Miracle-dz/UniFAR-FTUs huggingface dataset:
Medium access control in distributed cognitive radio networks

Since cognitive radio technology can significantly boost spectrum utilization by exploiting radio spectrum unused by licensed users, it is rapidly gaining popularity and inspiring numerous applications. However, many technical issues still need to be addressed for successful deployment of CR networks, especially in the MAC layer. We focus on CR networks that have distributed architecture because they offer ease of deployment, self-organizing capability, and flexibility in design, and are believed to be more practical for future deployments compared to their centralized counterparts. The MAC protocols for distributed CR networks should consider the key features of these networks such as lack of a central unit to coordinate the communication, dynamic topology, requirements to keep interference to primary users minimal, and variation of spectrum availability with time and location. To clarify the relevant research challenges and issues, we provide a detailed study of the critical design issues and an overview of current state-of-the-art MAC protocols proposed for DCRNs. A classification of existing proposals is provided, and their salient features, advantages, and limitations are discussed. We then introduce and study a novel MAC protocol that addresses some of the research issues better than existing solutions. We also highlight important research challenges that could drive future research in this area.
Optimizing stability bounds of finite-precision PID controller structures

This paper investigates a recently derived lower bound stability measure for sampled-data controller structures subject to finite-wordlength (FWL) constraints. The optimal realization of the digital PID controller with FWL considerations is formulated as a nonlinear optimization problem, and an efficient strategy based on adaptive simulated annealing (ASA) is adopted to solve this complex optimization problem. A numerical example of optimizing the finite-precision PID controller structure for a simulated steel rolling mill system is presented to illustrate the effectiveness of the proposed strategy.
Dynamic preload markers to predict fluid responsiveness during and after major gastrointestinal surgery: an observational substudy of the OPTIMISE trial.

BACKGROUND Stroke volume variation (SVV) and pulse pressure variation (PPV), termed dynamic markers of preload responsiveness, may predict the response to i.v. fluid in critically ill patients. However, the predictive accuracy of these variables during gastrointestinal surgery remains uncertain. METHODS Observational study of patients aged ≥50 yr undergoing major gastrointestinal surgery, enrolled in the OPTIMISE trial. Patients received six 250 ml fluid challenges with i.v. colloid solution (three during and three after surgery), while SVV and PPV were measured using the LiDCOrapid monitor (LiDCO Ltd, UK). Fluid responsiveness was defined as a stroke volume increase ≥10%. Area under the receiver operating characteristic curve was calculated with 95% confidence intervals. Adjustment for covariates was performed by regression modelling and a clustering method was used to adjust for intra-patient correlation. RESULTS One hundred patients were recruited between August 2010 and October 2012. Five hundred and fifty-six fluid challenges were administered and 159 (28.6%) were associated with increased stroke volume. The predictive value of both variables was poor during surgery [SVV 0.69 (0.63-0.77); PPV 0.70 (0.62-0.77)], and also after surgery [SVV 0.69 (0.63-0.78); PPV 0.64 (0.56-0.73)]. The findings were similar when analysed according to whether patients were mechanically ventilated [SVV 0.68 (0.63-0.77); PPV 0.69 (0.61-0.77)] or breathing spontaneously [SVV 0.69 (0.61-0.77); PPV 0.63 (0.56-0.72)]. Predictive value improved slightly in a sensitivity analysis excluding outlier values of SVV and PPV. CONCLUSIONS In this study, the predictive accuracy of SVV and PPV for fluid responsiveness was insufficient to recommend for routine clinical use during or after major gastrointestinal surgery.
Human but Not Yeast CHD1 Binds Directly and Selectively to Histone H3 Methylated at Lysine 4 via Its Tandem Chromodomains*

