Miracle-dz/UniFAR-FTUs huggingface dataset:
A Fault Localization Method Based on Similarity Weighting with Unlabeled Test Cases

In software fault localization problems, existing fault localization algorithms usually rely heavily on the perfection of test oracle. But in practice, there are a large number of test cases that lack accurate execution results. In order to utilize on unlabeled test cases, many test prediction and use case filter methods have been proposed. However, these methods ignore the similarity between test cases, which has been proven effective in fault localization studies using labeled test cases. Therefore, this paper proposes a fault localization method based on similarity weighting with unlabeled test cases. It uses the similarity of unlabeled test cases filtered by information entropy and labeled failed test cases as weights, and weights the suspicion calculation coefficients to enhance the importance of use cases similar to the failed cases. The experimental results show that similarity weighting effectively improves fault localization efficiency on all three program sets and all three localization algorithms. It can be seen that similarity of use case information also has an important role in the use of unlabeled test cases.
Driver’s Fatigue Classification based on Physiological Signals Using RNN-LSTM Technique

One of the major reasons for road accidents is driver’s fatigue which causes several fatalities every year. Various studies on road accidents have proved that 20% of the accidents are caused mainly due to fatigue among drivers while driving. This paper presents the use of deep learning technique in classifying fatigue in drivers. By using deep neural networks, features are extracted automatically from preprocessed data of physiological signals such as electrocardiogram, heart rate, skin conductance response and body temperature. Public dataset HciLAB was used to train and validate the classification model. In this work, a comparative analysis of using Recurrent Neural Network - Long Short-term Memory (RNN-LSTM) deep learning architecture and the standard artificial neural network (ANN) was proposed and developed to classify fatigue based on the physiological features of the driver. The results revealed the superiority RNN-LSTM (98%) over standard ANN (80%), for driver fatigue classification. The proposed methods, based on RNN-LSTM deep learning architecture introduced elevated average accuracy in comparison with the standard artificial neural network.
Collision Rate of Small Graupel and Water Drops

Abstract An approach permitting one to calculate the collision efficiency and the collision kernel of spherical particles of different densities for Reynolds numbers up to 100 (300-μm-radius drops, or 700-μm-radius graupel) is presented. It is used for the calculation of graupel–drop collision efficiencies and collision kernels in calm air for low-, medium-, and high-density graupel at 750- and 500-mb pressure levels. Low-density graupel interacts with water droplets in a way similar to ice crystals: there exists a cutoff size, below which graupel cannot collect water droplets. The authors have shown that the cutoff size decreases with the growth of graupel density, so that medium- and high-density graupel is able to collect droplets with the radii exceeding a certain minimum size. The graupel–drop collision efficiency increases with the drop size up to a maximum value and then sharply decreases to zero, when the drops' terminal velocity approaches the terminal velocity of graupel. As soon as the terminal.
Distributed State and Fault Fusion Filtering for Nonlinear Systems Subject to Quantization Effects

In this paper, the distributed state and fault fusion filtering problem is discussed for a class of multi-sensor networked systems (MSNSs) with randomly occurring quantized measurements (ROQMs). A series of random variables obeying the Bernoulli distribution are adopted to depict the phenomenon of the ROQMs and the fault signal is assumed to appear with an unknown constant type. The aim of this paper is to provide the state and fault fusion filtering algorithm by using the inverse covariance intersection fusion method. Moreover, a proper filter gain is designed by minimizing the local upper bound of filtering error covariance. Finally, the effectiveness of the presented fusion method is verified by using an illustrative example.
Free energies and pseudo-elastic transitions for shape memory alloys

