Thermal conductivity of comets

A value is described for the thermal conductivity of the frost layer and for the water-ice solid debris mixture. The value of the porous structure is discussed as a function of depth only. Graphs show thermal conductivity as a function of depth and temperature at constant porosity and density

PREVENTING APATHYANIMITTAJA MADHUMEHA - AN AYURVEDIC APPROACH

Prevention is always better than cure especially in diseases such as Type 2 DM which is fast gaining the status of a potential epidemic in India with more than 62 million diabetic individuals currently diagnosed with the disease. The disease Madhumeha can be correlated with Type 2 DM. The disease is characterized by metabolic abnormalities and long term complications involving the eyes, kidneys, nerves and blood vessels. Madhumeha being an Anushangi vyadhi will make the person suffer for life time. Complications are further more difficult to treat. Hence it is always recommended in Ayurvedic classics to prevent the manifestation of diseases as much as possible and also to prevent the Upadravas if Madhumeha is already manifested. A good and proper diet in disease is worth a hundred medicines and no amount of medication can do well to a patient who does not follow a strict regimen of diet. Pathya ahara is the first and foremost step while considering the prevention of Madhumeha. Another factor which has important role in the disease manifestation is improper Vihara which can be considered for increased urbanisation, high prevalence of obesity, sedentary lifestyles and stress. Healthy life style has a key role in preventing Madhumeha and also to ease the life with Madhumeha by delaying the complications. Hence the present study is aimed at collecting and compiling various preventive measures which are explained by our Ayurvedic Acharyas to prevent Madhumeha and its complications

Thermal conductivity of heterogeneous mixtures and lunar soils

The theoretical evaluation of the effective thermal conductivity of granular materials is discussed with emphasis upon the heat transport properties of lunar soil. The following types of models are compared: probabilistic, parallel isotherm, stochastic, lunar, and a model based on nonlinear heat flow system synthesis

Use of Low-Cost Ambient Particulate Sensors in Nablus, Palestine with Application to the Assessment of Regional Dust Storms

Few air pollutant studies within the Palestinian territories have been reported in the literature. In March–April and May–June of 2018, three low-cost, locally calibrated particulate monitors (AirU’s) were deployed at different elevations and source areas throughout the city of Nablus in Northern West Bank, Palestine. During each of the three-week periods, high but site-to-site similar particulate matter less than 2.5 µm in aerodynamic diameter (PM2.5) and less than 10 µm (PM10) concentrations were observed. The PM2.5 concentrations at the three sampling locations and during both sampling periods averaged 38.2 ± 3.6 µg/m3, well above the World Health Organization’s (WHO) 24 h guidelines. Likewise, the PM10 concentrations exceeded or were just below the WHO’s 24 h guidelines, averaging 48.5 ± 4.3 µg/m3. During both periods, short episodes were identified in which the particulate levels at all three sites increased substantially (≈2×) above the regional baseline. Air mass back trajectory analyses using U.S. National Oceanic and Atmospheric Administration’s (NOAA) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model suggested that, during these peak episodes, the arriving air masses spent recent days over desert areas (e.g., the Saharan Desert in North Africa). On days with regionally low PM2.5 concentrations (≈20 µg/m3), back trajectory analysis showed that air masses were directed in from the Mediterranean Sea area. Further, the lower elevation (downtown) site often recorded markedly higher particulate levels than the valley wall sites. This would suggest locally derived particulate sources are significant and may be beneficial in the identification of potential remediation options

Business Innovation through knowledge sharing: An applied study on the Jordanian Mobile Telecommunications Sector

