Search Results (93,290)

This study aimed to formulate a commercial quality index (CQI) for avocados (Persea americana Mill) produced in an inter-Andean valley in southern Peru. Thirty-eight commercial quality parameters of Hass and Fuerte avocados were evaluated under the marketing and export protocols approved in the Codex Alimentarius CXS 197-1995 issued by FAO and the Peruvian technical standard NTP 011.018. The index was formulated using information gathered from 44 experts in the Apurimac region. To weight the commercial quality parameters, the Delphi method was used, with the cooperation of expert producers and marketers, from which a weighted equation was formulated for the commercial quality index of Hass (CQI_h) and Fuerte (CQI_f) avocados. Fifteen parameters of interest were found for the formulation of the quality indexes for both varieties, which reported more than 50% coincidence among experts, based on physical and sensory evaluation. The CQI proposal would be a tool to help improve the quality attributes of avocado growers. Full article

Coffee is a critical agricultural commodity and is used to produce premium beverages enjoyed by people worldwide. The microbiome of coffee beans has proven to be an essential tool that improves the flavor profile of coffee by creating aromatic flavor compounds through natural fermentation. This study investigated the natural microbial consortium during the wet process fermentation of coffee onsite in Thailand in order to identify the correlation between microbial diversity and biochemical characteristics including flavor, aroma, and metabolic attributes. Our study found 64 genera of bacteria and 59 genera of yeast/ fungi present during the fermentation process. Group of microbes, mainly yeast and lactic acid bacteria, that predominated in the process were significantly correlated with preferable flavor and aroma compounds, including linalyl formate, linalool, cis-isoeugenol, trans-geraniol, and (-)-isopulegol. Some of the detected metabolites were found to be active compounds which could play a role in health. Full article

The analysis of large volumes of data collected from heterogeneous sources is increasingly important for the development of megacities, the advancement of smart city technologies, and ensuring a high quality of life for citizens. This study aimed to develop algorithms for analyzing and interpreting social media data to assess citizens’ opinions in real time and for verifying and examining data to analyze social tension and predict the development of situations during the implementation of urban projects. The developed algorithms were tested using an urban project in the field of transportation system development. The study’s material included data from social networks, messenger channels and chats, video hosting platforms, blogs, microblogs, forums, and review sites. An interdisciplinary approach was utilized to analyze the data, employing tools such as Brand Analytics, TextAnalyst 2.32, GPT-3.5, GPT-4, GPT-4o, and Tableau. The results of the data analysis showed identical outcomes, indicating a neutral perception among users and the absence of social tension surrounding the project’s implementation, allowing for the prediction of a calm development of the situation. Additionally, recommendations were developed to avert potential conflicts and eliminate sources of social tension for decision-making purposes. Full article

Feline lymphoma, a prevalent cancer in cats, exhibits varied prognoses influenced by anatomical site and cellular characteristics. In this study, we investigated the utility of flow cytometry and clonality analysis via PCR for antigen receptor rearrangement (PARR) with respect to characterizing the disease and predicting prognosis. For this purpose, we received fine needle aspirates and/or blood from 438 feline patients, which were subjected to flow cytometry analysis and PARR. We used a subset of the results from patients with confirmed B- or T-cell lymphomas for comparison to cytological or histological evaluation (n = 53). Using them as a training set, we identified the optimal set of flow cytometry parameters, namely forward scatter thresholds, for cell size categorization by correlating with cytology-defined sizes. Concordance with cytological sizing among this training set was 82%. Furthermore, 90% concordance was observed when the proposed cell sizing was tested on an independent test set (n = 24), underscoring the reliability of the proposed approach. Additionally, lymphoma subtypes defined by flow cytometry and PARR demonstrated significant survival differences, validating the prognostic utility of these methods. The proposed methodology achieves high concordance with cytological evaluations and provides an additional tool for the characterization and management of feline lymphoproliferative diseases. Full article

This paper presents a close-formation flight of two unmanned aerial vehicles (UAVs) and the aim of the study is to improve the understanding of the vortex effects between fixed-wing UAVs in a swarm using computational fluid dynamics (CFD) tools. To validate the numerical method, results of a variable-density wind tunnel test from the literature were used. This numerical CFD analysis was used to determine the lift coefficient (C_L) and the drag coefficient (C_D) values for a single UAV at various angles of attack. When examining the aerodynamic impact areas behind the UAV, the longitudinal distance between the two UAVs is not particularly effective for close flight. Therefore, CFD analyses were carried out on the two UAVs for both vertical and lateral distances. The optimum position for close-formation flight was identified using C_L/C_D ratios. The results of the analysis indicate that the most effective flights, across all lateral positions, occur when the two UAVs are vertically at the same height. In terms of aerodynamic efficiency, the most effective points for close-formation flight for wingspan b are at lateral distances of 0.875 b and 1 b. At these positions, flight efficiency can be increased by approximately 11.5%. Full article

