Miracle-dz/UniFAR-FTUs huggingface dataset:
Predictive perioperative factors for developing severe sepsis after major surgery.

BACKGROUND Early identification of high-risk patients undergoing major surgery can result in an aggressive management affecting the outcome. METHODS We designed a prospective cohort study of 93 adult patients undergoing major oncological surgery to identify the predictive risk factors for developing postoperative severe sepsis. RESULTS Nineteen of 93 patients developed a severe sepsis after surgery; seven of the septic patients died in intensive care unit. Multivariate analysis discriminated preoperative and postoperative (first and second day after surgery) predictive risk factors. The postoperative severe sepsis was independently associated with preoperative factors like male gender (OR 4.7, 95% CI between 1.5 and 15.5, P<0.01) and Charlson co-morbidity index (OR 1.3, 95% CI between 1.07 and 1.6, P<0.01). After the surgery, the presence of systemic inflammatory response syndrome (OR 4.0, 95% CI between 1.02 and 15.7, P<0.05) and a logistic organ dysfunction score on day 2 (OR 3.3, 95% CI between 1.9 and 5.7, P<0.001) were found as independent predictive factors. CONCLUSION We have shown that some of the markers that can be easily collected in the preoperative or postoperative visits can be used to screen the patients at high risk for developing severe sepsis after major surgery.
Intelligent Control of Electric Scooters

Most of the present day electric scooters are equipped with a voltage-driven DC motor powered by four 12-volt leadacid batteries and a hand-lever accelerator operated by the rider to control their speed. Because of the nonlinear battery discharge characteristics and different driving behaviors of riders, it is not easy to tell how much electric power remaining in the battery and how far the electric scooter can travel before the battery has to be re-charged. As a result, the reliability of the electric scooter is lacking. To tackle this problem and to enhance the capabilities of present electric scooters, we propose an intelligent control system that not only can control the speed of the electric scooter, but also can provide information about residual electric power in the battery system by monitoring its power consumption. This system consists of both motor driver control and energy management subsystems. The driver control subsystem is implemented as a closed-loop speed control system by using a muscle-like control law with excellent compliant property. The energy management subsystem is implemented by learning modules based on fuzzy neural networks and cerebellar model articulation controller networks, which can estimate and predict nonlinear characteristics of the power consumption of batteries and electric scooter dynamics. With this battery power monitoring subsystem the rider will be provided information regarding an estimated traveling distance at a given speed, and the maximum allowable speed to guarantee safety arrival at the destination with the residual battery capacity. Experimental results show that the performance of electric scooters can be improved substantially.
NBER WORKING PAPER SERIES THE MACROECONOMIC IMPACT OF MICROECONOMIC SHOCKS: BEYOND HULTEN'S THEOREM

We provide a nonlinear characterization of the macroeconomic impact of microeconomic productivity shocks in terms of reduced-form non-parametric elasticities for efficient economies. We also show how structural microeconomic parameters are mapped to these reduced-form general equilibrium elasticities. In this sense, we extend the foundational theorem of Hulten (1978) beyond first-order terms to capture nonlinearities. Key features ignored by first-order approximations that play a crucial role are: structural elasticities of substitution, network linkages, structural returns to scale, and the extent of factor reallocation. In a business-cycle calibration with sectoral shocks, nonlinearities magnify negative shocks and attenuate positive shocks, resulting in an aggregate output distribution that is asymmetric (negative skewness), fattailed (excess kurtosis), and has a lower mean, even when shocks are symmetric and thin-tailed. Average output losses due to short-run sectoral shocks are an order of magnitude larger than the welfare cost of business cycles calculated by Lucas (1987). Nonlinearities can also cause shocks to critical sectors to have disproportionate macroeconomic effects, almost tripling the estimated impact of the 1970s oil shocks on world aggregate output. Finally, in a long-run growth context, nonlinearities, which underpin Baumol’s cost disease, account for a 20 percentage point reduction in aggregate TFP growth over the period 1948-2017 in the US. David Rezza Baqaee UCLA 315 Portola Plaza Los Angeles D.R. Baqaee@lse.ac. uk Emmanuel Farhi Harvard University Department of Economics Littauer Center Cambridge, MA 02138 and NBER emmanuel.farhi@gmail.com
Improving area efficiency of residue number system based implementation of DSP algorithms

Residue Number System based applications involve modulo-arithmetic which is typically implemented using look-up-tables (LUTs) for a small value of modulus. In this paper we present a data coding technique to minimize the area of these LUTs when implemented using two level logic structures such as PLAs. We also present a technique that exploits the symmetry in these computations to further optimize the LUTs. Results show that area improvement of upto 66% can be achieved using these techniques.
On the reputation of the California, Michigan and New Jersey supreme courts

