Miracle-dz/UniFAR-FTUs huggingface dataset:
The determinants of subjective emotional intensity

Abstract What determines the subjective intensity of emotions? Four major groups of determinants are hypothesised: concerns (strength and relevance), appraisal, regulation, and individual differences. During six weeks subjects reported an emotion every week and answered questions on a computer. It appears that all four groups of supposed determinants are correlated with emotional intensity, the concern variables show the highest correlations. The importance of the determinants is not always the same, there are differences between the emotions and between the dimensions of emotional intensity. The relation between regulation and emotional intensity is complex: Causal relations are expected in both directions. On the one hand, a more intense emotion requires more regulation (positive causal effect), and on the other, regulation will decrease the intensity (negative causal effect). Indications of the existence of both relations are found. Regulation and intensity are positively correlated. The canonical corr.
A contribution to the theory of economic growth: Old and New

In this study it is possible to provide a simple theoretical and empirical literature framework that links the endogenous growth theory through to the classical economists’ theory. There is also the following phenomenon that emphasises the proceeding to Harrod-Domar growth model, through to the model of the neoclassical growth theory. The study utilising the production function and, through to the developed new models of “new growth theory”/ or endogenous growth theory that consider policy influences on growth and divergent outcomes among countries. Within this recent approach, theoretical and empirical studies have attempted to find the relationship between development of financial markets and the new approach of endogenous growth theory. Economists working in this area should target their work directly to the analysis of policy options in developing countries. Policymaking generally will benefit from empirical results generated from more carefully constructed structural economic models.
HOW NON-PROFIT INSPECTION SERVICES CAN CORRECT FOR CREDENCE GOOD TYPE MARKET FAILURES

The problems associated with asymmetric information and credence goods are a common worry to consumers who require the services of technicians with expert knowledge. A study was designed to see if the concerns of consumers were justified. Specifically, the study looks at two different samples of vehicle owners and the repair costs associated with a vehicle state safety inspection. In one sample the vehicles were inspected by a non-profit, state affiliated inspection station while in the second sample the vehicles were inspected by a for-profit vehicle inspection station. The results suggest that those vehicles inspected at a for-profit inspection station had higher repair costs than those vehicles inspected by a non-profit vehicle inspection station. JEL Classification: D82, L15, D8
An Advanced Survey on Hierarchical Routing Protocols in WSN

: Wireless Sensor Networks (WSNs) gives minimum expenses answers for different true issues.WSN is made of independent sensors builder at distance to control physical or environmental conditions, for example, sound, vibration, weight, temperature, movement or toxins and to agreeably exchange their information through the network to a main area. WSN are deployed in hostile environment so network becomes highly vulnerable and produces risk of attack. Therefore, numerous directing, power administration and information spread protocol have been particularly intended for WSNs.Planning power proficient directing mechanism to expand the whole network lifetime has turned out to be essential.In this paper performance of differentrouting protocols are compared, so this paper thinks about the diverse various hierarchical directing protocols.
Binding Mechanisms in Selective Laser Sintering and Selective Laser Melting

Purpose – This paper provides an overview of the different binding mechanisms in selective laser sintering (SLS) and selective laser melting (SLM), thus improving the understanding of these processes. Design/methodology/approach – A classification of SLS/SLM processes was developed, based on the binding mechanism occurring in the process, in contrast with traditional classifications based on the processed material or the application. A broad range of commercial and experimental SLS/SLM processes – found from recent articles as well as from own experiments – was used to explain the different binding mechanism categories. Findings – SLS/SLM processes can be classified into four main binding mechanism categories, namely “solid state sintering”, “chemically induced binding”, “liquid phase sintering – partial melting” and “full melting”. Most commercial processes can be classified into the latter two categories, which are therefore subdivided. The binding mechanism largely influences the process speed and the resulting part properties. Research limitations/implications – The classification presented is not claimed to be definitive. Moreover some SLM/SLM processes could be classified into more than one category, based on personal interpretation. Originality/value – This paper can be a useful aid in understanding existing SLS/SLM processes. It can also serve as an aid in developing new SLS/SLM processes.
Japanese Encephalitis Virus: Innate and Adaptive Immunity