Defining the protein factors that directly recognize post-translational, covalent histone modifications is essential toward understanding the impact of these chromatin “marks” on gene regulation. In the current study, we identify human CHD1, an ATP-dependent chromatin remodeling protein, as a factor that directly and selectively recognizes histone H3 methylated on lysine 4. In vitro binding studies identified that CHD1 recognizes di- and trimethyl H3K4 with a dissociation constant (Kd) of ∼5 μm, whereas monomethyl H3K4 binds CHD1 with a 3-fold lower affinity. Surprisingly, human CHD1 binds to methylated H3K4 in a manner that requires both of its tandem chromodomains. In vitro analyses demonstrate that unlike human CHD1, yeast Chd1 does not bind methylated H3K4. Our findings indicate that yeast and human CHD1 have diverged in their ability to discriminate covalently modified histones and link histone modification-recognition and non-covalent chromatin remodeling activities within a single human protein.
Predictive Analytics in Information Systems Research

textabstractThis research essay highlights the need to integrate predictive analytics into information systems research and shows several concrete ways in which this goal can be accomplished. Predictive analytics include empirical methods (statistical and other) that generate data predictions as well as methods for assessing predictive power. Predictive analytics not only assist in creating practically useful models, they also play an important role alongside explanatory modeling in theory building and theory testing. We describe six roles for predictive analytics: new theory generation, measurement development, comparison of competing theories, improvement of existing models, relevance assessment, and assessment of the predictability of empirical phenomena. Despite the importance of predictive analytics, we find that they are rare in the empirical IS literature. Extant IS literature relies nearly exclusively on explanatory statistical modeling, where statistical inference is used to test and evaluate the explanatory power of underlying causal models, and predictive power is assumed to follow automatically from the explanatory model. However, explanatory power does not imply predictive power and thus predictive analytics are necessary for assessing predictive power and for building empirical models that predict well. To show that predictive analytics and explanatory statistical modeling are fundamentally disparate, we show that they are different in each step of the modeling process. These differences translate into different final models, so that a pure explanatory statistical model is best tuned for testing causal hypotheses and a pure predictive model is best in terms of predictive power. We convert a well-known explanatory paper on TAM to a predictive context to illustrate these differences and show how predictive analytics can add theoretical and practical value to IS research.
Birth Trauma to the Vertebral Arteries

Birth is a very traumatic event. This is particularly emphasized by the frequency of intracranial haemorrhage and cerebral damage in the newborn infant. However, the greatest manipulative strain in all methods of delivery is imposed on the infant's neck and it is therefore surprising that there have been very few investigations of this region except following breech delivery. Moreover none of the reports records the effects of trauma on the cervical portions of the vertebral arteries, two of the principal vessels supplying the brain. It is the purpose of this paper to draw attention to traumatic lesions in the necks of infants delivered by a variety of methods who died round about the time of birth, and to indicate their possible significance in the production of damage to the brain.
The role of reactive oxygen species in methamphetamine self‐administration and dopamine release in the nucleus accumbens

Methamphetamine (METH) markedly increases dopamine (DA) release in the mesolimbic DA system, which plays an important role in mediating the reinforcing effects of METH. METH‐induced DA release results in the formation of reactive oxygen species (ROS), leading to oxidative damage. We have recently reported that ROS are implicated in behavior changes and DA release in the nucleus accumbens (NAc) following cocaine administration. The aim of this study was to evaluate the involvement of ROS in METH‐induced locomotor activity, self‐administration and enhancement of DA release in the NAc. Systemic administration of a non‐specific ROS scavenger, N‐tert‐butyl‐α‐phenylnitrone (PBN; 0, 50 and 75 mg/kg, IP) or a superoxide‐selective scavenger, 4‐hydroxy‐2,2,6,6‐tetramethylpiperidine‐1‐oxyl (TEMPOL; 0, 50 and 100 mg/kg, IP), attenuated METH‐induced locomotor activity without affecting generalized behavior in METH‐naïve rats. PBN and TEMPOL significantly attenuated METH self‐administration without affecting food intake. Increased oxidative stress was found in neurons, but not astrocytes, microglia or oligodendrocytes, in the NAc of METH self‐administering rats. In addition, TEMPOL significantly decreased METH enhancement of DA release in the NAc. Taken together, these results suggest that enhancement of ROS in the NAc contributes to the reinforcing effect of METH.
Max-Margin Tensor Neural Network for Chinese Word Segmentation

