Miracle-dz/UniFAR-FTUs huggingface dataset:
Can Autism be Detected at 18 Months?

Autism is currently detected only at about three years of age. This study aimed to establish if detection of autism was possible at 18 months of age. We screened 41 18–month-old toddlers who were at high genetic risk for developing autism, and 50 randomly selected 18–month-olds, using a new instrument, the CHAT, administered by GPs or health visitors. More than 80% of the randomly selected 18–month-old toddlers passed on all items, and none failed on more than one of pretend play, protodeclarative pointing, joint-attention, social interest, and social play. Four children in the high-risk group failed on two or more of these five key types of behaviour. At follow-up at 30 months of age, the 87 children who had passed four or more of these key types of behaviour at 18 months of age had continued to develop normally. The four toddlers who had failed on two or more of these key types of behaviour at 18 months received a diagnosis of autism by 30 months.
Evaluation of a Real‐Time PCR Assay to Detect Coxiella burnetii

Abstract: We evaluated real‐time PCR assays for the detection of C. burnetii which targets sequences that are present either in one (icd) or in several copies (transposase of IS1111a) on the chromosome. The assays are highly sensitive, with reproducible detection limits of approximately 10 copies per reaction, at least 100 times more sensitive than capture ELISA, when performed on infected placenta material and specific for C. burnetii. The numbers of IS1111 elements in the genomes of 75 C. burnetii isolates were quantified by real‐time PCR and proved to be highly variable.
Admissible Heuristics for Optimal Planning

HSP and HSPr are two recent planners that search the state-space using an heuristic function extracted from Strips encodings. HSP does a forward search from the initial state recomputing the heuristic in every state, while HSPr does a regression search from the goal computing a suitable representation of the heuristic only once. Both planners have shown good performance, often producing solutions that are competitive in time and number of actions with the solutions found by Graphplan and SAT planners. HSP and HSPr. however, are not optimal planners. This is because the heuristic function is not admissible and the search algorithms are not optimal. In this paper we address this problem. We formulate a new admissible heuristic for planning, use it to guide an IDA* search, and empirically evaluate the resulting optimal planner over a number of domains. The main contribution is the idea underlying the heuristic that yields not one but a whole family of polynomial and admissible heuristics that trade accuracy for efficiency. The formulation is general and sheds some light on the heuristics used in HSP and Graphplan, and their relation. It exploits the factored (Strips) representation of planning problems, mapping shortest-path problems in state-space into suitably defined shortest-path problems in atom-space. The formulation applies with little variation to sequential and parallel planning, and problems with different action costs.
Effect of Urban Land Use on Travel Behaviour: Evidence from Lahore

In urban areas across Asia and Africa, public investments in road infrastructure subsidise suburban sprawl and privilege car ownership. At the same time, restrictive land use ordinances prevent mixed-use land development, so distances between home and work increase; an outcome particularly burdensome in time and money for marginal groups. To analyse the effects of public investments in road infrastructure on commute times for different modes, the study uses a rare household travel survey from Lahore. A novel multilevel methodology nests individual-level commute times for different modes within a zone level of analysis which controls for differences in urban land use and road infrastructure. Results suggest that individuals who drive to work enjoy significant time benefits over those who walk to work. The policy implications focus attention on the need for infrastructure investments to mitigate the time costs for commuters who walk and who ride the bus.
Overexpression of human SOD1 improves survival of mice susceptible to endotoxic shock

