Miracle-dz/UniFAR-FTUs huggingface dataset:
Solution-processing of chalcogenide materials for device applications

Chalcogenide glasses are well-known for their desirable optical properties, which have enabled many infrared applications in the fields of photonics, medicine, environmental sensing and security. Conventional deposition methods such as thermal evaporation, chemical vapor deposition, sputtering or pulse laser deposition are efficient for fabricating structures on flat surfaces. However, they have limitations in deposition on curved surfaces, deposition of thick layers and component integration. In these cases, solution-based methods, which involve the dissolution of chalcogenide glasses and processing as a liquid, become a better choice for their flexibility. After proper treatment, the associated structures can have similar optical, chemical and physical properties to the bulk. This thesis presents an in-depth study of solution-processing chalcogenide glasses, starting from the "solution state" to the "film state" and the "structure state". Firstly, chalcogenide dissolution is studied to reveal the mechanisms at molecular level and build a foundation for material processing. Dissolution processes for various chalcogenidesolvent pairs are reviewed and compared. Secondly, thermal processing, in the context of high temperature annealing, is explained along with the chemical and physical properties of the annealed films. Another focus is on nanopore formation in propylamineprocessed arsenic sulfide films. Pore density changes with respect to annealing temperatures and durations are characterized. Base on a proposed vacancy coalescence theory, we have identified new dissolution strategies and achieved the breakthrough of pore-free film deposition. Thirdly, several solution methods developed along with the associated photonic structures are demonstrated. The first example is "spincoating and lamination", which produces thick (over 10 μm) chalcogenide structures. Both homogeneous thick chalcogenide structures and heterogeneous layers of different chalcogenide glasses or metals can be fabricated. Second, "micro-molding in capillaries" (MIMIC) and "micro-transfer molding" (μTM) methods are introduced for fabri-
Development of laser beam energy distribution measuring array based on calorimetric techniques

In order to measuring spatial distribution of high energy laser,an idea of honeycomb-like array combined with heat insulation energy detector was put forward.The measuring array based on calorimetric techniques with the performance of high irradiating tolerance and high measuring stability was developed.The system consists of a honeycomb-like board,calorimetric detector cells,a multi-channel data sampling system and processing software,etc.It is shown with the duty ratio 62%,the uniformity better than 5%,the large dynamic range of 600 times,and the total energy error less than 8.5%. The problems of absolute measurement of laser spatial distribution with the large area and dynamic range are resolved.An effective tool is provided to measure the laser spatial distribution.
Bearing fault feature extraction based on optimized EMD by adaptive resonance

According to the problem of how to select the sensitive intrinsic mode functions (IMFs), which can reflect the fault characteristics effectively, a novel sensitive IMF selected method based on adaptive resonance (AR) is proposed. Firstly, a series of IMFs are obtained by EMD, and the power spectrums are obtained for the original vibration signal and each IMF component. Then the resonant frequencies are identified, and the resonant frequencies are taken as the center frequencies of the band-pass filters. Secondly, the band-pass filters are designed to obtain the filtering frequency bands of original vibration signal and each IMF. And the subordinate relationship between filtering band of each IMF with the filtering band of the original vibration signal are compared to select the sensitive IMF. Finally, Perform envelope demodulation analysis to the IMF, and the characteristic information are provided for the subsequent fault diagnosis. The method is applied to the simulated signal and the actual rolling bearing ball fault signal, and they all verify the effectiveness of the method, and it is superior to that select sensitive IMF based on the kurtosis maximum principle.
The Consolidated Tree Construction algorithm in imbalanced defect prediction datasets

In this short paper, we compare well-known rule/tree classifiers in software defect prediction with the CTC decision tree classifier designed to deal with class imbalanced. It is well-known that most software defect prediction datasets are highly imbalance (non-defective instances outnumber defective ones). In this work, we focused only on tree/rule classifiers as these are capable of explaining the decision, i.e., describing the metrics and thresholds that make a module error prone. Furthermore, rules/decision trees provide the advantage that they are easily understood and applied by project managers and quality assurance personnel. The CTC algorithm was designed to cope with class imbalance and noisy datasets instead of using preprocessing techniques (oversampling or undersampling), ensembles or cost weights of misclassification. The experimental work was carried out using the NASA datasets and results showed that induced CTC decision trees performed better or similar to the rest of the rule/tree classifiers.
International Congress of Americanists

