Miracle-dz/UniFAR-FTUs huggingface dataset:
Redesigning the process of laparoscopic sleeve gastrectomy based on risk analysis resulted in 100 consecutive procedures without complications

Introduction In recent years, laparoscopic sleeve gastrectomy (LSG) is becoming increasingly popular. The quite simple technique, lack of anastomoses, fully stapling course of the resection and the laparoscopic approach influence the attractiveness of the procedure from the surgeon's perspective. Though the feasibility of LSG is appreciated, the range of complications seems to be considerable. Aim To prospectively evaluate modification of the bariatric process in LSG patients. Material and methods The initial results of the first series of LSG patients (G1) were unacceptable and led to redefinition, based on risk analysis, of the entire bariatric process. A number of corrective and preventive actions were implemented into the process. The impact of innovations on the outcomes of the next 100 LSGs (G2) was assessed. Complications, intraoperative difficulties and postoperative adverse events were registered. Results The total complication rate of the G1 group was 32% (8/25 patients). When several corrective and preventive actions were implemented in the subsequent process, there were no postoperative complications observed in the G2 group. Sixteen intraoperative difficulties were encountered in group G2 but resolved intraoperatively and did not affect the postoperative course. Conclusions The systemic approach to the LSG procedure by innovating the entire process significantly reduced the rate of complications. The ‘learning curve’ should not be limited only to the manual operative training. Preventive actions based on risk analysis should be considered as the core component in redesigning the process.
A Simpler and Faster Strongly Polynomial Algorithm for Generalized Flow Maximization

We present a new strongly polynomial algorithm for generalized flow maximization that is significantly simpler and faster than the previous strongly polynomial algorithm [34]. For the uncapacitated problem formulation, the complexity bound O(mn(m+n log n)log (n2/m)) improves on the previous estimate by almost a factor O(n2). Even for small numerical parameter values, our running time bound is comparable to the best weakly polynomial algorithms. The key new technical idea is relaxing the primal feasibility conditions. This allows us to work almost exclusively with integral flows, in contrast to all previous algorithms for the problem.
Participatory design of an online therapy for youth mental health

Online therapy has the potential to extend existing face-to-face support for mental health, but designers face challenges such as lack of user engagement. Participatory design could improve outcomes but is difficult to pursue in the mental health context. By working with a research-focused clinic we have been able to employ participatory design methods over a period of three years to develop and test an online therapy for young people with psychosis. This paper discusses our methods and results in the light of existing design frameworks for youth mental health, and reports experiences which will be useful for other researchers in the field. We have found that participatory approaches are indeed challenging in the mental health context, but can result in technology that is efficacious and acceptable to young people.
Full-text citation analysis: A new method to enhance scholarly networks

In this article, we use innovative full‐text citation analysis along with supervised topic modeling and network‐analysis algorithms to enhance classical bibliometric analysis and publication/author/venue ranking. By utilizing citation contexts extracted from a large number of full‐text publications, each citation or publication is represented by a probability distribution over a set of predefined topics, where each topic is labeled by an author‐contributed keyword. We then used publication/citation topic distribution to generate a citation graph with vertex prior and edge transitioning probability distributions. The publication importance score for each given topic is calculated by PageRank with edge and vertex prior distributions. To evaluate this work, we sampled 104 topics (labeled with keywords) in review papers. The cited publications of each review paper are assumed to be “important publications” for the target topic (keyword), and we use these cited publications to validate our topic‐ranking result and to compare different publication‐ranking lists. Evaluation results show that full‐text citation and publication content prior topic distribution, along with the classical PageRank algorithm can significantly enhance bibliometric analysis and scientific publication ranking performance, comparing with term frequency–inverted document frequency (tf–idf), language model, BM25, PageRank, and PageRank + language model (p
FSI within Aortic Arch Model over Cardiac Cycle and Influence of Wall Stiffness on Wall Stress in Layered Wall

The aorta is the largest artery that delivers blood from the heart to the rest of the body, and many cardiovascular diseases often occur on the aortic arch. The complex mechanical interaction between pulsatile blood flow and wall dynamics in the aortic arch model was simulated by means of computational loose coupling fluid-structure interaction analyses. This study investigates the pulsatile flow field in the aortic arch, shows the wall displacement and aorta deformation over cardiac cycle, determines wall stresses, evaluated the influence of wall stiffness, and provides physical insight into the biomechanics of aortic dissection. The numerical layered aortic model may prove useful for studying biomechanical analysis and the pathogeneses of aortic dissection.
Bruton's Tyrosine Kinase Regulates the Activation of Gene Rearrangements at the λ Light Chain Locus in Precursor B Cells in the Mouse

