Miracle-dz/UniFAR-FTUs huggingface dataset:
How Projective is Projective Content? Gradience in Projectivity and At-issueness

Projective content is utterance content that a speaker may be taken to be committed to even when the expression associated with the content occurs embedded under an entailment-canceling operator (e.g., Chierchia & McConnell-Ginet, 1990). It has long been observed that projective content varies in how projective it is (e.g., Karttunen, 1971; Simons, 2001; Abusch, 2010), though preliminary experimental research has been able to conﬁrm only some of the intuitions about projection variability (e.g., Smith & Hall, 2011; Xue & Onea, 2011). Given the sparse empirical evidence for projection variability, the ﬁrst goal of this paper was to investigate projection variability for projective content associated with 19 expressions of American English. The second goal was to explore the hypothesis, called the Gradient Projection Principle, that content projects to the extent that it is not at-issue. The ﬁndings of two pairs of experiments provide robust empirical evidence for projection variability and for the Gradient Projection Principle. We show that many analyses of projection cannot account for the observed projection variability and discuss the implications of our ﬁnding that projective content varies in its at-issueness for an empirically adequate analysis of projection. of the projectivity of projective content: the more projective content was judged to be not-at-issue in a speaker’s utterance, the more the speaker was taken to be committed to the content. The experiment also showed that the target expressions differ in the extent to which the projective content they are associated
Strong sex bias in elite control of paediatric HIV infection

Background: Reports of posttreatment control following antiretroviral therapy (ART) have prompted the question of how common immune control of HIV infection is in the absence of ART. In contrast to adult infection, where elite controllers have been very well characterized and constitute approximately 0.5% of infections, very few data exist to address this question in paediatric infection. Methods: We describe 11 ART-naive elite controllers from 10 cohorts of HIV-infected children being followed in South Africa, Brazil, Thailand, and Europe. Results: All but one of the elite controllers (91%) are females. The median age at which control of viraemia was achieved was 6.5 years. Five of these 11 (46%) children lost control of viraemia at a median age of 12.9 years. Children who maintained control of viraemia had significantly higher absolute CD4+ cell counts in the period of elite control than those who lost viraemic control. On the basis of data available from these cohorts, the prevalence of elite controllers in paediatric infection is estimated to be 5–10-fold lower than in adults. Conclusion: Although conclusions are limited by the study design, these data suggest that, whilst paediatric elite control can be achieved, compared with adult elite controllers, this occurs rarely, and takes some years after infection to achieve. Also, loss of immune control arises in a high proportion of children and often relatively rapidly. These findings are consistent with the more potent antiviral immune responses observed in adults and in females.
Birds of a Feather Flock Together? A Study of Developers' Flocking and Migration Behavior in GitHub and Stack Overflow

Interactions between individuals and their participation in community activities are governed by how individuals identify themselves with their peers. We want to investigate such behavior for developers while they are learning and contributing on socially collaborative environments, specifically code hosting sites and question/answer sites. In this study, we investigate the following questions about advocates, developers who can be identified as well-rounded community contributors and active learners. Do advocates flock together in a community? How do flocks of advocates migrate within a community? Do these flocks of advocates migrate beyond a single community? To understand such behavior, we collected 12,578 common advocates across a code hosting site - GitHub and a question/answering site - Stack Overflow. These advocates were involved in 1,549 projects on GitHub and were actively asking 114,569 questions and responding 408,858 answers and 1,001,125 comments on Stack Overflow. We performed an in-depth empirical analysis using social networks to find the flocks of advocates and their migratory pattern on GitHub, Stack Overflow, and across both communities. We found that 7.5% of the advocates create flocks on GitHub and 8.7% on Stack Overflow. Further, these flocks of advocates migrate on an average of 5 times on GitHub and 2 times on Stack Overflow. In particular, advocates in flocks of two migrate more frequently than larger flocks. However, this migration behavior was only common within a single community. Our findings indicate that advocates' flocking and migration behavior differs substantially from the ones found in other social environments. This suggests a need to investigate the factors that demotivate the flocking and migration behavior of advocates and ways to enhance and integrate support for such behavior in collaborative software tools.
Extended memory lifetime in spiking neural networks employing memristive synapses with nonlinear conductance dynamics

