Miracle-dz/UniFAR-FTUs huggingface dataset:
Paramagnetic rim and core sign lesions in paediatric multiple sclerosis patients

INTRODUCTION In the last years, susceptibilityweighted imaging (SWI) has been applied in multiple sclerosis (MS) to identify a subgroup of white matter lesions (WMLs) characterised by a hypointense rim (ie, paramagnetic rim lesions (PRL)). Correlative pathologicalMRI studies have shown that these lesions, defined as chronic active, are characterised by a peripheral ‘rim’ of ironladen activated microglia/ macrophages associated with ongoing demyelination and axonal loss. A subset of WMLs showing a diffuse hypointensity on SWI (ie, core sign lesions) has also been recently described. These lesions have been suggested to reflect acute inflammation showing widespread demyelination and infiltrates of activated microglia/ macrophages. PRLs are considered relatively specific for MS, are present across all adult MS phenotypes and predict a more severe disease evolution. On the other hand, core sign lesions have been observed at the earliest phases of adult MS, tended to disappear and shrink over a 3year period followup, and only a minority of them evolved into PRLs. Given the relevant diagnostic and prognostic implications of PRLs and core sign WMLs in MS, we explored their prevalence in paediatric MS patients.
Detecting Canine Mastication: A Wearable Approach

Mastication is considered a coping mechanism in dogs, therefore, providing chew toys as an enrichment technique may be particularly important in stressful environments, such as the kennel. However, the relationship between chewing and welfare in kennel-housed dogs has not been systematically examined. The purpose of this study was to develop a sensor to quantify chewing with the intention that this technology could be used to understand the relationship between chewing and welfare in kennel-housed dogs. We show that a collar-based microphone can sense canine bites on a Nylabone chew toy. Four human raters annotated bites on audio samples collected from twelve dogs with five minutes of continuous access to the chew toy. A high degree of reliability was found with an average intraclass correlation coefficient (ICC) of 0.994. Using consensus labeling for training, we created bite detection algorithms using random forest, logistic regression, and convolutional neural network (CNN) based techniques. The CNN-based system achieved the highest performance recognition with an accuracy of 88% with a 91% F1 score. This technology will allow us to analyze a larger data set to uncover relationships between chewing styles and stress, cognition, and other characteristics associated with dog welfare.
Blind dogs need guides too: towards technological support for blind dog caregiving

Blind or visually impaired pet dogs have additional challenges to overcome in their daily life in environments typically built for sighted humans, as do their caregivers in supporting them. From simple activities like finding their food in a hopefully stable home environment, to more complex activities like navigating an ever changing outdoor environment safely. While some support exists for blind and visually impaired dogs, frequently in the form of physical safety products and veterinary guidelines for care giving, little interactive technology yet exists to inform and complement caregivers’ abilities. In this paper, we present the results of an interview-based study with caregivers of blind and visually impaired dogs, using thematic analysis to construct core themes of support needed, and translated these into a prototype app. Our findings show that, while caregivers can adapt quickly to coping with a blind or visually impaired pet dog in their own environment, a gap exists in coping with (ever changing) outdoor environments, in particular identifying safe and suitable outdoor walking routes. We show an initial design of a mobile app for this purpose, and discuss to what extent software for informed caregiving of visually impaired pet dogs could benefit from further work.
Coronal Composition above the Solar Equator and the North Pole as Determined from Spectra Acquired by the SUMER Instrument on SOHO

Using spectra obtained by the SUMER instrument on the Solar and Heliospheric Observatory (SOHO) we have determined the composition of the bulk of the coronal plasma in the vicinity of the solar surface over a polar coronal hole and an equatorial region. Our measurements show that although low first ionization potential (FIP) elements are enriched by about a factor of 4 in the corona above the quiet equatorial region, little or no enrichment exists above the north polar coronal hole. These observations are in good agreement with the Ulysses in situ observations in both fast speed and slow speed winds.
Analyzing the Performance of SD-WAN Enabled Service Function Chains Across the Globe with AWS

