Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparing Outcomes of Laparoscopic Versus Open Bariatric Surgery

Objective:The objective of this study was to use nationally representative data to compare outcomes of open gastric bypass (OGB) versus laparoscopic gastric bypass (LGB) surgery. Background:The number of bariatric procedures continues to grow. Increasingly, these surgeries are being performed laparoscopically. However, few population-based studies have examined differences in outcomes between LGB and OGB surgeries. Population-based studies can provide further insight into differences in outcomes between open and laparoscopic bariatric procedures. Methods:Using the Nationwide Inpatient Sample, we identified adults undergoing LGB or OGB surgery during 2005 (n = 19,156). Following preliminary descriptive statistics, multiple logistic and linear regressions were used to obtain risk-adjusted outcomes, including postoperative in-hospital complications, reoperation, length of stay, and total charges. Results:The majority of patients in the study sample (74.5%) underwent laparoscopic bypass surgery in 2005. After adjusting for patient and hospital level factors, patients undergoing OGB surgery were more likely to experience reoperation as well as the following complications: pulmonary (odds ratio [OR] = 1.92 (1.54–2.38), P < 0.001); cardiovascular (OR = 1.54 [1.07–2.23], P = 0.02); procedural (OR = 1.29 [1.06–1.57], P < 0.01); sepsis (OR = 2.18 [1.50–3.16], P < 0.001); and anastomotic leak (OR = 1.32 [1.02–1.71], P = 0.03). After risk adjustment, LGB was associated with a shorter length of stay but higher total charges. Conclusion:Overall, LGB patients are less likely to experience reoperation and postoperative complications in the hospital and have a shorter length of stay but incur higher total charges than OGB patients.
Operationalizing Amartya Sen ’ s Capability Approach through Capability-Equivalent Income

Economic conditions that have a strong impact on individual well-being and freedom are sometimes not reflected in income. Amartya Sen proposed the Capability Approach to capture the welfare impact of such non-income economic condition. However, empirical applications of the capability approach are commonly expressed in reduced form which is not suitable for conducting welfare analysis wherein the distribution of preferences and choice constraints across households are separately identified and accounted for. Using the random utility theory, we incorporate capability into the job market choice set, as well as to the utility through disposable income and leisure. In this approach, we can transform capability to the traditional concept of income, which yields the equivalent utility or welfare as if there were no capability constraints. We deliberately chose Cambodia for the empirical analysis, because the civil war and genocide that occurred in the 1970s in the country can be considered a “natural shock”. These events have resulted in a high proportion of war-related disabilities, which can be considered as a source of capability constraint. By incorporating disability-associated constraints on the job choices and the disability-induced utility difference with respect to income and time spent on leisure, we show that capability disadvantages can be converted to a form of income through the compensation variation, which we denote as capability-equivalent income. We simulate a transfer program where disabled individuals are compensated with capability-equivalent income through an income tax to the top 20% earners. We find that inequality would be mitigated, and the overall welfare of the whole society would improve by 4%.
Search in Audio-Visual Content Using Peer-to-peer Information Retrieval View project Urban Narrative Intelligence Structures Project View project

Gang violence is a severe issue in major cities across the U.S. and recent studies [23] have found evidence of social media communications that can be linked to such violence in communities with high rates of exposure to gang activity. In this paper we partnered computer scientists with social work researchers, who have domain expertise in gang violence, to analyze how public tweets with images posted by youth who mention gang associations on Twitter can be leveraged to automatically detect psychosocial factors and conditions that could potentially assist social workers and violence outreach workers in prevention and early intervention programs. To this end, we developed a rigorous methodology for collecting and annotating tweets. We gathered 1,851 tweets and accompanying annotations related to visual concepts and the psychosocial codes: aggression, loss, and substance use. These codes are relevant to social work interventions, as they represent possible pathways to violence on social media. We compare various methods for classifying tweets into these three classes, using only the text of the tweet, only the image of the tweet, or both modalities as input to the classifier. In particular, we analyze the usefulness of mid-level visual concepts and the role of different modalities for this tweet classification task. Our experiments show that individually, text information dominates classification performance of the loss class, while image information dominates the aggression and substance use classes. Our multimodal approach provides a very promising improvement (18% relative in mean average precision) over the best single modality approach. Finally, we also illustrate the complexity of understanding social media data and elaborate on open challenges.
Multiclass Emotion Analysis Using NLP

