Miracle-dz/UniFAR-FTUs huggingface dataset:
What is an error?

CONTEXT Launched by the Institute of Medicine's report, "To Err is Human," the reduction of medical errors has become a top agenda item for virtually every part of the U.S. health care system. OBJECTIVE To identify existing definitions of error, to determine the major issues in measuring errors, and to present recommendations for how best to proceed. DATA SOURCE Medical literature on errors as well as the sociology and industrial psychology literature cited therein. RESULTS We have four principal observations. First, errors have been defined in terms of failed processes without any link to subsequent harm. Second, only a few studies have actually measured errors, and these have not described the reliability of the measurement. Third, no studies directly examine the relationship between errors and adverse events. Fourth, the value of pursuing latent system errors (a concept pertaining to small, often trivial structure and process problems that interact in complex ways to produce catastrophe) using case studies or root cause analysis has not been demonstrated in either the medical or nonmedical literature. CONCLUSION Medical error should be defined in terms of failed processes that are clearly linked to adverse outcomes. Efforts to reduce errors should be proportional to their impact on outcomes (preventable morbidity, mortality, and patient satisfaction) and the cost of preventing them. The error and the quality movements are analogous and require the same rigorous epidemiologic approach to establish which relationships are causal.
Generative Oversampling for Mining Imbalanced Datasets

—One way to handle data mining problems where class prior probabilities and/or misclassiﬁcation costs between classes are highly unequal is to resample the data until a new, desired class distribution in the training data is achieved. Many resampling techniques have been proposed in the past, and the relationship between resampling and cost-sensitive learning has been well studied. Surprisingly, however, few resampling techniques attempt to create new, artiﬁcial data points which generalize the known, labeled data. In this paper, we introduce an easily implementable resampling technique (generative oversampling) which creates new data points by learning from available training data. Empirically, we demonstrate that generative oversampling outperforms other well-known resampling methods on several datasets in the example domain of text classiﬁcation.
Promoting Sleep Oscillations and Their Functional Coupling by Transcranial Stimulation Enhances Memory Consolidation in Mild Cognitive Impairment

Alzheimer's disease (AD) not only involves loss of memory functions, but also prominent deterioration of sleep physiology, which is already evident at the stage of mild cognitive impairment (MCI). Cortical slow oscillations (SO; 0.5–1 Hz) and thalamocortical spindle activity (12–15 Hz) during sleep, and their temporal coordination, are considered critical for memory formation. We investigated the potential of slow oscillatory transcranial direct current stimulation (so-tDCS), applied during a daytime nap in a sleep-state-dependent manner, to modulate these activity patterns and sleep-related memory consolidation in nine male and seven female human patients with MCI. Stimulation significantly increased overall SO and spindle power, amplified spindle power during SO up-phases, and led to stronger synchronization between SO and spindle power fluctuations in EEG recordings. Moreover, visual declarative memory was improved by so-tDCS compared with sham stimulation and was associated with stronger synchronization. These findings indicate a well-tolerated therapeutic approach for disordered sleep physiology and memory deficits in MCI patients and advance our understanding of offline memory consolidation. SIGNIFICANCE STATEMENT In the light of increasing evidence that sleep disruption is crucially involved in the progression of Alzheimer's disease (AD), sleep appears as a promising treatment target in this pathology, particularly to counteract memory decline. This study demonstrates the potential of a noninvasive brain stimulation method during sleep in patients with mild cognitive impairment (MCI), a precursor of AD, and advances our understanding of its mechanism. We provide first time evidence that slow oscillatory transcranial stimulation amplifies the functional cross-frequency coupling between memory-relevant brain oscillations and improves visual memory consolidation in patients with MCI.
Loss of Methylation at H19 DMD Is Associated with Biallelic Expression and Reduced Development in Cattle Derived by Somatic Cell Nuclear Transfer1

Although cloning of mammals has been achieved successfully, the percentage of live offspring is very low because of reduced fetal size and fewer implantation sites. Recent studies have attributed such pathological conditions to abnormal reprogramming of the donor cell used for cloning. The inability of the oocyte to fully restore the differentiated status of a somatic cell to its pluripotent and undifferentiated state is normally evidenced by aberrant DNA methylation patterns established throughout the genome during development to blastocyst. These aberrant methylation patterns are associated with abnormal expression of imprinted genes, which among other genes are essential for normal embryo development and gestation. We hypothesized that embryo loss and low implantation rates in cattle derived by somatic cell nuclear transfer (SCNT) are caused by abnormal epigenetic reprogramming of imprinted genes. To verify our hypothesis, we analyzed the parental expression and the differentially methylated domain (DMD) methylation status of the H19 gene. Using a parental-specific analysis, we confirmed for the first time that H19 biallelic expression is tightly associated with a severe demethylation of the paternal H19 DMD in SCNT embryos, suggesting that these epigenetic anomalies to the H19 locus could be directly responsible for the reduced size and low implantation rates of cloned embryos in cattle.
Visual Literacy and Education: Seeing the World Meets Critical Thinking

