Evaluation of fracture treatment type on the recovery of gas from the cotton valley formation

Every tight gas well needs to be stimulated with a hydraulic fracture treatment to produce natural gas at economic flow rates and recover a volume of gas that provides an acceptable return on investment. Over the past few decades, many different types of fracture fluids, propping agents and treatment sizes have been tried in the Cotton Valley formation. The treatment design engineer has to choose the optimum fluid, optimum proppant, optimum treatment size and make sure the optimum treatment is mixed and pumped in the field. These optimum values also depend on drilling costs, fracturing costs and other economic parameters; such as gas prices, operating costs and taxes. Using information from the petroleum literature, numerical and analytical simulators, and statistical analysis of production data, this research provides a detailed economic evaluation of the Cotton Valley wells drilled in the Elm Grove field operated by Matador Resources to determine not only the optimum treatment type, but also the optimum treatment volume as a function of drilling costs, completion costs, operating costs and gas prices. This work also provides an evaluation of well performance as a function of the fracture treatment type by reviewing production data from the Carthage and Oak Hill Cotton Valley fields in Texas and the Elm Grove field in Louisiana

Speech to text translation enabling multilingualism.

Speech acts as a barrier to communication between two individuals and helps them in expressing their feelings, thoughts, emotions, and ideologies among each other. The process of establishing a communicational interaction between the machine and mankind is known as Natural Language processing. Speech recognition aids in translating the spoken language into text. We have come up with a Speech Recognition model that converts the speech data given by the user as an input into the text format in his desired language. This model is developed by adding Multilingual features to the existent Google Speech Recognition model based on some of the natural language processing principles. The goal of this research is to build a speech recognition model that even facilitates an illiterate person to easily communicate with the computer system in his regional language

ANTIFERTILITY ACTIVITY OF DECASCHISTIA CROTONIFOLIA LEAF EXTRACT ON MALE RATS

Objective: The objective was to investigate the male antifertility effect of Decaschistia crotonifolia leaf extract on male Wistar rats. Methods: The animals were divided into three groups of five animals each. The first group (I) served as control and received normal saline, and remaining Groups II and III were treated with plant extract at a dose of 200 and 400 mg/kg p.o., respectively, for 21 days. Results: Dose-dependent significant decrease in the weight of testes and epididymis was observed. Furthermore, a dose-related reduction in sperm count and motility was observed. A significant decrease in testosterone levels leading to infertility was also observed. Conclusion: The 70% methanolic leaf extract of D. crotonifolia has produced dose-dependent antifertility effect on male rats

Tripletformer for Probabilistic Interpolation of Irregularly sampled Time Series

Irregularly sampled time series data with missing values is observed in many fields like healthcare, astronomy, and climate science. Interpolation of these types of time series is crucial for tasks such as root cause analysis and medical diagnosis, as well as for smoothing out irregular or noisy data. To address this challenge, we present a novel encoder-decoder architecture called "Tripletformer" for probabilistic interpolation of irregularly sampled time series with missing values. This attention-based model operates on sets of observations, where each element is composed of a triple of time, channel, and value. The encoder and decoder of the Tripletformer are designed with attention layers and fully connected layers, enabling the model to effectively process the presented set elements. We evaluate the Tripletformer against a range of baselines on multiple real-world and synthetic datasets and show that it produces more accurate and certain interpolations. Results indicate an improvement in negative loglikelihood error by up to 32% on real-world datasets and 85% on synthetic datasets when using the Tripletformer compared to the next best model

