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    Ministry of Education Reports Findings in Malaria (Classification and clinical significance of immunogenic cell death-related genes in Plasmodium falciparum infection determined by integrated bioinformatics analysis and machine learning)

    67-68页
    查看更多>>摘要：New research on Mosquito-Borne Diseases - Malaria is the subject of a report. According to news originating from Fuzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Immunogenic cell death (ICD) is a type of regulated cell death that plays a crucial role in activating the immune system in response to various stressors, including cancer cells and pathogens. However, the involvement of ICD in the human immune response against malaria remains to be defined.” Financial support for this research came from Natural Science Foundation of Fujian Province,China. Our news journalists obtained a quote from the research from the Ministry of Education, “In this study, data from Plasmodium falciparum infection cohorts, derived from cross-sectional studies, were analysed to identify ICD subtypes and their correlation with parasitaemia and immune responses. Using consensus clustering, ICD subtypes were identified, and their association with the immune landscape was assessed by employing ssGSEA. Differentially expressed genes (DEGs) analysis, functional enrichment, protein-protein interaction networks, and machine learning (least absolute shrinkage and selection operator (LASSO) regression and random forest) were used to identify ICD-associated hub genes linked with high parasitaemia. A nomogram visualizing these genes’ correlation with parasitaemia levels was developed, and its performance was evaluated using receiver operating characteristic (ROC) curves. In the P. falciparum infection cohort, two ICD-associated subtypes were identified, with subtype 1 showing better adaptive immune responses and lower parasitaemia compared to subtype 2. DEGs analysis revealed upregulation of proliferative signalling pathways, T-cell receptor signalling pathways and T-cell activation and differentiation in subtype 1, while subtype 2 exhibited elevated cytokine signalling and inflammatory responses. PPI network construction and machine learning identified CD3E and FCGR1A as candidate hub genes. A constructed nomogram integrating these genes demonstrated significant classification performance of high parasitaemia, which was evidenced by AUC values ranging from 0.695 to 0.737 in the training set and 0.911 to 0.933 and 0.759 to 0.849 in two validation sets, respectively. Additionally, significant correlations between the expressions of these genes and the clinical manifestation of P. falciparum infection were observed. This study reveals the existence of two ICD subtypes in the human immune response against P. falciparum infection. Two ICD-associated candidate hub genes were identified, and a nomogram was constructed for the classification of high parasitaemia.”
      原文链接:
    • NETL
    • NSTL
    • Springer Nature

    Research Conducted at University of Cadiz Has Provided New Information about Artificial Intelligence (How Does the Visualization Technique Affect the Design Process? Using Sketches, Real Products and Virtual Models To Test the User's Emotional ...)

    68-69页
    查看更多>>摘要：New research on Machine Learning - Artificial Intelligence is the subject of a report. According to news originating from Cadiz, Spain, by NewsRx correspondents, research stated, “Testing products during the design process can help design teams anticipate user needs and predict a positive emotional response. Emerging technologies, e.g., Virtual Reality (VR), allow designers to test products in a more sophisticated manner alongside traditional approaches like sketches, photographs or physical prototypes.” Financial support for this research came from University of Malaga. Our news journalists obtained a quote from the research from the University of Cadiz, “In this paper, we present the results of a study conducted to evaluate the feasibility of seven visualization techniques for product assessment within the framework of emotional design, suggesting that the user’s perception depends on the visualization technique used to present the product. This research provides recommendations for product evaluation using physical, virtual, or conceptual prototypes to analyze the user’s emotional response throughout 19 parameters. Our results indicate that the use of virtual environments, including VR and VR with Passive Haptics (VRPH), can facilitate user participation in the design process, although these visualization techniques may also exaggerate the emotions perceived by users. In this context, VRPH tends to overstate the tactile perception of the product. Additionally, our results reveal that both virtual and conceptual environments can amplify a user’s likelihood to purchase a product. However, the latter setting could also potentially lead to confusion among users in regards to their perception of the product’s weight, dimensions, and cost.”
      原文链接:
    • NETL
    • NSTL
    • Univ Int Rioja-Unir

    Ghent University Hospital Reports Findings in Artificial Intelligence (Prediction of certainty in artificial intelligence-enabled electrocardiography)