Cloud Computing has revolutionized the information technology world and the application offering over the last two decades. At the same time recent trends in Network Function Virtualization (NFV) and Software-Defined Wide Area Networks (SD-WAN) and the combination of those with the Cloud paradigm has allowed an unprecedented shift of enterprise networking services towards the Public Cloud. Even though this network evolutionary approach brings many benefits, it still presents many drawbacks as well. The performance stability and service continuity over a black box Public Cloud infrastructure can hinder the formal service guarantees that many new emerging applications may have. To this end, in this paper, we aim to shed light on the overall performance achieved when deploying coast-to-coast and intercontinental Service Function Chains (SFCs) that interconnect geographically distributed enterprise branches over the Amazon Web Services (AWS) infrastructure. In particular, we investigate the impact of region, Virtual Machine (VM) instance, time of the day and day of the week in the overall throughput and delay attained. The obtained results show the strengths and weaknesses of entirely relying on the AWS infrastructure to offer networking services by investigating possible hidden performance bottlenecks.
Supervenience, Dynamical Systems Theory, and Non-Reductive Physicalism

It is often claimed (1) that levels of nature are related by supervenience, and (2) that processes occurring at particular levels of nature should be studied using dynamical systems theory. However, there has been little consideration of how these claims are related. To address the issue, I show how supervenience relations give rise to ‘supervenience functions’, and use these functions to show how dynamical systems at different levels are related to one another. I then use this analysis to describe a graded approach to non-reductive physicalism, and to critically assess Davidson’s arguments for psychological anomaly. I also show how this approach can inform empirical research in cognitive science. 1 States and State Spaces 2 The Supervenience Function and its Inverse 3 Dynamical Systems Theory and Supervenience 4 Inter-Level Relations and Non-Reductive Physicalism 5 Davidson on Psychological Anomalism 6 Symbolic Dynamics 1 States and State Spaces 2 The Supervenience Function and its Inverse 3 Dynamical Systems Theory and Supervenience 4 Inter-Level Relations and Non-Reductive Physicalism 5 Davidson on Psychological Anomalism 6 Symbolic Dynamics
STUDENTS' OVERRELIANCE ON PROPORTIONALITY: EVIDENCE FROM PRIMARY SCHOOL PUPILS SOLVING ARITHMETIC WORD PROBLEMS

Building on previous research on the tendency in students of diverse ages to overrely on proportionality in different domains of mathematics (e.g., geometry, probability), this study shows that – when confronted with missing-value word problems – Flemish primary school pupils strongly tend to apply proportional solution strategies, also in cases where they are not applicable. The evolution of this tendency is also investigated. It appeared that the overreliance on proportionality already emerges in the 2 nd grade, but it increases considerably up to the 5 th grade.
Cleavage kinetics of human mitochondrial RNase P and contribution of its non-nuclease subunits

RNase P is the endonuclease responsible for the 5’-end processing of tRNA precursors (pre-tRNAs). Unlike the single-subunit protein-only RNase P (PRORP) found in plants or protists, human mitochondrial RNase P is a multi-enzyme assembly that in addition to the homologous PRORP subunit comprises a methyltransferase (TRMT10C) and a dehydrogenase (SDR5C1) subunit; these proteins, but not their enzymatic activities, are required for efficient pre-tRNA cleavage. Here we report a detailed kinetic analysis of the cleavage reaction by human PRORP and its interplay with TRMT10C-SDR5C1 using a comprehensive set of mitochondrial pre-tRNAs. Surprisingly, we found that PRORP alone binds pre-tRNAs with nanomolar affinity and can even cleave some of them at reduced efficiency without the other subunits. Thus, the ancient binding mode, involving the tRNA elbow and PRORP’s PPR domain, seems retained by human PRORP, and its metallonuclease domain is in principle correctly folded and functional. Our findings support a model according to which the main function of TRMT10C-SDR5C1 is to direct PRORP’s nuclease domain to the cleavage site, thereby increasing the rate and accuracy of cleavage. Human PRORP’s dependence on the extra tRNA binder appears to have evolved to secure specificity in the cleavage of the structurally degenerating mitochondrial tRNAs.
Temporal perturbation of STAT1/2 activity reveals dynamic ligand discrimination of type I interferon signaling

