 Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
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- Prediction of Parent Data of Silkworm Breeding Based on Artificial Neural
Network-
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Abstract: Abstract A conventional breeding program typically deploys hundreds of crosses each year. However, only 1 or 2 percent of the combinations finally produce the desired variety. A large number of combinations are eliminated in the selection process of different breeding generations, breeding still depends largely on phenotypic selection and the experience of the breeder. The problems in traditional breeding, such as long cycles, low efficiency and poor foresight, have not been fundamentally solved. With the development of information technology and artificial intelligence, breeding with the help of modern technology has become a trend. The purpose of this study is to overcome the blindness of hybrid combinations by using computer artificial intelligence technology and establishing a simulated environment for silkworm breeding to help silkworm breeders. Based on backpropagation neural network, with the silkworm cocoon productivity as the breeding goal, the breeding model was established, the quantitative traits of more than 100 varieties were taken as samples to train the model, and the breeding simulation was carried out on this basis. By optimizing parental selection, and predicting parental selection, a hybridization test was carried out. The results showed that the difference between the predicted and tested values was 10.09% on average.
PubDate: 2023-03-21
- Optimization of the Formulation and Preparation of Andrographolide
Microemulsion by Box–Behnken Response Surface Methodology-
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Abstract: Abstract Andrographis paniculata is a bitter herb used in Asian countries to treat inflammation. Andrographolide (AG) is a diterpenoid compound extracted from Andrographolide paniculata. It is the main active component of Andrographolide paniculata. However, due to its low solubility in water, its biological use is extremely low and it is not easily absorbed during cervical recovery, greatly limiting its application in edible beverages. In this study, emulsifiers and co-emulsifiers were used to miniaturize the andrographolide extracted solution and the process system was optimized by response surface methodology. The AG oil solution was a light yellow transparent liquid; the HLB value was 12.2, which met the requirements of self-emulsification to form O/W micro-emulsion after emulsification. The stability of the optimized AG oil solution showed that the appearance of the solution was light yellow, clear and transparent, and unchanged, and the drug content remained stable at normal temperature and natural conditions for 0, 1, 3 and 6 months.
PubDate: 2023-03-01
- Biology of Rose Beetle (Adoretus versutus) from Terai Foothills of Kumaon
Region in India-
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Abstract: Abstract Adoretus versutus (Harold) is a major species of white grub distributed across the Indian subcontinent. This work was conducted to study the life cycle of A. versutus in Terai foothills of Kumaon region. Laboratory research directed toward its different life stages was carried out by collecting its adults by installing light traps during their adult emergence. The experimental findings on its life cycle revealed that A. versutus completes its life cycle in an average time span of 245 days. It comprises of various stages viz: eggs—8 days, first instar—23 days, second instar—34 days, third instar—145 days, pupal period—10 days and adult stage—25 days. This study gives the significant information on the life stages of A. versutus which can be a foundational work to plan the effective management techniques in future cases of any outbreak.
PubDate: 2023-02-24
- A New Random Forest and Support Vector Machine-based Intrusion Detection
Model in Networks-
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Abstract: Abstract There exist many intrusion detection systems (IDSs) to provide privacy and security to user data in networks. However, these models are prone to generate high false alarms due to large amounts of noisy data and large feature dimensions. This work aims to achieve a robust IDS by using a hybrid classification model consisting of random forest (RF) and support vector machine (SVM), called RF-SVM. Here, a novel feature optimization technique based on RF has been proposed to optimize the original feature space. Later, SVM is used over the optimized feature space for classification. To test the performance of the proposed model, both scenarios: (i) Anomaly detection and (ii) Signature detection, have been considered. For anomaly detection, binary SVM is used, where the data contain two classes: (i) Normal and (ii) Attack types, whereas, for attack signature detection, multi-class SVM is used to detect each attack type. Simulation results on four standard data sets: (i) NSL-KDD, (ii) ISCX-URL2016, (iii) CICDarknet2020 and (iv) CICDoHBrw2020 demonstrate that the proposed model shows better accuracy and false alarm rate (FAR) compared to other state-of-the-art models.