This study examines the adoption of Power Purchase Agreements (PPAs) and Renewable Energy Certificates (RECs) as strategic tools for decarbonization in the oil and gas sector. Focusing on the 21 largest oil and gas companies across Europe, North America, and South America, the analysis reveals varied adoption rates and strategic emphases between regions. European companies exhibit robust integration of PPAs and RECs to expand renewable energy capacities and reduce emissions, aligning closely with aggressive EU climate policies. In contrast, American companies show a cautious approach, focusing more on emission reduction from existing operations than on renewable expansions. The study’s findings indicate that, while both regions are advancing in their decarbonization efforts, European companies are leading with more defined renewable energy targets and comprehensive low-carbon strategies. This research contributes to understanding how different regulatory environments and market conditions influence corporate strategies towards sustainable energy transitions in traditionally hard-to-abate industries. Full article

Therapeutic cancer vaccines have been considered in recent decades as important immunotherapeutic strategies capable of leading to tumor regression. In the development of these vaccines, the identification of neoepitopes plays a critical role, and different computational methods have been proposed and employed to direct and accelerate this process. In this context, this review identified and systematically analyzed the most recent studies published in the literature on the computational prediction of epitopes for the development of therapeutic vaccines, outlining critical steps, along with the associated program’s strengths and limitations. A scoping review was conducted following the PRISMA extension (PRISMA-ScR). Searches were performed in databases (Scopus, PubMed, Web of Science, Science Direct) using the keywords: neoepitope, epitope, vaccine, prediction, algorithm, cancer, and tumor. Forty-nine articles published from 2012 to 2024 were synthesized and analyzed. Most of the identified studies focus on the prediction of epitopes with an affinity for MHC I molecules in solid tumors, such as lung carcinoma. Predicting epitopes with class II MHC affinity has been relatively underexplored. Besides neoepitope prediction from high-throughput sequencing data, additional steps were identified, such as the prioritization of neoepitopes and validation. Mutect2 is the most used tool for variant calling, while NetMHCpan is favored for neoepitope prediction. Artificial/convolutional neural networks are the preferred methods for neoepitope prediction. For prioritizing immunogenic epitopes, the random forest algorithm is the most used for classification. The performance values related to the computational models for the prediction and prioritization of neoepitopes are high; however, a large part of the studies still use microbiome databases for training. The in vitro/in vivo validations of the predicted neoepitopes were verified in 55% of the analyzed studies. Clinical trials that led to successful tumor remission were identified, highlighting that this immunotherapeutic approach can benefit these patients. Integrating high-throughput sequencing, sophisticated bioinformatics tools, and rigorous validation methods through in vitro/in vivo assays as well as clinical trials, the tumor neoepitope-based vaccine approach holds promise for developing personalized therapeutic vaccines that target specific tumor cancers. Full article

Background: Suspicious tumors of the lung require specific staging, intraoperative detection, and histological confirmation. We performed an intrathoracic, intraoperative contrast-enhanced ultrasound (Io-CEUS) for characterization of lung cancer. Methods: Retrospective analysis of prospectively collected data on the application of Io-CEUS in thoracic surgery for patients with operable lung cancer. Analysis of the preoperative chest CT scan and FDG-PET/CT findings regarding criteria of malignancy. Immediately before lung resection, the intrathoracic Io-CEUS was performed with a contrast-enabled T-probe (6–9 MHz—L3-9i-D) on a high-performance ultrasound machine (Loqic E9, GE). In addition to intraoperative B-mode, color-coded Doppler sonography (CCDS), or power Doppler (macrovascularization) of the lung tumor, contrast enhancement (Io-CEUS) was used after venous application of 2.4–5 mL sulfur hexafluoride (SonoVue, Bracco, Italy) for dynamic recording of microvascularization. The primary endpoint was the characterization of operable lung cancer with Io-CEUS. Secondly, the results of Io-CEUS were compared with the preoperative staging. Results: The study included 18 patients with operable lung cancer, who received Io-CEUS during minimally invasive thoracic surgery immediately prior to lung resection. In the chest CT scan, the mean size of the lung tumors was 2.54 cm (extension of 0.7–4.5 cm). The mean SUV in the FDG-PET/CT was 7.6 (1.2–16.9). All lung cancers were detected using B-mode and power Doppler confirmed macrovascularization (100%) of the tumors. In addition, Io-CEUS showed an early wash-in with marginal and mostly simultaneous central contrast enhancement. Conclusions: The intrathoracic application of Io-CEUS demonstrated a peripheral and simultaneous central contrast enhancement in the early phase, which seems to be characteristic of lung cancer. In comparison to preoperative imaging, Io-CEUS was on par with the detection of malignancy and offers an additional tool for the intraoperative assessment of lung cancer before resection. Full article