Bruton's tyrosine kinase (Btk) is a nonreceptor tyrosine kinase involved in precursor B (pre-B) cell receptor signaling. Here we demonstrate that Btk-deficient mice have an ∼50% reduction in the frequency of immunoglobulin (Ig) λ light chain expression, already at the immature B cell stage in the bone marrow. Conversely, transgenic mice expressing the activated mutant BtkE41K showed increased λ usage. As the κ/λ ratio is dependent on (a) the level and kinetics of κ and λ locus activation, (b) the life span of pre-B cells, and (c) the extent of receptor editing, we analyzed the role of Btk in these processes. Enforced expression of the Bcl-2 apoptosis inhibitor did not alter the Btk dependence of λ usage. Crossing 3-83μδ autoantibody transgenic mice into Btk-deficient mice showed that Btk is not essential for receptor editing. Also, Btk-deficient surface Ig+ B cells that were generated in vitro in interleukin 7-driven bone marrow cultures manifested reduced λ usage. An intrinsic defect in λ locus recombination was further supported by the finding in Btk-deficient mice of reduced λ usage in the fraction of pre-B cells that express light chains in their cytoplasm. These results implicate Btk in the regulation of the activation of the λ locus for V(D)J recombination in pre-B cells.
JURASSIC QUIET ZONE POLARITY REVERSAL MODEL 5271 frequent reversals occurring at rates similar to those of the Miocene

The Jurassic magnetic "Quiet Zone" (JQZ) contains magnetic lineations, but their low amplitudes make correlation and interpretation difficult. Part of the problem is the separation of source and sensor for old, deep ocean crust. We increased anomaly amplitudes by collecting magnetic data along two deep-tow profiles over western Pacific JQZ lineations. A magnetic polarity reversal timescale was constructed by matching deep-tow anomalies with a simple, rectangular block magnetization model for oceanic crust. The polarity sequence covers ~11 m.y. (156-167.5 Ma) and contains 88 pre-M29 polarity chrons extending to Chron M41. A limitation of this model is its poor representation of the oldest anomalies upward continued to sea level. On deep-tow profiles these anomalies have both longand short-wavelength components, but only the latter are easily modeled on a datum close to the source. An alternative polarity model was constructed to match the anomalies upward continued to sea level. This model retains only 44% of the deep-tow model polarity chrons because of short-wavelength attenuation by upward continuation. Because of the inferred periods and magnetization contrasts, we think many of the short-wavelength anomalies represent paleofield intensity fluctuations. In contrast, polarity reversals have been documented by prior magnetostratigraphic work for the younger part of the timescale covered by our model. Thus our data may show a transition from a geomagnetic field behavior dominated by intensity fluctuations to one dominated by reversals.
Incomplete Contingent Labor Contract, Asymmetric Residual Rights and Authority, the Theory of the Firm

In the paper the trade-offs among endogenous transaction costs caused by two-sided moral hazard, exogenous monitoring cost, and economies of specialization are specified in a Grossman, Hart and Moore (GHM) model to absorb Maskin and Tirole’s recent critique and Holmstrom and Milgrom’s criticism of the model of incomplete contract. The extended GHM model allowing incomplete contingent labor contract as well complete contingent contract of goods trade is used to explore the implications of structure of ownership and residual rights for the equilibrium network size of division of labor and productivity.
Differential Diagnosis of Benign and Malignant Intraductal Papillary Mucinous Tumors of the Pancreas: MR Cholangiopancreatography and MR Angiography

Objective To compare the usefulness of magnetic resonance cholangiopancreatography (MRCP) and MR angiography (MRA) in differentiating malignant from benign intraductal papillary mucinous tumors of the pancreas (IPMTs), and to determine the findings which suggest malignancy. Materials and Methods During a 6-year period, 46 patients with IPMT underwent MRCP. Morphologically, tumor type was classified as main duct, branch duct, or combined. The diameter of the main pancreatic duct (MPD), the extent of the dilated MPD, and the location and size of the cystic lesion, septum, and communicating channel were assessed. For all types of IPMTs, enhanced mural nodules and portal vein narrowing were evaluated at MRA. Results Combined-type IPMTs were more frequently malignant (78%) than benign (42%) (p < 0.05). Compared with benign lesions, malignant lesions were larger, and the caliber of the communicating channel was also larger (p < 0.05). Their dilated MPD was more extensive and of greater diameter (p < 0.05), and the presence of mural nodules was more frequent (p < 0.001). Conclusion Combined MRCP and MRA might be useful for the differential diagnosis of malignant and benign IPMTs of the pancreas.
Income, Unemployment and Crime in Turkey: An Analysis of Causality

