Miracle-dz/UniFAR-FTUs huggingface dataset:
Reconfigurable Logic for Hardware IP Protection: Opportunities and Challenges (Invited Paper)

Protecting the intellectual property (IP) of integrated circuit (IC) design is becoming a significant concern of fab-less semiconductor design houses. Malicious actors can access the chip design at any stage, reverse engineer the functionality, and create illegal copies. On the one hand, defenders are crafting more and more solutions to hide the critical portions of the circuit. On the other hand, attackers are designing more and more powerful tools to extract useful information from the design and reverse engineer the functionality, especially when they can get access to working chips. In this context, the use of custom reconfigurable fabrics has recently been investigated for hardware IP protection. This paper will discuss recent trends in hardware obfuscation with embedded FP-GAs, focusing also on the open challenges that must be necessarily addressed for making this solution viable.
The role of topical therapies along the psoriasis patient journey: An overview from the Symposium ‘Tailoring topical psoriasis treatments to patients' needs and expectations’ of the 30th EADV Congress 2021

This article summarizes a presentation titled ‘The role of topical therapies along the psoriasis patient journey’ held at the Satellite Symposium of the 30th European Academy of Dermatology and Venereology Congress. During this session, the role of topical treatments in the management of psoriasis was presented, with a particular focus on the current unmet needs and data gaps. Psoriasis plays a significant role in a patient's daily life, impacting them not only physically but also psychologically and socially. The disease burden increases with duration and severity. Topical therapies are the keystone of the management of psoriasis. About 70%–80% of patients present a mild‐to‐moderate form of psoriasis that can be successfully treated with topical agents. According to a German recommendation, patients with mild psoriasis should initiate a topical therapy in combination with skin care products. In the real‐life setting, the calcipotriol/betamethasone dipropionate (CAL/BDP) fixed combination was the most prescribed topical treatment for beyond‐mild patients in Germany, Spain and the United Kingdom. Healthcare professionals also often or very often prescribed topicals as an alternative to non‐biologic systemics in certain situations, such as patient preference (51%), contraindication (50%) and to limit side effects (26%). Adjunctive topical therapy to patients using systemic therapy is used to optimize treatment outcomes and improving the quality of life for patients. Topical treatments can be also effective in severe forms of psoriasis. However, there are still some gaps and unmet needs on topical therapy. Ineffectiveness, patient dissatisfaction and adherence are the largest barriers to treatment success. Main strengths of topical treatments include the availability of various topical ingredients and galenics, the adaptability to different anatomical areas and the possible combination with phototherapy and systemics. Moreover, patients in specific situations can benefit from switching to topical treatments (e.g. pregnancy or surgery).
A single‐sweep, nanosecond time resolution laser temperature‐jump apparatus

We describe a fast temperature‐jump (T‐jump) apparatus capable of acquiring kinetic relaxation transients via real‐time fluorescence detection over a time interval from nanoseconds to milliseconds in a single sweep. The method is suitable for aqueous solutions, relying upon the direct absorption of laser light by the bulk water. This obviates the need for additives (serving as optical or conductive heaters) that may interact with the sample under investigation. The longitudinal temperature profile is made uniform by counterpropagating heating pulses. Dead time is limited to one period of the probe laser (16 ns). The apparatus response is tested with aqueous tryptophan and the diffusion‐controlled dimerization of proflavine.
Exploring psychosocial risk factors for dropout in adolescent female soccer

