Miracle-dz/UniFAR-FTUs huggingface dataset:
Imagined versus Remembered Stories: Quantifying Differences in Narrative Flow

Lifelong experiences and learned knowledge lead to shared expectations about how common situations tend to unfold. Such knowledge of narrative event flow enables people to weave together a story. However, comparable computational tools to evaluate the flow of events in narratives are limited. We quantify the differences between autobiographical and imagined stories by introducing sequentiality , a measure of narrative flow of events, drawing probabilistic inferences from a cutting-edge large language model (GPT-3). Sequentiality captures the flow of a narrative by comparing the probability of a sentence with and without its preceding story context. We applied our measure to study thousands of diary-like stories, collected from crowdworkers about either a recent remembered experience or an imagined story on the same topic. The results show that imagined stories have higher sequentiality than autobiographical stories and that the sequentiality of autobiographical stories increases when the memories are retold several months later. In pur-suit of deeper understandings of how sequentiality measures the flow of narratives, we explore proportions of major and minor events in story sentences, as annotated by crowdworkers. We find that lower sequentiality is associated with higher proportions of major events. The methods and results highlight opportunities to use cutting-edge computational analyses, such as sequentiality, on large corpora of matched imagined and autobiographical stories to investigate the influences of memory and reasoning on language generation processes.
A theory of representation learning gives a deep generalisation of kernel methods

The successes of modern deep machine learning methods are founded on their ability to transform inputs across multiple layers to build good high-level representations. It is therefore critical to understand this process of representation learning. However, standard theoretical approaches (formally NNGPs) involving infinite width limits eliminate representation learning. We therefore develop a new infinite width limit, the Bayesian representation learning limit, that exhibits representation learning mirroring that in finite-width models, yet at the same time, retains some of the simplicity of standard infinite-width limits. In particular, we show that Deep Gaussian processes (DGPs) in the Bayesian representation learning limit have exactly multivariate Gaussian posteriors, and the posterior covariances can be obtained by optimizing an interpretable objective combining a log-likelihood to improve performance with a series of KL-divergences which keep the posteriors close to the prior. We confirm these results experimentally in wide but finite DGPs. Next, we introduce the possibility of using this limit and objective as a flexible, deep generalisation of kernel methods, that we call deep kernel machines (DKMs). Like most naive kernel methods, DKMs scale cubically in the number of datapoints. We therefore use methods from the Gaussian process inducing point literature to develop a sparse DKM that scales linearly in the number of datapoints. Finally, we extend these approaches to NNs (which have non-Gaussian posteriors) in the Appendices.
The characteristics of the Galactic center excess measured with 11 years of Fermi-LAT data

The excess of γ rays in the data measured by the Fermi Large Area Telescope from the Galactic center region is one of the most intriguing mysteries in Astroparticle Physics. This “Galactic center excess” (GCE), has been measured with respect to diﬀerent interstellar emission models (IEMs), source catalogs, data selections and techniques. Although several proposed interpretations have appeared in the literature, there are not ﬁrm conclusions as to its origin. The main diﬃculty in solving this puzzle lies in modeling a region of such complexity and thus precisely measuring the characteristics of the GCE. In this paper, we use 11 years of Fermi -LAT data, state of the art IEMs, and the newest 4FGL source catalog to provide precise measurements of the energy spectrum, spatial morphology, position, and sphericity of the GCE. We ﬁnd that the GCE has a spectrum which is peaked at a few GeV and is well ﬁt with a log-parabola. The normalization of the spectrum changes by roughly 60% when using diﬀerent IEMs, data selections and analysis techniques. The spatial distribution of the GCE is compatible with a dark matter (DM) template produced with a generalized Navarro-Frenk-White density proﬁle with slope γ = 1 . 2 − 1 . 3. No energy evolution is measured for the GCE morphology between 0 . 6 − 30 GeV at a level larger than 10% of the γ average value, which is 1.25. The analysis of the GCE modeled with a DM template divided into quadrants shows that the spectrum and spatial morphology of the GCE is similar in diﬀerent regions around the Galactic center. Finally, the GCE centroid is compatible with the Galactic center, with best-ﬁt position between l = [ − 0 . 3 ◦ , 0 . 0 ◦ ] , b = [ − 0 . 1 ◦ , 0 . 0 ◦ ], and it is compatible with a spherical symmetric morphology. In particular, ﬁtting the DM spatial proﬁle with an ellipsoid gives a major-to-minor axis ratio (aligned along the Galactic plane) between 0.8-1.2.
An Adaptive Mini-Block Fisher Method for Deep Neural Networks

