Miracle-dz/UniFAR-FTUs huggingface dataset:
HEARING CHILDREN: EVIDENCE FROM SYMBOLIC

Between 1980 and 2010, several lines of research consistently provided evidence that deaf and hard of hearing children have a delay of 2.0 to 3.5 years compared to hearing children, as shown by mathematics achievement tests (Frosted, 1996; see Nunes, 2004 for a review). In 2000, using the Stanford Achievement Test, Traxler showed that deaf and hard of hearing children obtained worse scores than hearing children. In a study with a group of 10 profoundly deaf students, Zarfaty, Nunes, and Bryant (2004), referencing Traxler, found that the numerical skills growth curves of these children were flatter than those of hearing students. These results suggested that the deaf students had only partially mastered the knowledge and skills needed to do math correctly. Delays in mathematical performance appear and remain relatively constant when findings from standardized achievement tests are applied (Traxler, 2000). Kritzer (2009) reported mathematical difficulties among deaf and hard of hearing children even prior to formal schooling, at ages 4–6 years. Studies addressing speEAF CHILDREN usually achieve lower scores on numerical tasks than normally hearing peers. Explanations for mathematical disabilities in hearing children are based on quantity representation deficits (Geary, 1994) or on deficits in accessing these representations (Rousselle & Noël, 2008). The present study aimed to verify, by means of symbolic (Arabic digits) and nonsymbolic (dot constellations and hands) magnitude comparison tasks, whether deaf children show deficits in representations or in accessing numerical representations. The study participants were 10 prelocutive deaf children and 10 normally hearing children. Numerical distance and magnitude were manipulated. Response time (RT) analysis showed similar magnitude and distance effects in both groups on the 3 tasks. However, slower RTs were observed among the deaf participants on the symbolic task alone. These results suggest that although both groups’ quantity representations were similar, the deaf group experienced a delay in accessing representations from symbolic codes. JOSÉ MIGUEL RODRÍGUEZSANTOS, MARINA CALLEJA, JAVIER GARCÍA-ORZA, MAURICIO IZA, AND JESÚS DAMAS
TO DEAF CHILDREN WHO SIGN : A RESPONSE TO WILLIAMS

In her invited essay on the promotion of vocabulary learning in young children with hearing loss (published in the Winter 2012 issue of the Annals, Williams (2012) takes an optimistic stance, recommending that seven specific classroom vocabulary interventions with storybook reading that have been used effectively with hearing children be adapted to meet the needs of deaf and hard of hearing children. Williams notes that these interventions, which she describes in her article, have yielded gains in the vocabulary learning of hearing children. Each intervention takes a whole language approach. It begins with a shared book-reading or read-aloud storybook session led by the teacher. Companion activities employ instruction that emphasizes both meaning and code. These activities include storybook reading with dialogic or interactive approaches (Lonigan & Whitehurst, 1998); explicit vocabulary instruction (Lonigan & Whitehurst, 1998); the use of props and language extension activities (Wasik & Bond, 2001); embedded “rich instruction” of specific vocabulary (Beck & McKeown, 2007); extended instruction of vocabulary before, during, COMMENTARY on Williams’s (2012) invited article on the use of adapted vocabulary learning interventions focuses on three areas: (a) Vocabulary interventions with storybook reading originally designed for hearing children can be adapted for deaf children. (b) Teachers are invited to reflect on how the read-aloud process in English differs from the read-aloud process in sign. (b) Teachers are asked to consider adding drawing and writing activities to reading lessons to show young deaf readers how reading and writing are reciprocal processes. The emergent literacy theory is used, as it informs and drives instructional vocabulary teaching practices for deaf children in preschool, kindergarten, and first grade. The emergent literacy theory broadly captures cognitive, social, perceptual, and linguistic understandings of how young signing deaf children acquire both English word recognition abilities and vocabulary knowledge, among other important prereading concepts. JEAN F. ANDREWS
Causes, effects and mitigation of unreliable healthcare supplies

Abstract This study investigates the means by which hospitals can improve the reliability of their medical supply value streams. Field research involving pharmacy supplies in eight Australasian public sector hospitals utilised a rigorous, multi-method data collection procedure based around the uncertainty circle model. Value stream maturity, performance inhibitors and pathways to effective improvement are explored. The high levels of value stream uncertainty detected are commonly the result of process immaturity and poor inter-functional integration. Chief among the common root causes is failure by the executive to acknowledge the strategic value of medical supplies management, which ultimately leads to higher materials cost and increased risk of a medical mishap. The study demonstrates how managers can use systems thinking and a context-free performance benchmark to identify effective interventions and potentially transferable best practices.
03 Mohan

