Hardware Architectures and Implementations for Associative Memories : the Building Blocks of Hierarchically Distributed Memories

During the past several decades, the semiconductor industry has grown into a global industry with revenues around $300 billion. Intel no longer relies on only transistor scaling for higher CPU performance, but instead, focuses more on multiple cores on a single die. It has been projected that in 2016 most CMOS circuits will be manufactured with 22 nm process. The CMOS circuits will have a large number of defects. Especially when the transistor goes below sub-micron, the original deterministic circuits will start having probabilistic characteristics. Hence, it would be challenging to map traditional computational models onto probabilistic circuits, suggesting a need for fault-tolerant computational algorithms. Biologically inspired algorithms, or associative memories (AMs)—the building blocks of cortical hierarchically distributed memories (HDMs) discussed in this dissertation, exhibit a remarkable match to the nano-scale electronics, besides having great fault-tolerance ability. Research on the potential mapping of the HDM onto CMOL (hybrid CMOS/nanoelectronic circuits) nanogrids provides useful insight into the development of non-von Neumann neuromorphic architectures and semiconductor industry. In this dissertation, we investigated the implementations of AMs on different hardware platforms, including microprocessor based personal computer (PC), PC cluster, field programmable gate arrays (FPGA), CMOS, and CMOL nanogrids. We studied two types of neural associative memory models, with and without temporal information. In this research, we first decomposed the computational models into basic and common operations, such as matrix-vector inner-product and k-winners-take-all (k-WTA). We then analyzed the baseline performance/price ratio of implementing the AMs with a PC. We continued with a similar performance/price analysis of the implementations on more parallel hardware platforms, such as PC cluster and FPGA. However, the majority of the research emphasized on the implementations with all digital and mixed-signal full-custom CMOS and CMOL nanogrids. In this dissertation, we draw the conclusion that the mixed-signal CMOL nanogrids exhibit the best performance/price ratio over other hardware platforms. We also highlighted some of the trade-offs between dedicated and virtualized hardware circuits for the HDM models. A simple time-multiplexing scheme for the digital CMOS implementations can achieve comparable throughput as the mixed-signal CMOL nanogrids

Effect of regional versus general anaesthesia on postoperative opioid consumption, clinical outcomes and cognitive function in Chinese patients undergoing metastatic cancer surgery

Purpose: To compare postoperative opioid consumption, inflammatory biomarkers, cognitive function and safety profile of regional anesthesia (RA) versus general anesthesia (GA) in Chinese patients undergoing metastatic cancer surgery.Method: Chinese patients undergoing metastatic cancer surgery were enrolled and received either RA or GA) in allocation ratio of 1:1. The following efficacy variables were assessed: 1) pain score was measured on VAS scale; 2) post-operative consumption; 3) inflammatory biomarkers; 4) cognitive function; 5) clinical outcomes. Safety was also assessed.Results: Data for a total of 220 patients were analyzed. Compared to GA alone, the combination of RA and GA demonstrated significantly greater reduction in post-operative pain with decreased postoperative opioid consumption. Also, RA/GA combination inhibited inflammatory response when compared to patients who received GA only, indicating that RA + GA improved immune response in patient undergoing surgical intervention. The severity of signs and symptoms of dementia were similar at baseline visit (p > 0.05). Patients of RA/GA group had significantly greater relief in signs and symptoms of dementia/cognitive impairment, when compared to the GA-treated patients (p < 0.05). However, incidence of complications (including adverse events) was comparable for both groups (p > 0.05). Additionally, RA/GA was also associated with shorter length of hospital stay, compared to GA.Conclusion: RA/GA combination demonstrates significantly greater improvement in the level of clinical outcomes, decreases postoperative opioid consumption, and improves cognitive functions when compared to GA in Chinese patients undergoing metastatic cancer surgery

Structure and seasonal variability of fronts in the Southeast Indian Ocean along sections from Fremantle, Australia to Antarctic Zhongshan Station

Four sections of expendable conductivity-temperature-depth (XCTD) profiles from Fremantle, Australia to Antarctic Zhongshan Station and Moderate Resolution Imaging Spectroradiometer-Aquarius (MODIS-A) sea surface temperature (SST) products were used to study the structure and seasonal variability of Southeast Indian Ocean fronts. Water mass analysis showed that surface water masses in the Southeast Indian Ocean were less salty in March than in November. Compared with November, the subtropical front (STF) moved southward about one degree of latitude in March, whereas seasonal variability of the subantarctic front (SAF) and polar front (PF) locations was not obvious. In March, the saline front moved northward about two degrees of latitude relative to the thermal front in the upper 100 m at the SAF, which was the northern boundary of sub-Antarctic surface water (SASW). Analysis of climatological SST gradients from the satellite data showed that regions of enhanced sea surface temperature (SST) gradients were collocated with frontal locations identified with the XCTD data using water mass criteria. The surface expression of the PF identified by the SST gradient was further south by about one degree of latitude relative to the subsurface expression of the PF identified by the northern boundary of cold water

Pre-treatment Resting-State Functional MR Imaging Predicts the Long-Term Clinical Outcome After Short-Term Paroxtine Treatment in Post-traumatic Stress Disorder