Japanese encephalitis virus (JEV) is a flavivirus that is one of the major causes of encephalitis in Eastern and Southern Asia with recent observations marking its spread to newer geographical regions. Flaviviruses, in general consitutute a global health threat since many of them are endemic in large parts of the Americas, Africa and Australia in addition to Asia and suitable vaccines are unavailable for many of them. JEV causes serious inflammation of the brain, which may lead to permanent brain damage, and has a high mortality rate. More than three billion people live in JE endemic areas and JEV is estimated to cause 45,000 human cases of disease and 10000 deaths per year (Solomon and Winter, 2004; van den Hurk et al., 2009). The occurrence of encephalitic epidemics in humans due to this virus have been recognized from 1870s in Japan where it was termed Japanese B encephalitis to distinguish it from type A encephalitis caused by sleeping sickness. The first prototype Nakayama strain was isolated and established in 1935 from the brain of a fatal case from Tokyo, Japan. This was closely followed by virus isolation from Culex tritaeniorrhynchus in 1936 confirming earlier suspicions that mosquitoes served as the transmission vector (Solomon et al., 2000). JEV transmission occurs through a zoonotic cycle involving mosquitoes as an important intermediate maintenance and replicative vector. Vertebrates, chiefly pigs and ardeid birds act as amplifying hosts. Only those animals that develop high viraemias are significant in this natural enzootic cycle. Humans are infected only coincidently when bitten by an infected mosquito and are dead end hosts. Human to human transmission is yet to be documented, possibly due to the presence of transient viraemia. The absence of high serum viraemia prevents the virus from being picked up during mosquito bites. Pigs play a major role in the transmission cycle with respect to human infection since they are often bred close to humans whereas herons, egrets and other ardeid birds are important for maintenance and overwintering of this virus. Among the other vertebrates, horses also develop central nervous system (CNS) infections and are considered as dead end hosts. Rodents are relatively refractory to infections while amphibians, reptiles and bats can also be infected (Mackenzie et al., 2004). JEV does not cause encephalitis in pigs and birds although it is
Identification of monetary policy shocks and its effects: FAVAR methodology for the Brazilian economy

This paper applies the factor-augmented vector autoregressive methodology (FAVAR) to analyze the impacy of monetary policy shocks on the Brazilian economy, using 125 monthly series for the period between January of 1995 and September of 2009. Overall, the results obtained were consistent with economic theory and no price puzzle is observed. The paper also compared the FAVAR with the VAR methodologies, concluding that the results were very similar under both methodologies and that the gain of using the FAVAR methodology is very limited when Brazilian data is used to study the effects of monetary shocks.
A neural network expert system shell

Presents the architecture of a hybrid neural network expert system shell. The system, structured around the concept of a "network element", is aimed at preserving the semantic structure of the expert system rules whilst incorporating the learning capability of neural networks into the inferencing mechanism. Using this architecture, every rule of the knowledge base is represented by a one- or two-layer neural network element. These network elements are dynamically linked up to form a rule-tree during the inferencing process. The system is also able to adjust its inferencing strategy according to different users and situations. A rule editor is also provided to enable easy maintenance of the neural network rule elements. <<ETX>>
EEPROM Memory Controller Architecture for an Out of Order Execution

