Miracle-dz/UniFAR-FTUs huggingface dataset:
Impaired Cognitive Functioning in Cochlear Implant Recipients Over the Age of 55 Years: A Cross-Sectional Study Using the Repeatable Battery for the Assessment of Neuropsychological Status for Hearing-Impaired Individuals (RBANS-H)

Primary Objective: To compare cognitive functioning among experienced, unilateral cochlear implant (CI) recipients and normal-hearing (NH) controls by means of the Repeatable Battery for the Assessment of Neuropsychological Status for Hearing-impaired individuals (RBANS-H). Methods: Sixty-one post-lingually and bilaterally severely hearing-impaired CI recipients (median age: 71.0, range: 58.3 to 93.9 years) with at least 1 year of CI experience (median: 12.4, range: 1.1 to 18.6 years) and 81 NH control participants (median age: 69.9, range: 50.1 to 87.1 years) took part in this cross-sectional study. The RBANS-H was performed, as well as an audiometric assessment, including best-aided speech audiometry in quiet (monosyllabic words) and in noise (Leuven Intelligibility Sentences test). Results: The RBANS-H performances of the CI recipients (mean: 88.1 ± 14.9) were significantly poorer than the those of the NH participants (mean: 100.5 ± 13.2), with correction of age, sex, and education differences (general linear model: p = 0.001). The mean difference, corrected for the effects of these three demographic factors, was 8.8 (± 2.5) points. Additionally, in both groups, a significant correlation was established between overall cognition and speech perception, both in quiet and in noise, independently of age. Conclusion: Experienced, unilateral CI recipients present subnormal cognitive functioning, beyond the effect of age, sex and education. This has implications for auditory rehabilitation after CI and may highlight the need for additional cognitive rehabilitation in the long term after implantation. Long-term prospective and longitudinal investigations are imperative to improve our understanding of cognitive aging in severely hearing-impaired individuals receiving CIs and its association with CI outcomes.
Attention-Guided Answer Distillation for Machine Reading Comprehension

Despite that current reading comprehension systems have achieved significant advancements, their promising performances are often obtained at the cost of making an ensemble of numerous models. Besides, existing approaches are also vulnerable to adversarial attacks. This paper tackles these problems by leveraging knowledge distillation, which aims to transfer knowledge from an ensemble model to a single model. We first demonstrate that vanilla knowledge distillation applied to answer span prediction is effective for reading comprehension systems. We then propose two novel approaches that not only penalize the prediction on confusing answers but also guide the training with alignment information distilled from the ensemble. Experiments show that our best student model has only a slight drop of 0.4% F1 on the SQuAD test set compared to the ensemble teacher, while running 12x faster during inference. It even outperforms the teacher on adversarial SQuAD datasets and NarrativeQA benchmark.
Keyword Search on RDF Graphs

The Resource Description Framework (RDF) is a family of speci cations developed and supported by theW3C consortium to represent information in the Web1. During the last years, RDF has gained popularity in many domains such as medicine and cultural heritage as a representation format for heterogeneous structured data on the Web [2]. RDF graphs can be interrogated by queries expressed with the SPARQL language. To write queries in this language can become very di cult. Users are required to know the language and the structure of the underlying dataset in order to write correct queries. Thus, the need for a system of keyword search for these graphs. Keyword search permits users to express their information need via a query in natural language, in a Google-like fashion. Keyword search over large knowledge bases can become di cult both in therms of memory and time required to answer to a single query. In this abstract, we discuss the experience of designing and implementing keyword search algorithms over big RDF databases.
Responses of birds to large-scale wildfires in southern California

