Miracle-dz/UniFAR-FTUs huggingface dataset:
Marketing Mix Modeling (MMM)- Concepts and Model Interpretation

Marketing mix modeling has existed for decades now. Everyone has been using it, some tapped its potential with enormous success while others are yet to see its true potential. Rapidly changing marketing environment, consumer dynamics and multi touch points have made it even more complex to get it right for any industry and product. The biggest challenge in the process of any marketing mix optimization is measuring real-time cross effects and cross channel impact on business. The intent of this paper is to introduce marketing managers, consultants, analysts, strategists, and researchers to an analytics application to optimize the allocation of a firm’s marketing budget in such a way that provides the maximum likelihood of generating higher ROI. MMM uses advanced econometrics and marketing science to objectively measure the relative efficacy and effectiveness of an entire set of marketing and advertising investments, competitive steal, or initiatives to produce sales and growth in both short and long term. In this paper we discuss the methodologies used to perform such analysis, how to overcome major challenges, and the benefits that can be derived from the analysis. We also discuss opportunities for improvement in media mix models that can produce agile granular measurement for better strategy.
Effect Nigella sativa extract for balancing immune response in pristane induced lupus mice model

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease with wide manifestations that require long-term treatment. Current treatment has not shown a satisfying result and still yields some side effects. Nigella sativa (NS) has anti-inflammatory and immunomodulatory effects and thus has the potential to improve SLE symptoms. This study aims to understand the NS effect on the level of anti-dsDNA and Treg percentage in pristane-induced lupus (PIL) mice. Anti-dsDNA has an important role in diagnosing and prognosing SLE with high specificity. Treg has been known to be disturbed in SLE. This is a true experimental, randomized posttest only controlled group design with 25 female Bagg and Albino/c mice as the subject, divided into five groups: negative control/K(−)/healthy mice, positive control/K(+)/PIL mice, and three treatment groups (three different doses of NS, 1.2, 2.4, and 4.8 g/kgBW/day). AntidsDNA analysis was conducted using enzyme-linked immunosorbent assay and Treg using flow cytometry. Treatment group 4.8 g/kgBW/day has significantly lower anti-dsDNA and significantly higher Treg than K(+) (p < 0.01). Linear regression test showed that escalation of NS dose is correlated with the decrease of anti-dsDNA and increase of Treg in PIL mice. Thus, NS has the potential to repair the immune function in SLE.
ISOLATION AND CHARACTERISATION OF A NEW ALKALI-HALOTOLERANT BACILLUS AQUIMARIS STRAIN LGMT10, PRODUCING EXTRACELLULAR HYDROLASES, FROM THE EFFLUENTS OF A THERMAL POWER PLANT, IN ALGERIA

Modern biotechnology takes into account cost, performance, and respect for the environment to set up an industrial process. In this sense, the study's goal is to highlight the presence of indigenous microbial microflora in the Terga thermal power plant effluents, which are capable of secreting extracellular hydrolases. Four different extracellular hydrolases classes, which are most of the time used in bioindustry, namely protease, amylase, lipase, and cellulase, were investigated in agar plate assay, to select microorganisms with an interesting enzymatic potential adapted to this type of environment. Consequently, the results have shown that among twelve isolated bacterial strains, three strains were screened based on their enzymatic potential, and were later identified by 16S rRNA gene sequencing, i.e. showing that the strains belong to the genus Pseudomonas aeruginosa, and Bacillus wiedmannii with a similarity percentage of 99.33% and 100%, respectively, with their corresponding type of strains. Among them, the strain LGMT10 that belongs to the Bacillus genus, and is closely related to Bacillus aquimaris, showed a 16S rRNA sequence similarity with the type of strain of 99.23%. This strain presents adequate characteristics to resist the harsh conditions of pH and NaCl. It could grow against wide ranges of NaCl concentrations between 0-12% (w/v), pH 5.5-12, and was able to produce extracellular hydrolases (i.e., protease, amylase, and cellulase) against pH ranges of 6.8-12 and NaCl concentrations between 0-12% (w/v) at 30 °C. This strain's intriguing enzymatic potential, as well as its pH and salinity tolerance, make it a promising candidate for various biotechnological applications in detergent, leather, textile, and food processing industries.
An Error Correction Model for Long Term Forecast of System Marginal Price

