Metric dimension of line graph of the subdivision of the graphs of convex polytopes

The metric generator for the simple connected graph Γ is the set of vertices Y ⊆ V(Γ) with the property that every pair of vertices u, v(u 6= v) ∈ V are determined (or resolved) by some vertex of Y. The minimum possible cardinality of this metric generator is called the metric dimension of Γ, denoted by dim(Γ)or β(Γ). In this article, we determine the exact metric dimension and some other properties of the line graph of the subdivision graph of the graph of convex polytope Dn (exists in the literature).Publisher's Versio

On the metric dimension of a class of planar graphs

Let H = (V, E) be a non-trivial connected graph with vertex set V and edge set E. A set of ordered vertices Rm from V (H) is said to be a resolving set for H if each vertex of H is uniquely determined by its vector of distances to the vertices of Rm. The number of vertices in a smallest resolving set is called the metric dimension of H. In this article, we study the metric dimension for a rotationally symmetric family of planar graphs, each of which is shown to have an independent minimum resolving set of cardinality three.Publisher's Versio

Development of Medium Power High Efficiency Multi-Level Buck-Boost DC-DC Converter

Power DC/DC converters or regulators form the backbone of different portable electronic devices like cellular phones, laptops, portable electronic devices which are using batteries as their power supply. Portable devices usually comprise of several sub-circuits that should be supplied with different voltage levels, which are not the same as battery’s voltage level which is the main supply voltage. A new approach of buck-boost converter is presented in this paper, that automatically detects the zero-inductor current & compels the convertor to deliberately switch from Continuous Conduction Mode (CCM) to Discontinuous Conduction Mode (DCM), once the inductor current attempts towards negative values, restricting the inductor current to approach towards negative value, and thus enhancing the convertor\u27s performance and efficiency at low load conditions. The converter steps down 200 V input voltage to 187 V and steps up to 211 V simultaneously at 100 Ω load resistance using PSIM software at switching frequency of 100 KHz. The comprehensive analysis of the topology is carried out and the simulated results are compared with the earlier designs at variable loads to verify the performance of the converter

Masquelet technique for management of posttraumatic bone defect in a patient of chronic osteomyelitis of long bone

Masquelet technique, which is the use of a temporary cement spacer followed by staged bone grafting, is a treatment strategy for reconstruction of large, infected, bone defects. This paper describes a patient treated with this technique to successfully manage postinfective or posttraumatic osseous long bone defect. Sequestrectomy was done and the injured limb was stabilized and aligned with application of external fixator at the time of initial antibiotic cement spacer placement. After 6 weeks of proper antibiotic coverage, all antibiotics were stopped for next 2 weeks. Clinical evaluation and investigations were done to rule out any residual infection. Osseous consolidation was successfully achieved with staged bone grafting and internal stabilization of long bone defect

Anaesthesia and anaesthesiologist speciality's knowledge assessment of paramedics in armed forces hospital: a questionnaire study

Background: Science of anaesthesia has revolutionized from traditional only application of relieving patient from pain induced during surgery to wide spectrum approaches like palliative care, critical care, perioperative care along with pain management. Despite of such critical roles in health care sector there is still a lack of awareness about anaesthesiology and anaesthesiologists. Current investigation was aimed towards assessing the awareness of paramedical staff regarding the role of anesthesiology.Methods: Current investigation was a prospective cross-sectional questionnaire-based study conducted on 100 paramedical staff posted in different departments of military hospital Jaipur.  All the study participants were interviewed face to face orally by an investigator using the set of questions listed in the questionnaire. Participants responses were documented and statistically represented as percentage.Results: Current study findings reveal that even though majority of the study participants (91) had experience more than 5 years in the hospital and most of them (˃90%) of participants were having educational level of higher secondary or graduation still the role of anaesthesiologist outside operation theatre was poorly known to paramedical staff. It was also observed in current investigation that role of anesthetist in pain clinic was poorly known to most of the participating paramedical staff.Conclusions: Providing knowledge about expertise of anesthesiologist among paramedical staffs by incorporating anaesthesia in the curriculum, in house training programs, use of pamphlets, internet and other easily assessable techniques is highly desirable for spreading awareness of anaesthesia and anesthetist among paramedical staff, so that patient can avail anaesthesia related services effectively

Phytochemical profile, in-vitro antioxidant, anti-diabetic and anti- inflammatory activities of traditionally used Euphorbia hirta (L.) growing under wild conditions of Northern Punjab