374 Abstract: In 2002 and 2003, ~4000 km2 of southern California burned in the region’s largest fires in over a century. Within 1–2 years post-fire, we established 81 bird-survey routes (totaling over 200 km) within the perimeters of the Pines, Cedar, and Coyote fires, and in nearby unburned habitat to serve as controls. We surveyed these routes repeatedly during both spring/ summer and winter for 5 years, with the objective of comparing species by pattern of response and identifying the species most strongly affected. Sampled habitat was primarily chaparral with isolated stands of oak woodland and coniferous forest. To quantify species’ responses, we used data from the San Diego County Bird Atlas (1997–2002) as a pre-fire baseline, and used mixed-effects regression models to assess overall response to fire and post-fire trends. Responses and trends were diverse: in spring/summer, 24 species responded positively, 14 were neutral, and 43 responded negatively. In winter, 8 were positive, 18 neutral, and 34 negative. Some positive species (e.g., Lazuli Bunting, Passerina amoena) were strong “fire-followers,” exploiting recently burned habitat, while others (e.g., Black-chinned Sparrow, Spizella atrogularis) increased mostly at higher elevations where forest was converted to chaparral. Neutral or “fire-resilient” species were either indifferent to fire (e.g., Ash-throated Flycatcher, Myiarchus cinerascens) or increased sharply after an initially negative response (e.g., Spotted Towhee, Pipilo maculatus). Among the negative or “fire-sensitive” species, recovery was often slow (e.g., California Thrasher, Toxostoma redivivum), and some continued to decline over time (e.g., Pygmy Nuthatch, Sitta pygmaea). By comparison with the pre-fire distribution as recorded in the atlas, the Rock Wren (Salpinctes obsoletus) was the strongest post-fire colonizer, while the Hutton’s Vireo (Vireo huttoni) was the species most reduced. Small isolated breeding populations of the Red-breasted Sapsucker (Sphyrapicus ruber), Red-breasted Nuthatch (Sitta canadensis), Hermit Thrush (Catharus guttatus), Fox Sparrow (Passerella iliaca), and Goldencrowned Kinglet (Regulus satrapa) were eliminated from the Cuyamaca Mountains for at least the first 5 years after the fire. Annual rainfall during the study varied widely, slowing recovery in dry years. Variation in numbers of many species, especially granivorous winter visitors, paralleled variation in annual rainfall. If the area of southern California that burns annually increases as predicted, fire-followers should benefit, while species that are rare, patchily distributed, and dependent on later stages of succession will be most at risk. If the fires are a symptom of a shift toward a drier climate, they may cause a long-term or permanent reduction in numbers and ranges of fire-sensitive species.
Social media privacy concerns: trusting beliefs and risk beliefs

Purpose The purpose of this paper is to build a research model that examines social media privacy concerns (SMPC) in relation to users’ trusting beliefs and risk beliefs. Design/methodology/approach An instrument with eight constructs (SMPC: collection, SMPC: secondary usage, SMPC: errors, SMPC: improper access, SMPC: control, SMPC: awareness, trusting beliefs and risk beliefs) was developed and administered to subjects from a mid-sized university in the USA. Collected data were analyzed using partial least square structural equation modeling. Findings The results showed that three of the six SMPC (i.e. secondary usage, improper access and awareness) were negatively and significantly associated with users’ trusting beliefs. In addition, three of the six SMPC (i.e. collection, errors and improper access) were positively and significantly associated with users’ risk beliefs. Practical implications Practical implications were aimed at the social media sites to design simple and straightforward privacy policy statements that are easy to understand; to safeguard users’ online privacy behaviors; and to develop mechanisms to protect personal information. Originality/value This study enhances the literature by contributing to a generalized knowledge of SMPC of users as they relate to their trusting beliefs and risk beliefs.
The production effect and the generation effect improve memory in picture naming

ABSTRACT The production effect (better memory for words read aloud than words read silently) and the picture superiority effect (better memory for pictures than words) both improve item memory in a picture naming task (Fawcett, J. M., Quinlan, C. K., & Taylor, T. L. (2012). Interplay of the production and picture superiority effects: A signal detection analysis. Memory (Hove, England), 20(7), 655–666. doi:10.1080/09658211.2012. 693510). Because picture naming requires coming up with an appropriate label, the generation effect (better memory for generated than read words) may contribute to the latter effect. In two forced-choice memory experiments, we tested the role of generation in a picture naming task on later recognition memory. In Experiment 1, participants named pictures silently or aloud with the correct name or an unreadable label superimposed. We observed a generation effect, a production effect, and an interaction between the two. In Experiment 2, unreliable labels were included to ensure full picture processing in all conditions. In this experiment, we observed a production and a generation effect but no interaction, implying the effects are dissociable. This research demonstrates the separable roles of generation and production in picture naming and their impact on memory. As such, it informs the link between memory and language production and has implications for memory asymmetries between language production and comprehension.
Determining the Influence of Image-based Cues on Human Skin Gloss Perception