The study aimed to identify and examine the influence of the individual and organizational knowledge sharing enablers on knowledge sharing behavior that leads to develop firm innovation capability. A descriptive analytical methodology approach was adopted in this research. For the purpose of data collection; a questionnaire was developed and administered for collecting data from the sample. 150 questionnaires were distributed randomly to employees in the managerial and development levels of the companies, (98) retrieved and (95) were accepted for analysis. After that, data analysis took place to examine the study variables. After conducting the analysis, the study found that while there is a positive effect of the individual factor “enjoyment in helping others” and the organizational factor “top management support” on the employee knowledge sharing behavior. There is no influence of the individual factor “knowledge self efficacy” and the organizational factor “organizational rewards” on the employee knowledge sharing behavior. Keywords: knowledge sharing, innovation, telecommunications, Jorda

On-The-Road Testing of the Effects of Driver’s Experience, Gender, Speed, and Road Grade on Car Emissions

On-road vehicles have become a dominant source of air pollution and energy consumption in many parts of the world. As a result, estimating the amount of pollution from these vehicles and analyzing the factors affecting their emission is necessary to understand and manage ambient air quality. Traditionally, automobile emissions have been measured with dynamometer tests using representative driving cycles. A review of the related literature shows that there is a lack of real life, on-the-road testing of automobile emissions. Moreover, a few previous studies have directly discussed the impact of driver variability on emissions from the vehicles. This research analyzes the impacts of driver experience, gender, speed, and road grade on vehicle emissions through on-the-road testing experiment in Logan, Utah, USA during summer of 2016. The methodology of the research starts by selecting a representative car to perform the tests on. The next step was to choose test drivers representing four groups: young males, young females, experienced males, and experienced females. After that, the drivers were assigned a specified route that has different speed limits and grades. Emissions from the car exhaust (specifically carbon monoxide-CO, hydrocarbons-HC, and nitrogen oxides-NOx) in addition to the engines rotational speed (rpm), car speed, and exhaust temperature, were measured every second while driving on the specified route. Statistical analysis of the results shows that contrary to the common stereotypes, experienced drivers emitted 52% more HC and 49% more NOx than young drivers and female drivers, and male drivers emitted 14% more HC and 44% more NOx than female drivers. It also shows that CO emission is not significantly dependent on age, gender, nor driving conditions. Finally, driving through low-speed segments emits significantly higher HC (79%), while driving through uphill segments emits significantly higher (98%) NOx than driving through downhill segment

Active and stable methane oxidation nano-catalyst with highly-ionized palladium species prepared by solution combustion synthesis

We report on the synthesis and testing of active and stable nano-catalysts for methane oxidation. The nano-catalyst was palladium/ceria supported on alumina prepared via a one-step solution-combustion synthesis (SCS) method. As confirmed by X-ray photoelectron spectroscopy (XPS) and high-resolution transmission electron microscopy (HTEM), SCS preparative methodology resulted in segregating both Pd and Ce on the surface of the Al 2 O 3 support. Furthermore, HTEM showed that bigger Pd particles (5 nm and more) were surrounded by CeO 2 , resembling a core shell structure, while smaller Pd particles (1 nm and less) were not associated with CeO 2 . The intimate Pd-CeO 2 attachment resulted in insertion of Pd ions into the ceria lattice, and associated with the reduction of Ce 4+ into Ce 3+ ions; consequently, the formation of oxygen vacancies. XPS showed also that Pd had three oxidation states corresponding to Pd0, Pd 2+ due to PdO, and highly ionized Pd ions (Pd (2+x)+ ) which might originate from the insertion of Pd ions into the ceria lattice. The formation of intrinsic Ce 3+ ions, highly ionized (Pd2+ species inserted into the lattice of CeO 2 ) Pd ions (Pd (2+x)+ ) and oxygen vacancies is suggested to play a major role in the unique catalytic activity. The results indicated that the Pd-SCS nano-catalysts were exceptionally more active and stable than conventional catalysts. Under similar reaction conditions, the methane combustion rate over the SCS catalyst was ~18 times greater than that of conventional catalysts. Full methane conversions over the SCS catalysts occurred at around 400 C but were not shown at all with conventional catalysts. In addition, contrary to the conventional catalysts, the SCS catalysts exhibited superior activity with no sign of deactivation in the temperature range between ~400 and 800 C. 2018 by the authors. Licensee MDPI, Basel, Switzerland.Acknowledgments: This paper was made possible by an NPRP Grant #6-290-1-059 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Stress Degradation Studies on Varenicline Tartrate and Development of a Validated Stability-Indicating HPLC Method

