ALBERT

Description: Background: Enterococcus is an important cause of infection in the hospital as well as in the community. Methods: A prospective study was done in Medical College, Kolkata for a period of 2 years (from January 2018 to December 2019). After obtaining clearance from the Institutional Ethics Committee, Enterococcus isolates from cases of vaginitis were included in the study. Identification of Enterococcus species was done by Gram stain and conventional biochemical tests along with automated identification by VITEK 2 Compact. These isolates were tested for antimicrobial susceptibility to different antibiotics by Kirby Bauer disc diffusion method and minimum inhibitory concentration (MIC) by VITEK 2 Compact. Interpretation of susceptibility was done according to the Clinical and Laboratory Standards Institute (CLSI) 2017 guidelines. Biofilm detection for Enterococcus species was done. Results: During the period of 2 years, 39 isolates of Enterococcus spp. were obtained from vaginitis cases. Among these, 27 were Enterococcus faecalis and 12 Enterococcus faecium. All isolates were highly susceptible to vancomycin, teicoplanin, and linezolid. Biofilm was detected in eight isolates of which five were strong biofilm producer and three moderate biofilm producers. Conclusion: Biofilm production is an important virulence factor in Enterococcus isolates from vaginitis.

Description: Solar energy is going to be a major component of global energy generation. Loss due to dust deposition has raised a great concern to the investors in this field. Pre-estimation of this reduced generation and hence the economic loss will help the operators’ readiness for efficient and enhanced economic energy management of the system. In an earlier article, a physics–based model is proposed for assessment of dust accumulation under various climatic conditions which is validated by data of a single location. In this paper, the universality of this model is established and is used to demonstrate the effect of generation loss due to dust deposition and of cleaning. Variation in the soiling pattern due to climatic covariates has also been studied. Generation loss is calculated for Solar Photovoltaic power plants of different capacities at various locations in India. Finally this model has also been extended to predict the generation accounting for the soiling loss in Photovoltaic system. All the calculated and predicted results are validated with the measured values of the above plants.

Description: Water resources are under growing pressures globally, and better basin planning is crucial to alleviate current and future water scarcity issues. Communicating the complex interconnections and needs of natural and human systems is a significant research challenge. With advances in cyberinfrastructure allowing for new innovative approaches to basin planning, this same technology can also facilitate better stakeholder engagement. The potential benefits of using digital basin planning platforms for stakeholder engagement are immense; yet, there is limited guidance on how to best use these platforms for more effective stakeholder engagement in water-related issues and projects. We detail our digital platform, Basin Futures, and highlight the potential uses for stakeholder engagement through an integrative framework across different assessment levels. Basin Futures is a web application that is an entry-level modelling tool that aims to support rapid and exploratory basin planning globally. As a cloud-based tool, it brings together high-performance computing and large-scale global datasets to make data analysis accessible and efficient. We explore the potential use of the tool through three case studies exploring agricultural development, transboundary water-sharing agreements and allocating water for environmental flows.

Description: Cheatgrass (Bromus Tectorum) is a highly invasive species in the Great Basin of the Western USA that is increasing the frequency and intensity of wildland fires. Though cheatgrass plays a significant role in the fire ecology of the Great Basin, very little is known about its combustion emissions. The fresh smoke from 16 open laboratory burns of cheatgrass was analyzed using real-time measurements and filter analysis. We presented measured intensive optical properties of the emitted smoke, including absorption Ångström exponent (AAE), scattering Ångström exponent (SAE), single scattering albedo (SSA), and other combustion properties, such as modified combustion efficiency (MCE) and fuel-based emission factors (EFs). In addition, we gave a detailed chemical analysis of polar organic species in cheatgrass combustion emissions. We presented EFs that showed a large variation between fuels and demonstrated that analysis of combustion emissions for specific fuels was important for studying and modeling the chemistry of biomass-burning emissions.

Description: The plant–microbe–soil nexus is critical in maintaining biogeochemical balance of the biosphere. However, soil loss and land degradation are occurring at alarmingly high rates, with soil loss exceeding soil formation rates. This necessitates evaluating marginal soils for their capacity to support and sustain plant growth. In a greenhouse study, we evaluated the capacity of marginal incipient basaltic parent material to support native plant growth and the associated variation in soil microbial community dynamics. Three plant species, native to the Southwestern Arizona-Sonora region, were tested with three soil treatments, including basaltic parent material, parent material amended with 20% compost, and potting soil. The parent material with and without compost supported 15%, 40%, and 70% germination of Common Bean (Phaseolus vulgaris L. ‘Tarahumara Norteño’), Mesquite (Prosopis pubescens Benth), and Panic Grass (Panicum Sonorum Beal), respectively, though germination was lower than in the potting soil. Plant growth was also sustained over the 30 day period, with plants in parent material (with and without amendment) reaching 50% height compared to those in the potting soil. A 16S rRNA gene amplicon sequencing approach showed Proteobacteria to be the most abundant phyla in both parent material and potting soil, followed by Actinobacteria. The potting soil showed Gammaproteobacteria (19.6%) to be the second most abundant class, but its abundance was reduced in the soil + plants treatment (5.6%–9.6%). Within the basalt soil type, Alphaproteobacteria (42.7%) and Actinobacteria (16.3%) had a higher abundance in the evaluated bean plant species. Microbial community composition had strong correlations with soil characteristics, but not plant attributes within a given soil material. Predictive functional potential capacity of the communities revealed chemoheterotrophy as the most abundant metabolism within the parent material, while photoheterotrophy and anoxygenic photoautotrophy were prevalent in the potting soil. These results show that marginal incipient basaltic soil, both with and without compost amendments, can support native plant species growth, and non-linear associations may exist between plant–marginal soil–microbial interactions.

