Miracle-dz/UniFAR-FTUs huggingface dataset:
Baseline reward circuitry activity and trait reward responsiveness predict expression of opioid analgesia in healthy subjects

Variability in opioid analgesia has been attributed to many factors. For example, genetic variability of the μ-opioid receptor (MOR)-encoding gene introduces variability in MOR function and endogenous opioid neurotransmission. Emerging evidence suggests that personality trait related to the experience of reward is linked to endogenous opioid neurotransmission. We hypothesized that opioid-induced behavioral analgesia would be predicted by the trait reward responsiveness (RWR) and the response of the brain reward circuitry to noxious stimuli at baseline before opioid administration. In healthy volunteers using functional magnetic resonance imaging and the μ-opioid agonist remifentanil, we found that the magnitude of behavioral opioid analgesia is positively correlated with the trait RWR and predicted by the neuronal response to painful noxious stimuli before infusion in key structures of the reward circuitry, such as the orbitofrontal cortex, nucleus accumbens, and the ventral tegmental area. These findings highlight the role of the brain reward circuitry in the expression of behavioral opioid analgesia. We also show a positive correlation between behavioral opioid analgesia and opioid-induced suppression of neuronal responses to noxious stimuli in key structures of the descending pain modulatory system (amygdala, periaqueductal gray, and rostral–ventromedial medulla), as well as the hippocampus. Further, these activity changes were predicted by the preinfusion period neuronal response to noxious stimuli within the ventral tegmentum. These results support the notion of future imaging-based subject-stratification paradigms that can guide therapeutic decisions.
Performance comparison of single-stage mixed-refrigerant Joule–Thomson cycle and reverse Brayton cycle for cooling 80 to 120 K temperature-distributed heat loads

Thermodynamic performance comparison of single-stage mixed-refrigerant Joule–Thomson cycle (MJTR) and pure refrigerant reverse Brayton cycle (RBC) for cooling 80 to 120 K temperature-distributed heat loads was conducted in this paper. Nitrogen under various liquefaction pressures was employed as the heat load. The research was conducted under nonideal conditions by exergy analysis methods. Exergy efficiency and volumetric cooling capacity are two main evaluation parameters. Exergy loss distribution in each process of refrigeration cycle was also investigated. The exergy efficiency and volumetric cooling capacity of MJTR were obviously superior to RBC in 90 to 120 K temperature zone, but still inferior to RBC at 80 K. The performance degradation of MJTR was caused by two main reasons: The high fraction of neon resulted in large entropy generation and exergy loss in throttling process. Larger duty and WLMTD lead to larger exergy losses in recuperator.
Genetic uniformity characterizes the invasive spread of water hyacinth (Eichhornia crassipes), a clonal aquatic plant

Aquatic plant invasions are often associated with long‐distance dispersal of vegetative propagules and prolific clonal reproduction. These reproductive features combined with genetic bottlenecks have the potential to severely limit genetic diversity in invasive populations. To investigate this question we conducted a global scale population genetic survey using amplified fragment length polymorphism markers of the world’s most successful aquatic plant invader –Eichhornia crassipes (water hyacinth). We sampled 1140 ramets from 54 populations from the native (South America) and introduced range (Asia, Africa, Europe, North America, Central America and the Caribbean). Although we detected 49 clones, introduced populations exhibited very low genetic diversity and little differentiation compared with those from the native range, and ∼80% of introduced populations were composed of a single clone. A widespread clone (‘W’) detected in two Peruvian populations accounted for 70.9% of the individuals sampled and dominated in 74.5% of the introduced populations. However, samples from Bangladesh and Indonesia were composed of different genotypes, implicating multiple introductions to the introduced range. Nine of 47 introduced populations contained clonal diversity suggesting that sexual recruitment occurs in some invasive sites where environmental conditions favour seedling establishment. The global patterns of genetic diversity in E. crassipes likely result from severe genetic bottlenecks during colonization and prolific clonal propagation. The prevalence of the ‘W’ genotype throughout the invasive range may be explained by stochastic sampling, or possibly because of pre‐adaptation of the ‘W’ genotype to tolerate low temperatures.
Sequential LMS for low-resource subband adaptive filtering: Oversampled implementation and polyphase analysis