A one-dimensional model for a shape memory alloy is proposed. It provides a simplified description of the pseudo-elastic regime, where stress-induced transitions from austenitic to oriented martensitic phases occurs. The stress-strain evolution is ruled by a bilinear rate-independent o.d. e. which also accounts for the fine structure of minor hysteresis loops and applies to the case of single crystals only. The temperature enters the model as a parameter through the yield limit $y$. Above the critical temperature $\theta_A^*$, the austenite-martensite phase transformations are described by a Ginzburg-Landau theory involving an order parameter $φ$, which is related to the anelastic deformation. As usual, the basic ingredient is the Gibbs free energy, $\zeta$, which is a function of the order parameter, the stress and the temperature. Unlike other approaches, the expression of this thermodynamic potential is derived rather then assumed, here. The explicit expressions of the minimum and maximum free energies are obtained by exploiting the Clausius-Duhem inequality, which ensures the compatibility with thermodynamics, and the complete controllability of the system. This allows us to highlight the role of the Ginzburg-Landau equation when phase transitions in materials with hysteresis are involved.
Cellulite: Clinical Challenges and Future Perspectives

BACKGROUND Existing cellulite interventions pose various clinical challenges related mostly to ecchymosis and recovery time. OBJECTIVE To discuss the current treatment options for minimizing recovery time, efficacy of these options, and investigations into possible future approaches. METHODS A roundtable meeting was convened to discuss and share views on the clinical challenges seen in the present practice of cellulite treatments along with future approaches and mitigation strategies. The participants' views helped guide a narrative review on this topic. RESULTS Cosmetic clinicians have a range of new interventions to choose from for cellulite improvement, each with different benefits and safety aspects. Bruising is a typical side effect that is seen with treatments targeting the fibrous septa, such as subcision and injectable treatments, and in some cases may produce long-lasting hyperpigmentation from postinflammatory hyperpigmentation or hemosiderin staining. Various strategies that could potentially mitigate bruising and other adverse effects of cellulite treatment are under clinical investigation, including, but not limited to, different injection techniques and dilutions, compression garments, cold packs, arnica gel, pulsed dye laser treatment, intralesional epinephrine, and tranexamic acid. CONCLUSION Clinical challenges including varying treatment outcomes and certain treatment sequelae remain, and further research is needed to prevent side effects and improve treatment outcomes.
THREE-DIMENSIONAL SHAPE AND EVOLUTION OF TWO ERUPTIVE FILAMENTS

On 2009 September 26, a dramatic and large filament (LF) eruption and a small filament (SF) eruption were observed in the He ii 304 Å line by the two EUVI telescopes aboard the STEREO A and B spacecraft. The LF heads out into space and becomes the bright core of a gradual coronal mass ejection (CME), while the eruption of the SF is characterized by motions of the filament materials. Using stereoscopic analysis of EUVI data, we reconstruct the three-dimensional shape and evolution of two eruptive filaments. For the first time, we investigate the true velocities and accelerations of 12 points along the axis of the LF, and find that the velocity and acceleration vary with the measured location. The highest points among the 12 points are the fastest in the first half hour, and then the points at the low-latitude leg of the LF become the fastest. For the SF, it is an asymmetric whip-like filament eruption, and the downward motions of the material lead to the disappearance of the former high-latitude endpoint and the formation of a new low-latitude endpoint. Based on the temporal evolution of the two filaments, we infer that the two filaments lie in the same filament channel. By combining the EUVI, COR1, and COR2 data of STEREO A together, we find that there is no impulsive or fast acceleration in this event. It displays a weak and persistent acceleration for more than 17 hr. The average velocity and acceleration of the LF are 101.8 km s−1 and 2.9 m s−2, respectively. The filament eruptions are associated with a slow CME with an average velocity of 177.4 km s−1. The velocity of the CME is nearly 1.6 times as large as that of the filament material. This event is one example of a gradual filament eruption associated with a gradual CME. In addition, the moving direction of the LF changes from a non-radial to a nearly radial direction with a variation of inclination angle of nearly 38. °2.
The Cerruti problem in dipolar gradient elasticity