Spiking neural networks (SNNs) employing memristive synapses are capable of life-long online learning. Because of their ability to process and classify large amounts of data in real-time using compact and low-power electronic systems, they promise a substantial technology breakthrough. However, the critical issue that memristor-based SNNs have to face is the fundamental limitation in their memory capacity due to finite resolution of the synaptic elements, which leads to the replacement of old memories with new ones and to a finite memory lifetime. In this study we demonstrate that the nonlinear conductance dynamics of memristive devices can be exploited to improve the memory lifetime of a network. The network is simulated on the basis of a spiking neuron model of mixed-signal digital-analogue sub-threshold neuromorphic CMOS circuits, and on memristive synapse models derived from the experimental nonlinear conductance dynamics of resistive memory devices when stimulated by trains of identical pulses. The network learning circuits implement a spike-based plasticity rule compatible with both spike-timing and rate-based learning rules. In order to get an insight on the memory lifetime of the network, we analyse the learning dynamics in the context of a classical benchmark of neural network learning, that is hand-written digit classification. In the proposed architecture, the memory lifetime and the performance of the network are improved for memristive synapses with nonlinear dynamics with respect to linear synapses with similar resolution. These results demonstrate the importance of following holistic approaches that combine the study of theoretical learning models with the development of neuromorphic CMOS SNNs with memristive devices used to implement life-long on-chip learning.
CD34 and CD117 Stemness of Lineage-Negative Cells Reverses Memory Loss Induced by Amyloid Beta in Mouse Model

A majority of the neurodegenerative disorders including Alzheimer's disease are untreatable and occur primarily due to aging and rapidly changing lifestyles. The rodent Alzheimer's disease models are critical for investigating the underlying disease pathology and screening of novel therapeutic targets in preclinical settings. We aimed to characterize the stemness properties of human umbilical cord blood (hUCB) derived lineage-negative (Lin−) stem cells based on CD34 and CD117 expression as well as surface morphology using flow cytometry and scanning electron microscopy, respectively. The efficacy of the stem cells was tested by its capacity to rescue the injury caused by intrahippocampal delivery of varying doses of amyloid beta. The hUCB Lin− stem cells reversed memory loss due to Aβ42-induced injury more effectively at micromolar concentration, and not picomolar concentration. More studies are required to delineate the underlying molecular events associated with hUCB Lin− stem cells.
Bayesian RL for Goal-Only Rewards

We address the challenging problem of reinforcement learning under goal-only rewards [1], where rewards are only non-zero when the goal is achieved. This reward definition alleviates the need for cumbersome reward engineering, making the reward formulation trivial. Classic exploration heuristics such as Boltzmann or -greedy exploration are highly inefficient in domains with goal-only rewards. We solve this problem by leveraging value function posterior variance information to direct exploration where uncertainty is higher. The proposed algorithm (EMU-Q) achieves data-efficient exploration, and balances exploration and exploitation explicitly at a policy level granting users more control over the learning process. We introduce general features approximating kernels, allowing to greatly reduce the algorithm complexity from O(N) in the number of transitions to O(M) in the number of features. We demonstrate EMU-Q is competitive with other exploration techniques on a variety of continuous control tasks and on a robotic manipulator.
The Influence of Percentage Weight-Bearing on Foot Radiographs