We explore the inﬂuence of surface and subsurface reﬂec-tions on skin gloss perception. We rely on multimodal photography to separate the surface and subsurface reﬂection images. Since the original data consists of a limited number of images (25 subjects, front and side view, before and after skin cleansing), we apply different transformations to surface and subsurface reﬂec-tion images, in order to generate a broad range of appearance of skin images. We conducted two empirical studies with the expanded set of data, at both the macro-scale level (whole face) and the meso-scale level (local skin patch). We found that increasing the contrast of surface reﬂection results in higher gloss perception, while a decrease in the amount of subsurface reﬂection (lower average lightness, darker complexion) results in higher gloss perception; however, the differential effect of subsurface re-ﬂection on gloss diminishes as the average lightness becomes very low. We also computed the statistics of the two reﬂection images and found their effects (sometimes opposite for the corresponding statistic) on gloss perception. We then learned a regression model based on the concatenation of statistics from the surface and sub-surface reﬂection images to predict relative gloss differences. Our results indicate that using the statistics from both modalities provides more consistent correlation with human judgments than us-ing only the statistics from a single modality.
GraphDBLP Released: Querying the Computer Scientists Network as a Graph

In this paper we introduce GraphDBLP, a tool that models the DBLP bibliography as a graph, and enriches the DBLP data through semantic keyword similarities computed via word-embedding. GraphDBLP has been implemented on top of the Neo4j graph-database, and it can be queried through the Cypher query language. We also provide three meaningful queries for exploring the DBLP community to (i) investigate author profiles by analysing their publication records; (ii) identify the most prolific authors on a given topic,and (iii) perform social network analyses over the whole community. GraphDBLP is available on Github. To date, it contains 5+ million nodes and 24+ million relationships, enabling users to explore the DBLP data by referencing more than 3.3 million publications, 1.7 million authors and more than 5 thousand publication venues. Thanks to the use of word-embedding, more than 7.5 thousand keywords and related similarity values were collected.
Modulation of inflammatory platelet-activating factor (PAF) receptor by the acyl analogue of PAF

Platelet-activating factor (PAF) is a potent inflammatory mediator that exerts its actions via the single PAF receptor (PAF-R). Cells that biosynthesize alkyl-PAF also make abundant amounts of the less potent PAF analogue acyl-PAF, which competes for PAF-R. Both PAF species are degraded by the plasma form of PAF acetylhydrolase (PAF-AH). We examined whether cogenerated acyl-PAF protects alkyl-PAF from systemic degradation by acting as a sacrificial substrate to enhance inflammatory stimulation or as an inhibitor to dampen PAF-R signaling. In ex vivo experiments both PAF species are prothrombotic in isolation, but acyl-PAF reduced the alkyl-PAF-induced stimulation of human platelets that express canonical PAF-R. In Swiss albino mice, alkyl-PAF causes sudden death, but this effect can also be suppressed by simultaneously administering boluses of acyl-PAF. When PAF-AH levels were incrementally elevated, the protective effect of acyl-PAF on alkyl-PAF-induced death was serially decreased. We conclude that, although acyl-PAF in isolation is mildly proinflammatory, in a pathophysiological setting abundant acyl-PAF suppresses the action of alkyl-PAF. These studies provide evidence for a previously unrecognized role for acyl-PAF as an inflammatory set-point modulator that regulates both PAF-R signaling and hydrolysis.
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape Recognition