PubDate: 2023-02-21
- In silico identification and comparative analysis of β-carotene protein
in mango (Mangifera indica L.)-
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Abstract: Abstract Mango is a healthfully rich natural product crop. This study inspected 29 sequences of β-carotene protein and one UniProt sequence of the Anacardiaceae family. Phylogenetic analysis showed that the β-carotene protein sequences might have different evolutionary patterns in Mangifera indica. A total of 17 motifs and 40 conserved domains among the test accessions were recognized. In silico identification of β-carotene protein and its comparative analysis may provide a basis for studying evolutionary relationships in future analyses with the aim of helping new enthusiastic young protein researchers or horticulturists as this is the first-ever detailed study of its kind among the Anacardiaceae family.
PubDate: 2023-02-19
- Impact of ICT-Enabled Teaching–Learning Processes in Physical Sciences
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Abstract: Abstract The COVID-19 (coronavirus disease) pandemic has caused a lot of damage to the social, economic and educational infrastructure of the world. The rapid change in the online learning environment calls for the development of effective learning strategies to support student learning. Principally information communication technology (ICT) emerged as a new hope in teaching–learning in streams like science and technology. Especially in the teaching-learning of a challenging subject like physics and its various streams, e.g. mechanics, wave, optics, etc., the use of ICT has increased exponentially due to its unique properties. However, some of its side effects have also been visible during this period. This study presents the feedback, experiences and recommendations of physics teachers regarding the application of ICT in the teaching–learning of physics. This article offers a comprehensive view of the impact of information and communication technology-enabled teaching–learning processes in physical sciences. To accomplish this study, an 18-question questionnaire was circulated among physics teachers across the nation and more than 100 physics teachers participated and recorded their responses. The outcomes of these responses were analysed, and corresponding conclusions with recommendations are presented. This study may be helpful for students, teachers, researchers and policymakers working in this field of ICT-enabled physics education.
PubDate: 2023-02-17
- A Bio-Inspired Technique for the Maximum Weighted Clique Problem
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Abstract: Abstract This paper discusses the particle swarm optimization-based approach, PSVC, for the maximum weighted clique problem (MWCP). This PSVC uses the swarm optimization technique with cost ratio parameter to construct the feasible solution for MWCP. This swarm technique is further tuned with two new local search procedures constructed with vertex tuning parameters that refine the feasible solution into the best optimal solution. The obtained results have been compared with the recently developed methods and statistical analysis made to show the effectiveness of the PSVC. These analyses indicate that the proposed PSVC is the best alternate approach for solving such NP-hard problems.
PubDate: 2023-02-16
- Accurate Dissolved Oxygen Prediction for Aquaculture Using Stacked
Ensemble Machine Learning Model-
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Abstract: Abstract Dissolved oxygen (DO) is the most vital water quality parameter that directly indicates the survival of aquatic life. Therefore, accurate DO prediction is essential for aquaculture water quality management for sustainable and profitable aquaculture production. Machine learning (ML) models have been successfully employed for water quality prediction. However, DO undergoes dynamic changes, which are nonlinear and complex, making accurate prediction of DO using conventional statistical methods and ML models a challenging task. To resolve this in this work, we propose a stacked ensemble ML model combining three different ML models as base learners and one ML model as a meta-learner to improve the DO prediction accuracy. The effectiveness of the stacked ensemble ML model has been evaluated using two different water quality datasets. The experimental results show that the stacked ensemble ML model achieves significant accuracy improvement compared with standalone ML models.
PubDate: 2023-02-11
- Trace Gas Pollutants Led to New Particle Formation and a Strong Convective
System Over Telangana, India-
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Abstract: Abstract New particle formation (NPF) is an important source of more than half of the atmosphere’s cloud condensation nuclei (CCN) and the transport of pollutants to the upper troposphere. We investigated a heavy rainfall event over Hyderabad, Telangana on 13 October 2020 using a combination of upper air sounding data and satellite images. A deep convective system developed on 13 October 2020 lifted the boundary layer pollutants such as carbon monoxide (CO) and nitrous oxide (N2O) to the upper troposphere evident from NASA’s TERRA satellite. The high concentrations of the trace gases (2.48–3.38 × 1018 mol cm−2 of CO and 269 ppbv of N2O) led to NPF at low temperatures and high relative humidity (> 80%) near the tropopause after surviving the deep convective updrafts. Under high concentration of gaseous pollutants and strong oxidation, large numbers of ultra-fine particles were generated by the NPF. These nucleation mode particles activated to form additional cloud droplets upon which condensation must have occurred. Further, in the absence of large particles, ultrafine particles acted as CCN and formed cloud droplets. Absorbing aerosols present above the clouds reversed the semi-direct effect and increased cloud cover resulting in heavy precipitation (283–322 mm) in less than 12 h (13 October 2020) over Hyderabad and its adjoining areas. This study suggests that remote sensing techniques can be used to study such unusual events that may not be possible with available infrastructure, especially when it occurs in inaccessible and remote areas.
