Miracle-dz/UniFAR-FTUs huggingface dataset:
Non-Aligned Ethylene-Glycol 30% Based Stagnation Point Fluid over a Stretching Surface with Hematite Nano Particles

This article examines the non-aligned stagnation point flow and heat transfer of an EthyleneGlycol and water based Nano fluid towards a stretching surface utilizing hematite (Fe3O4) as a heat enhancing agent. Resulting differential equations of the physical problem are solved numerically using Mid-point integration as a basic scheme along with Richardson extrapolation as an enhancement scheme. Influence of the flow governing parameters on the dimensionless velocity and temperature profile are expressed through graphs. Skin frictions co-efficient and Nusselt numbers are tabulated. It is observed that Ethylene-based nano fluids have higher local heat flux than water-based nano fluids. Computed numerical results of skin friction co-efficient are in good agreement with the existing available literature for the limited case.
Application of etomidate and propofol mixture in hematoma removal in patients with intracranial epidural hematoma.

OBJECTIVE To innvestigate the application of etomidate and propofol mixture in the evacuation of hematoma in patients with epidural hematoma. METHODS 98 patients with epidural hematoma were randomly divided into two groups: the joint group (n=49, anesthesia induction with etomidate and propofol) and the etomidate group (n=49, anesthesia induction with etomidate) using a random number table. Hemodynamics, stress response and cerebral oxygen metabolism were compared between the two groups at T0 (pre-anesthesia induction), T1 (after endotracheal intubation), T2 (10 min after the beginning of the operation) and T3 (the end of the operation). Adverse reactions were also analyzed. RESULTS Compared with T0, the mean arterial pressure (MAP) at T1, T2 and T3 in the joint group decreased first and then increased, and the MAP at T1 was significantly lower than that in the etomidate group (P<0.05). Compared with T0, blood oxygen saturation of internal jugular vein bulb (SjvO2) increased in T1-T3 groups, and SjvO2 in the joint group was higher than that in the etomidate group (all P<0.05). Compared with T0, cerebral oxygen uptake rate (CERO2) in the T1-T3 groups decreased significantly, and CERO2 at T3 in the joint group was higher than that in the etomidate group (all P<0.05). Compared with T0, the levels of cortisol and superoxide dismutase (SOD) at T3 in the two groups were significantly lower, but those in the etomidate group were higher than those in the combination group (all P<0.05). There was no significant difference in the incidence of postoperative anesthesia-related adverse reactions between the two groups (P>0.05). CONCLUSION Etomidate has less effect on hemodynamics and stress reaction during intravenous anesthesia, but its combination with propofol can improve cerebral oxygen metabolism to a certain extent with fewer adverse reactions.
The CRG-PVA hydrogels study of properties with various nanoparticles and their application for cultivation of phototrophic microorganisms

In this work we are demonstrate results of researches of the hydrogels based on carrageenan and polyvinyl alcohols properties with various nanoparticles Al2O3 and ZrO2 and their application for phototrophic microorganisms Chlorella vulgaris cultivation. X-ray diffraction of samples was carried out. Research on the cultivation of microalgae using the developed hydrogels has also been conducted, and the increase in productivity with the use of gels on average by 20% compared to the control sample has been shown. The highest productivity is observed with concentration 0.5% of ZrO2 nanoparticles. We conclude that using of hydrogels in the developed photobioreactors possess a perspective.
EXTRACTION AND CHARACTERIZATION OF CELLULOSE FROM JACKFRUIT (Artocarpus integer) PEEL

In the present study, cellulose was extracted from de-pectinated peel of Jackfruit. The peel was treated with alkali followed by a chemical process treatment. In present study, yield of jackfruit cellulose was 27g / 100g. The average particle size and zeta potential value of extracted cellulose is 0.730nm and 15.7mV respectively. Further, morphological characterization was carried out by using scanning microscopy. FTIR spectroscopy analysis revealed the presence of major absorptions indicative of cellulose and hemicellulose. The thermal profiles of the residual waste occurred in a minimum three steps, which representing the degradation profiles of hemicellulose, cellulose, and lignin * Corresponding author
Understanding perception of women entrepreneurs toward employees with reference to quality of work life balance (QWLB)

