Miracle-dz/UniFAR-FTUs huggingface dataset:
Simulation of Large Deformations in Elastic Solids via an Eulerian Approach

A considerable challenge in simulating large deformations in solids lies in keeping track of the material motion. Lagrangian and Eulerian frameworks are among the main approaches for dealing with such problems. The former explicitly keeps track of the solid during the simulation, whereas the latter uses a fixed spatial grid. The goal of this project is to implement a large deformation elasticity solver based on an Eulerian framework. The solver can simulate the deformation of a 1-D medium and its collision with different fixed barriers. In 2-D, the solver can find the steady state deformation of a solid subject to fixed boundary conditions. Code has also been written for simulating the translation and deformation of a solid with a free a surface. However, the implementation still suffers from bugs and is not fully functional. The simplest working underlying numerical methods are used, i.e., a first-order finite-difference spatial discretization, a first-order explicit Euler temporal discretization, and handling of collisions via non-penetrating linear constraints on velocity.
Sparse-View X-Ray CT Reconstruction Using (cid:96) 1 Regularization with Learned Sparsifying Transform

—A major challenge in X-ray computed tomography (CT) is to reduce radiation dose while maintaining high quality of reconstructed images. To reduce the radiation dose, one can reduce the number of projection views (sparse-view CT); however, it becomes difﬁcult to achieve high quality image reconstruction as the number of projection views decreases. Researchers have shed light on applying the concept of learning sparse representations from (high-quality) CT image dataset to the sparse-view CT reconstruction. We propose a new statistical CT reconstruction model that combines penalized weighted-least squares (PWLS) and (cid:96) 1 regularization with learned sparsifying transform (PWLS-ST-(cid:96) 1 ), and an algorithm for PWLS-ST-(cid:96) 1 . Numerical experiments for sparse-view CT show that our model signiﬁcantly improves the sharpness of edges of reconstructed images compared to the CT reconstruction methods using edge-preserving hyperbola regularizer and (cid:96) 2 regularization with learned ST.
A note on lag selection in time series using multi-step estimation

In applied time series analysis there is a great need to decide upon the number of lags. This is due to the fact that the theories at hand most often do not supply information regarding the number of lags, so we need procedures to let the data decide for us. Commonly used method includes information criteria, such as AIC and BIC, the bottom up and top down methods (start with a minimum/maximum number of lags and then test up/down) and testing for autocorrelation in the residuals. In this note we propose a new approach which is based on comparing the parameter estimates gained from minimizing one step ahead forecast error with the ones from minimizing the h− step ahead forecast errors. This evolves to a non-nested type of test. The proposed test statistic has an asymptotic χ-distribution. A small Monte Carlo Simulation is performed which shows that the size is close to the nominal and that it has good power. Compared to AIC, BIC, top-down and the Breusch-Godfrey test for autocorrelation in the residuals our test is the only one with both good size and power properties.
Numerical Chromosome Variation and Mitotic Segregation Defects in Cells Generated in the Adult Brain of Teleost Fish

In contrast to most other vertebrates, teleost fish exhibit an unparalleled capacity to generate new cells in both the intact and the injured adult brain. This dissertation is focused on the occurrence, the extent and the fate of aneuploid cells (genome-modified individual cells characterized by the loss or gain of whole chromosomes) generated in the teleostean brain. Aneuploidy is observed in 80% of the newly-generated cells of the adult brain, but occurs at a very low rate in liver tissue, as shown by metaphase chromosome spreads and flow-cytometric DNA content analysis. To further analyze this phenomenon, the mitotic machinery of adult brain cells was examined for chromosome segregation defects which showed lagging chromosomes at metaphase and anaphase, as well as micronuclei and anaphase bridges, in the intact adult brain. To identify the fate of aneuploid cells in the adult brain, the Sphase cell cycle marker 5-bromo-2-deoxyuridine (BrdU) was injected into the fish, which were kept for various postadministration survival times. In the 100- and 860-day BrdU survival periods, the rate of mitotic segregation defects was significantly reduced, compared to the 2h and the 30-day survival times. These findings suggest that a good portion of the cells with mitotic defects were eliminated, possibly by apoptotic cell death. The analysis of post BrdU administration survival times in Apteronotus leptorhynchus up to 860 days, and up to 203 days in Danio rerio, revealed that a significant proportion of cells which exhibit nuclear abnormalities after mitosis survived for the rest of the life of the fish. In conclusion, this thesis demonstrates the evidence of the generation and maintenance of aneuploid cells in the adult fish brain that arise through chromosome missegregation which is a widespread phenomenon in the teleostean central nervous system.
Phylogeny and a revised classification of the Chinese species of Nyssa (Nyssaceae) based on morphological and molecular data