ABSTRACT Objectives We examined the manner in which age, participation in other sports, socioeconomic status, perceived sport competence, achievement goal orientations, and perceived motivational climate may interact to predict the risk of dropout among adolescent female soccer players. Methods Self-reported data from 519 female soccer players between 10 and 19 years of age (M = 13.41, SD = 1.77) were analysed using a person-centred approach to uncover the interactions among risk factors and their relative predictability of dropout. Results Perceived motivational climate was identified as the main predictor, where relatively lower levels of mastery climate were associated with a higher dropout tendency (absolute risk reduction [ARR] = 12.2% ±6.1% [95% CL]). If combined with relatively lower levels of mastery climate, then relatively lower levels of perceived sport competence were related to higher dropout risks (ARR = 16.5% ±9.5%), whereas, in combination with relatively higher levels of mastery climate, then relatively lower levels of ego-orientated achievement goals were associated with higher dropout rates (ARR = 10.8% ±12.6%) Conclusions Our findings afford novel insights into the interactions between, and the relative importance of, various risk factors for dropout in adolescent female soccer. This knowledge may be useful for soccer associations, clubs, and coaches when developing guidelines and strategies that aim to foster young females’ sustained participation in organised soccer.
Causal evidence for the involvement of Broca’s area in second language acquisition: A longitudinal HD-tDCS study

A wealth of correlational evidence suggests that Broca’s area (the left inferior frontal gyrus) plays a role in second language acquisition. With the use of highly focal non-invasive brain stimulation, evidence for a targeted brain region’s causal role in some cognitive behavior can be assessed. Over three sessions, each one week apart, we used online anodal high-definition transcranial direct current stimulation (HD-tDCS) over Broca’s area during a novel foreign grammar training session. During training, participants who were naïve to Spanish were tasked with acquiring present tense conjugation rules for the three Spanish verb endings. In Session 1, we observed significant improvement in performance in two linguistic (reception and production) tasks but not in a non-linguistic (working memory) task. Sessions 2 and 3 were subject to a ceiling effect, which obscured any potentially long-lasting effects of the stimulation. We interpret these results as support for the idea that Broca’s area has languagelike specificity that is not limited to receptive or productive processes and as evidence that Broca’s area plays a causal role in foreign grammar acquisition.
Differential response of patient-derived primary glioblastoma cells to metabolic and adhesion inhibitors

Purpose This study aims to investigate Glioblastoma (GBM) cellular response to adhesion and metabolic inhibitors in the context of cells’ migration and cell-matrix adhesion properties. GBM is the most common incurable brain tumour. Decades of work into GBM chemical and molecular classification have identified mechanisms of drug resistance. Inhibitors targeting cancer cell migration and proliferation rarely take into consideration the heterogeneous migration property amongst cells, which may impact patients’ response to treatment. Methods Tissue samples were obtained from spatially distinct locations with different 5-aminolevulinic acid (5-ALA) fluorescent intensities, strong strongly fluorescent tumour cores, a weak fluorescent tumour rim, and nonfluorescent tumour margins. Samples were previously shown to be associated with different motility and adhesion properties. We tested tumour cells’ response to adhesion and metabolic inhibitors using metabolic assays. Cell survival was also monitored using time-lapse microscopy, while cultured on low-modulus polydimethylsiloxane representative of the stiffness of brain tissue. Results Metabolic viability assays, MTT and Cell Titer, showed substantial heterogeneity in drug potency. Highly fluorescent tumour core cells were significantly more resistant to an F0F1 ATP synthase inhibitor (Gboxin), and a FAK inhibitor (GSK2256098), and cell proliferation ceased post-treatment in vitro. Cells derived from non-fluorescent tumour margins exhibited higher potency for the ATP synthase inhibitor (Gboxin). However, cell proliferation persisted post-treatment. Conclusion Our study suggests that the adhesive and migration properties of cells account for the sensitivity to therapeutics in different regions of the tumour in individual patients and between patients with GBM.
Larval and adult traits coevolve in response to coastal oceanography to shape marine dispersal kernels