Abstract The significance of managing an employee’s work life balance (WLB) has been increased clearly over the past 20 years . Two major issues of life, work and family are important parameters for women to cooperate as an entrepreneur. Here as a researcher, I aim to explore the WLB of women with employees comparing each parameter as a whole. A survey of 80 women entrepreneurs is taken to determine the issues of quality of work life balance (QWLB) in accordance of women working as an entrepreneur and their perception toward employees. A systematic stratified sampling is done to illustrate the work-life scale between startups and established women entrepreneurs and comparing their type of firm as a single proprietorship, working with spouse and with partners. The generated data were subjected to standard statistical procedures, such as analysis of variance (ANOVA) and t-test of significance. Each of the statements possessed adequate reliability and validity. This study would be helpful for management consultants, academicians, and for entrepreneurs, human resource professionals to understand various QWLB issues faced by Indian Women Entrepreneurs.
Omidenepag isopropyl ophthalmic solution for open-angle glaucoma and ocular hypertension: an update

ABSTRACT Introduction: Current medical therapy for glaucoma consists of topical agents that lower intraocular pressure (IOP). Prostaglandin F2α analogues, the most commonly used class of IOP-lowering drugs, bind to prostaglandin FP receptors in tissues of the uveoscleral pathway. This binding increases the expression of matrix metalloproteinases, which degrade the extracellular matrix of the ciliary body, creating inter-muscular spaces allowing aqueous humor to exit the eye. Drawbacks to prostaglandin F2α analogues include cosmetic side effects, especially prostaglandin-associated periorbitopathy (PAP) syndrome. Areas covered: This review describes the novel prostaglandin E2 receptor antagonist, omidenepag isopropyl, which reduces IOP by improving drainage of uveoscleral and trabecular outflow, increasing the facility of outflow. In contrast to prostaglandin F2α analogues, omidenepag does not inhibit adipogenesis or promote eyelash growth. This review describes preclinical studies of omidenepag, published results of phase I–III clinical trials, and preliminary results of phase III trials currently in progress. Expert opinion: Omidenepag appears to provide IOP reductions comparable to those of prostaglandin F2α analogues, but without the cosmetic side effects common to prostaglandin F2α analogues, especially PAP syndrome. The lack of association between omidenepag and PAP suggests that long-term use of this agent may have advantages in patients with glaucoma.
Candidate Gender Quotas and Campaign Spending in Open-List Proportional Representation Systems: The Case of Chile

ABSTRACT This research note analyzes the effect of a candidate gender quota in Open-List Proportional Systems and its interaction with electoral spending. Focusing on the Chilean parliamentary elections of 2017, our evidence shows, first, that the quota law was effective in promoting the representation of women, but, second, the differences in the electoral performance between men and women grew considerably nevertheless. We argue that this result was due mainly to gender inequality in access to resources to finance electoral campaigns. Third, we found that this inequality exists only for candidates who are challenging incumbents, but not for the incumbents themselves: incumbent women are as competitive as men.
Mid-term redeployment of capacity of rescue centers considering the optimism of the decision maker

Abstract In this paper, we consider the problem of allocation of Emergency Vehicles (EVs) to Rescue Centers (RCs). The objective is to improve the operational response of the Fire and Rescue Services (SDIS) in France. More precisely, we focus on the mid-term management, and on the process of redeployment of EVs in RCs according to the evolution of requirements. At this level of decision, we do not have information on accidents. We only used the available information on the simultaneity of requirements. Based on the Hurwicz criterion, we develop a mathematical model and an iterative algorithm to solve it. The proposed approach takes into account both the uncertainty on the occurrence sequence of accidents, and the attitude towards optimization of the decision maker (DM). An illustration from the DM’s point of view is presented. It shows that this uncertainty significantly impacts the deployment of EVs. Results show that the proposed approach has an efficient resolution time for real size problems.
Modeling the effect of vaccination on selection for antibiotic resistance in Streptococcus pneumoniae

