Miracle-dz/UniFAR-FTUs huggingface dataset:
COMPARISON OF CASPOFUNGIN AND AMPHOTERICIN B FOR INVASIVE CANDIDIASIS

A BSTRACT Background Caspofungin is an echinocandin agent with fungicidal activity against candida species. We performed a double-blind trial to compare caspofungin with amphotericin B deoxycholate for the primary treatment of invasive candidiasis. Methods We enrolled patients who had clinical evidence of infection and a positive culture for candida species from blood or another site. Patients were stratified according to the severity of disease, as indicated by the Acute Physiology and Chronic Health Evaluation (APACHE II) score, and the presence or absence of neutropenia and were randomly assigned to receive either caspofungin or amphotericin B. The study was designed to compare the efficacy of caspofungin with that of amphotericin B in patients with invasive candidiasis and in a subgroup with candidemia. Results Of the 239 patients enrolled, 224 were included in the modified intention-to-treat analysis. Base-line characteristics, including the percentage of patients with neutropenia and the mean APACHE II score, were similar in the two treatment groups. A modified intention-to-treat analysis showed that the efficacy of caspofungin was similar to that of amphotericin B, with successful outcomes in 73.4 percent of the patients treated with caspofungin and in 61.7 percent of those treated with amphotericin B (difference after adjustment for APACHE II score and neutropenic status, 12.7 percentage points; 95.6 percent confidence interval, ¡0.7 to 26.0). An analysis of patients who met prespecified criteria for evaluation showed that caspofungin was superior, with a favorable response in 80.7 percent of patients, as compared with 64.9 percent of those who received amphotericin B (difference, 15.4 percentage points; 95.6 percent confidence interval, 1.1 to 29.7). Caspofungin was as effective as amphotericin B in patients who had candidemia, with a favorable response in 71.7 percent and 62.8 percent of patients, respectively (difference, 10.0 percentage points; 95.0 percent confidence interval, ¡4.5 to 24.5). There were significantly fewer drug-related adverse events in the caspofungin group than in the amphotericin B group. Conclusions Caspofungin is at least as effective as amphotericin B for the treatment of invasive candidiasis and, more specifically, candidemia. (N Engl J Med 2002;347:2020-9.)
Noise auralisation challenges in web and augmented reality applications

Auralisation of the machinery noise is becoming important with the development and availability of advanced noise modeling tools. With the auralisation, it is possible to enhance or replace the prototype or mock-up construction. For this purpose, we have developed real-time auralisation platforms for welding noise, engine noise and rock crushing station noise, among the others. The developed auralisation tools operate as stand-alone systems and also as web tools. Converting the stand-alone models to web applications is not a straightforward task, and several issues must be taken into an account. The other expansion path is to connect audible models to virtual or augmented reality environments. We simultaneously visualise and auralise 3D sound field of machinery noise with the combination of the audible model in a laptop computer and visualisation with a tablet PC. In this way we demonstrate the future of noise-related product prototyping and development.
Continuous time linear equalization based gigabit receiver for parallel interface

Modern processors are capable of working at a very high frequency with the advent of technology scaling. However, memory limits the overall speed of operation. In order to take complete advantage of these modern high-performance processors, it is essential to improve the data transfer rates in the memory. As per open NAND flash interface (ONFI) standard, the current data rate is around 800MBps. Between every successive ONFI standard, a 100% improvement in data rate has been observed. By extrapolating the existing trend, the data rate of next generation of ONFI can be about 1600MBps. This project aims at achieving 1333MBps to support an industrial need. Since the speed focused on Silicon is 1333MBps, the thesis strives to achieve 1400MBps in order to accommodate parasitics. At this high frequency, the channel response deteriorates because of dielectric loss and Inter-Symbol Interference (ISI). Additionally, crosstalk in parallel interface degrades the signal integrity. The technique used to restore the channel loss is called equalization. The thesis presents a design of Continuous Time Linear Equalization (CTLE) based gigabit receiver for ONFI parallel interface on 16nm FinFET technology. The design consists of a CTLE, a latch, a Current Mode Logic (CML) to Complementary MOSFET (CMOS) converter and a duty cycle corrector (DCC). A novel design has been proposed to support rail to rail Input Common Mode Range (ICMR) of the receiver to provide flexibility to the transmitter. This receiver compensates an estimated channel loss of 4dB at 1400MHz and provides a dc-gain of 10dB. Further, it maintains 50±1.5% duty cycle to support Double-Data-Rate(DDR) (2.8GbBs). For a given ICMR,a power efficiency of 1.4pJ/bit is achieved which is superior to the state-ofart designs. However, in order to support complete rail to rail ICMR the novel design was showing 4.7pJ/bit.
The Interactive Effect of Temperature and Salinity in the Nile Tilapia ( Oreochromis niloticus )

ii Dedication . iv Acknowledgements . v List of Tables . vii List of Figures . viii Chapter 1: Overview and Background . 1 Chapter 2: Flow cytometry analysis of the interactive effect of salinity and temperature on the cell cycle and apoptosis in Nile Tilapia, Oreochromis niloticus. 8 Figures & Tables for Chapter 2 . 23 Chapter 3: The interactive effect of salinity and temperature on p53, Gadd45 and Proliferating Cell Nuclear Antigen (PCNA) in Nile Tilapia, Oreochromis niloticus . 26 Figures & Tables for Chapter 3 . 40 Chapter 4: The response of CCAAT/enhancer binding protein-d (C/EBP-d) to salinity and temperature in Nile Tilapia, Oreochromis niloticus . 44 Figures & Tables for Chapter 4 . 54 Chapter 5: Conclusions and Future Directions . 55 References . 59
Analysis of Fatty Acid Composition and Healthy Lipids Indices in Raw and Processed Milk

