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Technological advancements are triggering disruptive inventions in the teaching and learning process. The introduction of massive online courses offers students many opportunities to enroll in any course they choose, transcending geographical barriers. However, online learning puts responsibility for learning on the learners and lack faculty-student and peer-peer direct interactions. The instructor's role also must be redefined to provide support and collaboration in the online environment. Recent research reports poor student retention and completion rates in such courses and there is a lack of effective frameworks and gap in research related to identifying key factors and finding solutions to these problems. A multi-faculty e-learning framework is proposed based on a theoretical model highlighting important factors to address these problems. Experimental results of an ANOVA analysis done on student performance data collected in a multi-faculty setup provided empirical evidence for its effectiveness in improving the student learning outcomes.

In a nuclear reactor, heat generated by the decay of fission products and radioactive materials is called decay heat or decay power. For measuring decay heat from radioactive samples, bismuth germanate scintillators based whole energy absorption spectrometer was commissioned recently. To standardize it, decay heat from neutron irradiated 197Au foil was measured from 7 min to 480 h. In this cooling period the decay heat reduced from 1668 ± 12.5 to 10 ± 1.8 pW. The measurements were compared with the predictions and the C/E ratios were found to be < 1.10. The fractional decay power contributions from betas and gammas for 198Au were obtained through the measurements and estimations. This work provided experience for planning irradiation and measuring time for further experiments with reactor structural materials and actinides.

Purpose While research on inguinal hernias is well-documented, ventral/incisional hernias still require investigation. In India, opinions on laparoscopic ventral hernia repair (LVHR) techniques are contested. The current consensus aims to standardize LVHR practice and identify gaps and unfulfilled demands that compromise patient safety and therapeutic outcomes. Methods Using the modified Delphi technique, panel of 14 experts (general surgeons) came to a consensus. Two rounds of consensus were conducted online. An advisory board meeting was held for the third round, wherein survey results were discussed and the final statements were decided with supporting clinical evidence. Results Experts recommended intraperitoneal onlay mesh (IPOM) plus/trans-abdominal retromuscular/extended totally extraperitoneal/mini- or less-open sublay operation/transabdominal preperitoneal/trans-abdominal partial extra-peritoneal/subcutaneous onlay laparoscopic approach/laparoscopic intracorporeal rectus aponeuroplasty as valid minimal access surgery (MAS) options for ventral hernia (VH). Intraperitoneal repair technique is the preferred MAS procedure for primary umbilical hernia < 4 cm without diastasis; incisional hernia in the presence of a vertical single midline incision; symptomatic hernia, BMI > 40 kg/m 2 , and defect up to 4 cm; and for MAS VH surgery with grade 3/4 American Society of Anaesthesiologists. IPOM plus is the preferred MAS procedure for midline incisional hernia of width < 4 cm in patients with a previous laparotomy. Extraperitoneal repair technique is the preferred MAS procedure for L3 hernia < 4 cm; midline hernias < 4 cm with diastasis; and M5 hernia. Conclusion The consensus statements will help standardize LVHR practices, improve decision-making, and provide guidance on MAS in VHR in the Indian scenario.

In this paper, the performance of three machine-learning methods for predicting short-term evolution and for reproducing the long-term statistics of a multiscale spatiotemporal Lorenz 96 system is examined. The methods are an echo state network (ESN, which is a type of reservoir computing; hereafter RC–ESN), a deep feed-forward artificial neural network (ANN), and a recurrent neural network (RNN) with long short-term memory (LSTM; hereafter RNN–LSTM). This Lorenz 96 system has three tiers of nonlinearly interacting variables representing slow/large-scale (X), intermediate (Y), and fast/small-scale (Z) processes. For training or testing, only X is available; Y and Z are never known or used. We show that RC–ESN substantially outperforms ANN and RNN–LSTM for short-term predictions, e.g., accurately forecasting the chaotic trajectories for hundreds of numerical solver's time steps equivalent to several Lyapunov timescales. The RNN–LSTM outperforms ANN, and both methods show some prediction skills too. Furthermore, even after losing the trajectory, data predicted by RC–ESN and RNN–LSTM have probability density functions (pdf's) that closely match the true pdf – even at the tails. The pdf of the data predicted using ANN, however, deviates from the true pdf. Implications, caveats, and applications to data-driven and data-assisted surrogate modeling of complex nonlinear dynamical systems, such as weather and climate, are discussed.

