Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Excess Carbon Emissions and Soil Toxicity as Unintended Consequences in Applying Biochar as a Geoengineering Scheme

Executive Summary In the years since the Industrial Revolution, atmospheric carbon dioxide levels have steadily risen, causing an associated increase in global warming. In an attempt to remedy some of the effects caused by global warming, various geoengineering schemes have been put forth as possible solutions in resolving the global warming problem. A large portion of these geoengineering solutions are categorized as carbon sequestration techniques, where the geoengineering schemes vary from injecting liquefied carbon dioxide into the deep ocean or fertilizing the oceans with iron to stimulate phytoplankton growth. The focus of this proposal is on carbon sequestration via biochar burial. Biochar is a form of carbon produced via pyrolysis, or combustion with no oxygen or very little oxygen. The pyrolysis process produces a high-density form of carbon, which can be used to sequester carbon through underground burial. A practical implementation of carbon sequestration via biochar would be to convert decaying plant matter into biochar, rather than to allow natural decay from occurring, which releases carbon contained in the biomass back into the atmosphere. However, being an extremely new geoengineering method, biochar still needs to be tested for unintended consequences that may surface from its global application as a carbon sequestration technique. Therefore, this proposal identifies and tests for two important unintended consequences: unintentional carbon emissions from biochar production via the use of traditional kilns and soil toxicity affecting crop productivity due to residual hydrocarbon content contained in biochar. In many parts around the world, farmers produce biochar as a supplemental fertilizer by utilizing traditional kilns often constructed of brick or clay. Although these kilns are inexpensive and easy to construct, there is no way of containing the gaseous pyrolysis byproduct (known as syngas). Syngas is rich in carbon emissions, which then 2 becomes released into the atmosphere and adds to the existing excess quantities of greenhouse gases already present in the atmosphere. A rigorous experiment needs to be conducted to assess the amount of carbon emissions emitted through biochar production via traditional kilns in order to establish a recommendation for the most eco-friendly method of producing biochar. Additionally, hydrocarbons are produced naturally during the pyrolysis process, and are released during combustion in the form of liquid, which is often harvested in commercial pyrolysis machines as fuel. However, hydrocarbons may not be completely released from the solid char during pyrolysis, and residual hydrocarbon contained in biochar incorporated into the soil …
Circadian Oscillations within the Hippocampus Support Memory Formation and Persistence

The ability to sustain memories over long periods of time, sometimes even a lifetime, is one of the most remarkable properties of the brain. Much knowledge has been gained over the past few decades regarding the molecular correlates of memory formation. Once a memory is forged, however, the molecular events that provide permanence are as of yet unclear. Studies in multiple organisms have revealed that circadian rhythmicity is important for the formation, stability, and recall of memories (Gerstner et al., 2009). The neuronal events that provide this link need to be explored further. This article will discuss the findings related to the circadian regulation of memory-dependent processes in the hippocampus. Specifically, the circadian-controlled mitogen-activated protein kinase (MAPK) and cAMP signal transduction pathway plays critical roles in the consolidation of hippocampus-dependent memory. A series of studies have revealed the circadian oscillation of this pathway within the hippocampus, an activity that is absent in memory-deficient, transgenic mice lacking Ca2+-stimulated adenylyl cyclases. Interference with these oscillations proceeding the cellular memory consolidation period impairs the persistence of hippocampus-dependent memory. These data suggest that the persistence of long-term memories may depend upon reactivation of this signal transduction pathway in the hippocampus during the circadian cycle. New data reveals the dependence of hippocampal oscillation in MAPK activity on the suprachiasmatic nucleus, again underscoring the importance of this region in maintaining the circadian physiology of memory. Finally, the downstream ramification of these oscillations in terms of gene expression and epigenetics should be considered, as emerging evidence is pointing strongly to a circadian link between epigenetics and long-term synaptic plasticity.
Hysteresis Eff Ects in Economics – Diff Erent Methods for Describing Economic Path-dependence #468 Ruhr Economic Papers #468 Hysteresis Eff Ects in Economics – Diff Erent Methods for Describing Economic Path-dependence Bibliografi Sche Informationen Der Deutschen Nationalbibliothek Hysteresis Eff Ec