THE twenty-sixth session of the International Congress of Americanists, which was to have taken place during November in Seville, had to be postponed owing to financial and political difficulties in Spain. The work of organisation is, however, well advanced and it is hoped that it may still be possible to hold the Congress early in 1935. It is unfortunate that the deliberations of this body, which are invariably of great scientific interest to students of the cultures of aboriginal America, should be subjected to interruption through political unrest. It will be remembered that when the Congress last met in La Plata at the close of 1932, conditions were anything but favourable to an international scientific assembly, and, indeed, had it not been for a certain disorganisation arising out of these conditions, it is probable that the invitation of Great Britain would have been accepted and the Congress would have met in London in close association with the First International Congress of Ethnological Sciences in August last.
Overnight deprivation from smoking disrupts amygdala responses to fear

Cigarette smoking, a major, yet avoidable, cause of disability and premature death, is the most prevalent form of nicotine addiction. An emerging theme in the neurobiology of nicotine addiction is the integrity of the amygdala. Using functional MRI, amygdala responses during a face perception task were compared between 28 chronic smokers [14 females, 14 males; age, 26.3 (2.8) years; age at onset of smoking, 15.8 (2.6) years; years smoked, 9.1 (2.1); cigarettes per day, 17.1 (3.7); Fagerström test for nicotine dependence score, 4.1 (1.9); exhaled carbon‐monoxide level, 17.8 (9.5) ppm] and 28 age‐ and education‐matched nonsmokers [14 females, 14 males; age, 26.9 (2.4) years]. Subjects underwent imaging on two separate occasions 1 week apart: smoking satiety versus overnight smoking deprivation, in a randomized counterbalanced order. Our results show no difference in amygdala responses to faces between nonsmokers and satiated smokers. However, overnight deprivation from smoking was associated with a significantly lowered amygdala response to fear, an effect that was probabilistically mapped to the basolateral amygdala. We suggest that aberrant amygdala reactivity in overnight‐deprived smokers may reflect a pre‐existing vulnerability to smoking and/or increase the risk of smoking relapse after a cessation attempt. Hum Brain Mapp, 2011. © 2011 Wiley‐Liss, Inc.
Title SOC : Satisfaction-Oriented Virtual Machine Consolidation inEnterprise

Server sprawl is a problem faced by data centers, which causes unnecessary waste of hardware resources, collateral costs of space, power and cooling systems, and administration. This is usually combated by virtualization based consolidation, and both industry and academia have put many efforts into solving the underlying virtual machine (VM) placement problem. However, IT managers’ preferences are seldom considered when making VM placement decisions. This paper proposes a satisfaction-oriented VM consolidation mechanism (SOC) to plan VM consolidation while taking IT managers’ preferences into consideration. In the mechanism, we propose: i) an XML-based description language to express managers’ preferences and metrics to evaluate the satisfaction degree; ii) to apply matchmaking to locate entities (i.e., VMs and physical machines (PMs)) that best match each other’s preferences; iii) to employ the VM placement algorithm proposed in our previous work to minimize the number of hosts required and the resource wastage on allocated hosts. SOC is compared with two baselines: placement-only and matchmakingonly. The simulation results show that most of the VM-to-PM mappings output from placement-only violate given preferences, while SOC has a satisfaction degree close to matchmaking-only, without requiring too many PMs as matchmaking-only does, but only an amount close to placement-only. In brief, Xi Li · John Murphy Lero@UCD, School of Computer Science and Informatics, University College Dublin, Dublin, Ireland E-mail: xi.li@ucdconnect.ie; j.murphy@ucd.ie Anthony Ventresque Lero@UCD, School of Computer Science and Informatics, University College Dublin, and IBM Research, Smarter Cities Technology Centre, Damastown Industrial Estate, Dublin, Ireland E-mail: anthony.ventresque@ucd.ie James Thorburn IBM Software Group, Toronto, Canada E-mail: jthorbur@ca.ibm. com
Applications of Thick Film Screen Printing and Ink Jet Printing for the Manufacturing of Single Use, Disposable Biosensors

