Miracle-dz/UniFAR-FTUs huggingface dataset:
Considerations for Using Mathematical Learning Progressions to Design Diagnostic Assessments

ABSTRACT Diagnostic assessments are intended to support teachers’ instructional decision making by providing instructionally relevant information. In this article, we propose that using cognitive theories of learning to design diagnostic assessments can provide teachers with two diagnostic outcomes: (a) the location of a student’s thinking within the learning process, and (b) identification of misconceptions and errors that may underlie student performance. We focus on two test design considerations that may support these diagnostic inferences, specifically (a) sequencing item content to align with learning progressions and (b) constructing multiple-choice items with diagnostically relevant distractors. We provide an illustrative example from middle-school mathematics.
Mapping Observations of DNC and HN13C in Dark Cloud Cores

We present results of mapping observations of the DNC, HN13C, and H13CO+ lines (J = 1-0) toward four nearby dark cloud cores, TMC-1, L1512, L1544, and L63, along with observations of the DNC and HN13C lines (J = 2-1) toward selected positions. By use of statistical equilibrium calculations based on the large velocity gradient (LVG) model, the H2 densities are derived to be × 105 cm-3, and the [DNC]/[HN13C] ratios are derived to be 1.25-5.44, with a typical uncertainty of a factor of 2. The observed [DNC]/[HNC] ratios range from 0.02 to 0.09, assuming a [12C]/[13C] ratio of 60. Distributions of DNC and HN13C are generally similar to each other, whereas the distribution of H13CO+ is more extended than those of DNC and HN13C, indicating that they reside in a more inward part of the cores than HCO+. The [DNC]/[HN13C] ratio is rather constant within each core, although small systematic gradients are observed in TMC-1 and L63. In particular, no such systematic gradient is found in L1512 and L1544, where a significant effect of depletion of molecules is reported toward the central part of the cores. This suggests that the [DNC]/[HNC] ratio would not be very sensitive to the depletion factor, unlike the [DCO+]/[HCO+] ratio. On the other hand, the core-to-core variation of the [DNC]/[HNC] ratio, which ranges over an order of magnitude, is more remarkable than the variation within each core. These results are interpreted qualitatively by a combination of three competing time-dependent processes: gas-phase deuterium fractionation, depletion of molecules onto grain surfaces, and dynamical evolution of a core.
RNA Splicing: A New Player in the DNA Damage Response

It is widely accepted that tumorigenesis is a multistep process characterized by the sequential accumulation of genetic alterations. However, the molecular basis of genomic instability in cancer is still partially understood. The observation that hereditary cancers are often characterized by mutations in DNA repair and checkpoint genes suggests that accumulation of DNA damage is a major contributor to the oncogenic transformation. It is therefore of great interest to identify all the cellular pathways that contribute to the response to DNA damage. Recently, RNA processing has emerged as a novel pathway that may contribute to the maintenance of genome stability. In this review, we illustrate several different mechanisms through which pre-mRNA splicing and genomic stability can influence each other. We specifically focus on the role of splicing factors in the DNA damage response and describe how, in turn, activation of the DDR can influence the activity of splicing factors.
Remarks on the boundary set of spectral equipartitions

Given a bounded open set in (or in a Riemannian manifold), and a partition of Ω by k open sets ωj, we consider the quantity , where λ(ωj) is the ground state energy of the Dirichlet realization of the Laplacian in ωj. We denote by ℒk(Ω) the infimum of over all k-partitions. A minimal k-partition is a partition that realizes the infimum. Although the analysis of minimal k-partitions is rather standard when k=2 (we find the nodal domains of a second eigenfunction), the analysis for higher values of k becomes non-trivial and quite interesting. Minimal partitions are in particular spectral equipartitions, i.e. the ground state energies λ(ωj) are all equal. The purpose of this paper is to revisit various properties of nodal sets, and to explore if they are also true for minimal partitions, or more generally for spectral equipartitions. We prove a lower bound for the length of the boundary set of a partition in the two-dimensional situation. We consider estimates involving the cardinality of the partition.
2.45 GHz Class E Power Amplifier for a Transmitter Combining LINC and EER

