Miracle-dz/UniFAR-FTUs huggingface dataset:
Soliton self-compression in a photonic crystal fiber with dispersion optimized for pumping near 1300 nm

In this paper, we have designed a high nonlinear photonic crystal fiber (HN-PCF) based on square-lattice geometry with the zero dispersion wavelength (ZDW) around 1300 nm. We came up to realize pulse compression of 28.4 fs around 1300 nm by the generation of solitons of different orders to obtain ultrashort pulses. First, we obtain 4 fs pulses in a PCF length of 66cm, then, we improved the pulse compression until 1.2 fs in a PCF length of 26 cm.This new design of the PCF could be applied for supercontinuum generation witch would be used in Optical Coherence Tomography for high resolution biomedical imaging.
STUDY ON PROPERTIES AND APPLICATIONS OF LAPLACE TRANSFORMATION: A REVIEW

Need of mathematics is increasing in modern life. To explain and for giving proof of their research findings, researchers from all fields of science uses various Mathematical process or tool or model. Laplace transform is one of the major techniques used by scientist and researchers for finding the results to their problems. In this paper we study the properties and broad range of Applications of Laplace transformations in various fields. In this paper we studied how Laplace transform has been used to solve the research problems. The current paper gives theory, problem worked on properties and application of Laplace transform. To present a scientific review on properties and applications of Laplace transformation is the motive of this paper. The review paper gives a survey on Laplace transformation technique. The solution of numerous studies, allow us to suggest the use of this technique to modeltheir research problem mathematically and to find the solution to the same.
S002531542000017Xjra 1..13

We present the description of a new species of genus Timea and the re-description of T. hechteli from cryptic habitats in the Gulf of Mexico. Timea alcoladoi sp. nov. is an encrusting, pale orange sponge, with megascleres ranging from styles to subtylostyles (185–990 μm long) and a single category of microscleres, spherostrongilaster characterized by a prominent rounded centre (5–15 μm in diameter). Timea hechteli was established by Lehnert & Heimler, based on the description of a very small specimen, previously recorded as Halicometes stellata by Little, and transferred to the genus Timea by Hechtel. However, because the name ‘stellata’ was preoccupied by the type species, T. stellata, the species was renamed T. hechteli, to honour George Hechtel. After the revision of Little’s material and new material, we present the re-description of T. hechteli. For both species, partial sequences of COI mtDNA and ITS1-5.8S-ITS2 rDNA region were obtained in order to complement our morphological taxonomy and establish their molecular systematic position among tethyids. Tree topologies for both loci were congruent by grouping together our species as a sister group of the main Tethyida clade, which is according to the current systematics of the group. The COI fragment showed Timea as polyphyletic due to two sequences of Timea (from GenBank) that were clustered with other sponge groups. The species described here are the first record of the genus Timea from the Mexican coast of the Gulf of Mexico. A taxonomic key for West Atlantic Timea species is also presented.
A Task Offloading Method with Edge for 5G-Envisioned Cyber-Physical-Social Systems

Recently, Cyber-Physical-Social Systems (CPSS) have been introduced as a new information physics system, which enables personnel organizations to control physical entities in a reliable, real-time, secure, and collaborative manner through cyberspace. Moreover, with the maturity of edge computing technology, the data generated by physical entities in CPSS are usually sent to edge computing nodes for effective processing. Nevertheless, it remains a challenge to ensure that edge nodes maintain load balance while minimizing the completion time in the event of the edge node outage. Given these problems, a Unique Task Offloading Method (UTOM) for CPSS is designed in this paper. Technically, the system model is constructed firstly and then a multi-objective problem is defined. Afterward, Improving the Strength Pareto Evolutionary Algorithm (SPEA2) is utilized to generate the feasible solutions of the above problem, whose aims are optimizing the propagation time and achieving load balance. Furthermore, the normalization method has been leveraged to produce standard data and select the global optimal solution. Finally, several necessary experiments of UTOM are introduced in detail.
Continuing medical education