Relations between economic variables are often characterized by a situation where initial conditions and the past realizations of economic variables matter. I.e. past (transient) exogenous disturbances and past states of the economic system do have an infl uence on the current economic relations. Typical examples are the dynamics of (un)employment in business cycles and the dynamics of the nexus of exchange rate and exports. Since the standard characteristics of hysteresis apply – i.e. permanent eff ects of a temporary stimulus, resulting in path-dependent multiple equilibria – these economic phenomena are correctly titled as “hysteresis”. Empirical research in economics is using diff erent methods in order to capture pathdependent eff ects. First econometric approaches tried to describe these eff ects by simple timeseries processes with unit(or zero)-root dynamics. However, since unit-root-dynamics are not related to genuine multiple equilibria but on the order of integration of the time series, these fi rst attempts were expanded by more sophisticated time-series models integrating structural breaks, threshold-cointegration or non-linear autoregressive distributed lag-models. Another branch of empirical studies tries to keep closer to the original concept of the macroloop, trying to apply an explicit Mayergoyz/ Preisach aggregation procedure for heterogeneous fi rms – if microeconomic information is available based on panel-data – or by using simple algorithms analogous to mechanical-play in order to apply simple OLS-regression methods on a fi ltered/transformed input-output relation. In this paper, we give an overview of the implementation of hysteresis in economics, with an emphasis on two aspects: (1) the diff erentiation between microand macroeconomic hysteresis including an outline of an adequate aggregation procedure, and (2) diff erent methods applied in econometrics in order to capture economic path-dependency empirically. JEL Classifi cation: C51, C62
Fast approximated relational and kernel clustering

The large amount of digital data requests for scalable tools like efficient clustering algorithms. Many algorithms for large data sets request linear separability in an Euclidean space. Kernel approaches can capture the non-linear structure but do not scale well for large data sets. Alternatively, data are often represented implicitly by dissimilarities like for protein sequences, whose methods also often do not scale to large problems. We propose a single algorithm for both type of data, based on a batch approximation of relational soft competitive learning, termed fast generic soft-competitive learning. The algorithm has linear computational and memory requirements and performs favorable to traditional techniques 1.
Classification of Spontaneous Speech of Individuals with Dementia Based on Automatic Prosody Analysis Using Support Vector Machines (SVM)

Analysis of spontaneous speech is an important tool for clinical linguists to diagnose various types of neurodegenerative disease that affect the language processing areas. Prosody, fluency and voice quality may be affected in individuals with Parkinson's disease (PD, degradation of voice quality, unstable pitch), Alzheimer's disease (AD, monotonic pitch), and the non-fluent type of Primary Progressive Aphasia (PPA-NF, hesitant, non-fluent speech). In this study, the performance of a SVM classifier is evaluated that is trained on acoustic features only. The goal is to distinguish different types of brain damage based on recorded speech. Results show that the classifier can distinguish some dementia types (PPA-NF, AD), but not others (PD).
A World of Competitors: Assessing the US High-Tech Advantage and the Process of Globalisation

Research universities throughout the world are part of a larger effort by countries to bolster science and technological innovation and compete economically. The United States remains highly competitive as a source of high-tech innovation because of a number of market positions, many the results of long-term investments in institutions (such as research universities) and in research and development funding, and more broadly influenced by a political culture that has tended to support entrepreneurs and risk taking. In essence, the United States was the first mover in pursuing the nexus of science and economic policy. The following essay attempts to place universities within this larger political and policy environment by discussing market factors that have influenced knowledge accumulation and high-tech innovation in the United States. It also gives an assessment of their current saliency in the face of globalisation and the growing market position of competitors, such as the European Union. The article also provides observations on major US state-based high-tech initiatives intended to create or sustain knowledge-based economic areas, and discusses the prospect of a major new federal initiative to increase national research and development funding.
OPTIMAL SELECTION OF SERVICE RATES IN QUEUEING WITH DIFFERENT COST

A single server queueing system with Poisson arrival is considered. The service time is a random variable exponentially distributed with the rate that can be selected from a set of K different rates. The queue has only a limited capacity N and those customers finding system with N persons will not stop. For different cost structure a service rate switching policy is found which minimizes the expected long run average cost.
Teachers’ aims of laboratory work in secondary school in Sweden

Introduction Laboratory work and practical work are common and significant components of science education. Teachers are expected by tradition, culture and curriculum (e.g. Boud, Dunn and Hegarty-Hazel, 1989; Lunetta, 1998; Skolverket, 1998) to involve labwork as a part of science education. Swedish National Curriculum (Skolverket, 1998) renders objectives involving for example development of students’ scientific skills, knowing how to plan and perform investigations and to critically analyze results. Two of the most important goals with labwork are to act as a link between theory and practice and to offer laboratory skills. There is an ongoing discussion about the efficiency of labwork for learning science (Hult, 2000; Tiberghien, Veillard, Le Maréchal, Buty and Millar, 2001). Based on my experience as a science teacher, there is a need to alter labwork. Individual teachers play a significant role in labwork conducted in science teaching and thus affects learning outcome from labwork. In this sense, teachers have to present comprehensive curriculum aims to motivate and engage students in meaningful labwork (Leach and Scott, 2003). The study presented here deals with teachers’ choices which depend on their views of science and learning in addition to e.g. practical and institutional constraints. By interviews and text analysis related to their own science teaching, secondary school teachers’ views were explored. The study was designed to describe and increase knowledge and understanding about teachers aims of laboratory work, e.g. their pre-labwork decisions. Some questions are: What choices are made by teachers, and how are they motivated? Do teachers’ aims with labwork correspond to teachers’ descriptions of labwork? How do teachers’ choices affect students’ prerequisites of learning from labwork? The purpose is to enlighten teachers’ labwork aims and objectives, motifs and priorities. Further studies in the PhD-project will explore what implications teachers’ aims have in reality and how students interpret these aims.
Cost-effectiveness of fluticasone propionate administered via metered-dose inhaler plus babyhaler spacer in the treatment of asthma in preschool-aged children.

