Training-Induced Improvement of Response Selection and Error Detection in Aging Assessed by Task Switching: Effects of Cognitive, Physical, and Relaxation Training

Cognitive control functions decline with increasing age. The present study examines if different types of group-based and trainer-guided training effectively enhance performance of older adults in a task switching task, and how this expected enhancement is reflected in changes of cognitive functions, as measured in electrophysiological brain activity (event-related potentials). One hundred forty-one healthy participants aged 65 years and older were randomly assigned to one of four groups: physical training (combined aerobic and strength training), cognitive training (paper–pencil and computer-aided), relaxation and wellness (social control group), and a control group that did not receive any intervention. Training sessions took place twice a week for 90 min for a period of 4 months. The results showed a greater improvement of performance for attendants of the cognitive training group compared to the other groups. This improvement was evident in a reduction of mixing costs in accuracy and intraindividual variability of speed, indexing improved maintenance of multiple task sets in working memory, and an enhanced coherence of neuronal processing. These findings were supported by event-related brain potentials which showed higher amplitudes in a number of potentials associated with response selection (N2), allocation of cognitive resources (P3b), and error detection (Ne). Taken together, our findings suggest neurocognitive plasticity of aging brains which can be stimulated by broad and multilayered cognitive training and assessed in detail by electrophysiological methods

Wavefront attributes in anisotropic media

Surface-measured wavefront attributes are the key ingredient to multiparameter methods, which are nowadays standard tools in seismic data processing. However, most operators are restricted to application to isotropic media. Whereas application of an isotropic operator will still lead to satisfactory stack results, further processing steps that interpret isotropic stacking parameters in terms of wavefront attributes will lead to erroneous results if anisotropy is present but not accounted for. In this paper, we derive relationships between the stacking parameters and anisotropic wavefront attributes that allow us to apply the common reflection surface type operator to 3-D media with arbitrary anisotropy for the zero-offset and finite-offset configurations including converted waves. The operator itself is expressed in terms of wavefront attributes that are measured in the acquisition surface, that is, no model assumptions are made. Numerical results confirm that the accuracy of the new anisotropic operator is of the same magnitude as that of its isotropic counterpart

The Levantine Basin - crustal structure and origin

The origin of the Levantine Basin in the Southeastern Mediterranean Sea is related to the opening of the Neo-Tethys. The nature of its crust has been debated for decades. Therefore, we conducted a geophysical experiment in the Levantine Basin. We recorded two refraction seismic lines with 19 and 20 ocean bottom hydrophones, respectively, and developed velocity models. Additional seismic reflection data yield structural information about the upper layers in the first few kilometers. The crystalline basement in the Levantine Basin consists of two layers with a P-wave velocity of 6.06.4 km/s in the upper and 6.56.9 km/s in the lower crust. Towards the center of the basin, the Moho depth decreases from 27 to 22 km. Local variations of the velocity gradient can be attributed to previously postulated shear zones like the Pelusium Line, the DamiettaLatakia Line and the BaltimHecateus Line. Both layers of the crystalline crust are continuous and no indication for a transition from continental to oceanic crust is observed. These results are confirmed by gravity data. Comparison with other seismic refraction studies in prolongation of our profiles under Israel and Jordan and in the Mediterranean Sea near Greece and Sardinia reveal similarities between the crust in the Levantine Basin and thinned continental crust, which is found in that region. The presence of thinned continental crust under the Levantine Basin is therefore suggested. A β-factor of 2.33 is estimated. Based on these findings, we conclude that sea-floor spreading in the Eastern Mediterranean Sea only occurred north of the Eratosthenes Seamount, and the oceanic crust was later subducted at the Cyprus Arc

