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Conversion of rice straw into nanocellulose offers a sustainable approach to agricultural waste management, yielding an industrially important product with potential applications. This work focuses on effectively extracting pure cellulose from both widely used Basmati and Parmal rice straw (BRS and PRS) using less alkali concentrations (3-5 % NaOH). The process was optimized via Box Behnken design at 90-150 °C temperatures for 90-150 min, which resulted in 88.

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Background: The removal of excessive neck skin is considered the key parameter in the best postoperative outcome after a neck rejuvenation surgery.

Objective: To evaluate the utility of a local anesthesia-based direct neck skin excision surgery in patients with skin laxity and sagging skin in the neck in terms of postoperative aesthetic outcome and patient satisfaction within a 12-month follow-up period.

Materials And Methods: A total of 47 female patients who underwent local anesthesia-based direct neck skin excision surgery for the rejuvenation of skin laxity and sagging skin in the cervical neck were included.

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Bioaugmented design and functional evaluation of low damage implantable array electrodes.

Bioact Mater

May 2025

State Key Laboratory for Manufacturing System Engineering, School of Mechanical Engineering, Xi'an Jiaotong University, China.

Implantable neural electrodes are key components of brain-computer interfaces (BCI), but the mismatch in mechanical and biological properties between electrode materials and brain tissue can lead to foreign body reactions and glial scarring, and subsequently compromise the long-term stability of electrical signal transmission. In this study, we proposed a new concept for the design and bioaugmentation of implantable electrodes (bio-array electrodes) featuring a heterogeneous gradient structure. Different composite polyaniline-gelatin-alginate based conductive hydrogel formulations were developed for electrode surface coating.

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Traditional rainfall data collection mainly relies on rain buckets and meteorological data. It rarely considers the impact of sensor faults on measurement accuracy. To solve this problem, a two-layer genetic algorithm-backpropagation (GA-BP) model is proposed.

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Air conditioning systems are widely used to provide thermal comfort in hot and humid regions, but they also consume a large amount of energy. Therefore, accurate and reliable load demand forecasting is essential for energy management and optimization in air conditioning systems. Within the current paper, a novel model on the basis of machine learning has been presented for dynamic optimal load demand forecasting in air conditioning systems.

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