The periodic and sequential partial update normalized LMS (P-NLMS and S-NLMS) algorithms and their variants are often used to reduce the computation cost of NLMS. In this paper, S-NLMS is employed in a low-resource subband adaptive filter implemented on an oversampled DFT filterbank. To analyze the system performance, we present a polyphase filterbank model for the P-NLMS and S-NLMS algorithms. It is shown that implicitly both algorithms employ perfect reconstruction delay chain analysis/synthesis filterbanks. As a result, the decimation involved in partial filter update does not introduce any steady-state performance degradation. The presented model can be employed to further predict and justify the convergence behavior of the partial update algorithms more accurately. Implementation of the S-NLMS algorithm on subband adaptive filters employing oversampled filterbanks is next described. Evaluation of the adaptive system performance shows that for stationary inputs, the S-NLMS algorithm (with proper step-size scaling) performs very similarly for moderate decimation factors of the S-NLMS.
"Is It Just Me?": Evaluating Attribution of Negative Feedback as a Function of Virtual Instructor's Gender and Proxemics

Virtual agents are used in a number of different outcome-based contexts such as physical and mental health, skill-based training, as well as classroom learning and pedagogy. Virtual agents in such applications are largely designed so that they project positive attitude and feedback towards the human participant. Human-human interactions, however, are certainly not exclusively positive in valence. For example, teachers and educators engage in both positive and negative feedback strategies for pedagogical outcomes. While the distinct effects of positive and negative feedback on learning are well established, few studies have attempted to examine the effects of negative feedback across different combinations of instructor's gender and proxemics-based physical behavior. This study explores this very question with a 2 (instructor gender)*2 (proxemic behavior) between subject design. In this experiment, participants (N=63) actively engage in a learning task with a male/female virtual instructor that provides negative feedback while either standing stationary or while physically approaching the participant. Based on the different deliveries of the negative feedback, the study aimed to identify the sources of variations in participant reactions to the negative feedback, namely patterns of attribution and both behavioral and physiological measurements of emotions. The results indicate that participants attribute greater self-blame (internal attribution) for their purported poor performance when interacting with the female virtual instructor than when interacting with the male virtual instructor. Participants also generally exhibited greater positive affect in response to female virtual professors than male virtual professors. These results are highly relevant both to the design of virtual agents as well as to adding to our understanding of the role of gender and behavior in human-human, non-peer interaction.
Summary Peoplewith schizophrenia have been categorised into three groups : thosewith

have been categorised into three groups: thosewith full insight (aware, correct attributers); those aware of beingunwell, butwhomisattributed their symptoms (aware, incorrect attributers); and those unaware of being ill (unaware). Cluster analysis of ‘awareness of illness’and ‘relabelling of symptoms’scores onthe Schedule for the Assessmentof Insight confirmed three distinct subgroups.The unaware groupwere impaired on executive andmemory tests, whereas those inthe aware, misattributing group were cognitively intact.Findings support an association betweenunawareness of illness and executive dysfunction, and highlightthe separation of symptom misattribution fromunawareness of illness.
CINNARIZINE LIQUID SOLID COMPACTS: PREPARATION EVALUATION