Euphorbia spp., are the widely distributed and traditionally used herbal plants due to their diverse biological activities. The aim of this study was comparative extraction of secondary metabolites with different solvents like acetone, ethanol, methanol and water and assessment of their biological activities from Euphorbia hirta L. Plant extracts from dried powder were prepared in different solvents. Phytochemicals like: phenolics, flavonoids and condensed tannins were estimated using standard assays. GC-FID studies were conducted to find out the presence of various bioactive compounds. Fingerprint analysis using UV, FT-IR and fluorescent spectroscopy was also conducted. Antioxidant activities using various assays, anti-diabetic and anti-inflammatory potential of extracts were evaluated. Fingerprint analysis using, UV-, FT-IR and fluorescent spectroscopy specified the occurrence of adequate level of polyphenolics in all solvent extracts. Amongst all solvents acetone gave higher yield of polyphenolics in-toto. GC-FID analysis of acetone extracts depicted the presence of bioactive compounds like major 1-naphthalenepropanol.  All extracts depicted enough level of antioxidant activities viz: DPPH, ABTS, hydroxyl radical, iron chelating and lipid peroxidation, but in a solvent dependent manner. Adequate anti-diabetic activity and anti-inflammatory activities were also observed in extracts. The results specified that by using suitable solvents bioactive compounds from Euphorbia species can be extracted and used as therapeutic agents having potential biological activities

Construction of Data Driven Decomposition Based Soft Sensors with Auto Encoder Deep Neural Network for IoT Healthcare Applications

The architecture of IoT healthcare is motivated towards the data-driven realization and patient-centric health models, whereas the personalized assistance is provided by deploying the advanced sensors. According to the procedures in surgery, in the emergency unit, the patients are monitored till they are stable physically and then shifted to ward for further recovery and evaluation. Normally evaluation done in ward doesn’t suggest continuous parameters monitoring for physiological condition and thus relapse of patients are common. In real-time healthcare applications, the vital parameters will be estimated through dedicated sensors, that are still luxurious at the present situation and highly sensitive to harsh conditions of environment. Furthermore, for real-time monitoring, delay is usually present in the sensors. Because of these issues, data-driven soft sensors are highly attractive alternatives. This research is motivated towards this fact and Auto Encoder Deep Neural Network (AutoEncDeepNN) is proposed depending on Health Framework in the internet assisting the patients with trigger-based sensor activation model to manage master and slave sensors. The advantage of the proposed method is that the hidden information are mined automatically from the sensors and high representative features are generated by multiple layer’s iteration. This goal is consistently achieved and thus the proposed model outperforms few standard approaches which are considered like Hierarchical Extreme Learning Machine (HELM), Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM). It is found that the proposed AutoEncDeepNN method achieves 94.72% of accuracy, 41.96% of RMSE, 34.16% of RAE and 48.68% of MAE in 74.64 ms

Analysing Urban Social Networks for Civic Participation: Data-Intensive Insights from the Civic Participation Test

This research delves into the dynamics of civic engagement in urban settings. The sample of participants was broad, with ages ranging from 22 to 40 years, nearly equal gender distribution (52% female, 48% male), and a range of educational backgrounds, including postgraduates (35%), bachelor's degree holders (40%), and high school graduates (25%). Numerous chances for participation exist in urban environments, as seen by our examination of data on civic activities. These include voter registration campaigns, town hall meetings, and community clean-up initiatives. In addition, members' responsibilities in these activities varied: 35% attended events, 15% made financial contributions, and 45% actively volunteered. Our results highlight the significance of social networks in urban civic engagement by showing that individuals with a wide range of social connections were more likely to participate in civic activities. The study's findings highlight the complex nature of civic participation in cities and have applications for encouraging diversity and community building in urban environments

Genetic diversity and population structure analyses in barley (Hordeum vulgare) against corn-leaf aphid, Rhopalosiphum maidis (Fitch)

Corn-leaf aphid (CLA), Rhopalosiphum maidis (Fitch) (Hemiptera: Aphididae) is a serious economic pest of barley worldwide. Breeding for aphid resistance in plants is considered a cost-effective and environmentally safe approach for aphid control, compared to the use of chemical pesticides. One of the challenges in breeding for aphid resistance is the identification of resistant plant genotypes, which can be achieved through the use of molecular markers. In the present study, a set of aphid specific 10 simple-sequence repeats (SSR) markers were used to investigate genetic diversity and population structure analyses in 109 barley genotypes against R. maidis. Three statistical methods viz., multivariate hierarchical clustering based on Jaccard’s similarity coefficient, principal coordinate analysis (PCoA) and the Bayesian approach were utilized to classify the 109 barley genotypes. The analyses revealed four subpopulations i.e., SubPop1, SubPop2, SubPop3 and SubPop4 with 19, 46, 20 and 24 genotypes including admixtures, respectively and represented 17.43%, 42.2%, 18.34% and 22.01% genotypes of the total population size, respectively. The studied SSR markers produced 67 polymorphic bands, with an average of 6.7 and ranging from 3 to 12 bands. Heterozygosity (H) was found to be highest in SSR28 (0.64) and lowest in SSR27 (0.89). The observed genetic diversity index varied from 0.10 to 0.34 (with an average of 0.19). Major allele frequency varied from 74.08% to 94.80%. On an average, 87.52% of the 109 barley genotypes shared a common major allele at any locus. Based on the Aphid Infestation Index (AII), only 2 genotypes were found to be resistant against CLA. SubPop2 also had lowest mean aphid population (28.83), widest genetic similarity index (0.60-1.00) and highest genetic similarity coefficient (0.82), which highlighted its potential for inclusion in future CLA resistance breeding programs