Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying the efficiency and biases of forest Saccharomyces sampling strategies

Saccharomyces yeasts are emerging as model organisms for ecology and evolution, and researchers need environmental Saccharomyces isolates to test ecological and evolutionary hypotheses. However, methods for isolating Saccharomyces from nature have not been standardized and isolation methods may influence the genotypes and phenotypes of studied strains. We compared the effectiveness and potential biases of an established enrichment culturing method against a newly developed direct plating method for isolating forest floor Saccharomyces spp. In a European forest, enrichment culturing was both less successful at isolating S. paradoxus per sample collected and less labor intensive per isolated S. paradoxus colony than direct isolation. The two methods sampled similar S. paradoxus diversity: the number of unique genotypes sampled (i.e., genotypic diversity) per S. paradoxus isolate and average growth rates of S. paradoxus isolates did not differ between the two methods, and growth rate variances (i.e., phenotypic diversity) only differed in one of three tested environments. However, enrichment culturing did detect rare S. cerevisiae in the forest habitat, and also found two S. paradoxus isolates with outlier phenotypes. Our results validate the historically common method of using enrichment culturing to isolate representative collections of environmental Saccharomyces. We recommend that researchers choose a Saccharomyces sampling method based on resources available for sampling and isolate screening. Researchers interested in discovering new Saccharomyces phenotypes or rare Saccharomyces species from natural environments may also have more success using enrichment culturing. We include step-by-step sampling protocols in the supplemental materials.
Isolation and Functional Analysis of CmMAX1 from Chrysanthemum

More axillary buds 1 (MAX1), initially identified in arabidopsis (Arabidopsis thaliana), is a key regulatory gene in strigolactone synthesis. CmMAX1, an ortholog of MAX1 was cloned from chrysanthemum (Chrysanthemum morifolium cv. Jinba). It had an open reading frame of 1611 bp and encoded 536 amino acid of P450 protein, with a conserved heme-binding motif of PFG × GPR × C × G, as well as PERF and KExxR motifs. The predicted amino acid sequence of CmMAX1 was most closely related to the MAX1 ortholog identified in lotus (Nelumbo nucifera), NnMAX1, with 55.33% amino acid sequence similarity. Expression analysis revealed there was no significant difference of CmMAX1 expression among various tissues. Phosphorus (P) deficiency significantly improved the expression levels of CmMAX1. Strigolactone, auxin, and cytokinin negatively regulated the expression of CmMAX1. Overexpression of CmMAX1 reduced the branch numbers of arabidopsis max1-1. These results suggest that CmMAX1 may be a candidate gene for reducing the shoot branching of chrysanthemum.
MODIFIED ALGORITHM OF COLLABORATIVE FILTERING FOR FORMING USER RECOMMENDATIONS

Background. In our online life, we get a lot of information, and more and more people don`t want to rummage impassable jungle of information. Each of us wants to quickly find what is looking for. Many sites such as YouTube, Facebook and Twitter have already had recommender system and many people have used it. Recommender systems are becoming more and more popular. Objective. The base algorithm of collaborative filtering which is used in recommender system is considered. We are trying to find bottleneck problems of base algorithm of collaborative filtering to improve it and take a gain in time. Methods. We have analyzed the base algorithm of collaborative filtering and have found bottleneck problem. The main runtime of the algorithm is concentrated to calculate user similarity. We calculated the average rating for object in cluster with weighting factor. We use two criterions to compare the base algorithm with the modified algorithm. First criterion is the algorithm runtime. Second criterion is amount of elementary permutations we have to do to get recommendations which are provided by the base algorithm of collaborative filtering. The main factors which influence the algorithm runtime of collaborative filtering are: number of users, amount of objects and percentage of filling. Results. The modified algorithm of collaborative filtering was compared with the base algorithm of collaborative filtering by two criteria. The difference between the results of both algorithms does not exceed 5%. The modified algorithm works faster than the base algorithm. Furthermore, with increasing the number of users or amount of objects the runtime difference will increase. The results of research are presented in graphs. Conclusions. We have analyzed the base algorithm of collaborative filtering and methods to improve it. We can conclude on the feasibility of the modified algorithm of collaborative filtering from the research. The modified method gives a great gain in time. If systems start to use this modified algorithm, this can solve the problem with the runtime of the algorithm of collaborative filtering and allows giving recommendations faster than the system which uses the base algorithm.
Religiosity and Environmentally Friendly Behavior of Millennial Muslim Consumers

