Bioconversion of Poultry Litter into Insect Meal and Organic Frasstilizer Using Black Soldier Fly Larvae as a Circular Economy Model for the Poultry Industry: A Review.

Poultry litter waste management poses a significant global challenge, attributed to its characteristics (odorous, organic, pathogenic, attracting flies). Conventional approaches to managing poultry litter involve composting, biogas generation, or direct field application. Recently, there has been a surge of interest in a novel technology that involves the bioconversion of organic waste utilizing insects (known as entomoremediation), particularly focusing on black soldier fly larvae (BSFL), and has demonstrated successful transformation of various organic waste materials into insect meal and frass (referred to as organic frasstilizer).

In Vitro Evaluation of Ruminal Digestibility, Fermentation Characteristics, and Bacterial Diversity of Kenaf Crop at Various Cutting Heights.

The current study investigated the in vitro degradability, in vitro gas production, methane (CH) production, and ruminal bacterial community of kenaf plants cut at different heights (130, 160, 190, 220, and 250 cm). These samples were subjected to an in vitro batch culture system using buffalo rumen fluid to measure gas and CH production at 3, 6, 9, 12, 24, 36, 48, and 72 h of incubation. Results reveal that crude protein (CP) concentration was the highest at the 220 cm height compared with the other heights.

Phosphoric acid based geopolymer foam-activated carbon composite for methylene blue adsorption: isotherm, kinetics, thermodynamics, and machine learning studies.

In this study, a binary composite adsorbent based on activated carbon and phosphoric acid geopolymer foam (ACP) was prepared by combining phosphoric acid geopolymer (PAGP) with activated carbon (AC) and applied for the removal of methylene blue (MB). Activated carbon was thoroughly mixed with a mixture of fly ash and metakaolin in varying ratios, followed by phosphoric acid activation and thermal curing. The ACP adsorbent was characterized using scanning electron microscope (SEM), Fourier transform infrared (FTIR) spectrophotometer, X-ray diffractometer (XRD), surface area analyser (SAP), and thermogravimetric analyser (TGA).

Artificial Intelligence in Computer-Aided Drug Design (CADD) Tools for the Finding of Potent Biologically Active Small Molecules: Traditional to Modern Approach.

Computer-Aided Drug Design (CADD) entails designing molecules that could potentially interact with a specific biomolecular target and promising their potential binding. The stereo- arrangement and stereo-selectivity of small molecules (SMs)--based chemotherapeutic agents significantly influence their therapeutic potential and enhance their therapeutic advantages. CADD has been a well-established field for decades, but recent years have observed a significant shift toward acceptance of computational approaches in both academia and the pharmaceutical industry.

A Novel Preoperative Scoring System to Accurately Predict Cord-Level Intraoperative Neuromonitoring Data Loss During Spinal Deformity Surgery: A Machine-Learning Approach.

Background: An accurate knowledge of a patient's risk of cord-level intraoperative neuromonitoring (IONM) data loss is important for an informed decision-making process prior to deformity correction, but no prediction tool currently exists.

Methods: A total of 1,106 patients with spinal deformity and 205 perioperative variables were included. A stepwise machine-learning (ML) approach using random forest (RF) analysis and multivariable logistic regression was performed.