PubDate: 2023-02-11
- Development of Ripening Gene-Specific Markers and their Association with
Shelf-Life in Mango (Mangifera indica L.) varieties-
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Abstract: Abstract Majority of the popular mango varieties have a very short shelf-life. Therefore, the present investigation was carried out to design functional markers and their association with shelf-life. A total of 35 shelf-life specific primers were designed using in silico mining of 95 ripening gene nucleotide sequences of Mangifera indica L. Of these specific primers, 27 showed polymorphism among the genotypes studied. Gene diversity (GD), average number of alleles per locus (An), polymorphism information content (PIC) and major allele frequency (Maf) observed were 0.38, 2.18, 0.30 and 0.68, respectively. Mango genotypes of varying shelf-life (long, medium and short) grouped separately into different clusters. Strong association of simple sequence repeats loci (SSRs) MSL-8 and MSLC-13 with physiological loss in weight (PLW) and titratable acidity was observed. Therefore, these ripening gene-specific SSRs loci could be used in marker-assisted breeding for fruit quality traits associated with shelf-life.
PubDate: 2023-02-08
- On Debris Reinforced-PVDF, Composite-Based 3D Printed Sensors for
Restoration of Heritage Building-
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Abstract: Abstract Some studies in the recent past have outlined the use of 3D-printed thermoplastic composite-based innovative strips with the capability of self-expansion and contraction as a snug fit-based solution for addressing crack propagation in heritage structures. But hitherto little has been reported on the use of debris-reinforced polyvinyl difluoride (PVDF) composite as a repair/maintenance solution for such heritage structures followed by health monitoring of repaired cracks as the Internet of things based solution in Industry Sports Medicine band with Bluetooth application. The debris-reinforced PVDF matrix composite has an inbuilt advantage of compatibility with heritage structures being collected from the same site and may be tuned as a sensor to ascertain crack propagation due to weathering effects, seismic movements, etc. In this study, three infill patterns available in commercial open-source software have been used as meta-structures namely: tri-hexagonal, triangle, and octet for the selected composition/proportion, and the mechanical, sensing, and morphological properties of the functional prototype were investigated. The results of the study outlined that the tri-hexagonal meta-structure has acceptable mechanical, piezoelectric, thermal, and sensing capabilities for the health monitoring of repaired cracks.
PubDate: 2023-02-06
- Ensemble of Time Series and Machine Learning Model for Forecasting
Volatility in Agricultural Prices-
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Abstract: Abstract Forecasting price volatility of agricultural commodities has immense importance nowadays. The use of traditional parametric model in capturing volatility in price series has been found to be inefficient. In this context, machine learning (ML) technique like support vector regression (SVR) may be applied to improve accuracy of forecasting. In the present investigation, an algorithm based on combination of parametric nonlinear time series model, i.e., generalized autoregressive conditional heteroscedastic (GARCH) model and supervised ML, e.g., SVR is proposed. The method is applied for forecasting volatility of onion price in two major markets of India, namely Delhi and Kolkata. The outperformance of the proposed algorithm in comparison to GARCH model has also been empirically established by means of Root Mean Square Error, Mean Absolute Error and R2 log.
PubDate: 2023-02-01
- Variations in Top Heat Loss Coefficient with Sky Temperature for a Flat
Plate Collector-
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Abstract: Abstract In the present work, the thermal loss coefficients for a single glazed flat plate collector located in Delhi have been estimated considering the impact of sky temperature. The range of variables considered in the present analysis is 333–423 K for absorber plate temperature, 10–20 W/m2K for wind heat transfer coefficient, 288–318 K for ambient temperature, and 30–70% for relative humidity. The study reveals that there are remarkable changes in the values of thermal loss coefficients when the effect of clear sky emissivity was undertaken as compared to conventional work. There was a total of 29–31% maximum variation and 24–26% minimum variation in the values of heat loss coefficient estimated for the temperature range of 308–318 K, whereas, for the winter season, for the temperature range of 208–298 K, the maximum variation in the values of thermal loss coefficients was estimated around 22–28% as compared to conventional work with a 21 to 26% minimum variation for summer conditions.
