Miracle-dz/UniFAR-FTUs huggingface dataset:
Flurbiprofen used in one-lung ventilation improves intraoperative regional cerebral oxygen saturation and reduces the incidence of postoperative delirium

Background We previously demonstrated that flurbiprofen increased arterial oxygen partial pressure and reduced intrapulmonary shunts. The present study aims to investigate whether flurbiprofen improves intraoperative regional cerebral oxygen saturation (rScO2) and reduces the incidence of postoperative delirium (POD) in elderly patients undergoing one-lung ventilation (OLV). Methods One hundred and twenty patients undergoing thoracoscopic lobectomy were randomly assigned to the flurbiprofen-treated group (n = 60) and the control-treated group (n = 60). Flurbiprofen was intravenously administered 20 minutes before skin incision. The rScO2 and partial pressure of arterial oxygen (PaO2) were recorded during the surgery, and POD was measured by the Confusion Assessment Method (CAM) within 5 days after surgery. The study was registered in the Chinese Clinical Trial Registry with the number ChiCTR1800020032. Results Compared with the control group, treatment with flurbiprofen significantly improved the mean value of intraoperative rScO2 as well as the PaO2 value (P < 0.05, both) and significantly reduced the baseline values of the rScO2 area under threshold (AUT) (P < 0.01) at 15, 30, and 60 min after OLV in the flurbiprofen-treated group. After surgery, the POD incidence in the flurbiprofen-treated group was significantly decreased compared with that in the control group (P < 0.05). Conclusion Treatment with flurbiprofen may improve rScO2 and reduce the incidence of POD in elderly patients undergoing thoracoscopic one-lung ventilation surgery for lung cancer. Clinical trial registration http://www.chictr. org/cn/, identifier ChiCTR1800020032.
Topology-based Algorithm for Users' Influence on Specific Topics in Micro-blog ⋆

In recent years, users’ influence in the Micro-blog has been studied extensively in the field of social network. Most previous studies are based on a single factor including followers, followees and tweets. However, Micro-blog is different from other social network services. It is difficult to truly reflect the scale and nature of the users’ influence with a single factor in the service. In this paper, we focus on the ranking strategies of users for specific topics in terms of two major factors (users’ activities and quality of tweets), which are highly relevant to the social network properties of the Micro-blog users and the properties of the Micro-blog itself. As a step forward, we propose a Weighted Ranking Algorithm (WRA) through analysing Kendall’s correlation of different rank lists by the two factors. The experimental results based on a large-scaled real dataset from Sina Micro-blog show that the proposed WRA algorithm is more effective than the existing algorithms.
An Analysis of the Factors Affecting the Spending and Saving Habits of College Students

This paper analyzes spending and saving behavior among students of various class years, ethnicities, and gender at Skidmore College using data collected from an original survey. The models incorporate both demographic characteristics as well as pertinent economic theory. Results indicate that Whites and Asians spend significantly more than other ethnicities while Blacks save significantly more. Findings also provide support for the Permanent Income Hypothesis, however, no significance was found regarding Hyperbolic Discounting.
Expression and prognosis analysis of PAQR5 in kidney cancer