3D object recognition has attracted wide research attention in the field of multimedia and computer vision. With the recent proliferation of deep learning, various deep models with different representations have achieved the state-of-the-art performance. Among them, point cloud and multi-view based 3D shape representations are promising recently, and their corresponding deep models have shown significant performance on 3D shape recognition. However, there is little effort concentrating point cloud data and multi-view data for 3D shape representation, which is, in our consideration, beneficial and compensated to each other. In this paper, we propose the Point-View Network (PVNet), the first framework integrating both the point cloud and the multi-view data towards joint 3D shape recognition. More specifically, an embedding attention fusion scheme is proposed that could employ high-level features from the multi-view data to model the intrinsic correlation and discriminability of different structure features from the point cloud data. In particular, the discriminative descriptions are quantified and leveraged as the soft attention mask to further refine the structure feature of the 3D shape. We have evaluated the proposed method on the ModelNet40 dataset for 3D shape classification and retrieval tasks. Experimental results and comparisons with state-of-the-art methods demonstrate that our framework can achieve superior performance.
Comparative study of bone marrow and blood plasma levels of IL-2 in aplastic anaemia and their relationship with disease severity

ABSTRACT Objectives: Interleukin-2 (alias: IL-2, TCGF, Lymphokine), a type of interleukin, is also a potent signalling molecule in the signalling cascade of the immune-mediated activation of T Lymphocytes leading to the destruction of haematopoietic stem cell (HSC) which is the basis of acquired aplastic anaemia (AAA). The objective was to study the association of IL-2 in the bone marrow plasma (BMP) and peripheral blood plasma (PBP) in AAA patients. Methods: A total of 52 BMP and PBP-paired samples (both from the same patients) was collected from the confirmed AAA patients and 10 healthy individuals. The level of IL-2 was measured by the quantitative enzyme-linked immunosorbent assay (ELISA). The Mann–Whitney U test was used for statistical analysis. Results: Significantly increased level of IL-2 was observed in the BMP than PBP of AAA patients. The level of IL-2 in PBP and BMP was found to be very low in the control cases. Considerably increased levels of IL-2 were found in the PBP and BMP of AAA patients as compared to controls (48.54 ± 21.89 vs. 1.99 ± 1.25 p-value < 0.00001) and (75.33 ± 41.9 vs. 3.12 ± 1.82; p-value < 0.00001) respectively. Among these patients, the IL-2 levels were higher in patients with Very Severe Aplastic Anaemia (VSAA) and Severe Aplastic Anaemia (SAA) than those with Non-severe Aplastic Anaemia (NSAA) in the PBP (65.6 ± 23.61 vs. 31.72 ± 7.64; p-value 0.00338) and (45.37 ± 16.25 vs. 31.72 ± 7.64; p-value 0.01468) respectively. Again the IL-2 levels were higher in patients with VSAA and SAA than those with NSAA in the BMP (115.01 ± 38.91 vs. 38.32 ± 19.49; p-value < 0.00001) and (66.44 ± 23.34 vs. 38.32 ± 19.49; p-value 0.0006). The IL-2 level was higher in VSAA than SAA in PBP (65.6 ± 23.61vs. 45.37 ± 16.25; p-value 0.0114) and BMP (115.01 ± 38.91 vs. 66.44 ± 23.34; p-value 0.00044). Conclusion: This study emphasized on the bone marrow and blood plasma levels of IL-2 in aplastic anaemia and their relationship with disease severity. The results indicate towards the fact that IL-2 may have an important association with the marrow failure of AAA patients and thus can help in disease development. Further study is necessary for better understanding.
Grafting antibiofilm polymer hydrogel film onto catheter by SARA SI-ATRP

Abstract Catheters are widely used and play an important role in medicine. However, catheter-associated infection is prevalent even under stringent sterile conditions. Biofilms are formed when bacteria populate the surfaces of catheters. This makes the biofilm resistant to antibiotics. Hence, it is imperative for there to be an inherently antifouling and anti-bacterial catheter to mitigate the formation of biofilm. This paper aims to outline the synthesis of non-leachable anti-biofilm and anti-bacterial cationic film coatings through direct polymerization using supplemental activator and reducing agent surface initiated atom transfer radical polymerization (SARA SI-ATRP). Three crosslinked cationic coatings comprising of Diallyl dimethyl ammonium chloride (DADMAC), or ε-poly-L-lysine HCl methacrylic acid (EPL-MA) together with a crosslinker (polyethylene glycol dimethacrylate, PEGDMA) were investigated. These non-leachable covalently linked coatings with DADMAC can achieve more than 2 log reduction (99.0%) with Methicillin-resistant Staphylococcus aureus (MRSA) and 1.25 log reduction (94.4%) with Vancomycin resistant Enterococcus (VRE) in in vitro studies.
Physical model of facial tissue and muscle articulation derived from computer tomography data