In modern day computer technology the time taken to access the information from the memory is larger compared to the time taken to execute the instructions. So we have to reduce the access time of the processor. An attempt has been made to reduce the time taken to execute the instructions by implementing several executing techniques so that the processor does not remain idle. In sequential execution the processor has to remain idle for a longer time in this process the processor is not used efficiently. Therefore to overcome this barrier out of order execution has been proposed by which the time taken to execute the instructions is reduced to a greater extent. In out of order execution the response time is reduced. The out of order also allows a prioritized handling of multiple operations. EEPROM is a nonvolatile memory which can be programmed and erased by using field electron emission the main characteristic of EEPROM is the way the memory programs and erases. Electrically erasable programmable read only memory controller architecture has been employed to enhance the performance of the system by executing the instructions in decoupled and out of order pattern so that the execution of instruction takes place at a faster rate and the efficiency of the processor is increased.
Short-term Effect of SpineMED Decompression System for Lumbar Disc Herniation

Objective: to explore the mechanism and effect of the non-surgical SpineMED decompression system for lumbar disc herniation . Method: We used the SpineMED decompression system manufactured by the Universal Pain Technology Canada. The operation consisted of a series of two force phases per cycle, which consisted of a 60 second “Maximum Tension” distraction phase (high force), and a 30 second “Minimum Tension” relaxation phase (low force) for an approximate period of 30 minutes. For the high force, the distractive tension was calculated as Body weight X 1/4 – 4.5 KG. For the low force, the distraction tension was set as High force tension X 1/2 + 3.5 KG. The pain was evaluated by Visual Analogue Scales (VAS) and MacNa method. Result: 118 patients were followed up for 1 year and 7 months. Compared with before the treatment, the VAS score decreased an average of 8.2 ±1.1, being significantly decreased (P<0.05)after the treatment. The rate of excellent and good was 93% and no complication was observed. Conclusion: For lumbar disc herniation, decompression has the advantages of safe, non-invasive, effective and complication free. It can be the first choice for patients with initial onset. Strictly controlled indication selection is the key to ensure the treatment effect.
Improved Extraction of Coupling Matrix and Unloaded Q from S-Parameters of Lossy Resonator Filters

Abstract—This paper presents a two-stage optimization method for accurately extracting the coupling matrix (CM) and the unloaded quality factor (unloaded Q) of each resonator from the measured (or simulated) S-parameters of lossy cross-coupled resonator bandpass filters. The method can be used in computer-aided tuning (CAT) of microwave filters to accelerate filter design and physical realization. In our method, the Cauchy method is employed for determining characteristic polynomials of the S-parameters in the normalized lowpass frequency domain, and the CM and unloaded Q are extracted by two-stage optimization method using genetic algorithm. With respect to the previous methods available in the literatures, the proposed method allows the CM extraction of the filter with sourceload coupling. Moreover, the accuracy and robustness of the method can be improved due to the usage of the second stage optimization. The proposed method is applied to the diagnosis of a general coupled resonator filter with/without source-load coupling.
1 0 O ct 2 01 8 On a Polytime Factorization Algorithm for Multilinear Polynomials over F 2 ⋆

In 2010, A. Shpilka and I. Volkovich established a prominent result on the equivalence of polynomial factorization and identity testing. It follows from their result that a multilinear polynomial over the finite field of order 2 can be factored in time cubic in the size of the polynomial given as a string. Later, we have rediscovered this result and provided a simple factorization algorithm based on computations over derivatives of multilinear polynomials. The algorithm has been applied to solve problems of compact representation of various combinatorial structures, including Boolean functions and relational data tables. In this paper, we describe an improvement of this factorization algorithm and report on preliminary experimental analysis.
Efficiency estimation method of three-wired AC to DC line transfer

The development of power semiconductor converters technology expands the scope of their application to medium voltage distribution networks (6-35 kV). Particularly rectifiers and inverters of appropriate power capacity complement the topology of such voltage level networks with the DC links and lines. The article presents a coefficient that allows taking into account the increase of transmission line capacity depending on the parameters of it. The application of the coefficient is presented by the example of transfer three-wired AC line to DC in various methods. Dependences of the change in the capacity from the load power factor of the line and the reactive component of the resistance of the transmission line are obtained. Conclusions are drawn about the most efficient ways of converting a three-wired AC line to direct current.
Frequency of Urinary Tract Bacterial Infection and their Susceptibility Patterns among Hemodialysis Patients in Zliten Hospital