Age-Related Differences in Working Memory Performance in A 2-Back Task

The present study aimed to elucidate the neuro-cognitive processes underlying age-related differences in working memory. Young and middle-aged participants performed a two-choice task with low and a 2-back task with high working memory load. The P300, an event-related potential reflecting controlled stimulus–response processing in working memory, and the underlying neuronal sources of expected age-related differences were analyzed using sLORETA. Response speed was generally slower for the middle-aged than the young group. Under low working memory load the middle-aged participants traded speed for accuracy. The middle-aged were less efficient in the 2-back task as they responded slower while the error rates did not differ for groups. An age-related decline of the P300 amplitude and characteristic topographical differences were especially evident in the 2-back task. A more detailed analysis of the P300 in non-target trials revealed that amplitudes in the young but not middle-aged group differentiate between correctly detected vs. missed targets in the following trial. For these trials, source analysis revealed higher activation for the young vs. middle-aged group in brain areas which support working memory processes. The relationship between P300 and overt performance was validated by significant correlations. To sum up, under high working memory load the young group showed an increased neuronal activity before a successful detected target, while the middle-aged group showed the same neuronal pattern regardless of whether a subsequent target will be detected or missed. This stable memory trace before detected targets was reflected by a specific activation enhancement in brain areas which orchestrate maintenance, update, storage, and retrieval of information in working memory

Antibiotic susceptibility and ability to form biofilm of Listeria monocytogenes strains isolated from frozen vegetables

L. monocytogenes poses a serious threat to public health, since most cases of listeriosis are connected with eating contaminated food. L. monocytogenes is often detected both in fresh and frozen vegetables. The aim of this study was to evaluate the antibiotic susceptibility and ability to form biofilm of L. monocytogenes strains isolated from frozen vegetable mixtures in Poland. Ninetynine genetically different strains were found among 100 isolates of L. monocytogenes. Among the 99 strains, 80 (80.8%) were susceptible to all tested antibiotics. Nineteen (19.2%) strains were resistant to one or more antibiotics. From this group of L. monocytogenes strains, most strains were resistant to erythromycin (16; 16,1%), penicillin (15; 15.1%), meropenem (12; 12.1%), cotrimoxazole (12; 12.1%), and ampicillin (3; 3.1%). According to the obtained results, differences in intensity of biofilm, both between those isolated in successive years and in the particular year, were observed. Performed analysis showed statistically insignificant faint negative correlation (r=–0.088) between the number of antibiotics to which strains were resistant and the intensity of biofilm formation by them. Food contamination with L. monocytogenes poses a threat to consumers, therefore it is necessary to monitor their antibiotic susceptibility, ability to form biofilm, and genetic similarity, in order to evaluate the strains persistence time in plant

A Type-Theoretic Account of Neg-Raising Predicates in Tree Adjoining Grammars

International audienceNeg-Raising (NR) verbs form a class of verbs with a clausal complement that show the following behavior: when a negation syntactically attaches to the matrix predicate, it can semantically attach to the embedded predicate. This paper presents an account of NR predicates within Tree Adjoining Grammar (TAG). We propose a lexical semantic interpretation that heavily relies on a Montague-like semantics for TAG and on higher-order types

Stiffness Moduli Modelling and Prediction in Four-Point Bending of Asphalt Mixtures: A Machine Learning-Based Framework

Stiffness modulus represents one of the most important parameters for the mechanical characterization of asphalt mixtures (AMs). At the same time, it is a crucial input parameter in the process of designing flexible pavements. In the present study, two selected mixtures were thoroughly investigated in an experimental trial carried out by means of a four-point bending test (4PBT) apparatus. The mixtures were prepared using spilite aggregate, a conventional 50/70 penetration grade bitumen, and limestone filler. Their stiffness moduli (SM) were determined while samples were exposed to 11 loading frequencies (from 0.1 to 50 Hz) and 4 testing temperatures (from 0 to 30 °C). The SM values ranged from 1222 to 24,133 MPa. Observations were recorded and used to develop a machine learning (ML) model. The main scope was the prediction of the stiffness moduli based on the volumetric properties and testing conditions of the corresponding mixtures, which would provide the advantage of reducing the laboratory efforts required to determine them. Two of the main soft computing techniques were investigated to accomplish this task, namely decision trees with the Categorical Boosting algorithm and artificial neural networks. The outcomes suggest that both ML methodologies achieved very good results, with Categorical Boosting showing better performance (MAPE = 3.41% and R2 = 0.9968) and resulting in more accurate and reliable predictions in terms of the six goodness-of-fit metrics that were implemented