Deep neural networks (DNNs) are currently predominantly trained using ﬁrst-order methods. Some of these methods (e.g., Adam, AdaGrad, and RMSprop, and their variants) incorporate a small amount of curvature information by using a diagonal matrix to precondition the stochastic gradient. Recently, effective second-order methods, such as KFAC, K-BFGS, Shampoo, and TNT, have been developed for training DNNs, by preconditioning the stochastic gradient by layer-wise block-diagonal matrices. Here we propose an adaptive "mini-block Fisher (MBF)" "preconditioned gradient method, that lies in between these two classes of methods. Speciﬁcally, our method uses a block-diagonal approximation to the empirical Fisher matrix, where for each layer in the DNN, whether it is convolutional or feed-forward and fully connected, the associated diagonal block is itself block-diagonal and is composed of a large number of mini-blocks of modest size. Our novel approach utilizes the parallelism of GPUs to efﬁciently perform computations on the large number of matrices in each layer. Consequently, MBF’s per-iteration computational cost is only slightly higher than it is for ﬁrst-order methods. The performance of our proposed method is compared to that of several baseline methods, on both autoencoder and CNN problems, to validate its effectiveness both in terms of time efﬁciency and generalization power. Finally, prove that an idealized version of MBF converges linearly.
Psychological Well-being among Doctors and Nurses: A Comparative Study

The present study examines the level of psychological well being among doctors and nurses. A total of 600 (doctors-300, nurses-300) samples were selected randomly from Bangalore City. Information was collected from using an instrument developed by Carol, D, Ryff’s Medium Form of Psychological Well Being Scale (PWBS). Results of the study revealed that doctors and nurses working in Bangalore City did not show significance differences in overall psychological wellbeing. However they showed significance differences in the domains of autonomy and environmental mastery. Whereas nurses score higher on autonomy and environmental mastery compare to doctors. Gender wise comparisons on over all psychological wellbeing did not show significance differences. However male and female differ only in the domain of personal growth, male respondents scored higher on Personal growth has compare to female respondent.
Institutional Knowledge at Singapore Management University Institutional Knowledge at Singapore Management University Summarizing Review Scores of "Unequal" Reviewers Summarizing Review Scores of "Unequal" Reviewers

A frequently encountered problem in decision making is the following review problem : review a large number of objects and select a small number of the best ones. An example is selecting conference papers from a large number of submissions. This problem involves two sub-problems: assigning reviewers to each object, and summarizing reviewers’ scores into an overall score that supposedly reﬂects the quality of an object. In this paper, we address the score summarization sub-problem for the scenario where a small number of reviewers evaluate each object. Simply averaging the scores may not work as even a single reviewer could inﬂuence the average signiﬁcantly. We recognize that reviewers are not necessarily on an equal ground and propose the notion of “leniency” to model this diﬀerence of reviewers. Two insights underpin our approach: (1) the “leniency” of a reviewer de-pends on how s/he evaluates objects as well as on how other reviewers evaluate the same set of objects, (2) the “leniency” of a reviewer and the “quality” of objects evaluated exhibit a mutual dependency relationship. These insights motivate us to develop a model that solves both “leniency” and “quality” simultaneously. We study the eﬀectiveness of this model on a real-life dataset.
Identity Integration and Creativity

