Instruct: Given a scientific paper title, retrieve paper titles that are cited by the given paper.
Query: The use of fly larvae for organic waste treatment.
From organic waste to biodiesel: Black soldier fly, Hermetia illucens, makes it feasible
Quantifying the components of the mass and energy balance of a black soldier fly ( BSF ) food waste composting system Tiny but Hungry
Rearing Methods for the Black Soldier Fly (Diptera: Stratiomyidae)
Anaerobic co-digestion of organic wastes
Current Anaerobic Digestion Technologies Used for Treatment of Municipal Organic Solid Waste
Helminth Ova Control in Wastewater and Sludge for Agricultural Reuse
Influences of chromium and cadmium on the development of black soldier fly larvae
Arthropod pest management in organic crops.
Organic contaminants in sewage sludge (biosolids) and their significance for agricultural recycling
Physico-chemical pretreatment and fungal biotreatment for park wastes and cattle dung for biogas production
THE BLACK SOLDIER FLY , HERMETIA ILLUCENS , AS A MANURE MANAGEMENT / RESOURCE RECOVERY TOOL
The Intestinal Bacterial Community in the Food Waste-Reducing Larvae of Hermetia illucens
Anaerobic digestion treatment of Tannery waste water
Novel and innovative pyrolysis and gasification technologies for energy efficient and environmentally sound MSW disposal.
Anaerobic co-digestion of food waste and piggery wastewater: focusing on the role of trace elements.
Edible insects as minilivestock
The melon fruit fly, Bactrocera cucurbitae: A review of its biology and management
Hydrothermal Carbonization of Municipal Waste Streams
Microbiological aspects of biowaste during composting in a monitored compost bin
Black soldier fly (Hermetia illucens) larvae enhances immune activities and increases survivability of broiler chicks against experimental infection of Salmonella Gallinarum
Biodiesel from algae: challenges and prospects.
Explanatory Item Response Models : A Brief Introduction
An overview of visible light communication systems
Learning Document Embeddings With CNNs
Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization