The Himalayan region is prone to landslides. Rainfall-induced slope failure activities in the Indian Himalaya cause considerable damage, posing a serious risk to life and property. This study ...attributes information regarding landslide triggering parameters to further delineate landslide susceptibility maps of Himachal Pradesh in the Himalayan region. The landslide inventory map was created using information from field visits, Linear Imaging Self-Scanning Sensor (LISS III), and Google Earth. Thereafter, eight landslide causative factors, viz. slope, aspect, curvature, elevation, Landuse Landcover (LULC), soil, lithology, and drainage density were performed by employing the weight of evidence (WOE), information value method (IVM) and the frequency ratio (FR) methods. Using the ArcGIS reclassification tool, the final landslide susceptibility zonation (LSZ) maps were categorized into five susceptibility zones: “very low, low, medium, high, and very high.” The success rate for WOE, FR, and IVM models was determined as 76.27%, 78.20%, and 76.09% respectively, depicting that the FR model based LSZ map is more accurate. According to the FR model based LSZ map, the highly susceptible classes in the case of aspect, curvature, and lithology are southeast, concave, and TBS, respectively. The sparsely vegetated areas are more prone to landslides than the other LULC areas. The higher elevations, ranging from 1191 to 1434, 1434–1655, and 1655–1876 m, are more vulnerable to landslide activities as compared to low elevations. The slope classes 30–45 and 45–60, medium drainage density class and fine loamy class of soils are more likely to landslides. The prepared susceptibility zone map can be used for future mitigation planning in the high and very high susceptibility zones in order to reduce landslide-related human and economic losses.
Sleep apnea is a prevalent sleep disorder characterized by frequent interruptions in breathing during sleep, leading to decreased levels of blood oxygen. This research introduces an energy-efficient ...digital hardware system built on an Artix 7 FPGA, explicitly designed for real-time sleep apnea detection. Our approach involves the classification of subject-specific sleep apnea and non-apnea events. We utilize inter-band energy ratio features extracted from multi-band Electroencephalogram (EEG) signals and employ a Linear Support Vector Machine (LSVM) classifier for this task. The features extracted-namely energy, kurtosis, and mobility-from five sub-bands demonstrate improved accuracy, sensitivity, and specificity compared to existing studies. The proposed model is evaluated using EEG signals from the openly accessible St. Vincent's sleep apnea UCDDB database. Our system achieves remarkable performance metrics, attaining the highest accuracy of 94.81%, a sensitivity of 93.10%, and a specificity of 96.43%. It accomplishes all this while maintaining minimal dynamic power consumption (19mW) and using minimal FPGA resources. This hardware system can be integrated into a System-on-a-Chip (SoC) platform, serving as a crucial component of a smart, wearable, automated sleep apnea detection device for real-time critical health diagnosis and screening.
Background
Unfavorable climatic changes have led to an increased threat of several biotic and abiotic stresses over the past few years. Looking at the massive damage caused by these stresses, we ...undertook a study to develop high yielding climate-resilient rice, using genes conferring resistance against blast (
Pi9
), bacterial leaf blight (BLB) (
Xa4, xa5, xa13, Xa21
), brown planthopper (BPH) (
Bph3, Bph17
), gall midge (GM) (
Gm4, Gm8
) and QTLs for drought tolerance (
qDTY
1.1
and
qDTY
3.1
) through marker-assisted forward breeding (MAFB) approach.
Result
Seven introgression lines (ILs) possessing a combination of seven to ten genes/QTLs for different biotic and abiotic stresses have been developed using marker-assisted selection (MAS) breeding method in the background of Swarna with drought QTLs. These ILs were superior to the respective recurrent parent in agronomic performance and also possess preferred grain quality with intermediate to high amylose content (AC) (23–26%). Out of these, three ILs viz., IL1 (
Pi9
+
Xa4
+
xa5
+
Xa21
+
Bph17
+
Gm8
+
qDTY
1.1
+
qDTY
3.1
), IL6 (
Pi9
+
Xa4
+
xa5
+
Xa21
+
Bph3
+
Bph17
+
Gm4
+
Gm8+ qDTY
1.1
+
qDTY
3.1
) and IL7 (
Pi9+ Xa4
+
xa5
+
Bph3
+
Gm4
+
qDTY
1.1
+
qDTY
3.1
) had shown resistance\tolerance for multiple biotic and abiotic stresses both in the field and glasshouse conditions. Overall, the ILs were high yielding under various stresses and importantly they also performed well in non-stress conditions without any yield penalty.
Conclusion
The current study clearly illustrated the success of MAS in combining tolerance to multiple biotic and abiotic stresses while maintaining higher yield potential and preferred grain quality. Developed ILs with seven to ten genes in the current study showed superiority to recurrent parent Swarna+drought for multiple-biotic stresses (blast, BLB, BPH and GM) together with yield advantages of 1.0 t ha
− 1
under drought condition, without adverse effect on grain quality traits under non-stress.
A large quantity of water is required during the conventional curing methods. This becomes challenging in the areas facing water scarcity and for concreting work in high-rise structures. This work ...presents a solution for the need for concrete that does not require extra water for curing. In the proposed solution, calcium lignosulfonate in different percentages was introduced as a self-curing agent in fresh concrete. The hardened concrete with calcium lignosulfonate was cured at ambient conditions, whereas the hardened concrete without calcium lignosulfonate was submerged in water for curing. The properties of fresh and hardened concrete with and without calcium lignosulfonate are compared. The results show a continuous increase in the slump with the increase in calcium lignosulfonate. However, 0.3% calcium lignosulfonate is identified as the optimum percentage for the desired mechanical property. The durability under a saline environment is studied in terms of loss in strength. Further, the change in strength is correlated with the mineralogical changes studied using X-ray diffraction results.
Epilepsy is a serious neurological disorder that results in seizures. It can be diagnosed by analyzing the brain's electrical activity using an electroencephalogram (EEG). However, the detection of ...seizures from massive EEG datasets is a challenging task. To address this challenge, researchers have developed several machine‐learning classifiers and feature extraction techniques for detecting seizures. This paper proposes an energy‐efficient and fast field programmable gate array (FPGA) architecture for detecting epileptic seizures using minimal computational resources. The seizure detection system uses the one Hjorth parameter (mobility) and another statistical parameter (nonlinear energy) as features and employs two efficient classifiers, quadratic discriminant analysis and linear support vector machine (LSVM), for classifying signals into seizure and nonseizure categories. The feature extractor block is connected individually to each of these classifiers. Subsequently, the performance of these two proposed models is evaluated in terms of accuracy, sensitivity, power consumption, resource utilization, and other metrics. The results demonstrate that the SVM classifier‐based model achieved the highest accuracy (99.4%) and sensitivity (98.8%) while consuming minimal dynamic power (0.057 mW) and utilizing the minimum FPGA resources. Thus, the proposed hardware system offers a reliable and energy‐efficient solution for detecting seizures in clinical and real‐time applications.
This paper proposes an energy‐efficient and fast Field programmable gate array (FPGA) architecture for detecting epileptic seizures using minimal computational resources. The results showed that the SVM classifier‐based model achieved the highest accuracy (99.4%) and sensitivity (98.8%) while consuming minimal dynamic power (0.057 mW) and utilizing the minimum FPGA resources.
This research study aims to understand the application of Artificial Neural Networks (ANNs) to forecast the Self-Compacting Recycled Coarse Aggregate Concrete (SCRCAC) compressive strength. From ...different literature, 602 available data sets from SCRCAC mix designs are collected, and the data are rearranged, reconstructed, trained and tested for the ANN model development. The models were established using seven input variables: the mass of cementitious content, water, natural coarse aggregate content, natural fine aggregate content, recycled coarse aggregate content, chemical admixture and mineral admixture used in the SCRCAC mix designs. Two normalization techniques are used for data normalization to visualize the data distribution. For each normalization technique, three transfer functions are used for modelling. In total, six different types of models were run in MATLAB and used to estimate the 28th day SCRCAC compressive strength. Normalization technique 2 performs better than 1 and TANSING is the best transfer function. The best k-fold cross-validation fold is k = 7. The coefficient of determination for predicted and actual compressive strength is 0.78 for training and 0.86 for testing. The impact of the number of neurons and layers on the model was performed. Inputs from standards are used to forecast the 28th day compressive strength. Apart from ANN, Machine Learning (ML) techniques like random forest, extra trees, extreme boosting and light gradient boosting techniques are adopted to predict the 28th day compressive strength of SCRCAC. Compared to ML, ANN prediction shows better results in terms of sensitive analysis. The study also extended to determine 28th day compressive strength from experimental work and compared it with 28th day compressive strength from ANN best model. Standard and ANN mix designs have similar fresh and hardened properties. The average compressive strength from ANN model and experimental results are 39.067 and 38.36 MPa, respectively with correlation coefficient is 1. It appears that ANN can validly predict the compressive strength of concrete.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The rate of municipal solid waste (MSW) generation in developing countries is continuously growing in proportion to the gross national product. Landfilling, incineration, composting, and waste to ...energy (WtE) have a brief history as management strategies for MSW in India. Economic evaluation via cost benefit analysis (CBA) of MSW is establishing the most appropriate treatment/disposal strategy and it is often a major concern for solid waste management (SWM) policymakers. Thus, this study aims to analyze the municipal solid waste management (MSWM) activities in India’s capital, Delhi, and the CBA of MSWM systems to identify the major problems and limitations involved. Sixty-sixsamples totaling 6,600 kg were collected and analyzed at random from various locations, including the sources of generation, composting plants, and disposal sites. Storage, collection, transportation, and recycling information were gathered from departments such as Municipal Corporation of Delhi (MCD), New Delhi Municipal Corporation (NDMC), Central Pollution Control Board (CPCB), and self-surveys. The total costs of each MSW option were calculated for cost analysis. The results revealed a high organic moisture content, indicating the possibility of composting and bio-methanation, except for waste from commercial, institutional area and restaurants that can be used to develop Refuse Derived Fuel (RDF). It was also revealed that only about 80% of the garbage generated in Delhi is collected. In terms of treatment and disposal, the MCD has proposed additional facilities such as disposal through sanitary landfills with linings, as well as a system for leachate collection and disposal. Furthermore, construction and demolition waste are used in the construction of various pavement components, such as base coarse, surface coarse, and so on. The total social value added by garbage trade operations in Delhi is expected to be INR 358.7 crores (approximately 46.60 million USD) between 2017 and 2020. Recycling saves the municipal budget about INR 17.6 crores (approximately 2.3 million USD per year).