STUDY OBJECTIVES To evaluate the cost-effectiveness of inhaled fluticasone propionate (FP) in children aged 12 to 47 months with asthma symptoms. DESIGN A retrospective economic analysis conducted from the perspective of the Danish health-care system, based on clinical data from a 12-week study. SETTING Thirty-three outpatient centers in nine countries. PATIENTS Two hundred thirty-seven children aged 12 to 47 months with documented history of recurrent wheeze or asthma symptoms. INTERVENTIONS Two dosages of FP, 100 microg/d and 200 microg/d, and placebo administered in two divided doses via a metered-dose inhaler and a Babyhaler (Glaxo Wellcome; Middlesex, UK) spacer device. MEASUREMENTS Effectiveness in terms of asthma exacerbations, control of cough and wheeze symptoms, symptom-free days, overall direct costs of asthma management in Danish kroner at 1999 prices, and mean and incremental cost-effectiveness ratios. RESULTS FP, 200 microg/d, was significantly more effective than placebo treatment in terms of the proportion of exacerbation-free patients (73.7% vs 59.8%; p = 0.025) and patients experiencing a > or = 25% improvement in cough symptoms (57.9% vs 39.0%; p = 0.018). The costs per exacerbation-free patient, per patient with a > or = 25% improvement in cough and wheeze symptoms from baseline, and per symptom-free day were lower in the FP groups than in the placebo group. The incremental cost-effectiveness ratios for these end points indicated that the additional benefits of FP, 200 microg/d, were achieved at a lower overall cost compared with placebo treatment. CONCLUSIONS From the perspective of the Danish health-care system, FP, 100 microg bid, administered via the Babyhaler inhalation device was cost-effective relative to standard therapy with bronchodilators alone.
Validation of a multivariable relay-based PID autotuner with specified robustness

This paper presents a multivariable relay-based PID autotuning strategy, which ensures a specified modulus margin (i.e. robustness). The algorithm is applied on the coupled quadruple tanks from Quanser. The system is challenging for control since it presents non-minimum phase transmission zeros. The performance of the autotuner is validated against a computer-aided design tool based on the frequency response, i.e. FRTool. The experimental results suggest that the proposed autotuning procedure has similar performance as the control design based on full knowledge of the system. This is a remarkable conclusion and provides a good motivation to claim that our algorithm may be useful in chemical process applications where full knowledge of the systems model is still a burden for the control engineer.
Piezoelectric energy harvesting in wireless sensor networks

The Usage of small scale and low power portable and wireless electronic devices is significantly increasing in wireless sensor networks (WSN). Also due to increase in number of these small scale devices, energy consumption is experiencing a substantial growth. Different researchers are now having a great interest in energy harvesting. Piezoelectric materials are assumed as excellent for power generation due to their better coupling properties. Piezoelectric material PZT-5H is used to harvest energy in wireless sensor network due to its very high permittivity and sensitivity property. These materials have electromechanical properties which are used to harvest energy. A cantilevered plate of size 16mm × 16mm × 1mm is considered. Finite element modeling of a plate is done and first five natural frequencies are calculated. Natural frequency is used to calculate the power which is further used to calculate the generated voltage with the help of resistive load. These materials can be used as sensors and actuators and can also be implemented in micro electromechanical systems. This paper presents an analysis of energy harvesting with micro electromechanical systems (MEMS). In this paper, a power of 155.2 μW and voltage of 5.8573 V has been generated with 1 mg of mass with device having a resonant frequency of 1766.5 Hz.
A Graph-Based Consensus Maximization Approach for Combining Multiple Supervised and Unsupervised Models