Background: The chronic phase of post-traumatic stress disorder (PTSD) and the limited effectiveness of existing treatments creates the need for the development of potential biomarkers to predict response to antidepressant medication at an early stage. However, findings at present focus on acute therapeutic effect without following-up the long-term clinical outcome of PTSD. So far, studies predicting the long-term clinical outcome of short-term treatment based on both pre-treatment and post-treatment functional MRI in PTSD remains limited.Methods: Twenty-two PTSD patients were scanned using resting-state functional MRI (rs-fMRI) before and after 12 weeks of treatment with paroxetine. Twenty patients were followed up using the same psychopathological assessments 2 years after they underwent the second MRI scan. Based on clinical outcome, the follow-up patients were divided into those with remitted PTSD or persistent PTSD. Amplitude of low-frequency fluctuations (ALFF) and degree centrality (DC) derived from pre-treatment and post-treatment rs-fMRI were used as classification features in a support vector machine (SVM) classifier.Results: Prediction of long-term clinical outcome by combined ALFF and DC features derived from pre-treatment rs-fMRI yielded an accuracy rate of 72.5% (p < 0.005). The most informative voxels for outcome prediction were mainly located in the precuneus, superior temporal area, insula, dorsal medial prefrontal cortex, frontal orbital cortex, supplementary motor area, lingual gyrus, and cerebellum. Long-term outcome could not be successfully classified by post-treatment imaging features with accuracy rates <50%.Conclusions: Combined information from ALFF and DC from rs-fMRI data before treatment could predict the long-term clinical outcome of PTSD, which is critical for defining potential biomarkers to customize PTSD treatment and improve the prognosis

Health risks and respiratory intake of submicron particles in the working environment: A case study

Background: Powder-coating processes have been extensively used in various industries. The submicron particles generated during the powder-coating process in the workplace have complex compositions and can cause serious diseases. The purpose of this study was to better understand the health risks and respiratory intake of submicron particles during the powder coating process.Methods: The concentrations of and variations in submicron particles were measured using real-time instruments. The health risks of submicron particles were analyzed using the Stoffenmanager Nano model. A new computational fluid dynamics model was used to assess the respiratory intake of ultrafine particles (UFPs), which was indicated by the deposited dosage of UFPs in the olfactory area, nasal cavity, and lungs. The deposited doses of UFPs were used to calculate the average daily doses (ADDs) of workers, according to the method described by the Environmental Protection Agency.Results: The number concentration (NC), mass concentration, surface area concentration, personal NC, and lung-deposited surface area concentration of submicron particles were >105 pt/cm3, 0.2–0.4 mg/m3, 600–1,200 μm2/cm3, 0.7–1.4 pt/cm3, and 100–700 μm2/cm3, respectively. The size distribution showed that the submicron particles mainly gathered between 30 and 200 nm. The health risk of submicron particles was high. Upon respiratory intake, most UFPs (111.5 mg) were inhaled into the lungs, a few UFPs (0.272 mg) were trapped in the nasal cavity, and a small minority of UFPs (0.292 mg) were deposited in the olfactory area. The ADD of male workers with 10 years of exposure in the olfactory area, nasal cavity, and lung were 1.192 × 10–3 mg/kg·d−1, 1.11 × 10–3 mg/kg·d−1, and 0.455 mg/kg·d−1, respectively.Conclusion: Owing to the high concentrations of submicron particles, the workers involved in the powder-coating process are at a high health risk. Moreover, the respiratory intake of UFPs by workers is high, which is suggested by the highly deposited dosage of UFPs in the lungs and the corresponding high ADD in workers. Control measures, including engineering control, management control, and personal protective equipment, must be improved for the protection of workers

The generalized Hamiltonian model for the shafting transient analysis of the hydro turbine generating sets.

yesTraditional rotor dynamics mainly focuses on the steady- state behavior of the rotor and shafting. However, for systems such as hydro turbine generating sets (HTGS) where the control and regulation is frequently applied, the shafting safety and stabilization in transient state is then a key factor. The shafting transient state inevitably involves multiparameter domain, multifield coupling, and coupling dynamics. In this paper, the relative value form of the Lagrange function and its equations have been established by defining the base value system of the shafting. Takingthe rotation angle and the angular speed of the shafting as a link, the shafting lateral vibration and generator equations are integrated into the framework of generalized Hamiltonian system. The generalized Hamiltonian control model is thus established. To make the model more general, additional forces of the shafting are taken as the input excitation in proposed model. The control system of the HTGS can be easily connected with the shafting model to form the whole simulation system of the HTGS. It is expected that this study will build a foundation for the coupling dynamics theory using the generalized Hamiltonian theory to investigate coupling dynamic mechanism among the shafting vibration, transient of hydro turbine generating sets, and additional forces of the shafting.National Natural Science Foundation of China under Grant Nos. 51179079 and 5083900

Altered Effective Connectivity Network of the Amygdala in Social Anxiety Disorder: A Resting-State fMRI Study

The amygdala is often found to be abnormally recruited in social anxiety disorder (SAD) patients. The question whether amygdala activation is primarily abnormal and affects other brain systems or whether it responds “normally” to an abnormal pattern of information conveyed by other brain structures remained unanswered. To address this question, we investigated a network of effective connectivity associated with the amygdala using Granger causality analysis on resting-state functional MRI data of 22 SAD patients and 21 healthy controls (HC). Implications of abnormal effective connectivity and clinical severity were investigated using the Liebowitz Social Anxiety Scale (LSAS). Decreased influence from inferior temporal gyrus (ITG) to amygdala was found in SAD, while bidirectional influences between amygdala and visual cortices were increased compared to HCs. Clinical relevance of decreased effective connectivity from ITG to amygdala was suggested by a negative correlation of LSAS avoidance scores and the value of Granger causality. Our study is the first to reveal a network of abnormal effective connectivity of core structures in SAD. This is in support of a disregulation in predescribed modules involved in affect control. The amygdala is placed in a central position of dysfunction characterized both by decreased regulatory influence of orbitofrontal cortex and increased crosstalk with visual cortex. The model which is proposed based on our results lends neurobiological support towards cognitive models considering disinhibition and an attentional bias towards negative stimuli as a core feature of the disorder