The purpose of this study is to investigate the impact of attitudes, subjective norms and religiosity on consumer intentions to support government policies on environmentally friendly behaviour. Based on a direct survey of 100 Muslim student respondents then analyzed using multiple linear regression, it was found that attitudes, subjective norms and religiosity as determinants of Muslim consumer intentions in supporting government policies on environmentally friendly behaviour, namely paid plastic bag policies. Finally, an important finding from this study is the contribution of subjective norms as the dominant determinant that influences the Muslim consumer's intention to support government policies to behave in an environmentally friendly manner by being willing to support a paid plastic bag policy.
Survey Evidence on Core Factors of Behavioral Biases: The Role of Cognition and Affect

In the past decades, a multitude of judgmental and behavioral biases with regards to financial decision making has been found. But are these biases connected with each other? Are people prone to, e.g., illusion of control, usually also more prone to confirmation or hindsight bias? In this study we show that nine common biases can indeed be reduced to only three main factors. These three factors can be related to biases in self-related and non-self-related information processing and in the connection between those. We also show that cognitive reflection decreases biases related to external, while emotions can increase biases related to internal information processing.
Monetary Policy Inertia and the Paradox of Flexibility

This paper revisits the paradox of flexibility, ie, the result that, in a liquidity trap, greater price flexibility amplifies output volatility in response to negative demand shocks. We argue this paradox is the consequence of a failure of standard models to correctly characterise monetary policy and that allowing for a smooth adjustment of the shadow policy rate eliminates the paradox and produces output responses to a negative demand shock that are in line with those under optimal monetary policy. The reason is that, under an inertial policy, a decline in the shadow rate implies that the future actual policy rate will remain relatively low, which increases expectations about the economic outlook and inflation. The rise in inflation expectations reduces the real rate, thereby sustaining real activity. As we raise the degree of price flexibility, a negative demand shock causes a sharper fall in the shadow rate and increase in inflation expectations, which leads to a more significant drop in the real rate and, hence, a milder decline in the output gap.
In-Silico Validation and Development of Chlorogenic Acid (CGA) Loaded Polymeric Nanoparticle for Targeting Neurodegenerative Disorders

Background: Recent decades witnessed a significant growth in terms of phytocompounds based therapeutics, extensively explored for almost all types of existing disorders. They have also been widely investigated in Neurodegenerative disorders (NDDs) and Chlorogenic acid (CGA), a polyphenolic compound having potential anti-inflammatory and anti-oxidative properties, emerged as a promising compound in ameliorating NDDs. Owing to its poor stability, bioavailability and release kinetics, CGA needed a suitable nanocarrier based pharmaceutical design for targeting NDDs. Objective: The current study is aimed at the in-silico validation of CGA as an effective therapeutic agent targeting various NDDs followed by the fabrication of polymeric nanoparticles-based carrier system to overcome its pharmacological limitations and improve its stability. Methods: A successful in-silico validation using molecular docking techniques along with synthesis of CGA loaded polymeric nanoparticles (CGA-NPs) by ionic gelation method was performed. The statistical optimisation of the developed CGA-NPs was done by Box Behnken method and then the optimized formulation of CGA-NPs was characterised using particle size analysis (PSA), Transmission electron microscopy (TEM), Fourier Transform Infrared spectroscopy (FTIR) along with in-vitro release kinetics analysis. Results & Conclusion: The results attained exhibited average particle size of 101.9 ± 1.5 nm, Polydispersibility (PDI) score of 0.065 and a ZP of −17.4 mV. On a similar note, TEM results showed a size range of CGA-NPs between 90 - 110 nm with a spherical shape of NPs. Also, the data from in-vitro release kinetics showed a sustained release of CGA from the NPs following the first-order kinetics suggesting the appropriate designing of nanoformulation.
Economic damages from on-going climate change imply deeper near-term emission cuts

Pathways toward limiting global warming to well below 2 ∘C, as used by the IPCC in the Fifth Assessment Report, do not consider the climate impacts already occurring below 2 ∘C. Here we show that accounting for such damages significantly increases the near-term ambition of transformation pathways. We use econometric estimates of climate damages on GDP growth and explicitly model the uncertainty in the persistence time of damages. The Integrated Assessment Model we use includes the climate system and mitigation technology detail required to derive near-term policies. We find an optimal carbon price of $115 per tonne of CO2 in 2030. The long-term persistence of damages, while highly uncertain, is a main driver of the near-term carbon price. Accounting for damages on economic growth increases the gap between the currently pledged nationally determined contributions and the welfare-optimal 2030 emissions by two thirds, compared to pathways considering the 2 ∘C limit only.
Interaction of Huanglongbing and Foliar Applications of Copper on Growth and Nutrient Acquisition of Citrus sinensis cv. Valencia