Objective: The objective of this research was to formulate cinnarizine tablets using the liquid-solid compact technique to enhance its solubility and dissolution rate.Methods: Cinnarizine liquid-solid compacts were formulated using propylene glycol as the non-volatile solvent, Neusilin US2 as the carrier material, Aerosil 200 as the coating material and croscarmellose sodium as the disintegrant. The interaction between drug and excipients were characterized by Fourier-transform infrared spectroscopy (FTIR) and differential scanning calorimetry (DSC) studies. Different batches of liquid, solid compacts were prepared by using varying carrier-coating excipient ratio and different concentration of liquid medication. Flow parameters such as bulk density, tapped density, Carr’s Index, Hausner’s Ratio as well as an angle of repose were used to test the flowability of the powder blend. The liquid-solid compacts were produced by direct compression method and were evaluated for tests such as weight variation, drug content, hardness, thickness, friability, wetting time, disintegration time as well as the in vitro dissolution studies.Results: The results of the preformulation studies of liquisolid compacts showed acceptable flow properties. The results of FTIR and DSC studies showed that there is no drug-excipient interactions. The different R values and concentrations were found to have a marked effect on the dissolution profile. Formulations with higher carrier: coating ratio (R-value) and lower drug concentrations displayed a better dissolution profile. The percentage of drug release of F3 with an R-value of 20 and a drug concentration of 10% was found to be 88.11% when compared to the conventional marketed tablet which released only 44.07% at the end of 2 h.Conclusion: From this research, it is inferred that liquid-solid technique is a promising and effective approach that can be used to enhance the dissolution rate of cinnarizine.
Answering N-Relation Natural Language Questions in the Commercial Domain

This paper presents SynchroBot, a Natural Language Question Answering system in the Commercial Domain. It relies on an RDF dataset and an RDFS ontology that we have developed for the commercial domain of the mobile phone industry. We propose an approach to understand and interpret natural language questions, based on the use of regular expressions to identify both the properties connecting entities, and their values. These regex are automatically learned from a subset of our dataset with a genetic algorithm.
Blue Light Sensing in Higher Plants*

Plants have evolved a range of sophisticated mechanisms to adapt and respond to their natural habitat. For example, plants rely heavily upon the surrounding light environment to direct their growth and development. Several different photoreceptor families are known to mediate the effects of light on plant development (1-3). These include the phytochrome (phy) family of photoreceptors, which monitor the red (600–700 nm) and far-red (700–750 nm) regions of the solar spectrum (4). In addition to the phytochromes, many important aspects of plant development are regulated by specific blue (390–500 nm) and/or UV-A (320–390 nm) light-absorbing receptors (5-7). Currently two classes of blue light receptors have been identified in plants: the cryptochromes and the phototropins. Here we briefly review the most recent advances in our understanding of blue light perception and signaling with an emphasis on the cryptochrome and phototropin photosensory systems.
Towards ubiquitous indoor localization service leveraging environmental physical features

Mainstream indoor localization technologies rely on RF signatures that require extensive human efforts to measure and periodically re-calibrate. Although recent crowdsourcing based work has started to address the issue, incentives are still lacking for wide user adoption. Thus the progress to ubiquitous localization remains slow. In this paper, we explore an alternative approach that leverages environmental physical features such as store logos or wall posters. A user uses a smartphone to obtain relative position measurements to such static reference points for the system to triangulate the user location. We study the principle of such localization, determine the suitable sensor, and devise guidelines for the user to choose reference points for better accuracy. To enable fast deployment, we propose a lightweight site survey method for service providers to quickly estimate the coordinates of reference points. We incorporate and enhance image matching algorithms with a heuristic technique to automatically identify chosen reference points at high accuracy. Extensive experiments have shown that the prototype achieves 4-5m accuracy at 80-percentile, comparable to the industry state-of-the-art, while covering a 150×75m mall and 300×200m train station requires a one time investment of only 2-3 man-hours from service providers.
Analysis of physical mechanisms for the detection of DNA in carbon nanotube field effect transistors for bio-sensing applications

This thesis discusses the use of carbon nanotube field effect transistors as sensors for DNA. It proposes a band-gap modulation as the underlying physical mechanism by which detection occurs. Previous works have established that either Schottky–barrier modulation or electro–static gating are the most significant mechanisms, depending on the particular device. By analyzing field effect mobilities it can be seen that the band-gap modulation effect shows up in every device and can be a reliable means by which detection of hybridized DNA molecules can occur.
A GENERALIZATION OF A CLASS OF BLIND SOURCE SEPARATION ALGORITHMS FOR CONVOLUTIVE MIXTURES

