Miracle-dz/UniFAR-FTUs huggingface dataset:
Phylogenetic Models of Language Diversification

Language diversi cation is a stochastic process which presents similarities with phylogenetic evolution. Recently, there has been interest in modelling this process to help solve problems which traditional linguistic methods cannot resolve. The problem of estimating and quantifying the uncertainty in the age of the most recent common ancestor of the Indo-European languages is an example. We model lexical change by a point process on a phylogenetic tree. Our model is speci cally tailored to lexical data and in particular treats aspects of linguistic change which are hitherto unaccounted for and which could have a strong impact on age estimates: catastrophic rate heterogeneity and missing data. We impose a prior distribution on the tree topology, node ages and other model parameters, give recursions to compute the likelihood and estimate all parameters jointly using Markov Chain Monte Carlo. We validate our methods using an extensive cross-validation procedure, reconstructing known ages of internal nodes. We make a second validation using synthetic data and show that model misspeci cations due to borrowing of lexicon between languages and the presence of meaning categories in lexical data do not lead to systematic bias. We fit our model to two data sets of Indo-European languages and estimate the age of Proto-Indo-European. Our main analysis gives a 95% highest posterior probability density interval of 7110 9750 years Before the Present, in line with the so-called Anatolian hypothesis for the expansion of the Indo- European languages. We discuss why we are not concerned by the famous criticisms of statistical methods for historical linguistics leveled by Bergsland and Vogt [1962]. We also apply our methods to the reconstruction of the spread of Swabian dialects and to the detection of punctuational bursts of language change in the Indo-European family.
Prediction of stock movement using phase space reconstruction and extreme learning machines

ABSTRACT Stock movement prediction is regarded as one of the most difficult, meaningful, and attractive research issues in the field of financial markets. The stock price data have non-stationary, noisy, and non-linear characteristics which make the movement and its prediction a challenging task. In this paper, we propose a framework to predict the stock price movement using phase space reconstruction (PSR) and extreme learning machines (ELM). The uniqueness of the framework is reflected by its feature transformation technique which computes the information distance from the transformed features in phase space. The distance from phase space dimensions are modelled with ELM to predict the stock price movement. A decision-level fusion is performed on the ELM models trained using each category of features to improve the prediction performance. The framework has been validated on one of the challenging Borsa Istanbul (BIST 100) dataset which is a widely used dataset in stock price prediction studies. The results from the proposed framework are compared with the conventional machine learning pipeline as well as the baseline methods, i.e., random and Naïve approach to show the effectiveness in prediction performance. Experimental results reveal that the framework improves predictive performance by 4.5% in terms of F-measure values.
Tugboat resting location optimization using AIS data analysis

In this thesis we investigate how well Automatic Identification System data can describe the nautical chain of the Port of Rotterdam and we use this data analysis to optimize the positioning of tugboat resting locations in the port. We find that the quality of AIS data is not flawless, however, it can accurately describe certain parts of the nautical chain, such as locations where pilot tenders and tugboats meet deepsea vessels to start or end service and service durations. Because of missing data, we find that the AIS data cannot be used to describe interarrival times of nautical service requests accurately. Using the findings of this analysis, we then model the problem of positioning tugboat resting locations in the Port of Rotterdam as a two-stage stochastic problem with uncertainty in the demand and return parameters. We are able to find upper and lower bounds on the optimal objective value of the stochastic model and we find the optimal solution within reasonable computation time. We test the effect of changing to the optimal locations with a discrete-event simulation model, where we find that a yearly saving of almost e65,000 or 3.8% of total costs is achieved.
Extenso ameloblastoma unicístico em mandíbula: relato de caso