Progestin and adipoQ receptor 5 (PAQR5) affects the development of various malignancies and is specifically expressed in kidney. However, the role of PAQR5 in renal carcinoma remains unclear. We assessed the state of PAQR5 expression in kidney renal clear cell carcinoma (KIRC) by The Cancer Genome Atlas and Gene Expression Omnibus datasets. Moreover, immunohistochemistry was performed to observe the expressions of PAQR5 protein in tumor tissues. The relationships between PAQR5 expression and clinical characteristics were investigated by UALCAN. Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier plotter were used to analyze the effect of PAQR5 expression levels on overall survival and relapse-free survival (RFS). The re lationships between clinical characteristics and survival were also evaluated by univariate and multifactorial Cox regression. Gene Ontology term analysis, Kyoto Encyclopedia of Genes and Genomes analysis, and gene set enrichment analysis were performed on PAQR5 to explain the enrichment pathways and functions. Protein and protein interactions were explained by GeneMANIA and STRING. We also explored the relevance of PAQR5 to tumor immune cell infiltration and immunomodulatory molecules by TIMER and GEPIA. Finally, we explored the correlation of PAQR5 with the pathway proteins STATs, HIF-1α, and mTOR using the GSE40435 dataset. PAQR5 expression was low in KIRC and correlated significantly with clinical characteristics including cancer stage, tumor grade, and nodal metastasis status. Low PAQR5 expression was significantly associated with poorer survival. Cox regression analysis indicated that upregulation of PAQR5 was an independent factor for a good prognosis of KIRC. PAQR5 downregulation was associated mainly with STAT3 target upregulation, tumorigenesis, and poor differentiation. PAQR5 expression also correlated positively with B cells, neutrophils, macrophages, and dendritic cells and negatively with the infiltration of FOXP3+ Treg cells and the immune checkpoint molecules PD-1, CTLA4, and LAG3. Moreover, PAQR5 expression in KIRC was negatively correlated with the pathway proteins STAT1/2/3/4/5A, HIF-1α, and mTOR. PAQR5 is an excellent predictor of KIRC prognosis and may be a potential molecular therapeutic target.
A Multi-Source Model of Perceived Organizational Support and Performance

This field study asks three questions concerning perceived organizational support (POS): 1) Does support from stakeholders such as direct reports predict POS? , 2) Does an additive model of support stemming from supervisors (PSS), coworkers (PCS), and direct reports/internal customers (DRS) predict POS better than the individual support variables? , and 3) Does POS predict counterproductive work behaviors (CWB)? Results (n=154) indicate strong relationships among all support variables, but only PCS and PSS predict POS. Findings also indicate POS is a strong predictor of both in-role and extrarole performance, as well as counterproductive work behaviors. Practical and theoretical implications are discussed.
Plasmapheresis vs . immunoglobulin in autoimmune neurologic diseases : a meta-analysis Word counts for :

Objectives: to evaluate the efficacy and safety of human immunoglobulin versus plasmapheresis in the management of autoimmune neurologic diseases. Likewise, length of hospital stay and duration of ventilator support were compared. Methods: Randomized controlled trials and analytical observational studies of more than 10 cases, were reviewed. Cochrane Neuromuscular Disease Group trials, MEDLINE, EMBASE, HINARI Ovid, the Database of abstracts of reviews of effectiveness and the Economic evaluation Database were searched as data source. Reference lists were examined for further relevant articles. A random-effect model was used to derive a pooled
Multi-level Massive Data Visualization: Methodology and Use Cases

This research focuses on massive data visualization that is based on dimensionality reduction methods. We propose a new methodology, which divides the whole data visualization process into separate interactive steps. In each step, some part of data can be selected for further analysis and visualization. The different dimensionality method can be chosen/changed in each step. The decision which methods to be chosen depends on desirable accuracy measures and visualization samples. In addition, there are provided statistical measures of the identified clusters. We have developed a special tool, which implements the proposed methodology. R language and Shiny package were used for developing the tool. In the paper, the principles of the methodology and features of the tool are presented by describing the specific use case.
Advanced wireless localisation methods dealing with incomplete measurements

Positioning techniques have become an essential part of modern engineering, and the improvement in computing devices brings great potential for more advanced and complicated algorithms. This thesis first studies the existing radio signal based positioning techniques and then presents three developed methods in the sense of dealing with incomplete data. Firstly, on the basis of received signal strength (RSS) location fingerprinting techniques, the Kriging interpolation methods are applied to generate complete fingerprint databases of denser reference locations from sparse or incomplete data sets, as a solution of reducing the workload and cost of offline data collection. Secondly, with incomplete knowledge of shadowing correlation, a new approach of Bayesian inference on RSS based multiple target localisation is proposed taking advantage of the inverse Wishart conjugate prior. The MCMC method (Metropolis-within-Gibbs) and the maximum a posterior (MAP) / maximum likelihood (ML) method are then considered to produce target location estimates. Thirdly, a new information fusion approach is developed for the time difference of arrival (TDOF) and frequency difference of arrival (FDOA) based dual-satellite geolocation system, as a solution to the unknown time and frequency offsets. All proposed methods are studied and validated through simulations. Result analyses and future work directions are discussed.
A constraint monitor algorithm for the Cassini spacecraft