    69-70页
    查看更多>>摘要：New research on Artificial Intelligence is the subject of a report. According to news reporting from Ghent, Belgium, by NewsRx journalists, research stated, “The 12-lead ECG provides an excellent substrate for artificial intelligence (AI) enabled prediction of various cardiovascular diseases. However, a measure of prediction certainty is lacking.” The news correspondents obtained a quote from the research from Ghent University Hospital, “To assess a novel approach for estimating certainty of AI-ECG predictions. Two convolutional neural networks (CNN) were developed to predict patient age and sex. Model 1 applied a 5 s sliding time-window, allowing multiple CNN predictions. The consistency of the output values, expressed as interquartile range (IQR), was used to estimate prediction certainty. Model 2 was trained on the full 10s ECG signal, resulting in a single CNN point prediction value. Performance was evaluated on an internal test set and externally validated on the PTB-XL dataset. Both CNNs were trained on 269,979 standard 12-lead ECGs (82,477 patients). Model 1 showed higher accuracy for both age and sex prediction (mean absolute error, MAE 6.9 ± 6.3 years vs. 7.7 ± 6.3 years and AUC 0.946 vs. 0.916, respectively, P<0.001 for both). The IQR of multiple CNN output values allowed to differentiate between high and low accuracy of ECG based predictions (P <0.001 for both). Among 10% of patients with narrowest IQR, sex prediction accuracy increased from 65.4% to 99.2%, and MAE of age prediction decreased from 9.7 to 4.1 years compared to the 10% with widest IQR. Accuracy and estimation of prediction certainty of model 1 remained true in the external validation dataset.”
      原文链接:
    • NETL
    • NSTL

    Data on Machine Learning Reported by Maria Alice Prado Cechinel and Colleagues (Predicting effluent quality parameters for wastewater treatment plant: A machine learning-based methodology)

    70-71页
    查看更多>>摘要：New research on Machine Learning is the subject of a report. According to news reporting out of Florianopolis, Brazil, by NewsRx editors, research stated, “Wastewater Treatment Plants (WWTPs) present complex biochemical processes of high variability and difficult prediction. This study presents an innovative approach using Machine Learning (ML) models to predict wastewater quality parameters.” Our news journalists obtained a quote from the research, “In particular, the models are applied to datasets from both a simulated wastewater treatment plant (WWTP), using DHI WEST software (WEST WWTP), and a real-world WWTP database from Santa Catarina Brewery AMBEV, located in Lages/SC - Brazil (AMBEV WWTP). A distinctive aspect is the evaluation of predictive performance in continuous data scenarios and the impact of changes in WWTP operations on predictive model performance, including changes in plant layout. For both plants, three different scenarios were addressed, and the quality of predictions by random forest (RF), support vector machine (SVM), and multilayer perceptron (MLP) models were evaluated. The prediction quality by the MLP model reached an R of 0.72 for TN prediction in the WEST WWTP output, and the RF model better adapted to the real data of the AMBEV WWTP, despite the significant discrepancy observed between the real and the predicted data. Techniques such as Partial Dependence Plots (PDP) and Permutation Importance (PI) were used to assess the importance of features, particularly in the simulated WEST tool scenario, showing the strong correlation of prediction results with influent parameters related to nitrogen content. The results of this study highlight the importance of collecting and storing high-quality data and the need for information on changes in WWTP operation for predictive model performance.”
      原文链接:
    • NETL
    • NSTL

    Investigators from University of California Davis Zero in on Machine Learning [Nitrogen Retrieval In Grapevine (Vitis Vinifera L.) Leaves By Hyperspectral Sensing]

