Enhancing Social Skills Among Secondary School Students: Evaluating The Impact Of The Autonomous Learner Model

Autonomous Learner Model developed by Betts and Kercher (Betts et al, 2021) is a framework developed to promote and support autonomous learning in students. The present investigation aimed to study the impact of the Autonomous Learner Model on Social skills among the Secondary school students. The design selected for the study was non-equivalent pre-test- post-test experimental group design. The study was conducted on a sample of secondary school students who were following the Kerala State syllabus. Specifically, the sample consisted of 74 students from Standard Nine of Holy Cross Higher Secondary School, Cherpunkal, Kottayam, Kerala. The instruments used for the study were Instructional materials based on Autonomous Learner Model and Existing Activity Oriented Method prepared by the investigators and Social Skill Rating Scale (Sood et al,2012). Treatment was given for two months in Social Science to the Experimental group using the Autonomous Learner Model, while the Control group received instruction using the current Activity Oriented Method. The study revealed that Autonomous Learner Model enhanced social skills among secondary school students when compared to the existing Activity Oriented Method of Instruction. The findings of the study will contribute to the existing body of knowledge on learner autonomy while providing practical insights for educators, curriculum developers, and policy makers to design educational interventions that foster holistic development among students

Bulk Utilization of Red Mud in Geopolymer Based Products

Red Mud is the solid residue generated from Alumina refinery during the process of bauxite ore processing through Bayer’s process. Typical generation of red mud is 1.5 tons of red mud per ton of alumina produced. The disposal and storage of red mud has been a concern for the alumina industry since its inception, more than a hundred years ago. With the increase in alumina production, the magnitude of the problem is getting multiplied. Its alkaline nature (Na2O ~ 3-7%) and fine size make red mud unsuitable for many applications; a limited utilization is reported in cement industries as one of the raw mix components for cement. The present work deals with the utilization of red mud in geopolymer based paving blocks. Alumina, silica and alkali are the essential items required for geopolymer preparation. Having all these in red mud, the current study attempted to use the same in geopolymer based products. The focus has been on bulk utilization of red mud; target strength of 20 MPa after 28 days of curing (M20 grade) has been the goal as this strength is sufficient for many applications. The study focused on optimizing the red mud content, alkali concentration, fly ash content, etc. The samples are tested for its compressive strength and leachability. The study reveals that significant amount of red mud incorporation is possible with products conforming to USEPA 1311 norms

Fear and food: Effects of predator-derived chemical cues and stoichiometric food quality on Daphnia

While resource quality and predator‐derived chemical cues can each have profound effects on zooplankton populations and their function in ecosystems, the strength and direction of their interactive effects remain unclear. We conducted laboratory experiments to evaluate how stoichiometric food quality (i.e., algal carbon [C] : phosphorus [P] ratios) affects responses of the zooplankter, Daphnia pulicaria, to predator‐derived chemical cues. We compared growth rates, body P content, metabolic rates, life‐history shifts, and survival of differentially P‐nourished Daphnia in the presence and absence of chemical cues derived from fish predators. We found effects of predator cues and/or stoichiometric food quality on all measured traits of Daphnia. Exposure to fish cues led to reduced growth and increased metabolic rates but had little effect on the body %P content of Daphnia. Elevated algal C : P ratios reduced growth and body %P and increased mass‐specific respiration rates. While most of the effects of predator cues and algal C : P ratios of Daphnia were non‐interactive, reduced survival and relatedly reduced population growth rates that resulted from P‐poor food were amplified in the presence of predator‐derived cues. Our results demonstrate that stoichiometric food quality interacts with antipredator responses of Daphnia, but these effects are largely trait dependent and appear connected to animal life‐history evolution. Given the ubiquity of predators and P‐poor food in lake ecosystems, our results highlight the importance of the interactive responses of animals to predator cues and poor nutrition

Stability of Monomer-Dimer Piles

We measure how strong, localized contact adhesion between grains affects the maximum static critical angle, theta_c, of a dry sand pile. By mixing dimer grains, each consisting of two spheres that have been rigidly bonded together, with simple spherical monomer grains, we create sandpiles that contain strong localized adhesion between a given particle and at most one of its neighbors. We find that tan(theta_c) increases from 0.45 to 1.1 and the grain packing fraction, Phi, decreases from 0.58 to 0.52 as we increase the relative number fraction of dimer particles in the pile, nu_d, from 0 to 1. We attribute the increase in tan(theta_c(nu_d)) to the enhanced stability of dimers on the surface, which reduces the density of monomers that need to be accomodated in the most stable surface traps. A full characterization and geometrical stability analysis of surface traps provides a good quantitative agreement between experiment and theory over a wide range of nu_d, without any fitting parameters.Comment: 11 pages, 12 figures consisting of 21 eps files, submitted to PR

