Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneous Determination of Atenolol, Rosuvastatin, Spironolactone, Glibenclamide and Naproxen Sodium in Pharmaceutical Formulations and Human Plasma by RP‐HPLC

A rapid and sensitive high-performance liquid chromatographic method was developed and validated for the simultaneous determination and quantification of atenolol, rosuvastatin, spimolactone, glibenclamide and naproxen sodium in bulk drugs, pharmaceutical formulations and in human plasma in the presence of internal standard (flurbiprofen). Chromatograms were developed with methanol and water (80:20, v/v) solvent system on a Purospher start, C 18 (5 μm, 250 x 4.6 mm) column and pH was adjusted to 3.40 with ortho-phosphoric acid. Mobile phase was pumped with a flow rate of 0.90 mL/minute with 235 nm UV detection. Standard curves were linear over the concentration range 0.25 -30 μg/mL -1 . The coefficients of variation (C.V. %), were < 3% and LOD and LOQ were < 0.0154 & 0.06 for inter- and intra-day, respectively. The method was applied to drug interaction studies of atenolol with rosuvastatin, spironolactone, glibenclamide and naproxen to illustrate the scope and application of the methods to manage four different therapeutic classes of drugs, as they are co-administered.
The influence of parent material and livestock intensification on plant‐available phosphorus values by the Olsen method in Northern Ireland

Abstract. Leaching of phosphorus (P) from agricultural land is the major cause of eutrophication of surface waters in Northern Ireland. However, soil testing using the Olsen method has shown that while soil P in some catchment areas of the Province is low, surface waters within these catchments are, nonetheless, every bit as eutrophic as other local catchments where soil P is high. Soil P measurements on over 6000 samples from Northern Ireland soils (A horizon only) have indicated that Olsen‐P values of improved grassland on most parent materials are linearly related to animal intensification. Exceptions are soils derived from peat, marl and basalt. For each of the latter soils, the measured Olsen‐P was shown to be around 10 mg L–1 lower than expected for farms with similar intensification on other parent materials. In particular, the mean Olsen‐P values of samples from basaltic soils under grass with total Fe above 62 g kg–1 and total Mg above 16 g kg–1 were significantly lower than those from basaltic soils with low total Fe (<37 g kg–1) and total Mg (<8 g kg–1). As a result of the depressed Olsen‐P value, excessive quantities of P may be applied to these soils to maintain a recommended soil P index thereby enhancing the potential for nutrient enrichment of adjacent surface waters. In such cases, coworkers have shown that acid ammonium oxalate may be a better extractant than bicarbonate as an indicator of plant‐available P.
The Main Role of Family Environment During COVID-19 Quarantine

This paper describes the role of the family environment during the COVID-19 quarantine. COVID-19 outbreak has attacked various regions in Indonesia; this has made both central and regional governments issued an appeal to avoid crowds and activities at home, including teaching and learning activities. However, home learning activities undertaken by students were considered less effective; there were still many students who left the house and did not do learning activities at home. This phenomenon could be minimized by the involvement of parents in learning activities during the quarantine period, which until now has not been certain when it will end. Parents need to increase their children's awareness and guide them to learn. In addition, during this quarantine period, children can use the time to memorize the Al-Qur'an. This program was carried out to educate parents about the importance of parents’ involvement in learning activities at home and memorizing the AlQur'an for children in the environment around the Matahari Pocis Community Reading Park. This activity involves the Matahari Pocis Community Reading Park as a partner and society around. The results achieved by this activity were children were able to memorize the Al-Qur'an in accordance with predetermined targets. Some children could memorize independently, while some others still need to be reminded. Other results showed that parents were involved in memorizing the Al-Qur'an and teaching and learning activities during the
Adaptive Multilooking of Multitemporal Differential SAR Interferometric Data Stack Using Directional Statistics

