ALBERT

Description: Collagenofibrotic glomerulopathy, a collagen type III kidney disease, is associated with proteinuria and accumulation ofcollagen type III in the glomerulus specifically the mesangium and/or capillary walls. The puromcyin aminonucleoside (PAN) nephropathy model was evaluated to examine the relation between COL3A1 mRNA and proteinuria. In Wistar rats administered PAN, a robust increase in proteinuria was accompanied by glomerular hypertrophy and expansion of both the Bowman’s capsule and Bowman’s space. An ~4-fold increase in renal COL3A1 mRNA was observed in the PAN cohort with urine protein exhibiting a direct (r = 0.8) and significant correlation with kidney COL3A1 mRNA level. Both Picrosirius red polarized microscopy and immunohistochemical analysis showed localization of collagen type III to the glomerular mesangium. Gene ontology-driven transcriptomic analysis reveals a robust COL3A1 network in the glomerular compartment.

Description: In recent times, with the globalization of markets, shrinking of land and climate change, food basket diversification, increase in demand for nutrient-rich food, the protected cultivation of high-value crops (HVCs) have assumed a pivotal role in augmenting higher crop productivity and profitability and enhancing nutritional security of the growing population. In this context, a study was undertaken to analyze the impact of protected cultivation in horticultural crops in the districts of Almora and Dehradun in the Uttarakhand state. It was mainly based on primary data obtained through a primary survey and focus group discussion with the 96 farmers practicing protected cultivation by using a well-structured and pre-tested questionnaire. In economic analysis, the project analysis tools were used to assess the feasibility of the protected cultivation. The study clearly demonstrated that the cultivation of vegetables and flowers under protected cultivation is a highly profitable enterprise. However, the findings of the study indicated that the subsidy scheme needs to be continued to encourage maximum farmers to adopt protected cultivation and farmers need to be encouraged to form farmers producers organizations (FPOs), which would help them in seeking better quality of inputs and enhancing negotiating power in the market to realize maximum returns for their farm produce.

Description: The main aim of this study is to document important ethnomedicinal plants from the Maraog region, located in the district of Shimla in Himachal Pradesh, India. A total of 110 medicinal plant species belonging to 102 genera and 57 families were reported from the study site. All of the species were collected from wild habitats. The rural people of the Maraog region were surveyed through interview methods, group discussions, and participatory observations. In the current study, data were collected from 88 informants through the snowball method. A total of 110 plant species were collected from the study area, including 64 herbs, 24 shrubs, 9 trees, 5 climbers, 3 grasses, and 5 ferns. Most of the plant species, reported from the study area, belong to the Rosaceae and Asteraceae families, each contributing 12 plant species, followed by the Lamiaceae family with 6 plant species. The most used part of the plant in the preparation of herbal medications is the leaves, which have been reported in 62 plants, followed by roots in 14 plants, and flowers and other aerial parts in 9 plants. The ethnomedicinal data were analyzed using “Use Value,” a statistical quantitative method, with Artemisia vestita having the highest use value (1.00), followed by Cannabis sativa (0.79), Rhododendron arboreum (0.79), and Datura stramonium (0.71). Older people were found to have a vast knowledge of wild medicinal plants, while the younger generation’s knowledge was lacking. As a result, traditional knowledge about the use of plants as a source of medicine has decreased day-by-day. Therefore, there is a need to document traditional ethnobotanical knowledge. The data could serve as a basis for research by pharmacological and nutraceutical industries for the development of novel drugs.

Description: This paper assessed the impact of soil and water conservation practices on farm productivity and risk exposure using data from 1204 plots in the semiarid tropics of India. A probit model was used to assess the determinants of adoption of soil bunds. We employed a moment-based approach for estimating crop revenue, its variability and downside risk exposure, i.e., crop failure. Furthermore, we also used a doubly robust method for assessing the impact of soil bunds on crop revenue, its variability and downside risk. Matching and propensity-based methods were also used to check robustness. The results show that training, access to credit and extension services are key determinants of adoption of soil bunds. Furthermore, the results also suggest that soil bunds not only improve the crop revenue but also reduce its variability. Most interestingly, we show that soil bunds also reduce the chances of downside risk, i.e., crop failure. Therefore, in view of increasing climate change and variability in the semiarid tropics, it can be suggested that soil bunds could be an important adaptation strategy for improving productivity and reducing risk exposure. This paper supports the investment in soil and water conservation technologies for sustaining the livelihood of resource-poor farmers of ecologically fragile regions such as the semiarid tropics.

Description: Penetration level of solar photovoltaic (PV) energy in the utility network is steadily increasing. This changes the fault level and causes protection problems. Furthermore, multi-tapped structure of distribution network deployed to integrate solar PV energy to the grid and supplying loads at the same time also raised the protection challenges. Hence, this manuscript is aimed at introducing an algorithm to identify and classify the faults incident on the network of utilities where penetration level of the solar PV energy is high. This fault recognition algorithm is implemented in four steps: (1) calculation of Stockwell transform-based fault index (STFI) (2) calculation of Wigner distribution function-based fault index (WDFI) (3) calculation of combined fault index (CFI) by multiplying STFI and WDFI (4) calculation of index for ground fault (IGF) used to recognize the involvement of ground in a fault event. The STFI has the merits that its performance is least affected by the noise associated with the current signals and it is effective in identification of the waveform distortions. The WDFI employs energy density of the current signals for estimation of the faults and takes care of the current magnitude. Hence, CFI has the merit that it considers the current magnitude as well as waveform distortion for recognition of the faults. The classification of faults is achieved using the number of faulty phases. An index for ground fault (IGF) based on currents of zero sequence is proposed to classify the two phase faults with and without the ground engagement. Investigated faults include phase to ground, two phases fault without involving ground, two phases fault involving ground and three phase fault. Fault recognition algorithm is tested for fault recognition with the presence of noise, various angles of fault incidence, different impedances involved during faulty event, hybrid lines consisting of overhead line (OHL) and underground cable (UGC) sections, and location of faults on all nodes of the test grid. Fault recognition algorithm is also tested to discriminate the transients due to switching operations of feeders, loads and capacitor banks from the faulty transients. Performance of the fault recognition algorithm is compared with the algorithms based on discrete wavelet transform (DWT), Stockwell transform (ST) and hybrid combination of alienation coefficient and Wigner distribution function (WDF). Effectiveness of the fault recognition algorithm is established using a detailed study on the IEEE-13 nodes test feeder modified to incorporate solar PV plant of capacity 1 MW in MATLAB/Simulink. Algorithm is also validated on practical utility grid of Rajasthan State of India.

