Miracle-dz/UniFAR-FTUs huggingface dataset:
Psychotic-like experiences with cannabis use predict cannabis cessation and desire to quit: a cannabis discontinuation hypothesis

Abstract Background Evidence suggests that cannabis-induced psychotic-like experiences may be a marker of psychosis proneness. The effect of such experiences on cannabis use has not systematically been examined. Methods We undertook a mixed-methods online survey of 1231 cannabis users (including 926 continued users) using the Cannabis Experiences Questionnaire. We examined the effect of psychotic-like and pleasurable experiences on cessation of cannabis and intention to quit. Socio-demographic variables, cannabis use parameters and substance misuse history were included as covariates. Free-text data explored subjective reasons for changes in use. Results Cessation of cannabis use was associated with greater psychotic-like experiences [p < 0.001, Exp(B) 1.262, 95% confidence interval (CI) 1.179–1.351], whilst continued cannabis users were more likely to report pleasurable experiences [p < 0.001, Exp(B) 0.717, 95% CI 0.662–0.776]. Intention to quit cannabis in continued users was associated with greater psychotic-like experiences [p < 0.003, Exp(B) 1.131, 95% CI 1.044–1.225], whilst intention to not quit was significantly associated with increased pleasurable experiences [p < 0.015, Exp(B) 0.892, 95% CI 0.814–0.978]. Whereas former users clearly ascribed cessation to negative experiences, continued users who expressed intention to quit less readily ascribed the intention to negative experiences. Conclusions Elucidation of psychotic-like experiences may form the basis of a therapeutic intervention for those who wish to quit. Cessation in those with cannabis-induced psychotomimetic experiences may offset the risk for the development of a psychotic disorder, in this higher risk group.
Understanding the role of memory subsystem on performance and energy-efficiency of Hadoop applications

The memory subsystem has always been one of the performance bottlenecks in computer systems. Given the large size of data, therefore, the questions of whether Big Data requires big memory and whether main memory subsystem plays an intrinsic role in the performance and energy-efficiency of Big Data are becoming important. In this paper, through a comprehensive real-system experimental analysis of performance, power and resource utilization, we have evaluated main memory characteristic of Hadoop MapReduce, a de facto standard for big data analytics. Through a methodical experimental setup we have analyzed the impact of DRAM capacity, operating frequency, and the number of channels on power and performance to understand the main memory requirements of this important Big Data framework. The characterization results across various Hadoop MapReduce applications from different domains illustrate that Hadoop MapReduce workloads show two distinct behaviors of being either CPU-intensive or Disk-intensive. Our experimental results showed that DRAM frequency as well as number of channels do not play a significant role on the performance of Hadoop workloads. On the other hand, our results indicate that increasing the number of DRAM channels reduces DRAM power and improves the energy-efficiency of Hadoop MapReduce applications.
Accounting for Negative Automaintenance in Pigeons: A Dual Learning Systems Approach and Factored Representations

Animals, including Humans, are prone to develop persistent maladaptive and suboptimal behaviours. Some of these behaviours have been suggested to arise from interactions between brain systems of Pavlovian conditioning, the acquisition of responses to initially neutral stimuli previously paired with rewards, and instrumental conditioning, the acquisition of active behaviours leading to rewards. However the mechanics of these systems and their interactions are still unclear. While extensively studied independently, few models have been developed to account for these interactions. On some experiment, pigeons have been observed to display a maladaptive behaviour that some suggest to involve conflicts between Pavlovian and instrumental conditioning. In a procedure referred as negative automaintenance, a key light is paired with the subsequent delivery of food, however any peck towards the key light results in the omission of the reward. Studies showed that in such procedure some pigeons persisted in pecking to a substantial level despite its negative consequence, while others learned to refrain from pecking and maximized their cumulative rewards. Furthermore, the pigeons that were unable to refrain from pecking could nevertheless shift their pecks towards a harmless alternative key light. We confronted a computational model that combines dual-learning systems and factored representations, recently developed to account for sign-tracking and goal-tracking behaviours in rats, to these negative automaintenance experimental data. We show that it can explain the variability of the observed behaviours and the capacity of alternative key lights to distract pigeons from their detrimental behaviours. These results confirm the proposed model as an interesting tool to reproduce experiments that could involve interactions between Pavlovian and instrumental conditioning. The model allows us to draw predictions that may be experimentally verified, which could help further investigate the neural mechanisms underlying theses interactions.
Effect of bottom sediment on content, bioaccumulation and translocation of heavy metals in maize biomass.