Stiffness Moduli Modelling and Prediction in Four-Point Bending of Asphalt Mixtures: A Machine Learning-Based Framework

Stiffness modulus represents one of the most important parameters for the mechanical characterization of asphalt mixtures (AMs). At the same time, it is a crucial input parameter in the process of designing flexible pavements. In the present study, two selected mixtures were thoroughly investigated in an experimental trial carried out by means of a four-point bending test (4PBT) apparatus. The mixtures were prepared using spilite aggregate, a conventional 50/70 penetration grade bitumen, and limestone filler. Their stiffness moduli (SM) were determined while samples were exposed to 11 loading frequencies (from 0.1 to 50 Hz) and 4 testing temperatures (from 0 to 30 °C). The SM values ranged from 1222 to 24,133 MPa. Observations were recorded and used to develop a machine learning (ML) model. The main scope was the prediction of the stiffness moduli based on the volumetric properties and testing conditions of the corresponding mixtures, which would provide the advantage of reducing the laboratory efforts required to determine them. Two of the main soft computing techniques were investigated to accomplish this task, namely decision trees with the Categorical Boosting algorithm and artificial neural networks. The outcomes suggest that both ML methodologies achieved very good results, with Categorical Boosting showing better performance (MAPE = 3.41% and R2 = 0.9968) and resulting in more accurate and reliable predictions in terms of the six goodness-of-fit metrics that were implemented

Improving quality indicator report cards through Bayesian modeling

<p>Abstract</p> <p>Background</p> <p>The National Database for Nursing Quality Indicators^®(NDNQI^®) was established in 1998 to assist hospitals in monitoring indicators of nursing quality (eg, falls and pressure ulcers). Hospitals participating in NDNQI transmit data from nursing units to an NDNQI data repository. Data are summarized and published in reports that allow participating facilities to compare the results for their units with those from other units across the nation. A disadvantage of this reporting scheme is that the sampling variability is not explicit. For example, suppose a small nursing unit that has 2 out of 10 (rate of 20%) patients with pressure ulcers. Should the nursing unit immediately undertake a quality improvement plan because of the rate difference from the national average (7%)?</p> <p>Methods</p> <p>In this paper, we propose approximating 95% credible intervals (CrIs) for unit-level data using statistical models that account for the variability in unit rates for report cards.</p> <p>Results</p> <p>Bayesian CrIs communicate the level of uncertainty of estimates more clearly to decision makers than other significance tests.</p> <p>Conclusion</p> <p>A benefit of this approach is that nursing units would be better able to distinguish problematic or beneficial trends from fluctuations likely due to chance.</p

31P-NMR and muSR Studies of Filled Skutterudite Compound SmFe4P12: Evidence for Heavy Fermion Behavior with Ferromagnetic Ground State

The 31P-NMR (nuclear magnetic resonance) and muSR (muon spin relaxation) measurements on the filled skutterudite system SmFe4P12 have been carried out. The temperature T dependence of the 31P-NMR spectra indicates the existence of the crystalline electric field effect splitting of the Sm3+$ (J = 5/2) multiplet into a ground state and an excited state of about 70 K. The spin-lattice relaxation rate 1/T1 shows the typical behavior of the Kondo system, i.e., 1/T1 is nearly T independent above 30 K, and varies in proportion to T (the Korringa behavior, 1/T1 \propto T) between 7.5 K and 30 K. The T dependence deviated from the Korringa behavior below 7 K, which is independent of T in the applied magnetic field of 1 kOe, and suppressed strongly in higher fields. The behavior is explained as 1/T1is determined by ferromagnetic fluctuations of the uncovered Sm3+ magnetic moments by conduction electrons. The muSR measurements in zero field show the appearance of a static internal field associated with the ferromagnetic order below 1.6 K.Comment: 6 pages, 9 figures, to be published in J. Phys. Soc. Jpn. 75 (2006