: In the present scenario, sentiment analysis has become a popular topic in the field of Machine Learning (ML) and Natural Language Processing (NLP). Sentiment analysis is the systematic process of determining the sentimental tone in a array of words. It helps to understand the emotion, attitudes, and opinions expressed in the sentence. Machine learning techniques are widely used in determining the emotions from texts due to their precise prediction. Various classifiers can be used for performing sentiment analysis which may provide different accuracy. This paper documents a comparative study of three machine learning classifiers namely, Support Vector Machine (SVM), Recurrent Neural Network (RNN)- Long Short Term Memory (LSTM) and Naive Bayes for performing seven class sentiment analysis. The emotions which were considered for this study were: ‘joy’, ‘sadness’, ‘anger’, ‘shame’, ‘guilt’, ‘disgust’ and ‘fear’. For analyzing the performance of these models precision, recall and F1 score were used. From the result, we come to know that the performance of a Recurrent Neural Network was much better than other classifiers .
Stick to Your Gums

Studies on the adherence properties of oral bacteria have been a major focus in microbiology research for several decades. The ability of bacteria to adhere to the variety of surfaces present in the oral cavity, and to become integrated within the resident microbial communities, confers growth and survival properties. Molecular analyses have revealed several families of Gram-positive bacterial surface proteins, including serine-rich repeat, antigen I/II, and pilus families, that mediate adherence to a variety of salivary and oral bacterial receptors. In Gram-negative bacteria, pili, auto-transporters, and extracellular matrix-binding proteins provide components for host tissue recognition and building of complex microbial communities. Future studies will reveal in greater detail the binding pockets for these adhesin families and their receptors. This information will be crucial for the development of new inhibitors or vaccines that target the functional regions of bacterial proteins that are involved in colonization and pathogenesis.
Factors affecting surface roughness of Al 2 O 3 films deposited on Cu substrates by an aerosol deposition method

In an aerosol deposition method, factors affecting the surface roughness of Al2O3 thick films deposited on Cu substrates at room temperature were studied to propose guidelines for the growth of aerosol-deposited ceramic films with a flat and smooth surface morphology. The surface roughness and deposition rates of aerosol-deposited Al2O3 films strongly depended on the initial surface roughness of substrates. Even on flat substrates, however, their surface roughness became worse with an increase of their film thickness. Through the investigation of surface morphologies from the initial growth stages to the final, it was revealed that the deterioration of the surface roughness of Al2O3 films on flat substrates was substantially associated with the evolution of craters during the deposition. The fundamental cause of these results was explained by impact of hard Al2O3 particles above 1 ìm in size by comparison with the surface morphologies of the aerosol-deposited Ag or polyimide films.
Comparative effects of rauwolscine, prazosin, and phentolamine on blood pressure and cardiac output in anesthetized rats.

The endogenous role of the alpha-adrenergic system in the maintenance of mean arterial pressure (MAP), total peripheral resistance (TPR), cardiac output (CO) and its distribution, and plasma norepinephrine and epinephrine release was investigated by the administration of selective alpha-adrenoceptor antagonists to halothane-anesthetized rats. The blockade of alpha 1-, alpha 2-, and both alpha 1- and alpha 2-receptors was accomplished by i.v. infusions of prazosin, rauwolscine, and phentolamine, respectively. The microsphere technique was used for the determination of CO and its distribution. Since the infusions of the three antagonists caused similar decreases of MAP and heart rate, the results suggest that postjunctional alpha 1- and alpha 2-receptors are both important in the control of MAP. During the infusion of prazosin, TPR was decreased but CO was not changed. In contrast, CO was decreased but TPR was not changed during the infusions of rauwolscine and phentolamine. Thus, CO was reduced after the blockade of alpha 2- but not alpha 1-receptors. All three antagonists caused an increase in percent distribution of CO to the lungs and muscle, suggesting that the sympathetic nervous system plays the greatest vasoconstrictor influence in the lungs and muscle via stimulations of both subtypes of alpha-adrenoceptors. The administration of either prazosin or rauwolscine caused little change in plasma catecholamine levels. In contrast, phentolamine caused large increases in both epinephrine and norepinephrine levels. Therefore catecholamine release was only increased after concurrent blockade of both alpha 1- and alpha 2-adrenoceptors.
Sociodemographic characteristics of dropouts from a child guidance clinic.

