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•The article reviews sex estimation methods used in forensic anthropology casework.•It also discusses the reliability of morphological, metric, molecular and radiographic methods.•Direct methods of sex estimation are found to be more reliable than the other methods.•GM and DSP methods are emerging as valid and widely used techniques in forensic anthropology. Sex estimation is considered as one of the essential parameters in forensic anthropology casework, and requires foremost consideration in the examination of skeletal remains. Forensic anthropologists frequently employ morphologic and metric methods for sex estimation of human remains. These methods are still very imperative in identification process in spite of the advent and accomplishment of molecular techniques. A constant boost in the use of imaging techniques in forensic anthropology research has facilitated to derive as well as revise the available population data. These methods however, are less reliable owing to high variance and indistinct landmark details. The present review discusses the reliability and reproducibility of various analytical approaches; morphological, metric, molecular and radiographic methods in sex estimation of skeletal remains. Numerous studies have shown a higher reliability and reproducibility of measurements taken directly on the bones and hence, such direct methods of sex estimation are considered to be more reliable than the other methods. Geometric morphometric (GM) method and Diagnose Sexuelle Probabiliste (DSP) method are emerging as valid methods and widely used techniques in forensic anthropology in terms of accuracy and reliability. Besides, the newer 3D methods are shown to exhibit specific sexual dimorphism patterns not readily revealed by traditional methods. Development of newer and better methodologies for sex estimation as well as re-evaluation of the existing ones will continue in the endeavour of forensic researchers for more accurate results.

The present study indicates the importance of using glass fiber reinforced polymer (GFRP) laminates with appropriate thickness and fibers orientation when exposed to harsh environmental conditions. The effect of different environmental conditions on tensile properties of different GFRP laminates is investigated. Laminates were exposed to three environmental conditions: (1) Freeze/thaw cycles without the presence of moisture, (2) freeze/thaw cycles with the presence of moisture and (3) UV radiation and water vapor condensation cycles. The effect of fiber configuration and laminate thickness were investigated by considering three types of fiber arrangement: (1) Continuous unidirectional, (2) continuous woven and (3) chopped strand mat and two thicknesses (2 and 5 mm). Microstructure and tensile properties of the laminates after exposure to different periods of conditioning (0, 750, 1250 and 2000 h) were studied using SEM and tensile tests. Statistical analyses were used to quantify the obtained results and propose prediction models. The results showed that the condition comprising UV radiation and moisture condition was the most aggressive, while dry freeze/thaw environment was the least. Furthermore, the laminates with chopped strand mat and continuous unidirectional fibers respectively experienced the highest and the lowest reductions properties in all environmental conditions. The maximum reductions in tensile strength for chopped strand mat laminates were about 7%, 32%, and 42% in the dry freeze/thaw, wet freeze/thaw and UV with moisture environments, respectively. The corresponding decreases in the tensile strength for unidirectional laminates were negligible, 17% and 23%, whereas those for the woven laminates were and 7%, 24%, and 34%.

Oil-water separation has become the prime concern for fossil fuel exploration industries. In the present study, superhydrophobic coating on filter paper was prepared to repellent water while allowing oil to flow freely from its porous structures. Coating was generated by solution-casting technique on cellulosic filter paper using silica nanoparticles (SiO2) along with silane coupler hexadecyltrimethoxysilane (HDTMS). The contact angle was measured, and it has shown 175.1° ± 1.5°, and the tilting angle is 1.5° ± 0.2°. The surface topography of coated and treated samples was also examined. Furthermore, thermal stability of fabricated filter papers was evaluated by annealing at a different range of temperatures (20 °C-220 °C). The pH resistance of the coatings were inspected by immersing the specimens in acidic and alkali solutions (pH 2-13). The mechanical durability was examined by tape-peeling and abrasion tests. Moreover, these samples have shown waterjet impact resistance. Filtration study was performed on coated filter papers using various oil-water mixtures of kerosene-water and petroleum ether-water and results have shown the separation efficiency of 99% and 98.5%, respectively. Thus these filter papers can have potential practical and industrial applications.

Monitoring vegetation phenology is essential for understanding the impacts of climate change on agricultural production. This study leverages Sentinel-2 data to develop an algorithm in Google Earth Engine (GEE) for calculating phenological metrics of rice crop cultivated over the hilly area, allowing for high-resolution, efficient, and large-scale analysis without the need for data download. The study focuses on key metrics, including the start of the season  and end of the season , length of growing season derived from various vegetation indices. The results demonstrate that NDVI-based phenological metrics closely align with the observed values at the experimental site, Malan. Moreover, the relationship of NDVI based length of growing season with the rice crop yield was found stronger with a R2 value of 0.68, depicting the capability of the satellite-based phenology metrics to estimate the rice crop yield in hilly region of Himachal Pradesh.

Presence of non-metallic inclusion deteriorates quality of steel and causes nozzle clogging during casting. Nozzle clogging eventually leads to a disruption of normal casting operations. This happens when solid alumina inclusions get accumulate in the nozzle of submerged entry nozzle (SEN). Therefore, it is required to understand the inclusion characteristics (shape, size and chemistry), which forms during the steelmaking process. Calcium is added in the steel ladle furnace (LF) in the form of CaSi wire to modify inclusions and to desulphurize steel. The range in which all the oxides become liquid and no solid sulphides begin to form is regarded as the \"optimum window\" or “liquid inclusion window” for calcium treatment. It is a target to obtain this calcium addition window, during calcium addition in the ladle furnace. This window mainly depends on the sulfur and total oxygen contents of the liquid steel bath. In the present study, inclusions characteristics such as volume fraction of inclusions, inclusion rating and EDS analysis of inclusions has been carried out using SEM-EDS. Thermodynamic study is carried out using thermodynamic software FACTSAGE and databases to find out formation of various calcium aluminates and the precipitation of CaS. Results show that liquid inclusion window mainly depends mainly on the sulphur level, total oxygen and aluminum content in the steel. These windows will help in calculation of calcium addition range for optimizing the addition of calcium in the ladle. These nomograms have been validated with actual plant condition to reduce the nozzle clogging during continuous casting.