The system marginal price of electricity is the amount paid to all the generating units, which is an important decision-making factor for the construction and maintenance of an electrical power unit. In this paper, we suggest a long-term forecasting model for calculating the system marginal price based on prices of natural gas and oil. As most variables used in the analysis are nonstationary time series, the long run relationship among the variables should be examined by cointegration tests. The forecasting model is similar to an error correction model which consists of a long run cointegrating equation and another equation for short run dynamics. To mitigate the robustness issue arising from the relatively small data sample, this study employs various testing and estimating methods. Compared to previous studies, this paper considers multiple fuel prices in the forecasting model of system marginal price, and provides greater emphasis on the robustness of analysis. As none of the cointegrating relations associated with system marginal price, natural gas price and oil price are excluded, three error correction models are estimated. Considering the root mean squared error and mean absolute error, the model based on the cointegrating relation between system marginal price and natural gas price performs best in the out-of-sample forecast.
A Critical Evaluation of Tracking Public Opinion with Social Media: A Case Study in Presidential Approval

There has been much interest in using social media to track public opinion. We introduce a higher level of scrutiny to these types of analyses, specifically looking at the relationship between presidential approval and “Trump” tweets and developing a framework to interpret its strength. We use placebo analyses, performing the same analysis but with tweets assumed to be unrelated to presidential approval, to assess the relationship and conclude that the relationship is less strong than it might otherwise seem. Secondly, we suggest following users longitudinally, which enables us to find evidence of a political signal around the 2016 presidential election. For the goal of supplementing traditional surveys with social media data, our results are encouraging, but cautionary.
Plasmonic nanoarcs: a versatile platform with tunable localized surface plasmon resonances in octave intervals.

: The tunability of the longitudinal localized surface plasmon resonances (LSPRs) of metallic nanoarcs is demonstrated with key relationships identified between geometric parameters of the arcs and their resonances in the infrared. The wavelength of the LSPRs is tuned by the mid-arc length of the nanoarc. The ratio between the attenuation of the fundamental and second order LSPRs is governed by the nanoarc central angle. Beneficial for plasmonic enhancement of harmonic generation, these two resonances can be tuned independently to obtain octave intervals through the design of a non-uniform arc-width profile. Because the character of the fundamental LSPR mode in nanoarcs combines an electric and a magnetic dipole, plasmonic nanoarcs with tunable resonances can serve as versatile building blocks for chiroptical and nonlinear optical devices.
Gender Differences in Peer Recognition by Economists

We study the selection of Fellows of the Econometric Society, using a new data set of publications and citations for over 40,000 actively publishing economists since the early 1900s. Conditional on achievement, we document a large negative gap in the probability that women were selected as Fellows in the 1933–1979 period. This gap became positive (though not statistically significant) from 1980 to 2010, and in the past decade has become large and highly significant, with over a 100% increase in the probability of selection for female authors relative to males with similar publications and citations. The positive boost affects highly qualified female candidates (in the top 10% of authors) with no effect for the bottom 90%. Using nomination data for the past 30 years, we find a key proximate role for the Society's Nominating Committee in this shift. Since 2012, the Committee has had an explicit mandate to nominate highly qualified women, and its nominees enjoy above‐average election success (controlling for achievement). Looking beyond gender, we document similar shifts in the premium for geographic diversity: in the mid‐2000s, both the Fellows and the Nominating Committee became significantly more likely to nominate and elect candidates from outside the United States. Finally, we examine gender gaps in several other major awards for U.S. economists. We show that the gaps in the probability of selection of new fellows of the American Academy of Arts and Sciences and the National Academy of Sciences closely parallel those of the Econometric Society, with historically negative penalties for women turning to positive premiums in recent years.
BIOENGINEERING OF THE CIRCULAR BACTERIOCIN FROM ENTEROCOCCUS FAECIUM NKR-5-3 BY NNK-SCANNING TO ENHANCE ITS BIOACTIVITY