The taxonomy of Nyssa (Nyssaceae) in China is confused and uncertain due to differing views about how many species should be recognized, and a scarcity of good morphological differential characters. In the present study, we examined 52 morphological characters from up to fifty accessions each of six of the seven species recognized in the Flora of China: N. yunnanensis, N. javanica, N. sinensis, N. shangszeensis, N. shweliensis and N. wenshanensis. Based on both principal coordinate analysis and UPGMA cluster analysis, N. yunnanensis and N. javanica were both morphologically distinct. However, accessions of N. sinensis, N. shangszeensis, N. shweliensis and N. wenshanensis were intermixed in both analyses and could not be discriminated from each other. Sequence data from nuclear ITS and the chloroplast regions trnH-psbA, rps16r-f, trnL-rps32F, trnS-G and trnL-F were used to further analyze the Nyssa species listed above, together with N. aquatica and N. sylvatica from North America. All analyses of the DNA data using maximum parsimony, maximum likelihood and Bayesian methods strongly supported the monophyly of Nyssa. Within Nyssa, N. yunnanensis and N. javanica were resolved as sister species, which were genetically distinct. The other four Chinese taxa were barely differentiated by molecular data, with only N. shangszeensis and N. wenshanensis weakly supported as monophyletic. Hence, based on morphological and molecular data, we recommend that N. shangszeensis, N. shweliensis and N. wenshanensis be reduced to synonyms of N. sinensis, and only N. sinensis, N. yunnanensis and N. javanica be recognized for Flora of China. The American N. aquatica and N. sylvatica were sister species in the cpDNA but not in the ITS analyses, indicating possible reticulate evolution.
HexArcade: Predicting Hexad User Types By Using Gameful Applications

Personalization is essential for gameful systems. Past research showed that the Hexad user types model is particularly suitable for personalizing user experiences. The validated Hexad user types questionnaire is an effective tool for scientific purposes. However, it is less suitable in practice for personalizing gameful applications, because filling out a questionnaire potentially affects a person's gameful experience and immersion within an interactive system negatively. Furthermore, studies investigating correlations between Hexad user types and preferences for gamification elements were survey-based (i.e.,not based on user behaviour). In this paper, we improve upon both these aspects. In a user study (N=147), we show that gameful applications can be used to predict Hexad user types and that the interaction behaviour with gamification elements corresponds to a users' Hexad type. Ultimately, participants perceived our gameful applications as more enjoyable and immersive than filling out the Hexad questionnaire.
Mycelial Fermentation in Submerged Culture of Schizophyllum commune and its Properties

The production of mycelia and polysaccharides from Schizophyllum commune was carried out in a potato dextrose broth containing 2% malt extract. The results showed that at 6 days of cultivation the highest dried mycelia was 8.65 g/L and the highest polysaccharides content was 1.98 g/L at 12 days of cultivation. The total phenolic content determined by Folin-Ciocalteu method was 8.54 mg GAEs/g extract. The reducing power of ethanolic extract of mycelia increased when the concentration of extract was increased. At 2.5 mg/ml of ethanolic extract, the reducing power was 0.684 and the radical scavenging activity of mycelia ethanolic extract on 0.2 mM of 1, 1-Diphynyl-2-picrylhydrazyl (DPPH) was 70.89%. Mycelia froma submerged culture showed inhibition activity on the growth of Bacillus cerues and Staphylococcus aureus. Fermentation of grape juice by S. commune mycelia produced approximately 6.09% (v/v) alcohol within 24 days. These results suggested that mycelia of S. commune have a high potential to be used as natural antioxidant agent, food supplement and alcoholic beverage producing microorganism instead of ethanol-producing yeast.
Caenorhabditis elegans as a biological model

