Miracle-dz/UniFAR-FTUs huggingface dataset:
LINKING BEES AND FLOWERS: HOW DO FLORAL COMMUNITIES STRUCTURE POLLINATOR COMMUNITIES?

Pollinators provide essential ecosystem services, and declines in some pollinator communities around the world have been reported. Understanding the fundamental components defining these communities is essential if conservation and restoration are to be successful. We examined the structure of plant-pollinator communities in a dynamic Mediterranean landscape, comprising a mosaic of post-fire regenerating habitats, and which is a recognized global hotspot for bee diversity. Each community was characterized by a highly skewed species abundance distribution, with a few dominant and many rare bee species, and was consistent with a log series model indicating that a few environmental factors govern the community. Floral community composition, the quantity and quality of forage resources present, and the geographic locality organized bee communities at various levels: (1) The overall structure of the bee community (116 species), as revealed through ordination, was dependent upon nectar resource diversity (defined as the variety of nectar volume-concentration combinations available), the ratio of pollen to nectar energy, floral diversity, floral abundance, and post-fire age. (2) Bee diversity, measured as species richness, was closely linked to floral diversity (especially of annuals), nectar resource diversity, and post-fire age of the habitat. (3) The abundance of the most common species was primarily related to post-fire age, grazing intensity, and nesting substrate availability. Ordination models based on age-characteristic post-fire floral community structure explained 39-50% of overall variation observed in bee community structure. Cluster analysis showed that all the communities shared a high degree of similarity in their species composition (27-59%); however, the geographical location of sites also contributed a smaller but significant component to bee community structure. We conclude that floral resources act in specific and previously unexplored ways to modulate the diversity of the local geographic species pool, with specific disturbance factors, superimposed upon these patterns, mainly affecting the dominant species.
Modeling Chronic Traumatic Encephalopathy: The Way Forward for Future Discovery

Despite the extensive media coverage associated with the diagnosis of chronic traumatic encephalopathy (CTE), our fundamental understanding of the disease pathophysiology remains in its infancy. Only recently have scientific laboratories and personnel begun to explore CTE pathophysiology through the use of preclinical models of neurotrauma. Some studies have shown the ability to recapitulate some aspects of CTE in rodent models, through the use of various neuropathological, biochemical, and/or behavioral assays. Many questions related to CTE development, however, remain unanswered. These include the role of impact severity, the time interval between impacts, the age at which impacts occur, and the total number of impacts sustained. Other important variables such as the location of impacts, character of impacts, and effect of environment/lifestyle and genetics also warrant further study. In this work, we attempt to address some of these questions by exploring work previously completed using single- and repetitive-injury paradigms. Despite some models producing some deficits similar to CTE symptoms, it is clear that further studies are required to understand the development of neuropathological and neurobehavioral features consistent with CTE-like features in rodents. Specifically, acute and chronic studies are needed that characterize the development of tau-based pathology.
Weighted sum rate maximization in the MIMO MAC with linear transceivers: Asymptotic results

We present asymptotic results for the weighted sum rate maximization in a MIMO multiple access channel with individual power constraints when the noise power at the receiver becomes small and linear filtering is applied at the transceivers. The key parameter that determines the optimum signaling strategy is the number of antennas at the base station. If there are more antennas than the user terminals have in sum, the asymptotically optimum transmit covariance matrices are scaled identities, whereas scaled rank-deficient projectors have to be chosen when the base station does not have enough degrees of freedom. We derive the optimum transmit covariance matrices for both antenna configurations and shed some light on the impact of the solutions on the underlying rate region structure. In addition, the impact of the optimum transmission strategy on the convex hull of the underlying rate region is demonstrated.
Aurora B kinase and protein phosphatase 1 have opposing roles in modulating kinetochore assembly

The outer kinetochore binds microtubules to control chromosome movement. Outer kinetochore assembly is restricted to mitosis, whereas the inner kinetochore remains tethered to centromeres throughout the cell cycle. The cues that regulate this transient assembly are unknown. We find that inhibition of Aurora B kinase significantly reduces outer kinetochore assembly in Xenopus laevis and human tissue culture cells, frog egg extracts, and budding yeast. In X. leavis M phase extracts, preassembled kinetochores disassemble after inhibiting Aurora B activity with either drugs or antibodies. Kinetochore disassembly, induced by Aurora B inhibition, is rescued by restraining protein phosphatase 1 (PP1) activity. PP1 is necessary for kinetochores to disassemble at the exit from M phase, and purified enzyme is sufficient to cause disassembly on isolated mitotic nuclei. These data demonstrate that Aurora B activity is required for kinetochore maintenance and that PP1 is necessary and sufficient to disassemble kinetochores. We suggest that Aurora B and PP1 coordinate cell cycle–dependent changes in kinetochore assembly though phosphorylation of kinetochore substrates.
Toward kilo-instruction processors