Bacteriocins are gene-encoded antimicrobial peptides that are traditionally appreciated as safe food preservative in the food industry and as possible alternative to conventional antibiotics in the pharmaceutical industry. Enterocin NKR-5-3B is a well characterized circular bacteriocin that possess exceptional stability due to the circular nature of its structure. In this paper, a mutant library of this bacteriocin was constructed through NNK-scanning whereby the presumed critical residues were targeted hoping to obtain bacteriocin derivatives with enhanced bioactivity. Thirteen (13) mutant phenotypes exhibited bioactivity enhancement relative to the native bacteriocin. The most notable bioactivity increases were observed from the phenotypes expressing V32C, V32A, and L40G that exhibited 233, 217, and 200% relative bioactivity, respectively. In-silico analyses of the resulting bacteriocin derivatives showed significant changes in the physico-chemical properties of the bacteriocin derivatives, particularly its hydrophobicity index, as a consequence of the introduced mutation. The V32C bacteriocin derivative which exhibited the strongest bioactivity enhancement was found to exhibit a reduction of the molecular surface hydrophobicity and isoelectric point. These changes may have contributed in the enhancement of its bioactivity. The identification of these critical mutations is highly valuable as basis for future studies on the rational design of bioengineered bacteriocins with enhanced bioactivity.
Dose verification and plan conformity with three different dosimeters for intensity-modulated radiation therapy plans

Background: The intensity-modulated radiotherapy (IMRT) enables personalized treatment; the complexity of this technique increased the need for patient-specific quality assurance (QA). Objective: Comparing three dosimeters that common for patient-specific QA of IMRT. Material and Method: cases were planned at Eclipse treatment planning system (TPS) to receive radiotherapy at Unique VARIAN linear accelerator LINAC; Patient-specific QA was performed with three independent dosimeters: Gafchromic films EPT2, Electronic Portal Image Device (EPID), and PTW 2D array. The absolute dose was measured and analysis of 2D gamma index was performed, then compared with the plan calculated in TPS. Results: Analysis of absolute dose measured have highest difference from dose in Gafchromic film (89.1±4) % while EPID had a lower range (96.6 ± 1.2) and 2Darray showed an agreement up to (99±1.2) for patient specific QA both EBT2 and EPID enable to compare the measured map with TPS calculations, for plan conformity the gafchromic film enable measurement with lower accuracy even with localized brain tumor, the heterogeneity in lung case slightly affect the EPID measurement, this found also with irregular surface of head and neck and increased depth within pelvic case examine. Measurement with 2D array found to be the optimum dosimeter within different conditions. Conclusion: different parameters might affect the accuracy of gafchromic film including film scanning, storing, and calibration curve. EPID has an average deviation appears in beam fluence and 2D array as a 2D ion chamber found to have the most accurate dosimeter, but still time consuming when compared to EPID.
Bundle construction and assessment before antineoplastic extravasation: a methodological study

João Marcos Alves Melo1 https://orcid.org/0000-0002-9056-6782 Patrícia Peres de Oliveira1 https://orcid.org/0000-0002-3025-5034 Andrea Bezerra Rodrigues2 https://orcid.org/0000-0002-2137-0663 Raíssa Silva Souza1 https://orcid.org/0000-0001-5010-763X Deborah Franscielle da Fonseca1 https://orcid.org/0000-0001-6001-2837 Thaís Fonseca Gontijo1 https://orcid.org/0000-0003-3021-5267 Edilene Aparecida Araújo da Silveira1 https://orcid.org/0000-0001-7378-2240
Node-to-node secure multiparty computation on Vantage6