A facial tissue model, articulated by synthetic muscles, provides a tool for observing, analyzing, and predicting soft tissue mobility on the face. A geometric model of facial tissue extracted from CT data improves the skin tissue simulation by using accurate skin tissue depths. This paper suggests that the ability to control the model resolution, muscle placement and activity requires an integrated modeling and animation system.
Outcomes of an individual counselling programme in Grozny, Chechnya: a randomised controlled study

Objectives To evaluate the effectiveness of individual counselling on functioning of clients participating in a mental health intervention in a humanitarian setting. Design Randomised controlled trial. Setting Mental health programme implemented by Médecins Sans Frontières in Grozny, Republic of Chechnya. Participants 168 eligible clients were randomly assigned to the intervention and waitlisted (2 months) arms between November 2014 and February 2015. Intervention Individual counselling sessions. Main outcome measures Change in functioning was measured using the Short Form 6 (SF6) and gender-specific locally adapted Chechen functioning instruments in the intervention group at the end of counselling and the waitlisted group after their waitlisted period. Unadjusted differences in gain scores (DGSs) between intervention and waitlisted groups were calculated with effect size (Cohen’s d) for both tools. Linear regression compared the mean DGS in both groups. Results The intervention group (n=78) improved compared with waitlisted controls (n=80) on the SF6 measures with moderate to large effect sizes: general health (DGS 12.14, d=0.52), body pain (DGS 10.26, d=0.35), social support (DGS 16.07, d=0.69) and emotional functioning (DGS 16.87, d=0.91). Similar improvement was seen using the Chechen functioning instrument score (female DGS −0.33, d=0.55; male DGS −0.40, d=0.99). Adjusted analysis showed significant improvement (p<0.05) in the intervention group for all SF6 measures and for the Chechen functioning instrument score in women but not men (p=0.07). Conclusions Individual counselling significantly improved participants’ ability to function in the intervention group compared with the waitlisted group. Further research is needed to determine whether similar positive results can be shown in other settings and further exploring the impact in male clients’ population. Trial registration number NTR4689.
Orchestration and Control in Software-Defined 5G Networks: Research Challenges

The fifth generation (5G) of cellular networks promises to be a major step in the evolution of wireless technology. 5G is planned to be used in a very broad set of application scenarios. These scenarios have strict heterogeneous requirements that will be accomplished by enhancements on the radio access network and a collection of innovative wireless technologies. Softwarization technologies, such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV), will play a key role in integrating these different technologies. Network slicing emerges as a cost-efficient solution for the implementation of the diverse 5G requirements and verticals. The 5G radio access and core networks will be based on a SDN/NFV infrastructure, which will be able to orchestrate the resources and control the network in order to efficiently and flexibly and with scalability provide network services. In this paper, we present the up-to-date status of the software-defined 5G radio access and core networks and a broad range of future research challenges on the orchestration and control aspects.
AN-Aided Transmit Beamforming Design for Secured Cognitive Radio Networks with SWIPT

We investigate multiple-input single-output secured cognitive radio networks relying on simultaneous wireless information and power transfer (SWIPT), where a multiantenna secondary transmitter sends confidential information to multiple single-antenna secondary users (SUs) in the presence of multiple single-antenna primary users (PUs) and multiple energy-harvesting receivers (ERs). In order to improve the security of secondary networks, we use the artificial noise (AN) to mask the transmit beamforming. Optimization design of AN-aided transmit beamforming is studied, where the transmit power of the information signal is minimized subject to the secrecy rate constraint, the harvested energy constraint, and the total transmit power. Based on a successive convex approximation (SCA) method, we propose an iterative algorithm which reformulates the original problem as a convex problem under the perfect channel state information (CSI) case. Also, we give the convergence of the SCA-based iterative algorithm. In addition, we extend the original problem to the imperfect CSI case with deterministic channel uncertainties. Then, we study the robust design problem for the case with norm-bounded channel errors. Also, a robust SCA-based iterative algorithm is proposed by adopting the S-Procedure. Simulation results are presented to validate the performance of the proposed algorithms.