The following study was conducted in 2016 and 2017 to determine the impact of frequent foliar copper (Cu) applications on Huanglongbing (HLB)-affected Citrus sinensis cv. Valencia orange. The experiment was conducted in a psyllid-free greenhouse with HLB-positive and non-HLB control trees grown in an Immokalee fine sand soil. The trees were well-maintained to promote health. Cu was applied to the foliage at 0x, 0.5x, 1x, and 2x the commercially recommended rates, which were 0, 46, 92, and 184 mm, respectively, with applications made 3x in both 2016 and 2017. The impact of HLB and Cu treatments on leaf and root Cu concentrations, vegetative growth, Candidatus Liberibacter asiaticus (CLasiaticus) genome copy number, and acquisition of other essential nutrients were determined. HLB caused the roots to acidify the soil more than non-HLB controls, which promoted Cu availability and promoted greater Cu concentrations in leaves and roots. HLB and Cu application treatments suppressed leaf area and total root length observable in rhizotron tubes such that, by the end of the experiment, leaf, stem, root, and whole-plant dry weights were reduced. HLB reduced foliar concentrations of calcium (Ca), magnesium (Mg), manganese (Mn), zinc (Zn) and possibly iron (Fe), but HLB did not affect root concentrations of these same essential nutrients. Cu application treatments did not affect leaf or root concentrations of other essential nutrients except foliar concentration of Fe, which may have been suppressed. Foliar applications of Cu are used to suppress Xanthomonas citri ssp. citri (Xcc) the causal agent of citrus canker, and the frequency of its use may need to be reconsidered in commercial groves.
Effectiveness of Schema Therapy in Psychological Distress, Body Image, and Eating Disorder Beliefs in Patients with Anorexia Nervosa

Background and Objective: Due to the role of recognition in eating disorders, the identification of core beliefs and cognitive schemas becomes debatable. This study aimed to determine the effectiveness of schema therapy in psychological distress, body image, and eating disorder beliefs in anorexic patients. Materials and Methods: This was an applied quasi-experimental study with a pretest and posttest design and control group. The statistical population of the study included patients with an eating disorder, attending the psychological, clinical psychiatric, and obesity treatment centers in Ahvaz, Iran, within the age range of 16-23 years in 2019. The subjects were selected using the purposive sampling method. In this study, the pretest (i.e., filling out the Eating Disorder Beliefs Questionnaire [EDBQ]) was performed before the schema therapy intervention. Then, the intervention was conducted on the experimental group; however, no intervention was carried out for the control group. After the termination of the treatment sessions (12 sessions of 45 min), the posttest was performed. Finally, 3 months following the termination of the treatment, the follow-up test was conducted. The data were obtained using the EDBQ, Psychological Distress Questionnaire, and Body Image Concern Inventory. The data were analyzed using multivariate analysis of covariance and SPSS software (version 22). Results: The results of the present study showed that schema therapy led to a decrease in psychological distress (F=157.36, P<0.0001, Eta=0.89), body image concern (F=8.03, P<0.001, Eta=0.29), and eating disorder beliefs (F=13.85, P<0.0001, Eta=0.91). Conclusion: It can be concluded that schema therapy reduces psychological distress, body image concerns, and eating disorder beliefs
Uncertainty Quantification of Ocean Parameterizations: Application to the K‐Profile‐Parameterization for Penetrative Convection

Parameterizations of unresolved turbulent processes often compromise the fidelity of large‐scale ocean models. In this work, we argue for a Bayesian approach to the refinement and evaluation of turbulence parameterizations. Using an ensemble of large eddy simulations of turbulent penetrative convection in the surface boundary layer, we demonstrate the method by estimating the uncertainty of parameters in the convective limit of the popular “K‐Profile Parameterization. ” We uncover structural deficiencies and propose an alternative scaling that overcomes them.
Sex differences in gene expression in the human fetal brain

Widespread structural, chemical and molecular differences have been reported between the male and female human brain. Although several neurodevelopmental disorders are more commonly diagnosed in males, little is known regarding sex differences in early human brain development. Here, we used RNA sequencing data from a large collection of human brain samples from the second trimester of gestation (N = 120) to assess sex biases in gene expression within the human fetal brain. In addition to 43 genes (102 Ensembl transcripts) transcribed from the Y-chromosome in males, we detected sex differences in the expression of 2558 autosomal genes (2723 Ensembl transcripts) and 155 genes on the X-chromosome (207 Ensembl transcripts) at a false discovery rate (FDR) < 0.1. Genes exhibiting sex-biased expression in human fetal brain are enriched for high-confidence risk genes for autism and other developmental disorders. Male-biased genes are enriched for expression in neural progenitor cells, whereas female-biased genes are enriched for expression in Cajal-Retzius cells and glia. All gene- and transcript-level data are provided as an online resource (available at http://fgen.psycm.cf.ac.uk/FBSeq1) through which researchers can search, download and visualize data pertaining to sex biases in gene expression during early human brain development.
Macroeconomic Determinants of Brain Drain in the Era of Globalization: Evidence from Pakistan