Type-I interferon (IFN-I) subtypes signal through the same IFNα receptor (IFNAR), and initiate temporal STAT1/2 activation to orchestrate innate and adaptive immunity. It remains unknown how IFNAR discriminates between subtypes (e.g., IFNα and IFNβ), and how STAT1/2 signaling is affected by time-varying inputs. Here, we utilize our microfluidic system and live-cell imaging to quantify STAT1/2 activation dynamics in a reporter fibroblast model. Population-averaged and single-cell analyses reveal distinct STAT1/2 responses to various IFNα and IFNβ inputs. Upon continuous stimulation, cells show less sensitivity but more sustained responses to IFNα over IFNβ. A short IFNα pulse induces nearly homogeneous STAT1/2 dynamics, in contrast to heterogeneous responses in IFNβ-pulsed cells. Distinct STAT1/2 refractory states emerge upon exposure to repeated IFN-I pulses, while alternating pulse stimulation reveals that IFNβ can revoke STAT1/2 refractoriness caused by IFNα, but not vice versa. These findings highlight the differences between IFNα and IFNβ signaling and how they can elicit distinct temporal cellular behaviors during viral infection.
De novo assembly of the black flounder genome. Why do pleuronectiformes have such a small genome size?

Black flounder (Paralichthys orbignyanus) is an economically important ma-rine fish with aquaculture potential in Argentina due to its market value. In this study, we sequenced the whole genome using an Illumina sequencing technology. We started with two independent libraries (from one female and one pool of females; each with 150 bp paired-end reads, a mean insert length of 350 bp, and >35 X-fold coverage). Each library was assembled separately using SOAPdenovo2 and the resulting contigs were scaffolded with SSPACE3 before gaps were filled with GapCloser. In vertebrates, including teleosts, the number of transposable elements (TEs) is related to genome size, but it remains unclear whether the size of introns and exons also plays a role. Therefore, the main objective of the present study was to test whether the small genome size of Pleuronectiformes is related to the size of their introns and exons. The assemblies re-sulted in a genome size of ∼538 Mbp (41.35% GC content, 0.11% undetermined bases). Analysis of the assemblies at the core genes level (subset of the 458 universally ex-pressed KOG families) revealed that more than 98% of core genes are present, with more than 78% of them having more than 50% coverage. This indicates a fairly complete and accurate genome at the coding sequence level. Prediction of genes based on statistical predictors (geneid) and sequence-based predictors (Exonerate, using a closely related species, Paralichthys olivaceus, as a reference) was performed. This revealed 25,231 protein-coding genes, 445 tRNAs, 3 rRNAs, and more than 1,500 non-coding RNAs of other types (including a complete set of spliceosomes and several types of snoRNA and miRNA). As a result, this study concluded that the reduced genome size of flounders is related to a reduction in transcript size, mainly through a reduction in exon number, but also through a reduction in large introns. Thus, both components seem to be involved in the strategy of genome reduction in Pleuronectiformes.
Using bimodal kernel for nonparametric regression specification test

For a nonparametric regression model with a fixed design, we consider the model specification test based on a kernel. Interestingly, we find that a bimodal kernel is useful for the model specification test with a correlated error, whereas a conventional unimodal kernel is useful only for an iid error. Another interesting finding is that the model specification test suffers from a convergence rate change whether the errors are correlated or not. These results are verified by deriving an asymptotic null distribution and asymptotic (local) power and by performing a simulation. Based on our findings, we recommend the use of a bimodal kernel for a nonparametric regression model specification test. The validity of the bimodal kernel for testing is demonstrated with the “drum roller” data (see Laslett(1994) and Altman (1994)).
A dynamic neural resource model bridges sensory and working memory