A 10 W class-E RF power amplifier (PA) is designed and fabricated using a Cree GaN HEMT. The proposed PA uses an innovative input circuit to optimize band with. At 2.45 GHz the PA achieves a PAE of 60 % at an outputpower of 40 dBm. The resulting amplifier is simulated and constructed using a transmissionline topology. Two of these amplifiers are fabricated on a single board for outphasing application. Their suitability for outphasing application and supply modulation is investigated.
Docetaxel Rechallenge in a Heavily Pretreated Patient With Castration-Resistant Prostate Cancer

AbstractChemotherapy agents for patients with metastatic castration-resistant prostate cancer (mCRPC) include docetaxel and cabazitaxel. Although docetaxel is approved in the first-line treatment setting, a few studies have shown that selected patients can benefit from docetaxel rechallenge.We, here, report the case of a heavily pretreated mCRPC patient who reported clinical benefit from receiving docetaxel after previous exposure to docetaxel, cabazitaxel, abiraterone, and enzalutamide.After 4 cycles of treatment, patient's performance status had improved to 1, the hemoglobin level was 12.9 g/dL and his serum prostate specific antigen levels were reduced by >70%, with no treatment-related adverse events.Although docetaxel rechallenge is a therapeutic option for selected patients, the risk of cumulative toxicity described in literature must be carefully considered.As the risk of cabazitaxel-related cumulative toxicity is probably lower, retreatment with cabazitaxel rather than docetaxel may also be an option in the setting of heavily pretreated mCRPC patients.
Instantaneous real-time head pose at a distance

In this paper we focus on robust, real-time human head pose estimation in low resolution RGB data without any smoothing motion priors e.g. direction of motion. Our main contributions lie in three major areas. First, we show that a generative Deep Belief Network model can be learned on human head data from multiple types of data sources. These sources have similar underlying data that are not necessarily labelled or have the same kind of ground truth. Second, we perform discriminative training using multiple disparate supervisory labels to fine tune the model for head pose estimation. Third, we present state-of-the-art results on two publicly available datasets using this new approach. Our implementation computes head pose for a head image in 0.8 milliseconds, making it real-time and highly scalable.
Market Managed Multi-service Internet (M3I): Economics driving Network Design

The fundamental economics of packet networking has led us to a mechanism to guarantee quality of service (QoS) with no flow handling in the core Internet, giving far better scalability, robustness and simplicity than previously. The same packet congestion mechanism is then generalised to encourage customers to manage all classes of trac responsibly and with optimal utilisation. A vision of the future is given, driven by the inexorable logic of economics. The economic concepts behind the engineering are briefly explained.
Use of nonsteroidal antiinflammatory drugs: an update for clinicians: a scientific statement from the American Heart Association.

Clinical trial data have prompted questions about the degree to which patients and their physicians should consider an increased risk of cardiovascular or cerebrovascular events when selecting medications for pain relief. Since the 2005 publication of a Science Advisory on the use of nonsteroidal antiinflammatory drugs (NSAIDs) by the American Heart Association,1 several important events have occurred that have served as the catalyst for this update for clinicians. (1) Additional data from randomized controlled trials of cyclooxygenase (COX)-2–selective agents have been reported and summarized in meta-analyses, which has reinforced the concern about cardiovascular events with COX-2 inhibitors (coxibs; Figure 1). (2) Several reports have appeared that have identified an increased risk of cardiovascular events even with the nonselective NSAIDs, which has raised concern about the use of those agents as well (Table). (3) Regulatory authorities in several regions of the world have introduced warning statements and advisories to both healthcare professionals and the lay public about the use of various NSAIDs (Figures 2 and 3⇓). Figure 1. Comparison of effects of different selective COX-2 inhibitors vs placebo on myocardial infarction. Event numbers and person-years of exposure, with corresponding mean annual event rates in parentheses, are presented for patients allocated to selective COX-2 inhibitor or placebo. Event rate ratios for pooled data with 95% CIs are indicated by a diamond; rate ratios for individual selective COX-2 inhibitors, with 99% CIs, are indicated by a square and horizontal line. Diamonds to the right of the solid line indicate hazard with a selective COX-2 inhibitor compared with placebo. As noted, there was a significant increase in the rate ratio for myocardial infarction with COX-2 inhibitors compared with placebo. Similar analyses (data not shown) include rate ratios of 1.42 (1.13 to 1.78; P =0.003) for vascular events, 1.02 (0.71 to 1.47; P …
RTL-based functional test generation for high defects coverage in digital SOCs