OBJECTIVE This study examined the characteristics of families who dropped out and families who maintained contact with a children's psychiatric outpatient clinic through various phases of intake and treatment. METHODS One year after intake, the authors examined the status of all patients (N = 555) who had sought treatment at an urban, university-affiliated children's psychiatric outpatient clinic over a two-year period and had completed the intake process. Factors associated with dropout were identified at four points in the clinic process: during intake, during evaluation, at completion of evaluation, and during treatment. RESULTS Urban residence, minority status, single-parent status, and Medicaid status were related to dropout at intake and during evaluation but not at subsequent clinic phases. Nonminority, two-parent, suburban families of higher socioeconomic status were more likely to drop out at the completion of the evaluation. CONCLUSIONS These results indicate that factors associated with attrition vary with the clinic phase. Further investigations of the clinical course of minority children and families involved with children's mental health services are necessary to understand the needs of this population and to design interventions such as increasing minority staff and providing training in multi-cultural competence.
Knowledge and Learning Capabilities in Nonprofit Organizations: A Relational Capital Perspective

Relational capital (RC) represents the knowledge and learning capabilities embedded in relationships external to an organization. The primary goal of this paper is to report preliminary findings through qualitative in-depth interviews collected from 35 senior executives in relation to their perceptions of RC in building knowledge and enhancing learning capability in 22 Australian nonprofit organizations. The findings revealed that RC was valued as the concept perceived to be able to assist nonprofit managers to conceptualize the development of knowledge and learning capabilities in external stakeholder relationships. However, the understanding and application of RC were substantially different to those contained in the literature. Scholars suggest that a balanced view of RC is essential when establishing external stakeholder relationships. The nonprofit managers often adopted a more focused relationship with key external stakeholders, which also happened to be primary fund providers for the organizations. Research implications of this theory-practice divide are discussed. Research limitations and future research direction are presented in the paper.
Induction of Gene Silencing by Hairpin RNA Expression in Tetrahymena thermophila Reveals a Second Small RNAPathway

ABSTRACT Unlike in other eukaryotes, in which it causes gene silencing, RNA interference (RNAi) has been linked to programmed DNA deletion in the ciliate Tetrahymena thermophila. Here we have developed an efficient method to inducibly express double-stranded RNA hairpins and demonstrated that they cause gene silencing through targeted mRNA degradation in all phases of the life cycle, including growth, starvation, and mating. This technique offers a new tool for gene silencing in this model organism. Induction of RNA hairpins causes dramatic upregulation of Dicer and Argonaute family genes, revealing a system capable of rapidly responding to double-stranded RNA. These hairpins are processed into 23- to 24-nucleotide (nt) small RNAs, which are distinctly different from the 28- to 30-nt small RNAs known to be associated with DNA deletion. Thus, two different small RNA pathways appear to be responsible for gene silencing and DNA deletion. Surprisingly, expression of the RNA hairpin also causes targeted DNA deletion during conjugation, although at low efficiencies, which suggests a possible crossover of these two molecular paths.
STRATEGIES TO MINIMIZE GENETIC DRIFT AND MAXIMIZE EXPERIMENTAL REPRODUCIBILITY IN MOUSE RESEARCH

THE IMPORTANCE OF GENETIC STABILITY IN MOUSE RESEARCH Genetic drift occurs in any independent mouse breeding colony and has the potential to negatively affect experimental reproducibility and scientific conclusions. Spontaneous mutations caused by genetic drift may go unrecognized for years until the specific research questions that depend on such mutations happen to be addressed. While it cannot be stopped completely, genetic drift and the impact on scientific discovery can be minimized through careful and thoughtful colony management practices. Because individual mouse breeding colonies may differ in size and management strategies, use of complete and accurate mouse strain nomenclature, including substrain designation, benefits the scientific community as a whole. To the average life science researcher, a mouse’s genetic background may be an afterthought, if even a thought at all. A researcher’s top priorities may be to understand disease, publish, and obtain funding. However, to successfully reach these goals, maintaining genetic stability, or preventing genetic drift, in a mouse colony should be of high importance. Laboratory mice are unique, live elements in scientific research that change over the course of their lifetime, and, importantly, from one generation to the next. After all, heritable changes in DNA sequence are the basis for species diversity and evolution in the wild. Even in the absence of evolutionary pressure, changes in DNA sequence occur. At first glance, these mutations seem to be silent, unimportant fluctuations in the genetic makeup of an individual. However, these seemingly insignificant mutations can become the source of unexplainable experimental irreproducibility. Mouse researchers, then, are met with a conundrum. Generating mice for research requires breeding, but with breeding comes the inherent risk to propagate genetic diversity and thus, to propagate experimental diversity. From one experiment to the next and from one publication to the next, data diversity is detrimental to scientific progress. The purpose of this paper is to educate researchers on the potential for genetic drift to impact research progress, to highlight best practices to minimize drift, and provide solutions to reverse drift if it arises in a mouse colony.
NWO / STAR / PWN Winter School on Mathematical Finance