Microbial competition and diversity may influence selection for antibiotic-resistant bacteria after vaccination. Vaccines and antibiotic resistance Using mathematical modeling, Davies et al. show that the association between penicillin consumption and penicillin nonsusceptibility in Streptococcus pneumoniae across 27 European countries can be explained by four different models of antibiotic resistance evolution. Each model encapsulates an alternative hypothesis for why antibiotic-sensitive and antibiotic-resistant bacterial strains coexist in the same population. The authors show that, depending on the model, vaccination can either inhibit or promote the spread of antibiotic resistance. This work suggests testable hypotheses to help predict or explain changes in antibiotic resistance after the introduction of new vaccines. Vaccines against bacterial pathogens can protect recipients from becoming infected with potentially antibiotic-resistant pathogens. However, by altering the selective balance between antibiotic-sensitive and antibiotic-resistant bacterial strains, vaccines may also suppress—or spread—antibiotic resistance among unvaccinated individuals. Predicting the outcome of vaccination requires knowing what drives selection for drug-resistant bacterial pathogens and what maintains the circulation of both antibiotic-sensitive and antibiotic-resistant strains of bacteria. To address this question, we used mathematical modeling and data from 2007 on penicillin consumption and penicillin nonsusceptibility in Streptococcus pneumoniae (pneumococcus) invasive isolates from 27 European countries. We show that the frequency of penicillin resistance in S. pneumoniae can be explained by between-host diversity in antibiotic use, heritable diversity in pneumococcal carriage duration, or frequency-dependent selection brought about by within-host competition between antibiotic-resistant and antibiotic-sensitive S. pneumoniae strains. We used our calibrated models to predict the impact of non–serotype-specific pneumococcal vaccination upon the prevalence of S. pneumoniae carriage, incidence of disease, and frequency of S. pneumoniae antibiotic resistance. We found that the relative strength and directionality of competition between drug-resistant and drug-sensitive pneumococcal strains was the most important determinant of whether vaccination would promote, inhibit, or have little effect upon the evolution of antibiotic resistance. Last, we show that country-specific differences in pathogen transmission substantially altered the predicted impact of vaccination, highlighting that policies for managing antibiotic resistance with vaccines must be tailored to a specific pathogen and setting.
Using Fluorescence in Biotechnology Instruction to Visualize Antibiotic Resistance & DNA

Abstract Fluorescence technology has many useful applications for both research and teaching, among them the detection of fluorescence in live transgenic organisms and of DNA in agarose gels. However, dedicated fluorescence imaging systems can be expensive and complex. We describe a simple apparatus for non-microscopic fluorescence imaging using affordable and readily available parts. We describe three activities of increasing complexity that utilize fluorescence illumination and teach principles of fluorescence. At the high school level, our more advanced activities can be used for lessons addressing NGSS performance expectations in HS-LS3 and HS-LS4.
Introduction to the Generic Special Issue