Dispersal emerges as an outcome of organismal traits and external forcings. However, it remains unclear how the emergent dispersal kernel evolves as a by-product of selection on the underlying traits. This question is particularly compelling in coastal marine systems where dispersal is tied to development and reproduction, and where directional currents bias larval dispersal downstream causing selection for retention. We modelled the dynamics of a metapopulation along a finite coastline using an integral projection model and adaptive dynamics to understand how asymmetric coastal currents influence the evolution of larval (pelagic larval duration) and adult (spawning frequency) life history traits, which indirectly shape the evolution of marine dispersal kernels. Selection induced by alongshore currents favors the release of larvae over multiple time periods, allowing long pelagic larval durations and long-distance dispersal to be maintained in marine life cycles in situations where they were previously predicted to be selected against. Two evolutionary stable strategies emerged: one with a long pelagic larval duration and many spawning events resulting in a dispersal kernel with a larger mean and variance, and another with a short pelagic larval duration and few spawning events resulting in a dispersal kernel with a smaller mean and variance. Our theory shows how coastal ocean flows are important agents of selection that can generate multiple, often co-occurring, evolutionary outcomes for marine life history traits that affect dispersal.
A characterization of cardiac-induced noise in R2* maps of the brain

Purpose Cardiac pulsation increases the noise level in brain maps of the transverse relaxation rate R2*. Cardiac-induced noise is challenging to mitigate during the acquisition of R2* mapping data because its characteristics are unknown. In this work, we therefore aim to characterize cardiac-induced noise in brain maps of the MRI parameter R2*. Methods We designed a sampling strategy to acquire multi-echo 3D data in 12 intervals of the cardiac cycle, monitored with a fingertip pulse-oximeter. We measured the amplitude of cardiac-induced noise in this data and assessed the effect of cardiac pulsation on R2* maps computed across echoes. The area of k-space that contains most of the cardiac-induced noise in R2* maps was then identified. Based on these characteristics, we introduced a tentative sampling strategy that aims to mitigate cardiac-induced noise in R2* maps of the brain. Results In inferior brain regions, cardiac pulsation accounts for R2* variations of up to 3s-1 across the cardiac cycle, i.e. ∼35% of the overall variability. Cardiac-induced fluctuations occur throughout the cardiac cycle, with a reduced intensity during the first quarter of the cycle. 50-60% of the overall cardiac-induced noise is localized near the k-space centre (k < 0.074 mm-1). The tentative cardiac noise mitigation strategy reduced the variability of R2* maps across repetitions by 11% in the brainstem and 6% across the whole brain. Conclusion We provide a characterisation of cardiac-induced noise in brain R2* maps that can be used as a basis for the design of mitigation strategies during data acquisition.
Force on a Rectangular Coil Moving above a Conducting Slab

The force on a rectangular current‐carrying coil moving above and parallel to a conducting plate of arbitrary thickness is investigated. Expressions are developed for the lift and drag forces on the coil as a function of speed. Numerical calculations are made for a very thick plate and for plates with thickness of the order of the skin depth. Thick‐plate results are compared with experimental measurements of lift and drag on a superconducting coil suspended above a rotating aluminum wheel.
Calderón–Zygmund operators acting on generalized Carleson measure spaces

We study Calderón–Zygmund operators acting on generalized Carleson measure spaces CMO r and show a necessary and sufficient condition for their boundedness. The spaces CMO r are a generalization of BMO, and can be regarded as the duals of homogeneous Triebel–Lizorkin spaces as well.
Handling ill-conditioned omics data with deep probabilistic models

