Miracle-dz/UniFAR-FTUs huggingface dataset:
PyCaMa: Python for cash management

Selecting the best policy to keep the balance between what a company holds in cash and what is placed in alternative investments is by no means straightforward. We here introduce PyCaMa, a Python module for multiobjective cash management based on linear programming that allows to derive optimal policies for cash management with multiple bank accounts in terms of both cost and risk of policies.
A unified framework for fitting Bayesian semiparametric models to arbitrarily censored spatial survival data

A comprehensive, unified approach to modeling arbitrarily censored spatial survival data is presented for the three most commonly-used semiparametric models: proportional hazards, proportional odds, and accelerated failure time. Unlike many other approaches, all manner of censored survival times are simultaneously accommodated including uncensored, interval censored, current-status, left and right censored, and mixtures of these. Left-truncated data are also accommodated leading to models for time-dependent covariates. Both georeferenced (location observed exactly) and areally observed (location known up to a geographic unit such as a county) spatial locations are handled; formal variable selection makes model selection especially easy. Model fit is assessed with conditional Cox-Snell residual plots, and model choice is carried out via LPML and DIC. Baseline survival is modeled with a novel transformed Bernstein polynomial prior. All models are fit via a new function which calls efficient compiled C++ in the R package \texttt{spBayesSurv}. The methodology is broadly illustrated with simulations and real data applications. An important finding is that proportional odds and accelerated failure time models often fit significantly better than the commonly-used proportional hazards model. Supplementary materials are available.
Seasonal Variation in the Incidence of Preeclampsia Based on the time of conception

Introduction: Approximately 3-8% of pregnancies are complicated by preeclampsia (PE) and complications of pregnancy-related hypertensive disorders that are the third leading cause of maternal deaths. This study was conducted to assess the incidence of preeclampsia in women based on month and season of the conception in northwestern Iran. Material and Methods: The present investigation is a descriptive analytic cross-sectional study including all pregnant women with singleton pregnancies admitted to the Urmia Medical Science University due to preeclampsia, 2007-2008. From 2824 women with singleton pregnancy, 166 of them had preeclampsia and 2658 did not. In all cases, the onset of pregnancy was determined and the relationship between month (season) of pregnancy and occurrence of preeclampsia was studied. The general information, primary characteristics and the history of the two groups were collected and compared. Results: The age, gravidity and parity in the affected group were lower and difference was statically significant. Being nulligravid and having previous abortion was higher in the case group; and the difference was not statically significant. Conclusion: Preeclampsia incidence increased in cases of conception in warm and hot season's esp. in summer. The average temperature of conception is higher in women with preeclampsia but the difference is not statically significant. Therefore, it is suggested to hold training classes for young couples in order to avoid such disorders.
The clinicopathological significance and ethnic difference of FHIT hypermethylation in non-small-cell lung carcinoma: a meta-analysis and literature review

: Emerging evidence indicates that FHIT is a candidate tumor suppressor in many types of tumors including non-small-cell lung carcinoma (NSCLC). However, the prognostic value and correlation between FHIT hypermethylation and clinicopathological characteristics of NSCLC remains unclear. In this report, we performed a meta-analysis to evaluate the effects of FHIT hypermethylation on the incidence of NSCLC and clinicopathological characteristics of human NSCLC patients. Final analysis of 1,801 NSCLC patients from 18 eligible studies was performed. FHIT hypermethylation was found to be significantly higher in NSCLC than in normal lung tissue. The pooled odds ratio (OR) from ten studies included 819 NSCLC and 792 normal lung tissues (OR = 7.51, 95% confidence interval [CI] = 2.98–18.91, P , 0.0001). Subgroup analysis based on ethnicity implied that FHIT hypermethylation level was higher in NSCLC tissues than in normal tissues in both Caucasians ( P = 0.02) and Asians ( P , 0.0001), indicating that the difference in Asians was much more significant. FHIT hypermethylation was also correlated with sex status, smoking status, as well as pathological types. In addition, patients with FHIT hypermethylation had a lower survival rate than those without (hazard ratio = 1.73, 95% CI = 1.10–2.71, P = 0.02). The results of this meta-analysis suggest that FHIT hypermethylation is associated with an increased risk and poor survival in NSCLC patients. FHIT hypermethylation, which induces the inactivation of FHIT gene, plays an important role in the carcinogenesis and clinical outcome and may serve as a potential diagnostic marker and drug target of NSCLC.
Identification of stable reference gene for qPCR studies in common wheat (Triticum aestivum L.) seedlings under short-term osmotic stress