While aspiring to become internationally valued producers of high-quality wines, certain Romanian wineries recently turned towards wine tourism. Given the increasing role of smart devices and online-based information in holiday selection and planning, the main objective of the paper is to evaluate the online presence, informational content and effectiveness of Romanian wineries’ websites for the promotion of wine tourism. This evaluation comprised 53 features tested in previous research and organized into four categories: main website characteristics, wine tourism, marketing, and education. Based on content analysis conducted on 154 websites of wineries identified in all Romanian regions, scores were computed and, subsequently, wineries were classified, mapped, and evaluated. The findings show that certain basic features are overall available, while exclusive features that could positively influence tourist preferences and experiences are insufficient in terms of design, education, and marketing characteristics. Less than 50% of the analysed websites inform about wine tasting activities, less than 35% specify visiting hours, and less than 20% mention tourist amenities. The websites that indicate other local wineries, allied industries or tourist attractions represent exceptions. This study underlines the importance of leveraging digital tools within the marketing strategy of wineries and the need to enhance networking among regional stakeholders as prerequisite for sustainable development. Full article

Ultrafast laser technology has moved from ultrafast to ultra-strong due to the development of chirped pulse amplification technology. Ultrafast laser technology, such as femtosecond lasers and picosecond lasers, has quickly become a flexible tool for processing brittle and hard materials and complex micro-components, which are widely used in and developed for medical, aerospace, semiconductor applications and so on. However, the mechanisms of the interaction between an ultrafast laser and brittle and hard materials are still unclear. Meanwhile, the ultrafast laser processing of these materials is still a challenge. Additionally, highly efficient and high-precision manufacturing using ultrafast lasers needs to be developed. This review is focused on the common challenges and current status of the ultrafast laser processing of brittle and hard materials, such as nickel-based superalloys, thermal barrier ceramics, diamond, silicon dioxide, and silicon carbide composites. Firstly, different materials are distinguished according to their bandgap width, thermal conductivity and other characteristics in order to reveal the absorption mechanism of the laser energy during the ultrafast laser processing of brittle and hard materials. Secondly, the mechanism of laser energy transfer and transformation is investigated by analyzing the interaction between the photons and the electrons and ions in laser-induced plasma, as well as the interaction with the continuum of the materials. Thirdly, the relationship between key parameters and ultrafast laser processing quality is discussed. Finally, the methods for achieving highly efficient and high-precision manufacturing of complex three-dimensional micro-components are explored in detail. Full article

Energy is a foundational element of the modern industrial economy. Prices of metals play a crucial role in energy sectors’ revenue evaluations, making them the cornerstone of effective payment management employed by resource policymakers. Copper is one of the most important industrial metals, and plays a vital role in various aspects of today’s economies. Copper is strongly associated with many industries, such as electrical wiring, construction, and equipment manufacturing; therefore, the price of copper has become a significant impact factor on the performance of related energy companies and economies. The accurate prediction of copper prices holds particular significance for market participants and policymakers. This study carried out research to address the gap in copper price forecasting using a one-dimensional convolutional neural network (1D-CNN). The proposed method was implemented and tested using extensive data spanning from November 1991 to May 2023. To assess the performance of the CNN model, standard evaluation metrics, such as the R-value, mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE), were employed. For the prediction of global copper prices, the proposed artificial intelligence algorithm demonstrated high accuracy. Lastly, future global copper prices were predicted up to 2027 by the CNN and compared with forecasts published by the International Monetary Fund and the International Society of Automation. The results show the exceptional performance of the CNN, establishing it as a reliable tool for monitoring copper prices and predicting global copper price volatilities near reality, and as carrying significant implications for policymakers and governments in shaping energy policies and ensuring equitable implementation of energy strategies. Full article