Ensemble learning has emerged as a powerful method for combining multiple models. Well-known methods, such as bagging, boosting, and model averaging, have been shown to improve accuracy and robustness over single models. However, due to the high costs of manual labeling, it is hard to obtain sufficient and reliable labeled data for effective training. Meanwhile, lots of unlabeled data exist in these sources, and we can readily obtain multiple unsupervised models. Although unsupervised models do not directly generate a class label prediction for each object, they provide useful constraints on the joint predictions for a set of related objects. Therefore, incorporating these unsupervised models into the ensemble of supervised models can lead to better prediction performance. In this paper, we study ensemble learning with outputs from multiple supervised and unsupervised models, a topic where little work has been done. We propose to consolidate a classification solution by maximizing the consensus among both supervised predictions and unsupervised constraints. We cast this ensemble task as an optimization problem on a bipartite graph, where the objective function favors the smoothness of the predictions over the graph, but penalizes the deviations from the initial labeling provided by the supervised models. We solve this problem through iterative propagation of probability estimates among neighboring nodes and prove the optimality of the solution. The proposed method can be interpreted as conducting a constrained embedding in a transformed space, or a ranking on the graph. Experimental results on different applications with heterogeneous data sources demonstrate the benefits of the proposed method over existing alternatives. (More information, data, and code are available at http://www.cse.buffalo.edu/~jing/integrate.htm.)
Modular Architecture of a Motion Controller for Quadrupeds Applied to the Walking Robots ALDURO and BISAM

As a contribution to the gait generation and motion control of quadrupeds a concept has been formulated that in its modular structure can be easily adapted and extended. It is generally suitable for quadrupedal walking machines (as shown for Alduro and Bisam) and only a few modules need to be adapted according to the machine specific topology.
Driver fatigue detection using machine vision approach

Driver fatigue plays a vital role in a large number of accidents. In this paper, a real time, machine vision-based system is proposed for the detection of driver fatigue which can detect the driver fatigue and can issue a warning early enough to avoid an accident. Firstly, the face is located by machine vision based object detection algorithm, then eyes and eyebrows are detected and their count (four or less) is computed. By comparison of the calculated number of black spots, with a predefined value, which is four (Two eyes and two eye brows), for a particular time interval, driver fatigue can be detected and a timely warning can be issued whenever there will be symptoms of fatigue. The main advantage of this system is its fast processing time and very simple equipment. This system runs at about 15 frames per second with a resolution of 320*240 pixels. This algorithm is implemented using MATLAB platform along with camera and is well suited for real world driving conditions since it can be non-intrusive by using a video camera to detect changes.
Web sessions clustering for behavioral targeting

In this paper we present our on going e ort to compare web sessions clusters based on di erent web sessions representations. Sessions within the same cluster represent common navigation patterns. We assume that users with the same navigation patterns have common interests and motivations at a point in time. Therefore, we represent sessions based on descriptions extracted from the URLs as well as, using temporal references. The session clusters were obtained using the K-Means algorithm. The results show that is possible to nd groups of sessions containing similar pages visited. It is also possible to extract intelligible descriptions from the sessions clusters. However, in the future, it is expected to evaluate the results obtained using an internal criteria.
Salvianolic Acid Improves Status Epilepticus and Learning and Memory Deficiency in Rat Model of Temporal Lobe Epilepsy

Background and Objective: Epilepsy is a long-lasting central nervous system disorder that is accompany with spontaneous seizures and insufficiency in learning and memory. Now drug treatment is the most common therapy but some patients do not research to suitable control of their seizures with current drugs. Hence, new treatment is needed to help those patients that are unaffected to existing drugs. In present study, we evaluate the protective effect of pretreatment with salvianolic acid B in experimental model of temporal lobe epilepsy in male rats.
Moving the mobile Evolved Packet Core to the cloud

In this paper, we describe an evolution of the mobile Evolved Packet Core (EPC) utilizing Software Defined Networking (SDN) that allows the EPC control plane to be moved into a data center. The EPC is a mobile aggregation network standardized by 3GPP for deployment of fixed and 4G mobile broadband services, having interoperability features for 3G and 2G mobile services. While mobile networks already deploy a considerable amount of software control, the ability of OpenFlow to decouple the control and data planes for IP routing provides the opportunity to simplify the configuration and maintenance of mobile aggregation networks by eliminating the distributed IP routing control plane. We extend OpenFlow 1.2 with two vendor extensions, one defining virtual ports to allow encapsulation and decapsulation and another to allow flow routing using the GTP Tunnel Endpoint Identifier (TEID). The result enables an architecture where the GTP control plane can be lifted up out of network elements such as the Serving Gateway and the Packet Data Network Gateway (PDN Gateway) and moved into a controller running in a virtual machine in a data center. The EPC network elements then run a simplified OpenFlow control plane, enhanced with GTP TEID routing extensions. We discuss a few new features that are enabled with GTP TEID routing and the status of a prototype.
The Brinson Model

RC H IN IG H TS Damien Laker is Director of Performance Attribution Strategy at Barra. Damien joined Barra in December 2002 when Barra acquired Investment Performance Objects (IPO), a company that Damien founded in 1998. IPO provided cutting edge investment performance analytics software for global asset managers. At the time of the acquisition, IPO had five clients in Australia, and one client in the UK.