Introduction: Clinical decisions are often made on weight-bearing radiographs. However, it is unknown whether various weight-bearing conditions alter specific radiographic measurements. The purpose of this study was to determine whether percentage weight-bearing influences radiographic measurements of the normal foot. Methods: A prospective study with 20 healthy individuals had radiographs of the foot under 5 weight-bearing conditions (non–weight-bearing, 10% body weight, 25% body weight, 50% body weight, and 100% body weight). Measurements were made of hallux valgus angle (HVA), 1-2 intermetatarsal angle (IMA), talonavicular coverage angle (TNCA), talocalcaneal angle (TCA), forefoot width, LisFranc distance, cuboid height to ground (CHG), and talo–first metatarsal angle (TMA) of each weight-bearing condition. Statistical differences of each measurement for each weight-bearing condition were determined. Results: The TNCA and TCA increased significantly, whereas the CHG decreased significantly with increased percentage body weight. There were no differences in HVA, IMA, forefoot width, LisFranc distance, and TMA with increased percentage body weight. Conclusions: This study shows an increase in TNCA and TCA, and decrease in CHG, demonstrating a flattening of the medial arch, increasing hindfoot valgus, and midfoot external rotation and abduction with increasing percentage body weight applied to a foot. Percentage weight-bearing does not change radiographs in the foot between 25% and 100% weight-bearing. The clinical relevance of this finding is that graduated postinjury or postoperative weight-bearing regimens may only be relevant if the patient is either less than or greater than 25% of body weight on their extremity. Levels of Evidence: Case Series, Level IV: Prospective
Multiple Interactions Made Easy (MIME): Large Scale Demonstrations Data for Imitation

In recent years, we have seen an emergence of data-driven approaches in robotics. However, most existing efforts and datasets are either in simulation or focus on a single task in isolation such as grasping, pushing or poking. In order to make progress and capture the space of manipulation, we would need to collect a large-scale dataset of diverse tasks such as pouring, opening bottles, stacking objects etc. But how does one collect such a dataset? In this paper, we present the largest available robotic-demonstration dataset (MIME) that contains 8260 human-robot demonstrations over 20 different robotic tasks (this https URL). These tasks range from the simple task of pushing objects to the difficult task of stacking household objects. Our dataset consists of videos of human demonstrations and kinesthetic trajectories of robot demonstrations. We also propose to use this dataset for the task of mapping 3rd person video features to robot trajectories. Furthermore, we present two different approaches using this dataset and evaluate the predicted robot trajectories against ground-truth trajectories. We hope our dataset inspires research in multiple areas including visual imitation, trajectory prediction, and multi-task robotic learning.
Worry is associated with inefficient functional activity and connectivity in prefrontal and cingulate cortices during emotional interference

Anxiety is known to impair attentional control particularly when Task demands are high. Neuroimaging studies generally support these behavioral findings, reporting that anxiety is associated with increased (inefficient) activity in dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC) during attentional control Tasks. However, less is known about the relationship between worry (part of the cognitive dimension of trait anxiety) and DLPFC/ACC function and connectivity during attentional control. In the present study, we sought to clarify this relationship.
Neuronal nicotinic acetylcholine receptors mediate ∆9‐THC dependence: Mouse and human studies

Cessation from prolonged use of ∆9‐tetrahydrocannabinol (THC), the primary active compound responsible for the cannabimimetic effects of cannabis, results in a mild to moderate withdrawal syndrome in humans and laboratory animals. Whereas manipulations of the endogenous cannabinoid system (eg, cannabinoid receptors and endocannabinoid regulating enzymes) alter nicotine withdrawal, in this study we asked the reciprocal question. Do nicotinic acetylcholine receptors (nAChRs) modulate THC withdrawal? To assess the role of different nAChR subtypes in THC withdrawal, we used transgenic mouse, preclinical pharmacological, and human genetic correlation approaches. Our findings show that selective α3β4* nAChR antagonist, AuIB, and α3β4* nAChR partial agonist, AT‐1001, dose‐dependently attenuated somatic withdrawal signs in THC‐dependent mice that were challenged with the cannabinoid‐1 receptor antagonist rimonabant. Additionally, THC‐dependent α5 and α6 nAChR knockout (KO) mice displayed decreased rimonabant precipitated somatic withdrawal signs compared with their wild‐type counterparts. In contrast, β2 and α7 nAChR KO mice showed no alterations in THC withdrawal signs. Moreover, deletion of β2 nAChR did not alter the reduced expression of somatic signs by the preferred α6β4* antagonist, BulA [T5A;P60]. Finally, the human genetic association studies indicated that variations in the genes that code for the α5, α3, β4, and α6 nAChRs were associated with cannabis disorder phenotypes. Overall, these findings suggest that α3β4* and α6β4* nAChR subtypes represent viable targets for the development of medications to counteract THC dependence.
Manipulation of Salmonella Typhi Gene Expression Impacts Innate Cell Responses in the Human Intestinal Mucosa