Preserving the function and survival of pancreatic beta-cells, in order to achieve long-term glycemic control and prevent complications, is an essential feature for an innovative drug to have clinical value in the treatment of diabetes. Innovative research is developing therapeutic strategies to prevent pathogenic mechanisms and protect beta-cells from the deleterious effects of inflammation and/or chronic hyperglycemia over time. A better understanding of receptors and signaling pathways, and of how they interact with each other in beta-cells, remains crucial and is a prerequisite for any strategy to develop therapeutic tools aimed at modulating beta-cell function and/or mass. Here, we present a comprehensive review of our knowledge on membrane and intracellular receptors and signaling pathways as targets of interest to protect beta-cells from dysfunction and apoptotic death, which opens or could open the way to the development of innovative therapies for diabetes. Full article

Background: Vision-based pulmonary diagnostics present a unique approach for tracking and measuring natural breathing behaviors through remote imaging. While many existing methods correlate chest and diaphragm movements to respiratory behavior, we look at how the direct visualization of thermal CO₂ exhale flow patterns can be tracked to directly measure expiratory flow. Methods: In this work, we present a novel method for isolating and extracting turbulent exhale flow signals from thermal image sequences through flow-field prediction and optical flow measurement. The objective of this work is to introduce a respiratory diagnostic tool that can be used to capture and quantify natural breathing, to identify and measure respiratory metrics such as breathing rate, flow, and volume. One of the primary contributions of this work is a method for capturing and measuring natural exhale behaviors that describe individualized pulmonary traits. By monitoring subtle individualized respiratory traits, we can perform secondary analysis to identify unique personalized signatures and abnormalities to gain insight into pulmonary function. In our study, we perform data acquisition within a clinical setting to train an inference model (FieldNet) that predicts flow-fields to quantify observed exhale behaviors over time. Results: Expiratory flow measurements capturing individualized flow signatures from our initial cohort demonstrate how the proposed flow field model can be used to isolate and analyze turbulent exhale behaviors and measure anomalous behavior. Conclusions: Our results illustrate that detailed spatial flow analysis can contribute to unique signatures for identifying patient specific natural breathing behaviors and abnormality detection. This provides the first-step towards a non-contact respiratory technology that directly captures effort-independent behaviors based on the direct measurement of imaged CO₂ exhaled airflow patterns. Full article

Spinocerebellar ataxia type 3/Machado–Joseph disease (SCA3/MJD) is a neurodegenerative disorder caused by the ATXN3 CAG repeat expansion. Preimplantation genetic testing for monogenic disorders (PGT-M) of SCA3/MJD should include reliable repeat expansion detection coupled with high-risk allele determination using informative linked markers. One couple underwent SCA3/MJD PGT-M combining ATXN3 (CAG)_n triplet-primed PCR (TP-PCR) with customized linkage-based risk allele genotyping on whole-genome-amplified trophectoderm cells. Microsatellites closely linked to ATXN3 were identified and 16 markers were genotyped on 187 anonymous DNAs to verify their polymorphic information content. In the SCA3/MJD PGT-M case, the ATXN3 (CAG)_n TP-PCR and linked marker analysis results concurred completely. Among the three unaffected embryos, a single embryo was transferred and successfully resulted in an unaffected live birth. A total of 139 microsatellites within 1 Mb upstream and downstream of the ATXN3 CAG repeat were identified and 8 polymorphic markers from each side were successfully co-amplified in a single-tube reaction. A PGT-M assay involving ATXN3 (CAG)_n TP-PCR and linkage-based risk allele identification has been developed for SCA3/MJD. A hexadecaplex panel of highly polymorphic microsatellites tightly linked to ATXN3 has been developed for the rapid identification of informative markers in at-risk couples for use in the PGT-M of SCA3/MJD. Full article

Small landscape features (i.e., trees outside forest, small woody features) and linear vegetation such as hedgerows, riparian vegetation, and green lanes are vital ecological structures in agroecosystems, enhancing the biodiversity, landscape diversity, and protecting water bodies. Therefore, their monitoring is fundamental to assessing a specific territory’s arrangement and verifying the effectiveness of strategies and financial measures activated at the local or European scale. The size of these elements and territorial distribution make their identification extremely complex without specific survey campaigns; in particular, remote monitoring requires data of considerable resolution and, therefore, is very costly. This paper proposes a methodology to map these features using a combination of open-source or low-cost high-resolution orthophotos (RGB), which are typically available to local administrators and are object-oriented classification methods. Additionally, multispectral satellite images from the Sentinel-2 platform were utilized to further characterize the identified elements. The produced map, compared with the other existing layers, provided better results than other maps at the European scale. Therefore, the developed method is highly effective for the remote and wide-scale assessment of SWFs, making it a crucial tool for defining and monitoring development policies in rural environments. Full article