Miracle-dz/UniFAR-FTUs huggingface dataset:
Incipient speciation in sympatric Nicaraguan crater lake cichlid fishes: sexual selection versus ecological diversification

The growing body of empirical evidence for sympatric speciation has been complemented by recent theoretical treatments that have identified evolutionary conditions conducive to speciation in sympatry. The Neotropical Midas cichlid (Amphilophus citrinellum) fits both of the key characteristics of these models, with strong assortative mating on the basis of a colour polymorphism coupled with trophic and ecological differentiation derived from a polymorphism in their pharyngeal jaws. We used microsatellite markers and a 480 bp fragment of the mitochondrial DNA control region to study four polymorphic populations of the Midas cichlid from three crater lakes and one large lake in Nicaragua in an investigation of incipient sympatric speciation. All populations were strongly genetically differentiated on the basis of geography. We identified strong genetic separation based on colour polymorphism for populations from Lake Nicaragua and one crater lake (Lake Apoyo), but failed to find significant genetic structuring based on trophic differences and ecological niche separation in any of the four populations studied. These data support the idea that sexual selection through assortative mating contributes more strongly or earlier during speciation in sympatry than ecological separation in these cichlids. The long–term persistence of divergent cichlid ecotypes (as measured by the percentage sequence divergence between populations) in Central American crater lakes, despite a lack of fixed genetic differentiation, differs strikingly from the patterns of extremely rapid speciation in the cichlids in Africa, including its crater lakes. It is unclear whether extrinsic environmental factors or intrinsic biological differences, e.g. in the degree of phenotypic plasticity, promote different mechanisms and thereby rates of speciation of cichlid fishes from the Old and New Worlds.
Identifying Novel Drug Indications through Automated Reasoning

Background With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process. Methodology In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications. Conclusion/Significance To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.
STABILITY ANALYSIS AND CONTROL OF A 3-D AUTONOMOUS AI-YUAN-ZHIHAO HYPERCHAOTIC SYSTEM

The stability analysis and control of a three-dimensional autonomous chaotic system that exhibits hyperchaotic properties is presented in this paper. The system's algebraic structure consists of six variable control parameters, three nonlinear terms and two cross-products which triggers hypersensitivity in its dynamic state evolutions. Stability analysis and control via fuzzy modelling confirms the controllability of its unstable orbits in well-tuned regions of stability using Lyapunov principles.
Correlation of magnetic resonance enteroclysis (MRE) and wireless capsule endoscopy (CE) in the diagnosis of small bowel lesions in Crohn's disease

Background: The aim was to evaluate and compare the diagnostic performance of magnetic resonance enteroclysis (MRE) and wireless video capsule endoscopy (CE) in detecting and classifying small bowel Crohn's disease (CD) proximal to the terminal ileum. Methods: Nineteen patients with histologically proven CD (M:F = 13:6; mean 34 years, range 17–65) were prospectively included in the study when presenting with clinical signs suggesting stricturing or inflammatory lesions of CD in the proximal small bowel. All patients underwent MRE with an infusion technique and were then admitted to CE. Results: As for the presence or absence of pathology, results of MRE and CE were in total agreement for 44/52 (85%) evaluated segments. In judging lesion severity, MRE and CE yielded identical results in 29/52 (56%) segments. MRE underestimated pathology in 7/52 (14%) segments and revealed more severe pathology in 6/52 (12%) segments. CE identified subtle (n = 7) or severe (n = 2) mucosal pathology while MRE was normal. CE entirely missed severe inflammatory mural changes depicted in MRE in 1/52 (2%) segments. Conclusions: MRE and CE show good correlation in the detection and localization of inflammatory bowel disease. As for disease activity, MRE is inferior in the detection of superficial mucosal disease but reliably discloses the presence of severe inflammatory changes within the bowel wall and beyond, which may be underestimated from the endoscopic aspect of the mucosal surface. MRE helps to rule out severe stenoses that should be referred for immediate surgical intervention. In conclusion, both modalities are complementary and MRE should be used in more severe cases of Crohn's disease and in patients who might have involvement beyond the mucosa of the small bowel.
The role of impulse oscillometry in detecting airway dysfunction in athletes