The Cassini spacecraft is commanded to turn from one point in space to another by commanding attitude, rate, and acceleration profiles, which the Attitude Controller is required to execute faithfully. Thc Constraint Monitor algorithm performs appropriate checks to ensure the legality and the realizability of the instantaneous attitude, rate, and acceleration commands. When the command is found to be unrealizable because of hardware limitations or itlegal because it may enter a constraint space, Constraint Monitor modifies it appropriately such that the legality of the command is maintained. In doing so it ensures that the rate and acceleration are not outside the capabilities of the attitude control hardware and that certain sensitive spacecraft boresights are protected from exposure to bright objects. The Cassini spacecraft, scheduled for launch in October 1997, will arrive at Saturn in 2004. On its way to Saturn, it will fly by Venus, Earth, and Jupiter to pick up the needed gravity assists. The spacecraft will be carrying a probe intended for delivery into the Titan atmosphere. The probe entry into the Titan atmosphere will occur about four months after Saturn arrival. Tltc spacecraft will conduct a tour of the Saturnian system for approximately four years. Several close flybys of Titan and Saturn's icy satellites are planned. The nominal mission will conclude in the year 2008. Cassini science objectives include investigation of Saturn's atmospheric composition, winds and temperature, configuration and dynamics of the magnetosphere, structure and composition of the rings, characterization of the icy satellites, and Titan's atmospheric constituent abundance. The rack mapper will perform surface imaging and altimetry during each Titan flyby. Cassini was originally onc of the two spacecraft of Mariner Mark 11 series intended for multi-mission purpose: the CRAF (Comet Rendezvous and Asteroid Flyby) and Cassini. The CRAF mission was to follow a comet ,artd conduct scientific investigations for 120 days and Iatcr flyby an asteroid. NASA budget constraints ncccssitzzted the cancellation of CRAF and dcscoping of Cassini spacecraft. Both the high and low precision scan platforms and their structural booms were deleted, m was the turn table which carried a fields and particles experiment. The spacecraft basebody zmurncd the role of the observation platform and the entire spacecraft now had to turn in order to do earth pointing, star tracking, and remote science pointing. This makes the detection and avoidance of spacecraft attitude constraints ever more difficult since movement of one boresight requires turning …
SMPCEngine: An N-Party Implementation of the Secure Multiparty Private Computation Protocol

SMPCEngine: An N-Party Implementation of the Secure Multiparty Private Computation Protocol Nicholas D. McKinney Chair of the Supervisory Committee: Dr. Anderson C.A. Nascimento Institute of Technology In this thesis, we implement a framework for secure multiparty computation. Our framework works in the commodity-based model, where the players running the distributed computation receive pre-distributed data from a trusted source during a setup phase. The framework allows secure multiplications of field elements, secure multiplications of matrices and matrix inversions. Differently from previous proposals, in our framework, the running times do not increase significantly as more players are added to the protocol. We illustrate the power of our solution by applying it to the problem of privately estimating driver’s drowsiness based on EEG data. We show that our private solution is practical and achieves a similar accuracy as a solution in the clear, where there are no privacy concerns.
Predicting Software Reliability using Computational Intelligence Techniques: A Review

