As fires grow in intensity and frequency each year, so has the resistance from their anthropic victims in the form of firefighting technology and research. Although it is impossible to completely prevent wildfires, the potential devastation can be minimized if fires are detected and precisely geolocated while still in their nascent phases. Furthermore, automated approaches without human involvement are comparatively more efficient, accurate and capable of monitoring extremely remote and vast areas. With this specific intention, many research groups have proposed numerous approaches in the last several years, which can be grouped broadly into these four distinct categories: sensor nodes, unmanned aerial vehicles, camera networks and satellite surveillance. This review paper discusses notable advancements and trends in these categories, with subsequent shortcomings and challenges. We also describe a technical overview of common prototypes and several analysis models used to diagnose a fire from the raw input data. By writing this paper, we hoped to create a synopsis of the current state of technology in this emergent research area and provide a reference for further developments to other interested researchers.

Land plants have developed robust roots to grow in diverse soil ecosystems. The distal end of the root tip has a specialized organ called the ‘root cap’. The root cap assists the roots in penetrating the ground, absorbing water and minerals, avoiding heavy metals and regulating the rhizosphere microbiota. Furthermore, root-cap-derived auxin governs the lateral root patterning and directs root growth under varying soil conditions. The root cap formation is hypothesized as one of the key innovations during root evolution. Morphologically diversified root caps in early land plant lineage and later in angiosperms aid in improving the adaptation of roots and, thereby, plants in diverse soil environments. This review article presents a retrospective view of the root cap’s important morphological and physiological characteristics for the root–soil interaction and their response toward various abiotic and biotic stimuli. Recent single-cell RNAseq data shed light on root cap cell-type-enriched genes. We compiled root cap cell-type-enriched genes from Arabidopsis, rice, maize and tomato and analyzed their transcription factor (TF) binding site enrichment. Further, the putative gene regulatory networks derived from root-cap-enriched genes and their TF regulators highlight the species-specific biological functions of root cap genes across the four plant species.

In the last several years, conventional Drug Delivery Systems (DDS) have evolved into DDS that are responsive to exogenous or endogenous stimuli. The objective of this work was to present a DDS that is responsive to an electric stimulus, in the form of bipolar electric pulses. The DDS structure is based on chitosan embedded with magnetic nanoparticles, and crosslinked with polyethylene glycol dimethacrylate to form microbeads. This DDS is loaded with vancomycin as the therapeutic agent of interest. Silver Inter-Digitated Electrodes (IDE) were printed on Polyimide substrates with a MEMS-based inkjet material deposition printer, and used to provide 100 Hz pulses of electric current to the DDS for 3 min. The results showed that the stimulated groups released ∼800% more vancomycin than the non-stimulated groups in the excitation duration, but followed a first-order elution profile otherwise. Another significance of our approach is that it does not need complicated or expensive fabrication processes, and can be customized according to the targeted implant site. The IDE system has also been modeled using COMSOL® to study the distributed electric fields and ion migration during the stimulus. This work demonstrates a novel and promising technique of providing stimulus to drug substrates for controllable drug delivery.

In generic terms, a Drug Delivery Substrate (DDS) can be described as a vehicle to transport drug to the point of interest. A DDS that would ideally have the capability to control drug dosage, achieve target specificity and localization, higher therapeutic efficacy, etc. has been pursued as a holy grail in pharmaceutical research. Over the years, diverse classes, structures and modifications of DDS have been proposed to achieve this aim. One of its major deterrents, however, is rapid elimination by the immune system prior to the intended functionality. Stealth engineering is broadly defined as designing the drug carrier to minimize or delay opsonisation until the encapsulated drug is delivered in the intended manner. Perpetual improvisation of stealth engineered DDS has been successful in increasing their circulation lifetime from few minutes to several days. This field of research has made much progress since their initiation in 1960s with the liposomes to DNA boxes currently and has benefited several areas of medical applications. This paper reviews the progress of some types of DDS, that have been published and indexed in major databases of scientific literature (including ScienceDirect, PubMed, Google Scholar)

Aptamer-based biosensors (Aptasensors) have gained significant interest over the last decade for higher specificity to their targets, lower cost, and longer shelf life compared to their antibodies-based counterparts. However, not much is known about the binding characteristic of aptamers to their targets, i.e molecular recognition properties as this is a relatively unexplored area of research. Therefore, there is a need to better understand how aptamers bind to their targets because it can help the identification of aptamers for specific targets and in turn, lower the cost of aptamer-based biosensors design. In this work, we performed MEME analysis to detect recurring, fixed length patterns (better known as motifs) in our aptamer database. We focused on previously published aptamers that target different steroids. We also conducted another round of MEME on the four aptamer sequence types combined to further understanding of aptamers. We obtained the most likely motif for each steroid group using two accuracy metrics called E-value and p-value. This lays the foundation for exploring different ways on how aptamers bind to a myriad of targets as well as understanding their binding precision.