Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Validation of Aviation Causal Contributors for Error Reporting Systems (ACCERS)

Objective: This investigation sought to develop a reliable and valid classification system for identifying and classifying the underlying causes of pilot errors reported under the Aviation Safety Action Program (ASAP). Background: ASAP is a voluntary safety program that air carriers may establish to study pilot and crew performance on the line. InASAP programs, similar to the Aviation Safety Reporting System, pilots self-report incidents by filing a short text description of the event. The identification of contributors to errors is critical if organizations are to improve human performance, yet it is difficult for analysts to extract this information from text narratives. A taxonomy was needed that could be used by pilots to classify the causes of errors. Method: After completing a thorough literature review, pilot interviews and a card-sorting task were conducted in Studies 1 and 2 to develop the initial structure of the Aviation Causal Contributors for Event Reporting Systems (ACCERS) taxonomy. The reliability and utility of ACCERS was then tested in studies 3a and 3b by having pilots independently classify the primary and secondary causes of ASAP reports. Results: The results provided initial evidence for the internal and external validity of ACCERS. Pilots were found to demonstrate adequate levels of agreement with respect to their category classifications. Conclusions: ACCERS appears to be a useful system for studying human error captured under pilot ASAP reports. Future work should focus on how ACCERS is organized and whether it can be used or modified to classify human error in ASAP programs for other aviation-related job categories such as dispatchers. Application: Potential applications of this research include systems in which individuals self-report errors and that attempt to extract and classify the causes of those events.
Systematic Analysis of Immune Infiltrates in High-Grade Serous Ovarian Cancer Reveals CD20, FoxP3 and TIA-1 as Positive Prognostic Factors

Background Tumor-infiltrating T cells are associated with survival in epithelial ovarian cancer (EOC), but their functional status is poorly understood, especially relative to the different risk categories and histological subtypes of EOC. Methodology/Principal Findings Tissue microarrays containing high-grade serous, endometrioid, mucinous and clear cell tumors were analyzed immunohistochemically for the presence of lymphocytes, dendritic cells, neutrophils, macrophages, MHC class I and II, and various markers of activation and inflammation. In high-grade serous tumors from optimally debulked patients, positive associations were seen between intraepithelial cells expressing CD3, CD4, CD8, CD45RO, CD25, TIA-1, Granzyme B, FoxP3, CD20, and CD68, as well as expression of MHC class I and II by tumor cells. Disease-specific survival was positively associated with the markers CD8, CD3, FoxP3, TIA-1, CD20, MHC class I and class II. In other histological subtypes, immune infiltrates were less prevalent, and the only markers associated with survival were MHC class II (positive association in endometrioid cases) and myeloperoxidase (negative association in clear cell cases). Conclusions/Significance Host immune responses to EOC vary widely according to histological subtype and the extent of residual disease. TIA-1, FoxP3 and CD20 emerge as new positive prognostic factors in high-grade serous EOC from optimally debulked patients.
Effect of intravenous injection of biperiden and clonazepam in dystonia

The acute effect of intravenous injections of biperiden and clonazepam was investigated in 14 patients with various forms of dystonia (segmental dystonia, 2; generalized dystonia, 6; and Meige's syndrome, 6). Eleven patients had primary dystonia, and 3 patients had a secondary form of dystonia. Doses of 5 mg of biperiden reduced dystonia when evaluated by total scores, global scores, and subjective scores. Two patients had marked side effects in the form of dizziness. Doses of 1 mg of clonazepam significantly reduced total scores and subjective scores, but the reduction in global score was insignificant. No patient had marked side effects following injection with clonazepam. These results correspond with earlier investigations of the longterm effects of anticholinergics and benzodiazepines. It is concluded that in some cases, intravenous injections can be used as a test for evaluating both effects and side effects of antidystonic medication prior to the institution of oral treatment. Long‐term intravenous treatment might be considered in individual cases.
Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study