Objetivo: Relatar um caso de Ameloblastoma Unicístico em região anterior de mandíbula, descrevendo os métodos diagnósticos utilizados e o tratamento empregado. Relato de Caso: Paciente do gênero feminino, 40 anos de idade, compareceu ao serviço de Cirurgia e Traumatologia Bucomaxilofacial da Faculdade de Odontologia da Universidade Federal da Bahia, com queixas de aumento de volume em região anterior de mandíbula, com evolução de 10 meses. O exame de imagem revelou lesão unilocular extensa que expandia cortical óssea em região de mento. Optou-se pela biópsia excisional da lesão, sob anestesia geral. O exame o espécime obtido confirmou o diagnóstico de Ameloblastoma Unicístico, para o qual decidiu-se pela manutenção da terapêutica inicial. A paciente segue em acompanhamento pela equipe, sem sinais de recidivas. Considerações Finais: O manejo do Ameloblastoma Unicístico por vezes demanda a biópsia excisional da lesão a fim de diferencia-la dos cistos odontogênicos e de individualizar seu padrão histológico. A abordagem conservadora pode ser adotada, desde que um acompanhamento rigoroso seja procedido.
Robotic Colorectal Surgery using Senhance® Robotic Platform: Single Center Experience with First 13 Cases

[full article, abstract in English; abstract in Lithuanian] Until recently, robotic surgery has been associated only with da Vinci robotic system. A novel Senhance® robotic system (TransEnterix Surgical Inc., Morrisville, NC, USA) has been introduced almost 5 years ago. Published reports on experience in colorectal surgery using this robotic platform is very limited. We present a prospective analysis of first 13 robotic colorectal surgeries in Klaipėda University Hospital, Klaipėda, Lithuania. 13 patients underwent various colorectal resections: 10 for colorectal cancer and 3 for colonic polyps. 7 were men and 6 women, age range 32–77 years, on an average 56 years. Among 10 patients with colorectal cancer, 3 had stage I, 3 stage II, 3 stage III and 1 stage IV colorectal cancer. 2 patients were operated for unremovable ascending colon adenomas and 1 underwent prophylactic subtotal colectomy with ileorectal anastomisis for familial adenomatous polyposis. Complication occurred in 1 case (7.7%). This patient underwent robotic abdominoperineal resection for low rectal cancer, developed postoperative bleeding from perineal wound on day 7 and had to be taken to operative room for oversuturing the bleeding vessel. Operative time was on an average 3 hours 50 minutes, ranging from 2 hours and 55 minutes to 6 hours and 10 minutes. In-hospital stay ranged from 5 to 16 days, on an average 7 days. Conclusion. Our experience with different types of robotic colorectal resections allows us to state that Senhance® robotic system is feasible and safe for colorectal surgery, and wider implementation of this system in our specialty worldwide is simply a question of time.
Human Rights in a Kantian Key

Abstract This article discusses Luigi Caranti’s Kant’s Political Legacy, which argues, among other things, that a Kantian reconstruction of dignity can provide a foundation for human rights. Caranti’s book is one of the most powerful recent reconstructions of Kant’s political philosophy. Four main points are argued in response. First, to what extent can dignity understood as a value ground the essentially relational character of human rights claims? Second, does Caranti explain why our mere rational capacity to set moral ends has dignity rather than the realization of that capacity in a morally righteous will? Third, how can the argument provided avoid the conclusion that, because people’s capacities vary, their dignity varies too? Fourth, is Kant’s political philosophy incompatible with our modern understanding of human rights and, in particular, their function in international law and practice?
Repeated sprint training in hypoxia – an innovative method

The year 2018 marked the 50th anniversary of the Mexico Olympic games, which represents the starting point of scientific research on hypoxic training. Since the original “Live High – Train High”, many altitude/hypoxic training methods have been developed. The aim of the present review is to present the most recent method called “Repeated Sprint training in Hypoxia” (RSH). RSH is of unprecedented interest in the altitude training area with 25 studies published in the 5-year period following the pioneer article in 2013, and with only two studies that did not report any beneficial effects. Potential mechanisms include transcriptional factors involved in oxygen-signaling and oxygen-carrying capacity and mitochondrial metabolism enzymes, improved behavior of fasttwitch fibers notably via compensatory vasodilatation, improved vascular relaxation and greater microvascular oxygen delivery as well as faster rate of phosphocreatine resynthesis. In general, RSH leads to superior repeated-sprint ability (i.e., faster mean sprint times or higher power outputs associated witha better resistance to fatigue during a repeated-sprint test) in normoxic conditions. RSH where hypoxia is induced by voluntary hypoventilation at low lung volume (named VHL) may also improve repeated-sprint performance more than in normoxia. Practically, RSH benefits have been demonstrated for a large range of team- (rugby, football, LaCrosse, Australian Football, field hockey), endurance (cycling, track and field, cross-country ski), racket (tennis) or combat (Jiu-Jitsu) sports.
Bearing Fault Detection Using Logarithmic Wavelet Packet Transform and Support Vector Machine