In this study, the relationship unemployment, GDP per capita and crime in Turkey in the years between 1985 and 2015 is analyzed econometrically and the relationship between these indicators is examined. Unit root test analysis, cointegration analysis and Granger causality model analysis are conducted in the study. In the result of the analysis, it is come into conclusion that there is a long-run relationship between the variables, and there is the two-way causality relationship between crime and GDP per capita and between crime and unemployment. but it is inferred that there is no causality relationship between GDP Per Capita and Unemployment.
Behavior Analysis Using a Multilevel Motion Pattern Learning Framework

The increasing availability of video data, through existing traffic cameras or dedicated field data collection, and the development of computer vision techniques pave the way for the collection of massive data sets about the microscopic behavior of road users. Analysis of such data sets helps in understanding normal road user behavior and can be used for realistic prediction of motion and computation of surrogate safety indicators. A multilevel motion pattern learning framework was developed to enable automated scene interpretation, anomalous behavior detection, and surrogate safety analysis. First, points of interest (POIs) were learned on the basis of the Gaussian mixture model and the expectation maximization algorithm and then used to form activity paths (APs). Second, motion patterns, represented by trajectory prototypes, were learned from road users' trajectories in each AP by using a two-stage trajectory clustering method based on spatial then temporal (speed) information. Finally, motion prediction relied on matching at each instant partial trajectories to the learned prototypes to evaluate potential for collision by using computing indicators. An intersection case study demonstrates the framework's ability in many ways: it helps reduce the computation cost up to 90%; it cleans the trajectory data set from tracking outliers; it uses actual trajectories as prototypes without any pre- and postprocessing; and it predicts future motion realistically to compute surrogate safety indicators.
Reproductive Health Disparities: A Focus on Family Planning and Prevention Among Minority Women and Adolescents

Minority women and adolescent females of all races and ethnicities are disproportionately affected by unintended pregnancy in the United States. Adolescents also experience an additional proportion of the burden compared to other age groups, as 82% of pregnancies among women 19 years old and younger are unintended. Moreover, minority and adolescent mothers are at increased risk for having preterm deliveries, low birth weight infants, and other complications. Unintended pregnancy continues to be an important public health problem in the United States, and prevention through family planning is urgently needed. This review presents an overview of the US demographics for unintended pregnancy among both minority and adolescent women and identifies current and past efforts to reduce unintended pregnancy, specifically among minority and adolescent females, through contraception and family-planning programs.
Silent Pauses in Simulated Request-Refusal Type Dialogues : A Phonetic Analysis of German, Korean, and Japanese

The present study analyzes the phonetic correlates of silent pauses in German, Korean and Japanese. Seventy two adult speakers participated to the experiment. Thirty six pairs of same-sex subjects were formed, i.e. 13 for German, 11 for Korean, and 12 for Japanese. Subjects interacted in 2 to 5 minute role-play dialogues of the 'request-refusal' type. One subject in each pair was instructed to play the role of a student asking for an appointment to the other, a professor, who was to refuse it. The corpus totaled 95 minutes in duration. The durations of silent pauses and of utterances were measured for the acoustic analysis using signal editors. Analyses of variance and other related statistics have been carried out on the measured data converted into logarithmic values. The following factors have been taken into account: language, gender, role, occurrence of pause, and utterance. Three statistically significant findings have been made: (1) a negative correlation between pause length and frequency; (2) a highly significant interaction between language and role, i.e. in each language, students and professors vary in their use of pauses; (3) a greater significance of pause than of utterance effect in interactional management.
Seasonal Factors Influencing Exercise-Induced Asthma

Purpose Exercise-induced bronchoconstriction (EIB) in patients with asthma occurs more frequently in winter than in summer. The concentration of house dust mite (HDM) allergens in beds also shows seasonal variation. This study examined the relationship between seasonal differences in the prevalence of EIB and sensitization to HDMs in patients with asthma. Methods The medical records of 74 young adult male patients with asthma-like symptoms who underwent bronchial challenge with methacholine, 4.5% saline and exercise, and allergen skin prick tests, were reviewed. The subjects were divided into summer (n=27), spring/fall (n=26) and winter (n=21) groups according to the season during which they underwent testing. Results The positive responses to exercise differed according to season (48.1% in summer, 73.1% in spring/fall, and 90.5% in winter; P<0.01). In addition, the prevalence of positive responses to HDM (70.4%, 88.5%, and 95.2%, respectively; P<0.05) and pollen skin tests (37.0%, 19.2%, and 0%, respectively; P<0.01) also showed significant seasonal differences. Severe responses to 4.5% saline showed a similar trend, although it was not statistically significant (44.4%, 50.0%, and 71.4%, respectively; P=0.07). Skin test reactivity to HDMs was significantly related to maximal fall in forced expiratory volume in one second (FEV1) following exercise (r=0.302, P<0.01) and the index of airway hyperresponsiveness (AHR) to 4.5% saline (r=-0.232, P<0.05), but not methacholine (r=-0.125, P>0.05). Conclusions Positive skin test reactions to HDMs and EIB occurred in winter, spring/fall, and summer in decreasing order of frequency. Seasonal variation in the prevalence of EIB may be related to seasonal variation in sensitization to HDMs, accompanied by differences in indirect, but not direct, AHR.
The psychological experience of river guiding: exploring the protective frame and implications for guide well-being