The continuously increasing gap between processor and memory speeds is a serious limitation to the performance achievable by future microprocessors. Currently, processors tolerate long-latency memory operations largely by maintaining a high number of in-flight instructions. In the future, this may require supporting many hundreds, or even thousands, of in-flight instructions. Unfortunately, the traditional approach of scaling up critical processor structures to provide such support is impractical at these levels, due to area, power, and cycle time constraints.In this paper we show that, in order to overcome this resource-scalability problem, the way in which critical processor resources are managed must be changed. Instead of simply upsizing the processor structures, we propose a smarter use of the available resources, supported by a selective checkpointing mechanism. This mechanism allows instructions to commit out of order, and makes a reorder buffer unnecessary. We present a set of techniques such as multilevel instruction queues, late allocation and early release of registers, and early release of load/store queue entries. All together, these techniques constitute what we call a kilo-instruction processor, an architecture that can support thousands of in-flight instructions, and thus may achieve high performance even in the presence of large memory access latencies.
Experience as an Object to Think with: from Sensing-in-action to Making-Sense of action in Full-Body Interaction Learning Environments

We present a qualitative, idiographic study aimed at exploring how children create bridges between embodied experience and meaning construction while interacting with a Full-Body Interaction Learning Environment. Starting from the analysis of four case studies, we illustrate different possible paths through which children can transform embodied experience into an 'object--to-think-with' and delineate the different resources for meaning making that they employed. These outcomes contribute to expand the current understanding around embodied learning with interactive technologies, as well as suggest a set of qualities to think about interaction design and future research.
A Nonlocal Maximum Likelihood Estimation Method for Rician Noise Reduction in MR Images

Postacquisition denoising of magnetic resonance (MR) images is of importance for clinical diagnosis and computerized analysis, such as tissue classification and segmentation. It has been shown that the noise in MR magnitude images follows a Rician distribution, which is signal-dependent when signal-to-noise ratio (SNR) is low. It is particularly difficult to remove the random fluctuations and bias introduced by Rician noise. The objective of this paper is to estimate the noise free signal from MR magnitude images. We model images as random fields and assume that pixels which have similar neighborhoods come from the same distribution. We propose a nonlocal maximum likelihood (NLML) estimation method for Rician noise reduction. Our method yields an optimal estimation result that is more accurate in recovering the true signal from Rician noise than NL means algorithm in the sense of SNR, contrast, and method error. We demonstrate that NLML performs better than the conventional local maximum likelihood (LML) estimation method in preserving and defining sharp tissue boundaries in terms of a well-defined sharpness metric while also having superior performance in method error.
The Carioca High and Low Conditioned Freezing Lines: A New Animal Model of Generalized Anxiety Disorder

Fear and anxiety are complex concepts. Both terms have been used to describe a set of highly orchestrated neural events that involve sensory processing and motor responses triggered by threatening situations. These events are mediated by central neural circuitries and peripheral neuroendocrine pathways and clearly have adaptive value. Sensory systems function as alerting signals to warn of real or potential danger, producing a shift to a state of high vigilance that prepares the individual to avoid or escape from a wide variety of dangerous situations. Most of these reactions are not exclusive to our species. Because of their importance for survival, fear and anxiety traits are believed to have been selected in human evolution and shaped by natural selection for their crucial role in protecting individuals who face adverse environments (Coutinho et al., 2010; Gross & Hen, 2004; Marks & Nesse, 1994). However, these highly adaptive events can be disabling when the individual experiences them excessively or when they occur in the absence of threatening stimuli. In these cases, they represent a pathological condition termed an anxiety disorder. Often chronic in nature, these disorders are among the most prevalent mental health problems across the individual life span, producing severe impairments in social and occupational functioning. According to an evolutionary perspective, an anxiety disorder reflects a malfunctioning of the neural circuits responsible for detecting, organizing, or expressing adaptive defense reactions (Jacobson & Cryan, 2010). Humans and nonhuman mammals share approximately the same behavioral defense strategies, reflected by activation of similar underlying neural circuitry. Therefore, animal models of anxiety can be extremely helpful for better understanding the behavioral, neural, and genetic substrates involved in these pathologies. The purpose of the present chapter is to present two new lines of rats that might be a useful model of generalized anxiety disorder (GAD). Before we discuss this model, defining how anxiety disorders are currently classified is important.
The transition in the contribution of living aquatic resources to food security