Interest rates play an important role, not only in attracting capital inflow, but also in macroeconomic stabilization and determining asset prices. Given the interdependent nature of member countries of the Association of Southeast Asian Nations (ASEAN), it is crucial to examine whether there is any evidence of co-movement of short-term domestic interest rates within these economies. In addition, because of their significant economic influence in the region, we explore the Granger causality with China and India in determining their impact on interest rate movement in ASEAN-5 economies. We find evidence of cointegration; there is comovement among the ASEAN interest rates. Further, based on the causality test, we find that China exerts more influence on the direction of the interest rates in the region.
Insights into the Complexity of a Dormant Mycobacterium tuberculosis Cluster Once Transmission Is Resumed

The precise study of the dynamics of tuberculosis transmission in socio-epidemiologically complex scenarios may require more thorough analysis than the standard molecular epidemiology strategies. Our study illustrates the epidemiological and bacteriological complexity present in a transmission cluster in a challenging epidemiological setting with a high proportion of migrant cases. ABSTRACT Genotyping tools help identify the complexity in Mycobacterium tuberculosis transmission clusters. We carried out a thorough analysis of the epidemiological and bacteriological complexity of a cluster in Almería, Spain. The cluster, initially associated with Moroccan migrants and with no secondary cases identified in 4 years, then reappeared in Spanish-born individuals. In one case, two Mycobacterium tuberculosis clonal variants were identified. We reanalyzed the cluster, supported by the characterization of multiple cultured isolates and respiratory specimens, whole-genome sequencing, and epidemiological case interviews. Our findings showed that the cluster, which was initially thought to have restarted activity with just a single case harboring a small degree of within-host diversity, was in fact currently growing due to coincidental reactivation of past exposures, with clonal diversity transmitted throughout the cluster. In one case, within-host diversity was amplified, probably due to prolonged diagnostic delay. IMPORTANCE The precise study of the dynamics of tuberculosis transmission in socio-epidemiologically complex scenarios may require more thorough analysis than the standard molecular epidemiology strategies. Our study illustrates the epidemiological and bacteriological complexity present in a transmission cluster in a challenging epidemiological setting with a high proportion of migrant cases. The combination of whole-genome sequencing, refined and refocused epidemiological interviews, and in-depth analysis of the bacterial composition of sputa and cultured isolates was crucial in order to correctly reinterpret the true nature of this cluster. Our global approach allowed us to reinterpret correctly the unnoticed epidemiological and bacteriological complexity involved in the Mycobacterium tuberculosis transmission event under study, which had been overlooked by the usual molecular epidemiology approaches.
Features of Brass Processing with Powerful Ultraviolet Lasers of Nanosecond Duration

We investigated the process of laser heat treatment of polished brass samples (36% zinc, containing a small amount of lead, which does not dissolve in the alloy and is in the form of inclusions, having micron and submicron size) by impacting to a series of 25 - 30 ultraviolet (UV) pulses of a Nd:YAG laser (third harmonic, wavelength λ = 355 nm, duration τ = 10 ns, pulse repetition rate f = 10 Hz, pulse energy density ~ 0.15 - 1.0 J/cm2) in the stationary spot mode. Copper and its alloys absorb up to 90% of the energy of this laser. It is found that the relaxation of the absorbed energy of laser radiation in the metal occurs nonuniformly. Defects in the metal structure such as grain boundaries and lead inclusions are visualized. Traces of crystallographic sliding appear inside some grains. With an increase in the number of impacting impulses, accumulation of damage is observed. A further increase in the radiation energy density leads to an aggravation of the observed phenomena.
Unfolding the dimensionality structure of social networks in ideological embeddings

Traditionally, public opinion on different issues of public debate has been studied through polls and surveys. Recent advancements in network ideological scaling methods, however, have shown that digital behavioral traces in social media platforms can be used to mine opinions at a massive scale. This has yet to be shown to work beyond one-dimensional opinion scales, which are best suited for two-party systems and binary social divides such as those observed in the US. In this article, we use multidimensional ideological scaling for coupled with referential attitudinal data for some nodes. We show that opinions can be mined in a multitude of issues: from social networks, embedding them in ideological spaces where dimensions stand for indicators of positive and negative opinions, towards issues of public debate. This method does not require text analysis and is thus language independent. We illustrate this approach on the Twitter follower network of French users leveraging political survey data.
Deterministic influence maximization approach for sequential active marketing

