Miracle-dz/UniFAR-FTUs huggingface dataset:
Female extrapair mate choice in a cooperative breeder: trading sex for help and increasing offspring heterozygosity

Sexual conflict between males and females over mating is common. Females that copulate with extrapair mates outside the pair-bond may gain (i) direct benefits such as resources or increased paternal care, (ii) indirect genetic benefits for their offspring, or (iii) insurance against infertility in their own social mate. Few studies have been able to demonstrate the different contexts in which females receive varying types of benefits from extrapair mates. Here, I examined sexual conflict, female extrapair mate choice, and patterns of extrapair paternity in the cooperatively breeding superb starling Lamprotornis superbus using microsatellite markers. Although extrapair paternity was lower than many other avian cooperative breeders (14% of offspring and 25% of nests), females exhibited two distinct mating patterns: half of the extrapair fertilizations were with males from inside the group, whereas half were with males from outside the group. Females with few potential helpers copulated with extrapair mates from within their group and thereby gained direct benefits in the form of additional helpers at the nest, whereas females paired to mates that were relatively less heterozygous than themselves copulated with extrapair mates from outside the group and thereby gained indirect genetic benefits in the form of increased offspring heterozygosity. Females did not appear to gain fertility insurance from copulating with extrapair mates. This is the first study to show that individuals from the same population mate with extrapair males and gain both direct and indirect benefits, but that they do so in different contexts.
Predicting patients' expectations of hospital chaplains: a multisite survey.

OBJECTIVE To identify patient expectations regarding chaplain visitation, characteristics of patients who want to be visited by a chaplain, and what patients deem important when a chaplain visits. PARTICIPANTS AND METHODS Three weeks after discharge, 4500 eligible medical and surgical patients from hospitals in Minnesota, Arizona, and Florida were surveyed by mail to collect demographic information and expectations regarding chaplain visitation. The survey was conducted during the following time periods: Minnesota participants, April 6 until April 25, 2006; Arizona participants, October 16, 2008, until January 13, 2009; Florida participants, October 16, 2008, until January 20, 2009. Categorical variables were summarized with frequencies or percentages. Associations between responses and site were examined using χ(2) tests. Multivariate logistic regression was used to assess the likelihood of wanting chaplain visitation on the basis of patient demographics and perceived importance of reasons for chaplain visitation. RESULTS About one-third of those surveyed responded from each site. Most were male, married, aged 56 years or older, and Protestant or Catholic. Of the respondents, nearly 70% reported wanting chaplain visitation, 43% were visited, and 81% indicated that visitation was important. The strongest predictor of wanting chaplain visitation was denomination vs no indicated religious affiliation (Catholic: odds ratio [OR], 8.11; 95% confidence interval [CI], 4.49-14.64; P<.001; evangelical Protestant: OR, 4.95; 95% CI, 2.74-8.91; P<.001; mainline Protestant: OR, 4.34; 95% CI, 2.58-7.29; P<.001). Being female was a weak predictor (OR, 1.48; 95% CI, 1.05-2.09; P=.03), as was site. Among the reasons given by respondents for wanting chaplain visitation, the most important were that chaplains served as reminders of God's care and presence (OR, 4.37; 95% CI, 2.58-7.40; P<.001) and that they provided prayer or scripture reading (OR, 2.54; 95% CI, 1.53-4.20; P<.001). CONCLUSION The results of this study suggest the importance medical and surgical patients place on being visited by a chaplain while they are hospitalized. Those who valued chaplains because they reminded them of God's care and presence and/or because they prayed or read scripture with them were more likely to desire a visit. Our results also suggest that being religiously affiliated is a very strong predictor of wanting chaplain visitation.
Large-scale extraction of gene interactions from full-text literature using DeepDive