Functional test is long viewed as unfitted for production test. The purpose of this contribution is to propose a RTL-based test generation methodology which can be rewardingly used both for design validation and to enhance the test effectiveness of classic, gate-level test generation. Hence, a RTL-based defect-oriented test generation methodology is proposed, for which a high defects coverage (DC) and a relatively short test sequence can be derived, thus allowing low-energy operation in test mode. The test effectiveness, regarding DC, is shown to be weakly dependent on the structural implementation of the behavioral description. The usefulness of the methodology is ascertained using the VeriDOS simulation environment and the CMUDSP ITC'99 benchmark circuit.
Impurity Reaction with Dislocations in Semiconductors

Basic aspects of impurity reaction with dislocations in semiconductors are discussed on the basis of the work of the author's group. Some important insights into the mechanism of impurity reaction with extended structural defects are deduced from a theoretical treatment of impurity distribution around a structural defect in thermal equilibrium, experimental observations on dislocation pinning, and the characteristics in the development of precipitates on various types of structural defects. The morphology of impurity precipitates formed on a dislocation plays an important role in the strength of dislocation pinning. Generally, the impurity±dislocation reaction is dependent on the species and concentration of impurities as well as the core structure of dislocation, and also on the thermal process of the crystal, i.e. the cooling rate from high temperature.
Distributed Estimation Over an Adaptive Incremental Network Based on the Affine Projection Algorithm

We study the problem of distributed estimation based on the affine projection algorithm (APA), which is developed from Newton's method for minimizing a cost function. The proposed solution is formulated to ameliorate the limited convergence properties of least-mean-square (LMS) type distributed adaptive filters with colored inputs. The analysis of transient and steady-state performances at each individual node within the network is developed by using a weighted spatial-temporal energy conservation relation and confirmed by computer simulations. The simulation results also verify that the proposed algorithm provides not only a faster convergence rate but also an improved steady-state performance as compared to an LMS-based scheme. In addition, the new approach attains an acceptable misadjustment performance with lower computational and memory cost, provided the number of regressor vectors and filter length parameters are appropriately chosen, as compared to a distributed recursive-least-squares (RLS) based method.
A framework for requirents monitoring of service based systems

This paper proposes a framework for monitoring the compliance of systems composed of web-services with requirements set for th. This framework assumes systems composed of web-services that are co-ordinated by a service composition process expressed in BPEL4WS and uses event calculus to specify the properties to be monitored. The monitorable properties may include behavioural properties of a syst which are automatically extracted from the specification of its composition process in BPEL4WS and/or assumptions that syst providers can specify in terms of events extracted from this specification.
American Journal of Epidemiology Original Contribution Heart Rate Variability, Ambient Particulate Matter Air Pollution, and Glucose Homeostasis: the Environmental Epidemiology of Arrhythmogenesis in the Women's Health Initiative