BackgroundQuantitative PCR (qPCR) is one of the most common and accurate methods of gene expression analysis. However, the biggest challenge for this kind of examinations is normalization of the results, which requires the application of dependable internal controls. The selection of appropriate reference genes (RGs) is one of the most crucial points in qPCR data analysis and for correct assessment of gene expression. Because of the fact that many reports indicate that the expression profiles of typically used RGs can be unstable in certain experimental conditions, species or tissues, reference genes with stable expression levels should be selected individually for each experiment. In this study, we analysed a set of ten candidate RGs for wheat seedlings under short-term drought stress. Our tests included five ‘traditional’ RGs (GAPDH, ACT, UBI, TUB, and TEF1) and five novel genes developed by the RefGenes tool from the Genevestigator database.ResultsExpression stability was assessed using five different algorithms: geNorm, NormFinder, BestKeeper, RefFinder and the delta Ct method. In the final ranking, we identified three genes: CJ705892, ACT, and UBI, as the best candidates for housekeeping genes. However, our data indicated a slight variation between the different algorithms that were used. We revealed that the novel gene CJ705892, obtained by means of in silico analysis, showed the most stable expression in the experimental tissue and condition.ConclusionsOur results support the statement, that novel genes selected for certain experimental conditions have a more stable level of expression in comparison to routinely applied RGs, like genes encoding actin, tubulin or GAPDH. Selected CJ705892 gene can be used as a housekeeping gene in the expression analysis in wheat seedlings under short-term drought. The results of our study will be useful for subsequent analyses of gene expression in wheat tissues subjected to drought.
Acupuncture for chronic knee pain: a randomized clinical trial.

IMPORTANCE There is debate about benefits of acupuncture for knee pain. OBJECTIVE To determine the efficacy of laser and needle acupuncture for chronic knee pain. DESIGN, SETTING, AND PARTICIPANTS Zelen-design clinical trial (randomization occurred before informed consent), in Victoria, Australia (February 2010-December 2012). Community volunteers (282 patients aged ≥50 years with chronic knee pain) were treated by family physician acupuncturists. INTERVENTIONS No acupuncture (control group, n = 71) and needle (n = 70), laser (n = 71), and sham laser (n = 70) acupuncture. Treatments were delivered for 12 weeks. Participants and acupuncturists were blinded to laser and sham laser acupuncture. Control participants were unaware of the trial. MAIN OUTCOMES AND MEASURES Primary outcomes were average knee pain (numeric rating scale, 0 [no pain] to 10 [worst pain possible]; minimal clinically important difference [MCID], 1.8 units) and physical function (Western Ontario and McMaster Universities Osteoarthritis Index, 0 [no difficulty] to 68 [extreme difficulty]; MCID, 6 units) at 12 weeks. Secondary outcomes included other pain and function measures, quality of life, global change, and 1-year follow-up. Analyses were by intention-to-treat using multiple imputation for missing outcome data. RESULTS At 12 weeks and 1 year, 26 (9%) and 50 (18%) participants were lost to follow-up, respectively. Analyses showed neither needle nor laser acupuncture significantly improved pain (mean difference; -0.4 units; 95% CI, -1.2 to 0.4, and -0.1; 95% CI, -0.9 to 0.7, respectively) or function (-1.7; 95% CI, -6.1 to 2.6, and 0.5; 95% CI, -3.4 to 4.4, respectively) compared with sham at 12 weeks. Compared with control, needle and laser acupuncture resulted in modest improvements in pain (-1.1; 95% CI, -1.8 to -0.4, and -0.8; 95% CI, -1.5 to -0.1, respectively) at 12 weeks, but not at 1 year. Needle acupuncture resulted in modest improvement in function compared with control at 12 weeks (-3.9; 95% CI, -7.7 to -0.2) but was not significantly different from sham (-1.7; 95% CI, -6.1 to 2.6) and was not maintained at 1 year. There were no differences for most secondary outcomes and no serious adverse events. CONCLUSIONS AND RELEVANCE In patients older than 50 years with moderate or severe chronic knee pain, neither laser nor needle acupuncture conferred benefit over sham for pain or function. Our findings do not support acupuncture for these patients. TRIAL REGISTRATION anzctr.org. au Identifier: ACTRN12609001001280.
L ESTIMATES FOR JOINT QUASIMODES OF SEMICLASSICAL PSEUDODIFFERENTIAL OPERATORS