Caenorhabditis elegans is a free-living harmless transparent nematode. it has been extensively used as a biological model. It was the first multicellular organism to have genome completely sequenced and 40% of its genes have human matches. This soil nematode offered great potential for genetic analysis, partly because of its rapid (3-day) life cycle, small size (1.5-mm-long adult), and ease of laboratory cultivation. It is an important model system for biological research in many fields including genomics, cell biology, neuroscience and aging. Compared to the use of other model organisms, such as mice, the short life cycle of C. elegans reduces the experimental cycle and facilitates biological study. The mature “female,” has precisely 959 somatic cells and the mature male, includes precisely 1031 somatic cells. As an invertebrate experimental system, it is now second only to Drosophila melanogaster in terms of convenience and popularity. Its transparency and the generation of multiple progeny have made the worm an attractive model for studies, including those on developmental and reproductive behavior. The properties of C. elegans and the research done using C. elegans provide a wealth of information and an attractive pool of resources for researchers.
Assessment of human and multiple UAVs interaction in police clearing operations

Unmanned aerial vehicle (UAV) or drone technology is developed maturely these years, and drone assists humans in various fields. Especially, it is a great solution for law-enforcement operations. Officers usually work individually or with a small group during the clearing operation, which may encounter uncertain events or surprising ambush from the hostile target and respond to the potential threat swiftly and appropriately. An assistant drone can support law-enforcement officer has the potential to increase the safety and reduce the number of casualties by detecting and spotting hostile target in advance during the operation. Drone swarms (multiple UAVs) are more efficient than a single drone in the searching process, and swift clearing operation means less possible injuries. Hence, this study is aiming to find an effective and intuitive single operator interface for multiple swarm law-enforcement operations based on the previous study. In a simulated environment, this study reconducted single monitor single drone trails as the benchmark, and both of single monitor swarm and multiple monitors swarm trailed are tested against each other and are assessed their effects on cognitive workload. The cooperation time and target identification are recorded, and officers completed a survey that included adjusted NASA-TLX survey, modified SART survey, and informal interview questions to determine the optimal setting.
Molecular Identification of the enterotoxin B gene from Staphylococcus aureus and the enterobactin B gene from Klebsiella pneumoniae

One hundred and five of clinical samples were collected from Central Teaching Hospital of paediatric and Medical city / Educational laboratory, period from 17/10/2016 to 23/1/2017, Klebsiella pneumoniae and Staphylococcus aureus isolates were diagnosed molecularly by using polymerase chain reaction, enterobactin B and enterotoxin B genes were amplified by using multiplex PCR. Multiplex PCR was performed for K. pneumonia and S. aureus isolates with two primers that target the ent B (enterobactin B) and entB (enterotoxin B) genes respectively. PCR was performed with the primer that targets the ent B (enterobactin B) gene, the result revealed that all eight samples of the K. pneumoniae isolates gave a band of 330 bp in size. On the other site the other primer that targets the ent B (enterotoxin B) gene, the result shows that only two isolate of S.aureus having a band of 411 bp in size. The reason leads to not all S. aureus species had enterotoxin B.
A Statistical Registration of Scale-Changing and Moving Objects with Application to the Human Gait Authentication