Abstract Background: Impulse oscillometry (IOS) has previously been proposed to provide greater sensitivity than spirometry when employed with indirect bronchoprovocation testing for the diagnosis of airway dysfunction in athletes. However, this recommendation is based on a highly selected population of symptomatic patients. Objective: To compare IOS, spirometry and respiratory symptoms following indirect bronchoprovocation in a screened cohort of athletes. Methods: One hundred and one recreational athletes were recruited. Respiratory symptoms were assessed via the Dyspnoea-12 questionnaire. Spirometry and IOS were performed pre and post a eucapnic voluntary hyperpnoea (EVH) challenge. Results: Ninety-four athletes completed the study. Sixteen athletes (17%) were positive for airway dysfunction based on spirometry (i.e. ≥10% fall in FEV1) and 17 athletes (18%) based on IOS (i.e. ≥50% increase in R5). Only nine athletes (10%) met both diagnostic thresholds. A poor relationship was observed between respiratory symptoms (i.e. Dyspnoea-12 score) and all spirometry and IOS variables. A direct relationship was observed between percentage change in R5 (r = 0.65), Z5 (r = 0.68), RF (r = 0.65), AX (r = 0.69) and the maximum fall in FEV1 (ΔFEV1max; p < 0.001). A weak relationship was observed between R20 (r = 0.27), X5 (r = 0.37) and ΔFEV1max (p < 0.01). Conclusion: Impulse oscillometry and spirometry do not concur precisely following indirect bronchoprovocation. However, IOS detects additional cases of airway dysfunction in athletes and therefore may provide diagnostic value in this population. Further work is required to establish diagnostic thresholds and fully determine the place of IOS in screening athletes for airway dysfunction.
Disinformation and the media: the case of Russia and Ukraine

The ongoing conflict between Russia and Ukraine can be analyzed as an instance where the Internet has strengthened the power of political actors to create disinformation. But it is no longer only the state-supported media monopoly that produces and disseminates propaganda. Citizens themselves actively participate in their own disenfranchisement by using social media to generate, consume or distribute false information, contributing to a new order where disinformation acquires increasing authority. This essay follows disinformation practices through the transition from broadcast to social media in post-Soviet times and theorizes how the coexistence of old and new media in the production of propaganda might inform our understanding of future scenarios, including in Western democracies.
Analysis of Work Practices of a Collaborative Software Development Team

This paper reports preliminary results of a field study of a software development team. This team develops a suite of tools called CTAS, designed to help air traffic controllers manage complex air traffic flows at large airports. We observed that CTAS developers employ two main tools for coordinating their work: a configuration management system and a bug tracking system. These tools allow them to coordinate their activities supporting a high level of parallel development. Communication and cooperation among developers with different roles is achieved using product requests. Future results from our study will provide insights into the complexities of cooperative software development and help to design tools to support it.
Kernel MSE algorithm: a unified framework for KFD, LS-SVM and KRR

We generalize the conventional minimum squared error (MSE) method to yield a new nonlinear learning machine by using the kernel idea and adding different regularization terms. We name it kernel minimum squared error (KMSE) algorithm, which can deal with linear and nonlinear classification and regression problems. With proper choices of the output coding schemes and regularization terms, we prove that KMSE is identical to the kernel Fisher discriminant (KFD) except for an unimportant scale factor, and it is directly equivalent to the least square version for support vector machine (LS-SVM). For continuous real output values, we find that KMSE is the kernel ridge regression (KRR) with a bias. Therefore KMSE can act as a general framework that includes KFD, LS-SVM and KRR as its particular cases. In addition, we simplify the formula to estimate the projecting direction of KFD. Experiments on artificial and real world data sets in numerical computation aspects demonstrate that KMSE is a class of powerful kernel learning machines.
Multi-Grid Algorithms with Applications to Elliptic Boundary Value Problems

This work is primarily concerned with solving the large sparse linear systems which arise in connection with finite-element or finite-difference procedures for solving self-adjoint elliptic boundary-value problems. These problems can be expressed in terms of abstract variational problems on Hilbert spaces. Our (mufti-grid) schemes involve a sequence of auxiliary finite-dimensional spaces which do not have to be nested. We approximate the solution using the largest (finite-dimensional) space. These schemes are recursive in nature: they combine smoothing iterations in a space with solving one or more correction problems using smaller spaces. Under certain circumstances, the solution to a problem can be approximated well using smaller spaces. Since the smaller spaces are required to have geometrically fewer unknowns than the largest space, the savings in computation can be substantial. In fact, we prove that these procedures are optimal order under appropriate conditions. Our general theory is discretization.
View-Contingent Aftereffects Suggest Joint Coding of Face Shape and View

While it is well established that different neural populations code different face views, behavioural evidence that these neurons also code other aspects of face shape is equivocal. For example, previous studies have interpreted the partial transfer of face aftereffects across different viewpoints as evidence for either view-specific coding of face shape or that the locus of adaptation is in face-coding mechanisms that are relatively robust to changes in face view. Here we show that it is possible to simultaneously induce aftereffects in opposite directions for 3/4 and front views of upright faces with manipulated mouth position (experiment 1). For example, simultaneous adaptation to 3/4 views with raised mouth position and front views with lowered mouth position caused raised mouth position to appear more normal for 3/4 views of novel faces, but less normal for front views. View-contingent adaptation did not occur for inverted faces, however (experiment 2). Dissociable aftereffects for different views of upright faces, but not for different views of inverted faces, suggest that neurons that code face view can also code other aspects of face shape.
Urinary Tract Infection Molecular Mechanisms and Clinical Translation

Rapid developments in infection biology create new and exciting options for individualized diagnostics and therapy. Such new practices are needed to improve patient survival and reduce morbidity. Molecular determinants of host resistance to infection are being characterized, making it possible to identify susceptible individuals and to predict their risk for future morbidity. Immunotherapy is emerging as a new strategy to treat infections worldwide and controlled boosting of the host immune defense represents an important therapeutic alternative to antibiotics. In proof of concept studies, we have demonstrated that this approach is feasible. The long-term goal is not just to remove the pathogens but to also develop technologies that restore resistance to infection in disease-prone patients and devise personalized therapeutic interventions. Here, we discuss some approaches to reaching these goals, in patients with urinary tract infection (UTI). We describe critical host signaling pathways that define symptoms and pathology and the genetic control of innate immune responses that balance protection against tissue damage. For some of these genes, human relevance has been documented in clinical studies, identifying them as potential targets for immune-modulatory therapies, as a complement to antibiotics.
Beamspace approach broadband array beamformer with sliding window LC-RLS algorithm for moving jammer suppression

In this paper, the beamspace approach for designing a broadband antenna array beamformer, with frequency invariant characteristics, is devised and implemented with the sliding window linearly constrained RLS algorithm, referred to as the SW-LC-RLS beamforming algorithm, to deal with broadband moving jammers suppression. From computer simulation results, we show that the proposed scheme is more robust against moving jammers compared to other conventional algorithms.
Transcription Factors Facilitating the Recruitment of Site-Specific Proinflammatory Gene Expression by 8-Oxoguanine DNA Glycosylase-1 Augments

Among the insidious DNA base lesions, 8-oxo-7,8-dihydroguanine (8-oxoG) is one of the most abundant, a lesion that arises through the attack by reactive oxygen species on guanine, especially when located in cis -regulatory elements. 8-oxoG is repaired by the 8-oxoguanine glycosylase 1 (OGG1)–initiated DNA base excision repair pathway. In this study, we investigated whether 8-oxoG repair by OGG1 in promoter regions is compatible with a prompt gene expression and a host innate immune response. For this purpose, we used a mouse model of airway inﬂammation, supplemented with cell cultures, chromatin immunoprecipitation, small interfering RNA knockdown, real-time PCR, and comet and reporter transcription assays. Our data show that exposure of cells to TNF- a altered cellular redox, increased the 8-oxoG level in DNA, recruited OGG1 to promoter sequences, and transiently inhibited base excision repair of 8-oxoG. Promoter-associated OGG1 then enhanced NF- k B/RelA binding to cis -elements and facilitated recruitment of speciﬁcity protein 1, transcription initiation factor II-D, and p-RNA polymerase II, resulting in the rapid expression of chemokines/cytokines and inﬂammatory cell accumulation in mouse airways. Small interfering RNA depletion of OGG1 or prevention of guanine oxidation signiﬁcantly decreased TNF- a –induced inﬂammatory responses. Taken together, these results show that nonproductive binding of OGG1 to 8-oxoG in promoter sequences could be an epigenetic mechanism to modulate gene expression for a prompt innate promoter and TNF- a –mediated innate immune responses (IIRs) in a mouse model of airway inﬂammation. These data strongly suggest a role of OGG1 in transcriptional activation of proinﬂammatory genes in response to oxidative stress.
Maternal anthropometry as a predictor of birth weight

Abstract Objective To determine whether maternal anthropometry predicted birth weight, and if so, to identify which cut-offs provided the best prediction of low birth weight (LBW) in a field situation. Design Community-based longitudinal study. Setting A rural union of Bhaluka Upazila, Mymensingh, located 110 km north-west of Dhaka, the capital of Bangladesh. Participants A total of 1104 normotensive, non-smoking pregnant women who attended community nutrition centres were studied from first presentation at the centre until delivery of their child. Results Most of the pregnant mothers were between 20 and 34 years of age. Over one-third of the women were nulliparous, while 12.8% were multiparous (parity ≥ 4). Most (93%) mothers registered between the 3rd and 5th month of pregnancy. The frequency of LBW ( < 2500 g) was 17%. Polynomial regression analyses showed that the best predictors of birth weight (based on adjusted R2 values) were in general weight at registration and weight at month 9, with adjusted R2 ranging from 2.5% to nearly 20%. Sequential regression analyses with height and weight showed that there was a significant effect of height after removing the weight variables, and adjusted R2 increased in all analyses. Weight and height at registration month continued to be the best predictors of LBW. Sensitivity and specificity curves were drawn for each registration month, body mass index and different weight gain groups, and using different weight and height combinations. The results showed that, for registration month 3–5, a combination of weight ( ≤ 45 kg) and height ( ≤ 150 cm) gave the highest sensitivity, which was 50%. However, maternal weight ≤ 43 kg in pregnancy month 3–5 alone gave the highest sensitivity of 80%. Conclusion The best predictor of birth weight as a continuous variable was maternal weight at registration, each 1 kg increase in weight at registration being associated with an increase in birth weight of about 260 g. Maternal weight ≤ 43 kg in pregnancy month 3–5 alone gave the highest sensitivity of 80%. A combination of initial weight and height of the mother was not as good a predictor of LBW as weight alone.
Adjoint‐based error estimation and mesh adaptation for hybridized discontinuous Galerkin methods

We present a robust and efficient target‐based mesh adaptation methodology, building on hybridized discontinuous Galerkin schemes for (nonlinear) convection–diffusion problems, including the compressible Euler and Navier–Stokes equations. The hybridization of finite element discretizations has the main advantage that the resulting set of algebraic equations has globally coupled degrees of freedom (DOFs) only on the skeleton of the computational mesh. Consequently, solving for these DOFs involves the solution of a potentially much smaller system. This not only reduces storage requirements but also allows for a faster solution with iterative solvers. The mesh adaptation is driven by an error estimate obtained via a discrete adjoint approach. Furthermore, the computed target functional can be corrected with this error estimate to obtain an even more accurate value. The aim of this paper is twofold: Firstly, to show the superiority of adjoint‐based mesh adaptation over uniform and residual‐based mesh refinement and secondly, to investigate the efficiency of the global error estimate. Copyright © 2014 John Wiley & Sons, Ltd.
Improvement of power efficiency in switched capacitor DC-DC converter by shoot-through current elimination

This paper presents a non overlapped rotational time interleaving scheme to eliminate shoot-through current in switched capacitor dc-dc converters. In addition to the improvement of power efficiency this scheme also reduces the output voltage ripple. In the integrated converter, current regulation control is incorporated with the basic switched capacitor converter to get the output voltage at a pre-specified level. The proposed converter has been designed in 0. 18μm CMOS process with a total flying capacitance of 330pF and load capacitance of 50pF. The capacitors are chosen such that on-chip implementation is possible. The basic switched capacitor converter provides 3.3V to 1.45V conversion and achieves power efficiency of 80.7% and output voltage ripple of 5.7mV at 10mA output current. For the same output current the integrated converter achieves a power power efficiency of 73.5% and output voltage ripple of 5mV for 1.35V output voltage.