this association was fully mediated by poor sleep quality. Neuroticism, emotional abuse and cognitive disorganisation were correlated with eveningness as well as with poor mental health and sleep quality. Neuroticism and emotional abuse, but not cognitive disorganisation, also had indirect effects on mental health via sleep quality. Our findings highlight the crucial role played by sleep quality in the chronotype-mental health relationship.