Probing memory of a complex visual image within a few hundred milliseconds after its disappearance reveals significantly greater fidelity of recall than if the probe is delayed by as little as a second. Classically interpreted, the former taps into a detailed but rapidly decaying visual sensory or “iconic” memory (IM), while the latter relies on capacity-limited but comparatively stable visual working memory (VWM). While iconic decay and VWM capacity have been extensively studied independently, currently no single framework quantitatively accounts for the dynamics of memory fidelity over these timescales. Here we extend a stationary neural population model of VWM with a temporal dimension, incorporating rapid sensory-driven accumulation of activity encoding each visual feature in memory, and a slower accumulation of internal error that causes memorized features to randomly drift over time. Instead of facilitating read-out from an independent sensory store, an early cue benefits recall by lifting the effective limit on VWM signal strength imposed when multiple items compete for representation, allowing memory for the cued item to be supplemented with information from the decaying sensory trace. Empirical measurements of human recall dynamics validate these predictions while excluding alternative model architectures. A key conclusion is that differences in capacity classically thought to distinguish IM and VWM are in fact contingent upon a single resource-limited WM store.
Anticancer efficacy of KRASG12C inhibitors is potentiated by PAK4 inhibitor KPT9274 in preclinical models of KRASG12C mutant pancreatic and lung cancers

KRASG12C inhibitors have revolutionized the treatment landscape for cancer patients harboring the G12C mutant isoform of KRAS. With the recent FDA approval of sotorasib and adagrasib, patients now have access to more promising treatment options. However, patients who receive these agents as a monotherapy usually develop drug resistance. Thus, there is a need to develop logical combination strategies that can delay or prevent the onset of resistance and simultaneously enhance the antitumor effectiveness of the treatment regimen. In this study, we aimed at pharmacologically targeting PAK4 by KPT9274 in combination with KRASG12C inhibitors in KRASG12C mutant pancreatic ductal adenocarcinoma (PDAC) and non–small cell lung cancer (NSCLC) preclinical models. PAK4 is a hub molecule that links several major signaling pathways and is known for its tumorigenic role in mutant Ras-driven cancers. We assessed the cytotoxicity of PAK4 and KRASG12C inhibitors combination in KRASG12C mutant 2D and 3D cellular models. KPT9274 synergized with both sotorasib and adagrasib in inhibiting the growth of KRASG12C mutant cancer cells. The combination was able to reduce the clonogenic potential of KRASG12C mutant PDAC cells. We also evaluated the antitumor activity of the combination in a KRASG12C mutant PDAC cell line-derived xenograft (CDX) model. Oral administration of a sub-optimal dose of KPT9274 in combination with sotorasib (at one-fourth of MTD) demonstrated significant inhibition of the tumor burden (p = 0.002). Similarly, potent antitumor efficacy was observed in an NSCLC CDX model where KPT9274, acting as an adjuvant, prevented tumor relapse following the discontinuation of sotorasib treatment (p = 0.0001). KPT9274 and sotorasib combination also resulted in enhanced survival. This is the first study showing that KRASG12C inhibitors can synergize with PAK4 inhibitor KPT9274 both in vitro and in vivo resulting in remarkably enhanced antitumor activity and survival outcomes. Significance KRASG12C inhibitors demonstrate limited durable response in patients with KRASG12C mutations. In this study, combining PAK4 inhibitor KPT9274 with KRASG12C inhibitors has resulted in potent antitumor effects in preclinical cancer models of PDAC and NSCLC. Our results bring forward a novel combination therapy for cancer patients that do not respond or develop resistance to KRASG12C inhibitor treatment.
Is it out yet? Automatic Future Product Releases Extraction from Web Data