Postprandial hypotension (PPH) is a common phenomenon among older adults. The degree to which individuals experience PPH is related to cerebrovascular risk factors and the presence of neurodegenerative diseases such as Alzheimer’s disease (AD). Carrier status of the E4 allele of the apolipoprotein E (APOE) gene is a risk factor for AD and influences a variety of responses to metabolic and dietary interventions. However, it is unknown whether APOE genotype influences the risk of PPH and whether type of meal can mediate that response. Acute meal study with a crossover design. 32 cognitively healthy older adults with (n=18) and without (n=14) E4+ carrier status. As a part of an ongoing meal study we examined the postprandial blood pressure response after ingestion of a high carbohydrate (HCM) and high fat meal (HFM). Blood pressure measurements were taken at 7 time points and change scores, area under the curve (AUC) scores were calculated. Data were analyzed by repeated measures ANOVA as well as Pearson correlation. Both meals produced a sustained drop in systolic (SBP) and diastolic (DBP) blood pressure, with 37.5% of participants meeting criteria for PPH. Participants carrying the E4+ risk gene experienced a larger decrease in SBP than E4- participants, and this was significantly different after the HFM (E4+ AUC = -30.8 ± 7.6, E4- AUC = -0.2 ± 8.7, p=0.015). Increasing age was associated with a larger drop in postprandial blood pressure but only for the E4+ group after the HFM (p=0.002). These data suggest that E4+ individuals experience a greater postprandial blood pressure response particularly following high fat feeding, and this effect becomes more pronounced with age. The prevalence of PPH may play a role in the development of AD and may be mediated by diet.

MapReduce is a popular, open source programming paradigm to handle big data which is an industry standard large scale data processing system used by many companies like Yahoo, Google, Facebook, etc. The YARN framework uses low resource fairness algorithms such as FIFO, Capacity, Fair, DRF scheduler, whereas these schedulers are not suitable for heterogeneous Hadoop clusters. Therefore, an Enhanced Combined Regression Ranking (eCRRYARN) algorithm was proposed to enhance resource fairness. The proposed algorithm uses linear regression model to estimate the expected resources to be availed by the tenants. The order ranking is given to the estimated resource and the resources shared as per the ranking provided. Hence, the Hierarchical Hadoop Cluster Resource Sharing (HHCRS) algorithm has been adopted for hierarchical distributed cluster aiming to design a cost effective cluster for organization which is spread across the globe.

In inline three cylinder engine, cylinder block is an integrated structure comprising the cylinders, coolant passages, intake and exhaust passages and ports, and crank case. The cylinder block is mostly fabricated by casting process. The surface irregularities in the top face of the casted cylinder block causes improper seating of cylinder head and surface finishing becomes essential. Hence the casted cylinder block was machined with series of operations such as rough milling, face milling, finish milling, honing, line boring, drilling, tapping and reaming operations. In face milling operation, milling machine requires special cutting tools to remove the surface irregularities of the cylinder block. In the vertical milling machine, 12.6 kg cutting tool is fitted and removed by manually and it leads safety problems to the workers. The manual tool changing method increases the idle time of the machine and hence a tool changing mechanism is required to overcome the above said problems. In this present work, tool changing mechanism is designed and fabricated for a vertical milling machine to perform top face milling operation. Hence a semi-automatic mechanism is suggested to minimize the time of tool replacement. The solid model of the semi-automatic mechanism was modelled using SOLIDWORKS and the stress analysis of the components of the tool changing mechanism was performed using ANSYS Workbench. The manual tool changing method increases the idle time of the machine and hence a tool changing mechanism is required to overcome the above said problems. The cutting tool replacement time is reduced as 4.10 minutes from 11.05 minutes.

Autism spectrum disorder (ASD) and temporal lobe epilepsy exhibit remarkable comorbidity, but for reasons not clearly understood. To reveal a common pathophysiological mechanism, we here describe and characterize an in vitro epileptiform activity in the rat hippocampus that exhibits common features with in vivo activity in rodent ASD models. We discovered the development of this activity in the CA1 region of horizontal slices after prolonged interictal-like epileptiform activity in the CA3 region that was provoked by incubation in high potassium artificial cerebrospinal fluid. The CA1 epileptiform bursts were insensitive to blockers of glutamatergic transmission, and were carried by synaptic as well as extrasynaptic, tonically activated gamma-aminobutyric acid type A (GABA(A)) receptors. The bursts bear resemblance to in vivo gamma-oscillatory activity found in rat ASD models with respect to their gamma frequency spectrum, their origin (in the CA1), and their sensitivity to blockers of cation-chloride pumps (NKCC1 and KCC2), as well as to oxytocin. Considering this bursting activity as an in vitro model for studying comorbidity between epilepsy and ASD may help to disentangle the intricate interactions that underlie the comorbidity between both diseases and suggests that extrasynaptic tonic GABAergic transmission could represent a potential target for ASD.

The increase in usage of IoT environment is beyond the limits, which use Wireless (WSN).These networks can be used in many environments like logistics, supply chain management,health management,e-governance, smart parking, smart city, and smart appliances. WSN is a collection of sensors spread across them to base station/sink. Remote sensing sensors do sensing of an object remotely and detectthe static or dynamic information.In this paper, discussion is made on how to monitor and track the person’scar within a shopping mall. Remote monitoring and local optimization techniques are used in smart parking architecture, which suits for smart parking environment. Further, description of some of the monitoring and tracking techniques which was used earlier also been discussed with different types of protocols used for this appropriate environment. These systems can be implemented for effective smart parking.