‘Generics’––and ‘generic reference’––should be a key analytic for understanding the relation between language and the ‘social’. Generics ‘express general claims about kinds and categories’ (Leslie 2012; see alsoLyons 1977;Krifka, Pelletier, Carlson, ter Meulen, Chierchia, & Link 1995; Gelman 2003; Leslie 2015). They are resources for talking about typesof things, activities, andpersonswithout reference to instantiations of those types as tokens.And theyabound in everyday talk—think, for instance, of the broad-brush descriptions that circulate around US politics: ‘liberals don’t care about God’; ‘conservatives are heartless’. In introducing, theorizing, and walking through cases of generic reference, the contributions that follow illuminate the role of abstraction in social and semiotic life. Gelman builds from her work on generics in cognitive psychology to reflect on what research on language as social action might offer scholars in her field, as she also suggests what cognitive psychology’s investigation of generics can offer in return. Sidnell examines fragments of Vietnamese conversation to show that generics ‘play a key role in the interactional articulation and, thus, the social circulation. of ideology’. In my contribution, I compare generics and specifics about gambling in Laos, arguing that these two referential strategies afford distinct kinds of social acts and force us to reckon with how we understand types and the terms that appear to stand in for them. McIntosh explores generic and specific uses of dehumanizing epithets among soldiers, uses which both enable abstraction about ‘the enemy’ and ‘sweep like a terrible net across a diverse human landscape, gathering people indiscriminately into the same abject type[s]’. And finally, Mannheim argues for the importance of generics as ‘cultural replicators’, which constrain and reproduce conventions for meaning making. These contributions show what generic reference offers as an analytic. Each builds from work in philosophy and linguistics, where generics have been a subject for decades, and from more recent work in cognitive psychology by Gelman and others (e.g. Gelman 2003, 2010; Gelman & Legare 2011; Brandone, Cimpian, Leslie, & Gelman 2012; Gelman & Roberts 2017; DeJesus, Callanan, Solis, & Gelman 2019). In this understanding of generics, generic reference is not a property of lexemes but a kind of construal of the use of an utterance. The same lexeme (e.g. ‘mosquito’) can be used to make a generic or specific reference:
NEW MARINE RESERVOIR CORRECTION VALUES (ΔR) APPLICABLE TO DATES ON NEOLITHIC SHELLS FROM THE SOUTH COAST OF KOREA

ABSTRACT Shells from Neolithic shell midden sites have been routinely dated in Korea, but they have not been calibrated based on the correction values (ΔR) for the marine reservoir effect (MRE). A lack of proper calibration has left dates on shells incomparable to those on terrestrial samples, and thus unusable in building the chronological sequence of shell middens. Here, we report the two new ΔR values of a pre-bomb (pre-1950) blue mussel from the south coast. We applied the two new and the two previously reported ΔR values to the three dates on marine shells from the Bibongri shell midden in southeastern Korea. Our ΔR adjusted calibration and the comparison to dates on charcoal and bone remains clarify an ambiguity in the stratigraphy and the Early Neolithic chronology at Bibongri. Our contribution is to provide the ΔR values that can be further applied to other Neolithic shell middens along the south coast.
A SIMPLE CO2 EXTRACTION METHOD FOR RADIOCARBON ANALYSES OF DISSOLVED INORGANIC CARBON IN WATER SAMPLES WITHOUT A CARRIER GAS

ABSTRACT We developed a simple and cost-effective method for extracting carbon from dissolved inorganic carbon (DIC) in water samples without a carrier gas. This method only slightly modifies the existing vacuum line for CO2 purification in radiocarbon research laboratories by connecting several reservoirs and traps. The procedure consists of repeated cycles of CO2 extraction from water into the headspace of the reaction container, expansion of the extracted gas into the vacuum line, and cryogenic trapping of CO2. High CO2 yield (∼98%) was obtained from a variety of water samples with a wide range of DIC concentrations (0.4–100 mmol·L−1, in the case of 1.2 mgC). The δ13C fractionation depended on the CO2 yield, while the 14C concentration was constant within the error range, regardless of the CO2 yield. The average δ13C discrepancy between the results of this method and direct analyses made using the GC-IRMS was 0.02 ± 0.06‰. The standard deviations (1σ) in fraction of modern carbon (F14C) ranged from 0.0002 to 0.0004 for waters below 0.01 of F14C, and below 0.8% of F14C values for waters above 0.1. We conclude that this method is useful for effectively extracting CO2 from DIC in water and yields accurate 14C data.
Towards Computing a Near-Maximum Weighted Independent Set on Massive Graphs