We develop a set of L estimates for functions u that are a joint quasimode (approximate eigenfunction) of r pseudodifferential operators p1(x, hD), . , pr(x, hD). This work extends Sarnak [10] and Marshall’s [8] work on symmetric space to cover a more general class of manifolds/operators. Let (M, g) be a compact, boundaryless Riemannian manifold of dimension n. It is well established that there is a countably infinite set of eigenfunctions ∆guj = −λjuj λj →∞ (0.1) which can be normalised to produce an orthonormal basis for L(M). An important question arising in harmonic analysis is to quantify the degree to which eigenfunctions can be spatially concentrated. One way to measure this concentration is to compare the L norm uj to its L 2 norm. In 1988 Sogge [11] obtained a set of estimates ||uj||Lp ≤ Cλ δ(n,p) j ||uj||L2 where δ(n, p) is given by the piecewise linear function δ(n, p) = { n−1 2 − n p 2(n+1) n−1 ≤ p ≤ ∞ n−1 4 − n−1 2p 2 ≤ p ≤ 2(n+1) n−1 . In fact the L∞ estimate was known much earlier; see [7] and [4]. However interpolation between the L∞ bound and the trivial L bound does not produce sharp estimates for any of the intermediate L. In comparison Sogge’s estimates are known to be sharp on the sphere. The high p estimates (that is p ≥ 2(n+1)/n−1) are saturated by zonal harmonics and the low p estimates (that is p ≤ 2(n+ 1)/n− 1) by highest weight harmonics. The same L bounds have be shown to hold for approximate eigenfunctions of semiclassical pseudodifferential operators with Laplace-like conditions on their symbol [6] and there is a rich literature of related results considering L estimates on lower dimension subsets of M (see for example [1],[5],[3],[12],[2]). In his letter to Morawetz [10], Sarnak asks about potential improvements for joint eigenfunctions of the form u = φ1(x1) · · ·φr(xr) where each φi is an eigenfunction of a differential (or pseudodifferential) operator Pi with P1 = ∆. He notes that on S 2 the invariance of zonal harmonics under rotation around the north pole prevents any improvement to the L∞ estimate where the second operator is the generator of rotations about the North/South axis,
European Journal of Educational Research

: This study aims to produce a product to evaluate students' critical thinking skills that departs from physics content where students often have misconceptions. This research is a development research with research stages covering a) research and review literature; (b) planning chapter objectives; (c) developing a preliminary form; (d) field-testing the preliminary form; (e) Revise the preliminary form; (f) conducting a main field-test. The Waves Critical Thinking (WCT) test developed consists of 7 questions with 15 specific domains. Total percentage of content validity test was obtained 87.98% with appropriate criteria and based on the construct validity WCT test, the Goodness of Fit criteria were obtained which were classified as fit. The test instrument being tested consists of 15 objective items. The reliability of WCT test results 0.597 as a Cronbach's alpha score with the medium category and all the components have a good level of composite reliability. The outcome of the study was the WCT test with a valid state for measuring students' CT in a specific domain of physics wave material.
Evaluación de las respuestas emocionales a la publicidad televisiva desde el Neuromarketing