Metabolic neuropathophysiology underlying the prediabetic state may confer susceptibility to the adverse health effects of ambient particulate matter <10 lm in diameter (PM 10). The authors therefore examined whether impaired glucose homeostasis modifies the effect of PM 10 on heart rate variability in a stratified, random sample of 4,295 Women's Health Initiative clinical trial participants, among whom electrocardiograms and fasting blood draws were repeated at 3-year intervals from 1993 to 2004. In multilevel, mixed models weighted for sampling design and adjusted for clinical and environmental covariables, PM 10 exposure was inversely associated with heart rate variability. Inverse PM 10 –heart rate variability associations were strongest for the root mean square of successive differences in normal-to-normal RR intervals (RMSSD). Among participants with impaired fasting glucose, there were À8. 0) decreases in the RMSSD per 10-lg/m 3 increase in PM 10 at high versus low levels of insulin (P < 0.01), insulin resistance (P < 0.01), and glucose (P ¼ 0.16), respectively. These associations were stronger among participants with diabetes and weaker among those without diabetes or impaired fasting glucose. The findings suggest that insulin and insulin resistance exacerbate the adverse effect of PM 10 on cardiac autonomic control and thus risk of coronary heart disease among nondiabetic, postmenopausal women with impaired fasting glucose. Abbreviations: HOMA-IR, insulin resistance according to homeostatic model assessment; PM 10 , particulate matter <10 lm in diameter; RMSSD, root mean square of successive differences in normal-to-normal RR intervals; SDNN, standard deviation of normal-to-normal RR intervals; WHI, Women's Health Initiative. Measures of heart rate variability derived from short-term electrocardiographic recordings are inversely associated with risk of incident coronary heart disease (1–4). They are also inversely associated with concentrations of ambient particulate matter air pollution among persons with and without diabetes (5, 6), implicating altered heart rate variability as a mechanism linking particulate matter exposures to coronary heart disease events. It has been suggested that the associations observed among nondiabetics may be attributable to metabolic abnormalities related to insulin resistance (7, 8). The metabolic neuropathophysiology common to both the prediabetic and diabetic states may therefore confer susceptibility to the adverse autonomic and cardiovas-cular effects of particulate matter, including reduced heart rate variability. Several studies have found evidence that indirectly supports this hypothesis (9–14), although most used administrative data to ascertain comorbid diabetes, an approach
An Enhanced Informed Watermarking Scheme Using the Posterior Hidden Markov Model

Designing a practical watermarking scheme with high robustness, feasible imperceptibility, and large capacity remains one of the most important research topics in robust watermarking. This paper presents a posterior hidden Markov model (HMM-) based informed image watermarking scheme, which well enhances the practicability of the prior-HMM-based informed watermarking with favorable robustness, imperceptibility, and capacity. To make the encoder and decoder use the (nearly) identical posterior HMM, each cover image at the encoder and each received image at the decoder are attacked with JPEG compression at an equivalently small quality factor (QF). The attacked images are then employed to estimate HMM parameter sets for both the encoder and decoder, respectively. Numerical simulations show that a small QF of 5 is an optimum setting for practical use. Based on this posterior HMM, we develop an enhanced posterior-HMM-based informed watermarking scheme. Extensive experimental simulations show that the proposed scheme is comparable to its prior counterpart in which the HMM is estimated with the original image, but it avoids the transmission of the prior HMM from the encoder to the decoder. This thus well enhances the practical application of HMM-based informed watermarking systems. Also, it is demonstrated that the proposed scheme has the robustness comparable to the state-of-the-art with significantly reduced computation time.
Classifying Fuzzy Subsumption in Fuzzy-EL+

Fuzzy Description Logics (f-DLs) have been proposed as extensions of classical Description Logics able to handle imprecise and vague knowledge. Although several extensions to expressive DLs have been proposed today and many reasoning algorithms exist there is still no scalable and efficient reasoning system reported, mainly due to inherited computational complexity from crisp DLs and the lack for optimisation techniques for fuzzy DL reasoning algorithms. Following the paradigm of classical DLs, fuzzy extensions to tractable DLs have been proposed. In the current paper we present a fuzzy extension to the tractable DL EL+, creating f-EL+. Besides the syntax and the extended semantics we also provide a reasoning algorithm for f-EL+. Interestingly, our algorithm supports classification over fuzzy subsumption for which scalable reasoning is not known.
Incorporating support vector machine for identifying protein tyrosine sulfation sites