The abundance and complexity of information now being delivered visually demands that we become visually literate, as well as verbally literate. We need to understand better a process we have taken for granted. In an age increasingly dominated by images – a media culture, it becomes imperative to develop an understanding of how our visual processing system works; how visual cognition is shaped by social, political, and cultural conditioning; and how visual messages are created to elicit specific responses. One of the chief goals of visual literacy education is to encourage critical analysis of visual communication by developing tools that help us understand and manage this complex activity. “Seeing” needs to become an actively conscious, not a passive activity for us. This thesis illustrates the importance of critical visual literacy, provides an historical overview of the visual literacy movement, and suggests a foundational approach to teaching the basics of visual literacy.
Does capital account openness lower inflation?

This paper investigates the relationship between capital account openness and inflation since the 1980s. It argues that widespread capital account liberalization during the last two decades appears to have contributed to the worldwide disinflation observed during the same period. The paper builds a theoretical model to motivate the presence of a negative link between financial integration and inflation. It tests the prediction of the theoretical model by employing static and dynamic panel data procedures. Financial integration appears to discipline monetary authorities, or to help them convince the private sector that they will be more disciplined in the future.
Large-Scale Aerial Image Categorization by Multi-Task Discriminative Topologies Discovery

Fast and accurately categorizing the millions of aerial images on Google Maps is a useful technique in multimedia applications. Existing methods cannot handle this task effectively due to two reasons. 1) It is challenging to build a realtime image categorization system, as some geo-aware Apps update over 20 aerial images per second. 2) The aerial images' topologies are the key to distinguish their categories, but they cannot be encoded by the generic visual descriptors. To solve these two problems, we propose an efficient aerial image categorization system, aiming at mining discriminative topologies of aerial images under a multi-task learning framework. Particularly, we first construct a region adjacency graph (RAG) that describes the topology of each aerial image. Thereby, aerial image categorization can be formulated as RAG-to-RAG matching. Based on graph theory, RAG-to-RAG matching is conducted by comparing all their respective graphlets (i.e., small subgraphs). Because the number of graphlets is huge, a multi-task feature selection algorithm is derived to discover topologies jointly discriminative to multiple categories. The discovered topologies are used to extract the discriminative graphlets. Finally, these graphlets are integrated into an AdaBoost model for predicting aerial image categories. Experiments show that our approach is competitive several existing recognition models. Further, over 24 aerial images are categorized per second, reflecting that our system is ready for real-world applications.
Increased rates of lipolysis among human immunodeficiency virus-infected men receiving highly active antiretroviral therapy.

Human immunodeficiency virus (HIV) lipodystrophy is associated with fat redistribution, dyslipidemia, and insulin resistance; however, the mechanism of insulin resistance remains unknown. We hypothesized that HIV-infected subjects with fat redistribution have increased rates of lipolysis and increased circulating free fatty acid (FFA) levels that contribute to insulin resistance. Anthrompometric and body composition data were obtained and a standard 75-g oral glucose tolerance test (OGTT) was performed on day 1 of the study. Stable isotope infusions of glycerol and palmitate were completed following an overnight fast to assess rates of lipolysis and FFA flux in HIV-infected men (n = 19) with and without fat redistribution and healthy controls (n = 8) on day 2. Total FFA levels after standard glucose challenge were increased among HIV-infected subjects and positively associated with abdominal visceral adipose tissue area. In contrast, fasting total FFA levels were inversely associated with subcutaneous fat area. Rates of basal lipolysis were significantly increased among HIV-infected subjects (rate of appearance [Ra] glycerol, 4.1 +/- 0.2 v 3.3 +/- 0.2 micromol/kg/min in controls; P =.02). Among HIV-infected subjects, use of stavudine (P =.006) and the rate of lipolysis (ie, Ra glycerol, P =.02) were strong positive predictors of insulin resistance as measured by insulin response to glucose challenge, controlling for effects of age, body mass index (BMI), waist-to-hip ratio (WHR), and protease inhibitor (PI) exposure. These data demonstrate increased rates of lipolysis and increased total FFA levels in HIV-infected subjects and suggest that increased lipolysis may contribute to insulin resistance in this patient population.
Auditory and Vestibular Mouse Mutants: Models For Human Deafness