The classical three-dimensional Cerruti problem of an isotropic half-space subjected to a concentrated tangential load on its surface is revisited here in the context of dipolar gradient elasticity. This generalized continuum theory encompasses the analytical possibility of size effects, which are absent in the classical theory, and has proven to be very successful in modelling materials with complex microstructure. The dipolar gradient elasticity theory assumes a strain-energy density function, which besides its dependence upon the standard strain terms, depends also on strain gradients. In this way, this theory can be viewed as a first-step extension of classical elasticity. The solution method is based on integral transforms and is exact. Of special importance is the behaviour of the new solution near to the point of application of the load where pathological singularities exist in the classical solution (based on the standard theory). The present results show departure from the ones predicted by the classical elasticity theory. Indeed, continuous and bounded displacements are found at the point of application of the load. Such a behaviour of the displacement field is, of course, more natural than the singular behaviour present in the classical solution.
Threshold Selection in Extreme Value Analysis

The main objective of statistics of extremes is the prediction of rare events, and its primary problem has been the estimation of the extreme value index (EVI). Whenever we are interested in large values, such estimation is usually performed on the basis of the largest k + 1 order statistics in the sample or on the excesses over a high level u. The question that has been often addressed in practical applications of extreme value theory is the choice of either k or u, and an adaptive EVI-estimation. Such a choice can be either heuristic or based on sample paths stability or on the minimization of a mean squared error estimate as a function of k. Some of these procedures will be reviewed. Despite of the fact that the methods provided can be applied, with adequate modifications, to any real EVI and not only to the adaptive EVI-estimation but also to the adaptive estimation of other relevant right-tail parameters, we shall illustrate the methods essentially for the EVI and for heavy tails, i.e., for a positive EVI.
Leaky Waves in Flatland

We introduce a new in-plane radiation mechanism that can occur in artificial or natural low-dimensional materials, which can be viewed as the "flatland" analog of conventional leaky-wave radiation. We show that this concept can be physically realized in suitably designed planar junctions of purely reactive, isotropic metasurfaces supporting line waves. Our results provide a new tool for manipulating surface waves, which can find interesting applications in the emerging field of van der Waals polaritonics.
Satellite-derived forest canopy greenness shows differential drought vulnerability of secondary forests compared to primary forests in Peru

Understanding tropical secondary forest canopy greenness and responses to climatic conditions is important for climate change mitigation, particularly in the tropics where secondary forest growth is a substantial carbon sink and a promoted natural climate solution. We here test three hypotheses: (a) forest canopy greenness is higher in younger, secondary forests than in older, primary or mature forests, (b) secondary forests are more vulnerable to climatic pressures and (c) there are significant differences between forest types regarding primary–secondary canopy greenness and their differential responses to drought anomalies. To explore these relationships, we monitored wet and dry seasonal greenness from 2001 to 2020, estimated through the enhanced vegetation index (EVI), of Peruvian tropical dry, montane and lowland secondary forests and compared it to nearby primary forests. We developed predictive models of seasonal EVI using remotely sensed variables, including land surface temperature (LST), evapotranspiration (ET), potential evapotranspiration (PET), ratio of ET and PET (ETn), and the standard precipitation index (SPI). Overall, there was a higher change in annual and seasonal EVI for secondary forests compared to primary forests. However, primary forests maintained relatively stable EVI levels during the wet season despite drought anomalies. When decoupling forest type canopy greenness and drought response, primary forest greenness in dry and lowland ecosystems were temporally more stable. Secondary montane had a lower increase in greenness when drought anomalies held during different seasons. Stepwise multiple linear regression models indicated that LST and ETn, a plant water use index, were the most significant factors to predict greening fluctuations in dry and montane forest types. ET and SPI mostly drove wet season mean EVI across all forest types. Predictors of dry season mean EVI varied, but mostly including water availability. Our results suggest that tropical secondary forests are more productive overall yet more vulnerable to prolonged drought.
Epidemiology and Risk Factor Analysis of Children with Bronchiolitis Admitted to the Intensive Care Unit at a Tertiary Care Center in Saudi Arabia