ON THE REPUTATION AND PRESTIGE OF THE CALIFORNIA, MICHIGAN AND NEW JERSEY SUPREME COURTS by Robert Yonkers May 2014 Advisor: Dr. Susan Fino Major: Political Science Degree: Master of Arts This thesis examines Horizontal Federalism and Policy Dissemination in a federal system by analyzing the state supreme courts of California, Michigan and New Jersey during various terms in their history, using a unique form of citation analysis that builds upon prior efforts. I want to see what, if anything, a raw citation count says about prestige or reputation. For example, what types of cases are cited? Are they followed, not followed, or part of a dissent or concurrence? Are cases expanding the rights of the criminally accused cited frequently by sister courts? The normative literature associates prestige with expanding the rights of criminal suspects using state constitutions. (The New Judicial Federalism) Similarly, reputation and prestige are also associated with high citation counts by sister courts. My first objective is to determine what is actually being cited and why and my second purpose is to ascertain whether decisions expanding the rights of criminal suspects are more frequently cited than other types of cases. If prestige and the New Judicial Federalism are closely associated, and high citation counts denote prestige, then it follows that a large percentage of citations by sister courts would be to such decisions. I conclude that, contrary to expectations, decisions involving the New
Wet and dry deposition of atmospheric nitrogen at ten sites in Northern China

Abstract. Emissions of reactive nitrogen (N) species can affect surrounding ecosystems via atmospheric deposition. However, few long-term and multi-site measurements have focused on both the wet and the dry deposition of individual N species in large areas of Northern China. Thus, the magnitude of atmospheric deposition of various N species in Northern China remains uncertain. In this study, the wet and dry atmospheric deposition of different N species was investigated during a three-year observation campaign at ten selected sites in Northern China. The results indicate that N deposition levels in Northern China were high with a ten-site, three-year average of 60.6 kg N ha−1 yr−1. The deposition levels showed spatial and temporal variation in the range of 28.5–100.4 kg N ha−1 yr−1. Of the annual total deposition, 40% was deposited via precipitation, and the remaining 60% was comprised of dry-deposited forms. Compared with gaseous N species, particulate N species were not the major contributor of dry-deposited N; they contributed approximately 10% to the total flux. On an annual basis, oxidized species accounted for 21% of total N deposition, thereby implying that other forms of gaseous N, such as NH3, comprised a dominant portion of the total flux. The contribution of NO3− to N deposition was enhanced in certain urban and industrial areas, possibly due to the fossil fuse combustion. As expected, the total N deposition in Northern China was significantly larger than the values reported by national scale monitoring networks in Europe, North America and East Asia because of high rates of wet deposition and gaseous NH3 dry deposition. Taken together, these findings show that NH3 emissions should be abated to mitigate high N deposition and associated potential impacts on ecosystems in Northern China. The present results improve our understanding of spatio-temporal variations of magnitudes, pathways and species of deposited N in the target areas, and are important not only to inform conservation and regulatory bodies but also to initiate further detailed studies. Uncertainties among current observations underscore the need to quantify the impact of vegetation on dry deposition and to refine the simulation of dry deposition velocity.
Depression and Associated Risk Factors Among Medical and Allied Health Sciences Students of Southern Punjab, Pakistan

Aim: Depression is diagnosed mostly in medical and allied health sciences students and affects their study performance. The study was conducted to obtain the prevalence of depression of the students of a developing area. The study also aimed to find the socio-demographic variables that could be the cause of depression in students. Method: A cross-sectional study was carried out in medical and allied health sciences students. Beck Depression Inventory (BDI) scale was analysis tool of depression. The participants with BDI scores of ≥ 17 were considered depressive. For statistical analysis, Mann-Whitney U and Kruskal-Wallis analysis of variance were used. Results: 40% of students that have participated in survey showed BDI scores of ≥ 17. Results of study showed high BDI scores among 2nd year students, poor socio-economic status, poor study performance and urban area students. Conclusion: Depression prevalence in medical and allied health sciences students was found to be high that was significantly related to being junior in study institute, poor in socio-economic level and study.
Data Acquisition System Based on the Mixed Programming of SQL Language and MATLAB

The design software used in the Matlab interface as the application development platform, and with a SQL Server database as the background data storage tool, in order to achieve efficient human-computer interaction function. From the results of view, the end result meets the design requirements, host computer receives a wireless sensor network module transmission to the temperature, humidity, air flow and other data, and can achieve data preservation and call SQL Severs database functions. System can also process the data through the integrated oscilloscope showing a variety of waveforms, for data analysis and processing functions.
Parallel Pipeline Volume Intersection for Real-Time 3D Shape Reconstruction on a PC Cluster