PubDate: 2022-12-12
DOI: 10.1007/s40009-022-01184-w
- Hepatitis C—Route of Asymptomatic to Symptomatic Switch in Raising
Hepatocarcinogenesis: Revisiting Nobel Prize 2020 in Physiology and
Medicine-
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Abstract: Abstract The Nobel committee has awarded Harvey J Alter, Michael Houghton and Charles M. Rice the Nobel Prize in Physiology and Medicine in 2020 for the discovery of HCV from contaminated blood. Hepatitis is a liver inflammatory disease caused by the Hepatitis B virus (HBV). Till date, HBV is known to cause liver inflammation through blood transfusion. However, a novel “non-A non-B hepatitis” (NANBH) has recently emerged responsible for liver inflammation, following the same route as HBV. At the beginning (after infection), the NANBH viral proteins gradually alter the function and pathways of normal hepatocyte cells in the liver to promote fibrosis to cirrhosis and eventually to hepatocellular carcinoma (HCC). This phenomenon is presented in the present communication. Hepatocarcinogenesis is attributed to asymptomatic infection by ss ( +) RNA virus, Hepatitis C of family Flaviviridae. Specific drugs that target HCV life cycle or patient immune response are in the process of development.
PubDate: 2022-12-10
DOI: 10.1007/s40009-022-01192-w
- Studies on Bioactive Compounds and Antioxidant Activity of Litchi (Litchi
Chinensis Sonn.) Fruit Cultivars Under Field Conditions-
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Abstract: Abstract Bioactive compounds and antioxidant activity in the fruit of ten litchi cultivars were estimated. The results showed significant variations in bioactive compounds and antioxidant activity among the litchi cultivars during three consecutive seasons from 2017 to 2019. Weather parameters affected the accumulation and quantification of ascorbic acid in pulp, total phenolics, and antioxidant activity in pulp and pericarp of litchi fruit. The highest content of ascorbic acid was recorded in cv. Early Bedana (48.29 mg/100 g), while cv. Late Large Red had the highest content of total phenolics (6.08 mg GAE/100 g) and antioxidant activity (8.15 Mol TE/g FW) among the cultivars studied. Higher temperature in the year 2019 was accompanied by about 29.14% higher pulp phenolics, and peel phenolics by 17.98%, compared to 2018 which recorded lower temperature during fruit growth and development. Environmental temperature impacted a significantly positive correlation (r > 0.99) with the quantity of bioactive compounds in litchi fruit, and vice versa.
PubDate: 2022-12-09
DOI: 10.1007/s40009-022-01180-0
- Can Pressmud Improve Nickel Availability in Lead Contaminated Soils '
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Abstract: Abstract Nickel (Ni) is an important micronutrient for crop growth and yield. Soil health parameters and nickel availability in soil may be affected by the lead contamination. In this regards, graded application of pressmud (PM) was applied, i.e. 0, 2.5, 5 and 10 g/kg on lead (Pb) contamination level (0, 100, 150, 300 mg/kg) and computed the PM interaction effect on Ni plant nutrient dynamics. PM levels 0 (control), 2.5, 5, and 10 g/kg were increased Ni shoot uptake by 11.168, 11.544, 14.679, and 18.296 µg/pot, respectively. However, on the other hand, the root uptake was 6.658, 26.545, and 26.590% higher than the control treatment in 2.5, 5 and 10 g/kg applied PM, respectively. The combined interaction mean of total Ni uptake was 17.866, 18.688, 22.456, 26.771 µg/pot in PM applied @ 0, 2.5, 5, 10 g/kg pot, respectively. This study is very much important to formulate a Ni immobilization strategies by adding PM in Pb contaminated soils.