    71-72页
    查看更多>>摘要：Current study results on Machine Learning have been published. According to news originating from Davis, California, by NewsRx correspondents, research stated, “Nitrogen (N) is a critical macronutrient that directly affects grapevine yield and quality but is also highly mobile in soil and can cause environmental contamination when over-applied. Monitoring leaf N content is useful for assessing vine N status and thereby improving N management plans, and the ability to assess N by remote sensing is desirable.” Financial supporters for this research include USDA-NIFA Specialty Crop Research Initiative, California Table Grape Commission. Our news journalists obtained a quote from the research from the University of California Davis, “Remote sensing technology has been utilized for retrieving N in agronomic crops since the 1990s. However, remote sensing has not been widely adopted for N management mainly due to variability in spectral patterns that emerge when training a model on one dataset and then applying it to a different dataset. Differences in environmental conditions, phenological stages, and plant varieties contribute to variability. This study aimed to understand the major factors limiting the generalizability of N-level retrieval algorithms in grapevine: the impact of leaf age and how calibrating nitrogen content, using either leaf dry mass (Nmass) or leaf area (Narea), influence the outcomes. This study also compares the performance among five major N retrieval approaches. We used spectral data from a hand-held hyperspectral sensor measuring wavelengths from 350 to 2500 nm from 664 individual leaf samples obtained from two grapevine varieties on three different sampling campaigns. Our findings indicate that while machine learning and chemometric approaches offer high accuracy levels (R2 = 0.78), the physical modeling approach utilizing the PROSPECT radiative transfer model (RTM) is capable of consistently retrieving N independent of specific dataset conditions and with an acceptable level of accuracy (R2 = 0.45) while using only 50% of the hyperspectral data. The estimation of Nmass using Proteinmass, which was calculated from Proteinarea retrieved by RTM and ground truth LMA, demonstrates a high potential for consistent retrieval of Total N (TN) in grapes. We also found that while calibrating a model by Narea can eliminate the negative impact of leaf age on prediction accuracy, Nmass still performed better in four out of five approaches tested.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    Researcher from Beihang University Discusses Findings in Robotics (Magnetically Driven Biopsy Capsule Robot with Spring Mechanism)

    72-73页
    查看更多>>摘要：Current study results on robotics have been published. According to news originating from Beijing, People’s Republic of China, by NewsRx editors, the research stated, “In recent years, capsule endoscopes (CEs) have appeared as an advanced technology for the diagnosis of gastrointestinal diseases. However, only capturing the images limits the advanced diagnostic procedures and so on in CE’s applications.” Financial supporters for this research include National Key R&D Program of China; Beijing Municipal Fund For Distinguished Young Scholars. The news editors obtained a quote from the research from Beihang University: “Herein, considering other extended functions like tissue sampling, a novel wireless biopsy CE has been presented employing active locomotion. Two permanent magnets (PMs) have been placed into the robots, which control the actuation of the capsule robot (CR) and biopsy mechanism by employing an external electromagnetic actuation (EMA) system. A spring has been attached to the biopsy mechanism to retract the biopsy tool after tissue collection. A camera module has also been attached to the front side of the CR to detect the target point and observe the biopsy process on the lesion. A prototype of CR was fabricated with a diameter of 12 mm and a length of 32 mm. A spring mechanism with a biopsy needle was placed inside the CR and sprang out around 5 mm.”
      原文链接:
    • NETL
    • NSTL
    • Mdpi

    Study Findings on Machine Translation Detailed by a Researcher at Henan University of Technology (Multi-mechanism neural machine translation framework for automatic program repair)

    73-74页
    查看更多>>摘要：Data detailed on machine translation have been presented. According to news originating from Zhengzhou, People’s Republic of China, by NewsRx correspondents, research stated, “Automatic program repair (APR) is crucial to improve software quality. Recently, neural machine translation (NMT) based modeling for bug fixes has demonstrated great potential.” The news reporters obtained a quote from the research from Henan University of Technology: “However, these approaches still have two major challenges. One is that their search space is limited due to the out-ofvocabulary (OOV) problem. The other is that the NMT-based APR models tend to ignore past translation information, which often leads to over-translation and under-translation. To address the above challenges, we propose MNRepair, a new NMT-based APR approach that combines multiple mechanisms to fix bugs in source code. Specifically, we devise an encoder-decoder NMT framework with the attention mechanism. Our framework combines the copy mechanism to overcome the OOV problem that occurs with source code.”
      原文链接:
    • NETL
    • NSTL

    Researchers from Dana-Farber Cancer Institute Discuss Findings in Robotics (Automated Radiolabeling and Handling of 177lu- and 225ac-psma-617 Using a Robotic Pipettor)