The human activity monitoring is one of the major tasks in the field of computer vision. Recently, not only the 2D images but also 3D shapes of a moving person are desired in kinds of cases, such as motion analysis, security monitoring, 3D video creation and so on. In this paper, we propose a parallel pipeline system on a PC cluster for reconstructing the 3D shape of a moving person in real-time. For the 3D shape reconstruction, we have extended the volume intersection method to the 3-base-plane volume intersection. By thus extension, the computation is accelerated greatly for arbitrary camera layouts. We also parallelized the 3-base-plane method and implemented it on a PC cluster. On each node, the pipeline processing is adopted to improve the throughput. To decrease the CPU idle time caused by I/O processing, image capturing, communications over nodes and so on, we implement the pipeline using multiple threads. So that, all stages can be executed concurrently. However, there exists resource conflicts between stages in a real system. To avoid the conflicts while keeping high percentage of CPU running time, we propose a tree structured thread control model. As a result, We achieve the performance as obtaining the full 3D volumes of a moving person at about 12 frames per second, where the voxel size is 5×5×5 [mm^3]. The effectiveness of the thread tree model in such real-time computation is also proved by the experimental results.
Solving the quantitative skills gap: a flexible learning call to arms!

ABSTRACT Recent years have witnessed the emergence of a growing literature bemoaning the level of quantitative methods provision within the U.K. Higher Education sector, noting its negative impact upon the subsequent skills of graduates and their preparedness for the workplace. The present paper documents and evaluates an attempt to counter these issues via the introduction of an increasing element of flexible learning on a business and financial forecasting module. Using a mixture of empirical methods, it is shown that flexible learning results in improvements in student performance and ability across a range of metrics. It is argued that ‘broad’ forms of flexible learning can be employed to overcome the concerns of an increasingly negative literature on quantitative methods provision and the subsequent skills levels of students.
Ranking - Convex Risk Minimization

The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0−1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U -processes as well as empirical processes. Keywords—convex loss function, empirical risk minimization, empirical process, U -process, boosting, euclidean family
Exaggerated Electrodermal Startle Responses After Intracardiac Shock Discharges in Patients With Implanted Cardioverter Defibrillators

Objective We studied whether repetitive intracardiac shock discharges of implantable cardioverter defibrillators (ICDs) provoke an enduring enhancement of startle responses. Methods The study population comprised 134 patients with an ICD. Among those, 67 patients had experienced shock delivery. Thirty-five patients had received five or more shocks. We used the startle reflex paradigm, which consisted of 15 acoustic stimuli (95 dB, 1000 Hz, 500 ms duration). Skin conductance response was measured using a constant 0.5 V through 8-mm electrodes placed on each subject’s nondominant palm. Response magnitude was calculated by subtracting the baseline response level of the 2 seconds immediately preceding tone onset from the maximum response level within 1 to 4 seconds after tone onset. The left orbicularis oculi electromyogram (EMG) response was calculated by subtracting the mean EMG level during the 2 seconds immediately preceding tone onset from the highest EMG level measured within 40 to 200 ms after tone onset. Habituation was defined by the response slope of the regression equation and by the number of trials required to reach the nonresponse criterion. Results Although EMG response measures of magnitude and habituation failed to yield differences between study groups, patients who had experienced five or more ICD shocks exhibited a significantly larger skin conductance response magnitude in comparison to the patients who had experienced fewer than five shocks (median, interquartile range: 0.364, 0.209–0.618 vs. 0.512, 0.375–0.791; Mann-Whitney U test, p = .007). Poorer habituation in the group with five or more shocks in comparison with the low shock group was confirmed both by the number of trials needed to reach the nonresponse criterion (median, interquartile range: 10, 5–14 vs. 5, 2–13;p = .003) and by the response slope (median, interquartile range: 0.209, 0.116–0.274 vs. 0.262, 0.181–0.332;p = .008). After controlling for potential confounding factors (age, anxiety, aversiveness of stimuli, time since last shock experience, and use of &bgr;-adrenoceptor antagonists), intracardiac shock discharges had the strongest impact on augmented skin conductance response magnitude (adjusted odds ratio = 3.0, 95% confidence interval = 1.3–7.2, p = .01) and impaired habituation (adjusted odds ratio = 2.8, 95% confidence interval = 1.2–6.3;p = .015). Conclusions Intracardiac shock discharges are associated with augmented skin conductance responses and slower habituation, indicating sustained sympathetic arousability, which is presumably centrally mediated.
Information extraction based on probing algorithm with Bayesian approach