Although immunity induced by typhoid fever is moderated and short-lived, typhoid vaccination with the attenuated Ty21a oral vaccine generates long-lasting protection rates reaching up to 92%. Thus, there are important differences on how wild-type Salmonella and typhoid vaccine strains stimulate host immunity. We hypothesize that vaccine strains with different mutations might affect gut inflammation and intestinal permeability by different mechanisms. To test this hypothesis, we used an in vitro organotypic model of the human intestinal mucosa composed of human intestinal epithelial cells, lymphocytes/monocytes, endothelial cells, and fibroblasts. We also used six Salmonella enterica serovar Typhi (S. Typhi) strains: the licensed Ty21a oral vaccine, four typhoid vaccine candidates (i.e., CVD 908, CVD 909, CVD 910, and CVD 915) and the wild-type Ty2 strain. We found that genetically engineered S. Typhi vaccine strains elicit differential host changes not only in the intestinal permeability and secretion of inflammatory cytokines, but also in the phenotype and activation pathways of innate cells. These changes were distinct from those elicited by the parent wild-type S. Typhi and depended on the genetic manipulation. In sum, these results emphasize the importance of carefully selecting specific manipulations of the Salmonella genome in the development of typhoid vaccines.
Cross-Protective Shigella Whole-Cell Vaccine With a Truncated O-Polysaccharide Chain

Shigella is a highly prevalent bacterium causing acute diarrhea and dysentery in developing countries. Shigella infections are treated with antibiotics but Shigellae are increasingly resistant to these drugs. Vaccination can be a countermeasure against emerging antibiotic-resistant shigellosis. Because of the structural variability in Shigellae O-antigen polysaccharides (Oag), cross-protective Shigella vaccines cannot be derived from single serotype-specific Oag. We created an attenuated Shigella flexneri 2a strain with one rather than multiple Oag units by disrupting the Oag polymerase gene (Δwzy), which broadened protective immunogenicity by exposing conserved surface proteins. Inactivated Δwzy mutant cells combined with Escherichia coli double mutant LT(R192G/L211A) as adjuvant, induced potent antibody responses to outer membrane protein PSSP-1, and type III secretion system proteins IpaB and IpaC. Intranasal immunization with the vaccine preparation elicited cross-protective immunity against S. flexneri 2a, S. flexneri 3a, S. flexneri 6, and Shigella sonnei in a mouse pneumonia model. Thus, S. flexneri 2a Δwzy represents a promising candidate strain for a universal Shigella vaccine.
Clock Around the Clock: Time-Based Device Fingerprinting