The research aimed to assess the effect of bottom sediment on the content, bioaccumulation and translocation of heavy metals in maize biomass. The investigations were conducted in 2006-2007 as a pot experiment on light soil of the granulometric composition of weakly-loamy sand. The experimental design comprised 3 treatments: without sediment (I), a 5% sediment admixture (II) and a 10% sediment admixture to the soil (III). Bottom sediment was added to the soil in the first year of the investigations. The content of Zn, Cu, Ni. Pb, Cd and Cr was determined using the ICP-EAS method in the plant material after its dry mineralization and ash solution in HNO3. The uptake of the above-mentioned metals by maize was computed alongside their bioaccumulation and translocation coefficients. The effect of bottom sediment admixture on heavy metal concentrations in maize was determined to be varied, e.g. a 5% dose of sediment added to soil decreased the content of all the analyzed heavy metals in the biomass of maize aerial parts, whereas a 10% admixture increased the content of Cu, Ni, Pb and Cr. The values of bioaccumulation coefficients revealed that an admixture of both doses of bottom sediment led to a decreased accumulation of Zn, Cu, Cd, Cr and Ni (5% dose) in maize aerial biomass. Moreover, the plant more easily accumulated Zn, Cd and Cu than Cr, Ni or Pb. Permissible amounts of heavy metals in plants to be used as animal fodder were not exceeded in the maize biomass.
Mycoplasma genitalium in Women: Current Knowledge and Research Priorities for This Recently Emerged Pathogen

Health consequences of sexually transmitted diseases disproportionately affect women, making it important to determine whether newly emerged pathogens cause sequelae. Although the pathogenic role of Mycoplasma genitalium in male urethritis is clear, fewer studies have been conducted among women to determine its pathogenic role in the female reproductive tract. Pelvic inflammatory disease (PID) is an important cause of infertility and ectopic pregnancy, and Chlamydia trachomatis and Neisseria gonorrhoeae are recognized microbial causes. Emerging data demonstrate an association between M. genitalium and PID, and limited data suggest associations with infertility and preterm birth, yet the attributable risk for female genital tract infections remains to be defined. Further investigations are needed to better define the impact of M. genitalium on women's reproductive health. Importantly, prospective studies evaluating whether screening programs and targeted treatment of M. genitalium improve reproductive outcomes in women are necessary to guide public health policy for this emerging pathogen.
Mechanical properties of nacre constituents and their impact on mechanical performance

The mechanical properties of nacre constituents from red abalone were investigated. Electron microscopy studies revealed that the tablets are composed of single-crystal aragonite with nanograin inclusions. Both nanoasperities and aragonite bridges are present within the interfaces between the tablets. By means of nanoindentation and axial compression tests, we identified single tablet elastic and inelastic properties. The elastic properties are very similar to those of single-crystal aragonite. However, their strength is higher than previously reported values for aragonite. A finite element model of the interface accounting for nanoasperities and the identified properties revealed that the nanoasperities are strong enough to withstand climbing and resist tablet sliding, at least over the initial stages of deformation. Furthermore, it was observed that the model over-predicts strength and under-predicts ductility. Therefore, we conclude that other interface features must be responsible for the enhanced performance of nacre over its constituents.
Nonlinear Deconvolution by Sampling Biophysically Plausible Hemodynamic Models.

