Introduction: We undertook the present study to analyze morphological features of a skull supposed to be that of Alum Bheg, a martyr from 1857 Indian Freedom Struggle (also called Sepoy Mutiny), using established methods to validate identity with regards to age and height as available in the note found with the skull (about 32 year and 5 feet 7½ inch). Methods: Identification of sex of the skull was done based on established criteria. Analysis for closure of skull sutures (cranial and facial) and measurement of orbitomedial (OM) & maxillomedial (MM) facial anthropometric lines were undertaken to provide an estimated age against each examined suture as well as group of sutures through established scoring systems. Further, approximate height of individual was estimated from skull length using regression equations from a reference adult Indian male population. Results: Established criteria confirmed that the skull was of a male individual and skull sutures and age related morphological changes in bones indicate that it belonged to an individual in age range 20 -50 years with an average of 30 years and approximate height between 5 feet 8.2 inch to 6 feet 1 inch. Discussion: Based on our observations we suggest that the skull belonged to a male individual around 30 years of age and height 5 feet 8.2 inch to 6 feet 1 inch. The observed values are in approximation with that mentioned in the historical note and slight differences may be attributed either to gross reporting of original values or limitations of anthropometric analysis.

Alum sludge, an inevitable by-product from the water purification process, which had been applied as substrates in some constructed wetlands with good performance, especially for phosphorus (P) adsorption. The raw alum sludge is like clay lump with irregular shape and has a leaching concern used in the water. For a better reuse, herein, sludge was fired to produce alum sludge ceramsite (ASC) with a uniform spherical shape via four-step process of kneading sludge ball, air drying, preheating at 400°C for 10 min and firing at 600℃ for 5 min. Thereafter the physicochemical properties and P adsorption ability of ceramsite were investigated. Through XRD and FT-IR tests, there was no obvious difference between ASC and air-dried alum sludge ball (adASB) on the phase structure, but a certain amount of Al-OH group loss on the surface of ASC. The structure of ASC was still amorphous as same as adASB, while ASC possessed more micropore structure and bigger specific surface area than those of adASB. Adsorption experiments showed the P adsorption behaviors of ASC and adASB were much similar, and their adsorption kinetics all accorded with the two-step adsorption kinetics rate equation and pseudo-second-order kinetics equation. The maximum adsorption capacities of ASC and adASB fitted by Langmuir model were 1.66 mg/g and 1.89 mg/g respectively. It should be pointed that, compared with other adsorbents, ASC produced in this study still had a higher ability to adsorb P. Therefore, ASC should have a great application potential for P removal in the wastewater treatment in China.

Leptospirosis is a zoonotic disease of global importance. The current killed vaccine provides serovar-specific protection without sterilizing immunity. Several surface antigens, including Leptospira immunoglobulin-like proteins (LigA and LigB), have been identified as subunit vaccine candidates; however, they require potent adjuvants. Bacterial Lipopolysaccharide (LPS), including lipid A, is a well-known immunostimulatory agent, and the formulation of Monophosphoryl Lipid A (MPLA) in Alum is a clinical adjuvant. Being less endotoxic, we tested the adjuvant activity of lipid A purified from L. interrogans serovar Pomona (PLA) for its ability to activate innate and enhance antigen-specific adaptive immune response. PLA-induced activation of macrophages similar to levels induced by MPLA, albeit at a much higher dose, indicating that it is less stimulatory than MPLA. Mice immunized with a Variable portion of LigA (LAV) formulated in Alum and PLA (LAV-Alum-PLA) induced significantly higher levels of LAV-specific humoral and cellular immune response than Alum but similar to levels induced by Alum-MPLA. The adjuvant activity of PLA seems to be quite similar to MPLA and primarily mediated through enhanced recruitment, activation, and uptake of antigens by innate immune cells. Moreover, like MPLA, the PLA formulation was able to generate a long-term memory response. Most importantly, PLA demonstrated better potency than MPLA formulation and generated sterilizing immunity against challenge in a hamster model of leptospirosis. Altogether, our study has provided important insight into the adjuvant activity of Leptospira lipid A and has opened avenues for the development of LPS-based vaccines against this dreadful zoonosis.

Alum sludge is a byproduct of water treatment plants and its use as a soil stabilizer has gained increasing attention due to its economic and environmental benefits. Its application has been shown to improve the strength and stability of soil, making it suitable for various engineering applications. However, to go beyond just measuring the effects of alum sludge as a soil stabilizer, this paper explores the use of artificial intelligence (AI) methods to predict the California bearing ratio (CBR) of soils stabilized with alum sludge. Three AI methods, including two black box methods (artificial neural network and support vector machines) and one grey box method (genetic programming), were used to predict CBR based on a database with nine input parameters. The results showed that all three AI models were able to predict CBR with good accuracy, with coefficient of determination (R2) values ranging from 0.94 to 0.99 and mean absolute error (MAE) values ranging from 0.30 to 0.51. In a novel approach, the genetic programming method was used to produce an equation to estimate CBR, which included seven inputs and accurately predicted CBR. The analysis of sensitivity and importance of parameters showed that the number of hammer blows for compaction was the most important parameter, while the parameters for maximum dry density of soil and mixture were the least important. This study suggests that AI methods can effectively predict the performance of alum sludge as a soil stabilizer, and the proposed equation using genetic programming can be a useful tool for predicting CBR.