Current Distribution in the Three-Dimensional Random Resistor Network at the Percolation Threshold

We study the multifractal properties of the current distribution of the three-dimensional random resistor network at the percolation threshold. For lattices ranging in size from $8^3$ to $80^3$ we measure the second, fourth and sixth moments of the current distribution, finding {\it e.g.\/} that $t/\nu=2.282(5)$ where $t$ is the conductivity exponent and $\nu$ is the correlation length exponent.Comment: 10 pages, latex, 8 figures in separate uuencoded fil

Surface permeability of porous media particles and capillary transport

We have established previously, in a lead-in study, that the spreading of liquids in particulate porous media at low saturation levels, characteristically less than 10% of the void space, has very distinctive features in comparison to that at higher saturation levels. In particular, we have found that the dispersion process can be accurately described by a special class of partial differential equations, the super-fast non-linear diffusion equation. The results of mathematical modelling have demonstrated very good agreement with experimental observations. However, any enhancement of the accuracy and predictive power of the model, keeping in mind practical applications, requires the knowledge of the effective surface permeability of the constituent particles, which defines the global, macroscopic permeability of the particulate media. In the paper, we demonstrate how this quantity can be determined through the solution of the Laplace-Beltrami Dirichlet problem, we study this using the well-developed surface finite element method

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

Background: Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings: The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions: TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients

Variation in neurosurgical management of traumatic brain injury

Background: Neurosurgical management of traumatic brain injury (TBI) is challenging, with only low-quality evidence. We aimed to explore differences in neurosurgical strategies for TBI across Europe. Methods: A survey was sent to 68 centers participating in the Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. The questionnaire contained 21 questions, including the decision when to operate (or not) on traumatic acute subdural hematoma (ASDH) and intracerebral hematoma (ICH), and when to perform a decompressive craniectomy (DC) in raised intracranial pressure (ICP). Results: The survey was completed by 68 centers (100%). On average, 10 neurosurgeons work in each trauma center. In all centers, a neurosurgeon was available within 30 min. Forty percent of responders reported a thickness or volume threshold for evacuation of an ASDH. Most responders (78%) decide on a primary DC in evacuating an ASDH during the operation, when swelling is present. For ICH, 3% would perform an evacuation directly to prevent secondary deterioration and 66% only in case of clinical deterioration. Most respondents (91%) reported to consider a DC for refractory high ICP. The reported cut-off ICP for DC in refractory high ICP, however, differed: 60% uses 25 mmHg, 18% 30 mmHg, and 17% 20 mmHg. Treatment strategies varied substantially between regions, specifically for the threshold for ASDH surgery and DC for refractory raised ICP. Also within center variation was present: 31% reported variation within the hospital for inserting an ICP monitor and 43% for evacuating mass lesions. Conclusion: Despite a homogeneous organization, considerable practice variation exists of neurosurgical strategies for TBI in Europe. These results provide an incentive for comparative effectiveness research to determine elements of effective neurosurgical care

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Not AvailableBacterial metabolites are one of the primary sources of drugs that we currently use to treat several diseases. However, bacterial drug discovery and development is a challenging and time-consuming process, and the emergence of new diseases and the development of resistance to currently available drugs demand the discovery of new metabolites with better biological activities. The new advancements in microbial technology, omics, genome and metabolic engineering, synthetic biology and the interdisciplinary approach of these fields overcome the hurdles in drug discovery and heterologous synthesis from bacteria. The gut microbiome performs a vital role in sustaining human health and aids in tackling various diseases. The metabolites produced by the gut microbiome act as an energy source for colon epithelium, maintain pH, help in cell differentiation and induces apoptosis in abnormal cells. The review discusses about the bacterial derived bioactive compounds, advancements and technologies in bacterial synthesis of bioactive sources and genomic and synthetic biology methods for the bioprospecting of bacterial metabolites. Since the gut microbiome relates to colon health, we have also discussed the techniques comprising probiotics, prebiotics, microbiome transplantation, toxins, and bacteriocins capable of preventing and managing colon associated health condition. Future directions in bacterial bioactive metabolite production are also discussed.Not Availabl