We have shown here several examples of how hearing and vestibular impaired mouse mutants are generated and the insight that they provide in the study of auditory and vestibular function. These types of genetic studies may also lead to the identification of disease-susceptibility genes, perhaps the most critical element in presbyacusis (age-related hearing loss). Some individuals may be more prone to hearing loss with increasing age or upon exposure to severe noise, and susceptibility genes may be involved. Different inbred mice show a variety of age-related and noise-induced hearing loss that varies between normal hearing and severe deafness throughout their life span /27/. Genetic diversity between inbred mouse strains has been shown to be a powerful tool for the discovery of modifier genes. Already two studies have found regions in which modifier genes for deafness may reside /28-29/. Future studies will hopefully lead to the identification of genes that modify hearing loss and will help us understand the variability that exists in human hearing, a crucial component in developing successful treatment strategies. The first human non-syndromic deafness-causing gene was identified in 1995, and since then, additional genes have been discovered. Much of the credit for this boom is due to deaf and vestibular mouse mutants. Their study has led to great insight regarding the development and function of the mammalian inner ear, and correlations with human deafness can now be made since mutations in the same genes have been found in these two mammals. As deafness is the most common form of sensory impairment and affects individuals of all ages, elucidating the function of the auditory and vestibular systems through genetic approaches is essential in improving and designing effective treatments for hearing loss.
Message Forwarding Strategies in Device-to-Device Based Mobile Social Networking in Proximity (MSNP)

Device to Device (D2D) based mobile social networking in proximity (MSNP) has witnessed great development on smartphones. Message forwarding/data routing in MSNP relies on the movement of individuals and their encounter opportunities to relay data to the destination, so-called store-carry-forward (SCF) mode. Due to lacking continuous network connectivity and must handle dynamic topology, message forwarding mechanism in MSNP is challenging. In recent years, exploiting MSNP users' social behaviours to forward message, have drawn tremendous interests. In this paper, we provide the taxonomy of social behaviour-based forwarding strategies, comprehensively summarize and compare various schemes, including location-based and encounter-based (further divided into social property based and community-based) strategies. Location-based strategies forward data to the individuals geographically closer to the destination, while encounter-based strategies forward data to the users more socially active through considering human interactions. Then, we present open issues in MSNP forwarding strategies and their potential solutions. The goal of this work is to provide deep understanding on SCF based message forwarding in MSNP which properly incorporate the individual's social characteristics, and bring new visions to MSNP research and applications.
PEGylation of a Vesicular Stomatitis Virus G Pseudotyped Lentivirus Vector Prevents Inactivation in Serum

ABSTRACT One disadvantage of vesicular stomatitis virus G (VSV-G) pseudotyped lentivirus vectors for clinical application is inactivation of the vector by human serum complement. To prevent this, monomethoxypoly(ethylene) glycol was conjugated to a VSV-G-human immunodeficiency virus vector expressing Escherichia coli beta-galactosidase. The modification did not affect transduction efficiency in vitro and protected the vector from inactivation in complement-active human and mouse sera. Blood from mice dosed intravenously with either the unmodified or the PEGylated virus particles was assayed for active vector by a limiting-dilution assay to evaluate transduction efficiency and for p24, an indicator of the total number of virus particles present. PEGylation extended the circulation half-life of active vector by a factor of 5 and reduced the rate of vector inactivation in the serum by a factor of 1,000. Pharmacokinetic profiles for the total number of virus particles present in the circulation were unaffected by PEGylation. Modification of the vector with poly(ethylene) glycol significantly enhanced transduction efficiency in the bone marrow and in the spleen 14 days after systemic administration of the virus. These results, in concert with the pharmacokinetic profiles, indicate that PEGylation does protect the virus from inactivation in the serum and, as a result, improves the transduction efficiency of VSV-G pseudotyped lentivirus vectors in susceptible organs in vivo.
Spatial targeting of type II protein kinase A to filopodia mediates the regulation of growth cone guidance by cAMP

The second messenger cyclic adenosine monophosphate (cAMP) plays a pivotal role in axonal growth and guidance, but its downstream mechanisms remain elusive. In this study, we report that type II protein kinase A (PKA) is highly enriched in growth cone filopodia, and this spatial localization enables the coupling of cAMP signaling to its specific effectors to regulate guidance responses. Disrupting the localization of PKA to filopodia impairs cAMP-mediated growth cone attraction and prevents the switching of repulsive responses to attraction by elevated cAMP. Our data further show that PKA targets protein phosphatase-1 (PP1) through the phosphorylation of a regulatory protein inhibitor-1 (I-1) to promote growth cone attraction. Finally, we find that I-1 and PP1 mediate growth cone repulsion induced by myelin-associated glycoprotein. These findings demonstrate that the spatial localization of type II PKA to growth cone filopodia plays an important role in the regulation of growth cone motility and guidance by cAMP.
Revisiting communication performance models for computational clusters

