Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of an intraperitoneal drug-release device for advanced ovarian cancer therapy

More than 14,000 women in the United States die from ovarian cancer each year. The standard of care is tumor-debulking surgery followed by adjuvant chemotherapy. Combination intraperitoneal (IP) and intravenous (IV) chemotherapy has been shown to lengthen survival over IV therapy alone. Large-volume infusions, drug-associated toxicity, and catheter-associated complications, however, increase morbidity and limit patient adherence, often resulting in discontinuation of IP therapy. The technical skill required for catheter implantation and IP chemotherapy administration has also limited its clinical adoption. The proposed solution is an implantable IP device capable of localized drug delivery that maintains the efficacy of the standard of care and overcomes current clinical challenges. A reservoir-based device was developed to release cisplatin at a constant rate. In vivo studies demonstrated that continuous dosing reduces tumor burden to the same extent as weekly IP injections. The implanted device induced significantly less systemic toxicity compared to IP injections, despite administration of higher cumulative doses. A subsequent in vitro study revealed that greater tumor shrinkage following continuous cisplatin exposure was achieved with smaller tumor nodules. These results support that an implanted device would be maximally effective against microscopic residual disease. In vitro results also illustrated that a human-scale device fabricated from orifice-lined silicone can be designed to release cisplatin continuously at the desired rate. The promising preclinical results in this thesis highlight the potential for this novel IP dosing regimen to improve the treatment of late-stage ovarian cancer and set the stage for development of the proposed human device. Thesis Supervisor: Michael J. Cima, PhD Title: David H. Koch Professor of Engineering
The use of e-dictionary to read e-text by intermediate and advanced learners of Chinese

This study focuses on the pedagogical outcomes connected with the use of an e-dictionary by intermediate and advanced learners of Chinese to aid in reading an expository Chinese e-text. Twenty intermediate and advanced participants read an e-text twice aided by an e-dictionary and wrote recalls of the text in English. In addition to low frequency words, intermediate students frequently looked up high and middle frequency words, whereas advanced participants did not have much difficulty with either high or middle frequency words. The e-dictionary helped intermediate participants consolidate word meaning, learn new words and close the vocabulary knowledge gap between them and advanced learners; in contrast, the e-dictionary afforded less reading development for the advanced group. As for reading comprehension, the e-dictionary enhanced reading comprehension of intermediate participants to a level comparable to advanced students. The low comprehension of advanced participants might partly have been caused by their unfamiliarity with the inductive discourse structure of the text. Clearly, intermediate students benefited more than advanced learners from using the e-dictionary, which provides translations in the first language.
An Introductory Grammar of Rabbinic Hebrew

The student is introduced to the grammar, forms of expression, and idiosyncrasies of Rabbinic Hebrew. The book comprises 32 teaching units, each with a phraseology section, vocabulary, and exercise texts. Historical and morphological aspects are discussed as well as syntax and usage. There is an introductory survey of research into Rabbinic Hebrew and a detailed bibliography.
Programming Erlang: Software for a Concurrent World

Erlang solves one of the most pressing problems facing developers today: how to write reliable, concurrent, high-performance systems. It's used worldwide by companies who need to produce reliable, efficient, and scalable applications. Invest in learning Erlang now. Moore's Law is the observation that the amount you can do on a single chip doubles every two years. But Moore's Law is taking a detour. Rather than producing faster and faster processors, companies such as Intel and AMD are producing multi-core devices: single chips containing two, four, or more processors. If your programs aren't concurrent, they'll only run on a single processor at a time. Your users will think that your code is slow. Erlang is a programming language designed for building highly parallel, distributed, fault-tolerant systems. It has been used commercially for many years to build massive fault-tolerated systems that run for years with minimal failures. Erlang programs run seamlessly on multi-core computers: this means your Erlang program should run a lot faster on a 4 core processor than on a single core processor, all without you having to change a line of code. Erlang combines ideas from the world of functional programming with techniques for building fault-tolerant systems to make a powerful language for building the massively parallel, networked applications of the future. This book presents Erlang and functional programming in the familiar Pragmatic style. And it's written by Joe Armstrong, one of the creators of Erlang. It includes example code you'll be able to build upon. In addition, the book contains the full source code for two interesting applications: A SHOUTcast server which you can use to stream music to every computer in your house, and a full-text indexing and search engine that can index gigabytes of data. Learn how to write programs that run on dozens or even hundreds of local and remote processors. See how to write robust applications that run even in the face of network and hardware failure, using the Erlang programming language.
Transcranial magnetic stimulation (TMS) application in sport medicine: A brief review