In this article, we present an innovative space–time adaptive multilooking technique that operates on a sequence of multitemporal, differential synthetic aperture radar interferograms. The developed approach relies on the application of the fundamentals of directional statistics theory. At variance with other methods that identify the set of statistically homogenous pixels (SHPs) within a multilooking (complex averaging) window based on the statistics of the single-look-complex (SLC) SAR images, the proposed method is exclusively based on the analysis of the multitemporal sequence of full resolution DInSAR interferograms. The SHPs are then used to generate spatially adaptive multilooked interferograms both at the native, full-scale grid of the SLC images and at the multilooked resolution scale. The algorithm is effective and simple to implement, only requiring the availability of a sequence of full-scale differential SAR interferometry (DInSAR) interferograms. The interferograms can then be used to generate ground displacement time-series through advanced multitemporal interferometric SAR (MTInSAR) approaches. Experimental results obtained by applying the adopted technique to two SAR data sets acquired at X- and L-band, respectively, demonstrate the validity of the developed method.
Query transformation for multi-lingual product search

In this paper, we study the problem of enabling multi-lingual product search for a global shopping store. In particular, given an existing search system and product catalog in a primary language, and a search query in a secondary language, transform the query into a semantically equivalent one in the primary language in order to retrieve the most relevant products. Direct application of machine translation does not always work well in this application due to several factors: 1) lack of consideration of the search system’s response to a transformed search query, 2) sensitivity to spelling/grammatical errors, 3) fragility to inputs in a language that is different from the ones the search system is trained for, and 4) poor handling of named entities (e.g. brand names, model numbers). To address these challenges, we propose a Query Transformation system that consists of 1) a language identifier to detect the language of the input query, 2) a deep neural machine translation model fine-tuned on human-curated parallel query corpus and learned, during training, to copy entities such as model numbers, and 3) a traffic re-ranker which selects the transformation that may help the search system retrieve the most relevant products. Furthermore, we show that standard machine translation evaluation metrics such as BLEU are unsuitable for this application. Therefore, we propose a new offline performance metric that measures how accurately a transformed query reflects customer’s shopping intent and how well the existing search system responds to the transformed query. We present compelling offline and online results: 11% and 3% in improvements in offline nDCG@8 for Spanish (ES) → English (EN) and French (FR) → EN, and 10% and 22% in reduction in online product type search defects for ES → EN and FR → EN, respectively, over a state-of-the-art statistical machine translation system for product search.
The Correct Replacement for the Wrong Starling’s law is the Hydrodynamic of the Porous Orifice (G) Tube: The Complete Physics and physiological Evidence with Clinical Relevance and Significance

Introduction and objective To report the complete evidence that Starling's law is wrong, and the correct replacement is the hydrodynamic of the G tube detailed. New physiological evidence is provided with clinical relevance and significance. Material and methods The physics proof is based on G tube hydrodynamic. Physiological proof is based on study of the hind limb of sheep: running plasma and later saline through the artery compared to that through the vein as regards the formation of oedema. The clinical significance is based on 2 studies one prospective and a 23 cases series on volumetric overload shocks (VOS). Results Hydrodynamic of G tube showed that proximal, akin to arterial, pressure induces suction "absorption" not "filtration". In Poiseuille’s tube side pressure is all positive causing filtration based on which Starling proposed his hypothesis, The physiological evidence proves that the capillary works as G tube not Poiseuille's tube: Oedema occurred when fluids are run through the vein but not through the artery. There was no difference using saline or albumin. The wrong Starling's law dictates the faulty rules on fluid therapy inducing VOS causing ARDS. Conclusion Hydrodynamic of the G tube challenges the role attributed to arterial pressure as filtration force in Starling’s law. A literature review shows that oncotic pressure does not work either. The new hydrodynamic of G tube is proposed to replace Starling’s law which is wrong on both forces. The physiological proof and relevance to clinical importance on the pathogenesis of clinical syndromes are discussed. The puzzles of TURP syndrome, Dilution HN and ARDS are resolved.
Entrepreneur’s Experience as Business angels’ and Venture Capitalists’ Decision criteria