Thick film screen printing and ink jet printing are mature, costeffective manufacturing processes in micro-electronic industries. However, the applications of these processes to the production of chemical and biological sensors remain limited. The potential for using these technologies in producing cost-effective chemical and biological sensors, particularly for single use, disposable sensors has not been fully explored. Nano particle metallic catalysts have unique properties in many electrochemical reactions. Thus, the incorporation of nanoparticle catalysts into the thick film printing processing in the manufacturing of electrochemical based chemical and biological sensors can be attractive in the advance of the single use, disposable biosensor. Thus, the combined thick film printing and nano metallic catalysts approach is used in the manufacturing of cost effective, single use, disposable biosensors. This platform technology will be based on the enzymatic reactions which will yield an electrochemically active product such as H2O2, NADH, and NAD + .
Does Walkability Contribute to Geographic Variation in Psychosocial Distress? A Spatial Analysis of 91,142 Members of the 45 and Up Study in Sydney, Australia

Walkability describes the capacity of the built environment to promote walking, and has been proposed as a potential focus for community-level mental health planning. We evaluated this possibility by examining the contribution of area-level walkability to variation in psychosocial distress in a population cohort at spatial scales comparable to those used for regional planning in Sydney, Australia. Data on psychosocial distress were analysed for 91,142 respondents to the 45 and Up Study baseline survey between January 2006 and April 2009. We fit conditional auto regression models at the postal area level to obtain smoothed “disease maps” for psychosocial distress, and assess its association with area-level walkability after adjusting for individual- and area-level factors. Prevalence of psychosocial distress was 7.8%; similar for low (7.9%), low-medium (7.9%), medium-high (8.0%), and high (7.4%) walkability areas; and decreased with reducing postal area socioeconomic disadvantage: 12.2% (most), 9.3%, 7.5%, 5.9%, and 4.7% (least). Unadjusted disease maps indicated strong geographic clustering of psychosocial distress with 99.0% of excess prevalence due to unobserved and spatially structured factors, which was reduced to 55.3% in fully adjusted maps. Spatial and unstructured variance decreased by 97.3% and 39.8% after adjusting for individual-level factors, and another 2.3% and 4.2% with the inclusions of area-level factors. Excess prevalence of psychosocial distress in postal areas was attenuated in adjusted models but remained spatially structured. Postal area prevalence of high psychosocial distress is geographically clustered in Sydney, but is unrelated to postal area walkability. Area-level socioeconomic disadvantage makes a small contribution to this spatial structure; however, community-level mental health planning will likely deliver greatest benefits by focusing on individual-level contributors to disease burden and inequality associated with psychosocial distress.
Structure-Dynamics Relationships in Bursting Neuronal Networks Revealed Using a Prediction Framework

The question of how the structure of a neuronal network affects its functionality has gained a lot of attention in neuroscience. However, the vast majority of the studies on structure-dynamics relationships consider few types of network structures and assess limited numbers of structural measures. In this in silico study, we employ a wide diversity of network topologies and search among many possibilities the aspects of structure that have the greatest effect on the network excitability. The network activity is simulated using two point-neuron models, where the neurons are activated by noisy fluctuation of the membrane potential and their connections are described by chemical synapse models, and statistics on the number and quality of the emergent network bursts are collected for each network type. We apply a prediction framework to the obtained data in order to find out the most relevant aspects of network structure. In this framework, predictors that use different sets of graph-theoretic measures are trained to estimate the activity properties, such as burst count or burst length, of the networks. The performances of these predictors are compared with each other. We show that the best performance in prediction of activity properties for networks with sharp in-degree distribution is obtained when the prediction is based on clustering coefficient. By contrast, for networks with broad in-degree distribution, the maximum eigenvalue of the connectivity graph gives the most accurate prediction. The results shown for small () networks hold with few exceptions when different neuron models, different choices of neuron population and different average degrees are applied. We confirm our conclusions using larger () networks as well. Our findings reveal the relevance of different aspects of network structure from the viewpoint of network excitability, and our integrative method could serve as a general framework for structure-dynamics studies in biosciences.
A pilot study of a randomized controlled trial of yoga as an intervention for PTSD symptoms in women.