Background Protective effects of the antioxidant enzyme Cu-Zn superoxide dismutase (SOD1) against endotoxic shock have not been demonstrated in animal models. We used a murine model to investigate whether overexpression of SOD1 protects against endotoxic shock, and whether the genetic background of SOD1 affects its effective protective effects and susceptibility to endotoxic shock. Methods Transgenic (tg) mice overexpressing human SOD1 and control mice were divided into four groups based on their genetic background: (1) tg mice with mixed genetic background (tg-JAX); (2) wild-type (WT) littermates of tg-JAX strain (WT-JAX); (3) tg mice with C57BL/6J background (tg-TX); (4) WT littermates of tg-TX strain (WT-TX). Activity of SOD1 in the intestine, heart, and liver of tg and control mice was confirmed using a polyacrylamide activity gel. Endotoxic shock was induced by intraperitoneal injection of lipopolysaccharide. Survival rates over 120 hours (mean, 95% confidence interval) were analyzed using Kaplan–Meier survival curves. Results Human SOD1 enzymatic activities were significantly higher in the intestine, heart, and liver of both tg strains (tg-JAX and tg-TX) compared with their WT littermates (WT-JAX and WT-TX, respectively). Interestingly, the endogenous SOD1 activities in tg-JAX mice were decreased compared with their WT littermates (WT-JAX), but such aberrant changes were not observed in tg-TX mice. There was no difference in the survival time between tg-JAX and WT-JAX groups after endotoxic shock (P > 0.05). However, the survival time in the tg-TX group was more than twofold longer than that in the WT-TX group (P < 0.05). In addition, WT-JAX mice survived significantly longer than WT-TX mice (P < 0.05). Conclusion Aberrant decrease of endogenous SOD1 activities may have overshadowed the effect of overexpression of SOD1 in tg mice (tg-JAX). Mice with C57BL/6J background (tg-TX) are more susceptible to lipopolysaccharide-induced endotoxic shock than those with mixed genetic background (tg-JAX). Overexpression of SOD1 is protective only in mice with C57BL/6J background (tg-TX).
Scalable Peer-to-Peer Indexing with Constant State

We present a distributed indexing scheme for peer to peer networks. Past work on distributed indexing traded off fast search times with non-constant degree topologies or network-unfriendly behavior such as flooding. In contrast, the scheme we present optimizes all three of these performance measures. That is, we provide logarithmic round searches while maintaining connections to a fixed number of peers and avoiding network flooding. In comparison to the well known scheme Chord, we provide competitive constant factors. Finally, we observe that arbitrary linear speedups are possible and discuss both a general brute force approach and specific economical optimizations.
CONSTRAINED MAXIMUM A POSTERIORI APPROACH FOR SPEECH ENHANCEMENT

The maximum a posteriori estimator based on HMM’s is successful to some degree because of the incorporation of prior knowledge of speech and markovian properties of the models. The enhanced speech quality is, however, not satisfying at low input SNR. In order to improve speech quality at low input SNR, this paper proposes a method that incorporates codebook constrained Wiener filter into MAP framework to impose spectral constraints on estimated speech signals. The objective measures, global SNR and Itakura-Saito distortion measure, verified the quality improvement of the proposed method.
Strictly declarative specification of sophisticated points-to analyses

We present the DOOP framework for points-to analysis of Java programs. DOOP builds on the idea of specifying pointer analysis algorithms declaratively, using Datalog: a logic-based language for defining (recursive) relations. We carry the declarative approach further than past work by describing the full end-to-end analysis in Datalog and optimizing aggressively using a novel technique specifically targeting highly recursive Datalog programs. As a result, DOOP achieves several benefits, including full order-of-magnitude improvements in runtime. We compare DOOP with Lhotak and Hendren's PADDLE, which defines the state of the art for context-sensitive analyses. For the exact same logical points-to definitions (and, consequently, identical precision) DOOP is more than 15x faster than PADDLE for a 1-call-site sensitive analysis of the DaCapo benchmarks, with lower but still substantial speedups for other important analyses. Additionally, DOOP scales to very precise analyses that are impossible with PADDLE and Whaley et al.'s bddbddb, directly addressing open problems in past literature. Finally, our implementation is modular and can be easily configured to analyses with a wide range of characteristics, largely due to its declarativeness.
GUIR at SemEval-2016 task 12: Temporal Information Processing for Clinical Narratives

