Anomalous proximity effect in gold coated (110) YBa2Cu3O7−δYBa_2Cu_3O_{7-\delta} films: Penetration of the Andreev bound states

Scanning tunneling spectroscopy of (110) $YBa_2Cu_3O_{7-\delta}/Au$ bi-layers reveal a proximity effect markedly different from the conventional one. While proximity-induced mini-gaps rarely appear in the Au layer, the Andreev bound states clearly penetrate into the metal. Zero bias conductance peaks are measured on Au layers thinner than 7 nm with magnitude similar to those detected on the bare superconductor films. The peaks then decay abruptly with Au thickness and disappear above 10 nm. This length is shorter than the normal coherence length and corresponds to the (ballistic) mean free path.Comment: 5 prl format pages, 4 figures, to be published in PR

Allocating Security Expenditures under Knightian Uncertainty: an Info-Gap Approach

We apply the information gap approach to resource allocation under Knightian (non-probabilistic) uncertainty in order to study how best to allocate public resources betweencompeting defense measures. We demonstrate that when determining the level and composi-tion of defense spending in an environment of extreme uncertaintyvis-a-visthe likelihood ofarmed conflict and its outcomes, robust-satisficing expected utility will usually be preferableto expected utility maximisation. Moreover, our analysis suggests that in environments withunreliable information about threats to national security and their consequences, a desirefor robustness to model misspecification in the decision making process will imply greaterexpenditure on certain types of defense measures at the expense of others. Our results alsoprovide a positivist explanation of how governments seem to allocate security expendituresin practice

Allocating Security Expenditures under Knightian Uncertainty: an Info-Gap Approach

We apply the information gap approach to resource allocation under Knightian (non-probabilistic) uncertainty in order to study how best to allocate public resources between competing defense measures. We demonstrate that when determining the level and composition of defense spending in an environment of extreme uncertainty vis-a-vis the likelihood of armed conflict and its outcomes, robust-satisficing expected utility will usually be preferable to expected utility maximization. Moreover, our analysis suggests that in environments with unreliable information about threats to national security and their consequences, a desire for robustness to model misspecification in the decision making process will imply greater expenditure on certain types of defense measures at the expense of others. Our results also provide a positivist explanation of how governments seem to allocate security expenditures in practice

Pharmacists' knowledge and attitudes about natural health products: A mixed-methods study

Objectives: To explore knowledge and attitude of pharmacists in Qatar towards natural health products (NHPs). Methods: The quantitative component of this study consisted of an anonymous, online, self-administered questionnaire to assess knowledge about NHPs among pharmacists in Qatar. Descriptive statistics and inferential analysis were conducted using Statistical Package of Social Sciences (SPSS®). Means and standard deviation were used to analyze descriptive data, and statistical significance was expressed as P-value, where P≤0.05 was considered statistically significant. Associations between variables were measured using Pearson correlation. The qualitative component utilized focus group (FG) meetings with a purposive sample of community pharmacists. Meetings were conducted until a point of saturation was reached. FG discussions were audio-taped and transcribed verbatim. Data were analyzed using a framework approach to sort the data according to emerging themes. Results: The majority of participants had average to poor knowledge about NHPs while only around 7% had good knowledge. In the FG meetings, participants considered the media, medical representatives, and old systems of natural health as major source of their knowledge. They criticized undergraduate pharmacy courses (for inadequately preparing pharmacists to deal with NHPs) and the pharmacy regulations (for being irrelevant). A perception of NHPs as being “safe” still exists among pharmacists. Conclusions: Pharmacists’ ability to provide effective services associated with NHPs is limited by poor access to evidence-based information and poor knowledge. A perception of NHPs and CAM as 'safe' still exists among pharmacists, and regulations related to NHPs require addressing to follow best practice and ensure patient safety.Scopu

Allocating Security Expenditures under Knightian Uncertainty: an Info-Gap Approach

We apply the information gap approach to resource allocation under Knightian (non-probabilistic) uncertainty in order to study how best to allocate public resources between competing defense measures. We demonstrate that when determining the level and composition of defense spending in an environment of extreme uncertainty vis-a-vis the likelihood of armed conflict and its outcomes, robust-satisficing expected utility will usually be preferable to expected utility maximization. Moreover, our analysis suggests that in environments with unreliable information about threats to national security and their consequences, a desire for robustness to model misspecification in the decision making process will imply greater expenditure on certain types of defense measures at the expense of others. Our results also provide a positivist explanation of how governments seem to allocate security expenditures in practice