The influence maximization problem aims to find the best seeding set of nodes in a network to increase the influence spread, under various information diffusion models. Recent advances have shown the importance of the timing of the seeding and introduced the sequential seeding approach, determining a step-by-step cascade of activations. Our study explores a novel Deterministic Influence Maximization Approach (DIMA) for time-based sequential seeding dynamics in a threshold-based model. We examine the problem characteristics and formulate solutions optimizing a scheduled sequential seeding strategy. Based on a set of empirical simulations we demonstrate the properties of the deterministic sequential problem, incorporate three different mathematical programming formulations and provide an initial benchmark for optimization techniques.
Evaluation of a Marine Dredged Sediment as Raw Material Compared to Volcanic Scoria for the Development of Lime-Pozzolan Eco-Binders

In the context of global warming, the built environment offers relevant opportunities to reduce GHG emissions that underlie climate change. In particular, this can be achieved with the development of low-embodied energy building materials such as bio-based concretes. Hemp concrete has been the subject of many investigations in the field of non-load bearing infill walls in France since the early 1990s. In addition to hygrothermal performances, the use of crop by-products definitely helps to limit the carbon footprint. Hemp concretes are often produced by mixing the plant aggregates with lime-based binders. The latter have many benefits among which the water vapor permeability. However, CO2 emissions due to the decarbonation of limestone for the production of lime largely contribute to the overall environmental balance of these materials. The use of natural pozzolans (volcanic scoria) combined with hydrated lime goes back to the Greco-Roman period and reduces carbon emissions. Nonetheless, it does not necessarily meet the issue related to the depletion of granular natural resources. Hence, this study deals with the design of a new low-carbon binder based on marine dredged sediment seen as an alternative strategic granular resource that can be considered renewable. The sediment comes from the Port of Dunkirk in the North of France and is mainly composed of silt and quartz sand. It was finely ground and compared to a lowly reactive basaltic pozzolan. Lime-pozzolan pastes were prepared and stored in a moist environment under room (20°C) and high temperature (50°C). The hardening kinetics of pastes was followed through mineralogical studies (TGA, XRD) and compressive strength development. The results showed that the hardening of pastes including the marine sediment was suitable in the case of samples stored at 50°C and make it possible to use such a binder for precast bio-based concretes.
Collateral cleavage of 28s rRNA by RfxCas13d causes death of mice

The CRISPR-Cas13 system is an RNA-guided RNA-targeting system, and has been widely used in transcriptome engineering with potentially important clinical applications. However, it is still controversial whether Cas13 exhibits collateral activity in mammalian cells. Here, we found that knocking down gene expression using RfxCas13d in the adult brain neurons caused death of mice, which was not resulted from the loss of target gene function or off-target effects. Mechanistically, we showed that RfxCas13d exhibited collateral activity in mammalian cells, which is positively correlated with the abundance of target RNA. The collateral activity of RfxCas13d could cleave 28s rRNA into two fragments, leading to translation attenuation and activation of the ZAKα-JNK/p38-immediate early gene (IEG) pathway. These results provide new mechanistic insights into the collateral activity of RfxCas13d and warn that the biosafety of CRISPR-Cas13 system needs further evaluation before applying it to clinical treatments.
Automatic grading of cervical biopsies by combining full and self-supervision

In computational pathology, predictive models from Whole Slide Images (WSI) mostly rely on Multiple Instance Learning (MIL), where the WSI are represented as a bag of tiles, each of which is encoded by a Neural Network (NN). Slide-level predictions are then achieved by building models on the agglomeration of these tile encodings. The tile encoding strategy thus plays a key role for such models. Current approaches include the use of encodings trained on unrelated data sources, full supervision or self-supervision. While self-supervised learning (SSL) exploits unlabeled data, it often requires large computational resources to train. On the other end of the spectrum, fully-supervised methods make use of valuable prior knowledge about the data but involve a costly amount of expert time. This paper proposes a framework to reconcile SSL and full supervision, showing that a combination of both provides efficient encodings, both in terms of performance and in terms of biological interpretability. On a recently organized challenge on grading Cervical Biopsies, we show that our mixed supervision scheme reaches high performance (weighted accuracy (WA): 0.945), outperforming both SSL (WA: 0.927) and transfer learning from ImageNet (WA: 0.877). We further shed light upon the internal representations that trigger classification results, providing a method to reveal relevant phenotypic patterns for grading cervical biopsies. We expect that the combination of full and self-supervision is an interesting strategy for many tasks in computational pathology and will be widely adopted by the field.
Impact of Biobased Surfactants on Hygrothermal Behaviour of Gypsum Foams