Minicourse on Rough volatility Jim Gatheral (The City University of New York) Rough volatility The scaling properties of historical volatility time series, which now appear to be universal, together with the scaling properties of implied volatility smiles, motivate a new class of stochastic volatility models where paths of volatility are rougher than those of Brownian motion. Rough volatility connects the microstructure of financial markets with the large-scale behavior of volatility as encoded in the implied volatility surface. Rough volatility models are typically very parsimonious yet are in remarkable agreement with both econometric data and option prices. Practical applications include efficient forecasting of future integrated variance and option pricing. This mini-course will include the following topics: • Scaling properties of the time series of historical volatility • Estimation of H • Volatility forecasting • The volatility surface: Stylized facts • The rough Bergomi model • Relating historical and implied model parameters • The rough Heston model • The hybrid BSS scheme • Diamonds and the Exponentiation Theorem • Calibration of model parameters References: 1. Elisa Alòs, Jim Gatheral, and Radoš Radoičić, Exponentiation of conditional expectations under stochastic volatility, https://papers.ssrn. com/sol3/papers.cfm? abstract_id= 2983180, (2017). 2. Christian Bayer, Peter Friz and Jim Gatheral, Pricing under rough volatility, Quantitative Finance 16(6), 887-904, (2016). 3. Mikkel Bennedsen, Asger Lunde, and Mikko S. Pakkanen, Hybrid scheme for Brownian semistationary processes, Finance and Stochastics 21(4), 931-965, (2017). 4. Mikkel Bennedsen, Asger Lunde, and Mikko S. Pakkanen, Decoupling the short-and longterm behavior of stochastic volatility, https://arxiv.org/abs/1610.00332, (2016). 5. Omar El Euch and Mathieu Rosenbaum, The characteristic function of rough Heston models, Mathematical Finance, https://onlinelibrary.wiley. com/doi/10.1111/ mafi.12173, (2018).
Changes in Transcript Abundance in Chlamydomonas reinhardtii following Nitrogen Deprivation Predict Diversion of Metabolism1[W][OA]

Like many microalgae, Chlamydomonas reinhardtii forms lipid droplets rich in triacylglycerols when nutrient deprived. To begin studying the mechanisms underlying this process, nitrogen (N) deprivation was used to induce triacylglycerol accumulation and changes in developmental programs such as gametogenesis. Comparative global analysis of transcripts under induced and noninduced conditions was applied as a first approach to studying molecular changes that promote or accompany triacylglycerol accumulation in cells encountering a new nutrient environment. Towards this goal, high-throughput sequencing technology was employed to generate large numbers of expressed sequence tags of eight biologically independent libraries, four for each condition, N replete and N deprived, allowing a statistically sound comparison of expression levels under the two tested conditions. As expected, N deprivation activated a subset of control genes involved in gametogenesis while down-regulating protein biosynthesis. Genes for components of photosynthesis were also down-regulated, with the exception of the PSBS gene. N deprivation led to a marked redirection of metabolism: the primary carbon source, acetate, was no longer converted to cell building blocks by the glyoxylate cycle and gluconeogenesis but funneled directly into fatty acid biosynthesis. Additional fatty acids may be produced by membrane remodeling, a process that is suggested by the changes observed in transcript abundance of putative lipase genes. Inferences on metabolism based on transcriptional analysis are indirect, but biochemical experiments supported some of these deductions. The data provided here represent a rich source for the exploration of the mechanism of oil accumulation in microalgae.
Influence of environmental heterogeneity on genetic diversity and structure in an endemic southern Californian oak

Understanding how specific environmental factors shape gene flow while disentangling their importance relative to the effects of geographical isolation is a major question in evolutionary biology and a specific goal of landscape genetics. Here, we combine information from nuclear microsatellite markers and ecological niche modelling to study the association between climate and spatial genetic structure and variability in Engelmann oak (Quercus engelmannii), a wind‐pollinated species with high potential for gene flow. We first test whether genetic diversity is associated with climatic niche suitability and stability since the Last Glacial Maximum (LGM). Second, we use causal modelling to analyse the potential influence of climatic factors (current and LGM niche suitability) and altitude in the observed patterns of genetic structure. We found that genetic diversity is negatively associated with local climatic stability since the LGM, which may be due to higher immigration rates in unstable patches during favourable climatic periods and/or temporally varying selection. Analyses of spatial genetic structure revealed the presence of three main genetic clusters, a pattern that is mainly driven by two highly differentiated populations located in the northern edge of the species distribution range. After controlling for geographic distance, causal modelling analyses showed that genetic relatedness decreases with the environmental divergence among sampling sites estimated as altitude and current and LGM niche suitability. Natural selection against nonlocal genotypes and/or asynchrony in reproductive phenology may explain this pattern. Overall, this study suggests that local environmental conditions can shape patterns of genetic structure and variability even in species with high potential for gene flow and relatively small distribution ranges.