Non-invasive methods to measure brain activity are important to understand cognitive processes in the human brain. A prominent example is functional magnetic resonance imaging (fMRI), which is a noisy measurement of a delayed signal that depends non-linearly on the neuronal activity through the neurovascular coupling. These characteristics make the inference of neuronal activity from fMRI a difficult but important step in fMRI studies that require information at the neuronal level. In this article, we address this inference problem using a Bayesian approach where we model the latent neural activity as a stochastic process and assume that the observed BOLD signal results from a realistic physiological (Balloon) model. We apply a recently developed smoothing method called APIS to efficiently sample the posterior given single event fMRI time series. To infer neuronal signals with high likelihood for multiple time series efficiently, a modification of the original algorithm is introduced. We demonstrate that our adaptive procedure is able to compensate the lacking of inputs in the model to infer the neuronal activity and that it outperforms dramatically the standard bootstrap particle filter-smoother in this setting. This makes the proposed procedure especially attractive to deconvolve resting state fMRI data. To validate the method, we evaluate the quality of the signals inferred using the timing information contained in them. APIS obtains reliable event timing estimates based on fMRI data gathered during a reaction time experiment with short stimuli. Hence, we show for the first time that one can obtain accurate absolute timing of neuronal activity by reconstructing the latent neural signal.
Estimation of the effective thermal properties of cracked rocks

In geo-engineering applications, the effective thermal properties (ETPs) of cracked rock are strongly dependent on the configuration of the cracks and the thermal properties of the saturating fluid, which differs from that of the rock matrix. In this study, methods for predicting the ETPs of cracked rock are investigated. The effects of various factors such as the crack distribution, the type of saturating fluid and the applied stress on the ETPs are analysed. Formulas for the effective thermal conductivity (ETC) and the effective thermal expansion (ETE) are developed in a discrete form based on the homogenisation method, where the interactions of the cracks in different directions are neglected. To analyse the effects of the crack distribution and the type of saturating fluid on the ETC and the ETE, an example of saturated rock with one family of cracks is considered. The results reveal that the crack distribution has a significant anisotropic effect on both the ETC and the ETE. The difference in the bulk moduli of the rock matrix and the fluid in the cracks also has an important effect on the ETE. The behaviour of the ETC and the ETE of granite at various levels of stress is analysed with triaxial compression tests. The growth of microcracks induced by the applied stresses causes significant anisotropy in both the ETC and the ETE. This study provides insight into the factors that affect the ETC and the ETE and methods to estimate the ETC and the ETE of cracked rock in geo-engineering applications.
Effect of Oral Supplementation of Putrescine and L-glutamine on the Histomorphology of Small Intestine and Growth Performance in Broiler Chickens

A work was conducted to study the effect of putrescine and L-glutamine supplementation on histomorphology of small intestine in broiler chickens. Five groups of ten chicks each in three replicates reared up to 42 days were used for this study. Putrescine and L-glutamine were orally supplemented at 0% level as control (T1), putrescine 0.05% (T2), putrescine 0.1% (T3), L-glutamine 0.5% (T4) and L-glutamine 1% (T5) from 0 day to 7 days after hatch. At 2nd and 3rd week of age, 3 birds from each groupwere slaughtered and tissue samples from small intestine (duodenum, jejunum and ileum) were collected for histomorphological studies. Statistically significant (p<0.01) increase in duodenal and jejunal villi length, width,crypt length and ileal villi length and width were observed in L-glutamine fed groups than putrescine and control groups. There was no significant difference in duodenal crypt length/width, jejunal crypt width and ileal crypt length/width. It can be inferred that L-glutamine promoted the intestinal villi development during early posthatch life, thus increasing the nutrients absorption and growth performance as body weight gain in broiler chickens.
Both Baseline and Change in Lower Limb Muscle Strength in Younger Women Are Independent Predictors of Balance in Middle Age: A 12‐Year Population‐Based Prospective Study