Document Annotation is the task of adding metadata information in the document which is useful in information extraction. Document annotation has emerged as a different stream in data mining. Majority of algorithms are concentrated on query workload. This paper uses Probing algorithm with Bayesian approach which identifies the attribute based on query workload, text frequency and content of the previous text annotation such as content value. This method has been implemented in datasets that facilitates data annotation and prioritizes the values of the attributes by ranking scheme. Query cost is also low when compared to other approach. The experimental analysis shows a better performance while comparing with other methods because probability theory provides a principled foundation for such reasoning under uncertainty.
Runtime monitoring of robotics software components: Increasing robustness of service robotic systems

Component Based Software Engineering is a common approach to master complexity in service robotic systems. Moreover, these systems must be robust and safe. Common robotic middlewares and frameworks provide component models with well defined communication mechanisms. However, generic means are missing to gain insight into running components. Components must be monitored (i) during their development for debugging purposes, (ii) during their integration into a system for verification and error detection purposes and (iii) at runtime for administration and online diagnosis purposes. This paper presents a generic concept for runtime monitoring of robotics software components which is independent of any specific robotic middleware and framework. After that, a reference implementation shows a concrete integration of the concept into the SmartSoft component model. Two real world scenarios at the end demonstrate the usage of monitoring.
Parkin Protects against Oxygen-Glucose Deprivation/Reperfusion Insult by Promoting Drp1 Degradation

Ischemic stroke results in severe brain damage and remains one of the leading causes of death and disability worldwide. Effective neuroprotective therapies are needed to reduce brain damage resulting from ischemic stroke. Mitochondria are crucial for cellular energy production and homeostasis. Modulation of mitochondrial function mediates neuroprotection against ischemic brain damage. Dynamin-related protein 1 (Drp1) and parkin play a key role in regulating mitochondrial dynamics. They are potential therapeutic targets for neuroprotection in ischemic stroke. Protective effects of parkin-Drp1 pathway on mitochondria were assessed in a cellular ischemia-reperfusion injury model. Mouse neuroblastoma Neuro2a (N2a) cells were subjected to oxygen-glucose deprivation/reperfusion (OGDR) insult. OGDR induces mitochondrial fragmentation. The expression of Drp1 protein is increased after OGDR insult, while the parkin protein level is decreased. The altered protein level of Drp1 after OGDR injury is mediated by parkin through ubiquitin proteasome system (UPS). Drp1 depletion protects against OGDR induced mitochondrial damage and apoptosis. Meanwhile, parkin overexpression protects against OGDR induced apoptosis and mitochondrial dysfunction, which is attenuated by increased expression of Drp1. Our data demonstrate that parkin protects against OGDR insult through promoting degradation of Drp1. This neuroprotective potential of parkin-Drp1 pathway against OGDR insult will pave the way for developing novel neuroprotective agents for cerebral ischemia-reperfusion related disorders.
Improving network performance through task duplication for parallel applications on clusters

While data replication is widely used in clusters to provide fault tolerance, it can heavily stress communication networks and degrade overall performance of parallel applications. The performance degradation is particularly unacceptable with disk-write-intensive applications. As a result, data duplication management for parallel applications running on clusters is a significant and urgent challenge. This paper presents the design, implementation, and evaluation of a network-aware task duplication management system, or TUFF, where redundant data can be regenerated by corresponding duplicate tasks rather than directly replicating through networks. In addition, TUFF is capable of improving availability performance of parallel applications, because TUFF allows two replicas of each I/O-intensive task to be executed on two different nodes. We have implemented and evaluated TUFF using extensive simulations under a diverse set of workload conditions. Experimental results show that TUFF improves the overall performance of parallel applications running on clusters by efficiently reducing network resource consumption.
Privacy-Enhanced Keyword Search in Clouds

The advent of cloud computing has dramatically changed the IT scene, as it offers cost savings and improvements to major operations. Nevertheless, the major obstacle relies on the effort on how to secure sensitive data files that are outsourced to the cloud environment. To ensure confidentiality, the sensitive data are usually encrypted prior to being outsourced. Nevertheless, effective data utilization remains a challenging task and there is a clear need for a secure and efficient searching mechanism over the encrypted data in the cloud, to increase the us-ability of the secure cloud environment. Unfortunately, existing work in the area of secure searching in the outsourcing scenario usually incur high computational complexity, which makes the approach impractical. In this paper, we take one step ahead by proposing an efficient keyword search scheme for cloud computing. Our solution is very lightweight, and it enables efficient multi-user keyword search over outsourced data files in the cloud environment, without leaking any private information about both the data owner and users in the search query. We formally define the security requirements and prove that our scheme is secure under a simple assumption in the standard model.