Desde el siglo pasado hemos presenciado una evolucion constante de las tecnicas de comunicacion publicitarias en un intento de adaptacion a las nuevas realidades sociales del mercado. Como recurso estrategico, la Neurociencia aporta una nueva perspectiva al permitir explorar aquellos motivos dificiles de verbalizar o inconscientes que hay detras de los comportamientos de los consumidores. El presente trabajo tiene como objetivo descubrir la relacion entre las emociones inducidas en los mensajes publicitarios audiovisuales y su impacto en el recuerdo de los sujetos. Para alcanzar este objetivo se ha realizado un experimento con ocho mensajes publicitarios audiovisuales (seis representativos de seis emociones basicas: alegria, sorpresa, ira, asco, miedo y tristeza; y dos racionales) en el que se han utilizado, por un lado, tecnicas de Neuromarketing como son la actividad electrica cardiaca (ECG) y la actividad electrica de la dermis (AED) de los sujetos; y, por otro, una tecnica de investigacion convencional, un cuestionario aplicado a los sujetos que han participado en la investigacion. Los resultados ponen de manifiesto variaciones en las medidas realizadas en los mensajes correspondientes a la alegria, la sorpresa y la ira, mientras que, tanto para el recuerdo sugerido del mensaje trasmitido como para la actividad del anunciante, el anuncio con mejores resultados ha sido el de la tristeza, anuncio que tambien ha sido considerado el mas atractivo para los sujetos participantes.
Free vibrations of geometrically nonlinear column locally resting on the winkler elastic foundation under the specific load

The results of theoretical and numerical studies concerning continuous system subjected to the follower force directed towards the positive pole, locally resting on Winkler elastic foundation are presented in this paper. The load by follower force directed towards the positive pole is guaranteed by loading structure built of loading and receiving heads made of elements of circular outlines. Abovementioned heads are real constructions, used in experimental research of continuous systems. Taking into account total mechanical energy of the system, the Hamilton’s principle and the small parameter method, the differential equations of motion and boundary conditions of the considered column were determined. On the basis of a solution of the issue of dynamics of the system, an appropriate formulas were formulated and then the trajectory of curves on the plane frequency of free vibrations – the value of external load were calculated taking into considerations physical and geometrical parameters of the structure, including parameter of loading head and parameters describing Winkler elastic foundation.
Local Large Language Models for Complex Structured Medical Tasks

This paper introduces an approach that combines the language reasoning capabilities of large language models (LLMs) with the benefits of local training to tackle complex, domain-specific tasks. Specifically, the authors demonstrate their approach by extracting structured condition codes from pathology reports. The proposed approach utilizes local LLMs, which can be fine-tuned to respond to specific generative instructions and provide structured outputs. The authors collected a dataset of over 150k uncurated surgical pathology reports, containing gross descriptions, final diagnoses, and condition codes. They trained different model architectures, including LLaMA, BERT and LongFormer and evaluated their performance. The results show that the LLaMA-based models significantly outperform BERT-style models across all evaluated metrics, even with extremely reduced precision. The LLaMA models performed especially well with large datasets, demonstrating their ability to handle complex, multi-label tasks. Overall, this work presents an effective approach for utilizing LLMs to perform domain-specific tasks using accessible hardware, with potential applications in the medical domain, where complex data extraction and classification are required.
HANDAL: A Dataset of Real-World Manipulable Object Categories with Pose Annotations, Affordances, and Reconstructions

We present the HANDAL dataset for category-level object pose estimation and affordance prediction. Unlike previous datasets, ours is focused on robotics-ready manipulable objects that are of the proper size and shape for functional grasping by robot manipulators, such as pliers, utensils, and screwdrivers. Our annotation process is streamlined, requiring only a single off-the-shelf camera and semi-automated processing, allowing us to produce high-quality 3D annotations without crowd-sourcing. The dataset consists of 308k annotated image frames from 2.2k videos of 212 real-world objects in 17 categories. We focus on hardware and kitchen tool objects to facilitate research in practical scenarios in which a robot manipulator needs to interact with the environment beyond simple pushing or indiscriminate grasping. We outline the usefulness of our dataset for 6-DoF category-level pose+scale estimation and related tasks. We also provide 3D reconstructed meshes of all objects, and we outline some of the bottlenecks to be addressed for democratizing the collection of datasets like this one. Project website: https://nvlabs.github. io/HANDAL/
Infinite-channel deep stable convolutional neural networks