A study on the human gait is important in the fields of the biometrics study and the sports/health managements for planning optimal trainings. Olshen et al. (1989) proposed the bootstrap estimation for confidence intervals of the functional data with application to the gait cycle data observed by the motion capture system. Kaziska and Srivastava (2007) proposed the method based on the data matching techniques using the dynamic time warping of human silhouettes. Gait analysis is mainly based on motion capture system and video data. The motion capture system can give the precise measurements of trajectories of moving objects, but it requires the laboratory environments and we cannot be used this system in the field study. On the other hand, the video camera is handy to observe the gait motion in the field study, but such data has many restrictions on analysis based on the filming conditions. In particular, the video data filmed from the frontal-view is difficult to analyze, because the subject getting closer to the camera, and observed data includes the scale-changing parameters. To cope with this, Okusa et al. (2011) proposed a registration for scales of moving object using the method of nonlinear least squares with application to the gait analysis assuming constant speed. In this study, focusing on the human gait cycles, we consider the human gait modeling based on simple gait structure. We estimate the parameters of the human gait cycles using the method of nonlinear least squares (Okusa et al. 2011). We can also show that estimated parameters may be used for the human gait recognition. We apply a nearest-neighbor classifier, using the estimated parameters, to perform the human gait recognition, and present results from an experiment involving 55 subjects. As a result, our method shows 96.3% recognition rate, that has the better performance compared to other methods.
Nosophobia, hypochondriasis, and willingness of people to seek healthcare amidst the COVID-19 pandemic in Calabar Metropolis of Cross River State, Nigeria

Aim: This study investigated the prevalence of nosophobia, hypochondriasis, and willingness of people to seek healthcare amidst the COVID-19 pandemic in Calabar Metropolis of Cross River State, Nigeria. Methods: A cross-sectional descriptive survey design and questionnaire was used to collect data from 200 respondents randomly sampled. Data were sorted, cleaned, coded, and analysed using Statistical Package for the Social Sciences (SPSS) version 20 software, and hypotheses tested using Chi-square test, significant at 95% confidence interval (CI) (0.05). Results: One hundred and eighty two (91%) respondents presented with nosophobia and hypochondriasis, slightly more in women (92 [46%]) as compared to men (90 [45%]), and these had increased with age. Phobia was attributed more to the coronavirus disease 2019 (COVID-19) (48 [24%]), and human immunodeficiency virus and acquired immuno-deficiency syndrome (HIV/AIDS) (40 [20%]) as compared to other diseases, that also, instilled fear and anxiety on respondents. One hundred and fifty seven (78.5%) displayed poor willingness to seek healthcare. Conclusions: Nosophobia and hypochondriasis were found to be associated with age and healthcare seeking behaviour. Gender and education did not play significant role. Fear varied according to the type of diseases. Therefore, public sensitisation is necessary.
Methodology for cross-cultural adaptation of psychometric instruments

Cross-cultural research is important to compare data from subjects with distinct cultural characteristics. The adaptation of psychometric measurement instruments is commonly observed in the literature. This study presents a methodology to perform the cross-cultural adaptation of instruments in different cultures using as example the Weight Concerns Scale (WCS) when applied to a sample of Brazilian and Portuguese female university students. Participated of this study 263 Portuguese students (mean=20.6 years, standard deviation = 1.8) and 252 Brazilian students (mean=21.1 years, standard deviation = 2.8). The participants responded the European and Brazilian Portuguese conciliated version of WCS. The face and content validity of the WCS were evaluated. Confirmatory factorial analysis was used and the goodness-of-fit indices applied were the chi-square by degrees of freedom ratio ( 2 /df), comparative fit index (CFI), normed fit index (NFI) and the root mean square error of approximation (RMSEA). The convergent validity was evaluated by the average variance extracted (AVE). The reliability was estimated by the composite reliability (CR) and internal consistency () of the measures. The factorial stability was checked by multiple-group analysis with groups’ differences evaluated by  2 tests. The conciliated version of the WCS presented adequate fit to total sample ( 2 /df = 6.57; CFI= .97; NFI= .96; RMSEA= .10), Brazilian sample ( 2 /df= 5.37; CFI= .95; NFI= .93; RMSEA=.13), and Portuguese sample ( 2 /df= 3.20; CFI= .98; NFI= .97; RMSEA= .09). The WCS presented strong invariance between the two countries (p > .05). Analysis showed that the cross-cultural version adapted of WCS shows adequate validity, reliability and stability for both countries with different cultural contexts.
Statistical analysis of stochastic processes in social networks