Recently, neural network models for natural language processing tasks have been increasingly focused on for their ability to alleviate the burden of manual feature engineering. In this paper, we propose a novel neural network model for Chinese word segmentation called Max-Margin Tensor Neural Network (MMTNN). By exploiting tag embeddings and tensorbased transformation, MMTNN has the ability to model complicated interactions between tags and context characters. Furthermore, a new tensor factorization approach is proposed to speed up the model and avoid overfitting. Experiments on the benchmark dataset show that our model achieves better performances than previous neural network models and that our model can achieve a competitive performance with minimal feature engineering. Despite Chinese word segmentation being a specific case, MMTNN can be easily generalized and applied to other sequence labeling tasks.
Endogenous Metabolites‐Mediated Communication Between OAT1/OAT3 and OATP1B1 May Explain the Association Between SLCO1B1 SNPs and Methotrexate Toxicity

Although OATP1B1 is not expressed in the kidney, polymorphisms in SLCO1B1 have been associated with methotrexate clearance or toxicity. This unexpected pharmacogenetic association may reflect remote communication between liver and kidney transporters. This study confirms the pharmacogenetic association with methotrexate toxicity in adult patients with hematological malignancies. Using a targeted urinary metabolomics approach, we identified 38 and 34 metabolites which were differentially excreted between wildtype and carriers of the c.388A>G or c.521T>C variant alleles, respectively, half of them being associated with methotrexate toxicity. These metabolites mainly consisted of fatty acid derivatives and microbiota catabolites, including glycine conjugates and other uremic toxins, all known OATs substrates. These results suggest that dysfunction of a transporter affects the excretion profile of endogenous or exogenous substrates, possibly through metabolite‐mediated interactions involving other transport systems, even in distant organs. This opens the way for better comprehension of complex pharmacokinetics and transporter‐mediated drug–drug or nutrient–drug interactions.
Directing human neural stem/precursor cells into oligodendrocytes by overexpression of Olig2 transcription factor

Multipotential neural stem/precursor cells of the central nervous system were extensively studied for their properties of generating myelinating oligodendrocytes both in vitro and in vivo upon engraftment in animal models of myelin disorders, such as leucodystrophy and multiple sclerosis. These studies provided proof‐of‐principle that efficient myelination can be achieved by cell transplantation. However, one major drawback of cell‐based therapy of myelin diseases is the difficulty in generating oligodendrocytes efficiently from human fetal neural stem/precursor cells (hNPC). Here we explored whether overexpression of the basic helix‐loop‐helix (bHLH) transcription factor Olig2 in fetal hNPC could enhance the generation of oligodendrocytes both in vitro and in vivo. We report that transduction of hNPC with Olig2‐encoding lentiviral vectors enhances their commitment toward an oligodendroglial fate. Moreover, Olig2‐transduced hNPC, grafted into the dysmyelinated shiverer mouse brain, survived up to 9 weeks, migrated extensively, and differentiated into MBP+ myelinating oligodendrocytes. In contrast, control hNPC remained at a less mature stage and generated very few myelinating oligodendrocytes. Our study indicates that bHLH transcription factors, such as Olig2, are interesting targets for directing hNPC into myelinating oligodendrocytes. © 2009 Wiley‐Liss, Inc.
Reverse Engineering the Amen Break — Score-Informed Separation and Restoration Applied to Drum Recordings

This work addresses the extraction of high-quality component signals from drum solo recordings (breakbeats) for music production and remixing purposes. Specifically, we employ audio source separation techniques to recover sound events from the drum sound mixture corresponding to the individual drum strokes. Our separation approach is based on an informed variant of non-negative matrix factor deconvolution (NMFD) that has been proposed and applied to drum transcription and separation in earlier works. In this paper, we systematically study the suitability of NMFD and the impact of audio- and score-based side information in the context of drum separation. In the case of imperfect decompositions, we observe different cross-talk artifacts appearing during the attack and the decay segment of the extracted drum sounds. Based on these findings, we propose and evaluate two extensions to the core technique. The first extension is based on applying a cascaded NMFD decomposition while retaining selected side information. The second extension is a time–frequency selective restoration approach using a dictionary of single note drum sounds. For all our experiments, we use a publicly available data set consisting of multitrack drum recordings and corresponding annotations that allows us to evaluate the source separation quality. Using this test set, we show that our proposed methods improve the quality of the component signals.
Physics-Based Visual Characterization of Molecular Interaction Forces