FIORENZO MOSCATELLI1,§, ANNA VALENZANO1§, VINCENZO MONDA2, MARIA RUBERTO3, GIUSEPPE MONDA1, ANTONIO I.TRIGGIANI1, EMANUELE MONDA1, SERGIO CHIEFFI2, INES VILLANO2, LUCIA PARISI4, MICHELE ROCCELLA4, ANTONIETTA MESSINA2,* 1Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy 2Department of Experimental Medicine, Università degli Studi della Campania “Luigi Vanvitelli”, Italy 3Department of Medical-Surgical and Dental Specialties, Second University of Naples, Italy 4Department of Psychological, Pedagogical and Educational Sciences, University of Palermo, Italy
Large Scale Text Classiflcation using Semi-supervised Multinomial

Numerous semi-supervised learning methods have been proposed to augment Multinomial Naive Bayes (MNB) using unlabeled documents, but their use in practice is often limited due to implementation di‐culty, inconsistent prediction performance, or high computational cost. In this paper, we propose a new, very simple semi-supervised extension of MNB, called Semi-supervised Frequency Estimate (SFE). Our experiments show that it consistently improves MNB with additional data (labeled or unlabeled) in terms of AUC and accuracy, which is not the case when combining MNB with Expectation Maximization (EM). We attribute this to the fact that SFE consistently produces better conditional log likelihood values than both EM+MNB and MNB in labeled training data.
High-speed non-contact ultrasound system for rail track integrity evaluation

Ultrasonic rail inspection is the most commonly implemented method for detecting internal rail defects. While the conventional ultrasound wheel probe has gained its popularity within rail maintenance community, it suffers from the limited test speeds (25 mph at most). This paper presents the state-of-the-art developments in ultrasonic rail inspection technique that utilizes non-contact receivers and no active transmitters. The transfer function between two points of the rail is reconstructed by deconvolutions of multiple pairs of receivers that sense the acoustics naturally excited in the rail by the running wheels. The deconvolution process eliminates the random effect of the excitation to reconstruct a stable acoustic transfer function of the rail. A fixed bulk delay and frequency selection technique are introduced to facilitate the power spectral density estimation for robust transfer function reconstruction. A multivariate analysis based on selected features extracted from various frequency bands is conducted on the signals recorded by multiple sensor pairs respectively. Furthermore, damage index traces based on data from different sensor pairs provide system redundancy for improved reliability with the voting logic for damage detection. The proposed approach lends itself to extremely high testing speeds (as fast as the service train speed, e.g. 60 mph and above), that would enable the real-time evaluation of rail track integrity at train operational speeds. A prototype based on this passive-only inspection idea has been constructed and tested with the DOTX216 testing vehicle of the Federal Railroad Administration at the Transportation Technology Center (TTC) in Pueblo, CO in September 2016. Test runs were made at various speeds from 25 mph to 80 mph (the maximum speed allowed on the test track). The results show the feasibility of stable reconstruction of the transfer function from the random wheel excitation, as well as the detection of joints and welds present in the track. Some tests were also conducted on TTC Defect Farm showing the potential for defect defection.
Spiritual emergency : when personal transformation becomes a crisis

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Galaxy and mass assembly (GAMA): Bulge-disk decomposition of KiDS data in the nearby universe

We derive single Sérsic fits and bulge-disk decompositions for 13096 galaxies at redshifts z < 0.08 in the GAMA II equatorial survey regions in the Kilo-Degree Survey (KiDS) g, r and i bands. The surface brightness fitting is performed using the Bayesian two-dimensional profile fitting code ProFit. We fit three models to each galaxy in each band independently with a fully automated Markov-chain Monte Carlo analysis: a single Sérsic model, a Sérsic plus exponential and a point source plus exponential. After fitting the galaxies, we perform model selection and flag galaxies for which none of our models are appropriate (mainly mergers/Irregular galaxies). The fit quality is assessed by visual inspections, comparison to previous works, comparison of independent fits of galaxies in the overlap regions between KiDS tiles and bespoke simulations. The latter two are also used for a detailed investigation of systematic error sources. We find that our fit results are robust across various galaxy types and image qualities with minimal biases. Errors given by the MCMC underestimate the true errors typically by factors 2-3. Automated model selection criteria are accurate to $>90{{\%}}$ as calibrated by visual inspection of a subsample of galaxies. We also present g − r component colours and the corresponding colour-magnitude diagram, consistent with previous works despite our increased fit flexibility. Such reliable structural parameters for the components of a diverse sample of galaxies across multiple bands will be integral to various studies of galaxy properties and evolution. All results are integrated into the GAMA database.
Computer-Based Fluency Evaluation of English Speaking Tests for Koreans