PubDate: 2022-12-08
DOI: 10.1007/s40009-022-01160-4
- A Scientific Report on Infestation and Biology of Orange Drinker, Euthrix
laeta (Walker, 1855) (Lepidoptera: Lasiocampidae) on Shisham (Dalbergia
sissoo Roxb.) from Assam, India-
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Abstract: Abstract The infestation and biology of Orange Drinker, Euthrix laeta (Walker, 1855) (Lepidoptera: Lasiocampidae) on Shisham (Dalbergia sissoo Roxb.) were studied and reported from Assam, India, in this short communication. The female lays 13–17 spherical eggs in batches on the stem of the young seedlings with a total fecundity of 200–232 eggs per female. The final instar larvae were brownish to ash grey with distinct patterns and measured 6.7–9.5 cm in length. The pupa is 2.6 cm long, brown and held inside a white papery cocoon attached firmly to the stem. The pest completed four generations in a year. The E. laeta larva severely defoliates D. sissoo during the seedling stage in nurseries, causing the drying of seedlings. E. laeta larva caused 10–75.26% damage in D. sissoo plus trees. The D. sissoo plus trees ‘TST-1’ showed the highest per cent damage (75.26%) by E. laeta larva. The D. sissoo plus trees ‘TDT-2’ showed the minimum damage (10%) by E. laeta larva.
PubDate: 2022-12-08
DOI: 10.1007/s40009-022-01189-5
- On Meta-structure Inspired 3D Printing of Dual Alloys Using DMLS
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Abstract: Abstract Direct metal laser sintering (DMLS) is one of the established processes for the fabrication of implants/scaffolds of metallic alloys (like Ti–6Al–4V, 17–4 precipitate hardened (PH) stainless steel (SS), Ni, etc.). But hitherto little has been reported on dual alloys printing of Ti–6Al–4V and 17–4 PH SS, dissimilar metallic alloys selected based upon the difference in melting point (MP) for fabrication of meta-structure inspired functional prototypes. This paper reports the DMLS-based dual alloys printing by using two different meta-structures (dodecahedron, and octet of Ti–6Al–4V) as infill between Ti–6Al–4V and 17–4 PH SS sandwich structures. Results of the study suggest that octet-based meta-structure was better than dodecahedron (due to a smaller number of nodes) for successful printing of dual alloys with DMLS. The results are supported by scanning electron microscopy (SEM) based on grain size, surface texture, and porosity analysis.
PubDate: 2022-12-07
DOI: 10.1007/s40009-022-01181-z
- Assessment of Antioxidant Properties of Elaeagnus latifolia L.: An
Important Wild Edible Fruit Species of Western Himalaya-
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Abstract: Abstract Elaeagnus latifolia L. (family: Elaeagnaceae), is a wild-growing Himalayan shrub. Fresh berries of the species are consumed by mountainous populace as a food supplement, however as the biochemical attributes of the species is still lacking or limited. Therefore, the present study was focused to analyze polyphenolics-antioxidant properties of both fresh & dried berries in different solvents, collected from Chaudas valley of Pithoragarh district. Results showed a significant (p < 0.05) variation among investigated parameters in different solvents. As a result, fresh berries were found potent source of polyphenolics (phenolics 1.65; flavonoids 1.35; flavonols 1.21; tannins 1.49; proanthocyanidins 1.21 mg/g, respectively) and antioxidants (ABTS 2.55; DPPH 2.74; FRAP 2.25; OH· 1.16; NO·1.19 mM AAE/100 g), respectively, as compared with dried berries. The moderate polarity of solvents (ethanol, methanol) was found suitable for harnessing maximum potential of the species. Furthermore, results suggested that both fresh & dried fruit berries are natural sources of various health benefit compounds (polyphenolics, antioxidants and other bioactive constituents), and should be further utilize for preparation of nutritious food stuffs which will be beneficial for plummeting the malnutrition deficiency.
PubDate: 2022-12-07
DOI: 10.1007/s40009-022-01182-y
- A Paradigm Shift is Expected in Ethnobiology: Challenges and Opportunities
Post-COVID-19-
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Abstract: Abstract Documentation of the folk knowledge of indigenous communities forms an integral part of the subject “ethnobiology”. Pursuing leads obtained through ethnobiological documentation has played a key role in maintaining human health and wellbeing. The current pandemic that we are passing through is expected to strengthen the subject with many challenges and opportunities. In this paper, we highlight the avenues and the role of the subject in the times to come. We strongly believe a paradigm shift in ethnobiology is lurking around the corner.
PubDate: 2022-12-07
DOI: 10.1007/s40009-022-01194-8
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