Motivation: A complete repository of gene–gene interactions is key for understanding cellular processes, human disease and drug response. These gene–gene interactions include both protein–protein interactions and transcription factor interactions. The majority of known interactions are found in the biomedical literature. Interaction databases, such as BioGRID and ChEA, annotate these gene–gene interactions; however, curation becomes difficult as the literature grows exponentially. DeepDive is a trained system for extracting information from a variety of sources, including text. In this work, we used DeepDive to extract both protein–protein and transcription factor interactions from over 100 000 full-text PLOS articles. Methods: We built an extractor for gene–gene interactions that identified candidate gene–gene relations within an input sentence. For each candidate relation, DeepDive computed a probability that the relation was a correct interaction. We evaluated this system against the Database of Interacting Proteins and against randomly curated extractions. Results: Our system achieved 76% precision and 49% recall in extracting direct and indirect interactions involving gene symbols co-occurring in a sentence. For randomly curated extractions, the system achieved between 62% and 83% precision based on direct or indirect interactions, as well as sentence-level and document-level precision. Overall, our system extracted 3356 unique gene pairs using 724 features from over 100 000 full-text articles. Availability and implementation: Application source code is publicly available at https://github.com/edoughty/deepdive_genegene_app Contact: russ.altman@stanford.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Sustained Reduction of Seizures in Patients with Intractable Epilepsy after Self-Regulation Training of Slow Cortical Potentials – 10 Years After

The aim of this study was to determine whether the reduction of seizures in patients with intractable epilepsy after self-regulation of slow cortical potentials (SCPs) was maintained almost 10 years after the end of treatment. Originally, 41 patients received training with SCP-neurofeedback. A control group of 12 patients received respiratory feedback while another group of 11 patients had their anticonvulsant medications reviewed. Nineteen patients in the experimental group participated at least in parts of the long-term follow-up, but only two patients from each control group agreed to do so. The follow-up participants completed the same seizure diaries as in the original study. Patients of the experimental group also took part in three SCP-training sessions at the follow-up evaluation. Due to the small sample size, the results of participants in the control groups were not considered in the analysis. A significant decrease in seizure frequency was found about 10 years after the end of SCP treatment. The clinical significance of this result is considered medium to high. All patients were still able to self-regulate their SCPs during the feedback condition. This success was achieved without booster sessions. This is the longest follow-up evaluation of the outcome of a psychophysiological treatment in patients with epilepsy ever reported. Reduced seizure frequency may be the result of patients continued ability to self-regulate their SCPs. Given such a long follow-up period, the possible impact of confounding variables should be taken into account. The small number of patients participating in this follow-up evaluation diminishes the ability to make causal inferences. However, the consistency and duration of improvement for patients who received SCP-feedback training suggests that such treatment may be considered as a treatment for patients with intractable epilepsy and as an adjunct to conventional therapies.
A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae)

Genomic sequencing is no longer a novelty, but gene function annotation remains a key challenge in modern biology. A variety of functional genomics experimental techniques are available, from classic methods such as affinity precipitation to advanced high-throughput techniques such as gene expression microarrays. In the future, more disparate methods will be developed, further increasing the need for integrated computational analysis of data generated by these studies. We address this problem with magic (Multisource Association of Genes by Integration of Clusters), a general framework that uses formal Bayesian reasoning to integrate heterogeneous types of high-throughput biological data (such as large-scale two-hybrid screens and multiple microarray analyses) for accurate gene function prediction. The system formally incorporates expert knowledge about relative accuracies of data sources to combine them within a normative framework. magic provides a belief level with its output that allows the user to vary the stringency of predictions. We applied magic to Saccharomyces cerevisiae genetic and physical interactions, microarray, and transcription factor binding sites data and assessed the biological relevance of gene groupings using Gene Ontology annotations produced by the Saccaromyces Genome Database. We found that by creating functional groupings based on heterogeneous data types, magic improved accuracy of the groupings compared with microarray analysis alone. We describe several of the biological gene groupings identified.
Active and passive mid-infrared photonic devices in ZnSe based materials