The fishing industry's aggressive and expanding search for fish from the sea reached a turning point in 1990. After many years of increasing production, the global marine and inland catch from natural stocks declined from the 1989 peak of about 89 million tons to 85 million tons in 1993. Aquaculture production did not increase enough to meet the shortfall, and total production also fell in 1990 and 199. Present indications are that production from natural stocks will be below the current level in the year 2020; at best, it will maintain its present level. The author addresses five major issues: (1) maximizing the use of aquatic resources; (2) resource management; (3) intensification of fisheries exploitation; (4) integration of fisheries and aquaculture; and (5) the difficult problem of balancing national versus international interests.
Components of conscious awareness in a long-term modality effect

The advantage in long-term recognition memory of words vocalized at study over those read silently was investigated by requiring subjects to indicate when recognizing a word whether or not they could consciously recollect its prior occurrence. The advantage for vocalization occurred only for words which subjects indicated were accompanied by recollective experience, and the results were not affected by whether subjects vocalized the test words or read them silently. It is concluded that this modality effect, and possibly other similar ones, originate in episodic memory and not in a procedural or ‘quasimemory’ system. Differences between the present results and those obtained elsewhere using intentional learning instructions are discussed.
Introducing Causality and Traceability in Word-of-Mouth Algorithms

Understanding the spread of information in a social network has proven useful in numerous areas, with viral marketing and epidimeology being two of the more prominent ones. Word-of-mouth algorithms are one class of algorithms that have been developed to model how information is verbally spread in a social network. However, two significant limitations of current word-of-mouth algorithms are their inability to: (1) capture when communication or contacts take place and (2) explain where the information possessed by each individual came from. In this paper, we present a novel word-of-mouth algorithm that addresses these drawbacks by considering the temporality of communication and by tracing the spread of influence within a social network. The traces of influence prove useful for the identification of the most important individuals in a social network and for inferring causality. We apply the proposed algorithm to a large set of call detail records (CDRs) and validate it via simulations of word-of-mouth traces. Our two main findings are that (1) influence is better understood when the temporal dimension is added to the model and (2) the spread of information and influence in a network has several statistical invariants.
Cross-ownership and concentration in MIBEL: Liberalization and integration experience

The liberalization of electricity market in Europe during the 90's and the European aim of integrating energy national markets aimed mainly increase efficiency and decreasing energy prices for consumers. Nevertheless, a wave of mergers and acquisitions reduce the number of independent players in the market and increases the concern about market concentration and his effects on market power. In our research we follow Maxwell et al (1999) and we derive a generalized HHI (GHHI). Our concern is to evaluate the evolution of the degree of concentration in key moments for both Iberian markets separately and after the integration. The question asked in our work is if and to what extent the creation of ownership ties between generation firms can re-establish market power and undo what the liberalization and integration has achieved.
Adherence to prescribing recommendations made on a provincial formulary.

Guidance regarding appropriate and cost-effective use of prescription drugs is published in the Ontario Drug Benefit Formulary in the form of "therapeutic notes. " We conducted a cross-sectional study of all residents of Ontario aged 66 and older who received a new prescription for one of two drugs, aliskiren or sitagliptin, between December 1, 2008 and March 31, 2012 to determine how frequently such guidance is followed. Approximately half of initial prescriptions for aliskiren and sitagliptin were prescribed in a manner that did not conform to the therapeutic note recommendations (51.4% and 49.3%, respectively). Given this high rate of non-conformance, policy makers may wish to use other mechanisms to influence prescriber behaviour to improve the quality and efficiency of healthcare.
Predictors of mental health care stigma and its association with the therapeutic alliance during the initial intake session

Abstract Objective: We investigated the association between socio-demographic and clinical variables with mental health care stigma, and the impact of the latter on the quality of the therapeutic alliance measured at intake. Method: Consecutive clients (N = 236) filled questionnaires upon accessing services for a new episode of care. Immediately following the intake, a randomly selected sample of clients and their corresponding therapists (n = 102) completed the Working Alliance Inventory – Bond Scale. Results: Lower mean years of education and higher emotional distress (both partial r = .17) were significantly associated with higher stigma. Higher care stigma negatively correlated with therapists' ratings of the therapeutic alliance during the intake (partial r = −.22), but not with those of clients. Conclusions: Care stigma is present among service-users and may affect outcomes of the intake.
Social network analysis and software evolution: A perspective method for software architecture analysis

Present day software is largely composed of smaller manageable units which work together to overcome a larger problem. Considering software system as a network of connected software elements, e.g. service oriented architecture, it would be eligible to methods for analyzing networks, e.g. social network analysis. This paper presents a theoretical foundation for applying social network analysis on service oriented architecture and deriving technique for analysis of a software system focusing on the evolution, architectural decisions and non-functional properties (maintainability, dependability, availability).
Optical Imaging of Intrinsic Signals in Chinchilla Auditory Cortex