Identity integration among bicultural individuals refers to the perception that their two cultural identities are compatible. Previous research has shown that identity integration is likely to lead to enhanced creativity. However, this research was conducted among first and second generation immigrants, but not among mixed-race individuals. The current research examined identity integration and creativity among mixed-race individuals. We also explored the role of integrated identity experiences at home. We found that identity integration was related to increases in creativity; and this was partly mediated via integrated identity experiences at home. Our findings suggest that positive bicultural experiences at home may create a context for the individual to integrate their biracial identities; and this is ultimately beneficial for creativity.
Improvement in Machining Efficiency of Complex Profiles using 5-Axes Simultaneous Machining Approach

This research paper focuses on the process of machining complex and varying contour aerofoil parts used in aerospace industry like wings, blades of turbine and diffusers, etc. The main theme is to enhance productivity and on the other hand achieving accurate machining results for complex profile parts. The research consists of three main parts viz. Accurate and optimized tool path generation of complex profile, understanding and conversion of a 5-axes machine kinematics into mathematical relationships and developing a post processor which converts cutter location file into machine readable file, and finally a time and accuracy study has been made and compared with techniques used previously for machining of such components. Tool path is generated on CAM software from where CL (Cutter Location) file is generated, then by use of mathematical calculations post processor is developed and used for the conversion of that CL file into machine readable file. Time and accuracy analysis has been made in the end on an impeller blade machining. Tool paths generated in CAM software requires to be very closely analyzed in order to ensure collision free tool paths as movement in all 5-axes increases the chances of collision of head to work piece or with the table. For the study of 5-axes machine kinematics and calculations, a general 5-axes machine having 3 linear axes and two axes in rotary/tilting table has been used. By applying mathematical relationships using rotational matrix theorem and dot product of two vector quantities, equations were derived for rotary and tilting axes and then written in programming language (Visual C ++ ) for line to line conversion of CL file into machine readable file. finish the surface of the blades and the leading/trailing edge finish hub surface the impeller. cutting like feed, speed, axial of cut, radial depth dependent on the spindle power of the machine and the type of the material of part to be machined and that of the cutter itself. The selection of the size of the cutting tool used for the machining of each process is also dependant on the minimum area between two adjacent surfaces of the blades of impeller and maximum curvature of the blade from shroud surface to hub surface in order to avoid collision of the cutting tool with the blade surfaces. In the end, how the new approach has benefited is analyzed. The need for research on new approach was very demanding as to manufacture complex profile parts mostly used in aerospace industry with traditional machining approaches causes unpredictable delays due to manual calculations, inaccurate machining results like poor surface finish, tool breakage, etc, as well as requirement of various jigs/fixtures and skilled workers for accomplishing the task all the time. Now by adopting the approach as explored in this research gives a lot of advantages over traditional manufacturing approach. Some important features compared are presented in the tabular form.
Social and Institutional Factors Capable of Improving Environmental Qualities: A Case Study of 5 ASEAN Economies

This study aims to analyze the impact of social (human, educational, and financial development) and institutional factors (corruption and administrative effectiveness) on environmental quality. Data were obtained from 5 ASEAN economies from 2000-2018, with the Brush Pagon LM and Pearson CD used to test the cross-section dependency of variables. The results showed that OLS depicted positive effects of human, educational, and financial development, with administrative effectiveness on environmental quality, with nega- tive effects due to corruption. In conclusion, the government needs to promote social and institutional factor in order to improve environmental performance.
On the Calibration, Veriﬁcation and Validation of an Agent-Based Model of the HPC Input/Output System