The work described in this thesis details the development of mid-infrared waveguide laser sources created through the fabrication of waveguide structures in Cr 2+ : ZnSe using ultrafast laser inscription (ULI). Current quantum cascade laser (QCL) technology in the 2 – 5 μm region offer compact and robust sources suited to use outside the laboratory but the technology does not offer the high average powers, >100 mW, and wide tuneability, 2 – 3.3 μm of Cr 2+ : ZnSe laser sources. The development of a Cr 2+ : ZnSe waveguide laser source provides an environmentally robust product with access to powers and tuneable ranges greater than that provided by QCL systems. The first phase of the investigation produced the first successful refractive index modification of ZnSe using ULI. Both positive and negative refractive index changes were achieved and utilised to fabricate a range of waveguides in ZnSe and Cr 2+ : ZnSe. Low loss near-infrared waveguides were demonstrated through exploitation of the positive refractive index change. Low loss mid-infrared depressed cladding waveguides were subsequently demonstrated utilising the negative refractive index change. These waveguides were characterised at wavelengths of 1928, 2300 and 3390 nm as representative of pump and signal wavelengths in Cr 2+ : ZnSe laser systems. Finally, the newly fabricated Cr 2+ : ZnSe waveguides were constructed into waveguide laser cavities and pumped with a thulium fibre laser source operating at 1928 nm. Laser operation is demonstrated in both waveguides devices at wavelengths of 2573 and 2486 nm with a maximum achieved output power of 285 mW and a slope efficiency of 45%. Furthermore, a tuneable laser source is constructed in the Littman-Metcalf configuration exhibiting a maximum tuning range of 510 nm, 2330-2840 nm, with output powers exceeding 25 mW across the full range. These waveguide laser devices offer an environmentally robust and compact source in the 2 – 3 μm region with improvements upon maximum power and tuneability ranges in current quantum cascade laser sources. The waveguide laser sources reported open the door to products offering the robust nature of QCL sources with the higher powers and 2 – 3 μm tuneability associated with current bulk Cr 2+ : ZnSe laser systems.
North/South Differences Among Italian Emerging Adults Regarding Criteria Deemed Important for Adulthood and Life Satisfaction

The main goal of this study was to compare Northern and Southern Italian emerging adult university students, regarding the importance attributed to criteria for adulthood and the levels of life and education satisfaction. Self-report questionnaires were filled by 475 Northern and Southern Italian University students (Age M = 22.91, 76% females, n = 359). Multivariate analysis of variance revealed that Southern emerging adults were more likely to place importance on family capacities, norm compliance, interdependence and role transitions as criteria for achieving adulthood than Northern emerging adults. Regarding gender differences, females were more likely to believe in the importance of norm compliance than males, while males were more likely to espouse the importance of legal transitions. Finally, emerging adults from the North reported higher levels of life satisfaction than their Southern counterparts. We interpreted these findings in light of socio-economical and gender socialization differences among Northern and Southern Italian emerging adults.
Perioperative Blood Glucose Monitoring in the General Surgical Population

Several studies have shown a relationship between poor outcome and uncontrolled blood glucose (BG) in cardiac, neurosurgical, critical care, and general surgical patients. A major study showed that tight glycemic control (80–110mg/dl) was related to increased mortality. Based on evidence from controlled studies, the American Diabetes Association, and the Society of Thoracic Surgeons, maintaining intraoperative BG levels in the 140–180 mg/dl range seems appropriate. Optimization of the patient's preoperative medications and the use of insulin infusions, as well as surgical and anesthetic technique, are important factors for achieving desirable perioperative BG control. Minimizing BG variability during surgery should be part of the glycemic control strategy. Advances in real-time glucose monitoring may soon benefit hospitalized diabetes and nondiabetes patients.
Itelmenite, Na2CuMg2(SO4)4, a new anhydrous sulfate mineral from the Tolbachik volcano