In this paper, we propose an automatic fluency evaluation algorithm for English speaking tests. In the proposed algorithm, acoustic features are extracted from an input spoken utterance and then fluency score is computed by using support vector regression (SVR). We estimate the parameters of feature modeling and SVR using the speech signals and the corresponding scores by human raters. From the correlation analysis results, it is shown that speech rate, articulation rate, and mean length of runs are best for fluency evaluation. Experimental results show that the correlation between the human score and the SVR score is 0.87 for 3 speaking tests, which suggests the possibility of the proposed algorithm as a secondary fluency evaluation tool
Implementation of Recommender System for Web pages

In Web based applications, Recommender systems have become fundamental information access system. They effectively prune large information spaces which provide appropriate decision making and suggestions, so that the users are directed towards those web pages that best meet their needs, preferences and interests. In web-based context, this can be achieved by basic rough set model and collaborative filtering techniques in decision making of the web pages. The recommender system can be implemented based on two types of techniques which are content based filtering and collaborative filtering. Content based filtering constructs a recommendation on basis of user’s behavior (historical browsing information) and collaborative filtering uses group knowledge to form a recommendation based on like users. Sparsity, the cold-start problem, fraud are main challenges in recommender system.This paper proposes recommendations to the user that varies from one user to another user which is based on the user's profile. (For example, for a search with same keyword a student will be suggested differently compared to a scholar or a teacher). The abstract should state the purpose, approach, results and conclusions of the work. The author should assume that the reader has some knowledge of the subject but has not read the paper. Thus, the abstract should be intelligible and complete in it-self (no numerical references); it should not cite figures, tables, or sections of the paper. The abstract should be written using third person instead of first person.
Aplicación de los métodos de toma de decisiones LP-GW-AHP y lógica difusa para la selección de una electiva académica en la Universidad del Atlántico, Colombia

Resumen En este articulo de investigacion se describen y se aplican los metodos de toma de decision multicriterio LP-GW-AHP y logica difusa para la seleccion de una electiva academica en la Universidad del Atlantico. En el proceso de toma de decision participaron varios grupos de personas con un alto conocimiento relativo a cada una de las alternativas de decision, a los cuales se les denomino expertos. Inicialmente, se recolecto la informacion necesaria para la toma de decision de acuerdo con los puntos de vista de los expertos en el tema. Seguidamente, se establecieron las ponderaciones cuantitativas y cualitativas de cada uno de los criterios a evaluar para obtener las preferencias individuales de los expertos. Finalmente, se aplico la tecnica de toma de decisiones grupal con logica difusa para saber la preferencia grupal de los expertos. Palabras clave Logica difusa, Metodo AHP, Metodo LP-GW-AHP, Toma de decisiones multicriterio. Abstract This article describes and presents the application of multiple-criteria LP-GW-AHP decision making methods for selecting an elective course in the University of the Atlantico. During the decision making process participated several groups of people having high knowledge, called experts, regarding each of the decision alternatives. First was collected the information necessary for decision making based on the points of view of the experts on the subject. After this were established the quantitative and qualitative weights of each of the evaluated criteria in order to obtain particular preferences of the experts. Finally was applied the group decision making technique using fuzzy logic in order to know the group preferences of the experts. Keywords Fuzzy logic, AHP Method, LP-GW-AHP Method, Multiple-criteria Decision-making. Resume Dans cet article on decrit et applique les methodes de prise de decisions de multiples criteres LP-GW-AHP et logique floue pour selectionner une cours electif dans l’Universite de l’Atlantico. Dans ce processus de prise de decisions ont participe plusieurs groupes de personnes avec une haute connaissance relatif a chaque des alternatifs de decision, ceux qu’on a appele les expertes. Au debut on a reuni l’information necessaire pour la prise de decisions d’apres les points de vue des experts dans les sujets. Apres on a etabli les ponderations quantitatif et qualitatives de chaque un des criteres a evaluer pour obtenir les preferences individuels des expertes. Finalement on a applique la technique de prise de decisions de groupe avec la logique floue pour savoir la preference de groupe des experts. Mots-cles Logique floue, Methode AHP, Methode LP-GW-AHP, Prise de decisions de multiples criteres.
PEMBENTUKAN KATA DAN ISTILAH BARU DALAM BAHASA ARAB MODERN