There are many business angels’ and venture capitalists’ decision criteria they apply when they are assessing business proposals of entrepreneurs asking for investment. Entrepreneur’s experience and experience of his/her team are considered as the most important of all criteria related to the entrepreneur. Using theoretical literature analysis we investigated experience as decision criteria used by business angels and venture capitalists and some limitation of their usage. We found that there are many types of experience available and identified several limitations for applying them in the decision process. In the empirical literature, there are discussed various types of experience such as professional experience, industry experience, managerial experience, leadership experience, domain-specific experience, entrepreneurial experience, start-up experience, international experience, work experience, track record and functional experience (production, marketing, financial etc.).
Lattice Constants and Thermal Expansion Coefficient of Air Clathrate Hydrate in Deep Ice Cores from Vostok, Antarctica

We measured the temperature-dependent lattice constant of air hydrates in deep ice cores from Vostok, Antarctica, using single-crystal X-ray diffraction. Thus the thermal expansion coefficient was determined, the first for a structure II clathrate hydrate containing small guest molecules. Despite their high dissociation pressures, measurements were done at atmospheric pressure because the air hydrates had stabilized during their original residence at high pressure. At 200 K, the lattice constant and thermal expansion coefficient were 17.20 A and 44 (±9) × 10-6 K-1, respectively. This thermal expansion coefficient is approximately equal to that from tetrahydrofuran hydrate, another structure II hydrate, but the lattice constant is 0.3% smaller. Crystal structure refinement determined that the total cage occupancy by air molecules was 0.9.
The Effects of Message Tone and Formats of CSR Messages on Engagement in Social Media

As more consumers are interested in sustainability issues and evaluate brands based on their social responsibility issues involved, firms are using social media platforms in order to communicate with consumers about Corporate Social Responsibility (CSR) activities. However, the current literature focuses mostly on factors drive engagement of promotional messages, while little evidence was found in the literature on how to design effective CSR messages on social media to engage consumers. Using over 3,000 branded posts on Facebook and Twitter, this research explores factors that help CSR messages become more engaging in social media. The results show that, on average, CSR messages had a negative significant effect on consumer engagement. However, CSR messages became more engaging when designed with emotional appeals, longer texts, and a hashtag. While marginal, CSR messages with informational appeals and humor undermined the effect of CSR messages on engagement. Finally, we explore different types of CSR messages by their beneficiary scope and the role of brands in the message and discuss what message contents drive more engagement in social media. This research contributes to the academic literature and managers by providing new insights on how to design CSR messages for effective communications in social media.
The effect of Tamoxifen on Indomethacin induced hepato-nephrotoxicity in rats

Background: Indomethacin is a widely prescribed nonsteroidal anti-inflammatory drug (NSAID) with a known hepato-renal toxicity. Tamoxifen is the treatment of choice for women with estrogen receptor-positive breast cancer. Aim: This study was aimed to investigate the effects of tamoxifen (TAM) on renal toxicity and hepatic damage induced by indomethacin (IND) in rats. Methods: Hepato-renal toxicity was induced in female Wistar rats by a single dose of IND (150 mg/kg) administered by gavage. TAM pretreatment involved Subcutaneous (SC) administration of the drug in a dose of 0.5 mg/kg/day for 5 consecutive days. Assessment of liver and kidney toxicities was based on determination of the activity of liver enzymes sGPT, sGOT, ALP, serum urea and serum creatinine as well as the ratio of liver and kidneys weight to total body weight and on histopathological evaluation. Results: Oral administration of IND produced a significant elevation in liver and kidneys weight ratio, sGOT, sGPT, serum urea and serum creatinine levels compared to negative control group. The pretreatment with TAM 0.5mg/kg before induction of IND toxicity, resulted in significant reduction in serum urea, creatinine and liver enzymes activity and significantly protected the liver and the kidneys from injury induced by IND. Histopathological examination of kidneys and livers confirmed the protective effect of TMA. This protection by TAM may be related to its scavenging activity of free radicals, its antioxidant properties or to stimulation of ERs by TAM and its metabolites. Conclusion: This study may suggest that the pretreatment with multiple low doses of TAM will significantly reduce INDinduced hepato-renal toxicity.
New Approach for Indoor Positioning With Wi-Fi Using Quadratic Antenna Arrays