Core biopsy rapidly replaced fine needle aspiration (FNA) over the past decade in evaluation of diseases of the female breast in many centers in the USA. We continue to heavily utilize FNA for the initial evaluation of breast masses in our institution. In this article, we discuss the cytologic and core biopsy findings in challenging breast lesions such as papillary and mucinous proliferations, fibroepithelial neoplasms, and low grade cancers. We specifically focus on the pitfalls and limitations of both diagnostic modalities in these selected specific lesions. Diagn. Cytopathol. 2012;40:262–272. ' 2011 Wiley Periodicals, Inc.
Compressive Spectral Imaging Microscopy for Cancer Detection (COSMIC)

We developed a novel spectral microscopy imaging method that opens the path towards automated cancer detection in biopsies. By using the advanced compressive sensing framework, we are able to capture spectral images with unprecedented resolution and speed. We tested the performance of our compressive hyperspectral imaging system for histopathology of cancer cells and have been able to demonstrate unprecedented high detection accuracy. Our method is based on a commercial microscope, it is modular and versatile, and can be used for other applications that require rapid acquisition of high quality spectral images.
Optimization of alkali pretreatment conditions for wax removal from bamboo culm

Appropriate chemical reagents were selected for removing the wax layer of bamboo culm, and optimal treatment conditions with the selected agents were determined in this study. Solutions of potassium carbonate, potassium hydroxide, sodium carbonate, and sodium chloride, along with their mixtures with 1% sodium dodecyl sulfate, were tested for efficacy of wax removal on culms of giant timber bamboo (Phyllostachys bambusoides S. et Z.), hachiku bamboo (Phyllostachys nigra var. henosis Stapf), and moso bamboo (Phyllostachys pubescens Mazel). Of the tested reagents, the mixture of potassium hydroxide and sodium dodecyl sulfate showed the best capability. The effects of varying concentrations of the selected reagents and reaction times at 90 °C were investigated by response surface methodology (RSM). Quadratic regression models representing the degree of wax removal at various treatment conditions were determined. The coefficients of determination of the fitted models were greater than 0.98, meaning that the models were highly accurate in predicting the degree of wax removal. According to the fitted models, the optimal conditions of potassium hydroxide concentration, sodium dodecyl sulfate concentration, and reaction time were 5.08%, 3.6%, and 63 min, respectively. The use of an RSM model offers considerable flexibility for practical uses because it allows multiple solutions with any desired level of wax removal.
Lysyl Oxidase-like 2 ( LOXL 2 ) and E 47 EMT factor : Novel partners in E-cadherin repression and early metastasis colonization

Lysyl Oxidase-like 2 (LOXL2) and E47 EMT factor: Novel partners in E-cadherin repression and early metastasis colonization Giacomo Canesin, Eva P. Cuevas, Vanesa Santos, Celia López-Menéndez, Gema MorenoBueno, Yujie Huang, Katalin Csiszar, Francisco Portillo, Héctor Peinado, David Lyden and Amparo Cano a. Departamento de Bioquímica, Universidad Autónoma de Madrid (UAM), Instituto de Investigaciones Biomédicas "Alberto Sols" CSIC-UAM, IdiPAZ, Madrid, Spain. b. Fundación MD Anderson International Madrid. 28033 Madrid, Spain c. Department of Pediatrics, Cell and Developmental Biology, Weill Cornell Medical College, New York, NY 10021, USA. d. John A Burns School of Medicine, University of Hawaii, Honolulu, HI 96822, USA.
The relationship between employee engagement, transformational leadership , perceived support and intention to quit : an exploratory story

Employee engagement (ENG) is a concern for most organisations as it influences productivity rates and ultimately the financial outcome of an organisation. In order to increase the levels of ENG it is important that organisations identify the antecedents of ENG. There are many antecedents of ENG, for the purposes of this study, the antecedents are: transformational leadership (TFL) and perceived support (PS). It is also important for organisations to gain an understanding of how employee engagement influences employees' intention to quit (ITQ) an organisation. This study is an exploratory attempt to see if firstly, direct relationships exist between the constructs: TFL and ENG; ENG and ITQ; PS and ENG; TFL and PS; TFL and ITQ; PS and ITQ. Secondly, to see if indirect relationships exist between: TFL and ITQ when mediated by ENG and PS and ITQ when mediated by ENG. Pearson's Product Moment correlations, Standard Multiple Regression and partial correlation were used to assess the above propositions. Baron and Kenny's (1986) 3 step process was used to test for mediation. The sample consisted of 43 employees from a financial institution. A significant positive relationship was found between: TFL and ENG; TFL and PS; PS and ENG. A direct negative relationship was found between: ENG and ITQ; TFL and ITQ; PS and ITQ. The TFL-ITQ relationship was found to be completely mediated by ENG. The PS-ITQ relationship was found to be partially mediated by ENG. PS was the only construct that made a unique contribution when predicting ENG and ITQ. Implications include the fact that PS in organisations may be crucial. It not only has a significant contribution to ENG, but to retaining employees as well. If organisations seek to maximise their resources, they need to focus on the implications that PS has on ENG.
An AI Approach Towards Civil Engineering Design Annotations and Object Detection