The advent of high-throughput technologies has produced an increase in the dimensionality of omics datasets, which limits the application of machine learning methods due to the great unbalance between the number of observations and features. In this scenario, dimensionality reduction is essential to extract the relevant information within these datasets and project it in a low-dimensional space, and probabilistic latent space models are becoming popular given their capability to capture the underlying structure of the data as well as the uncertainty in the information. This article aims to provide a general classification and dimensionality reduction method based on deep latent space models that tackles two of the main problems that arise in omics datasets: the presence of missing data and the limited number of observations against the number of features. We propose a semi-supervised Bayesian latent space model that infers a low-dimensional embedding driven by the target label: the Deep Bayesian Logistic Regression (DBLR) model. During inference, the model also learns a global vector of weights that allows to make predictions given the low-dimensional embedding of the observations. Since this kind of datasets is prone to overfitting, we introduce an additional probabilistic regularization method based on the semi-supervised nature of the model. We compared the performance of the DBLR against several state-of-the-art methods for dimensionality reduction, both in synthetic and real datasets with different data types. The proposed model provides more informative low-dimensional representations, outperforms the baseline methods in classification and can naturally handle missing entries. Highlights Inference of the latent space driven by the label value. The DBLR infers different low-dimensional latent distributions depending on the label value, forcing clustering in the latent space in an informative manner, thus capturing the underlying structure of the data. Classification. During inference, the model additionally learns a global vector of weights that allows to make predictions given the low-dimensional representation of the data. Handling missing data. As the DBLR is a probabilistic generative model, it can naturally handle partially missing observations during the training process, including not annotated observations as censored samples. In this article we cover the Missing at Random (MAR) case. Regularization method to handle small datasets. In order to handle small high-dimensional datasets, which usually entail overfitting problems, we introduced an additional regularization mechanism following a drop-outlike strategy that relies in the generative semi-supervised nature of the model. Handling different data types. We have defined and implemented different observation likelihood models that can be used to describe different data types. In particular, we show how to use the DBLR with binary and real-valued features.
Proﬁling intra- and inter-individual differences in child and adolescent brain development

As we move toward population-level developmental neuroscience, understanding intra- and interindividual variability in brain maturation and sources of neurodevelopmental heterogeneity becomes paramount. Large-scale, longitudinal neuroimaging studies have uncovered group-level neurodevelopmental trajectories, and while recent work has begun to untangle intra- and interindividual diﬀerences, they remain largely unclear. Here, we aim to quantify both intra- and inter-individual variability across facets of neurodevelopment from late childhood to early adolescence in the Adolescent Brain Cognitive Development (ABCD) Study, and examine the contributions of age, sex, puberty, sociodemographic factors, and MRI scanner manufacturer to inter-individual variability. Our results provide novel insight into diﬀerences in microstructure development between cortical and subcortical gray matter. We found that an individual’s starting point is related to how their brain changes, across all brain outcomes. Although both sex and pubertal status contributed to inter-individual variability, we found limited support for hypotheses regarding greater male-than-female variability and increases in inter-individual variability throughout puberty. Finally, we uncovered enmeshed contributions of sociodemographics and MRI scanner manufacturers to inter-individual variability in this dataset, due in part to sociodemographic diﬀerences in participants scanned on Siemens, GE, and Philips MRIs. This work highlights pockets of individual variability for future investigation, describes a promising approach for quantifying deviations from normative development, and urges caution in covariate choice for investigators using ABCD Study data.
Genetic load and adaptive potential of a recovered avian species that narrowly avoided extinction

High genetic diversity is often a good predictor of long-term population viability, yet some species persevere despite having low genetic diversity. Here we study the genomic erosion of the Seychelles paradise flycatcher (Terpsiphone corvina), a species that narrowly avoided extinction after having declined to 28 individuals in the 1960s. The species recovered unassisted to over 250 individuals in the 1990s and was downlisted from Critically Endangered to Vulnerable in the IUCN Red List in 2020. By comparing historical, pre-bottleneck (130+ years old) and modern genomes, we uncovered a 10-fold loss of genetic diversity. The genome shows signs of historical inbreeding during the bottleneck in the 1960s, but low levels of recent inbreeding after the demographic recovery. We show that the proportion of severely deleterious mutations has reduced in modern individuals, but mildly deleterious mutations have remained unchanged. Computer simulations suggest that the Seychelles paradise flycatcher avoided extinction and recovered due to its long-term small Ne. This reduced the masked load and made the species more resilient to inbreeding. However, we also show that the chronically small Ne and the severe bottleneck resulted in very low genetic diversity in the modern population. Our simulations show this is likely to reduce the species’ adaptive potential when faced with environmental change, thereby compromising its long-term population viability. In light of rapid global rates of population decline, our work highlights the importance of considering genomic erosion and computer modelling in conservation assessments
Genomic diversity of Streptococcus uberis isolated from clinical mastitis of cattle in selected areas of Bangladesh