Cosmetic industries are highly committed to finding natural sources of functional active constituents preferable to safer materials to meet consumers' demands. Marine macroalgae have diversified ...bioactive constituents and possess potential benefits in beauty care products. Hence, the present study was carried out to characterize the biochemical profile of marine macroalga
by using different techniques for revealing its cosmetic potentials. In results, the FTIR study characterized the presence of different bioactive functional groups that are responsible for many skin-beneficial compounds whereas six and fifteen different important phycocompounds were found in GCMS analysis of ethanolic and methanolic extracts, respectively. In the saccharide profile of
, a total of eight different carbohydrate derivatives were determined by the HRLCMS Q-TOF technique, which showed wide varieties of cosmetic interest. In ICP AES analysis, Si was found to be highest whereas Cu was found to be lowest among other elements. A total of twenty-one amino acids were measured by the HRLCMS-QTOF technique, which revealed the highest amount of the amino acid, Aspartic acid (1207.45 nmol/mL) and tyrosine (106.77 nmol/mL) was found to be the lowest in amount among other amino acids. Their cosmetic potentials have been studied based on previous research studies. The incorporation of seaweed-based bioactive components in cosmetics has been extensively growing due to its skin health-promoting effects.
Rice blast and bacterial leaf blight, are major disease, significantly threatens rice yield in all rice growing regions under favorable conditions and identification of resistance genes and their ...superior haplotypes is a potential strategy for effectively managing and controlling this devastating disease. In this study, we conducted a genome-wide association study (GWAS) using a diverse set of 147 rice accessions for blast and bacterial blight diseases in replications. Results revealed 23 (9 for blast and 14 for BLB) significant marker-trait associations (MTAs) that corresponded to 107 and 210 candidate genes for blast and BLB, respectively. The
analysis of the candidate genes led to the identification of eight superior haplotypes for blast, with an average SES score ranging from 0.00 to 1.33, and five superior haplotypes for BLB, with scores ranging from 1.52cm to 4.86cm superior haplotypes. Among these, superior haplotypes
and
were identified with the lowest average blast scores of 0.00-0.67, and superior haplotype
exhibited the lowest average lesion length (1.88 - 2.06cm) for BLB. A total of ten accessions for blast and eight accessions for BLB were identified carrying superior haplotypes were identified. These haplotypes belong to aus and indx subpopulations of five countries (Bangladesh, Brazil, India, Myanmar, and Pakistan). For BLB resistance, eight accessions from six countries (Bangladesh, China, India, Myanmar, Pakistan, and Sri Lanka) and four subpopulations (aus, ind1A, ind2, and ind3) were identified carrying superior haplotypes. Interestingly, four candidate genes,
, and
encoding transposon and retrotransposon proteins were among those with superior haplotypes known to play a crucial role in plant defense responses. These identified superior haplotypes have the potential to be combined into a single genetic background through haplotype-based breeding for a broader resistance spectrum against blast and bacterial blight diseases.
The elite Indian rice variety, Naveen is highly susceptible to major biotic and abiotic stresses such as blast, bacterial blight (BB), gall midge (GM) and drought which limit its productivity in ...rainfed areas. In the present study, a combined approach of marker-assisted forward (MAFB) and back cross (MABC) breeding was followed to introgress three major genes, viz., Pi9 for blast, Xa21 for bacterial blight (BB), and Gm8 for gall midge (GM) and three major QTLs, viz., qDTY.sub.1.1, qDTY.sub.2.2 and qDTY.sub.4.1 conferring increased yield under drought in the background of Naveen. At each stage of advancement, gene-based/linked markers were used for the foreground selection of biotic and abiotic stress tolerant genes/QTLs. Intensive phenotype-based selections were performed in the field for identification of lines with high level of resistance against blast, BB, GM and drought tolerance without yield penalty under non-stress situation. A set of 8 MAFB lines and 12 MABC lines with 3 to 6 genes/QTLs and possessing resistance/tolerance against biotic stresses and reproductive stage drought stress with better yield performance compared to Naveen were developed. Lines developed through combined MAFB and MABC performed better than lines developed only through MAFB. This study exemplifies the utility of the combined approach of marker-assisted forward and backcrosses breeding for targeted improvement of multiple biotic and abiotic stress resistance in the background of popular mega varieties.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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