A simple, rapid and stability-indicating reversed-phase liquid chromatographic method was developed for the assay of varenicline tartrate (VRT) in the presence of its degradation products generated from forced decomposition studies. The HPLC separation was achieved on a C18 Inertsil column (250 mm × 4.6 mm i.d. particle size is 5 μm) employing a mobile phase consisting of ammonium acetate buffer containing trifluoroacetic acid (0.02M; pH 4) and acetonitrile in gradient program mode with a flow rate of 1.0 mL min−1. The UV detector was operated at 237 nm while column temperature was maintained at 40 °C. The developed method was validated as per ICH guidelines with respect to specificity, linearity, precision, accuracy, robustness and limit of quantification. The method was found to be simple, specific, precise and accurate. Selectivity of the proposed method was validated by subjecting the stock solution of VRT to acidic, basic, photolysis, oxidative and thermal degradation. The calibration curve was found to be linear in the concentration range of 0.1–192 μg mL−1 (R2 = 0.9994). The peaks of degradation products did not interfere with that of pure VRT. The utility of the developed method was examined by analyzing the tablets containing VRT. The results of analysis were subjected to statistical analysis

Differentiating Noninvasive Follicular Thyroid Neoplasm with Papillary-Like Nuclear Features from Classic Papillary Thyroid Carcinoma: Analysis of Cytomorphologic Descriptions Using a Novel Machine-Learning Approach.

Background:Recent studies show various cytomorphologic features that can assist in the differentiation of classic papillary thyroid carcinoma (cPTC) from noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP). Differentiating these two entities changes the clinical management significantly. We evaluated the performance of support vector machine (SVM), a machine learning algorithm, in differentiating cases of NIFTP and encapsulated follicular variant of papillary thyroid carcinoma with no capsular or lymphovascular invasion (EFVPTC) from cases of cPTC with the use of microscopic descriptions. SVM is a supervised learning algorithm used in classification problems. It assigns the input data to one of two categories by building a model based on a set of training examples (learning) and then using that learned model to classify new examples. Methods:Surgical pathology cases with the diagnosis of cPTC, NIFTP, and EFVPTC, were obtained from the laboratory information system. Only cases with existing fine-needle aspiration matching the tumor and available microscopic description were included. NIFTP cases with ipsilateral micro-PTC were excluded. The final cohort consisted of 59 cases (29 cPTCs and 30 NIFTP/EFVPTCs). Results:SVM successfully differentiated cPTC from NIFTP/EFVPTC 76.05 ± 0.96% of times (above chance, P \u3c 0.05) with the sensitivity of 72.6% and specificity of 81.6% in detecting cPTC. Conclusions:This machine learning algorithm was successful in distinguishing NIFTP/EFVPTC from cPTC. Our results are compatible with the prior studies, which show cytologic features are helpful in differentiating these two entities. Furthermore, this study shows the power and potential of this approach for clinical use and in developing data-driven scoring systems, which can guide cytopathology and surgical pathology diagnosis

Numerical Studies for Solving Fractional Riccati Differential Equation

In this paper, finite difference method (FDM) and Pade\u27-variational iteration method (Pade\u27- VIM) are successfully implemented for solving the nonlinear fractional Riccati differential equation. The fractional derivative is described in the Caputo sense. The existence and the uniqueness of the proposed problem are given. The resulting nonlinear system of algebraic equations from FDM is solved by using Newton iteration method; moreover the condition of convergence is verified. The convergence\u27s domain of the solution is improved and enlarged by Pade\u27-VIM technique. The results obtained by using FDM is compared with Pade\u27-VIM. It should be noted that the Pade\u27-VIM is preferable because it always converges to the solution even for large domain