This paper is aimed to discuss how to produce new words and terms in Modern Standard Arabic (MSA). Due to the development of Science, Technology, and Arts, new words and terms are born. Because the new words and terms are derived from foreign languages, especially English, some methods of formation in Arabic language are needed. There are (5) five methods of this formation. Firstly, Qiyas; the use of analogy in producing new words and terms based on the Arabic rules. Secondly, isytiqaq; the use of old Arabic form to produce a new words and terms. Thirdly, translation of foreign language to Arabic. Fourtly, borrowing from foreign languages which have two categories; ta`rib (fully Arabization) and tadkhil (borrowing). Fiftly, acronym/abbreviation which is newly used in Arabic language.
Kinematic design of a 7-DOF cable-driven humanoid arm: a solution-in-nature approach

A solution-in-nature approach has been adopted in the design of a 7-DOF humanoid robotic arm. Similar to a human arm, the proposed robotic arm consists of three sequentially connected modules, i.e., a 3-DOF shoulder module, a 1-DOF elbow module, and a 3-DOF wrist module. To mimic the driving scheme of the human arm, all of the three arm modules are driven by cables which are functionally equivalent to human muscles (can pull but cannot push). Such a robotic arm has the advantages of light weight, high dexterity, and large reachable workspace. Hence, it can be an ideal versatile arm for various service robots to perform human-like operations. Two critical design analysis issues, i.e., displacement analysis and cable-tension analysis are addressed in more details. The closed form solution is derived for the forward displacement analysis, while the inverse displacement solution is obtained through an optimization technique. An effective cable-tension analysis algorithm is proposed in light of the analysis method for force-closure grasps.
Reprogramming Low-end IoT Devices from the Cloud

The Internet of Things (IoT) consists in a variety of smart connected objects, among which a category of low-end devices based on micro-controllers. The orchestration of low-end IoT devices is not straightforward because of the lack of generic and holistic solutions articulating cloud-based tools on one hand, and low-end IoT device software on the other hand. In this paper, we describe such a solution, combining a cloud-based IDE, graphical programming, and automatic JavaScript generation. Scripts are pushed over the Internet and over-the-air for the last hop, updating runtime containers hosted on heterogeneous low-end IoT devices running RIOT. We demonstrate a prototype working on common off-the-shelf low-end IoT hardware with as little as 32kB of memory.
Does ewe nutrition during pregnancy affect the neonatal behaviour of twin-born lambs?

In this experiment the effects of feeding treatments from mid pregnancy until lambing on the behaviour of twin-bearing ewes and their lambs were investigated. Fifty seven four-year-old Romney ewes were offered a medium (1164 ± 31.6 and 819 ± 16.0 kg DM/ ha preand post-grazing pasture mass, respectively) or ad libitum (2181 ± 47.6 and 1431 ± 24.6 kg DM/ha preand post-grazing pasture mass, respectively) feeding treatment from day 76 of pregnancy until after lambing. At ear-tagging the time taken for the lambs to stand, make contact with, suck from and follow their dam was recorded. A maternal behaviour score based on the distance the ewe moved away from her lambs during tagging was also recorded. Survival analysis showed that lambs born to ewes offered the medium feeding treatment from mid pregnancy until lambing were quicker to stand, suck and follow compared with lambs born to ewes offered the ad libitum feeding treatment (P<0.05). It is unclear whether these behaviours indicate that lambs born to ewes in the medium treatment were more vigorous or that they had unmet needs that prompted the apparent increase in vigour. Ewe feeding treatments did not affect the maternal behaviour of the ewes.
Anton: Answer Set Programming in the Service of Music

With the increasing efficiency of answer set solvers and a better understanding of program design, answer set programming has reached a stage where it can be more successfully applied in a wider range of applications and where it attracts attention from researchers in other disciplines. One of these domains is music synthesis. In this paper we approach the automation and analysis of composition of music as a knowledge representation and advanced reasoning task. Doing so, it is possible to capture the underlying rules of melody and harmony by a very small, simple and elegant set of logic rules that can be interpreted under the answer set semantics. Our system, Anton, is the first algorithmic composer to combine both harmonic and melodic composition. In addition to describing the composition system thus created we consider the advantages of constructing an algorithmic composer this way, and also the limitations of current solvers.
Finding Repeats and Signatures in DNA Sequences Using MPI Clusters

One of the most striking features of genomic DNA sequences is the extent to which repeated substrings occur in the genome. In C. elegans with a genome sequence of 100.2 million nucleotides over 7,000 families of repeat sequences have been identified. Families of repeat sequences account for about one third of the human genome. Repeat sequences come in many different flavors and are responsible for different functions and diseases. Finding repeats has applications in finding defective genes, and in forensic DNA fingerprinting. It also allows us to find differences between genomes.