- Design is one of the principal steps in the creation challenge. Error in layout causes failure in the construction level as properly as inside the assignment improvement degree. Misunderstandings of design standards between parties lead to design mistakes which may additionally lower the first-rate of construction works. It also reasons cost overruns and venture delays.AI strategies can assist inexperienced device operators to hold out complex tasks, which machine operators otherwise couldn’t. It is high-quality in the ones industries which might be locating it increasingly tough to source fairly skilled and skilled operators. The most important applications for AI inside the production sector appear to coagulate around via using gadget getting to know for pattern recognition as nicely as image reputation By the use of AI most of the huge creation companies have started out to advantage greater prominence because of its enhancing safety of human workers in creation sites.Hence the aim of our paper is to create a ML model capable of identifying errors and correcting errors automatically to reduce processing time and training model that learns from the existing data , drawing to recognize the error in the new assigned data and intimidate the errors to be viewed and corrected.
BERT-based conformal predictor for sentiment analysis

We deal with the Natural Language Processing (NLP) task of Sentiment Analysis (SA) on text, by applying Inductive Conformal Prediction (ICP) on a transformers based model. SA, which is the interpretation and classiﬁcation of emotions, also referred to as emotional artiﬁcial intelligence, can be set up as a Text Classiﬁcation (TC) problem. Transformers are deep neural network models based on the attention mechanism and make use of transfer learning by being pretrained on a large unlabeled corpus. Transformer based models have been the state of the art for dealing with various NLP tasks ever since they were proposed at the end of 2018. Our classiﬁer consists of the BERT model for turning words into contextualized word embeddings with parameters ﬁne-tuned on the used corpus and a fully connected output layer for performing the classiﬁcation task. We examine the performance of the underlying BERT model and the proposed ICP on the Large Movie Review dataset consisting of 50000 movie reviews. The results show that the good performance of the underlying classiﬁer is carried on to the ICP extension without any substantial accuracy loss while the provided prediction sets are tight enough to be useful in practise.
A Rough Set Approach for User Identification Based on EEG Signals

Biometric technologies, referring to those that identify or verify the identity of a person using physiological (e.g. face and fingerprint) or behavioral characteristics (e.g., signature and voice), have the potential to solve many of the security problems. Traditional biometrics, such as facial patterns, fingerprints, eye irises, hand geometry and voice patterns, are well known for person authentication or identification purposes. Despite their widely used, such biometrics have certain limitations. It has been shown in previous studies that the brain-wave pattern for each individual is unique and thus can be used as a biometric. We present in this paper an intelligent rough set approach for user identification based on EEG Signals. We have tested the approach with various features set and a result o 92.6 accuracy was obtained with one of the featuresets.
Training methods and nutritional aspects to increase muscle mass : a systematic review