Bronchiolitis is a leading cause of hospitalization worldwide for children aged ≤2 years. Few studies have compared general ward and pediatric intensive care unit (PICU) admissions, particularly in Saudi Arabia. This retrospective cohort study aimed to compare the demographic and clinical characteristics of children with bronchiolitis admitted to the general ward with those admitted to the PICU. Children (≤6 years) previously diagnosed with bronchiolitis and admitted to the PICU or general ward at a tertiary center in Saudi Arabia between May 2016 and May 2021 were included. Multiplex polymerase chain reaction was used to identify respiratory viruses. Of the 417 patients enrolled, 67 (16.06%) were admitted to the PICU. The PICU group was younger (median, 2 months; interquartile range [IQR], 1–5 months) vs. (6 months; IQR, 2.65–13.25 months). There was a dramatic reduction in bronchiolitis admissions during the COVID-19 pandemic. The most common causative virus was respiratory syncytial virus (RSV) (54.9%). In the multivariate regression analysis, hypoxia, hyperinflation on X-ray, and non-RSV bronchiolitis were independently associated with PICU admission. However, a higher chronological age and cough were protective. Children with Down syndrome, immunodeficiency, or neuromuscular disorders, and intermediate preterm infants (29–33 weeks of gestation) are at a high risk of PICU admission (adjusted odds ratio: 2.4, 7.1, 2.9, and 2.9; p = 0.037, 0.046, 0.033, and 0.029, respectively). Bronchiolitis is still one of the leading causes of PICU admission. Particular attention should be paid to preventive measures, especially in the post-COVID-19 era, targeting high-risk groups.
Risk processes analyzed as fluid queues

This paper presents the Laplace transform of the time until ruin for a fairly general risk model. The model includes both the classical and most Sparre-Andersen risk models with phase-distributed claim amounts as special cases. It also allows for correlated arrival processes, and claim sizes that depend upon environmental factors such as periods of contagion. The paper exploits the relationship between the surplus process and fluid queues, where a number of recent developments have provided the basis for our analysis.
Existence of Critical Points for the Ginzburg-Landau Functional on Riemannian Manifolds

Existence of Critical Points for the Ginzburg-Landau Functional on Riemannian Manifolds Jeff Mesaric Doctor of Philosophy Graduate Department of Mathematics University of Toronto 2009 In this dissertation, we employ variational methods to obtain a new existence result for solutions of a Ginzburg-Landau type equation on a Riemannian manifold. We prove that if N is a compact, orientable 3-dimensional Riemannian manifold without boundary and γ is a simple, smooth, connected, closed geodesic in N satisfying a natural nondegeneracy condition, then for every > 0 sufficiently small, ∃ a critical point u ∈ H(N ;C) of the Ginzburg-Landau functional E (u) := 1 2π| ln | ∫ N |∇u| + (|u| 2 − 1) 2 2 and these critical points have the property that E (u )→ length(γ) as → 0. To accomplish this, we appeal to a recent general asymptotic minmax theorem which basically says that if E Γ-converges to E (not necessarily defined on the same Banach space as E ), v is a saddle point of E and some additional mild hypotheses are met, then there exists 0 > 0 such that for every ∈ (0, 0), E possesses a critical point u and lim →0E (u ) = E(v). Typically, E is only lower semicontinuous, therefore a suitable notion of saddle point is needed. Using known results on R, we show the Ginzburg-Landau functional E defined above Γ-converges to a functional E which can be thought of as measuring the arclength of a limiting singular set. Also, we verify using regularity theory for almost-minimal currents that γ is a saddle point of E in an appropriate sense.
First-principles study of electronic, mechanical and piezoelectric properties of Janus MoSH