Identifying the release of new products and their predicted demand in advance is highly valuable for E-Commerce marketplaces and re-tailers. The information of an upcoming product release is used for inventory management, marketing campaigns and pre-order suggestions. Often, the announcement of an upcoming product release is widely available in multiple web pages such as blogs, chats or news articles. However, to the best of our knowledge, an automatic system to extract future product releases from web data has not been presented. In this work we describe an ML-powered multi-stage pipeline to automatically identify future product releases and rank their predicted demand from unstructured pages across the whole web. Our pipeline includes a novel Longformer-based model which uses a global attention mechanism guided by pre-calculated Named Entity Recognition predictions related to product releases. The model training data is based on a new corpus of 30K web pages manually annotated to identify future product releases. We made the dataset openly available at https: //doi.org/10.5281/zenodo.6894770 .
A periodic-like solution in channel flow

We search channel flow for unsteady solutions for different Reynolds numbers and configurations by extending a shooting method which was previously used to obtain a travelling-wave solution. A general initial condition is considered. A periodic-like solution to the incompressible Navier–Stokes equations in a minimal flow unit is found. One cycle of the solution consists of two typical intervals: a single-streak period and a double-streak period. The solution seems to be periodic; however, it cannot be distinguished from a heteroclinic cycle which consists of two heteroclinic orbits connecting two single-streak solutions, because the solution is tracked only for one and half periods.
The optical to near-infrared emission of BL Lac objects: simultaneous observations

We present simultaneous optical to near-IR observations of 34 blazars, most of which classical BL Lacertae objects, with repeated observations for 21 of them. The observations cover a period of 3 years with a typical time interval of 6 months. With the sole exception of PKS 2208-137, all observed optical to near-IR flux distributions can be described either by a single power law (f ν ∞ν −α ) or by a power law plus the contribution of a standard elliptical galaxy. The optical and near-IR emission are strongly correlated and usually maintain the spectral index even under substantial flux variations. The average spectral index of the nonthermal emission, in the range 8×10 13 to 7×10 14 Hz, is 1.08±0.06 with significantly flatter spectra for the x-ray selected subsample
Simultaneous Estimation of Diethylcarbamazine Citrate and Cetirizine Hydrochloride in Formulation by RP-HPLC

A Simple and reproducible method for simultaneous estimation of Diethylcarbamazine citrate (DECC) and Cetirizine hydrochloride (CTH) by High performance liquid chromatography (HPLC) in formulation was developed. The analysis was performed with a mobile phase containing Acetonitrile and mixed phosphate buffer (KH2PO4 and K2HPO4, adjusted to pH – 3.0 with 10% orthophosphoric acid) in the ratio of 60:40(%v/v) at a flow rate of 1ml/min. A phenomenex C18 column (250 × 4.6mm,5μm)was used. The wavelength of DECC is 216nm and Cetirizine is 230nm and from the overlapping spectra a wavelength of 220nm is selected and simultaneous estimation is carried out. The analysis was performed in the linearity range of 24–144 μg/ml for Diethylcarbamazine citrate and 0.8 -4.8 μg/ml for Cetirizine hydrochloride and the minimum detectable level was 0.62 μg/ml and 0.105 μg/ml. The correlation coefficient was 0.998 and 0.997. Thus the developed and validated chromatographic method for Diethylcarbamazine citrate and Cetirizine hydrochloride is said to be rapid, simple, accurate and cost effective that can be applied for routine analysis in research institution, quality control department in industries and in clinical pharmacokinetic studies.
Numerical estimation of thermal conductivity from boundary temperature measurements

A numerical algorithm is proposed to estimate the thermal conductivity of a homogeneous material from boundary temperature measurements. In this inverse analysis the homogeneous material is divided into several subdomains, and the thermal conductivity in each individual subdomain is assumed to be a linear function of temperature. A hybrid numerical scheme involving the combination of the Laplace transform technique and the control volume method is used to solve the pertinent nonlinear equations. The estimated thermal conductivity of the material is taken as a combination of estimated values of those subdomains. The accuracy of the predicted results is examined from an illustrated case using simulated transient boundary temperature data with measurement errors. Results show that good estimations on the thermal conductivity can be obtained with arbitrary initial guess values. The present study found that the thermal conductivity can be determined without measuring temperature data inside the material.