—This study investigated the possibilities to create node to node communication between Vantage6 algorithm containers without the interposition of the Vantage6 server. Three infrastructures are created: an overlay network in swarm mode, an overlay network with an external key-value store, and a VPN network. The performance of these setups are tested on throughput with iperf3 and on the duration to perform a secure sum algorithm script between three nodes. Throughput is higher on the overlay networks and running a secure sum algorithm on the overlay network is faster than running this algorithm in the VPN setup. A swarm and an overlay network are manually created on the Vantage6 server virtual machine. The docker-manager Python script of the Vantage6 node is changed to join the swarm and connect the algorithm containers to the overlay network. To achieve this new feature a workaround is needed, since the Docker API does not support overlay networks.
Spiritual intelligence and mindfulness as predictors of life satisfaction among youth of Jammu and Kashmir

This study investigated the relationship among spiritual intelligence mindfulness and life satisfaction among young adults. The sample consisted of 168 young adults. Spiritual Intelligence Questionnaire (SIQ) by Abdollahzadeh et al. (2009) [1] Mindful Attention Awareness Scale (MASS) by Brown and Ryan (2003) [7] Satisfaction with Life Scale (SWLS) by Diener et al., (1985) [12] were used to study the variables. Pearson product moment correlation and stepwise regression were applied to analyze the data. Results indicated that there was significant positive relationship among spiritual intelligence mindfulness and life satisfaction whereas only spiritual intelligence significantly predicted life satisfaction among young adults.
Assessing the QoME of NMP via Audio Analysis Tools

Analyzing the Quality of Musicians’ Experience (QoME) in Network Music Performance (NMP) typically involves having musicians perform NMP sessions and then assessing their experience via questionnaires. Such subjective studies produce results with wide variances, making the extraction of solid conclusions difficult. For this reason, we complemented a subjective study on the effects of delay in the QoME of NMP with an analysis of the audio captured during the study using automated tools. Specifically, we used signal processing techniques to analyze the captured audio, in order to detect tempo evolution during each performance and examine its correlation with delay. Our results indicate that musicians in real NMP settings are more tolerant to delay than previously thought, holding a steady tempo even with one way delays of 40 ms.
Antipredator phenotype in crucian carp altered by a psychoactive drug

Abstract Predator‐inducible defenses constitute a widespread form of adaptive phenotypic plasticity, and such defenses have recently been suggested linked with the neuroendocrine system. The neuroendocrine system is a target of endocrine disruptors, such as psychoactive pharmaceuticals, which are common aquatic contaminants. We hypothesized that exposure to an antidepressant pollutant, fluoxetine, influences the physiological stress response in our model species, crucian carp, affecting its behavioral and morphological responses to predation threat. We examined short‐ and long‐term effects of fluoxetine and predator exposure on behavior and morphology in crucian carp. Seventeen days of exposure to a high dose of fluoxetine (100 µg/L) resulted in a shyer phenotype, regardless of the presence/absence of a pike predator, but this effect disappeared after long‐term exposure. Fluoxetine effects on morphological plasticity were context‐dependent as a low dose (1 µg/L) only influenced crucian carp body shape in pike presence. A high dose of fluoxetine strongly influenced body shape regardless of predator treatment. Our results highlight that environmental pollution by pharmaceuticals could disrupt physiological regulation of ecologically important inducible defenses.
Prediction of Hanwoo Cattle Phenotypes from Genotypes Using Machine Learning Methods

