Segregation and precipitation of Er in Ge

Although Er-doped Genanomaterials are attractive for photonic applications, very little is known about the basic properties of Er in Ge. Here, the authors study the annealing behavior of Geimplanted with keV Er ions to doses resulting in ≲1at.% of Er. Large redistribution of Er, with segregation at the amorphous/crystalline interface, starts at ≳500°C, while lower temperatures are required for material recrystallization. However, even at 400°C, Er forms precipitates. The concentration of Er trapped in the bulk after recrystallization decreases with increasing temperature but is independent of the initial bulk Er concentration for the range of ion doses studied here.Work at the ANU was supported by the ARC

Nonsuicidal Self-Injury and Suicidal Behavior: A Latent Class Analysis among Young Adults

Although there is a general consensus among researchers that engagement in nonsuicidal self-injury (NSSI) is associated with increased risk for suicidal behavior, little attention has been given to whether suicidal risk varies among individuals engaging in NSSI. To identify individuals with a history of NSSI who are most at risk for suicidal behavior, we examined individual variability in both NSSI and suicidal behavior among a sample of young adults with a history of NSSI (N = 439, Mage = 19.1). Participants completed self-report measures assessing NSSI, suicidal behavior, and psychosocial adjustment (e.g., depressive symptoms, daily hassles). We conducted a latent class analysis using several characteristics of NSSI and suicidal behaviors as class indicators. Three subgroups of individuals were identified: 1) an infrequent NSSI/not high risk for suicidal behavior group, 2) a frequent NSSI/not high risk for suicidal behavior group, and 3) a frequent NSSI/high risk for suicidal behavior group. Follow-up analyses indicated that individuals in the ‘frequent NSSI/high risk for suicidal behavior’ group met the clinical-cut off score for high suicidal risk and reported significantly greater levels of suicidal ideation, attempts, and risk for future suicidal behavior as compared to the other two classes. Thus, this study is the first to identity variability in suicidal risk among individuals engaging in frequent and multiple methods of NSSI. Class 3 was also differentiated by higher levels of psychosocial impairment relative to the other two classes, as well as a comparison group of non-injuring young adults. Results underscore the importance of assessing individual differences in NSSI characteristics, as well as psychosocial impairment, when assessing risk for suicidal behavior

Sustained-release niacin induced acute liver failure: an autopsy report

Niacin, either alone or in combination with other anti-hyperlipidemic agents, safely and effectively addresses most lipid abnormalities in patients with mixed dyslipidemias. Niacin is the only available agent that significantly lowers lipoprotein (a) and has the greatest high density lipoprotein cholesterol-raising effects of all available agents. Despite niacin’s numerous beneficial lipid effects, patient compliance to long-term therapy is challenged by its common side effects which include nausea, pruritus, and vasodilatory flushing. The incidence of these unpleasant side effects in patients taking the Immediate Release (IR) form of the drug is close to 100 %. To avoid these side effects, Sustained Release (SR) formulations of the drug were created which lower the rate of nausea, flushing and pruritus markedly. Unfortunately, the SR form is associated with a high incidence of chemical hepatitis and rarely fulminant hepatic failure, which is not seen in patients taking the IR form. We report the autopsy findings of a 68 years old man who died of fulminant liver failure three weeks after switching from IR to SR form of niacin. All other toxic, infectious and autoimmune causes of liver failure were ruled out clinically. His liver biopsy one-week antemortem was consistent with chemical hepatitis, such as has been described for slow-release niacin. At autopsy the liver showed diffuse massive hepatic necrosis with no background fibrosis. SR Niacin is widely available over the counter; however, there is substantial scientific evidence that the drug is associated with potentially fatal hepatotoxicity

Optimization of Lipid Extraction From Municipal Scum Sludge for Biodiesel Production Using Statistical Approach

Design of Experiment (DoE) as a statistical method was applied for optimizing lipid extraction conditions from scum sludge. Four different extraction variables were optimized namely methanol to hexane ratio (%), solvent to sludge ratio (ml/g), temperature (oC), and extraction time (h). Process optimization was conducted through three main steps: 1) 2k factorial screening design; 2) Steepest ascent method; and 3) Box-Behnken design and response surface method. Based on 2k factorial screening design, methanol to hexane ratio, solvent to sludge ratio and temperature were identified as highly significant variables affecting lipid extraction from scum sludge. Based on screening results, the steepest ascent method was used followed by Box-Behnken design and Response Surface Method (RSM) were then applied for optimization. The maximum extracted lipid of 29.4% (wt lipid/wt dry sludge- %) was achieved at 40% methanol to hexane ratio (%), 40 solvent to sludge ratio (ml/g), 90oC and 6 hours extraction time. The results revealed that lipid extraction increases with reducing the methanol to hexane ratio, increasing solvent to sludge ratio and increasing temperature The results demonstrated the potentiality of scum sludge for biodiesel production from scum sludge compared with the amount of lipid extracted from primary and secondary sludge reported by other studies.Article History: Received Feb 16th 2017; Received in revised form May 5th 2017; Accepted June 4th 2017; Available onlineHow to Cite This Article: Ibrahim, S.N.H, and Hamza, E.A. (2017). Optimization of Lipid Extraction from Municipal Scum Sludge for Biodiesel Production Using Statistical Approach. International Journal of Renewable Energy Development, 6(2), 171-179.https://doi.org/10.14710/ijred.6.2.171-17