This letter provides a versatile solution for indoor positioning systems (IPS). Existing IPS designs are either accurate but complicated, or simple yet not accurate. All of the available solutions solely target positioning. In this letter, a novel idea is proposed as a proof of concept, which can be augmented in the IEEE 802.11 standards. The proposed concept offers adjustable positioning accuracy, along with the provision of networking. It is based on designing two steering quadratic phased antenna arrays providing two orthogonal footprints intersecting at the location of interest. With a distinct service set identifier (SSID) associated with each footprint, determining the position becomes straightforward. Some scenarios are possible for maintaining the communication aspects of the IEEE 802.11. Two quadratic microstrip antenna arrays and two feeding circuits with phase shifters are used to achieve the steer. The letter includes the RF design, simulation and analysis for further illustration.
A comparison between extended aeration sludge and conventional activated sludge treatment for removal of linear alkylbenzene sulfonates (Case study: Kermanshah and Paveh WWTP)

Linear alkylbenzene sulfonates (LASs) are anionic surfactants with extensive application as detergents. Discharge of wastewater containing these chemicals results in negative environmental impacts. In the present study, the process performance of an extended aeration activated sludge (EAAS) system in Paveh’s wastewater treatment plant (WWTP) and a conventional activated sludge (CAS) system in Kermanshah’s WWTP removing LAS and chemical oxygen demand (COD) were compared. The amounts of LAS removal in the CAS and the EAAS systems were calculated as 93.73 and 96.7%, respectively. It was concluded that EAAS system may be used for treating municipal wastewater with better LAS, COD, and total suspended solids (TSS) removal efficiency compared with CAS system.
Simulating dynamics of –13C of CO2 in the planetary boundary layer over a boreal forest region: covariation between surface fluxes and atmospheric mixing

Stable isotopes of CO2 contain unique information on the biological and physical processes that exchange CO2 between terrestrial ecosystems and the atmosphere. Ecosystem exchange of carbon isotopes with the atmosphere is correlated diurnally and seasonally with the planetary boundary layer (PBL) dynamics. The strength of this kind of covariation affects the vertical gradient of δ13C and thus the global δ13C distribution pattern. We need to understand the various processes involved in transport/diffusion of carbon isotope ratio in the PBL and between the PBL and the biosphere and the troposphere. In this study, we employ a one-dimensional vertical diffusion/transport atmospheric model (VDS), coupled to an ecosystem isotope model (BEPS-EASS) to simulate dynamics of 13CO2 in the PBL over a boreal forest region in the vicinity of the Fraserdale (FRD) tower (49°52’29.9”N, 81°34’12.3”W) in northern Ontario, Canada. The data from intensive campaigns during the growing season in 1999 at this site are used for model validation in the surface layer. The model performance, overall, is satisfactory in simulating the measured data over the whole course of the growing season.We examine the interaction of the biosphere and the atmosphere through the PBL with respect to δ13C on diurnal and seasonal scales. The simulated annual mean vertical gradient of δ13C in the PBL in the vicinity of the FRD tower was about 0.25‰ in 1999. The δ13C vertical gradient exhibited strong diurnal (29%) and seasonal (71%) variations that do not exactly mimic those of CO2. Most of the vertical gradient (96.5% ±) resulted from covariation between ecosystem exchange of carbon isotopes and the PBL dynamics, while the rest (3.5%±) was contributed by isotopic disequilibrium between respiration and photosynthesis. This disequilibrium effect on δ13C of CO2 dynamics in PBL, moreover, was confined to the near surface layers (less than 350 m).
Spatio-Temporal Optimization of Deep Neural Networks for Reconfigurable FPGA SoCs