Objectives To assess the performance of a panel of common single nucleotide polymorphisms (genotypes) associated with type 2 diabetes in distinguishing incident cases of future type 2 diabetes (discrimination), and to examine the effect of adding genetic information to previously validated non-genetic (phenotype based) models developed to estimate the absolute risk of type 2 diabetes. Design Workplace based prospective cohort study with three 5 yearly medical screenings. Participants 5535 initially healthy people (mean age 49 years; 33% women), of whom 302 developed new onset type 2 diabetes over 10 years. Outcome measures Non-genetic variables included in two established risk models—the Cambridge type 2 diabetes risk score (age, sex, drug treatment, family history of type 2 diabetes, body mass index, smoking status) and the Framingham offspring study type 2 diabetes risk score (age, sex, parental history of type 2 diabetes, body mass index, high density lipoprotein cholesterol, triglycerides, fasting glucose)—and 20 single nucleotide polymorphisms associated with susceptibility to type 2 diabetes. Cases of incident type 2 diabetes were defined on the basis of a standard oral glucose tolerance test, self report of a doctor’s diagnosis, or the use of anti-diabetic drugs. Results A genetic score based on the number of risk alleles carried (range 0-40; area under receiver operating characteristics curve 0.54, 95% confidence interval 0.50 to 0.58) and a genetic risk function in which carriage of risk alleles was weighted according to the summary odds ratios of their effect from meta-analyses of genetic studies (area under receiver operating characteristics curve 0.55, 0.51 to 0.59) did not effectively discriminate cases of diabetes. The Cambridge risk score (area under curve 0.72, 0.69 to 0.76) and the Framingham offspring risk score (area under curve 0.78, 0.75 to 0.82) led to better discrimination of cases than did genotype based tests. Adding genetic information to phenotype based risk models did not improve discrimination and provided only a small improvement in model calibration and a modest net reclassification improvement of about 5% when added to the Cambridge risk score but not when added to the Framingham offspring risk score. Conclusion The phenotype based risk models provided greater discrimination for type 2 diabetes than did models based on 20 common independently inherited diabetes risk alleles. The addition of genotypes to phenotype based risk models produced only minimal improvement in accuracy of risk estimation assessed by recalibration and, at best, a minor net reclassification improvement. The major translational application of the currently known common, small effect genetic variants influencing susceptibility to type 2 diabetes is likely to come from the insight they provide on causes of disease and potential therapeutic targets.
General properties of general Bayesian learning

We investigate the general properties of general Bayesian learning, where ``general Bayesian learning'' means inferring a state from another that is regarded as evidence, and where the inference is conditionalizing the evidence using the conditional expectation determined by a reference probability measure representing the background subjective degrees of belief of a Bayesian Agent performing the inference. States are linear functionals that encode probability measures by assigning expectation values to random variables via integrating them with respect to the probability measure. If a state can be learned from another this way, then it is said to be Bayes accessible from the evidence. It is shown that the Bayes accessibility relation is reflexive, antisymmetric and non-transitive. If every state is Bayes accessible from some other defined on the same set of random variables, then the set of states is called weakly Bayes connected. It is shown that the set of states is not weakly Bayes connected if the probability space is standard. The set of states is called weakly Bayes connectable if, given any state, the probability space can be extended in such a way that the given state becomes Bayes accessible from some other state in the extended space. It is shown that probability spaces are weakly Bayes connectable. Since conditioning using the theory of conditional expectations includes both Bayes' rule and Jeffrey conditionalization as special cases, the results presented generalize substantially some results obtained earlier for Jeffrey conditionalization.
Relation of Stimulus-Size to Pattern Discrimination Training for the Hooded Rat

Two experiments were performed to determine the relation of pattern area, background area, and pattern-background ratio to discrimination learning in the hooded rat. In Exp. 1 (triangle-circle discrimination) and Exp. 2 (diamond-square discrimination) a 1-sq. in. pattern placed on a 4-sq. in. background resulted in faster learning and a higher level of performance than three other pattern-background combinations. It was concluded that (a) supraliminal variation in stimulus-size is related to efficiency of discrimination learning, and (b) a unique combination of an optimal pattern and background area may be more critical than pattern area, background area, or pattern-background ratio per se.
QoS based aggregation in high speed IEEE802.11 wireless networks

We propose a novel frame aggregation algorithm with statistical delay guarantee for high speed IEEE802.11 networks considering link quality fluctuations. We use the concept of effective capacity to formulate frame aggregation with QoS guarantee as an optimization problem. The QoS guarantee is in the form of a target delay bound and violation probability. We apply proper approximations to derive a simple formulation, which is solved using a Proportional-Integral-Derivative (PID) controller. The proposed PID aggregation algorithm independently adapts the amount of time allowance for each link, while it needs to be implemented only at the Access Point (AP), without requiring any change to the 802.11 Medium Access Control (MAC). More importantly, the aggregator does not consider any physical layer or channel information, as it only makes use of queue level metrics, such as average queue length and link utilization, for tuning the amount of time allowance. NS-3 simulations show that our proposed scheme outperforms Earliest Deadline First (EDF) scheduling with maximum aggregation size and pure deadline-based aggregation, both in terms of maximum number of stations and channel efficiency.
DIRAC FUNDAMENTAL QUANTIZATION OF GAUGE THEORIES IS THE NATURAL WAY OF REFERENCE FRAMES IN MODERN PHYSICS

We analyse two known principal approaches to the quantization of physical models. They are the Faddeev-Popov (FP) “heuristic” approach, based on fixing a gauge in the FP path integrals formalism, and the “fundamental” approach of Dirac based on the constraint-shell reduction of Hamiltonians with deleting of unphysical variables. The relativistically invariant FP “heuristic” approach deals with a small class of problems associated with S-matrices squared considering on-shell quantum fields. On the other hand, the “fundamental” quantization approach of Dirac involves the manifest relativistic covariance of quantum fields that survive the constraintshell reduction of Hamiltonians. One can apply this approach to a broader class of problems than by studying S-matrices. Investigations of various bound states in QED and QCD are examples of such applications. In the present study, with the example of the Dirac “fundamental” quantization of the Minkowskian non-Abelian Higgs model (studied in its historical retrospective), we show obvious advantages of this quantization approach. The arguments in favour of the Dirac fundamental quantization of a physical model will be presented as a way of Einstein and Galilei relativity in modern physics.
Yield and characterization of subcutaneous human adipose-derived stem cells by flow cytometric and adipogenic mRNA analyzes.

BACKGROUND AIMS Adipose-derived stromal/stem cells (ASC) capable of multipotential differentiation can be isolated with high yields from human subcutaneous lipoaspirates. This study reports our recent experience of isolating and immunophenotypically characterizing ASC from >60 human patients with a mean age of 43.6 and body mass index (BMI) of 27. METHODS We examined the ASC yield per unit volume of lipoaspirate tissue, the surface antigen profile based on flow cytometry, histochemical differentiation potential along the adipogenic and osteogenic pathways, and expression of adipogenic mRNA by transcriptomic microarray and reverse transcription (RT)-polymerase chain reaction (PCR). RESULTS The population (n = 64) of predominantly Caucasian (84.3%) female (90.6%) donors had a mean age of 43.6 +/- 11.1 years and a mean BMI of 27.0 +/- 3.8. A yield of 375 +/- 142 x 10(3) ASC was obtained per milliliter of lipoaspirate within a 4.1 +/- 0.7-day culture period (n = 62). The ASC population was uniformly CD29(+) CD34(+) CD44(lo) CD45(lo) CD73(+) CD90(+) CD105(+) and capable of undergoing both adipogenesis and osteogenesis in vitro based on Oil Red O and Alizarin Red staining, respectively. Adipogenic differentiation was associated with a significant induction of multiple mRNA associated with lipid storage and synthesis based on microarray analysis of n = 3 donors. During an adipogenic differentiation time-course, representative mRNA (adiponectin, C/EBPalpha, leptin and LPL) displayed increases of several orders of magnitude. CONCLUSIONS These findings demonstrate the reproducibility of subcutaneous lipoaspirates as a consistent and abundant source of functional ASC from donors across a spectrum of ages and BMI. These results have relevance for regenerative medical applications exploiting autologous and allogeneic ASC for soft and hard tissue engineering.
A Spin Glass Model of Path Integration in Rat Medial Entorhinal Cortex

Electrophysiological recording studies in the dorsocaudal region of medial entorhinal cortex (dMEC) of the rat reveal cells whose spatial firing fields show a remarkably regular hexagonal grid pattern (Fyhn et al., 2004; Hafting et al., 2005). We describe a symmetric, locally connected neural network, or spin glass model, that spontaneously produces a hexagonal grid of activity bumps on a two-dimensional sheet of units. The spatial firing fields of the simulated cells closely resemble those of dMEC cells. A collection of grids with different scales and/or orientations forms a basis set for encoding position. Simulations show that the animal’s location can easily be determined from the population activity pattern. Introducing an asymmetry in the model allows the activity bumps to be shifted in any direction, at a rate proportional to velocity, to achieve path integration. Furthermore, information about the structure of the environment can be superimposed on the spatial position signal by modulation of the bump activity levels without significantly interfering with the hexagonal periodicity of firing fields. Our results support the conjecture of Hafting et al. (2005) that an attractor network in dMEC may be the source of path integration information afferent to hippocampus.
Presence of a conspecific causes divergent changes in resting metabolism, depending on its relative size

It is well established that the average metabolism of many species of fish varies with group size. However, it is not clear whether all individuals respond in the same way. Here, we use a newly calibrated method of measuring the metabolic rate of fish from opercular (ventilatory) movements that allows for the first-time estimation of changes in resting metabolic rate (RMR) of each individual within different social groups and when alone. The presence of a conspecific had divergent effects on the RMR of juvenile Atlantic salmon Salmo salar, depending on its relative body size: the presence of a smaller fish caused a 40 per cent reduction, whereas the presence of a slightly larger fish approximately doubled RMR. These effects occurred in the absence of activity and were sustained at lower magnitude in the case of the relatively smaller conspecific even if a transparent barrier prevented any physical interactions between fish. Changes in RMR were mirrored by changes in eye colour that indicate they were linked to stress levels. These contrasting and strong responses show that even the nearby presence of a conspecific can have profound and variable effects on an individual's energy budget; they also highlight the complex trade-offs involved in social interactions.
Eliminating false matches for the projective registration of free-form surfaces with small translational motions

