Testing the Efficacy of a Polyester Bagging Method for Selfing Switchgrass, and Characterizing Male Sterility in Upland-lowland Switchgrass Hybrids and Their S1 Progenies

Panicum virgatumPlant & Soil Scienc

On metric dimension of cube of trees

Let $G=(V,E)$ be a connected graph and $d_{G}(u,v)$ be the shortest distance between the vertices $u$ and $v$ in $G$. A set $S=\{s_{1},s_{2},\cdots,s_{n}\}\subset V(G)$ is said to be a {\em resolving set} if for all distinct vertices $u,v$ of $G$, there exist an element $s\in S$ such that $d(s,u)\neq d(s,v)$. The minimum cardinality of a resolving set for a graph $G$ is called the {\em metric dimension} of $G$ and it is denoted by $\beta{(G)}$. A resolving set having $\beta{(G)}$ number of vertices is named as {\em metric basis} of $G$. The metric dimension problem is to find a metric basis in a graph $G$, and it has several real-life applications in network theory, telecommunication, image processing, pattern recognition, and many other fields. In this article, we consider {\em cube of trees} $T^{3}=(V, E)$, where any two vertices $u,v$ are adjacent if and only if the distance between them is less than equal to three in $T$. We establish the necessary and sufficient conditions of a vertex subset of $V$ to become a resolving set for $T^{3}$. This helps determine the tight bounds (upper and lower) for the metric dimension of $T^{3}$. Then, for certain well-known cubes of trees, such as caterpillars, lobsters, spiders, and $d$-regular trees, we establish the boundaries of the metric dimension. Further, we characterize some restricted families of cube of trees satisfying $\beta{(T^{3})}=\beta{(T)}$. We provide a construction showing the existence of a cube of tree attaining every positive integer value as their metric dimension

Modeling of Joint Parker Solar Probe - Metis/Solar Orbiter Observations

We present a first theoretical modeling of joint Parker Solar Probe (PSP) - Metis/Solar Orbiter (SolO) quadrature observations Telloni et al 2022c. The combined observations describe the evolution of a slow solar wind plasma parcel from the extended solar corona ($3.5-6.3$ R$_\odot$) to the very inner heliosphere (23.2 R$_\odot$). The Metis/SolO instrument remotely measures the solar wind speed finding a range from $96-201$ kms$^{-1}$, and PSP measures the solar wind plasma in situ, observing a radial speed of 219.34 kms$^{-1}$. We find theoretically and observationally that the solar wind speed accelerates rapidly within 3.3 -- 4 R$_\odot$, and then increases more gradually with distance. Similarly, we find that the theoretical solar wind density is consistent with the remotely and in situ observed solar wind density. The normalized cross-helicity and normalized residual energy observed by PSP are 0.96 and -0.07, respectively, indicating that the slow solar wind is very Alfv\'enic. The theoretical NI/slab results are very similar to PSP measurements, which is a consequence of the highly magnetic field-aligned radial flow ensuring that PSP can measure slab fluctuations and not 2D. Finally, we calculate the theoretical 2D and slab turbulence pressure, finding that the theoretical slab pressure is very similar to that observed by PSP.Comment: 12 pages, 5 figure

Unruptured left ventricular pseudoaneurysm following inferior wall myocardial infarction

Left ventricular (LV) pseudoaneurysm is a rare but potentially lethal complication of acute myocardial infarction (MI). We report a very rare case of a 60 year-old woman with a ruptured myocardial wall, and a non-ruptured LV pseudoaneurysm. The patient presented with acutely worsening shortness of breath and exertional dyspnea of one month’s duration, and palpitation. She had an inferior wall MI nine months previously. Coronary angiography showed severe stenosis at right coronary artery. Echocardiography, LV angiography, and computed tomography angiography revealed a large pseudoaneurysm postero-inferior to the LV. Surgical resection of the pseudoaneurysm was performed and repair of the ruptured LV wall done, with good results. (Cardiol J 2012; 19, 5: 539-542

Chemical profiling and antioxidant activities of essential oil from rhizomes of Acorus calamus L.