—High Performance Computing (HPC) applications can spend a signiﬁcant portion of their execution time making Input/Output (I/O) operations into ﬁles. Improving I/O performance becomes more important for the HPC community as parallel applications produce more data and use more compute resources. One of the methods used to evaluate and understand the I/O performance behavior of such applications in new I/O system or different conﬁgurations is using modeling and simulation techniques. In this paper, we present a simulation model of the HPC I/O system by using Agent-Based Modelling and Simulation (ABMS) based on the functionality of the I/O Software Stack. Our proposal is modeled using the concept of white box so that the speciﬁc behavior of each of the modules or layers in the system can be observed. The I/O software stack layers are analyzed using code instrumentation for the features corresponding to I/O operations and calibration of the initial model. The veriﬁcation and validation of an initial implementation has shown a similar behavior between the measured and simulated values for the Interleaved or Random (IOR) benchmark by using different ﬁle sizes.
THE ENIGMATIC SPIN EVOLUTION OF PSR J0537-6910: R-MODES, GRAVITATIONAL WAVES AND THE CASE FOR CONTINUED TIMING

We discuss the unique spin evolution of the young X-ray pulsar PSR J0537-6910, a system in which the regular spin down is interrupted by glitches every few months. Drawing on the complete timing data from the Rossi X-ray Timing Explorer (RXTE, from 1999-2011), we argue that a trend in the inter-glitch behaviour points to an effective braking index close to n = 7, much larger than expected. This value is interesting because it would accord with the neutron star spinning down due to gravitational waves from an unstable r-mode. We discuss to what extent this, admittedly speculative, scenario may be consistent and if the associated gravitational-wave signal would be within reach of ground based detectors. Our estimates suggest that one may, indeed, be able to use future observations to test the idea. Further precision timing would help enhance the achievable sensitivity and we advocate a joint observing campaign between the Neutron Star Interior Composition ExploreR (NICER) and the LIGO-Virgo network.
Image Reconstruction of Internal Defects in Wood Based on Segmented Propagation Rays of Stress Waves

In order to detect the size and shape of defects inside wood, an image reconstruction method based on segmented propagation rays of stress waves is proposed. The method uses sensors to obtain the stress wave velocity data by hanging around the timber equally, visualizes those data, and reconstructs the image of internal defects with the visualized propagation rays. The basis of the algorithm is precisely segmenting the rays to benefit the spatial interpolation. First, a ray segmentation algorithm using the elliptical neighborhood technique is proposed, which can be used to segment the rays and estimate the velocity values of segmented rays by the nearby original rays using elliptical zones. Second, a spatial interpolation algorithm utilizing a segmented ellipse according to the segmented rays is also proposed, which can be used to estimate the velocity value of a grid cell by the segmented ellipses corresponding to the nearby segmented rays. Then, the image of the internal defect inside the wood is reconstructed. Both simulation and experimental data were used to evaluate the proposed method, and the area and shape of the imaging results were analyzed. The comparison results show that the proposed method can produce high quality reconstructions with clear edges and high accuracy.
Scholars' Mine Scholars' Mine Coring of Soft Soil-like Rock Material Coring of Soft Soil-like Rock Material

A new coring technique is described for the sampling of highly altered rock. This and an innovative field survey method were developed to supply valid and representative data for numerical modelling of openings in this soil-like material. The results were not onlv reflective of in situ behaviour, but successful enough to be adopted for the sampling and modelling of other highly altered surface crown pillar masses, mining structures in need of better design methods.
International Journal of Science and Business

Oilseeds contribute a significant amount to Sub-Saharan African countries' agricultural products, produced for oil and protein, next to cereals and pulses. The region has a comparative advantage of producing and exporting different types of oilseeds, to serve the increasing demand worldwide. However, these countries experience very low performance in the international market. As a result, it becomes an important area of concern and intervention for the policymakers in these respective countries. There have been various researches done to explore the basic causes of export inefficiencies. Some of the study findings have been complementing, while others are contrasting and many of the researches do not acknowledge the internal and external factors that determine the region's agricultural commodities export competitiveness. Considering relevant panel data in the years 1995 to 2017 and applying the fixed-effect model, the study examines the moderating effect of the institutional environment on the link between factor and demand conditions and the export competitiveness of oilseeds. The result prevails as productivity and export quantity have a significant effect on export competitiveness and the institutional environment significantly moderates their relationship. The study contributes to both theory (competitive advantage, institutional-based view theory) and practice (oilseed industry leaders and policymakers). IJSB Accepted 9 February 2021 Published 26 Febreary 2021 DOI: 10.5281/zenodo.4565105
THE PREVALENCE AND RELATIONSHIP OF ANEMIA IN ELDERLY HOSPITALIZED PATIENTS WITH COMORBIDITIES Of Anemia In Elderly Hospitalized Patients