ABSTRACT Janus transition metal dichalcogenides (TMDCs) type two-dimensional materials have been widely studied because of their unique asymmetrical structures and properties. In the preparation of Janus TMDCs, replacing the top layer S atoms of MoS2 with H atoms could yield unique Janus MoSH, which has been scarcely reported. In this work, the electronic, mechanical and piezoelectric properties of Janus MoSH are systematically studied using first principles calculations for the first time. The band structure of Janus MoSH is of metallic nature with two bands crossing the Fermi level. This material has a stable structure, and the Poison ratio ν > 1/3 indicates the good ductility. The relatively higher piezoelectric coefficients, e11 of −4.27 × 10−10 C/m and d11 of −5.09 pm/V for Janus MoSH, compared with the typical piezoelectric semiconductor materials MoS2 (3.64 × 10−10 C/m and 3.73 pm/V, respectively) may reflect suitable piezoelectric effect in the former. The above calculations may show that Janus MoSH would be potentially adopted as efficient sensors and piezoelectric components.
The behavior of maximum likelihood estimates under nonstandard conditions

This paper proves consistency and asymptotic normality of maximum likelihood (ML) estimators under weaker conditions than usual. In particular, (i) it is not assumed that the true distribution underlying the observations belongs to the parametric family defining the ML estimator, and (ii) the regularity conditions do not involve the second and higher derivatives of the likelihood function. The need for theorems on asymptotic normality of ML estimators subject to (i) and (ii) becomes apparent in connection with robust estimation problems; for instance, if one tries to extend the author's results on robust estimation of a location parameter [4] to multivariate and other more general estimation problems. Wald's classical consistency proof [6] satisfies (ii) and can easily be modified to show that the ML estimator is consistent also in case (i), that is, it converges to the 0o characterized by the property E(logf(x, 0) log f(x, O0)) < 0 for 0 . Oo, where the expectation is taken with respect to the true underlying distribution. Asymptotic normality is more troublesome. Daniels [1] proved asymptotic normality subject to (ii), but unfortunately he overlooked that a crucial step in his proof (the use of the central limit theorem in (4.4)) is incorrect without condition (2.2) of Linnik [5]; this condition seems to be too restrictive for many purposes. In section 4 we shall prove asymptotic normality, assuming that the ML estimator is consistent. For the sake of completeness, sections 2 and 3 contain, therefore, two different sets of sufficient conditions for consistency. Otherwise, these sections are independent of each other. Section 5 presents two examples.
Prevalence of Hypercholesterolemia and Awareness of Risk Factors, Prevention and Management Among Adults Visiting Referral Hospital in Ethiopia

Background Unhealthy lifestyles and physical inactivity are among the contributing factors of hypercholesterolemia. This study assessed the prevalence, awareness of risk factors, and prevention and treatment of hypercholesterolemia among adults who visited Woldia referral hospital, Northeast Ethiopia. Methods A cross-sectional survey was conducted among adults who visited Woldia referral hospital from May to August 2022. Data was collected using a structured questionnaire through a face-to-face interview and patient medical record review. Logistic regression analysis was employed to determine the association between hypercholesterolemia and other variables. A p-value at a 95% confidence level was statistically significant. Results A total of 1180 eligible adults were included in the study. The magnitude of hypercholesterolemia was 26.4%. The majority of the respondents were aware of some risk factors, such as higher fat intake (82.3%), obesity (67.2%), and lack of adequate exercise (56.1%). However, the majority of the respondents were not aware that smoking, alcohol consumption, and age (86.8% for all) had cardiovascular risk. The majority of the respondents were aware that eating a limited amount of saturated fat (56.5%), maintaining a healthy weight (67.2%), and taking prescribed medications properly (86.8%) can prevent the risk of hypercholesterolemia. However, a larger proportion of respondents were unaware that smoking cessation (86.8%), exercise (55.3%), alcohol restriction (86.8%), and stress avoidance (75.3%) can prevent cardiovascular risks. Age (p = 0.036), smoking (p = 0.007), alcohol use (p = 0.013), fruit consumption (p = 0.019), saturated oil use (p = 0.031), level of physical activity (p < 0.001), and body mass index (p = 0.03) were significantly associated with hypercholesterolemia. Conclusion This study concluded that more than one-fourth of adults had hypercholesterolemia. The majority of the respondents did not have an awareness of common cardiovascular risk factors and prevention and treatment techniques regarding unhealthy lifestyles and physical inactivity.