Adventure tours are a fast-growing segment of the tourism market and guide behaviour has been identified as a critical factor in tourist satisfaction. However, little research has investigated guides’ emotional and motivational experiences and implications for psychological well-being. This study analyses critical incidents from autoethnographical data captured during a 10-year span of white-water river guiding in the northern and southern hemispheres. Reversal theory constructs inform analysis of psychological states and emotions experienced throughout guide training, development, and river trip interactions. Factors that may influence guides’ 'protective frames’, emotions, and motivational states are discussed, along with implications for guide and client well-being.
Temperature Control of Fimbriation Circuit Switch in Uropathogenic Escherichia coli: Quantitative Analysis via Automated Model Abstraction

Uropathogenic Escherichia coli (UPEC) represent the predominant cause of urinary tract infections (UTIs). A key UPEC molecular virulence mechanism is type 1 fimbriae, whose expression is controlled by the orientation of an invertible chromosomal DNA element—the fim switch. Temperature has been shown to act as a major regulator of fim switching behavior and is overall an important indicator as well as functional feature of many urologic diseases, including UPEC host-pathogen interaction dynamics. Given this panoptic physiological role of temperature during UTI progression and notable empirical challenges to its direct in vivo studies, in silico modeling of corresponding biochemical and biophysical mechanisms essential to UPEC pathogenicity may significantly aid our understanding of the underlying disease processes. However, rigorous computational analysis of biological systems, such as fim switch temperature control circuit, has hereto presented a notoriously demanding problem due to both the substantial complexity of the gene regulatory networks involved as well as their often characteristically discrete and stochastic dynamics. To address these issues, we have developed an approach that enables automated multiscale abstraction of biological system descriptions based on reaction kinetics. Implemented as a computational tool, this method has allowed us to efficiently analyze the modular organization and behavior of the E. coli fimbriation switch circuit at different temperature settings, thus facilitating new insights into this mode of UPEC molecular virulence regulation. In particular, our results suggest that, with respect to its role in shutting down fimbriae expression, the primary function of FimB recombinase may be to effect a controlled down-regulation (rather than increase) of the ON-to-OFF fim switching rate via temperature-dependent suppression of competing dynamics mediated by recombinase FimE. Our computational analysis further implies that this down-regulation mechanism could be particularly significant inside the host environment, thus potentially contributing further understanding toward the development of novel therapeutic approaches to UPEC-caused UTIs.
Feline Shark Animal Mammal Bird Eagle BlueFish Squirrel Company Snake Bank Dog Cat Thing Lizard Organization Reptile Fish Dolphin Agent Crocodile

Neural-symbolic integration is a field in which classical symbolic knowledge mechanisms are combined with neural networks. This is done to provide satisfactory computational capabilities from the network side and to exploit the descriptive power of symbolic reasoning. Logic Tensor Networks (LTNs) are a deep learning model that can be used to combine data with fuzzy logic to provide inferences and reasoning mechanisms over data. While LTNs have been shown effective in some contexts no detailed analysis on their capabilities for deductive logical reasoning has been conducted. In this paper we explore the capabilities and the limitations of LTNs in terms of deductive reasoning.
An Empirical Study on Preprocessing High-Dimensional Class-Imbalanced Data for Classification

The emerging new data types bring tremendous challenges to data mining. There is an enormous amount of high-dimensional class-imbalanced data in different fields. In this case, traditional classification methods are not appropriate because they are prone to ensure the accuracy of the majority class. Meanwhile, the curse of dimensionality makes situations more complicated. Finding a complicated classifier is not an easy way and such a classifier may overfit for the data. Preprocessing these data before classification is a more direct method. For the cross effect of high-dimension and class-imbalance, it is necessary to know about how preprocessing methods (feature selection and data sampling) affect the final classification. Previous experiments either had less considerations on datasets or introduced other characteristics to make the situation more complicated. We use two types of feature selection (wrapper and filter) and data sampling (oversampling and undersampling) methods on twelve selected datasets with different dimensions and imbalanced-level in four fields, and test the effects on the performance of c4.5 classifier. In our setting, experiments state that (1) feature selection before sampling is mostly better, (2) among the combinations of feature selection and data sampling, undersampling performs better than oversampling when the dataset is largely imbalanced, (3) when dataset is less imbalance, preprocessing may not be necessary, (4) In wrapper-based feature selection, we suggest using the simple searching method.