Reduce the impact of the building sector has become a key point of sustainable development. The production of lightweight materials for the building industry is therefore a must. To produce such materials, foaming is a process commonly used to trap air bubbles and achieve a range of low densities. A sufficient low thermal conductivity and an acceptable ability to regulate humidity variations in order to limit overall energy consumption are the sought properties. In this study, a direct foaming method is applied to formulate gypsum foams using a commercial Plaster and two biobased foaming agents based on proteins. An anionic surfactant (α-olefin sulphonate sodium salt) is used as a reference surfactant. Varying the mixing time, protein content and water content, gypsum foams were produced. The foam volume is measured continuously during the mixing step and the foam homogeneity is controlled. The densities of fresh foams and of the hardened foams are used to identify the links between formulation and foams properties. Gypsum foam specimens with different densities ranging from 300 to 750 kg/m3 are produced. The thermal conductivity and the Moisture Buffer Value measurements are performed. Such properties appear directly linked to the porosity and pore connection of the foams. The obtained results highlight the contribution of biobased surfactant to the performance of gypsum foams.
Physical, Thermal and Microstructural Characterization of Earth Mortars Stabilized with Incorporating Air Additive

In recent years, the search for non-conventional materials has intensified, aiming to reduce environmental impacts in the civil construction sector as a strategy for more sustainable development. Among these materials, earth mortars are a promising option, as they have technological, economic, and environmental advantages. Due to the absence of literary data on the use of air-incorporating additives (AEA) in earth mortars, the objective of this article is to verify the influence of the incorporation of AEA (0,10, 20, and 40% of the total volume of the mixture) in the mechanical properties (compression strength at 28 days), physical (total water absorption by immersion), thermal, and microstructural (scanning electron microscopy) of the referred mortars. The study was carried out in a stabilized earth mortar, with a 1:3 mass mix proportion (binder: aggregate). The raw materials used were constituted by binders (cement, hydrated lime, fly ash, metakaolinite), aggregates (sand, a coarse fraction of the soil), additives (AEA, calcium chloride, superplasticizer), and water. The water-binder material ratio (a / bm) was fixed at 0.65, and the consumption of binder and aggregate was 461.71 and 1385.12 kg, respectively, per m3 of the mixture. The tests demonstrated that the incorporation of the additive influenced the behavior under compression (strength and stiffness reduction), thermal performance (conductivity reduction), and physical behavior (absorption and voids index´s increases) compared to the mixture without AEA. From the analysis of the results, it was found that the incorporation of air in the mortars led to an increase in porosity, directly influencing the thermal insulation capacity, measured by thermal conductivity. Microstructure changes were observed through SEM images, corroborating the influence of the AEA. Under compression loads, the stiffness reduction decreases the risk of eventual cracking, however, the reduction in strength should be controlled to meet normative limits.
Adversarially Robust Imitation Learning

: Modern imitation learning (IL) utilizes deep neural networks (DNNs) as function approximators to mimic the policy of the expert demonstrations. However, DNNs can be easily fooled by subtle noise added to the input, which is even non-detectable by humans. This makes the learned agent vulnerable to attacks, especially in IL where agents can struggle to recover from the errors. In such light, we propose a sound Adversarially Robust Imitation Learning (ARIL) method. In our setting, an agent and an adversary are trained alternatively. The former with adversarially attacked input at each timestep mimics the behavior of an online expert and the latter learns to add perturbations on the states by forcing the learned agent to fail on choosing the right decisions. We theoretically prove that ARIL can achieve adversarial robustness and evaluate ARIL on multiple benchmarks from DM Control Suite. The result reveals that our method (ARIL) achieves better robustness compare with other imitation learning methods under both sensory attack and physical attack.
The Role of Personality in Prediction of Satisfaction With Life in Recreational Athletes During the First Wave of Pandemic Covid-19

The aim of this research is to contribute to the understanding of the concept of satisfaction with life by determining the relationship between personality traits and the subjective experience of satisfaction with life in students—recreational athletes. This research is based on the biological theory of personality by Hans Eysenck and it attempts to offer explanations of a possible change in satisfaction with life in the period of great social deprivation caused by the Covid-19 pandemic. The sample of subjects consisted of 120 undergraduate students (N = 120) of all years and both sexes, 55 (45.8%) males and 65 (54.2%) females, at the Faculty of Sport and Physical Education, the University of Nis. The average age of the subjects was 23.63 years (SD = 2.070). Eysenck's personality questionnaire (Eysenck Personality Questionnaire, EPQ: Eysenck et al., 1885, adapted and translated by Šipka, 1985) was used for the operationalization of personality structure. The SWLS scale (Satisfaction With Life Scale, Diener et al., 1985) was used for estimating satisfaction with life. A significant regression model, which explains 11% of variance in the subjective experience of satisfaction with life in recreational athletes, was obtained. In the model, extraversion stands out as a significant predictor from the group of personality traits (β = 0.279). Neuroticism (β = −0.160) and psychoticism (β = −0.122) did not prove to be significant predictors of satisfaction with life in the structural model regardless of there being a significant negative correlation between neuroticism and satisfaction with life. The more extraverted participants had a keener subjective sense of satisfaction with life.