There are two main approaches for blind source separation (BSS) on time series using second-order statistics. One is to utilize the nonwhiteness property, and the other one is to utilize the nonstationarity property of the source signal. In this paper, we combine both approaches for convolutive mixtures using a matrix notation that leads to a number of new insights. We give rigorous derivations of the corresponding time-domain and frequency-domain approaches by generalizing a known cost function so that it inherently allows joint optimization for several time lags of the correlations. The approach is suitable for on-line and off-line algorithms by introducing a general weighting function allowing for tracking of time-varying environments. For both, the time-domain and frequency-domain versions, we discuss links to well-known and also to extended algorithms as special cases. Moreover, using the so-called generalized coherence, we establish links between the time-domain and frequency-domain algorithms and show that our cost function leads to an update equation with an inherent normalization.
Adaptive resource allocation in multiuser FDD-DMT systems

The performance of multiuser digital subscriber line (DSL) systems is constrained by crosstalk noise. This becomes especially noticeable in DSL systems that use high frequencies as in very high speed DSL (VDSL), since the crosstalk increases with frequency. To minimize the performance losses due to the crosstalk the users should coordinate and optimize their spectra with the aim of jointly maximizing the bit rates of all users. However, the multiuser DSL environment is modelled as a Gaussian interference channel and the rate region for this channel model is still an unsolved problem in information theory. This problem, for multiuser frequency division duplex discrete multi-tone (FDD-DMT) systems, is solved in a suboptimal way by our proposed Normalized-Rate Iterative Algorithm (NRIA). The NRIA determines optimized down- and upstream subcarrier allocations for the bundle and implicitly performs power control and power allocation for all users. In this paper we show, by simulation, that this algorithm achieves a significant performance improvement over existing standardized upstream power back-off (UPBO) and spectra plans in VDSL.
Plasmonic-Enhanced Organic Photovoltaic Devices for Low-Power Light Applications

In this study, we prepared plasmonic-enhanced organic photovoltaic (OPV) devices incorporating gold nanoparticles (Au NPs) for low-power lighting applications. Gold NP-decorated graphene oxides were incorporated into the hole-transporting and active layer layers of the OPVs to trigger plasmonic effects. After adding the Au NPs, the devices exhibited higher photocurrents and power conversion efficiencies (PCEs) under both 1-sun and low-level illumination conditions; PCE enhancement factors of greater than 20% were achieved. Most interestingly, the device enhancement factors were much higher under low-level lighting than they were under sunlight. We attribute the improvement in device efficiency to the localized surface plasmon resonance originating from the Au NPs.
Improving Sequential Decision Making with Cognitive Priming

Cognitive priming occurs when items or objects that are the focus of attention prime associated items in memory; these associations are learned over time between related items as an agent interacts with an environment. This mechanism guides attention toward associations relevant to the current situation and facilitates learning by retrieving those associated concepts from long-term memory. We apply priming to two sequential decision problems for the game of Minecraft: selecting the best tool to mine blocks and choosing the next subgoal in a maze. For learning tool selection, we leverage prior work that learned subgoal dependencies (e.g., wheat requires seeds) from the Minecraft community wiki. We apply these dependencies to train an associative memory that primes the selection of a tool for breaking a block and show that priming reduces the regret of choosing the incorrect tool. For subgoal selection, our prior work showed that decision trees can be learned to select the next subgoal for a simple variant of Minecraft. In two studies, we assess how well priming can select subgoals and show that priming performs comparably to decision trees. The first study shows that priming outperforms an incremental decision tree algorithm, while the second study examines the effect of noise in the training and testing data to show that priming performs comparably to a batch decision tree algorithm. Overall, these findings suggest that priming is an effective mechanism for either learning directly or for improving learning.
Student Satisfaction With Blackboard-Style Videos