We have assessed sound frequency and intensity responses in primary auditory cortex of the (ketamine) anesthetized chinchilla using optical imaging of intrinsic signals. Temporal cortex was exposed via a 10-mm craniotomy and a windowed chamber was mounted. A 4-second period of gated tones (10 ms rise/fall; 50 ms plateau; 10/s) was presented to the contralateral ear at levels between 0 and 80 dB SPL. The cortical surface was illuminated with 540 nm light and video images captured in 0.5-second bins for 7.5 s (Imager 2001; Optical Imaging). Intrinsic signals were first apparent 0.5–1 s after stimulus onset, and were maximal after 3–4 s; they decayed over several seconds. The cortical area in which intrinsic activity was detected corresponded closely with electrophysiologically defined AI cortex. Intrinsic signals can reliably be detected to stimuli at 30–40 dB SPL, and in general, the area of intrinsic signal activity tends to expand with increasing stimulation level. Using stimulation levels of 80 dB SPL, we show that low-frequency stimuli (0.5–1 kHz) evoke intrinsic signals in anterior areas whilst posterior areas are activated by high-frequency stimuli (e.g. 16 kHz). Thus a low- to high-frequency tonotopic organization is seen along this axis.
Moderate and Severe Microcytic Anemia in the Emergency Department: Indicators of Care

Iron deficiency anemia (IDA) occurs in 4% to 8% of children aged 12 to 36 months. Health implications include poor growth and cognitive and motor developmental delay. Recent studies have suggested that opportunities exist to identify children at risk for IDA in the emergency department (ED). This study aimed to explore physician adherence to indicators of care in the management of young children with moderate to severe microcytic anemia in the ED.
The relative validity of psychopathy versus risk/needs-based assessments in the prediction of adolescent offending behaviour

Purpose. The predictive validity of the psychopathy checklist-youth version (PCL:YV) and Youth Level of Service/Case Management Inventory (YLS/CMI) for juvenile offenders were compared to examine whether a broad needs–risk tool predicted violence better than a focused individual assessment of psychopathy. Methods. 94 adolescents from residential and secure units were interviewed and assessed using the PCL:YV and YLS/CMI. Total scores were retrospectively applied to staff-recorded incidents of violence, total number of charges and convictions and formally recorded assaults. The predictive accuracy of each tool was assessed using correlational and receiver operator characteristic analyses. Results. The PCL:YV was a better predictor of staff-recorded violence than the YLS/CMI; both instruments were similar in their ability to predict total number of charges and convictions and assaults. When subdivided by gender, the correlations for predicting staff recorded violence in male participants were significantly higher than for female participants for both test instruments. Both instruments were broadly equivalent in their association with assaults and charges and convictions by gender. Conclusion. The PCL:YV is a better predictor of recorded violence than the YLS/CMI, but for charges and convictions and assaults, the YLS/CMI and PCL:YV were comparable for UK adolescent offenders. When recalculated to exclude the likelihood of predictor–criterion overlap, the results were the same. These findings are discussed in relation to the value of using risk–needs assessment instruments as compared with scales with a more psychopathological and personality focus.
Tracking job performance trajectories over time: A six-year longitudinal study

There is considerable interest in moving beyond static investigations of job performance to studying the dynamics of job performance over relatively long periods of time. In the present research, we investigated the development of job performance using a large sample of 420 employees followed over a six-year period for which yearly job performance evaluations by managers were available. Latent growth models indicated the presence of a nonlinear trajectory, with alternating phases of stability, sharp increase, and abrupt decrease. Level of education, the perception of one’s direct supervisor, and self-efficacy significantly predicted individual job performance levels observed at Wave 2. Quadratic job tenure, level of education, the perception of one’s direct supervisor, and self-efficacy were found to be significant predictors of job performance development. Findings are discussed in the light of their implications for future studies examining job performance longitudinally.
Study on Fast Human Activity Recognition Based on Optimized Feature Selection

Sensor-based human activity recognition has attracted much scholarly attention due to its merit of wide applicability. However, because of such hardware limitations as battery capacity and computing power, most current generation of wearable devices cannot yet benefit from those activity recognition methods based on deep learning theory and high dimension features since implementing these methods are time-consuming and need a relatively large amount of calculation. A solution, therefore, is proposed for this situation, which aims to reduce computational complexity by reducing the feature dimension through analyzing the linear correlation between the features. Based on the support vector machine model of single-layer fully connected network, the training and recognition time are significantly reduced while the recognition accuracy is still ensured. The experiment is based on the public dataset in the UCI Machine Learning Repository, and it uses Caffe, a deep learning framework, to structure the support vector machine model. In the experiment, when the feature dimension is reduced from 561 to 130, the training time can be reduced by 70% while the recognition accuracy is kept at a promising 91%.