Description: A wind measurement campaign using a single scanning light detection and ranging (LiDAR) device was conducted at the Hazaki Oceanographical Research Station (HORS) on the Hazaki coast of Japan to evaluate the performance of the device for coastal wind measurements. The scanning LiDAR was deployed on the landward end of the HORS pier. We compared the wind speed and direction data recorded by the scanning LiDAR to the observations obtained from a vertical profiling LiDAR installed at the opposite end of the pier, 400 m from the scanning LiDAR. The best practice for offshore wind measurements using a single scanning LiDAR was evaluated by comparing results from a total of nine experiments using several different scanning settings. A two-parameter velocity volume processing (VVP) method was employed to retrieve the horizontal wind speed and direction from the radial wind speed. Our experiment showed that, at the current offshore site with a negligibly small vertical wind speed component, the accuracy of the scanning LiDAR wind speeds and directions was sensitive to the azimuth angle setting, but not to the elevation angle setting. In addition to the validations for the 10-minute mean wind speeds and directions, the application of LiDARs for the measurement of the turbulence intensity (TI) was also discussed by comparing the results with observations obtained from a sonic anemometer, mounted at the seaward end of the HORS pier, 400 m from the scanning LiDAR. The standard deviation obtained from the scanning LiDAR measurement showed a greater fluctuation than that obtained from the sonic anemometer measurement. However, the difference between the scanning LiDAR and sonic measurements appeared to be within an acceptable range for the wind turbine design. We discuss the variations in data availability and accuracy based on an analysis of the carrier-to-noise ratio (CNR) distribution and the goodness of fit for curve fitting via the VVP method.

Description: LiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models.

Description: Despite the tremendous efforts exhibited by various utilities around the world during the past few years, there are still exceedingly many remote regions unreached by the electrical grid. For those regions, the enormous available potential of renewable energy resources is believed to be useful for the development of a stand-alone power supply system. This paper presents the modeling of a stand-alone hybrid system for the remote area of Ethiopia. A comparison of the economic performance of various scenarios of a stand-alone photovoltaic (PV)-wind hybrid system, with battery storage and diesel as a backup for electrifying remote rural areas, is presented. Therefore, a practical example, Kutur village of Awlio kebele of the Axum district, Ethiopia (which is 30 km away from the closest national grid) is considered for this research. Two electric load scenarios are estimated by considering the set of incandescent and efficient lamps for lighting for the 120 existing households. The above-mentioned solar radiation and wind speed are then used as an input to simulate the hybrid set-up for the high and low load estimation using HOMER software. The simulation result shows that the net present costs (NPC) corresponding to the high and low load scenarios is $262,470 and $180,731, respectively. Besides, an essential load forecasting is performed to see the effect of the increase in electric demand of the community on the required investment to install a stand-alone hybrid set-up. The NPC after load forecasting is found to be more than three folds of the NPC required for the reference year. In both cases, the simulation results indicate that using a stand-alone PV-wind hybrid system with battery storage and a diesel generator as a backup for electrifying Kutur village is cost-effective and comparable against the cost required for electrifying the village by extending the grid.

Description: Penetration level of renewable energy (RE) in the utility grid is continuously increasing to minimize the environmental concerns, risk of energy security, and depletion of fossil fuels. The uncertain nature and availability of RE power for a short duration have created problems related to the protection, grid security, power reliability, and power quality. Further, integration of RE sources near the load centers has also pronounced the protection issues, such as false tripping, delayed tripping, etc. Hence, this paper introduces a hybrid grid protection scheme (HGPS) for the protection of the grid with RE integration. This combines the merits of the Stockwell Transform, Hilbert Transform, and Alienation Coefficient to improve performance of the protection scheme. The Stockwell Transform-based Median and Summation Index (SMSI) utilizing current signals, Hilbert Transform-based derivative index (HDI) utilizing voltage signals, and Alienation Coefficient index (ACI) utilizing voltage signals were used to compute a proposed Stockwell Transform-, Hilbert Transform-, and Alienation-based fault index (SAHFI). This SAHFI was used to recognize the fault conditions. The fault conditions were categorized using the number of faulty phases and the proposed Stockwell Transform and Hilbert Transform-based ground fault index (SHGFI) utilizing zero sequence currents. The fault conditions, such as phase and ground (PGF), any two phases (TPF), any two phases and ground (TPGF), all three phases (ATPF), and all three phases and ground (ATPGF), were recognized effectively, using the proposed SAHFI. The proposed method has the following merits: performance is least affected by the noise, it is effective in recognizing fault conditions in minimum time, and it is also effective in recognizing the fault conditions in different scenarios of the grid. Performance of the proposed approach was found to be superior compared to the discrete wavelet transform (DWT)-based method reported in the literature. The study was performed using the hybrid grid test system realized by integrating wind and solar photovoltaic (PV) plants to the IEEE-13 nodes network in MATLAB software.