Poor balance is a risk factor for falls and fracture in older adults, but little is known about modifiable factors affecting balance in younger women. This study aimed to examine whether lower limb muscle strength (LMS) in young women and changes in LMS are independent predictors of balance in middle age. This was an observational 10‐year follow‐up of 470 women aged 25 to 44 years at baseline who had previously participated in a 2‐year population‐based randomized controlled trial of osteoporosis education interventions. Linear regression was used to examine the association between baseline LMS (by dynamometer) and change in LMS over 12 years with balance at 12 years (timed up and go test [TUG], step test [ST], functional reach test [FRT], and lateral reach test [LRT]). LMS declined by a mean of 17.3 kg over 12 years. After adjustment for potential confounders, baseline and change in LMS were independently beneficially associated with TUG (β = –0.008 sec/kg, 95% confidence interval [CI] –0.01 to –0.006, and β = –0.006 sec/kg, 95% CI –0.009 to –0.003 for baseline and change, respectively), FRT (β = 0.057 cm/kg, 95% CI 0.030 to 0.084, and β = 0.071 cm/kg, 95% CI 0.042 to 0.101, respectively), and LRT (β = 0.030 cm/kg, 95% CI 0.012 to 0.049, and β = 0.022 cm/kg, 95% CI 0.002 to 0.043, respectively) 12 years later. There was an association between baseline LMS and ST (β = 0.044 steps/kg, 95% CI 0.022 to 0.067) but not between change in LMS and ST. Among young women, greater LMS at baseline and slower decline over time are both associated with better balance in midlife. Analogous to the contributions of peak bone mass and bone loss to fracture risk in older adults, this suggests that both improvement of muscle strength in younger age and prevention of age‐related loss of muscle strength could be potentially useful strategies to improve balance and reduce falls in later life. © 2017 American Society for Bone and Mineral Research.
Genomic differences between nasal Staphylococcus aureus from hog slaughterhouse workers and their communities

New human pathogens can emerge from the livestock-human interface and spread into human populations through many pathways including livestock products. Occupational contact with livestock is a risk factor for exposure to those pathogens and may cause further spreading of those pathogens in the community. The current study used whole genome sequencing to explore nasal Staphylococcus aureus obtained from hog slaughterhouse workers and their community members, all of whom resided in a livestock-dense region in rural North Carolina. Sequence data were analyzed for lineage distribution, pathogenicity-related genomic features, and mobile genetic elements. We observed evidence of nasal S. aureus differences between hog workers and non-workers. Nasal S. aureus from hog workers showed a greater lineage diversity than nasal S. aureus from community residents. Hog worker isolates were less likely to carry the φSa3 prophage and human-specific immune evasion cluster genes than community resident isolates (φSa3 prophage: 54.5% vs. 91.7%, Benjamini-Hochberg (BH) corrected p = 0.035; immune evasion cluster genes: 66.7% vs. 100%, BH p = 0.021). Hog worker isolates had a lower prevalence and diversity of enterotoxins than community resident isolates, particularly lacking the enterotoxin gene cluster (39.4% vs. 70.8%, BH p = 0.125). Moreover, hog worker isolates harbored more diverse antibiotic resistance genes, with a higher prevalence of carriage of multiple resistance genes, than community resident isolates (75.8% vs. 29.2%, BH p = 0.021). Phylogenetic analysis of all ST5 isolates, the most abundant lineage in the collection, further supported separation of isolates from hog workers and non-workers. Together, our observations suggest impact of occupational contact with livestock on nasal S. aureus colonization and highlight the need for further research on the complex epidemiology of S. aureus at the livestock-human interface.
Simple and Complex Centromeric Satellites in Drosophila Sibling Species