Tyrosine sulfation is a post‐translational modification of many secreted and membrane‐bound proteins. It governs protein‐protein interactions that are involved in leukocyte adhesion, hemostasis, and chemokine signaling. However, the intrinsic feature of sulfated protein remains elusive and remains to be delineated. This investigation presents SulfoSite, which is a computational method based on a support vector machine (SVM) for predicting protein sulfotyrosine sites. The approach was developed to consider structural information such as concerning the secondary structure and solvent accessibility of amino acids that surround the sulfotyrosine sites. One hundred sixty‐two experimentally verified tyrosine sulfation sites were identified using UniProtKB/SwissProt release 53.0. The results of a five‐fold cross‐validation evaluation suggest that the accessibility of the solvent around the sulfotyrosine sites contributes substantially to predictive accuracy. The SVM classifier can achieve an accuracy of 94.2% in five‐fold cross validation when sequence positional weighted matrix (PWM) is coupled with values of the accessible surface area (ASA). The proposed method significantly outperforms previous methods for accurately predicting the location of tyrosine sulfation sites. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2009
Do recommender systems benefit users? a modeling approach

Recommender systems are present in many web applications to guide purchase choices. They increase sales and benefit sellers, but whether they benefit customers by providing relevant products remains less explored. While in many cases the recommended products are relevant to users, in other cases customers may be tempted to purchase the products only because they are recommended. Here we introduce a model to examine the benefit of recommender systems for users, and find that recommendations from the system can be equivalent to random draws if one always follows the recommendations and seldom purchases according to his or her own preference. Nevertheless, with sufficient information about user preferences, recommendations become accurate and an abrupt transition to this accurate regime is observed for some of the studied algorithms. On the other hand, we find that high estimated accuracy indicated by common accuracy metrics is not necessarily equivalent to high real accuracy in matching users with products. This disagreement between estimated and real accuracy serves as an alarm for operators and researchers who evaluate recommender systems merely with accuracy metrics. We tested our model with a real dataset and observed similar behaviors. Finally, a recommendation approach with improved accuracy is suggested. These results imply that recommender systems can benefit users, but the more frequently a user purchases the recommended products, the less relevant the recommended products are in matching user taste.
Glutamine Synthetase Is a Genetic Determinant of Cell Type–Specific Glutamine Independence in Breast Epithelia

Although significant variations in the metabolic profiles exist among different cells, little is understood in terms of genetic regulations of such cell type–specific metabolic phenotypes and nutrient requirements. While many cancer cells depend on exogenous glutamine for survival to justify the therapeutic targeting of glutamine metabolism, the mechanisms of glutamine dependence and likely response and resistance of such glutamine-targeting strategies among cancers are largely unknown. In this study, we have found a systematic variation in the glutamine dependence among breast tumor subtypes associated with mammary differentiation: basal- but not luminal-type breast cells are more glutamine-dependent and may be susceptible to glutamine-targeting therapeutics. Glutamine independence of luminal-type cells is associated mechanistically with lineage-specific expression of glutamine synthetase (GS). Luminal cells can also rescue basal cells in co-culture without glutamine, indicating a potential for glutamine symbiosis within breast ducts. The luminal-specific expression of GS is directly induced by GATA3 and represses glutaminase expression. Such distinct glutamine dependency and metabolic symbiosis is coupled with the acquisition of the GS and glutamine independence during the mammary differentiation program. Understanding the genetic circuitry governing distinct metabolic patterns is relevant to many symbiotic relationships among different cells and organisms. In addition, the ability of GS to predict patterns of glutamine metabolism and dependency among tumors is also crucial in the rational design and application of glutamine and other metabolic pathway targeted therapies.