Background and Aims: Acorus calamus L. is an indigenous herb in Nepal. It belongs to family Acoraceae and grows in wet land with scented rhizomes. It is also known as Sweet flag in English and commonly as Bojho in Nepal. The present investigation reveals the chemical compositions and antioxidant activity of rhizome essential oil of A. calamus. Methods: Essential oil of rhizomes of Acorus calamus L. from Kaski district, Nepal was extracted by hydrodistillation method and volatile constituents were analyzed Gas chromatography-Mass spectrometry. The antioxidant potential of essential oil was analyzed by 1,1-Diphenyl-2-Picrylhydrazyl (DPPH) scavenging assay. Results: A GC-MS analysis revealed the presence of β-asarone (22.38%), α-asarone (14.97%), 1-(4,6-dimethoxy-2,3-dimethylphenyl ethanone (14.24%), Isoelemicin (5.68%), cis-Methylisoeugenol (4.26%), α-calacorene (4.16%), and other 20 minor components. From DPPH assay, half maximal inhibitory concentration (IC50) value of essential oil was found to be 108.71 µg/mL. Conclusions: These findings have strengthened the A. calamus L. is good source of compounds like β-asarone, α-asarone and can be used as potential antioxidants. BIBECHANA 17 (2020) 89-9

Machine learning driven prediction of lattice constants in transition metal dichalcogenides

Machine learning represents an emerging branch of artificial intelligence, centering on the enhancement of algorithms in computer programs through the utilization of data and the accumulation of research-driven knowledge. The requirement for artificial intelligence in materials science is essential due to the significant need for innovative high-performance materials on a large scale. In this report, the gradient boosting regression tree model of machine learning was applied to predict the lattice constants of cubic and trigonal MX2 systems (M=transition metal and X=chalcogen atoms). The theoretical/experimental values of the materials were compared to the predicted values to calculate the standard errors such as RMSE (root mean square error) and MAE (mean absolute error). The features used to predict lattice constants were ionic radius, lattice angles, bandgap, formation energy, total magnetic moment, density and oxidation states. The features versus contribution barplot has been drawn to reveal the contribution level of each parameter in the degree of [0,1] to obtain the predictions. This report provides a precise account of the prediction methodology for lattice parameters of the transition metal dichalcogenides family, a process that was previously not reported

Chemical profiling and antioxidant activities of essential oil from rhizomes of Acorus calamus L.

Background and Aims: Acorus calamus L. is an indigenous herb in Nepal. It belongs to family Acoraceae and grows in wet land with scented rhizomes. It is also known as Sweet flag in English and commonly as Bojho in Nepal. The present investigation reveals the chemical compositions and antioxidant activity of rhizome essential oil of A. calamus. Methods: Essential oil of rhizomes of Acorus calamus L. from Kaski district, Nepal was extracted by hydrodistillation method and volatile constituents were analyzed Gas chromatography-Mass spectrometry. The antioxidant potential of essential oil was analyzed by 1,1-Diphenyl-2-Picrylhydrazyl (DPPH) scavenging assay. Results: A GC-MS analysis revealed the presence of β-asarone (22.38%), α-asarone (14.97%), 1-(4,6-dimethoxy-2,3-dimethylphenyl ethanone (14.24%), Isoelemicin (5.68%), cis-Methylisoeugenol (4.26%), α-calacorene (4.16%), and other 20 minor components. From DPPH assay, half maximal inhibitory concentration (IC50) value of essential oil was found to be 108.71 µg/mL. Conclusions: These findings have strengthened the A. calamus L. is good source of compounds like β-asarone, α-asarone and can be used as potential antioxidants. BIBECHANA 17 (2020) 89-9

Machine learning driven prediction of lattice constants in transition metal dichalcogenides