ABSTRACT Itelmenite, ideally Na2CuMg2(SO4)4, was found in a fumarole of the Naboko scoria cone of the Tolbachik volcano Fissure Eruption (2012–2013), Kamchatka Peninsula, Russia. Itelmenite occurs as irregularly shaped grains as well as microcrystalline masses associated with anhydrite, saranchinaite, hermannjahnite, euchlorine, thénardite, aphthitalite and hematite. Itelmenite is orthorhombic, Pbca, a = 9.568(2) Å, b = 8.790(2) Å, c = 28.715(8) Å, V = 2415.0(11) Å3 and Z = 4 (from single-crystal diffraction data). The nine strongest lines of the powder X-ray diffraction pattern are [d(I)(hkl)]: 7.9614(41)(102), 7.1803(32)(004), 5.9122(64)(112), 3.8455(87)(122), 3.6292(52)(214), 3.3931(62)(215), 3.0003(44)(027), 2.9388(100)(312) and 2.4975(56)(230). The chemical composition determined by the electron-microprobe analysis is (wt.%): Na2O 10.77, K2O 0.20, MgO 11.10, CuO 15.38, ZnO 5.61, SO3 56.42, total 99.48. The empirical formula based on O = 32 apfu is (Na3.93K0.05)Σ3. 98Mg3.12(Cu2.19Zn0.78)Σ2. 97S7.97O32. The simplified formula is Na2CuMg2(SO4)4 taking into account structural data. The crystal structure was solved by direct methods and refined to an agreement index R1 = 0.034 on the basis of 1855 independent observed reflections. The structure of itelmenite is based on a unique type of [A2+3(SO4)4]2– (A = Mg, Cu and Zn) heteropolyhedral framework with voids filled by Na+ cations.
Receptor-Like Tyrosine Phosphatase PTP10D Is Required for Long-Term Memory in Drosophila

Tyrosine phosphorylation mediates multiple signal transduction pathways that play key roles in developmental processes and behavioral plasticity. The level of tyrosine phosphorylation is regulated by protein tyrosine kinases and protein tyrosine phosphatases (PTPs). Extensive studies have investigated the roles of tyrosine kinases in memory formation. However, there were few studies on PTPs. To date, learning has been shown to be defective only for mouse knock-outs of PTPα, leukocyte common antigen-related, or PTPδ. A major limitation of these studies arises from their inability to distinguish an acute (biochemical) impairment of memory formation from a more chronic abnormality in neurodevelopment. From a behavioral screen for defective long-term memory, we found chi mutants to disrupt expression of the PTP10D protein tyrosine phosphatase gene. We show that chi mutants are normal for learning, early memory, and anesthesia-resistant memory, whereas long-term memory specifically is abolished. Significantly, induction of a heat shock-PTP10D+ transgene before training fully rescues the memory defect of chi mutants, thereby demonstrating an acute role for PTP10D in behavioral plasticity. We show that PTP10D is widely expressed in the embryonic CNS and in the adult brain. Transgenic expression of upstream activating sequence-PTP10D+ in mushroom bodies is sufficient to rescue the memory defect of chi mutants. Our data clearly demonstrate that signaling through PTP10D in mushroom bodies is critical for the formation of long-term memory.
Efficient online learning for opportunistic spectrum access

The problem of opportunistic spectrum access in cognitive radio networks has been recently formulated as a non-Bayesian restless multi-armed bandit problem. In this problem, there are N arms (corresponding to channels) and one player (corresponding to a secondary user). The state of each arm evolves as a finite-state Markov chain with unknown parameters. At each time slot, the player can select K <; N arms to play and receives state-dependent rewards (corresponding to the throughput obtained given the activity of primary users). The objective is to maximize the expected total rewards (i.e., total throughput) obtained over multiple plays. The performance of an algorithm for such a multi-armed bandit problem is measured in terms of regret, defined as the difference in expected reward compared to a model-aware genie who always plays the best K arms. In this paper, we propose a new continuous exploration and exploitation (CEE) algorithm for this problem. When no information is available about the dynamics of the arms, CEE is the first algorithm to guarantee near-logarithmic regret uniformly over time. When some bounds corresponding to the stationary state distributions and the state-dependent rewards are known, we show that CEE can be easily modified to achieve logarithmic regret over time. In contrast, prior algorithms require additional information concerning bounds on the second eigenvalues of the transition matrices in order to guarantee logarithmic regret. Finally, we show through numerical simulations that CEE is more efficient than prior algorithms.
Evaluations of Climate and Land Management Effects on Lake Carbon Cycling Need to Account for Temporal Variability in CO2 Concentrations