Urinary tract infection (UTI) caused by microorganisms such as bacteria, virus, fungus, and parasites that affects upper or lower urinary tract. Renal failure or renal insufficiency is a medical condition in which the kidney fails to adequately filter waste product from the blood. In a study of 103 patients, the target group was dialysis patients who attended regularly to kidney dialysis unit, at Zliten Teaching Hospital in Libya. During the period of study from March to June 2015 were representing the study population. The results showed that the highest rate of UTI among the hemodialysis was observed among the age group 56-65 (52.4%). Result showed also UTI was highest in dialysis patients how have diabetes (53.8%). The susceptibility pattern of isolated showed that the Gram negative isolates were most sensitive to meropenem (100%), followed by amikacin (91.7%) and imipenem (91.7%). However, in the Gram positive isolates showed high sensitivity to (100%) to nitrofurantoin, deptomycin, and linezolid followed by teicoplanin (90.5%). The result also showed resistance marker among isolated bacteria were BALCT (42.4 %), MRS (36.4 %), STAIML (11.6%), ALTER (6.1%), HLGR (3.0%), ESBL (3.0%).
DBFT: Efficient Byzantine Consensus with a Weak Coordinator and its Application to Consortium Blockchains

This paper introduces a deterministic Byzantine consensus algorithm that relies on a new weak coordinator. As opposed to previous algorithms that cannot terminate in the presence of a faulty or slow coordinator, our algorithm can terminate even when its coordinator is faulty, hence the name weak coordinator. The key idea is to allow processes to complete asynchronous rounds as soon as they receive a threshold of messages, instead of having to wait for a message from a coordinator that may be slow. The resulting algorithm assumes partial synchrony, is resilience optimal, time optimal and does not need signatures. Our presentation is didactic: we first present a simple safe binary Byzantine consensus algorithm, modify it to ensure termination, and finally present an optimized reduction from multivalue consensus to binary consensus that may terminate in 4 message delays. To evaluate our algorithm, we deployed it on 100 machines distributed in 5 datacenters across different continents and compared its performance against the randomized solution from Mostefaoui, Moumem and Raynal [PODC14] that terminates in O(1) rounds in expectation. Our algorithm always outperforms the latter even in the presence of Byzantine behaviors. Our algorithm has a subsecond average latency in most of our geo-distributed experiments, even when attacked by a well-engineered coalition of Byzantine processes.
Controlling the Unknown

A lot of work has been done in the area of building componentbased systems with correct-by-construction adaptors. This is accomplished by using preexisting specifications of the component behaviour. But what happens when known components get to interact with incompletely specified, black-box components? How can we avoid errors in this kind of system, without modifying existing/legacy components? We present a method to explore and control such systems. Our approach exploits information in both correct and erroneous runs to build a controller that ensures our system will avoid observed errors when interacting with the unspecified component. We consider the behavioural specifications for our known, legacy component to be previously documented and we infer partial behaviour information of the unknown component by studying its reactions to various interaction scenarios.
Portfolios of Hedge Funds: What Investors Really Invest in

Using monthly return data over the period June 1994 - May 2001 we investigate the performance of randomly selected baskets of hedge funds ranging in size from 1 to 20 funds. The analysis shows that increasing the number of funds can be expected to lead not only to a lower standard deviation but also, and less attractive, to lower skewness and increased correlation with the stock market. Most of the change occurs for relatively small portfolios. Holding more than 15 funds changes little. The population average appears to be a good approximation for the average basket of 15 or more funds. With 15 funds, however, there is still a substantial degree of variation in performance between baskets, which dissolves only slowly when the number of funds is increased. Survivorship bias is largely independent of portfolio size and thus cannot be diversified away. Finally, our efficiency test indicates that one only needs to combine a small number of funds to obtain a substantially more efficient risk-return profile than that offered by the average individual hedge fund.
Comparative Study of Soft Computing Techniques on Medical Datasets