Social networks are an important part of human activity. The statistical analysis and risk assessment in complex social networks has to take into account extremes arising as nodes with large degrees or large PageRanks. These large nodes surrounded by smaller nodes build clusters of interconnected objects. The cluster structure of the network is caused by dependence between nodes that have appeared due to social relationships and common interests. A study of the stochastic properties of these clusters may improve the dissemination of information and advertisements. Clusters may be determined as conglomerates of nodes whose degrees exceed a high threshold. To study clusters determined by the exceedances of the degree metric, we apply results of extreme value theory. Namely, the asymptotically equivalent distributions of cluster and inter-cluster sizes obtained in Markovich (2014) and the extremal index that determines the dependence measure of extremes are used. Sampling techniques like a PageRank random walk, and Metropolis-Hastings Markov chains are often used to collect information about characteristics of nodes such as their in(cid:13)uence and popularity. To compare sampling techniques, we propose to estimate the (cid:12)rst hitting time, i.e. the minimal time to reach a large node. To this end, we use the author’s recent results with regard to the hitting time of threshold exceedances and its asymptotically equivalent geometric-like distribution and the limit mean. Secondly, we look deeper into the PageRank random walk that can be considered as a speci(cid:12)c branching process. Jelenkovi(cid:19)c and Olvera-Cravioto (2010), and Volkovich, Litvak (2010) proved that the stationary distribution of the PageRank process is heavy-tailed, regularly varying. We study extremal properties of the PageRank process. Particularly, we represent the extremal index of the PageRank process obtained in Avrachenkov, Markovich and Sreedharan (2014) by means of copulas. The exposition is provided by illustrations arising form the statistical analysis of real data that have been obtained in social networks.
Changing census by combining administrative sources and sample surveys

Istat, the National Institute of Statistics of Italy, to overcome the main gaps of a decennial population census, a too big and no more sustainable survey with too many sunk costs, is moving to a censimento permanente, a new kind of census which, in order to produce census outputs every year, makes a more intensive use of administrative and statistical sources in a sequence of well-engineered operations and requires a limited additional effort in “ad hoc” sample surveys. We are making in-depth studies on methods and new technologies that can be employed to get these goals and on the underlying conceptual issues. According to the European Regulation on population and housing censuses, the population is the set of usual residents, defined as those who have lived or intend to live for a period of more than 12 months in their place of usual residence. Considering that intentions to live are not registered in administrative sources, and also that the identification of residents who lived longer than a year is quite difficult, this definition is tough to apply from existing sources. Moreover the actual usual resident population may differ from the registered population because of undocumented or not canceled migrations or improper registration for fiscal convenience. From the methodological point of view, we are investigating on the predictive capacity of models having usual residence as response variables and data from multiple administrative and statistical sources as independent variables, and among them, latent class models and several generalization of capture – recapture methods to the use of multiple lists. To achieve the goals set to the censimento permanente is extremely important the increase of the availability of administrative data sources and a more extensive use of new technologies for data collection.
Comparative multivariate forecast performance for the G7 Stock Markets: VECM Models vs deep learning LSTM neural networks

The prediction of stock prices dynamics is a challenging task since these kind of financial datasets are characterized by irregular fluctuations, nonlinear patterns and high uncertainty dynamic changes.The deep neural network models, and in particular the LSTM algorithm, have been increasingly used by researchers for analysis, trading and prediction of stock market time series, appointing an important role in today’s economy.The main purpose of this paper focus on the analysis and forecast of the Standard & Poor’s index by employing multivariate modelling on several correlated stock market indexes and interest rates with the support of VECM trends corrected by a LSTM recurrent neural network.