Objective: This paper presents an automated approach that combines Fisher ranking and dimensional reduction method as kernel principal component analysis (KPCA) with support vector machine (SVM) to accurately classify the defects of rolling element bearing used in induction motor. Methodology: In this perspective, vibration signal produced by rolling element bearing was decomposed to four levels using wavelet packet decomposition (WPD) method. Thirty one Logarithmic Root Mean Square Features (LRMSF) were extracted from four level decomposed vibration signals. Initially, thirty one features were rank by Fisher score and top ten rank features were selected. For effective detection, top ten features were reduced to a new feature using dimension reduction methods as KPCA and generalized discriminant analysis (GDA). After this, the new feature applied to SVM for binary classification of bearing defects. For analysis of this thirty six standard vibration datasets taken from online available bearing data center website of Case Western Reserve University on bearing conditions like healthy (NF), inner race defect (IR) and ball bearing (BB) defects at different loads. Results: The simulated numerical results show that proposed method KPCA with SVM classifier using Gaussian Kernel achieved an accuracy (AC) of 100, Sensitivity (SE) of 100%, Specificity (SP) of 99.3% and Positive prediction value (PPV) of 99.3% for NF_IRB dataset, and an AC of 100, SE of 99.8%, SP of 100% and PPV of 100% for NF_BBB dataset.
Forgiveness and Subjective well-being as correlates of National Identity

This study examined relationship between forgiveness and subjective well-being as correlates of National identity: implications for National Development. The participants were 166 students who were drawn from Nnamdi Azikiwe University Awka. Age range of participants was between 17 years and 29 years while mean age was 21.24 years and standard deviation 2.17. Data for the study was collected using forgiveness scale Rye (1998), subjective well-being scale by Diener, Emmons, Larsen and Griffin (1985) and National Identity Scale by Lilli and Diehl (1999). The study adopted correlation design. Consequently Pearson product moment correlation coefficient was used to as the statistical tool for data analysis. Result showed that there was significant correlation between forgiveness and national identity at r= . 53**, P < . 00. Also there was a significant positive correlation between Subjective well-being and national identity at r=. 48**, P<. 001. It was concluded that both forgiveness and subjective well-being relate positively to national development. It was recommended that forgiveness should be adopted among students as this will enhance national identity. Also, that school management should seek ways to improve well being of students so as to enhance sense of identity.
EFFECT OF INTRATUMORAL INJECTION OF DOXORUBICIN IN THE TREATMENT OF INDUCED ORAL SQUAMOUS CELL CARCINOMA (EXPERIMENTAL STUDY)