Extraction and interpretation of temporal information from clinical text is essential for clinical practitioners and researchers. SemEval 2016 Task 12 (Clinical TempEval) addressed this challenge using the THYME 1 corpus, a corpus of clinical narratives annotated with a schema based on TimeML 2 guidelines. We developed and evaluated approaches for: extraction of temporal expressions (TIMEX3) and EVENTs; TIMEX3 and EVENT attributes; document-time relations; and narrative container relations. Our approach is based on supervised learning (CRF and logistic regression), utilizing various sets of syntactic, lexical and semantic features with addition of manually crafted rules. Our system demonstrated substantial improvements over the baselines in all the tasks.
Special Issue “COVID-19 Coagulopathy: Advances on Pathophysiology and Therapies”

The Special Issue on COVID-19 coagulopathy initiated one year ago aimed to shed light on the mechanisms underlying the changes in the coagulation status making SARS-CoV-2 infection such a tough adversary for every one of the medical specialties encountering it, along with overseeing the therapeutic applications derived from the current understanding of these mechanisms [. ].
Surrogate-Based MOEA/D for Electric Motor Design With Scarce Function Evaluations

This paper proposes a surrogate-assisted multiobjective evolutionary algorithm based on decomposition (sMOEA/D) for the design of electric motors. The idea is to improve the surrogate gradually during the optimization. Simulation results show that the proposed method is competitive with state-of-the-art multiobjective optimization algorithms needing only a small number of function evaluations.
THE GUINEA PIG COCHLEA

Corresponding address to: Didier Dulon, EMI 99-27 INSERM Université de Bordeaux 2 Laboratoire de Biologie Cellulaire et Moléculaire de l'Audition Hôpital Pellegrin, 33076 Bordeaux, France. Telephone: (33) 5 56 24 20 47, Fax : (33) 5 56 96 29 84 Didier.dulon@bordeaux.inserm. fr 36 pages and 10 figures Running Title: BK channels and cochlear hair cells
Refining the Oort and Galactic constants

The local stellar kinematics of the Milky Way offer a useful tool for studying the rotation curve of the Galaxy. These kinematics — usually parametrized by the Oort constants AB— depend on the local gradient of the rotation curve as well as its absolute value (Θ0), and the Sun's distance to the Galactic Centre (R0). The density of interstellar gas in the Milky Way is shown to vary non-monotonically with radius, and so contributes significantly to the local gradient of the rotation curve. We have therefore calculated mass models for the Milky Way that include this component, and have derived the corresponding radial variation in the Oort constants. Between 0.9R0 and 1.2 R0 the Oort functionsA(R) and B(R) differ significantly from the general ∼ Θ0/R dependence. Various previously inexplicable observations are shown to be consistent with these new predictions. For example, these models may explain the ∼ 40 per cent difference between the values for 2 A R0 derived from radial velocity data originating in the inner and outer Galaxy. They also go some way toward explaining the different shapes of the velocity ellipsoids of giant and dwarf stars in the solar neighbourhood. However, a consistent picture only emerges if one adopts small values for the radius of the solar circle (R0 = 7.1 ± 0.4 kpc) and local circular speed (Θ0 = 184 ± 8 km s−1). With these Galactic constants the rotation curve of the Milky Way declines slowly in the outer Galaxy; Vrot(20 kpc) = 166 km s−1. Our low value for the distance to the Galactic Centre agrees well with the only direct determination of R0 (7.2 ± 0.7 kpc). Using these Galactic constants, we also find that the proper motion of Sgr A* is consistent with the observational constraints. Simple analytic arguments as well as detailed calculations show that the radial velocities and proper motions of our best-fitting model are entirely consistent with the radial velocities of Cepheids and the Hipparcos measurements of their proper motions.
Multi-model adaptive spatial hypertext

