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Unveiling whole body vibration squat intensity insight from oxygen consumption and heart rate response
Multiarm-Assisted Design of Dendron-like Degradable Ionizable Lipids Facilitates Systemic mRNA Delivery to the Spleen
Cause and consequences of Common Snook (Centropomus undecimalis) space use specialization in a subtropical riverscape
The intelligent selenium-enriched tea withering control system
Kinetic and Affinity Profiling Rare Earth Metals Using a DNA Aptamer
MXene-based multilayered and ultrawideband absorber for solar cell and photovoltaic applications
O <sub>2</sub> Activation and Enzymatic C–H Bond Activation Mediated by a Dimanganese Cofactor
A wideband coaxial-to-waveguide transition devised with topology optimization
Feature enhanced cascading attention network for lightweight image super-resolution
Application of three statistical approaches to explore effects of dietary intake of multiple persistent organic pollutants on ER-positive breast cancer risk in the French E3N cohort
Abstract Persistent organic pollutants (POPs) are a group of organic chemical compounds. Contradictory results have emerged in epidemiological studies attempting to elucidate their relationship with breast cancer risk. This study explored the relationship between dietary exposures to multiple POPs and ER-positive breast cancer risk in the French E3N cohort study, using three different approaches to handle multicollinearity among exposures. Intakes of 81 POPs were estimated using food consumption data from a validated semi-quantitative food frequency questionnaire and food contamination data. In the first approach, hierarchical clustering was performed to identify clusters of correlated POPs. For each cluster, the levels of POPs belonging to it were averaged. These average levels were then included in a Cox model to estimate their associations with ER-positive breast cancer occurrence. The second and third approaches applied in the present study were Principal component Cox regression (PCR-Cox) and partial least squares Cox regression (PLS-Cox) respectively, both being dimension-reduction methods (respectively unsupervised and supervised) coupled to a Cox model, used to identify principal components of POPs and to estimate their associations with ER-positive breast occurrence. All models were adjusted for potential confounders previously identified using a directed acyclic graph. The study included 66,722 women with a median follow-up of 20.3 years, during which 3,739 developed an incident ER-positive breast cancer. The variable clustering method did not identify any association between the averaged variables and ER-positive breast cancer risk. Five components were retained using both the PCR-Cox and PLS-Cox methods explaining 82% and 77% of the variance in the initial exposure matrix respectively. Among these components, none was significantly associated with the occurrence of ER-positive breast cancer. This study provides an illustrative example of the application of three distinct statistical methods in the context of highly correlated environmental exposures, discussing their potential relevance and limitations within this specific framework.
Comparative efficacy of plant derived extracts with the insecticide mospilan on two whitefly species Bemisia tabaci biotype B and Trialeurodes ricini
Abstract The insecticidal, synergistic, and acetylcholinesterase (AChE) inhibitory effects of plant n-hexane extracts (HEs) were evaluated. The HEs from thyme (Thymus vulgaris L.) leaves, garlic (Allium sativum L.) bulbs, and weeping willow (Salix babylonica L.) leaves were used in comparison with the acetamiprid insecticide (mospilan) against two whitefly species, Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) biotype B and Trialeurodes ricini (Genn.) (Hemiptera: Aleyrodidae). Furthermore, using the choice test design, the repellent efficacy of three extracts was investigated against whitefly B. tabaci biotype B. The chemical compositions of HEs were identified using gas chromatography-mass spectrometry (GC-MS) and gas chromatography with flame-ionization detection (GC-FID) analysis. The main compounds of thyme HE were thymol and geranyl-α-terpinene; in garlic bulbs HE were diallyl sulfide and allyl tetrasulfide; and in weeping willow HE were 6-phenyltridecane, 6-phenyldodecane, and 5-phenyldodecane, while the methylated fatty acids were stearic and palmitic. The HEs of weeping willow and garlic showed the maximum toxicity against B. tabaci, while the HEs of thyme and garlic showed the highest toxicity against T. ricini. Mospilan with HEs resulted in a potentiating effect, with co-toxicity factors ranging between 21.47 for a mixture of garlic HE + mospilan against B. tabaci and 37.65 for weeping willow HE + mospilan against T. ricini. The mix of mospilan + weeping willow HE recorded the highest acetylcholinesterase (AChE) inhibitory effect 48 h after treatment. The highest expulsion effect was recorded by 2% thyme HE, with a repellency index (RI) of 88.22%. The HE of weeping willow at 1% exhibited the highest attractant effect with an RI value of -8.94%. The current research lays the groundwork for the integrated pest management (IPM) of B. tabaci biotype B and T. ricini by employing natural extracts and pesticides blends.
MicroRNA-150-3p enhances the antitumour effects of CGP57380 and is associated with a favourable prognosis in non-small cell lung cancer
DeepDrug as an expert guided and AI driven drug repurposing methodology for selecting the lead combination of drugs for Alzheimer’s disease
The use of green synthesized TiO2/MnO2 nanoparticles in solar power membranes for pulp and paper industry wastewater treatment
Abstract The pulp and paper manufacturing wastewater is as complicated as any other industrial effluent. A promising approach to treating water is to combine photocatalysis and membrane processes. This paper demonstrates a novel photocatalytic membrane technique for solar-powered water filtration. The method is based on creating green-prepared TiO2, and MnO2 nanoparticles (NPs) using Pomegranate peels and Seder leaf extracts and incorporation into polyvinylidene chloride to produce a novel water purification system that combines semiconductor photocatalysis with membrane filtration. The prepared heterostructure of the TiO2/MnO2 nanocomposite membrane provides photogenerated charge separation. To ensure chemical bonding at the membrane surface, Raman and Fourier transform infrared spectroscopy (FT-IR) were employed. The modified membrane’s hydrophilicity and roughness increased significantly. Additionally, the modified nanocomposite membrane’s porosity was measured. The integrated process demonstrated much higher removal of humic acid and high efficiency of wastewater treatment for pulp and paper. In sunlight, humic acid removal was 98% from synthetic wastewater. While using the produced membrane on pulp and paper effluent, these studies indicate that: in the dark, the removal was 50%, while in the sunlight, the removal increased to 70%, with a reduction in the COD from 1500 mg/L to 247 mg/L. Additionally, the TDS decreased from 1630 to 452 ppt in the sunlight. This research sheds light on how solar energy can clean wastewater from the pulp and paper industry while improving membrane separation. Also, an alternative source to sunlight was used to manufacture a photocatalytic membrane with high efficiency for wastewater treatment and an inexpensive price.
Challenges and insights of transferring animal maze studies principles to human spatial learning research
ATKB-PID: an adaptive control method for micro tension under complex hot rolling conditions
Abstract At present, the parameters of the controllers in hot rolling roughing microtension control systems are not adaptively adjustable to variations in working conditions, which compromises both width accuracy and production stability. To address this issue, this paper introduces an ATKB-PID adaptive micro tension control method. This method incorporates a linear attention layer and utilizes a K-Nearest Neighbors (KNN) algorithm to predict the optimal learning rate and inertia coefficient under actual operating conditions. Furthermore, an objective function is tailored to production indices to enhance model performance. Comparative experiments with both established and recently introduced controllers demonstrate that the proposed ATKB-PID method exhibits a smaller steady-state error and quicker adjustment time. The ATKB-PID control method is well-suited for the complex and dynamic microtension control demands in thermal roughing processes, showing promising application potential.