Brucella abortus S19 is a smooth strain used as live vaccine against bovine brucellosis. Smooth lipopolysaccharide (LPS) is responsible for its residual virulence and serological interference. Rough mutants defective of LPS are more attenuated but confers lower level of protection. We describe a modified B. abortus S19 strain, named as S19Δper, which exhibits intermediate rough phenotype with residual O-polysaccharide (OPS). Deletion of perosamine synthetase gene resulted in substantial attenuation of S19Δper mutant without affecting immunogenic properties. It mounted strong immune response in Swiss albino mice and conferred protection similar to S19 vaccine. Immunized mice produced higher levels of IFN-γ, IgG2a and thus has immune response inclined towards Th1 cell mediated immunity. Sera from immunized animals did not show agglutination reaction with RBPT antigen and thus could serve as DIVA (Differentiating Infected from Vaccinated Animals) vaccine. S19Δper mutant displayed more susceptibility to serum complement mediated killing and sensitivity to polymyxin B. Pregnant guinea pigs injected with S19Δper mutant completed full term of pregnancy and did not cause abortion, still birth or birth of weak offspring. S19Δper mutant with intermediate rough phenotype displayed remarkable resemblance to S19 vaccine strain with improved properties of safety, immunogenicity and DIVA capability for control of bovine brucellosis.

This study assesses the performance of auto-regressive integrated moving average (ARIMA), artificial neural network (ANN), support vector machine (SVM) and extreme learning machine (ELM), in predicting meteorological drought with Standardized Precipitation Index (SPI-6 and SPI-12) for Kalahandi district, Odisha. Mann-Kendall tests showed no significant trend in SPI value for both shorter and longer scales. Model performance was evaluated using correlation coefficient (CC), root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), and mean absolute error (MAE) during the training as well as testing phases. For SPI-6, ARIMA performed well during training (NSE = 0.66, RMSE = 0.60) but showed a decline in testing (NSE = 0.25). Machine learning models, including ELM, SVM and ANN exhibited better consistency, with NSE values ranging from 0.45 to 0.47. For SPI-12, ANN delivered the highest accuracy with NSE values of 0.91 and 0.89 and RMSE values of 0.31 and 0.29 in training and testing, respectively. Graphical analysis further demonstrated that ANN and SVM outperformed ARIMA by effectively capturing nonlinear trends and extreme fluctuations. Overall, machine learning models, particularly ANN and SVM, proved to be superior for predicting both long-term (SPI-12) and short-term (SPI-6) precipitation indices, highlighting their effectiveness for accurate drought forecasting.

What is already known on this topic? We report a female with pycnodysostosis with associated with GH deficiency who was managed with rhGH. She had a favourable response with improvement in height standard deviation score of 1 over 18 months of treatment. rhGH unmasked central hypothyroidism requiring l-thyroxine replacement. A patient with pycnodysostosis requires monitoring for central hypothyroidism and other pituitary hormone deficiencies, especially if rhGH treatment is being offered.

An elevated level of macrophage inhibitory cytokine-1 (MIC-1) is reported in the sera of patients with metastatic prostate cancer compared with that of benign diseases and healthy adults. We investigated the mechanistic role of MIC-1 overexpression in the metastasis of prostate cancer cells. Our study showed a progressive increase in secretory MIC-1 production correlated with the increase in the metastatic potential of PC-3 and LNPCa prostate cancer metastatic variants. Further, the in vitro studies using ‘loss-’ and ‘gain’-of-function approaches showed that ectopic overexpression of MIC-1 (PC-3-MIC-1) and forced downregulation of MIC-1(PC-3M-siMIC-1) enhanced and reduced the motility and invasiveness of these cells, respectively. Supporting our in vitro observations, all the mice orthotopically implanted with PC-3-MIC-1 cells developed metastasis compared with none in the PC-3-vector group. Our results showed that MIC-1 overexpression was associated with apparent changes in actin organization. In addition, an enhanced phosphorylation of focal adhesion kinase (FAK) and guanosine-5′-triphosphate (GTP)-bound RhoA was also seen; however, no significant change was observed in total FAK and RhoA levels in the PC-3-MIC-1 cells. Altogether, our findings show that MIC-1 has a role in prostate cancer metastasis, in part, by promoting the motility of these cells. Activation of the FAK–RhoA signaling pathway is involved in MIC-1-mediated actin reorganization, and thus, leads to an increase in the motility of prostate cancer cells.

Purpose In the present context of a globalised economy, market requirements are changing regularly in term of product cost, delivery time, safety and environmental issues. Apart from conventional measures, environmental factors have become an integral part of performance measurement system. This study aims to analyse major barriers and factors in green supply chain (GSC) management implementation. Design/methodology/approach The present study has tried to identify barriers and factors for green supply chain management (GSCM) based on literature review. Factors for GSCM have been modelled by interpretive structural modelling (ISM) approach. Findings Based on literature review, 12 factors have been identified. It has been observed that top management commitment, integration among supply chain members, vendors’ development, environmental friendly packaging and transportation, reverse logistic management and development of a green performance measurement system are major drivers for successful implementation of GSCM. Research Limitations/implications Organisations need to follow a proactive approach for taking GSC initiatives. For generalisation of findings, empirical study and some case studies need to be carried out. Originality/value Findings of this study will help organisations in strategy formulation for GSCM and successful implementation for sustainable competitiveness.