Machine learning represents an emerging branch of artificial intelligence, centering on the enhancement of algorithms in computer programs through the utilization of data and the accumulation of research-driven knowledge. The requirement for artificial intelligence in materials science is essential due to the significant need for innovative high-performance materials on a large scale. In this report, the gradient boosting regression tree model of machine learning was applied to predict the lattice constants of cubic and trigonal MX2 systems (M=transition metal and X=chalcogen atoms). The theoretical/experimental values of the materials were compared to the predicted values to calculate the standard errors such as RMSE (root mean square error) and MAE (mean absolute error). The features used to predict lattice constants were ionic radius, lattice angles, bandgap, formation energy, total magnetic moment, density and oxidation states. The features versus contribution barplot has been drawn to reveal the contribution level of each parameter in the degree of [0,1] to obtain the predictions. This report provides a precise account of the prediction methodology for lattice parameters of the transition metal dichalcogenides family, a process that was previously not reported

Evaluation of appropriateness of prescription and polypharmacy in the geriatric population: a cross sectional study at a comprehensive geriatric clinic in a tertiary care hospital

Objective: To assess the prescription quality in a comprehensive geriatric clinic and to determine the frequency of inappropriate prescription and polypharmacy.Methods: Both males and female patients above the age of 60 y attending a comprehensive geriatric clinic of a tertiary care hospital were included in the study. Medications taken by the patients, excluding vitamins, minerals and herbal medications were counted in each patient and analyzed by considering their medical history and using universally accepted tools like medication appropriateness index, START, STOPP & Beer's criteria. In this study, polypharmacy was considered as having 6 or more medications per prescription. Results: A total of 120 patients were included in the study. Around 82 (68.33%) patients had less than 6 prescribed medications and 38 patients (31.66%) were on 6 or more than 6 medications. The number of medications used by the patients is 4.37±2.33. Around 21 (17.5%) were on medications that are not indicated, 25 patients (20.83%) were receiving medications which are to be avoided in elderly as per the Beer's and STOPP criteria. Medication was underused in 24 patients (20%) as per START criteria. When both overused drugs and drugs to be avoided were considered for assessment of inappropriateness, 39 patients (32.5%) were found to be receiving inappropriate medication. Among the drugs to be avoided in elderly, amitriptyline was the most common drug and was used in 15 (12.5%) patients. Antihypertensives were the most common potential prescribing omissions in geriatric patients.Conclusion: Polypharmacy is seen in a significant proportion of geriatric patients. Inappropriate prescription and potential prescribing omissions were observed in a significant proportion of geriatric patients.Keywords: Polypharmacy, Geriatrics, Beer's criteria, STOPP criteri

Turbulent Transport in a Three-dimensional Solar Wind

Turbulence in the solar wind can play essential roles in the heating of coronal and solar wind plasma and the acceleration of the solar wind and energetic particles. Turbulence sources are not well understood and thought to be partly enhanced by interaction with the large-scale inhomogeneity of the solar wind and the interplanetary magnetic field and/or transported from the solar corona. To investigate the interaction with background inhomogeneity and the turbulence sources, we have developed a new 3D MHD model that includes the transport and dissipation of turbulence using the theoretical model of Zank et al. We solve for the temporal and spatial evolution of three moments or variables, the energy in the forward and backward fluctuating modes and the residual energy and their three corresponding correlation lengths. The transport model is coupled to our 3D model of the inhomogeneous solar wind. We present results of the coupled solar wind-turbulence model assuming a simple tilted dipole magnetic configuration that mimics solar minimum conditions, together with several comparative intermediate cases. By considering eight possible solar wind and turbulence source configurations, we show that the large-scale solar wind and IMF inhomogeneity and the strength of the turbulence sources significantly affect the distribution of turbulence in the heliosphere within 6 au. We compare the predicted turbulence distribution results from a complete solar minimum model with in situ measurements made by the Helios and Ulysses spacecraft, finding that the synthetic profiles of the turbulence intensities show reasonable agreement with observations