Scanning tunneling spectroscopy characterization of the pseudogap and the x = 1/8 anomaly in La2-xSrxCuO4 thin films

Using scanning tunneling spectroscopy we examined the local density of states of thin c-axis La2-xSrxCuO4 films, over wide doping and temperature ranges. We found that the pseudogap exists only at doping levels lower than optimal. For x = 0.12, close to the 'anomalous' x = 1/8 doping level, a zero bias conductance peak was the dominant spectral feature, instead of the excepted V- shaped (c-axis tunneling) gap structure. We have established that this surprising effect cannot be explained by tunneling into (110) facets. Possible origins for this unique behavior are discussed.Comment: 15 pages, 6 figure

Utilization of Agricultural Waste in Treating Water Pollutants

This study investigated the applicability of chemically (phosphoric acid) activated bagasse pith and date pits in the adsorption of water pollutants. The textural properties including porous parameters, monolayer equivalent surface area, total pore volumes, average pore radius, Methylene blue number and other physic-chemical characterization were investigated. The activated carbons were analyzed for moisture content, ash content. Ultimate analysis was done by using CHNS analyzer (Cairo University, Micro-analytical Center). To investigate the effect of phosphoric acid on the raw material, thermo gravimetric analysis (TGA) and differential thermo gravimetric (DTG) recordings were determined. The adsorption of heavy metals as pollutants, including Co, Sr, Cu, Cs, Pb, Cd, Ni, Fe, Zn, was studied in a batch experiments. Comparison of date pits activated carbon with commercial activated carbon was done, and the results indicated that using of prepared activated carbon for removal of Co, Sr, Cu, Cs, Pb, Cd, Ni,  Fe, Zn was  more effective than commercial activated carbon

And yet it moves: Recovery of volitional control after spinal cord injury

Preclinical and clinical neurophysiological and neurorehabilitation research has generated rather surprising levels of recovery of volitional sensory-motor function in persons with chronic motor paralysis following a spinal cord injury. The key factor in this recovery is largely activity-dependent plasticity of spinal and supraspinal networks. This key factor can be triggered by neuromodulation of these networks with electrical and pharmacological interventions. This review addresses some of the systems-level physiological mechanisms that might explain the effects of electrical modulation and how repetitive training facilitates the recovery of volitional motor control. In particular, we substantiate the hypotheses that: (1) in the majority of spinal lesions, a critical number and type of neurons in the region of the injury survive, but cannot conduct action potentials, and thus are electrically non-responsive; (2) these neuronal networks within the lesioned area can be neuromodulated to a transformed state of electrical competency; (3) these two factors enable the potential for extensive activity-dependent reorganization of neuronal networks in the spinal cord and brain, and (4) propriospinal networks play a critical role in driving this activity-dependent reorganization after injury. Real-time proprioceptive input to spinal networks provides the template for reorganization of spinal networks that play a leading role in the level of coordination of motor pools required to perform a given functional task. Repetitive exposure of multi-segmental sensory-motor networks to the dynamics of task-specific sensory input as occurs with repetitive training can functionally reshape spinal and supraspinal connectivity thus re-enabling one to perform complex motor tasks, even years post injury

Smart Bagged Tree-based Classifier optimized by Random Forests (SBT-RF) to Classify Brain- Machine Interface Data

Brain-Computer Interface (BCI) is a new technology that uses electrodes and sensors to connect machines and computers with the human brain to improve a person\u27s mental performance. Also, human intentions and thoughts are analyzed and recognized using BCI, which is then translated into Electroencephalogram (EEG) signals. However, certain brain signals may contain redundant information, making classification ineffective. Therefore, relevant characteristics are essential for enhancing classification performance. . Thus, feature selection has been employed to eliminate redundant data before sorting to reduce computation time. BCI Competition III Dataset Iva was used to investigate the efficacy of the proposed system. A Smart Bagged Tree-based Classifier (SBT-RF) technique is presented to determine the importance of the features for selecting and classifying the data. As a result, SBT-RF is better at improving the mean accuracy of the dataset. It also decreases computation cost and training time and increases prediction speed. Furthermore, fewer features mean fewer electrodes, thus lowering the risk of damage to the brain. The proposed algorithm has the greatest average accuracy of ~98% compared to other relevant algorithms in the literature. SBT-RF is compared to state-of-the-art algorithms based on the following performance metrics: Confusion Matrix, ROC-AUC, F1-Score, Training Time, Prediction speed, and Accuracy