Molecular simulations are used in many areas of biotechnology, such as drug design and enzyme engineering. Despite the development of automatic computational protocols, analysis of molecular interactions is still a major aspect where human comprehension and intuition are key to accelerate, analyze, and propose modifications to the molecule of interest. Most visualization algorithms help the users by providing an accurate depiction of the spatial arrangement: the atoms involved in inter-molecular contacts. There are few tools that provide visual information on the forces governing molecular docking. However, these tools, commonly restricted to close interaction between atoms, do not consider whole simulation paths, long-range distances and, importantly, do not provide visual cues for a quick and intuitive comprehension of the energy functions (modeling intermolecular interactions) involved. In this paper, we propose visualizations designed to enable the characterization of interaction forces by taking into account several relevant variables such as molecule-ligand distance and the energy function, which is essential to understand binding affinities. We put emphasis on mapping molecular docking paths obtained from Molecular Dynamics or Monte Carlo simulations, and provide time-dependent visualizations for different energy components and particle resolutions: atoms, groups or residues. The presented visualizations have the potential to support domain experts in a more efficient drug or enzyme design process.
Influence of Running and Walking on Hormonal Regulators of Appetite in Women

Nine female runners and ten walkers completed a 60 min moderate-intensity (70% VO2max) run or walk, or 60 min rest in counterbalanced order. Plasma concentrations of the orexogenic peptide ghrelin, anorexogenic peptides peptide YY (PYY), glucagon-like peptide-1 (GLP-1), and appetite ratings were measured at 30 min interval for 120 min, followed by a free-choice meal. Both orexogenic and anorexogenic peptides were elevated after running, but no changes were observed after walking. Relative energy intake (adjusted for cost of exercise/rest) was negative in the meal following running (−194 ± 206 kcal) versus walking (41 ± 196 kcal) (P = 0.015), although both were suppressed (P < 0.05) compared to rest (299 ± 308 and 284 ± 121 kcal, resp.). The average rate of change in PYY and GLP-1 over time predicted appetite in runners, but only the change in GLP-1 predicted hunger (P = 0.05) in walkers. Results provide evidence that exercise-induced alterations in appetite are likely driven by complex changes in appetite-regulating hormones rather than change in a single gut peptide.
The abundance and colours of galaxies in high-redshift clusters in the cold dark matter cosmology

High-redshift galaxy clusters allow us to examine galaxy formation in extreme environments. Here we compile data for 15 z > 1 galaxy clusters to test the predictions from a state-of-the-art semi-analytical model of galaxy formation. The model gives a good match to the slope and zero-point of the cluster red sequence. The model is able to match the cluster galaxy luminosity function at faint and bright magnitudes, but underestimates the number of galaxies around the break in the cluster luminosity function. We find that simply assuming a weaker dust attenuation improves the model predictions for the cluster galaxy luminosity function, but worsens the predictions for the red sequence at bright magnitudes. Examination of the properties of the bright cluster galaxies suggests that the default dust attenuation is large due to these galaxies having large reservoirs of cold gas as well as small radii. We find that matching the luminosity function and colours of high-redshift cluster galaxies, whilst remaining consistent with local observations, poses a challenge for galaxy formation models.
Rhinometry: Spectrum of nasal profile among Nigerian Africans

