Dry Sliding Wear Behavior of Austenitic Stainless Steel Material by Gas Nitriding Process

In industries, components must operate under extreme conditions such as high load, speed, temperature and chemical environment. Materials are selected according to commercial availability, cost and their properties such as strength, hardness, etc. AISI 904L is a high-alloy stainless steel with low carbon content, poor surface hardness and wear characteristics. Many engineering failures are caused by fatigue, corrosion, and poor wear resistance, begins at the surface level. This causes cracks in the surface, reducing the material’s life. The surfaces of the materials were subjected to severe thermal, chemical, and shock loads. The selected AISI 904L materials for this work were subjected to gas nitriding process and processed with 3 different time parameters such as 12 hours, 18 hours and 24 hours respectively and named as GN1, GN2 and GN3. The treatments were done at a constant temperature of 650°C. Gas nitriding, in comparison to other nitriding processes such as plasma and liquid nitriding, provides good dimensional stability, reduced deformation, and uniform case depth regardless of the size and shape of the specimen. To analyze the wear properties, a pin on a disc machine is used. Finally, metallographic studies were performed by scanning electron microscopy

Bioethanol Production From Biomass Extracted From Sunn Hemp Seed

In this chapter, the general procedures for the biomass and bio-ethanal manufacturing processes are explained. The various physical and chemical pre-treating methods for biomass are elaborated. The various acid hydrolysis methods, enzyme immobilisation methods, fermentation methods, and optimising the parameters and factors for hydrolysis have been exemplified. The stage-by-stage bioethanol production processes from Sunn hemp seed has been illustrated. Biomass preparation, pre-treatment processes, hydrolysis, synthesis of ferrites, and study of bioethanol characterizations are graphically exemplified. The microstructure of untreated and treated hemp biomass has been displayed. The variations in bioethanol concentration with increasing treatment time have been discussed. The incorporation of optimization parameters for producing quality bioethanol is also interpreted.</jats:p

Dry Sliding Wear Behavior of Austenitic Stainless Steel Material by Gas Nitriding Process

In industries, components must operate under extreme conditions such as high load, speed, temperature and chemical environment. Materials are selected according to commercial availability, cost and their properties such as strength, hardness, etc. AISI 904L is a high-alloy stainless steel with low carbon content, poor surface hardness and wear characteristics. Many engineering failures are caused by fatigue, corrosion, and poor wear resistance, begins at the surface level. This causes cracks in the surface, reducing the material’s life. The surfaces of the materials were subjected to severe thermal, chemical, and shock loads. The selected AISI 904L materials for this work were subjected to gas nitriding process and processed with 3 different time parameters such as 12 hours, 18 hours and 24 hours respectively and named as GN1, GN2 and GN3. The treatments were done at a constant temperature of 650°C. Gas nitriding, in comparison to other nitriding processes such as plasma and liquid nitriding, provides good dimensional stability, reduced deformation, and uniform case depth regardless of the size and shape of the specimen. To analyze the wear properties, a pin on a disc machine is used. Finally, metallographic studies were performed by scanning electron microscopy.</jats:p

Quality control analysis, phytochemistry, and pharmacognosy of botanical source plants for Murva [Chonemorpha fragrans (Moon) Alston and Marsdenia tenacissima (Roxb.) Moon]: A comparative assessment

135-159Ayurveda extensively documents numerous medicinal plants and their therapeutic properties, but the lack of precise botanical descriptions often results in regional substitutions without scientific validation. Marsdenia tenacissima is identified as the botanical source of Murva in the Ayurveda Pharmacopoeia of India (API), while Chonemorpha fragrans is commonly used as its substitute in Southern India. This study evaluates the suitability of C. fragrans as an alternative to M. tenacissima through pharmacognostic, physicochemical, and preliminary phytochemical analyses of their aqueous and hydroalcoholic extracts. High-performance thin-layer chromatography (HPTLC) and Gas Chromatography-Mass Spectroscopy (GC-MS/MS) were employed for fingerprint profiling. The study revealed distinct morphological differences: M. tenacissima roots were yellow-buff with a complex xylem structure, while C. fragrans roots were brown with white latex. Both plants exhibited glycosides and saponins, but alkaloids and phenols were exclusive to C. fragrans. Hydroalcoholic extracts of C. fragrans displayed a richer array of phytoconstituents. HPTLC analysis identified gallic acid in the aqueous extract of C. fragrans and the hydroalcoholic extract of M. tenacissima, with quercetin present in all extracts and beta-sitosterol exclusive to hydroalcoholic extracts. These findings suggest that C. fragrans could potentially substitute M. tenacissima in Ayurvedic formulations, but further pharmacological studies are necessary to confirm their therapeutic equivalence

Predicting progression in Parkinson's Disease using baseline and 1-Year change measures

Background: Improved prediction of Parkinson’s disease (PD) progression is needed to support clinical decision-making and to accelerate research trials. Objectives: To examine whether baseline measures and their 1-year change predict longer-term progression in early PD. Methods: Parkinson’s Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models. Results: Among 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= –0.199; 95% CI = –0.315, –0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= –0.6229; 95% CI = –1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= –0.325;95% CI = –0.695, 0.045); predictors in the model accounted for 44.1% of the variance. Conclusions: Baseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding