APPLEBY-IN-WESTMORLAND (Reino Unido) (Inglaterra). Planos de población (1754?). 1:2000

Escala gráfica de 12 chains [= 12,1 cm]. Orientado con lis en rosa de ocho vientosRelieve a trazosToponimia de las principales callesLeyenda explicativa de los edificios y terrenos representados y de la clave cromática utilizada para diferenciar los campos cercados antiguamente o en la actualidad, etcNotas explicativas sobre la extensión del terreno perteneciente al castilloForma parte de la Colección MendozaInserta: "The Nort Eas View of the Castle

Mapping the Space of Genomic Signatures

We propose a computational method to measure and visualize interrelationships among any number of DNA sequences allowing, for example, the examination of hundreds or thousands of complete mitochondrial genomes. An "image distance" is computed for each pair of graphical representations of DNA sequences, and the distances are visualized as a Molecular Distance Map: Each point on the map represents a DNA sequence, and the spatial proximity between any two points reflects the degree of structural similarity between the corresponding sequences. The graphical representation of DNA sequences utilized, Chaos Game Representation (CGR), is genome- and species-specific and can thus act as a genomic signature. Consequently, Molecular Distance Maps could inform species identification, taxonomic classifications and, to a certain extent, evolutionary history. The image distance employed, Structural Dissimilarity Index (DSSIM), implicitly compares the occurrences of oligomers of length up to $k$ (herein $k=9$) in DNA sequences. We computed DSSIM distances for more than 5 million pairs of complete mitochondrial genomes, and used Multi-Dimensional Scaling (MDS) to obtain Molecular Distance Maps that visually display the sequence relatedness in various subsets, at different taxonomic levels. This general-purpose method does not require DNA sequence homology and can thus be used to compare similar or vastly different DNA sequences, genomic or computer-generated, of the same or different lengths. We illustrate potential uses of this approach by applying it to several taxonomic subsets: phylum Vertebrata, (super)kingdom Protista, classes Amphibia-Insecta-Mammalia, class Amphibia, and order Primates. This analysis of an extensive dataset confirms that the oligomer composition of full mtDNA sequences can be a source of taxonomic information.Comment: 14 pages, 7 figures. arXiv admin note: substantial text overlap with arXiv:1307.375

Number of Active Social Media Users as Predictors of HIPAA Infringements

HIPAA Infringements Correlate Linearly with Number of Social Media Users. Social media use has made information sharing much easier – including protected health information. Interestingly, as social media has become more popular over the years, HIPAA violations have also become more common. The calculated R and P values suggest a strong correlation exists between social media use and HIPAA complaints

Whole-Body Vibration Alleviates Symptoms of Morphine Withdrawal

Whole-body vibration at 80 Hz has previously been shown to blunt neuropathological markers and behavioral symptoms of alcohol dependence. Here, we evaluate its ability to ameliorate symptoms of morphine use and withdrawal. Behavioral and neurophysiological symptoms of withdrawal were reduced significantly by whole-body vibration treatment

An integrated, probabilistic model for improved seasonal forecasting of agricultural crop yield under environmental uncertainty

We present a novel forecasting method for generating agricultural crop yield forecasts at the seasonal and regional-scale, integrating agroclimate variables and remotely-sensed indices. The method devises a multivariate statistical model to compute bias and uncertainty in forecasted yield at the Census of Agricultural Region (CAR) scale across the Canadian Prairies. The method uses robust variable-selection to select the best predictors within spatial subregions. Markov-Chain Monte Carlo (MCMC) simulation and random forest-tree machine learning techniques are then integrated to generate sequential forecasts through the growing season. Cross-validation of the model was performed by hindcasting/backcasting and comparing forecasts against available historical data (1987–2011) for spring wheat (Triticum aestivum L.). The model was also validated for the 2012 growing season by comparing forecast skill at the CAR, provincial and Canadian Prairie region scales against available statistical survey data. Mean percent departures between wheat yield forecasted were under-estimated by 1–4% in mid-season and over-estimated by 1% at the end of the growing season. This integrated methodology offers a consistent, generalizable approach for sequentially forecasting crop yield at the regional-scale. It provides a statistically robust, yet flexible way to concurrently adjust to data-rich and data-sparse situations, adaptively select different predictors of yield to changing levels of environmental uncertainty, and to update forecasts sequentially so as to incorporate new data as it becomes available. This integrated method also provides additional statistical support for assessing the accuracy and reliability of model-based crop yield forecasts in time and space

Physiological Responses Underlying the Perception of Effort during Moderate and Heavy Intensity Cycle Ergometry

This study examined patterns of responses for physiological and perceptual variables during cycle ergometry at a constant rate of perceived exertion (RPE) within the moderate and heavy exercise intensity domains. Nineteen (mean age 21.3 ± 0.5 years; 43.4 ± 2.0 mL·kg−1·min−1 VO2Peak) moderately trained cyclists performed an incremental test to exhaustion and two 60 min constant RPE rides at the RPE corresponding to the gas exchange threshold (RPEGET) and 15% above the GET (RPEGET+15%). Oxygen consumption (VO2), respiratory exchange ratio (RER), heart rate (HR), minute ventilation (VE), breathing frequency (FB), and power output (PO) were monitored throughout the rides. Polynomial regression analyses showed VO2, RER, HR, and VE (correlation = −0.85 to −0.98) tracked the decreases in PO required to maintain a constant RPE. Only FB tracked RPE during the moderate and heavy intensity rides. Repeated measures ANOVAs indicated that VO2 during the 60 min rides at RPEGET was not different (p \u3e 0.05) from VO2 at GET from the incremental test to exhaustion. Thus, monitoring intensity using an RPE associated with the GET is sustainable for up to 60 min of cycling exercise and a common mechanism may mediate FB and the perception of effort during moderate and heavy intensity cycle ergometry

Physiological Responses Underlying the Perception of Effort during Moderate and Heavy Intensity Cycle Ergometry

This study examined patterns of responses for physiological and perceptual variables during cycle ergometry at a constant rate of perceived exertion (RPE) within the moderate and heavy exercise intensity domains. Nineteen (mean age 21.3 ± 0.5 years; 43.4 ± 2.0 mL·kg−1·min−1 VO2Peak) moderately trained cyclists performed an incremental test to exhaustion and two 60 min constant RPE rides at the RPE corresponding to the gas exchange threshold (RPEGET) and 15% above the GET (RPEGET+15%). Oxygen consumption (VO2), respiratory exchange ratio (RER), heart rate (HR), minute ventilation (VE), breathing frequency (FB), and power output (PO) were monitored throughout the rides. Polynomial regression analyses showed VO2, RER, HR, and VE (correlation = −0.85 to −0.98) tracked the decreases in PO required to maintain a constant RPE. Only FB tracked RPE during the moderate and heavy intensity rides. Repeated measures ANOVAs indicated that VO2 during the 60 min rides at RPEGET was not different (p \u3e 0.05) from VO2 at GET from the incremental test to exhaustion. Thus, monitoring intensity using an RPE associated with the GET is sustainable for up to 60 min of cycling exercise and a common mechanism may mediate FB and the perception of effort during moderate and heavy intensity cycle ergometry

Individual Responses for Muscle Activation, Repetitions, and Volume during Three Sets to Failure of High- (80% 1RM) \u3ci\u3eversus\u3c/i\u3e Low-Load (30% 1RM) Forearm Flexion Resistance Exercise

This study compared electromyographic (EMG) amplitude, the number of repetitions completed, and exercise volume during three sets to failure of high- (80% 1RM) versus low-load (30% 1RM) forearm flexion resistance exercise on a subject-by-subject basis. Fifteen men were familiarized, completed forearm flexion 1RM testing. Forty-eight to 72 h later, the subjects completed three sets to failure of dumbbell forearm flexion resistance exercise with 80% (n = 8) or 30% (n = 7) 1RM. EMG amplitude was calculated for every repetition, and the number of repetitions performed and exercise volume were recorded. During sets 1, 2, and 3, one of eight subjects in the 80% 1RM group demonstrated a significant linear relationship for EMG amplitude versus repetition. For the 30% 1RM group, seven, five, and four of seven subjects demonstrated significant linear relationships during sets 1, 2, and 3, respectively. The mean EMG amplitude responses show that the fatigue-induced increases in EMG amplitude for the 30% 1RM group and no change in EMG amplitude for the 80% 1RM group resulted in similar levels of muscle activation in both groups. The numbers of repetitions completed were comparatively greater, while exercise volumes were similar in the 30% versus 80% 1RM group. Our results, in conjunction with those of previous studies in the leg extensors, suggest that there may be muscle specific differences in the responses to high- versus low-load exercise