In this paper, we make a detailed study of two rigid-motion constraints. The importance of these two constraints is twofold: first, they reveal the inherent relationship between the three-dimensional-two-dimensional (3-D-2-D) point correspondences and the motion parameters of interest; second, they can be used to measure the traditional ICP criterion established point match qualities based on which different point matches can be compared and relatively good point matches can be selected for motion-parameter update in the projective registration of free-form surfaces subject to small translational motions. The experimental results based on both synthetic data and real images have shown that the rigid motion constraints are powerful in evaluating the possible 3-D-2-D point matches established by the traditional ICP criterion, thus achieving encouraging projective registration results.
Universal behavior of the osmotically compressed cell and its analogy to the colloidal glass transition

Mechanical robustness of the cell under different modes of stress and deformation is essential to its survival and function. Under tension, mechanical rigidity is provided by the cytoskeletal network; with increasing stress, this network stiffens, providing increased resistance to deformation. However, a cell must also resist compression, which will inevitably occur whenever cell volume is decreased during such biologically important processes as anhydrobiosis and apoptosis. Under compression, individual filaments can buckle, thereby reducing the stiffness and weakening the cytoskeletal network. However, the intracellular space is crowded with macromolecules and organelles that can resist compression. A simple picture describing their behavior is that of colloidal particles; colloids exhibit a sharp increase in viscosity with increasing volume fraction, ultimately undergoing a glass transition and becoming a solid. We investigate the consequences of these 2 competing effects and show that as a cell is compressed by hyperosmotic stress it becomes progressively more rigid. Although this stiffening behavior depends somewhat on cell type, starting conditions, molecular motors, and cytoskeletal contributions, its dependence on solid volume fraction is exponential in every instance. This universal behavior suggests that compression-induced weakening of the network is overwhelmed by crowding-induced stiffening of the cytoplasm. We also show that compression dramatically slows intracellular relaxation processes. The increase in stiffness, combined with the slowing of relaxation processes, is reminiscent of a glass transition of colloidal suspensions, but only when comprised of deformable particles. Our work provides a means to probe the physical nature of the cytoplasm under compression, and leads to results that are universal across cell type.
Shrink fast correctly!

Function inlining, case-folding, projection-folding, and dead-variable elimination are important code transformations in virtually every functional-language compiler. When one of these reductions strictly reduces the size of the program (e.g., when the inlined function has only one applied occurrence), we call it a shrink reduction. Appel and Jim [1] introduced an algorithm to perform all shrink reductions (producing a shrink normal form) in quasilinear time. They proved confluence but not correctness. We have implemented this algorithm as part of an end-to-end verified compiler for Gallina, the specification language of the Coq theorem prover. We have given the first proofs of these properties: correctness with respect to contextual equivalence, reduction (in one pass) of all administrative redexes with one applied occurrence introduced by CPS conversion, and termination. The correctness and termination proofs are machine-checked in Coq. Because we use a pure functional language without imperative array update, our implementation is O(N log N) rather than O(N). Still, it's quite fast: we give performance results on some nontrivial benchmarks.
KW-class clad-pumped Raman all-fiber laser with brightness enhancement

The importance of average power scaling of fiber lasers (FL) is well known. However, power scaling is strongly limited by factors such as thermal load, and non-linear effects. An alternative path for reaching high powers utilizes the stimulated Raman scattering mechanism, and harnesses its power and brightness enhancement potential to reach high average power, high brightness FL. kW scale Raman FLs have been demonstrated, however they are in core-pumping configurations, meaning that they require an a-priori existing brighter kW laser that acts as their pump modules. There have been only a few publications of Raman FLs where the generated signal has a higher brightness than the pump source at levels of ≥100W, the highest, being at 250W. Here we report a strictly all-fiber clad pumped Raman FL with a CW power output of 800 W with a conversion efficiency of 80%. To the best of our knowledge this is the highest power and highest efficiency Raman FL demonstrated in any configuration allowing brightness enhancement (i.e clad pumped or graded index fiber, excluding step-index core pumped), thus being the first kW-class Raman FL with brightness enhancement. This result was achieved with a specially designed triple-clad fiber (TCF). The core was 25 μm, 0.065 NA, and the inner cladding was 45 μm 0.22NA. The choice of the small inner clad allows obtaining sufficient Raman gain without requiring too long a fiber, as well as being compatible with the waist size of the pump source fiber. In addition this diameter complies with the inner-clad/core ratio which prevents generation of a 2nd Stokes laser beam. Two fiber Bragg gratings at 1120 nm written onto the TCF, were employed as the oscillator’s reflectors. The cavity was pumped by a lower beam-quality source with an M2 of ~8 at 1070 nm. The Raman signal generated in the core, at the first Stokes wavelength of 1120 nm, showed an improved beam-quality in relation to the pump.