Carbon dioxide (CO2) concentrations in lakes vary strongly over time. This variability is rarely captured by environmental monitoring but is crucial for accurately assessing the magnitude of lake CO2 emissions. However, it is unknown to what extent temporal variability needs to be captured to understand important drivers of lake carbon cycling such as climate and land management. We used environmental monitoring data of Swedish forest lakes collected in autumn (n = 439) and throughout the whole open water season (n = 22) from a wet and a dry year to assess temporal variability in effects of climate and forestry on CO2 concentrations across lakes. Effects differed depending on the season and year sampled. According to cross‐lake comparisons based on autumn data, CO2 concentrations increased with annual mean air temperature (dry year) or catchment forest productivity (wet year) but were not related to colored dissolved organic matter concentrations. In contrast, open water‐season averaged CO2 concentrations were similar across temperature and productivity gradients but increased with colored dissolved organic matter. These contradictions resulted from scale mismatches in input data, lead to weak explanatory power (R2 = 9–32%), and were consistent across published data from 79 temperate, boreal, and arctic lakes. In a global survey of 144 published studies, we identified a trade‐off between temporal and spatial coverage of CO2 sampling. This trade‐off clearly determines which conclusions are drawn from landscape‐scale CO2 assessments. Accurate evaluations of the effects of climate and land management require spatially and temporally representative data that can be provided by emerging sensor technologies and forms of collaborative sampling.
Stela: Enabling Stream Processing Systems to Scale-in and Scale-out On-demand

The era of big data has led to the emergence of new real-time distributed stream processing engines like Apache Storm. We present Stela (STream processing ELAsticity), a stream processing system that supports scale-out and scale-in operations in an on-demand manner, i.e., when the user requests such a scaling operation. Stela meets two goals: 1) it optimizes post-scaling throughput, and 2) it minimizes interruption to the ongoing computation while the scaling operation is being carried out. We have integrated Stela into Apache Storm. We present experimental results using micro-benchmark Storm applications, as well as production applications from industry (Yahoo! Inc. and IBM). Our experiments show that compared to Apache Storm's default scheduler, Stela's scale-out operation achieves throughput that is 21-120% higher, and interruption time that is significantly smaller. Stela's scale-in operation chooses the right set of servers to remove and achieves 2X-5X higher throughput than Storm's default strategy.
Choice-Supportive Misremembering: A New Taxonomy and Review

Although the literature on the influence of memory on decisions is well developed, research on the effects of decision making on memory is rather sparse and scattered. Choice-supportive misremembering (i.e., misremembering choice-related information that boosts the chosen option and/or demotes the foregone options) has been observed in several studies and has the potential to affect future choices. Nonetheless, no attempt has been made to review the relevant literature, categorize the different types of choice-supportive misremembering observed, and critically appraise the existing evidence and proposed explanations. Thus, starting from a new theoretically motivated and empirically grounded taxonomy, we review the current research. Our taxonomy classifies choice-supportive misremembering into four conceptually distinct types: misattribution is when information is attributed to the wrong source, fact distortion when the facts are remembered in a distorted manner, false memory when items that were not part of the original decision scenarios are remembered as presented and, finally, selective forgetting is when information is selectively forgotten. After assessing the impact of various potentially moderating factors, we evaluate the evidence for each type of misremembering and conclude that the support for the phenomenon is solid in relation to misattribution when recognition memory is assessed, but significantly weaker for the other three types, and when other memory tests are used to assess memory. Finally, we review the cognitive and emotional explanations proposed for choice-supportive misremembering in the light of the available evidence and identify the main gaps in the current knowledge and the more promising avenues for future research.