Abstract Blackboard-style videos with simple drawings illustrating concepts have become immensely popular in recent years. However, there has been no published research evaluating their efficacy in nursing education. This pilot study evaluates the use of blackboard-style videos in an online pathophysiology course. Quantitative and qualitative evaluation data were analyzed to evaluate student satisfaction. The data indicated that students were highly satisfied with the course and the delivery of content using blackboard-style videos. The qualitative analysis uncovered two key themes explaining the high level of satisfaction: visual plus narrative explanations support learning and student control over pacing enhances learning.
Low-energy theory for superfluid and solid matter and its application to the neutron star crust

We formulate a low-energy effective theory describing phases of matter that are both solid and superfluid. These systems simultaneously break translational symmetry and the phase symmetry associated with particle number. The symmetries restrict the combinations of terms that can appear in the effective action and the lowest order terms featuring equal number of derivatives and Goldstone fields are completely specified by the thermodynamic free energy or, equivalently, by the long-wavelength limit of static correlation functions in the ground state. We show that the underlying interaction between particles that constitute the lattice and the superfluid gives rise to entrainment, and mixing between the Goldstone modes. As a concrete example we discuss the low-energy theory for the inner crust of a neutron star, where a lattice of ionized nuclei coexists with a neutron superfluid.
Replication study: androgen receptor splice variants determine taxane sensitivity in prostate cancer

In 2015, as part of the Prostate Cancer Foundation–Movember Foundation Reproducibility Initiative, we published a Registered Report (Shan et al., 2015) that described how we intended to replicate selected experiments from the paper “Androgen Receptor Splice Variants Determine Taxane Sensitivity in Prostate Cancer” (Thadani-Mulero et al., 2014). Here we report the results of those experiments. Growth of tumor xenografts from two prostate cancer xenograft lines, LuCaP 86.2, which expresses wild-type androgen receptor (AR) and AR variant 567, and LuCaP 23.1, which expresses wild-type AR and AR variant 7, were not affected by docetaxel treatment. The LuCaP 23.1 tumor xenografts grew slower than in the original study. This result is different from the original study, which reported significant reduction of tumor growth in the LuCaP 86.2. Furthermore, we were unable to detect ARv7 in the LuCaP 23.1, although we used the antibody as stated in the original study and ensured that it was detecting ARv7 via a known positive control (22rv1, Hörnberg et al., 2011). Finally, we report a meta-analysis of the result.
Relationship of SITA and full-threshold standard perimetry to frequency-doubling technology perimetry in glaucoma.

PURPOSE To compare full-threshold (FT) and SITA algorithms for standard automated perimetry (SAP) with frequency-doubling technology perimetry (FDT) in glaucoma, to help clinicians to relate results in patients who have had two or more of these tests during follow-up. METHODS This study was a retrospective analysis of data from a longitudinal prospective study at the University of California, San Diego. One hundred four eyes of 104 patients with glaucomatous optic neuropathy detected by optic disc stereophotographs were included. All patients had standard perimetry (SITA and FT) and FDT within 3 months of each other. Global indices, abnormality and severity using two threshold algorithms of standard perimetry were compared with FDT. RESULTS More eyes had normal visual fields by SAP-FT (57 eyes) than by either SAP-SITA (42 eyes) or FDT (45 eyes), although SAP-FT agreed more closely with FDT (kappa = 0.54 +/- 0.08) on the presence of a visual field defect than did SAP-SITA (kappa = 0.34 +/- 0.08). Correlations of FDT to standard perimetry global indices were similar regardless of the threshold strategy used for standard perimetry, yielding r2= 0.38-0.57 for SAP-FT with FDT, 0.36-0.54 for SAP-SITA with FDT. CONCLUSIONS Despite many similarities of SAP-SITA and SAP-FT, switching the standard of comparison from SAP-FT to SAP-SITA changes the relationship to FDT with regard to visual field abnormality, but not correlations of global indices. FDT detected abnormal fields in more eyes than SAP-FT. SAP-FT tended to detect a subset of eyes found abnormal by FDT. Visual field defects may be detected more often by FDT and SAP-SITA in eyes with early visual field loss, but these two tests may not agree on which eyes show field loss in patients who undergo both tests at follow-up.