In this paper, we analyze restrictions of traditional models affecting the accuracy of analytical prediction of the execution time of collective communication operations. In particular, we show that the constant and variable contributions of processors and network are not fully separated in these models. Full separation of the contributions that have different nature and arise from different sources will lead to more intuitive and accurate models, but the parameters of such models cannot be estimated from only the point-to-point experiments, which are usually used for traditional models. We are making the point that all the traditional models are designed so that their parameters can be estimated from a set of point-to-point communication experiments. In this paper, we demonstrate that the more intuitive models allow for much more accurate analytical prediction of the execution time of collective communication operations on both homogeneous and heterogeneous clusters. We present in detail one such a point-to-point model and how it can be used for prediction of the execution time of scatter and gather. We describe a set of communication experiments sufficient for accurate estimation of its parameters, and we conclude with presentation of experimental results demonstrating that the model much more accurately predicts the execution time of collective operations than traditional models.
Tree Age Effects on Fine Root Biomass and Morphology over Chronosequences of Fagus sylvatica, Quercus robur and Alnus glutinosa Stands

There are few data on fine root biomass and morphology change in relation to stand age. Based on chronosequences for beech (9–140 years old), oak (11–140 years) and alder (4–76 years old) we aimed to examine how stand age affects fine root biomass and morphology. Soil cores from depths of 0–15 cm and 16–30 cm were used for the study. In contrast to previously published studies that suggested that maximum fine root biomass is reached at the canopy closure stage of stand development, we found almost linear increases of fine root biomass over stand age within the chronosequences. We did not observe any fine root biomass peak in the canopy closure stage. However, we found statistically significant increases of mean fine root biomass for the average individual tree in each chronosequence. Mean fine root biomass (0–30 cm) differed significantly among tree species chronosequences studied and was 4.32 Mg ha-1, 3.71 Mg ha-1 and 1.53 Mg ha-1, for beech, oak and alder stands, respectively. The highest fine root length, surface area, volume and number of fine root tips (0–30 cm soil depth), expressed on a stand area basis, occurred in beech stands, with medium values for oak stands and the lowest for alder stands. In the alder chronosequence all these values increased with stand age, in the beech chronosequence they decreased and in the oak chronosequence they increased until ca. 50 year old stands and then reached steady-state. Our study has proved statistically significant negative relationships between stand age and specific root length (SRL) in 0–30 cm soil depth for beech and oak chronosequences. Mean SRLs for each chronosequence were not significantly different among species for either soil depth studied. The results of this study indicate high fine root plasticity. Although only limited datasets are currently available, these data have provided valuable insight into fine root biomass and morphology of beech, oak and alder stands.
Optimizing photovoltaic model parameters for simulation

Photovoltaic (PV) model is used in simulation study to validate the system design of a PV system. With an accurate PV model for use in circuit orientated software, the behavior of PV array under different environmental conditions can be observed for study. In this paper, the unknown parameters of a single diode PV model are identified using the Particle Swarm Optimization (PSO) approach with log barrier constraint. The proposed method has been applied to a PV module KC65T and has shown accurate modeling result.
Moving Molecules in Crystalline Solids: Gradual Structure Transition and Spin Transition/Crossover

Magnetic switches working in solid states are of recent interest for applications to sensor, memory, etc. The author and co-workers have developed various unconventional spin transition/crossover materials. The first example is a supramolecular chemistry consisting of genuine organic nitroxide biradicals with a triplet ground state. Each nitroxide group is located close to each other to form weak covalent bonds in an intermolecular fashion. Biradicals are polymerized/depolymerized stepwise. The second example belongs to 3d-2p heterospin systems where the nitroxide oxygen atom is directly bonded to a nickel(II) or copper(II) ion. The planar/nonplanar chelate structure changes, accompanied by high-/low-spin transition due to a 3d-2p exchange-coupling switch. A novel entropy-driven spin crossover scenario has been established. The third example is a 3d iron(II) spin crossover material carrying a stearyl (C18) group. An order-disorder-type structural transition appears with respect to the alkyl conformation. As these examples show, single-crystal-to-single-crystal structural transitions are often observed. It is because the spin entropy term regulates the atomic dislocation enthalpy, and the entropy change due to the spin multiplicity is basically small. These molecular motions clarified by means of detailed crystallography afford one of the most convincing evidence for the spin transition phenomenon.
Submission to ICGI-2000 Computational complexity of problems on probabilistic grammars and transducers

Determinism plays an important role in grammatical inferen ce. However, in practice, ambiguous grammars (and non determinism grammars in particular) are m o used than determinism grammars. Computing the probabilityof parsing a given string or its mo st probable parse with Stochastic Regular Grammarscan be performed in linear time. However, the problem of findi ng the most probable string has yet not given any satisfactory answer. In this paper we pr ove that the problem is NP-hard and does not allow for a Polynomial Time Approximation Scheme. T he result extends toStochastic Regular Syntax-Directed Translation Schemes .