INTRODUCTION: Oral squamous cell carcinoma (OSCC) is the sixth common cancer. Surgery remains the main way of OSCC treatment. It is followed by radiotherapy and chemotherapy either alone or in combination. Conventional chemotherapy is associated with systemic toxicity. Doxorubicin (DOX) is one of the effective chemotherapeutic drugs. Direct delivery of chemotherapeutics may reduce their side effects. OBJECTIVES: The study aimed to evaluate the anticancer effect of intratumoral injection of DOX in the treatment of chemically induced OSCC. MATERIALS AND METHODS: Thirty-two Syrian golden male hamsters were used as an animal model for oral carcinogenesis. After cancer induction, the hamsters were divided into 4 groups; saline-intraperitoneal (IP), saline-intratumoral, DOX-IP, and DOX-intratumoral. The clinical evaluation of the proposed treatment included measuring the change in tumor volume before and after treatment, whereas, the histological evaluation included calculating the apoptotic index. The proliferative activity was evaluated immunohistochemically by minichromosome maintenance 3 (MCM3). In all statistical results, a p < 0.05 was considered significant. RESULTS: The DOX-IP and DOX-intratumoral groups reported significant decrease in the mean tumor volume. The apoptotic index (AI) was significant only in the DOX-intratumoral group. The MCM3 immunostain showed significant decrease in the values of mean area percent (MA%) and mean optical density (MOD) in DOX-intratumoral group, whereas the DOX-IP group was insignificant in its MA% and MOD. CONCLUSION : Local delivery of this chemotherapeutic drug may be suitable alternative to the systemic administration, with superior anticancer effect in the treatment of superficial tumors. KEY WORDS: Oral squamous cell carcinoma, Chemotherapy, Doxorubicin, Intratumoral, Hamsters, Minichromosome maintenance 3
Fisiología del páncreas exocrino

La síntesis de proteínas es un proceso esencial para la vida de una célula; por lo tanto, cada célula está capacitada para llevar a cabo la pro­ ducción de las proteínas necesarias para cumplir con sus funciones. Más allá de esta síntesis de proteínas, en esencia común a todas las células, algunas de ellas sintetizan también proteínas que cumplen funciones fuera del sitio de origen. Es­ tas son las llamadas proteínas "for export” , y una de las células que suelen tomarse como ejemplo de este proceso son las acinares del pán­ creas, a través de la liberación de sus enzimas.
Promoting Organic Production & Consumption: A Case of Punjab, Pakistan

The study seeks to investigate the impact of major determinants influencing marketing potential and consumer’s willingness to pay for organic vegetables in Punjab, Pakistan. In this regard, two districts (Lahore and Toba Tek Singh) were selected purposively. Information was collected for the main organic vegetables. Convenient sampling technique was used to collect data because limited numbers of respondents were available. A sample size of 50 organic farmers (25 from each district) and 50 consumers (25 from each district) was selected. Multivariate regression analysis was employed to identify and evaluate the effects of marketing potential (farmers) and the consumer’s willingness to pay for organic vegetables in the study area. According to selected organic vegetable growers’ potential existed for the organic vegetables farming in the country and major variables influencing significantly the market potential for organic vegetables as income, price, no pesticide residues whereas hygienic food and more nutrients in the organic vegetables affecting insignificantly the market potential for organic vegetables in the study area. The relationship between the dependent variable (demand for organic vegetables) and independent variables (income, hygienic food, price, pesticide residues and more nutrients in the organic vegetables) was estimated by using a regression model. On the other hand, a consumer survey was conducted in order to delineate the effect of consumer’s willingness to pay for organic vegetables in the selected area. The findings of the research depicted that no synthetic pesticide residues, appearance and prices of organic vegetables influencing significantly the consumer’s willingness to pay for organic vegetables whereas quality, long shelf life and taste affecting insignificantly the consumer’s willingness to pay for organic vegetables in the study area. The price of the organic vegetables should be low that’s why every consumer will purchase organic vegetables instead of conventional vegetables. It should be assured by the government that there are no pesticide residues in the organic vegetables. The farming community may be motivated to produce quality seeds of organic vegetables. A pilot farming program should be initiated with joint involvement of public and private sectors.
CLIK on PLCs! Attacking Control Logic with Decompilation and Virtual PLC