The vertices in many graphs are weighted unequally in real scenarios, but the previous studies on the maximum independent set (MIS) ignore the weights of vertices. Therefore, the weight of an MIS may not necessarily be the largest. In this paper, we study the problem of maximum weighted independent set (MWIS) that is defined as the set of independent vertices with the largest weight. Since it is intractable to deliver the exact solution for large graphs, we design a reducing and tie-breaking framework to compute a near-maximum weighted independent set. The reduction rules are critical to reduce the search space for both exact and greedy algorithms as they determine the vertices that are definitely (or not) in the MWIS while preserving the correctness of solutions. We devise a set of novel reductions including low-degree reductions and high-degree reductions for general weighted graphs. Extensive experimental studies over real graphs confirm that our proposed method outperforms the state-of-the-arts significantly in terms of both effectiveness and efficiency.
Budget Allocation as a Multi-Agent System of Contextual & Continuous Bandits

Budget allocation for online advertising suffers from multiple complications, including significant delay between the initial ad impression to the call to action as well as cold-start prediction problems for ad campaigns with limited or no historical performance data. To address these issues, we introduce the Contextual Budgeting System (CBS ), a budget allocation framework using a multi-agent system of contextual & continuous Multi-Armed Bandits. Our proposed solution decomposes the problem into a convex optimization problem whose objective is drawn using Thompson Sampling. In order to efficiently deal with context and cold-start, we propose a transfer learning mechanism using supervised learning methods that augment simple parametric models. We apply an implementation of this algorithm to all spending for new driver acquisition at Lyft and measure a (22 ± 10)% improvement in the mean Cost Per user Acquisition (CPA) over a previous non-contextual model, based on Markov Chain Monte-Carlo, generating tens of millions of dollars annually in efficiency improvements while also increasing total user acquisition.
Towards Robust Prediction on Tail Labels

Extreme multi-label learning (XML) works to annotate objects with relevant labels from an extremely large label set. Many previous methods treat labels uniformly such that the learned model tends to perform better on head labels, while the performance is severely deteriorated for tail labels. However, it is often desirable to predict more tail labels in many real-world applications. To alleviate this problem, in this work, we show theoretical and experimental evidence for the inferior performance of representative XML methods on tail labels. Our finding is that the norm of label classifier weights typically follows a long-tailed distribution similar to the label frequency, which results in the over-suppression of tail labels. Base on this new finding, we present two new modules: (1)ReRank works to re-rank the predicted score, which significantly improves the performance on tail labels by eliminating the effect of label-priors; (2)Taug augments tail labels via a decoupled learning scheme, which can yield more balanced classification boundary. We conduct experiments on commonly used XML benchmarks with hundreds of thousands of labels, showing that the proposed methods improve the performance of many state-of-the-art XML models by a considerable margin (6% performance gain with respect to PSP@1 on average). Anonymous source code is available at https://github.com/ReRANK-XML/rerank-XML.
Learning Reliable User Representations from Volatile and Sparse Data to Accurately Predict Customer Lifetime Value

In industry, customer lifetime value (LTV) prediction is a challenging task, since user consumption data is usually volatile, noisy, or sparse. To address these issues, this paper presents a novel Temporal-Structural User Representation (named TSUR) network to predict LTV. We utilize historical revenue time series and user attributes to learn both temporal and structural user representations, respectively. Specifically, the temporal representation is learned with a temporal trend encoder based on a novel multi-channel Discrete Wavelet Transform~(DWT) module, while the structural representation is derived with Graph Attention Network (GAT) on an attribute similarity graph. Furthermore, a novel cluster-alignment regularization method is employed to align and enhance these two kinds of representations. In essence, such a fusion way can be considered as the association of temporal and structural representations in the low-pass representation space, which is also useful to prevent the data noise from being transferred across different views. To our knowledge, it is the first time that temporal and structural user representations are jointly learned for LTV prediction. Extensive offline experiments on two large-scale real-world datasets and online A/B tests have shown the superiority of our approach over a number of competitive baselines.