Software measurement is yet in an infant stage. There is hardly any efficient quantitative method to represent software reliability. The existing methods are not generic and have many limitations. Various techniques could be used to enhance software reliability. However, one has to not only balance time but also cater to budget constraints. Computational Intelligence (CI) techniques that have been explored for software reliability prediction have shown remarkable results. In this paper, the applications of CI techniques for software reliability prediction are surveyed and an evaluation based on some selected performance criteria is presented.
Modified metropolis annealing algorithm for QM-AYA arithmetic coder design optimization

The QM-Coder is an adaptive binary arithmetic coder for the JPEG and JBIG image compression standards. This coder employs a probability estimation state table (finite state machine). The present state corresponds to the current probability estimate. The estimate takes the form of the augend value that (on encode) is added to the code string if the less probable symbol occurs. The state changes only if the arithmetic coder experiences a renormalization. The QM-AYA coder is derived from the Q-Coder and the QM-Coder. A modified Metropolis method was used to fine-tune the QM-AYA augend values for improved compression performance. Heuristics in the search strategy to determine the next change in augend values reduce the estimated 54 year run time of the generalized annealing algorithm to 4 weeks.
Computational Methods for the Integrated Deterministic and Probabilistic Safety Assessment of a Simplified Cooling Circuit for a Tokamak Superconducting Magnet

The objective of this thesis is considering the safety analysis of the simplified cooling system of a single module of the ITER Central Solenoid in a cold test facility to classify the different abnormal transients and identify the components failure that may drive the system into a Loss-Of-Flow Accident. The IDPSA framework is applied for the first time to a fusion system to study the dynamic response of the system. Two different operating condition are considered: a first simplified case, in which it is assumed a constant current flowing in the module. In the second part, the real ITER current scenario is considered to study the consequence of the abnormal transients both for the safety of the facility and the consequence for ITER. In fact, the hot-spot temperature of the strands computed in this second case can be assumed close to the values reached in ITER. A set of 100 different accidental scenarios is generated according to the Multiple Value Logic and it is simulated using the validate 4C thermal-hydraulic code. To post-process the scenarios, it is applied the spectral clustering algorithm to identify the most similar scenarios grouped using the Fuzzy-C-Means. The results are compared with the ones obtained using the ESAX algorithm. The Silhouette and the DaviesBouldin indexes are used to evaluate the clusters obtained and to choose the spectral clustering as best algorithm. Its results are used to identify the prototypical components failure that may drive the system to evolve towards the different clusters obtained.
Repair and Replacement Strategy for Optimizing Cost and Time of Warranty Process using Integer Programming

Warranty is an assurance issued by a company as the manufacturer to guarantee that its product is damage-free within a specified period. The warranty process is usually carried out when a complaint or damage regarding the product is received. The warranty process consists of two decisions that the company establishes to handle the process. The occurring problem is in the warranty process; there is not any standard established to determine the cost to incur for the warranty process. In this research, integer programming method was used to do optimization on repair and replacement strategy in warranty process. Before doing optimization, mathematical model must be created. Using that mathematical model, the results show that the costs of the warranty process decrease by 16.97%, while the time increases by 13.9%. So, with this method company will be increase the profit.
The Silence of Memory: Armistice Day, 1919-1946

Lest we forget - the invention and reception of Armistice Day unknown soldiers - the marginality of veterans on 11 November and men like flowers are cut - the Haig Poppy appeal 1919-39 the undertones of war - Armistice Day in the thirties the irony of history - Armistice Day from peace to war God our help - the churches, Armistice Day and Remembrance Sunday the restoration of tradition?
Fundamental Circuit Topology of Duo-Active-Neutral-Point-Clamped, Duo-Neutral-Point-Clamped, and Duo-Neutral-Point-Piloted Multilevel Converters