: Data classification is process of dividing dataset into two or more different classes where each class contains similar type of data items. In this paper we compare the different classification technique using the WEKA tool that will be helpful for decision making in medical diagnosis. WEKA is open source tool providing classification using soft computing technique for data mining process. Our goal is to analysis of the performance of different classifiers on different medical datasets. The analysis is done for five different medical datasets with four different classifiers in terms of the execution time, correctly classified, incorrectly classified and the mean absolute error. From the obtained results of classifiers we conclude that KNN is the effective classifier for medical dataset than other classifiers we used for the analysis.
Negative thermal expansion ofReO3: Neutron diffraction experiments and dynamical lattice calculations

Tapan Chatterji,1 Paul F. Henry,2 R. Mittal,3,4 and S. L. Chaplot4 1Jülich Centre for Neutron Science, Forschungszentrum Jülich Outstation at Institut Laue-Langevin, BP 156, 38042 Grenoble Cedex 9, France 2Institut Laue-Langevin, BP 156, 38042 Grenoble Cedex 9, France 3Forschungszentrum Jülich, Jülich Centre for Neutron Science, c/o TU München, Lichtenbergstrasse 1, D-85747 Garching, Germany 4Solid State Physics Division, Bhabha Atomic Research Centre, Trombay, Mumbai 400085, India Received 30 May 2008; revised manuscript received 4 September 2008; published 8 October 2008
Scanning integer points with lex-cuts: A finite cutting plane algorithm for integer programming with linear objective

We consider the integer points in a unimodular cone K ordered by a lexicographic rule defined by a lattice basis. To each integer point x in K we associate a family of inequalities (lex-cuts) that defines the convex hull of the integer points in K that are not lexicographically smaller than x. The family of lex-cuts contains the Chvatal-Gomory cuts, but does not contain and is not contained in the family of split cuts. This provides a finite cutting plane method to solve the integer program min{cx : x \in S \cap Z^n }, where S \subset R^n is a compact set and c \in Z^n . We analyze the number of iterations of our algorithm.
Atherogenic Ratios in Patients with Recurrent Acute Coronary Syndrome and Receiving Statin Therapy: Clinical Usefullness as Cardiovascular Predictors

Patients who have already suffered a vascular event require more and better control of cardiovascular risk factors. Different atherogenic indexes such as TC/HDLc, LDLc/HDLc, apoB/apoA-I, LDLc/apoB and non-HDLc/HDLc have been used to follow-up the patients because of their predictive capacity of the lipid profile. The aim of this study was to evaluate atherogenic ratios as a marker of the lipid residual risk in high-risk patients receiving statin therapy and to know the changes produced by previous lipid-lowering drugs treatment for a previous coronary event. The study including patients admitted to coronary care units of six Spanish tertiary hospitals for Acute Coronary Syndrome (ACS). A total of 633 ACS patients were included; of these, 478 (75.8%) had presented a myocardial infarction and 153 (24.2%) angina. A previous ACS had occurred in 43.1% of cases, and was the first episode in 56.9% of the studied patients. Among patients with known ischemic heart disease, 187 (52.2%) were receiving lipid-lowering drugs, mainly statins (182 patients, 50.7%). Of those with a first ACS, 59 (21.7%) were on lipid-lowering drugs: 55 (20.1%) statins and 4 (1.7%) fibrates. Patients with recurrent ACS had similar triglyceride and HDLc levels, but significantly lower total cholesterol and LDLc concentrations compared with those presenting the first ACS. Patients with recurrent ACS had significantly lower non-HDLc levels, TC/HDLc and LDLc/HDLc, but higher HDLc/TC and HDLc/LDLc ratios compared with first ACS patients. In patients taking statins the lipid residual vascular risk was related with the persistence of cardiovascular risk factors, and related with lipid profile with dyslipemia no-LDL dependent. So, we can conclude that the correction of lipid profile by statin is not per se sufficient to control cardiovascular risk.