Simple Summary Machine learning has been extensively used in analyzing big data and in conditions where the number of parameters is much bigger than the number of observations. Recently, there have been an increasing number of successful applications of machine learning in genomic prediction as this method makes weaker assumptions, is capable of dealing with the dimensionality problem, and can be more flexible for describing complex relationships. In this study, we evaluated the predictive ability of three machine learning methods, namely, random forest (RF), extreme gradient boosting (XGB), and support vector machine (SVM), when predicting the carcass traits of Hanwoo cattle. These machine learning algorithms were compared with the standard linear method (GBLUP). Our results revealed that XGB method had the best predictive correlation for carcass weight and marbling score. Meanwhile, the best predictive correlation for backfat thickness and eye muscle area was delivered by GBLUP. Moreover, in terms of mean squared error (MSE) of prediction, GBLUP delivered the lowest MSE value for all traits. Abstract Hanwoo was originally raised for draft purposes, but the increase in local demand for red meat turned that purpose into full-scale meat-type cattle rearing; it is now considered one of the most economically important species and a vital food source for Koreans. The application of genomic selection in Hanwoo breeding programs in recent years was expected to lead to higher genetic progress. However, better statistical methods that can improve the genomic prediction accuracy are required. Hence, this study aimed to compare the predictive performance of three machine learning methods, namely, random forest (RF), extreme gradient boosting method (XGB), and support vector machine (SVM), when predicting the carcass weight (CWT), marbling score (MS), backfat thickness (BFT) and eye muscle area (EMA). Phenotypic and genotypic data (53,866 SNPs) from 7324 commercial Hanwoo cattle that were slaughtered at the age of around 30 months were used. The results showed that the boosting method XGB showed the highest predictive correlation for CWT and MS, followed by GBLUP, SVM, and RF. Meanwhile, the best predictive correlation for BFT and EMA was delivered by GBLUP, followed by SVM, RF, and XGB. Although XGB presented the highest predictive correlations for some traits, we did not find an advantage of XGB or any machine learning methods over GBLUP according to the mean squared error of prediction. Thus, we still recommend the use of GBLUP in the prediction of genomic breeding values for carcass traits in Hanwoo cattle.
Isolation and purification of polysaccharides from transgenic crown gall cultures of Panax quinquefolium

Objective To investigate the polysaccharides constituents from the transgenic crown gall cultures of Panax quinquefolium. Methods The crude polysaccharides PPQ50 and PPQ70 were extracted by water-ethanol method from the crown gall of P. quinquefolium. Four polysaccharides, named PPQ50-1, PPQ50-2, PPQ70-1, and PQ70-2, were isolated and purified by DEAE Sepharose and Sephacry S-100 column chromatography. Results The homogeneity of four polysaccharides was examined by gel chromatography and polarimetry. Their molecular weights were determined by gel filtration chromatography. They were 4.7×104, 2.9×105, 7.5×104, and 1.3×105, respectively. The sugar composition was analyzed by HPLC. The polysaccharides are mainly composed of neutral sugar particularly of D-glucose. The structure elucidation of PPQ50-2 was also supported by 1H-NMR and 13C-NMR spectroscopy. Conclusion All of the four polysaccharides are first isolated and purified from the transgenic crown gall cultures of P. quinquefolium.The result shows the PPQ50-2 and PPQ70-2 are both glucans.
Antibody Protection against Long-Term Memory Loss Induced by Monomeric C-Reactive Protein in a Mouse Model of Dementia

Monomeric C-reactive protein (mCRP), the activated isoform of CRP, induces tissue damage in a range of inflammatory pathologies. Its detection in infarcted human brain tissue and its experimentally proven ability to promote dementia with Alzheimer’s disease (AD) traits at 4 weeks after intrahippocampal injection in mice have suggested that it may contribute to the development of AD after cerebrovascular injury. Here, we showed that a single hippocampal administration of mCRP in mice induced memory loss, lasting at least 6 months, along with neurodegenerative changes detected by increased levels of hyperphosphorylated tau protein and a decrease of the neuroplasticity marker Egr1. Furthermore, co-treatment with the monoclonal antibody 8C10 specific for mCRP showed that long-term memory loss and tau pathology were entirely avoided by early blockade of mCRP. Notably, 8C10 mitigated Egr1 decrease in the mouse hippocampus. 8C10 also protected against mCRP-induced inflammatory pathways in a microglial cell line, as shown by the prevention of increased generation of nitric oxide. Additional in vivo and in vitro neuroprotective testing with the anti-inflammatory agent TPPU, an inhibitor of the soluble epoxide hydrolase enzyme, confirmed the predominant involvement of neuroinflammatory processes in the dementia induced by mCRP. Therefore, locally deposited mCRP in the infarcted brain may be a novel biomarker for AD prognosis, and its antibody blockade opens up therapeutic opportunities for reducing post-stroke AD risk.