Information delivery on the Web often relies on general purpose Web pages that require the reader to adapt to them. This limitation is addressed by approaches such as spatial hypermedia and adaptive hypermedia. Spatial hypermedia augments the representation power of hypermedia and adaptive hypermedia explores the automatic modification of the presentation according to user needs. This dissertation merges these two approaches, combining the augmented expressiveness of spatial hypermedia with the flexibility of adaptive hypermedia. This dissertation presents the Multi-model Adaptive Spatial Hypermedia framework (MASH). This framework provides the theoretical grounding for the augmentation of spatial hypermedia with dynamic and adaptive functionality and, based on their functionality, classifies systems as generative, interactive, dynamic or adaptive spatial hypermedia. Regarding adaptive hypermedia, MASH proposes the use of multiple independent models that guide the adaptation of the presentation in response to multiple relevant factors. The framework is composed of four parts: a general system architecture, a definition of the fundamental concepts in spatial hypermedia, an ontological classification of the adaptation strategies, and the philosophy of conflict management that addresses the issue of multiple independent models providing contradicting adaptation suggestions. From a practical perspective, this dissertation produced WARP, the first MASH-based system. WARP's novel features include spatial transclusion links as an alternative to navigational linking, behaviors supporting dynamic spatial hypermedia, and personal annotations to spatial hypermedia. WARP validates the feasibility of the multi-model adaptive spatial hypermedia and allows the exploration of other approaches such as Web-based spatial hypermedia, distributed spatial hypermedia, and interoperability issues between spatial hypermedia systems. In order to validate the approach, a user study comparing non-adaptive to adaptive spatial hypertext was conducted. The study included novice and advanced users and produced qualitative and quantitative results. Qualitative results revealed the emergence of reading behaviors intrinsic to spatial hypermedia. Users moved and modified the objects in order to compare and group objects and to keep track of what had been read. Quantitative results confirmed the benefits of adaptation and indicated a possible synergy between adaptation and expertise. In addition, the study created the largest spatial hypertext to date in terms of textual content.
Well-being indices: what about Italian scenario?

This paper proposes a review of the Italian well-being scenario, introducing its peculiarities and defects. The aim is to provide a detailed image, also to policy-makers, describing the accuracy, timeliness and territorial coverage. All these characteristics are a challenge for a good planning, for a correct international comparison or to integrate well-being indices with new data, represented, as example, by big data. Abstract Questo lavoro propone una rassegna delle misure del benessere in Italia, presentandone peculiarità e difetti. L’obiettivo è fornire un’immagine dettagliata, anche ai policy-makers, descrivendone l’accuratezza, la tempestività e la copertura territoriale. Tutte queste caratteristiche rappresentano una sfida per una buona pianificazione, per un corretto confronto internazionale o per l’integrazione con nuove fonti di dati, rappresentate, ad esempio, dai big data.
ShenLingLan Influences the Attachment and Migration of Ovarian Cancer Cells Potentially through the GSK3 Pathway

Background: Ovarian cancer presents a major clinical challenge in the UK. Glycogen synthase kinase-3 (GSK-3) has been linked to cancer. This study tested the impact of ShenLingLan (SLDM) on ovarian cancer cell behaviour and its links to GSK-3. Methods: Fresh ovarian tumours (n = 52) were collected and processed. Histopathologcial and clinical information were collected and analysed against GSK-3 transcript levels using quantitative PCR (qPCR). Immortalised ovarian cancer cells’ protein alterations in response to SLDM were identified using a Kinexus™ protein kinase array. The effects of SLDM and a combination of SLDM and TWS119 on ovarian cancer cells ability to attach and migrate were evaluated using electrical cell-substrate impedance sensing (ECIS). Results: Transcript expression of GSK-3β was significantly increased in ovarian tumours which were poorly differentiated, patients with recurrence and in patients who had died from ovarian cancer. Treating SKOV-3 ovarian cells with SLDM reduced GSK-3 expression and GSK-3α (Y279). Treatment with SLDM reduced ovarian cancer cells ability to attach and migrate, which was further reduced in the presence of TWS119. Conclusions: This study identified a potential mechanism by which SLDM may exert anti-metastatic effects. Further work is needed to investigate the in vivo effects SLDM has on ovarian tumours.
On two different classes of estimators in two-phase sampling using multi-auxiliary variables

This paper looks at the estimation of a finite population mean when emphasis is laid on the use of information on p auxiliary variables under a two-phase sampling set-up. On adopting two different estimation techniques, attention has been given on the construction of two different classes of estimators viz., a class of chain-type estimators and a class of predictive-type estimators, and their precision has been studied.
Learning name pronunciations in automatic speech recognition systems