Introducción: El aumento de la masa muscular es uno de los principales retos de los entrenadores deportivos, ya sea para optimizar el rendimiento, por razones estéticas o para la mejora de la salud. Por ello, el objetivo de este trabajo fue analizar los métodos de entrenamiento y aspectos nutricionales de mayor importancia para el aumento de la masa muscular. Material y método: Se realizó una búsqueda bibliográfica en las bases de datos PubMed y Google Scholar usando los siguientes términos: “hypertrophy”, “skeletal muscle”, “strength” y “training”, y, por otro lado, “hypertrophy”, “skeletal muscle” y “nutrition”. Resultados: Tras aplicar las estrategias de búsqueda, se obtuvieron un total de 322 artículos sobre métodos de entrenamiento y 269 respecto a estrategias nutricionales. Tras la lectura de título y resumen se eliminaron 238 y 212 artículos respectivamente. Finalmente, se seleccionaron 26 artículos sobre métodos de entrenamiento y 11 sobre estrategias nutricionales, los cuales cumplieron los criterios de inclusión, y fueron incluidos en esta revisión. Conclusiones: Los resultados de este estudio sugieren la realización de un entrenamiento con cargas con las siguientes características: 3-5 series de 6-12 repeticiones realizadas en el rango de movimiento completo, con una intensidad cercana al fallo muscular (repeticiones en reserva de 0 a 2), con un volumen de entrenamiento semanal alto, y una frecuencia semanal de 3 días por grupo muscular, empleando varios ejercicios diferentes, combinando contracciones concéntricas y excéntricas, utilizando un foco atencional interno y con un descanso entre series de 2-3 minutos es el método más efectivo para el aumento de la masa muscular. Las estrategias nutricionales juegan un papel fundamental sobre el aumento de la masa muscular, siendo imprescindible un sobre aporte energético para que se produzca hipertrofia. Además, la ingesta de nutrientes como la proteína de suero de leche, la leucina y los ácidos grasos omega-3 favorecen la acreción proteica muscular. Palabras clave: Hipertrofia. Entrenamiento con cargas. Nutrición. Summary
Collaborative-AI: social robots accompanying and approaching people

Collaborative AI to approach or to accompany people using social robots will be a fundamental robotics ﬁeld in the near future. If we desire to share and to collaborate with social robots during the development of our daily task, social robots should be able to develop Collaborative AI task, such us accompanying or approaching people. In this article, we will present the robot-people accompaniment and approaching missions through the four levels of abstractions of Collaborative AI systems and describe the main Collaborative AI functionalities that are needed for these missions. We will also show the system that we have developed for accompany one or two pedestrians and approaching on person by a robot in an urban space.
ADVERSE REPRODUCTIVE HEALTH EFFECTS OF EXPOSURE TO CHLORINATION DISINFECTION BY PRODUCTS

Chlorination disinfection by-products (DBPs) are formed when water is chlorinated and the organic matter in the water reacts with chlorine to form these by-products. There have been concerns about the potential health effects of these by-products, including cancer and reproductive effects. Here we have reviewed the literature on reproductive health effects. Epidemiological studies on neural tube defects, urinary tract defects and small for gestation age/intra growth retardation have shown the most consistent statistically significant associations with an index of DBPs, but generally the risk estimates are small. The interpretation of the studies is not straight forward because they may not be directly comparable because of differences in DBP mixtures, exposure categories and actually uptake of DBPs due to differences in e.g. ingestion rates, showering, bathing, and swimming. Only few specific DBPs have been studied and THMs have often been used as a marker for other DBPs, since they are often routinely available. Sample sizes, and therefore power, have at times been low, particularly when the population was split into exposure categories. Although most studies considered some confounders, (residual) confounding by other water contaminants or other factors related to water intake, cannot always be excluded. Case ascertainment, for outcomes such as spontaneous abortion and certain congenital anomalies is far from straight forward, and for the latter at times anomalies are lumped together with different aetiology, which may be inappropriate. Furthermore, as with many reproductive epidemiological, if the putative agent affects both early pregnancy loss and later birth outcomes such as congenital anomalies, interpretation of later birth outcomes may be more difficult.
Impurity models and products of random matrices

This is an extended version of lectures given at the Summer School on Stochastic Processes and Random Matrices, held at the École de Physique, Les Houches, in July 2015. The aim is to introduce the reader to the theory of one-dimensional disordered systems and products of random matrices, confined to the 2×2 case. The notion of impurity model— that is, a system in which the interactions are highly localised— links the two themes and enables their study by elementary mathematical tools. After discussing the spectral theory of some impurity models, we state and illustrate Furstenberg’s theorem, which gives sufficient conditions for the exponential growth of a product of independent, identically-distributed matrices.
MASTER THESIS Analysis of kernel matrices and their relation to RVM performance