Posttraumatic stress disorder (PTSD) is a debilitating condition that affects approximately 10% of women in the United States. Although effective psychotherapeutic treatments for PTSD exist, clients with PTSD report additional benefits of complementary and alternative approaches such as yoga. In particular, yoga may downregulate the stress response and positively impact PTSD and comorbid depression and anxiety symptoms. We conducted a pilot study of a randomized controlled trial comparing a 12-session Kripalu-based yoga intervention with an assessment control group. Participants included 38 women with current full or subthreshold PTSD symptoms. During the intervention, yoga participants showed decreases in reexperiencing and hyperarousal symptoms. The assessment control group, however, showed decreases in reexperiencing and anxiety symptoms as well, which may be a result of the positive effect of self-monitoring on PTSD and associated symptoms. Between-groups effect sizes were small to moderate (0.08-0.31). Although more research is needed, yoga may be an effective adjunctive treatment for PTSD. Participants responded positively to the intervention, suggesting that it was tolerable for this sample. Findings underscore the need for future research investigating mechanisms by which yoga may impact mental health symptoms, gender comparisons, and the long-term effects of yoga practice.
Application of DNA Analysis in Quantifying Cashmere and Wool Binary Blend

Cashmere is one of the finest and softest animal fibers used by textile industry. False declaration is quite common due to its scarcity and high economic value. We have developed an objective method for quantifying cashmere and wool mixture based on DNA technology. Mitochondrial DNA, a species-specific genetic material exists in each cell, presenting a relatively strong capacity to resist physical and chemical treatments, seems to be an ideal target for species identification. As goat and sheep belong to a different genus, a real-time PCR based analysis method for quantifying cashmere and wool mixture was developed. Cashmere collected from different countries and regions were employed to prove its effectiveness. Dyed samples provided by CCMI round trial showed that it is a reliable and objective method. Various cashmere products of different processing stages were tested with the method. Results showed that the method can be applied in authenticity inspection of commercial products.
Effects of Exergames on Balance, Functional Mobility, and Quality of Life of Geriatrics Versus Home Exercise Programme: Randomized Controlled Study.

AIM To compare the effects of exergames (EGs) using the Xbox Kinect™ device and home exercise (HE) on balance, functional mobility, and quality of life of individuals aged 65 years or older. METHOD One hundred participants who met the inclusion criteria were randomized to the EG or HE group. The EG group took part in a 6-week programme using the Xbox360Kinect™ device, and the HE group took part in a 6-week balance exercise programme at home 5 days a week. The Berg Balance Scale (BBS) was used to assess balance, the Timed Up and Go (TUG) test was used to evaluate functional walking, and the Short Form 36 (SF-36) was used to assess quality of life. RESULTS Forty-eight participants in the EG group and 42 participants in the HE group completed the study. The groups were similar in terms of age, sex, and pretreatment values of BBS, TUG, and SF-36. Although the BBS scores of both groups improved significantly (all p<0.05), the post-treatment scores of the EG group were better than those of the HE group. The TUG scores improved only in the EG group (p<0.05). The increase in the BBS scores and decrease in the TUG test scores were significant only in the EG group (all p<0.05). A significant improvement was also observed in the quality of life parameters of physical functioning, social role functioning, physical role restriction, general health perceptions, and physical component scores in the post-exercise evaluations of the EG group. The participants commented that they found the EG programme very entertaining. CONCLUSION The EG can be considered a safe, entertaining and sustainable alternative to HE programmes, and it may have positive effects on balance, functional walking and quality of life in geriatric subjects.
LPS-Induced proNGF Synthesis and Release in the N9 and BV2 Microglial Cells: A New Pathway Underling Microglial Toxicity in Neuroinflammation