Abstract Nasal parameters measurements are useful in anthropology to distinguish people into racial and ethnic groups. Materials and methods A cross-sectional survey among Nigerians aged 18 to 70 years of Nigerian parentage randomly selected at the ENT Clinic of the University of Ilorin teaching hospital (U.I.T.H.), Ilorin, Nigeria without gender discrimination had measurement of their nasal parameters done using a sliding caliper: Nasal height, width, tip protrusion, alar thickness, nasal septal thickness and nares diameter. Results 105 subjects were seen, the age range 18 to 70 years (mean of 28.63 + 13.06 years). There was 58 males and 47 females with a male/female ratio of 1.2:1. The mean nasal width/height (Nasal index -NI) was 90.7 in males and 88.2 in females. Males had a higher NI compared to female (p < 0.03). The commonest type of nasal variability is Type A (70.5%), Platyrrhine nose, Type B (26.7%) especially in females (mesorrhine) and Type C (leptorrhine) (2.8%). Conclusions There is significant association between the sex of an individual and type of Nose. Platyrrhine nose, among males and mesorrhine among females, only 2.8% being leptorrhine. The nasal indices were higher in males than in females.
Transfer Learning for Cross-Language Text Categorization through Active Correspondences Construction

Most existing heterogeneous transfer learning (HTL) methods for cross-language text classification rely on sufficient cross-domain instance correspondences to learn a mapping across heterogeneous feature spaces, and assume that such correspondences are given in advance. However, in practice, correspondences between domains are usually unknown. In this case, extensively manual efforts are required to establish accurate correspondences across multilingual documents based on their content and meta-information. In this paper, we present a general framework to integrate active learning to construct correspondences between heterogeneous domains for HTL, namely HTL through active correspondences construction (HTLA). Based on this framework, we develop a new HTL method. On top of the new HTL method, we further propose a strategy to actively construct correspondences between domains. Extensive experiments are conducted on various multilingual text classification tasks to verify the effectiveness of HTLA.
Preliminary examination of cognitive reserve theory in closed head injury.

This investigation was designed to provide preliminary support for cognitive reserve theory in closed head injury (CHI), and demonstrate the effectiveness of using the Oklahoma premorbid intelligence estimate (OPIE) in research and clinical activities. Out of a possible 124 consecutive referrals, 26 patients (N=26) who underwent neuropsychological assessment following brain injury met study inclusion/exclusion criteria. Participants were included if they had exited post-traumatic amnesia (PTA), demonstrated uncompromised upper extremity use, displayed adequate verbal communication, and were judged capable of completing a full neuropsychological evaluation. Participants were divided into a closed head injury-negative premorbid history (CHI-) or closed head injury-positive premorbid history (CHI+) group based upon premorbid variables (e.g., history of alcoholism). Groups did not differ in terms of demographic variables or premorbid IQ. Despite having less severe head injuries, the CHI+ group had a greater pre-post difference for PIQ, and a significantly larger VIQ/PIQ discrepancy than the CHI- group. In conclusion, these findings suggest that the CHI+ group had diminished cognitive reserve secondary to the aggregate effects of premorbid insult, which resulted in greater cognitive decline following an additional stressor (i.e., CHI) than what might otherwise be expected from the head injury alone.
Descriptive Epidemiology of Musculoskeletal Injuries and Concussions in the National Football League, 2012-2014

Background: The risk of all-cause injury and concussion associated with football is significant. The National Football League (NFL) has implemented changes to increase player safety warranting investigation into the incidence and patterns of injury. Purpose: To document the incidence and patterns of all-cause injury and concussions in the NFL. Study Design: Descriptive epidemiology study. Methods: Injury data were collected prospectively from official NFL injury reports over 2 regular seasons from 2012 to 2014, with identification of injury incidence rates and patterns. Concussion rate ratios were calculated using previously reported NFL rates. Results: A total of 4284 injuries were identified, including 301 concussions. The all-cause injury rate was 395.8 per 1000 athletes at risk (AAR) and concussion incidence was 27.8 per 1000 AAR. Only 2.3% of team games were injury free. Wide receivers, tight ends, and defensive backs had the highest incidence of injury and concussion. Concussion incidence was 1.61-fold higher in 2012 to 2014 compared with 2002 to 2007. The knee was injured most frequently, followed by the ankle, hamstring, shoulder, and head. Conclusion: The incidence of all-cause injury and concussion in the NFL is significant. Concussion injury rates are higher than previous reports, potentially reflecting an improvement in recognition and awareness. Injury prevention efforts should continue to reduce the prevalence of injury associated with football.