Many speech recognition systems that provide over-the phone services, e.g. name dialers, stock quote providers, location finders, rely on the accurate recognition of proper names. For this to happen, the systems need to know how their users will pronounce these words. However, predicting the pronunciation of a proper name is a notoriously difficult problem as it depends on the origin of the name, the linguistic background of the speaker, and other cultural and sociological factors, in addition of course to the word spelling. In this paper, we describe a data-driven method that learns proper name pronunciations from audio samples of these words. The algorithm relies on the machinery of a general purpose speech recognizer to find the phone sequence that best matches the sample speech waveforms. In addition, it incorporates linguistic knowledge automatically acquired from a pronunciation dictionary to ensure that the learned pronunciations are "reasonable" from a linguistic viewpoint. We show on a corporate name dialing database that the proposed algorithm reduces the call routing error rate by 40% compared to a reference letter-to-phone pronunciation engine.
Pointing to space: Modeling of deictic interaction referring to regions

In daily conversation, we sometimes observe a deictic interaction scene that refers to a region in a space, such as saying “please put it over there” with pointing. How can such an interaction be possible with a robot? Is it enough to simulate people's behaviors, such as utterance and pointing? Instead, we highlight the importance of simulating human cognition. In the first part of our study, we empirically demonstrate the importance of simulating human cognition of regions when a robot engages in a deictic interaction by referring to a region in a space. The experiments indicate that a robot with simulated cognition of regions improves efficiency of its deictic interaction. In the second part, we present a method for a robot to computationally simulate cognition of regions.
Hierarchical routing on unstructured identifiers

In this paper we follow the vision that the IP address hierarchy is going to collapse and propose a novel routing and addressing method based on non-structured addresses. The proposed concept, called HUId, clearly separates intra-domain routing (i.e., routing between hosts within a network domain) and inter-domain routing (i.e., routing between networks). The separation is based on two different routing mechanisms and having two different identifiers. The scope of these identifiers, however, are not disjunct. This simple framework helps eliminating the need for a protocol covering and managing the border links. This paper investigates the benefits of such an architecture and mechanisms like mapping and fail-over with site multi-homing. Finally, we elaborate on reusing existing technologies to give a simple implementation guideline.
A Physical Model for Work-Function Variation in Ultra-Short Channel Metal-Gate MOSFETs

In this letter, an accurate physical model for work-function variation (WFV) relevant to ultrashort-channel (<; 32 nm) MOSFETs has been formulated that considers the work function and size of the individual grains in determining the local MOS band structure. The proposed model is shown to be much more accurate than the most recently published model. Additionally, using this new model, WFV effect in a 3-D device can be captured using 2-D device simulation, resulting in a significantly lower simulation time.
A hexapod robot modeled on the stick insect, Carausius morosus

Robot builders have often used insects as a source of inspiration when designing their mechanical systems, due to their ability to easily navigate uneven terrain, overcome or avoid obstacles, and adjust gaits based on traveling speed. Robotics has borrowed from nature with varying degrees of abstraction, from physical appearance to observed behaviours. This paper describes the design and construction of a robotic hexapod based on the stick insect, Carausius morosus. Physically, it is an 18.8:1 scale representation of the insect with 3-DoF legs. The to-scale design was chosen to provide similar physical attributes, such as joint and leg locations, sizes, and ranges-of-motion, which will allow more meaningful comparisons between robot performance and actual insect movements (as opposed to arbitrary hexapod designs). A custom-designed leg control board is responsible for deciding leg joint movements based on a model of the neurobiological systems identified in the insect. A distributed network of six boards will be used to control the legs based on internal parameters that can be modulated by descending commands or adaptively altered by ascending sensory signals when interacting with the environment. Our final aim in this work is to add a vision system to create depth maps, which will be used as an input to a learning system, coupled with the mechanical sensory system, such that terrain that triggers reflex actions can be associated with visual cues in order to predictively avoid obstacles and potholes.