Purpose While aberrant activation of microglial cells was evidently involved in neuroinflammation and neurotoxicity in the neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease, objective of study was to address if activated microglias deliver their effect by releasing pro-neurotrophins. Materials and methods By in vitro culture of N9 and BV2 cell lines and lipopolysaccharide (LPS) stimulation model, generation and release of proNGF, proBDNF and MMP-9 was studied in the activated microglial cells by immunocytochemistry, western blotting and bioassay methods. Results Activation of microglial cells was observed with obvious increasing iba1-immunoreactivity following LPS stimulation in cell culture. Synthesis and up-regulation of proNGF protein significantly occurred in N9 and BV2 cells 12h-48h after LPS exposure, whereas no significant changes of proBDNF and MMP9 were observed in these microglial cell lines with LPS insult. More interestingly, extracellular release or secretion of proNGF molecule was also detected in culture medium of N9 cells after LPS stimulation. Finally, bioassay using MTT, Hoechst/PI and TUNEL staining in SH-SY5Y cells further confirmed that proNGF treatment could result in apoptotic cell death but it did not significantly influence cell viability of SH-SY5Y cells. Conclusions This in vitro study revealed LPS-stimulated proNGF synthesis and release in activated N9/BV2 microglial cell lines, also suggesting that proNGF may appeal a new pathway or possible mechanism underlying microglial toxicity in the neuroinflammation and a potential target for therapeutic manipulation of the neurodegenerative diseases.
Features of Magneto-Optical Response on Multilayer Nanostructures {(Co45Fe45Zr10)Z(Al2O3)100-Z/α-Si:H}n

Spectral and field dependencies of Transversal Kerr Effect (TKE) for [(Co45Fe45Zr10)Z(Al2O3)100-Z(X)/α-Si:H(Y)] n multilayers have been studied in the energy range 0.5 - 4.0 eV. It was found that TKE field dependencies in the nearest IR energy range exhibit anomalous behavior for structures only with thin Si layers and this behavior vanishes with increasing of the Si layer thickness. TKE spectra measured in small and large magnetic fields were essentially different. It was shown that magneto-optical response of multilayered structure composite-silicon is the sum of contributions from two composites: (Co45Fe45Zr10) - Al2O3 + Si + silicides and (Co45Fe45Zr10) - Si + silicides, which have a different sign of TKE in the nearest IR spectrum and their magnetic states depend both on composite and semiconducting layer thicknesses.
Risk-sensitive inverse reinforcement learning via semi- and non-parametric methods

The literature on inverse reinforcement learning (IRL) typically assumes that humans take actions to minimize the expected value of a cost function, i.e., that humans are risk neutral. Yet, in practice, humans are often far from being risk neutral. To fill this gap, the objective of this paper is to devise a framework for risk-sensitive (RS) IRL to explicitly account for a human’s risk sensitivity. To this end, we propose a flexible class of models based on coherent risk measures, which allow us to capture an entire spectrum of risk preferences from risk neutral to worst case. We propose efficient non-parametric algorithms based on linear programming and semi-parametric algorithms based on maximum likelihood for inferring a human’s underlying risk measure and cost function for a rich class of static and dynamic decision-making settings. The resulting approach is demonstrated on a simulated driving game with 10 human participants. Our method is able to infer and mimic a wide range of qualitatively different driving styles from highly risk averse to risk neutral in a data-efficient manner. Moreover, comparisons of the RS-IRL approach with a risk-neutral model show that the RS-IRL framework more accurately captures observed participant behavior both qualitatively and quantitatively, especially in scenarios where catastrophic outcomes such as collisions can occur.