Streptococci are the major etiology in mastitis, a cause of huge economic losses in the dairy industries. Streptococcus (S.) agalactiae, S. dysagalactiae and S. uberis are mostly encountered in bovine mastitis; however, data on the diversity and characteristics of Streptococcus in clinical mastitis of cattle in Bangladesh is lacking. Thus, the present study was aimed to determine the diversity and antimicrobial resistance pattern of Streptococcus spp. isolated from clinical mastitis of cattle reared in Bangladesh. A total of 105 milk samples comprising eighty (80) from cattle with clinical mastitis (CCM) and twenty-five (25) from apparently healthy cattle (AHC) in four prominent dairy farms and one dairy community were purposively collected and examined in this study. Milk samples were enriched in Luria Bertani broth (LB) and Streptococcus spp. was isolated on Modified Edwards Medium and identified by 16S rRNA gene sequencing. Among eighty (80) clinical samples, eighteen (18) were positive for Streptococcus spp. while none of the milk from AHC revealed Streptococcus by cultural and molecular examination. Sequencing and phylogenetic analysis identified 55.6%, 33.3%, 5.6% and 5.6% of the Streptococcus isolates as S. uberis, S. agalactiae, S. hyovaginalis and S. urinalis, respectively. Antibiotic sensitivity testing with antimicrobials commonly used to treat clinical mastitis revealed 100%, 100%, and 30% of the S. agalactiae, S. hyovaginalis, and S. uberis as multidrug-resistant, respectively. Molecular characterization through whole genome sequencing of five (5) S. uberis isolates identified at least two novel ST types of S. uberis circulating in the study areas with one ST (4/5 isolates) clustered with the isolates from China, India and Thailand, and the other (1/5) with UK, Ireland and Australia. Pan-genome analysis and phylogeny of the core genome sequences also clustered the isolates into two sub-clusters, indicating the presence of at least two different subtypes of S. uberis in the study area. On virulence profiling, all the isolates of this study were found to harbor at least 35 virulence and putative virulence genes probably associated with intramammary infection (IMI) indicating all the S. uberis isolated in this study as potential pathogen. From the overall findings it was evident that Strepococcus occurring in bovine mastitis are diverse and S. uberis genome carries an array of putative virulence factors which need to be investigated genotypically and phenotypically to identify a specific trait or determinant governing the virulence and fitness of this bacterium. Moreover, Streptococcus isolated in this study carried multidrug resistance which needs careful consideration during the selection of a treatment regimen for mastitis.
Microbial diversity ensures the stability of carbon cycling processes under increasing temperature in model soils

Biodiversity loss and climate change are two of the most alarming threats to ecosystem functioning and stability. These factors are, however, typically investigated separately, overlooking potential interactions between species extinctions and climate change on ecosystems. Here, we evaluated how different temperature regimes impact the relationship between microbial diversity and ecosystem functioning, in terms of temperature sensitivity of carbon (C) cycling functions. We hypothesized that more diverse soil communities promote the stability of C cycling functions under both temperature regimes. We did not observe a ubiquitous response of all C-cycling processes to temperature increases within the distinct community diversities. While growth was stable with increasing temperatures among the diversity levels, respiration rates increased more strongly at low diversity levels than high diversity levels at higher temperatures. Carbon use efficiency, which integrates both growth and respiration, tended to decrease with temperature at lower levels of diversity. Jointly, these results demonstrate the importance of belowground soil community diversity for maintaining C-cycling thermal response under changing climate.