    74-74页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news originating from Boston, Massachusetts, by NewsRx correspondents, research stated, “While automated modules for F- 18 and C-11 radiosyntheses are standardized with features such as multiple reactors, vacuum connection and semi-preparative HPLC, labeling and processing of compounds with radiometals such as Zr-89, Lu- 177 and Ac-225 often do not require complex manipulations and are frequently performed manually by a radiochemist. These procedures typically involve transferring solutions to and from vials using pipettes followed by heating of the reaction mixture, and do not require all the features found in most commercial automated synthesis units marketed as F-18 or C-11 modules.” Our news journalists obtained a quote from the research from Dana-Farber Cancer Institute, “Here we present an efficient automated method for performing radiosyntheses involving radiometals by adapting a commercially available robotic pipettor originally developed for high-throughput processing of biological samples. While a robotic pipettor is less costly than a radiosynthesis module, it holds many similar advantages over manual radiosynthesis such as minimization of operator error, lower operator exposure rates, and abbreviated synthesis times, among others. To demonstrate the feasibility of using the OpenTrons OT-2 robotic pipettor to perform automated radiosyntheses, we radiolabeled and formulated (177) Lu- PSMA-617 and (225) Ac-PSMA-617 on the system.”
      原文链接:
    • NETL
    • NSTL
    • Wiley

    Findings in the Area of Robotics Reported from University of Stuttgart (Cooperative Object Transportation With Differentialdrive Mobile Robots: Control and Experimentation)

    75-75页
    查看更多>>摘要：Investigators publish new report on Robotics. According to news reporting out of Stuttgart, Germany, by NewsRx editors, research stated, “Non -prehensile cooperative object transportation is a challenging model problem for distributed control and organization methods but also has practical applications. Therefore, it is widely studied in distributed robotics research.” Financial support for this research came from German Research Foundation (DFG). Our news journalists obtained a quote from the research from the University of Stuttgart, “This paper describes and evaluates a novel transportation scheme for differential -drive mobile robots that is, to the authors’ best knowledge, the most versatile scheme of its kind successfully evaluated with real -world hardware. The proposed scheme can conceptually deal with any number of robots and arbitrary polygonal objects, including non -convex ones, without having to retune, retrain, or reconfigure any of the control parameters between different scenarios. This is achieved by splitting the task into a formation control and a formation finding task, both of which are tackled with model -based approaches using distributed optimization. Formation control and formation finding are complicated by the robots’ non-holonomic kinematic constraints. Therefore, a tailored distributed model predictive controller is used for formation control. Finding formations relies on a multibody-dynamics representation of the robots -object system to properly account for contact and non-holonomic constraints.”
      原文链接:
    • NETL
    • NSTL
    • Elsevier

    University of Craiova Researchers Advance Knowledge in Artificial Intelligence (Artificial intelligence and IoT driven technologies for environmental pollution monitoring and management)

    76-76页
    查看更多>>摘要：Research findings on artificial intelligence are discussed in a new report. According to news reporting originating from Craiova, Romania, by NewsRx correspondents, research stated, “Detecting hazardous substances in the environment is crucial for protecting human wellbeing and ecosystems.” Funders for this research include Rural Development Administration. Our news journalists obtained a quote from the research from University of Craiova: “As technology continues to advance, artificial intelligence (AI) has emerged as a promising tool for creating sensors that can effectively detect and analyze these hazardous substances. The increasing advancements in information technology have led to a growing interest in utilizing this technology for environmental pollution detection. AI-driven sensor systems, AI and Internet of Things (IoT) can be efficiently used for environmental monitoring, such as those for detecting air pollutants, water contaminants, and soil toxins. With the increasing concerns about the detrimental impact of legacy and emerging hazardous substances on ecosystems and human health, it is necessary to develop advanced monitoring systems that can efficiently detect, analyze, and respond to potential risks. Therefore, this review aims to explore recent advancements in using AI, sensors and IOTs for environmental pollution monitoring, taking into account the complexities of predicting and tracking pollution changes due to the dynamic nature of the environment. Integrating machine learning (ML) methods has the potential to revolutionize environmental science, but it also poses challenges.”
      原文链接:
    • NETL
    • NSTL
    • Frontiers Media Sa