IMAGE TRANSMISSION BASED POWER COMPARISON ANALYSIS OF MC-CDMA SYSTEMS

In many applications retransmission of lost packets are not permitted. In an OFDM system, due to channel fading, only a subset of carriers are usable for successful data transmission. If the channel state information is available at the transmitter, it is possible to take a proactive decision of mapping the descriptions optimally onto the good subcarriers and discard at the transmitter itself the remaining descriptions, which would have been otherwise dropped at the receiver due to unacceptably high channel errors. In this paper we present an energy saving approach to transmission of discrete wavelet transformation based compressed image frames over the OFDM channels. Based on one-bit channel state information at the transmitter, the descriptions in order of descending priority are assigned to the currently good channels. In order to reduce the system power consumption, the mapped descriptions onto the bad sub channels are dropped at the transmitter. Via analysis, supported by MATLAB simulations, we demonstrate the usefulness of our proposed scheme in terms of system energy saving without compromising the received quality in terms of peak signal-noise ratio

TiO2 multi-leg nanotubes for surface-enhanced Raman scattering

In the recent past, significant research efforts have been put forth to fabricate cost-effective substrates for surface-enhanced Raman scattering (SERS) applications. Here we propose semiconducting TiO2 multi-leg nanotubes and Au nanoparticle-coated TiO2 multi-leg nanotubes (TiO2 MLNTs and Au/TiO2 MLNTs) as SERS substrates. The unique multi-leg architecture of TiO2 nanotubes demonstrated enhanced light-harvesting properties facilitated by an induced photonic absorption edge. Remarkable high SERS sensitivity is observed towards the detection of Methylene blue (MB), up to nM concentration (E.F. ∼104) using TiO2 MLNTs. The same is attributed to the resonantly matched photonic absorption edge of TiO2 MLNTs with the wavelength of incident laser probe light. On the other hand, the Au nanoparticle coating further leveraged the light absorption ability of TiO2 MLNTs with the aid of localized surface plasmon resonance mode. As such, Au/TiO2 MLNTs showed excellent enhancement in SERS sensitivity (E.F. ∼105, for nM of MB) facilitated by the synergy between the plasmonic modes of Au and the photonic absorption mode of TiO2 MLNTs. UV-Vis diffuse reflectance and Raman spectroscopy measurements are highlighted to elucidate the light absorption and SERS sensitivity of the TiO2 and Au/TiO2 MLNTs

A New Validated Liquid Chromatographic Method for the Determination of Loratadine and its Impurities

An improved gradient, reversed-phase liquid chromatographic (RP-LC) method was developed and subsequently validated for the determination of Loratadine and its impurities/degradation products in pharmaceutical drug substance. Separation was achieved with Inertsil ODS-3V, 250 × 4.6 mm, 5μ column with gradient elution at a flow rate of 1.0 mL min−1. UV detection was performed at 220 nm. The described method is linear over a range of LOQ (0.044, 0.088, 0.084, and 0.072 μg mL−1 for impurity-B, impurity-C, impurity-D, and impurity-E respectively) to 1.2 μg mL−1 (0.6 μg mL−1 of the specification limit) for all the impurities and degradation products. The recovery of impurities were found to be in the range of 85–115 %. The method is simple, selective, and accurate for the quantification of impurities and degradation products of Loratadine in its bulk drug samples

GR-273 Building a Chatbot

A chatbot is now a part of many online applications like Health Care, Education, E-commerce, etc. It made the conversation between the customers and the service providers much more convenient as the chatbot can answer most of the queries without human intervention from the website side. This saves a lot of time and work

Primary Hepatic Leiomyosarcoma Report of a rare case with review of literature

Primary hepatic leiomyosarcoma is an extremely rare tumor with a dismal prognosis and difficulty in diagnosis. We present a 36-year-old female who presented with complaints of pain in right hypochondrium and epigastric region. Real-time ultrasonography revealed an enlarged liver with multiple hypoechoic lesions of varying sizes in both the lobes of the liver. USG guided core biopsy from the lesion showed an infiltrating malignant spindle cell neoplasm positive for smooth muscle actin and caldesmon-H confirming the diagnosis of leiomyosarcoma. It is vital to diagnose these lesions even on limited biopsies as early diagnosis can reduce hospital and operative morbidity and mortality rates in the patients