Centromeres are the chromosomal sites of assembly for kinetochores, the protein complexes that attach to spindle fibers and mediate separation of chromosomes to daughter cells in mitosis and meiosis. In most multicellular organisms, centromeres comprise a single specific family of tandem repeats—often 100–400 bp in length—found on every chromosome, typically in one location within heterochromatin. Drosophila melanogaster is unusual in that the heterochromatin contains many families of mostly short (5–12 bp) tandem repeats, none of which appear to be present at all centromeres, and none of which are found only at centromeres. Although centromere sequences from a minichromosome have been identified and candidate centromere sequences have been proposed, the DNA sequences at native Drosophila centromeres remain unknown. Here we use native chromatin immunoprecipitation to identify the centromeric sequences bound by the foundational kinetochore protein cenH3, known in vertebrates as CENP-A. In D. melanogaster, these sequences include a few families of 5- and 10-bp repeats; but in closely related D. simulans, the centromeres comprise more complex repeats. The results suggest that a recent expansion of short repeats has replaced more complex centromeric repeats in D. melanogaster.
First report of Toumeyella parvicornis (Cockerell) in Europe (Hemiptera: Coccidae).

Toumeyella parvicornis (Cockerell), the Pine tortoise scale, is reported for the first time from Europe. Pre-imaginal instars and adults were observed starting from the fall of 2014 in several municipalities of Campania (Italy). Since the species is recorded as a harmful pest of several pine species in North America and the Caribbean, the presence of this alien insect in Europe is alarming and represents a possible major threat for native pine species and related economic activities.
Computing Fractional Laplacians on Complex-Geometry Domains: Algorithms and Simulations

We consider a fractional Laplacian defined in bounded domains by the eigen-decomposition of the integer-order Laplacian, and demonstrate how to compute very accurately (using the spectral element method) the eigenspectrum and corresponding eigenfunctions in two-dimensional prototype complex-geometry domains. We then employ these eigenfunctions as trial and test bases to first solve the fractional diffusion equation, and subsequently to simulate two-phase flow based on the Navier--Stokes equations combined with a fractional Allen--Cahn mass-preserving model. A key point to the effectiveness of an exponential convergence of this approach is the use of a weighted Gram--Schmidt orthonormalization of the eigenfunctions that guarantees accurate projection and recovery of spectral accuracy for smooth solutions. We demonstrate that even when only part of the eigenspectrum is computed accurately we can still obtain exponential convergence if we employ the complete set of the eigenvectors of the discrete Laplacian.
Design principles for nonequilibrium self-assembly

Significance Understanding the principles governing self-assembly remains an important problem in statistical mechanics. We find, surprisingly, that general design principles for this challenging problem can be obtained by applying ideas from the field of stochastic thermodynamics to nonequilibrium self-assembly problems. Our central results constrain the set of possible configurations achievable under a nonequilibrium drive. We consider an important class of self-assembly problems, and using the formalism of stochastic thermodynamics, we derive a set of design principles for growing controlled assemblies far from equilibrium. The design principles constrain the set of configurations that can be obtained under nonequilibrium conditions. Our central result provides intuition for how equilibrium self-assembly landscapes are modified under finite nonequilibrium drive.
Risk Stratification Methods and Provision of Care Management Services in Comprehensive Primary Care Initiative Practices

PURPOSE Risk-stratified care management is essential to improving population health in primary care settings, but evidence is limited on the type of risk stratification method and its association with care management services. METHODS We describe risk stratification patterns and association with care management services for primary care practices in the Comprehensive Primary Care (CPC) initiative. We undertook a qualitative approach to categorize risk stratification methods being used by CPC practices and tested whether these stratification methods were associated with delivery of care management services. RESULTS CPC practices reported using 4 primary methods to stratify risk for their patient populations: a practice-developed algorithm (n = 215), the American Academy of Family Physicians’ clinical algorithm (n = 155), payer claims and electronic health records (n = 62), and clinical intuition (n = 52). CPC practices using practice-developed algorithm identified the most number of high-risk patients per primary care physician (282 patients, P = .006). CPC practices using clinical intuition had the most high-risk patients in care management and a greater proportion of high-risk patients receiving care management per primary care physician (91 patients and 48%, P =.036 and P =.128, respectively). CONCLUSIONS CPC practices used 4 primary methods to identify high-risk patients. Although practices that developed their own algorithm identified the greatest number of high-risk patients, practices that used clinical intuition connected the greatest proportion of patients to care management services.