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Advancing educational data mining for enhanced student performance prediction: a fusion of feature selection algorithms and classification techniques with dynamic feature ensemble evolution
Comprehensive study of the microplastic footprint in the urban pond and river of Eastern India
These frustrated scientists want to leave the United States — do you? Take Nature’s poll
An optimal federated learning-based intrusion detection for IoT environment
Novel method to measure track irregularity based on multiple MEMS-IMU and geometric constraint
Daily briefing: Should the Stanford Prison Experiment be retracted?
First insights and future research perspectives from the sarcoidosis registry at the Medical University of Vienna
Saturn has a whopping 274 moons ― scientists want to know why
Tolerance and effectiveness of inhaled antibiotics at standard or low doses in COPD patients with chronic Pseudomonas aeruginosa bronchial infection
Deep learning based agricultural pest monitoring and classification
Massively parallel characterization of transcriptional regulatory elements
Abstract The human genome contains millions of candidate cis -regulatory elements (cCREs) with cell-type-specific activities that shape both health and many disease states 1 . However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these cCREs. Here we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of more than 680,000 sequences, representing an extensive set of annotated cCREs among three cell types (HepG2, K562 and WTC11), and found that 41.7% of these sequences were active. By testing sequences in both orientations, we find promoters to have strand-orientation biases and their 200-nucleotide cores to function as non-cell-type-specific ‘on switches’ that provide similar expression levels to their associated gene. By contrast, enhancers have weaker orientation biases, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict cCRE function and variant effects with high accuracy, delineate regulatory motifs and model their combinatorial effects. Testing a lentiMPRA library encompassing 60,000 cCREs in all three cell types further identified factors that determine cell-type specificity. Collectively, our work provides an extensive catalogue of functional CREs in three widely used cell lines and showcases how large-scale functional measurements can be used to dissect regulatory grammar.
Cross-sectional associations between multiple plasma heavy metals and lung function among elderly Chinese
Author Correction: HIV-1 Env trimers asymmetrically engage CD4 receptors in membranes
Efficacy of continuous venovenous hemodiafiltration in patients with metformin associated lactic acidosis and acute kidney injury
POD24-Based prognostic signature enables personalized risk stratification in mantle cell lymphoma
A biopsychological network approach to variables contributing to preoperative quality of life in patients undergoing cardiac surgery
Abstract Quality of life (QoL) in cardiac surgery patients is increasingly recognized as a critical outcome, influenced by biopsychosocial variables. This study aims to explore the associations between preoperative QoL and various psychological and biomedical variables in patients undergoing cardiac surgery. The study includes cross-sectional baseline data from 204 cardiac surgery patients in two distinct cardiac surgery samples: Data collection for the PSY-HEART I trial (coronary artery bypass grafting) was conducted from 2011 to 2015, while data for the ValvEx (valvular surgery) trial were collected between 2020 and 2022. We assessed psychological variables, such as illness beliefs and expectations, alongside biomedical variables, including body mass index, EuroSCORE II, and C-reactive protein levels. Data analysis involved partial correlation Gaussian Graphical Models (GGM) and Directed Acyclic Graphs (DAGs) to identify key nodes and pathways affecting QoL. The resulting GGM was estimated to be rather sparse (38 of 136 possible edges were present) and the case-drop bootstrap node stability estimates ranged from sufficient (CS-Coefficient Bridge Expected Influence = 0.28) to good (CS-Coefficient Expected Influence = 0.51). Our analyses revealed strong associations between psychological variables and preoperative QoL, with current and expected illness-related disability being central to the network. Medical variables showed weaker connections to QoL. The DAG indicated that expected disability influenced current disability and preoperative QoL, suggesting that preoperative expectations may be crucial for postoperative outcomes. This study underscores the importance of psychological variables, particularly illness perceptions and expectations, in determining QoL in cardiac surgery patients. Targeting these variables through preoperative interventions may enhance postoperative recovery and QoL, advocating for a biopsychosocial approach in cardiac surgery care.
Magnetically and optically active edges in phosphorene nanoribbons
Abstract Nanoribbons, nanometre-wide strips of a two-dimensional material, are a unique system in condensed matter. They combine the exotic electronic structures of low-dimensional materials with an enhanced number of exposed edges, where phenomena including ultralong spin coherence times 1,2 , quantum confinement 3 and topologically protected states 4,5 can emerge. An exciting prospect for this material concept is the potential for both a tunable semiconducting electronic structure and magnetism along the nanoribbon edge, a key property for spin-based electronics such as (low-energy) non-volatile transistors 6 . Here we report the magnetic and semiconducting properties of phosphorene nanoribbons (PNRs). We demonstrate that at room temperature, films of PNRs show macroscopic magnetic properties arising from their edge, with internal fields of roughly 240 to 850 mT. In solution, a giant magnetic anisotropy enables the alignment of PNRs at sub-1-T fields. By leveraging this alignment effect, we discover that on photoexcitation, energy is rapidly funnelled to a state that is localized to the magnetic edge and coupled to a symmetry-forbidden edge phonon mode. Our results establish PNRs as a fascinating system for studying the interplay between magnetism and semiconducting ground states at room temperature and provide a stepping-stone towards using low-dimensional nanomaterials in quantum electronics.
Crop suitability analysis for the coastal region of India through fusion of remote sensing, geospatial analysis and multi-criteria decision making
Abstract Crop suitability analysis plays an important role in identifying and utilizing the areas suitable for better crop growth and higher yield without deteriorating the natural resources. The present study aimed to identify suitable areas for rice and coconut cultivation across the coastal region of India using the analytic hierarchy process (AHP) integrated with geographic information systems (GIS) and remote sensing. A total of nine parameters were selected for suitability analysis including elevation, slope, soil depth, drainage, texture, pH, soil organic carbon, rainfall, temperature and a land use land cover (LULC) constraint map. This study represents the first-ever application of an integrated approach combining AHP, GIS, and remote sensing for crop suitability analysis in entire coastal region of India. The weights for the parameters and subclasses were assigned using the AHP method based on experts’ opinions. Subsequently, all the thematic maps were overlaid using the weighted overlay analysis to generate a land suitability map. Separately, the LULC crop mask map was used to extract suitable areas for rice and coconut cultivation to create crop-specific suitability maps. The final suitability maps were classified into four different classes: highly suitable, moderately suitable, marginally suitable, and not suitable for crop production. The findings revealed that approximately 13.68% of the study area was highly suitable, with around 19.26% and 18.35% being moderately and marginally suitable, respectively, and 13.76% was not suitable for rice cultivation. Similarly, for coconut cultivation, approximately 11% were highly suitable, with 27.40% and 18.34% being moderately and marginally suitable. However, about 35% of the total study region was deemed permanently unsuitable for any type of cultivation. The suitability maps were validated using area under receiver operating characteristic curve (AUROC). The AUROC values for rice and coconut were found to be 0.764 and 0.740 indicating high accuracy. By strategically cultivating rice and coconut in highly and moderately suitable locations identified in the current study, and utilizing marginally suitable areas for other crops, it is possible to achieve financial viability in agricultural production by increasing crop yield without causing harm to natural resources.