This article proposes a technique for optimizing the timing performance and the resource consumption of hardware accelerators for deep neural network (DNN) inference on FPGA-based system-on-chips (SoC). When required, the accelerators are decomposed into chunks, each exploiting at best the available FPGA area, and dynamic partial reconfiguration (DPR) is leveraged to schedule such chunks at run-time. To this end, the article presents accurate models of the resource consumption and timing of DNN accelerators provided by the Xilinx FINN framework. The models are then used to formulate an optimization problem that computes the optimal decomposition of DNN accelerators (and their configuration) by minimizing the inference time while ensuring area constraints on the FPGA. Experimental results on Zynq-7000 platforms demonstrate that the proposed technique provides consistent improvements with respect to both stock configurations of the accelerators and other configurations that can be obtained with a static FPGA allocation.
Origin of glassy crystalline behavior in the thermal properties of clathrate hydrates: a thermal conductivity study of tetrahydrofuran hydrate

The thermal conductivity of tetrahydroruran hydrate was measured from 15 to 100 K. The present data complement earlier measurements at higher temperatures and confirm the speculation on the glassy behavior in the tehermal conductivity of clarathrate hydrates. The experimental results can be interpreted by using a resonant scattering mechanism. The interactions between localized low-frequency vibrations of the guest molecules with the acoustic phonons of the host lattice are responsible for the thermal glassy behavior of the clathrate hydrates, despite their well-defined crystalline structures
Financial Literacy and Intertemporal Arbitrage

We study the role of financial literacy for inter-temporal decision-making using an adapted version of the Convex Time Budget Protocol (Andreoni and Sprenger 2012). While we find no evidence of dynamically inconsistent preferences in the aggregate, we document substantial heterogeneity in choice-patterns and estimated parameters at the individual-level: We find that subjects with higher levels of financial literacy are more likely to make patient inter-temporal choices, to allocate the entire budget to a single payment-date, allocate the entire budget to corner choices as interest rates increase, and to show individual discount factors which are in line with extra-experimental market rates. At the same time, financial literacy is uncorrelated with choice consistency and estimated individual error parameters. These results serve as suggestive evidence for inter-temporal arbitrage among financially literate respondents, thereby revealing a potential confound in time-preference elicitation tasks relying on time-dated monetary rewards.
Using a Hybrid Deep Neural Network for Gas Classification

In terms of electronic nose algorithms, data pre-processing and classifier type are the two main factors affecting gas classification results. In the early stage, data pre-processing mostly takes specific information from gas-reaction waveforms as features and uses machine learning algorithms, such as K-Nearest Neighbor(KNN) and Support Vector Machine(SVM), to classify the gas data. In recent years, some research has been done on using deep learning for gas classification. The data pre-processing takes the overall process of the gas reaction as a feature map, and the classifier uses Convolutional Neural Network(CNN) architecture to classify the gases, resulting in classification accuracy being significantly higher than those of traditional machine learning algorithms. In addition, external factors such as wind speed, and distance from the gas source are also important factors affecting gas classification. The objectives of this study are as follows: 1) improving the data pre-processing method and classifier structure in deep learning for gas analysis and 2) using hybrid deep neural networks with Multilayer Perceptron (MLP) for environment compensation to improve the sensor drift problem caused by external factors. This study used one open-source gas dataset, applied three data pre-processing methods and two deep learning architectures (GasNet, SimResNet-9) for gas analysis and comparison, selected the method with the best classification accuracy and used it in Deep Neural Networks with MLP environmental compensation to promote the accuracy of classification further by learning the relationship between external factors and gas data. The proposed SimResNet-10_X_MLP was used for data training and classification in this study, achieving a 95% classification accuracy.