Kernel methods have played a major role in the last two decades in modelling and visualization of complex problems in data science. Their strong theoretical foundations, effectiveness and applicability both for supervised as well as unsupervised learning methods made them one of the most widely used machine learning techniques. These algorithms rely on mapping the data into a high-dimensional space and their main ingredient are kernel functions that allow to perform inner product computations in the feature space without explicitly evaluating the mapping into that space. However, kernel choice remains an open research area and the reasons why some kernel functions perform better for some problems than others are not yet understood. Moreover, high computational cost of kernel based methods makes it extremely inefficient to use standard model selection methods such as cross validation and creates a need for careful kernel design and parameter choice. These reasons justify prior analysis of kernel matrices, that is, mathematical objects generated by the kernel functions. This thesis explores these topics and tries to pinpoint desirable properties of kernel matrices that increase the likelihood of obtaining good model performance in terms of generalisation power, as well as relate these properties to the model’s fitting ability. Finally, it derives a heuristic for achieving close-to-optimal modelling results while keeping the computational cost low and thus provides a recipe for efficient analysis when processing resources are limited. Analysis of kernel matrices and their relation to RVM performance
Minimum Quantity Lubrication Turning of Ferrous Metals: —Measurement of tool temperature using fiber-coupled two-color pyrometer—

In this paper, the MQL turning of two types of ferrous metals: chromium-molybdenum steel SCM440H and pearlite malleable cast iron FCMP: are dealt with. In order to verify the cooling effect of MQL, the tool temperature at the flank face is measured using a newly assembled fiber-coupled two-color pyrometer. In the case of SCM440H, the tool temperature in MQL turning is approximately 100°C lower than that in dry turning. In the case of FCMP, the tool temperature in dry turning at a cutting speed of 600m/min reaches as much as about 1050°C, but it drops 930°C in MQL turning.
HEPARIN-BINDING GROWTH FACTOR ANALOGS

(63) Continuation of application No. 1 1/065,970, filed on Feb. 24, 2005, now Pat. No. 7,598.224, which is a continuation-in-part of application No. 1 1/064,039, filed on Feb. 22, 2005, now Pat. No. 7,482,427, which is a continuation-in-part of application No. 10/644.703, filed on Aug. 19, 2003, now Pat. No. 7,700.563, which is a continuation-in-part of application No. 10/224,268, filed on Aug. 20, 2002, now Pat. No. 7,166,574.
Renal Function in Patients with or without a Left Ventricular Assist Device Implant During Listing for a Heart Transplant

Background Left ventricular assist device (LVAD) implantation may improve kidney function, but in patients awaiting heart transplantation, the long-term effects of LVAD implantation on renal function and subsequent clinical outcome are unclear. Material/Methods We analyzed data in patients with LVAD implants (n=139) and without LVAD implants (n=1038) who were listed for a heart transplant at our institution between 2000 and 2019. The primary endpoint was an impairment in renal function (decrease of creatinine-based estimated glomerular filtration rate [eGFR] by ≥30%) up to a maximum of 2 years after listing. Secondary endpoints were chronic kidney disease stage 4 or 5, heart transplantation, survival during listing, and 1-year survival after transplantation. Results Values for eGFR increased after LVAD implantation (P=0.001) and were higher at the time of waitlisting in the LVAD group than in the non-LVAD group (P=0.002), but were similar between groups at the end of waitlisting (P=0.75). Two-year freedom from renal impairment was 50.6% and 66.7% in the LVAD and non-LVAD groups, respectively, with a multivariable-adjusted hazard ratio for the LVAD versus the non-LVAD group of 1.78 (95% confidence interval 1.19–2.68; P=0.005). Two-year freedom from chronic kidney disease stages 4–5 was similar between study groups (LVAD group: 83.5%; non-LVAD group: 80.1%; =0.50). The 2-year probability of transplantation was slightly lower in the LVAD group than in the non-LVAD group (50.0% and 55.8%, respectively, P=0.017). However, 2-year survival on the waiting list and 1-year survival after transplantation did not differ significantly between study groups (P-values >0.20). Conclusions Our data indicate a transient improvement in creatinine-based eGFR values by LVAD implantation without influencing survival.