The interplay between infinite-width neural networks (NNs) and classes of Gaussian processes (GPs) is well known since the seminal work of Neal (1996). While numerous theoretical refinements have been proposed in the recent years, the interplay between NNs and GPs relies on two critical distributional assumptions on the NN’s parameters: A1) finite variance; A2) independent and identical distribution (iid). In this paper, we consider the problem of removing A1 in the general context of deep feed-forward convolutional NNs. In particular, we assume iid parameters distributed according to a stable distribution and we show that the infinite-channel limit of a deep feed-forward convolutional NNs, under suitable scaling, is a stochastic process with multivariate stable finite-dimensional distributions. Such a limiting distribution is then characterized through an explicit backward recursion for its parameters over the layers. Our contribution extends results of Favaro et al. (2020) to convolutional architectures, and it paves the way to expand exciting recent lines of research that rely on classes of GP limits.
Compressible Rayleigh-Taylor turbulent mixing under different acceleration histories

Compressible Rayleigh-Taylor turbulent mixing (CRTM) induced by Rayleigh-Taylor instability occurs when a compressible fluid of heavy density is accelerated or supported against gravity by a compressible fluid of light density, and is of fundamental importance in applications from combustion, to inertial confinement fusion, and to astrophysics. Traditionally, CRTFs are studied under constant acceleration histories. Due to the nature of the processes, however, it is necessary to study CRTF under general acceleration histories g(t). In this aspect, the evolution of Rayleigh-Taylor turbulent mixing under complex acceleration histories, including changes in signs, have been studied numerically[1] and experimentally[2] for incompressible flows, leaving an open question on that of compressible flows. In fact, most engineering problems are compressible. In addition, the available engineering turbulence models cannot capture the variation of mixing width for CRTM with complex acceleration histories, such as the gravity reversal. In order to better understanding the dynamic of CRTM under different variation histories, several DNS cases with different acceleration histories have been conducted and analyzed.
Impacts of high-contrast image processing on atmospheric retrievals

Many post-processing algorithms have been developed in order to better separate the signal of a companion from the bright light of the host star, but the effect of such algorithms on the shape of exoplanet spectra extracted from integral field spectrograph data is poorly understood. The resulting spectra are affected by noise that is correlated in wavelength space due to both optical and data processing effects. Within the framework of Bayesian atmospheric retrievals, we aim to understand how these correlations and other systematic effects impact the inferred physical parameters. We consider three algorithms (KLIP, PynPoint and ANDROMEDA), optimizing the choice of algorithmic parameters using a series of injection tests into archival SPHERE and GPI data of the HR 8799 system. The wavelength-dependent covariance matrix is calculated to provide a measure of instrumental and algorithmic systematics. We perform atmospheric retrievals using petitRADTRANS on optimally extracted spectra to measure how these data processing systematics influence the retrieved parameter distributions. The choice of data processing algorithm and parameters significantly impact the accuracy of retrieval results, with the mean posterior parameter bias ranging from 1 to 3 $\sigma$ from the true input parameters. Including the full covariance matrix in the likelihood improves the accuracy of inferred parameters, and cannot be accounted for using ad hoc scaling parameters in the retrieval framework. Using the Bayesian information criterion and other statistical measures as a heuristic goodness-of-fit metrics, the retrievals including the full covariance matrix are favoured when compared to using only the diagonal elements.
On the signs of the principal minors of Hermitian matrices

The signed enhanced principal rank characteristic sequence (sepr-sequence) of a given $n \times n$ Hermitian matrix $B$ is the sequence $t_1t_2 \cdots t_n$, where $t_k$ is $\tt A^*$, $\tt A^+$, $\tt A^-$, $\tt N$, $\tt S^*$, $\tt S^+$, or $\tt S^-$, based on the following criteria: $t_k = \tt A^*$ if all the order-$k$ principal minors of $B$ are nonzero, and two of those minors are of opposite sign; $t_k = \tt A^+$ (respectively, $t_k = \tt A^-$) if all the order-$k$ principal minors of $B$ are positive (respectively, negative); $t_k = \tt N$ if all the order-$k$ principal minors of $B$ are zero; $t_k = \tt S^*$ if $B$ has a positive, a negative, and a zero order-$k$ principal minor; $t_k = \tt S^+$ (respectively, $t_k = \tt S^-$) if $B$ has both a zero and a nonzero order-$k$ principal minor, and all the nonzero order-$k$ principal minors of $B$ are positive (respectively, negative). A complete characterization of the sequences of order $2$ and order $3$ that do not occur as a subsequence of the sepr-sequence of any Hermitian matrix is presented (a sequence has order $k$ if it has $k$ terms). An analogous characterization for real symmetric matrices is presented as well.