Description: Visible Light Communication (VLC) is a promising field in optical wireless communications, which uses the illumination infrastructure for data transmission. The important features of VLC are electromagnetic interference-free, license-free, etc. Additionally, Multiple-Input-Multiple-Output (MIMO) techniques are enabled in the VLC for enhancing the limited modulation bandwidth by its spectral efficiency. The data transmission through the MIMO-VLC system is corrupted by different interferences, namely thermal noise, shot noise and phase noise, which are caused by the traditional fluorescent light. In this paper, an effective precoding technique, namely Block Bi-Diagonalization (BBD), is enabled to mitigate the interference occurring in the indoor MIMO-VLC communications. Besides, a Quadrature Amplitude Modulation (QAM) is used to modulate the signal before transmission. Here, the indoor MIMO-VLC system is developed to analyze the communication performance under noise constraints. The performance of the proposed system is analyzed in terms of Bit Error Rate (BER) and throughput. Furthermore, the performances are compared with three different existing methods such as OAP, FBM and NRZ-OOK-LOS. The BER value of the proposed system of scenario 1 is 0.0501 at 10 dB, which is less than that of the FBM technique.

Description: Deep learning methods have been very effective for a variety of medical diagnostic tasks and have even outperformed human experts on some of those. However, the black-box nature of the algorithms has restricted their clinical use. Recent explainability studies aim to show the features that influence the decision of a model the most. The majority of literature reviews of this area have focused on taxonomy, ethics, and the need for explanations. A review of the current applications of explainable deep learning for different medical imaging tasks is presented here. The various approaches, challenges for clinical deployment, and the areas requiring further research are discussed here from a practical standpoint of a deep learning researcher designing a system for the clinical end-users.

Description: Evidences from more than three decades of work support the function of non-duplex DNA structures called G-quadruplex (G4) in important processes like transcription and replication. In addition, G4 structures have been studied in connection with DNA base modifications and chromatin/nucleosome arrangements. Recent work, interestingly, shows promise of G4 structures, through interaction with G4 structure-interacting proteins, in epigenetics—in both DNA and histone modification. Epigenetic changes are found to be intricately associated with initiation as well as progression of cancer. Multiple oncogenes have been reported to harbor the G4 structure at regulatory regions. In this context, G4 structure-binding ligands attain significance as molecules with potential to modify the epigenetic state of chromatin. Here, using examples from recent studies we discuss the emerging role of G4 structures in epigenetic modifications and, therefore, the promise of G4 structure-binding ligands in epigenetic therapy.

Description: Evolving over millions of years, hair-like natural flow sensors called cilia, which are found in fish, crickets, spiders, and inner ear cochlea, have achieved high resolution and sensitivity in flow sensing. In the pursuit of achieving such exceptional flow sensing performance in artificial sensors, researchers in the past have attempted to mimic the material, morphological, and functional properties of biological cilia sensors, to develop MEMS-based artificial cilia flow sensors. However, the fabrication of bio-inspired artificial cilia sensors involves complex and cumbersome micromachining techniques that lay constraints on the choice of materials, and prolongs the time taken to research, design, and fabricate new and novel designs, subsequently increasing the time-to-market. In this work, we establish a novel process flow for fabricating inexpensive, yet highly sensitive, cilia-inspired flow sensors. The artificial cilia flow sensor presented here, features a cilia-inspired high-aspect-ratio titanium pillar on an electrospun carbon nanofiber (CNF) sensing membrane. Tip displacement response calibration experiments conducted on the artificial cilia flow sensor demonstrated a lower detection threshold of 50 µm. Furthermore, flow calibration experiments conducted on the sensor revealed a steady-state airflow sensitivity of 6.16 mV/(m s−1) and an oscillatory flow sensitivity of 26 mV/(m s−1), with a lower detection threshold limit of 12.1 mm/s in the case of oscillatory flows. The flow sensing calibration experiments establish the feasibility of the proposed method for developing inexpensive, yet sensitive, flow sensors; which will be useful for applications involving precise flow monitoring in microfluidic devices, precise air/oxygen intake monitoring for hypoxic patients, and other biomedical devices tailored for intravenous drip/urine flow monitoring. In addition, this work also establishes the applicability of CNFs as novel sensing elements in MEMS devices and flexible sensors.

Description: We report the effectiveness of silver nanocluster (Ag-NC) against the biofilm of Pseudomonas aeruginosa (PA). Two DNA aptamers specific for PA and part of their sequences were chosen as templates for growing the Ag-NC. While circular dichroism (CD) studies determined the presence of secondary structures, UV/Vis absorption, and fluorescence spectroscopic studies confirmed the formation of the fluorescent Ag-NC on the DNA templates. Furthermore, mesoscopic physics-based partial wave spectroscopy (PWS) was used to analyze the backscattered light signal that can detect the degree of nanoscale mass density/refractive index fluctuations to identify the biofilm formation, comparatively among the different aptamers with respect to the control sample. The importance of the secondary structure of the aptamer DNA in targeting, successfully binding with the cells and delivering the Ag-NC, is evidenced by the decrease in disorder strength (Ld) of the Ag-NC treated samples compared to the untreated PA cells, which showed the abundance of higher Ld in the PWS studies. The higher Ld value attributed to the higher mass density fluctuations and the formation of biofilm. We envision this study to open a new avenue in using a powerful optical microscopic technique like PWS in detection, and DNA aptamer enclosed silver nanoclusters to prevent biofilms for opportunist pathogens like Pseudomonas aeruginosa.