Multilevel voltage-source converters are well-suited for power conversion applications demanding higher power density, reliability, efficiency, and power quality. An unremitting and persistent research for developing advanced multilevel converter topologies with improved characteristics, performance, modulation techniques, and control methods continues. This paper proposes duo-neutral-point-clamped (D-NPC), duo-active-neutral-point-clamped (D-ANPC), and duo-neutral-point-piloted (D-NPP) multilevel voltage-sourced converter topologies. The D-NPC, D-ANPC, and D-NPP converters phase-leg is realized by adding low-frequency semiconductor power switches to their structures. This results in a substantial reduction in the number of the high-frequency pulsewidth-modulation insulated-gate bipolar transistors and clamping passive devices including diodes as well as flying-capacitors (FCs). Moreover, a drastic abatement in the total voltage rating and total stored energy of the FCs within the D-ANPC topology is achieved compared to the classic ANPC configuration. The experimental results are provided for D-NPC, D-ANPC, and D-NPP converters to validate the feasibility of their topology and modulation method for control of the multilevel converters.
Determining the difficulties of massive mımo technology for next generation wireless systems

Next generation wireless communications systems are emerging as new requirements for spectral efficiency and energy efficiency. Many multiple-input multiple-output (MIMO) systems, with dozens or even hundreds of antennas, can provide significant improvements in spectral efficiency, energy efficiency and system reliability. Realistic channel models are indispensable for the design, performance evaluation and optimization of Massive MIMO wireless systems. With this technique, many improvements will be possible. However, Massive MIMO also has some difficulties such as signal processing complexity, size of antenna arrays, etc. for next generation wireless systems. For this reason, this paper is to determine coming challenges and research directions of the intended Massive MIMO system.
Framework for handling data veracity in big data

Big Data is the term used for massive amount of data collected by different means and in various formats. Data Veracity refers to the uncertainty of available data; this means that the quality of the collected data cannot be trusted. This paper reports on ongoing research based on using the Semantic Web technology to verify user entered data and increase dependability on Big Data. Validating, cleaning and reducing collected data are the major activities required to enhance the quality of the collected data.
A Multilevel Hazards Model for Child Mortality In Nigeria

Many researchers have devoted considerable attention to the impact of individual-level factors on child mortality, but little is known about how family and community characteristics affect health of children. Trend in child mortality as well as its determinants, has long been the subject of academic and policy debates. In spite of this, the problem of child mortality remains as daunting as ever. In fact, advancement in medical sciences and the upsurge in information and telecommunication technology equipment have not significantly reduced child mortality in the country, unlike in the West. The Multilevel proportional hazards model for data that are hierarchically clustered at three levels was applied to the study of covariates of child mortality in Nigeria. This study merges two parallel developments of statistical tools for data analysis: statistical methods known as hazard models that are used for analyzing event-duration data and statistical methods for analyzing hierarchically clustered data known as multilevel models. These developments have rarely been integrated in research practice and the formalization and estimation of models for hierarchically clustered survival data remain largely uncharted. The model was estimated using the Newton-Raphsons numerical search approach. The model accounts for hierarchical clustering with three random effects or frailty effects. We assume that the random effects are independent and follow the Exponential and Weibull distribution. The results indicate that bio-demographic factors are more important in infancy while socioeconomic factors and household and environmental conditions have a greater effect in childhood. Furthermore, there is significant variation in child mortality risks even after controlling for measured determinants of mortality. Also, factors that fall under family and community level are more significant indicating that child survival is most controlled or determined by family and community factors and variables at the child level is not weighty. This suggests that there may exits unobserved or unobservable factors related to mortality.
Didaktikte Antropolojik Kuram ve Kullanımına Yönelik Örnekler

This documentation study aiming to present a theoretical frame for didactical researchesis composed of two main parts: the first part aims to clearly state what the science of didactic is, and make apparent differences with other close domains. For this purpose, definitions and concepts specific to didactic are presented. In the second part, the Anthropological Theory, which was introduced by Y. Chevallard in the 1980\'s, and is one of the most important theory in didactic, is discussed, as well as related studies. The analysis of the documents used revealed that the use of the Anthropological Theory offers a new viewpoint to researches aiming to explain the relation between learning and teaching situations.