—This paper presents CLIK , a new remote attack on the control logic of a programmable logic controller (PLC) in industrial control systems. The control logic deﬁnes how a PLC controls a physical process such as a nuclear plant. A full control logic attack faces two critical challenges: 1) infecting the control logic in a PLC at a ﬁeld site and, 2) hiding the infection from engineering software at a control center since the software can obtain the infected logic from the PLC and reveal it to a control engineer. The existing academic efforts only (partially) address the former. CLIK is a ﬁrst practical control-logic attack that deals with both challenges successfully. It modiﬁes the control logic running in a remote target PLC automatically to disrupt a physical process. CLIK also employs a new virtual PLC approach that hides the malicious modiﬁcations by engaging the engineering software with a captured network trafﬁc of the original (uninfected) control logic. It is fully implemented on real hardware/software used in industrial settings and is made publicly available for academic research on control logic attacks 1 . CLIK consists of four phases and takes less than a minute to complete an attack cycle. As part of the implementation, we found a critical (zero-day) vulnerability in the password authentication mechanism of a target PLC, which allows the attacker to overwrite password hash in the PLC during the authentication process and gain access to the (protected) control logic. We have disclosed the vulnerability responsibly to the PLC vendor who has already patched the vulnerability 2 .
Análise qualitativa da política de manutenções dos sistemas de um pwr típico por redes neurais artificiais

Proceedings and techniques in order to maximize the reliability and the availability of industrial plants have been used along the last decades by specialists and professionals of maintenance. However, the modern industrial systems’ sizing, and the increasing complexity and interdependence among its components have become this activity’s planning a more and more difficult task. Considering this scenario, the objective of the present work is to provide a computational tool which is able to help about the taking decision's task, and about planning policies of maintenance practiced in thermonuclear plants. The tool developed is based on the artificial neural networks (ANN) for the recognition of standards and establishment of correlations among events occurred in the components of pressurized water reactor (PWR) typical systems. The ANN work as miners of database of failure events, and are able to identify connections and to establish imperceptible inferences even for the most experienced specialists in maintenance of nuclear systems. The results were attained from realistic data and are confronted against the maintenance's classic policies which are practiced nowadays on PWR thermonuclear plants. These results show the solidity of the technique in valuing and predicting failures in a real powerplant, and is able to be used as a tool for supporting decisions about planning maintenance policies on a typical PWR.
lFIT: an unsupervised discretization method based on the Ramer-Douglas-Peucker algorithm

Discretization is the process of converting continuous values into discrete values. It is a preprocessing step of several machine learning and data mining algorithms and the quality of discretization may drastically affect the performance of these algorithms. In this study we propose a discretization algorithm, namely line fitting-based discretization (lFIT), based on the Ramer--Douglas--Peucker algorithm. It is a static, univariate, unsupervised, splitting-based, global, and incremental discretization method where intervals are determined based on the Ramer--Douglas--Peucker algorithm and the quality of partitioning is assessed based on the standard error of the estimate. To evaluate the performance of the proposed method, a set of experiments are conducted on ten benchmark datasets and the achieved results are compared to those obtained by eight state-of-the-art discretization methods. Experimental results show that lFIT achieves higher predictive accuracy and produces less number of inconsistency while it generates larger number of intervals. The obtained results are also validated through Friedman's test and Holm's post hoc test which revealed the fact that lFIT produces discretization schemes that statistically comply both with supervised and unsupervised discretization methods.
Über die Veränderung der Insulinsensitivität in gesunden, HIV-negativen Probanden nach einer 14-tägigen Einnahme von geboostertem Elvitegravir, Darunavir und Lopinavir in Kombination mit Emtricitabin/Tenofovir disoproxil fumarat

Aufgrund der zunehmenden Bedeutung der Langzeittoxizitat antiretroviraler Medikamente war das Ziel der vorliegenden Arbeit, mogliche Veranderungen der Insulinsensitivitat nach Einnahme der festen Dosiskombination (E/c/F/TDF) und F/TDF+LPV/r im Vergleich zu F/TDF+DRV/r mittels hyperinsulinamischer euglykamischer Clamp (HEGC) Technik zu untersuchen. Zudem sollten Veranderungen des Lipidmetabolismus untersucht werden. Es zeigte sich eine statistisch signifikante Reduktion der Insulinsensitivitat durch F/TDF+LPV/r, jedoch weder durch E/c/F/TDF noch durch F/TDF+DRV/r. Bei F/TDF+LPV/r und F/TDF+DRV/r zeigte sich ein teilweise signifikant negativerer Einfluss auf den Lipidmetabolismus als beim neueren Regime E/c/F/TDF.