Operative Technique and Complication Avoidance in Supraorbital Endoscopic Keyhole Craniotomy

Objective: The aim of the current study is to describe the technical details of the endoscopic supraorbital keyhole craniotomy and how to avoid complications related with it.Material and Methods: In this cross sectional observational study nine preserved human cadavers from TheSkull Base Lab of Weill Cornell Medical College, Cornell University, New York, USA were used. Total number of18 endoscopic supraorbital keyhole craniotomies were performed. Distances between the different targetedanatomical constructs were looked at and measured.Results: A supraorbital craniotomy was performed with details on the technique of the surgery. The secondmajor part of the results comprised of per-operative complications and how to avoid these complications.Conclusion: To treat anterior and middle skull base pathologies, the endoscopic supraorbital keyholecraniotomy is an effective, valuable and minimal access surgical choice

Correlated Markov Quantum Walks

We consider the discrete time unitary dynamics given by a quantum walk on $\Z^d$ performed by a particle with internal degree of freedom, called coin state, according to the following iterated rule: a unitary update of the coin state takes place, followed by a shift on the lattice, conditioned on the coin state of the particle. We study the large time behavior of the quantum mechanical probability distribution of the position observable in $\Z^d$ for random updates of the coin states of the following form. The random sequences of unitary updates are given by a site dependent function of a Markov chain in time, with the following properties: on each site, they share the same stationnary Markovian distribution and, for each fixed time, they form a deterministic periodic pattern on the lattice. We prove a Feynman-Kac formula to express the characteristic function of the averaged distribution over the randomness at time $n$ in terms of the nth power of an operator $M$. By analyzing the spectrum of $M$, we show that this distribution posesses a drift proportional to the time and its centered counterpart displays a diffusive behavior with a diffusion matrix we compute. Moderate and large deviations principles are also proven to hold for the averaged distribution and the limit of the suitably rescaled corresponding characteristic function is shown to satisfy a diffusion equation. An example of random updates for which the analysis of the distribution can be performed without averaging is worked out. The random distribution displays a deterministic drift proportional to time and its centered counterpart gives rise to a random diffusion matrix whose law we compute. We complete the picture by presenting an uncorrelated example.Comment: 37 pages. arXiv admin note: substantial text overlap with arXiv:1010.400

Efficient Gated Convolutional Recurrent Neural Networks for Real-Time Speech Enhancement

Deep learning (DL) networks have grown into powerful alternatives for speech enhancement and have achieved excellent results by improving speech quality, intelligibility, and background noise suppression. Due to high computational load, most of the DL models for speech enhancement are difficult to implement for realtime processing. It is challenging to formulate resource efficient and compact networks. In order to address this problem, we propose a resource efficient convolutional recurrent network to learn the complex ratio mask for real-time speech enhancement. Convolutional encoder-decoder and gated recurrent units (GRUs) are integrated into the Convolutional recurrent network architecture, thereby formulating a causal system appropriate for real-time speech processing. Parallel GRU grouping and efficient skipped connection techniques are engaged to achieve a compact network. In the proposed network, the causal encoder-decoder is composed of five convolutional (Conv2D) and deconvolutional (Deconv2D) layers. Leaky linear rectified unit (ReLU) is applied to all layers apart from the output layer where softplus activation to confine the network output to positive is utilized. Furthermore, batch normalization is adopted after every convolution (or deconvolution) and prior to activation. In the proposed network, different noise types and speakers can be used in training and testing. With the LibriSpeech dataset, the experiments show that the proposed real-time approach leads to improved objective perceptual quality and intelligibility with much fewer trainable parameters than existing LSTM and GRU models. The proposed model obtained an average of 83.53% STOI scores and 2.52 PESQ scores, respectively. The quality and intelligibility are improved by 31.61% and 17.18% respectively over noisy speech

Web-enabled Intelligent System for Continuous Sensor Data Processing and Visualization

A large number of sensors deployed in recent years in various setups and their data is readily available in dedicated databases or in the cloud. Of particular interest is real-time data processing and 3D visualization in web-based user interfaces that facilitate spatial information understanding and sharing, hence helping the decision making process for all the parties involved. In this research, we provide a prototype system for near real-time, continuous X3D-based visualization of processed sensor data for two significant applications: thermal monitoring for residential/commercial buildings and nitrogen cycle monitoring in water beds for aquaponics systems. As sensors are sparsely placed, in each application, where they collect data for large periods (of up to one year), we employ a Finite Differences Method and a Neural Networks model to approximate data distribution in the entire volume