Physical device fingerprinting exploits hardware features to uniquely identify a machine. This technique has been used for authentication, license binding, or attackers identification, among other tasks. More recently, hardware features have also been introduced to identify web users and perform web tracking. A particular type of hardware fingerprint exploits differences in the computer internal clock signals. However, previous methods to test for these differences relied on complex experiments performed by running native code in the target machine. In this paper, we show a new way to compute a hardware finger- printing, based on timing the execution of sequences of instructions readily available in API functions. Due to its simplicity, this method can also be performed remotely by simply timing few seemingly innocuous lines of JavaScript code. We tested our approach with different functions, such as common string manipulation or widespread cryptographic routines, and found that several of them can be used as basic blocks for fingerprinting. Using this technique, we implemented a tool called CryptoFP. We tested its native implementation in a homogeneous scenario, to distinguish among a perfectly identical (both in software and hardware) set of computers. CryptoFP was able to correctly discriminate all the identical computers in this scenario and recognize the same computer also under different CPU load configurations, outperforming every other hardware fingerprinting method. We then show how CryptoFP can be implemented using a combination of the HTML5 Cryptography API and standard timing API for web device fingerprinting. In this case, we compared our method, both in the same homogeneous scenario and by performing an experiment with real-world users running heterogeneous devices, against other state-of-the-art web device fingerprinting solutions. In both cases, our approach clearly outperforms all existing methods.
Learning to Localize Using a LiDAR Intensity Map

In this paper we propose a real-time, calibration-agnostic and effective localization system for self-driving cars. Our method learns to embed the online LiDAR sweeps and intensity map into a joint deep embedding space. Localization is then conducted through an efficient convolutional matching between the embeddings. Our full system can operate in real-time at 15Hz while achieving centimeter level accuracy across different LiDAR sensors and environments. Our experiments illustrate the performance of the proposed approach over a large-scale dataset consisting of over 4000km of driving.
Matching Game Based Framework for Two-Timescale Cooperative D2D Communication

We consider a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the opportunities to use the licensed spectrum. To reduce the overhead, we propose a novel two-timescale resource allocation scheme, in which the pairing between CUs and D2D pairs is decided at a long timescale and time allocation for CU and D2D pair is determined at a short timescale. Specifically, to characterize the long-term payoff of each potential CU-D2D pair, we investigate the optimal cooperation policy to decide the time allocation based on the instantaneous channel state \mbox{information (CSI)}. We prove that the optimal policy is a threshold policy. Since CUs and D2D pairs are self-interested, they are paired only when they agree to cooperate mutually. Therefore, to study the behaviors of CUs and D2D pairs, we formulate the pairing problem as a matching game, based on the long-term payoff of each possible pairing. Furthermore, unlike most previous matching model in D2D networks, we allow transfer between CUs and D2D pairs to improve the performance. Besides, we propose an algorithm, which converges to an $\epsilon$-stable matching.
Home Monitoring of Retinal Sensitivity on a Tablet Device in Intermediate Age-Related Macular Degeneration

Purpose We determine the feasibility of using a home-based tablet device to monitor retinal sensitivity (RS) in intermediate age-related macular degeneration (iAMD), the benefits of weekly reminders, and the comparison with clinic-based results. Methods A customized test for tablets was designed to measure RS (within central 2°) in individuals with iAMD at weekly intervals in their home, with remote data collection. Half of the participants were randomized to receive weekly test reminders. Clinic-based microperimetric macular sensitivity results were compared to tablet results. Participation rates were analyzed at 2 months. Results Of 38 participants (mean age, 70.3 years) with iAMD enrolled in the study, 21 (55%) were using the tablet-based test at 2 months. Common reasons for inactivity were noncompatible devices (41.1%) or other technology access issues (35.3%). Participants with weekly reminders completed tests more regularly (6.6 ± 3.9 vs. 8.7 ± 4.1 days, P = 0.01), but weekly reminders showed no effect on participation rates (P = 0.69). Mean RS from the tablet device (25.03 ± 2.41 dB) was not significantly different from the clinic-based microperimetry performance (25.21 ± 2.20 dB; P = 0.58). Conclusions Regular monitoring of retinal function on a tablet device in a home setting in individuals with iAMD is feasible with results comparable to those of clinic-based microperimetry. Weekly reminders resulted in more frequent testing. Seamless ability to access technology will be important for higher participation rates. Translational Relevance The use of home-monitoring on a tablet-device is promising, but adequate support for an older cohort to take up technology is required if such a tool is to be useful for long-term home monitoring.