: Objective: The aim of our stud was to find out the prevalence and relationship of anemia in elderly hospitalized patients with comorbidities. Study Design: A descriptive study. Place and Duration: This study was conducted at medical department, Allied hospital Faisalabad for the duration of one year starting from November, 2019 to October, 2020. Methodology: In our present study we selected 100 patients with the use of non-probability convenient sampling technique. According to World Health Organization (WHO) criteria we defined anemia as Hemoglobin in Females were <12 g/dL and in Males were <13 g/dL. According to grades of anemia: in severe grade of patient’s hemoglobin were <8g/dl, in mild grade of patient’s hemoglobin were between 11g/dl and lower limit of normal and in moderate grade of patient’s hemoglobin were between 8 g/dl and 10.9 g/dl. SPSS version 20 was used for the analysis of data. Results: In our present study we selected 100 patients in which 63% were found to be anemic. 57% patients were found in mild form of anemia, 30% patients were found in moderate form of anemia and 12% patients were found in severe form of anemia. 49% of anemic patients had 3 or more comorbidities. According to gender distribution, 53 patients were male and 47 patients were female. In our study the most common diseases are heart disease, diabetes chronic kidney disease and hypertension. Conclusion: At the end of our study, we conclude that frequency of anemia is more in hospitalized patients and its directly associate with number of comorbidities. Physicians should have a high index of skepticism and low threshold for treatment of anemia in elderly patients as this can significantly impact the disease outcome. In our present study we selected 100 patients in which 63% were found to be anemic. 57% patients were found in mild form of anemia, 30% patients were found in moderate form of anemia and 12% patients were found in severe form of anemia.
DMSO_A_304634 2029..2039

Department of Gastroenterolgy & Hepatology, China-Japan Union Hospital, Jilin University, Changchun, 130033, People’s Republic of China Objective: Non-alcoholic fatty liver disease (NAFLD), previously thought to predominantly affect obese individuals, has also been shown to occur in subjects who have a relatively normal body mass index (BMI). Due to the normal BMI, non-obese NAFLD are easily to be ignored and eventually lead to potential liver injuries. Methods: A population-based cross-sectional study was conducted on 1608 cases with normal serum alanine aminotransferase (ALT) levels who were divided into an obese group (BMI ≥25 kg/m) and a non-obese group (BMI <25 kg/m). NAFLD was diagnosed by ultrasound and Fibro Scan examination. Non-obese populations were divided into NAFLD group (CAP ≥240 db/m) and non-NAFLD group (CAP <240 db/m). The incidence of NAFLD in the obese and non-obese populations and constituent ratios of genders, age, and serum levels of triglycerides (TG), cholesterol (CHOL), and blood glucose were compared. Risk factors of NAFLD in non-obese people were analyzed by multivariate logistics regression. Results: The occurrence of NAFLD was higher in the obese group than in the non-obese group, regardless of gender (P <0.001). In the non-obese group, the occurrence of NAFLD in female patients was lower than that in male (P=0.001). The occurrence of NAFLD increased with age, with 50–59 years being the peak age of incidence in both male and female. The peak age of NAFLD occurrence in non-obese male patients was more delayed than that in obese male patients. BMI (OR=1.311, P=0.000) and TG (OR=2.545, P=0.000) were risk factors for NAFLD in the non-obese population. Conclusion: Compared with obese population, the incidence of NAFLD in non-obese population was relatively low and more frequently in male than in female, the peak age of NAFLD occurrence in non-obese male patients was also delayed. BMI and TG should still be controlled to avoid the occurrence of NAFLD although the BMI of such patients is normal.