The Brain Drain (BD) is a cynosure of all the eyes because it has become a grave issue for Pakistan. Every year, thousands of students graduate from colleges and universities. Our markets cannot accommodate such a huge number of graduates so; these people prefer to migrate to other parts of the world. This paper attempts to investigate the factors affecting brain drain in Pakistan by utilizing the data for 1990 to 2018. Indices of variables are constructed in this study to measure the potential of factors causing migration from Pakistan to other developed economies. Secondary data has been taken from the World Development Indicator (WDI) and the Bureau of Emigration and Overseas Employment (BEOE). This study finds that in long run governance, financial stability, the standard of living, and infrastructure have a negative and significant impact on the dependent variable (Brain drain). Social openness does not show a significant impact on brain drain in the long run. This study concludes that brain drain in developing nations is a serious matter and it should be addressed on a priority basis. This study helps policymakers to develop policies to reduce the migration of highly skilled labour.
CompStor Novos: low cost yet fast assembly-based variant calling for personal genomes

Application of assembly methods for personal genome analysis from next generation sequencing data has been limited by the requirement for an expensive supercomputer hardware or long computation times when using ordinary resources. We describe CompStor™ Novos, achieving supercomputer-class performance in de novo assembly computation time on standard server hardware, based on a tiered-memory implementation. Run on commercial off-the-shelf servers, Novos assembly is more precise and 10-20 times faster than that of existing assembly algorithms. Furthermore, we integrated Novos into a variant calling pipeline and demonstrate that both compute times and precision of calling point variants and indels compare well with standard alignment-based pipelines. Additionally, assembly eliminates bias in the estimation of allele frequency for indels and naturally enables discovery of breakpoints for structural variants with base pair resolution. Thus, Novos bridges the gap between alignment-based and assembly-based genome analyses. Extension and adaption of its underlying algorithm will help quickly and fully harvest information in sequencing reads for personal genome reconstruction.
Learning from Tasmania: Designing a distinctive student learning experience

lutruwita / Tasmania, an island in the south of Australia, offers one of two popular gateways to Antarctica. Aside from having some of the best beaches in the world, it is the home to one of a handful of the sandstone universities of Australia, University of Tasmania. For the past eighteen years, our colleagues have been collaborating on an annual Teaching Matters conference to share our learning and teaching practice, and collaboratively grow as educators of the next generation of leaders.
On the Origins of Financial Development: Ancestral Population Diversity and Financial Risk-Taking

We show that risk-taking originates in preindustrial ancestral population diversity. We use data on immigrants residing in the United States and show that controlling for all known determinants of portfolio decisions, diversity positively affects stock market participation and asset allocation but not the ownership of bonds or savings accounts. The diversity effect relates to the level of individualism and knowledge in the origin country. Nevertheless, diversity is significant in the presence of more than 100 control variables or when instrumenting diversity with plant variety. Overall, deep-rooted factors unrelated to contemporary social and economic conditions affect risk-taking.
SEPN: A Sequential Engagement Based Academic Performance Prediction Model

Students’ performance prediction is a crucial task in today's online education. By predicting a student's final grade in an academic examination, intervene can be applied in advance. Recently, many machine learning models have been designed to couple students’ online activity with their academic performance. However, it is difficult for these models to effectively make prediction due to the excessive difference in feature selection. While in most cases, too many parameters and heterogeneous features can also be one of the main sticking points. To this end, we propose a sequential engagement based academic performance prediction network. It consists of two main components: an engagement detector and a sequential predictor. The engagement detector leverages the advantages of a convolutional neural network to detect students’ engagement patterns through their daily activities. The sequential predictor adopts the structure of long short-term memory and learns the interaction from the engagement feature spaces and demographic features. By comparing with various existing advanced machine learning models, the results show that this method has better performance than the existing ones when involving the engagement detection mechanism.
Unlocking clients: The importance of relationships in the financial advisory industry

We investigate the importance of client relationships in the financial advisory industry. We exploit firm-level variation in adoption of the Broker Protocol, which enabled clients to follow their advisers to member firms without fear of litigation. We show that advisers’ ability to maintain client relationships is a significant predictor of their employment decisions; that about 40\% of client assets follow advisers when they move; and that once clients are ``unlocked,” firms become less willing to fire advisers for misconduct. Firms that unlock their clients subsequently experience higher levels of misconduct and increase their fees, calling into question whether clients are better off.