The aim of the present study was to examine the fatty acid composition and healthy lipids indices in raw milk and dairy products, covering the main stages of production. The fresh cheese, butter, sour cream, and ultra-high temperature treated milk, representing differences in technological approach were chosen for the study. Fatty acids methyl esters were quantified using a gas chromatograph equipped with flame ionization detector and a capillary column SP-2560. No significant influence of the technological process has been identified. The concentrations and profile of fatty acids and healthy lipids indices in final product fat were primarily dependent on the content of the raw milk or cream. The significant difference (P<0.05) in main groups of fatty acids and healthy lipids indices were determined according to the season (except for sour cream). Summer raw milk and cream was a healthier option for the production of fresh cheese, ultra-high temperature milk, and butter.
Single Tooth Implant? a Systematic review

Should a tooth with pulpal involvement be saved through endodontic therapy, or extracted and replaced with a single tooth implant? Within the limitations of the existing literature, this systematic review of treatment outcomes found that initial endodontic treatment had a high long-term survival rate, equivalent to replacement of a missing tooth with an implant-supported restoration. Single tooth implants should be considered as the first treatment option for patients requiring extraction and tooth replacement.
Facing High EEG Signals Variability during Classification Using Fractal Dimension and Different Cutoff Frequencies

In the development of a brain-computer interface (BCI), some issues should be regarded in order to improve its reliability and performance. Perhaps, one of the most challenging issues is related to the high variability of the brain signals, which directly impacts the accuracy of the classification. In this sense, novel feature extraction techniques should be explored in order to select those able to face this variability. Furthermore, to improve the performance of the selected feature extraction technique, the parameters of the filter applied in the preprocessing stage need to be properly selected. Then, this work presents an analysis of the robustness of the fractal dimension as feature extraction technique under high variability of the EEG signals, particularly when the training data are recorded one day and the testing data are obtained on a different day. The results are compared with those obtained by an autoregressive model, which is a technique commonly used in BCI applications. Also, the effect of properly selecting the cutoff frequencies of the filter in the preprocessing stage is evaluated. This research is supported by several experiments carried out using a public data set from the BCI international competition, specifically data set 2a from BCIIC IV, related to motor tasks. By a statistical test, it is demonstrated that the performance achieved using the fractal dimension is significantly better than that reached by the AR model. Also, it is demonstrated that the selection of the appropriate cutoff frequencies improves significantly the performance in the classification. The increase rate is approximately of 17%.
Offline handwritten pre-segmented character recognition of Gurmukhi script

In this paper, we have proposed a feature extraction technique for recognition of segmented handwritten characters of Gurmukhi script. The experiments have been performed with 7000 specimens of segmented offline handwritten Gurmukhi characters collected from 200 different writers. We have considered the set of 35 basic characters of the Gurmukhi script and have proposed the feature extraction technique based on boundary extents of the character image. PCA based feature selection technique has also been implemented in this work to reduce the dimension of data. We have used k-NN, SVM and MLP classifiers. SVM has been used with four different kernels. In this work, we have achieved maximum recognition accuracy of 93.8% for the 35-class problem when SVM with RBF kernel and 5-fold cross validation technique were employed.
A Compact Minimally Invasive Antenna for OTA Testing

This letter presents a compact dual-polarized over-the-air testing antenna with low radar cross section (RCS) for the fifth-generation and emerging wireless communication systems. The proposed antenna design is achieved by slotting two orthogonal Vivaldi antennas in a cross-shaped form into a two-part three-dimensional printed radome and loading microwave-absorbing materials (MAMs) at the antenna's outer edges. The proposed antenna has a rocket-nest shape with a diameter of 63.4 and 113.68 mm length. The −10 dB impedance bandwidth (S11) is obtained from a range of 2.1 up to 6 GHz. The two-part radome is formed by polylactic acid and acrylonitrile butadiene styrene dielectric materials, respectively. Their respective dielectric constants are approximately 2.6 and 4.5 within the −10 dB impedance bandwidth. The MAMs geometry and distribution location are optimized to suppress induced current over the antenna. An antenna prototype has been fabricated and measured. The measured results agree reasonably well with the simulated results. The results show that the use of the two-part radome enables the achievement of low RCS with compact form factor. Furthermore, a low bistatic RCS of between 2 and 6 GHz is observed in simulation for angular ranges of ${{\boldsymbol \theta }} \in [ { - {\text{30}^\circ }, + {\text{30}^\circ }} ]$ and $\boldsymbol{\Phi } \in [ { - {\text{90}^\circ }, + {\text{90}^\circ }} ]$.
Improving the efficiency and selectivity of Cd2+ removal using a modified resin in the continuous electropermutation process

ABSTRACT This study was undertaken to enhance the selectivity and the removal efficiency of Cd2+ from a mixture solution containing Cd2+ and Na+ using continuous electropermutation (EP) with alginate-modified resin (MR). The surface of the MR was characterized via scanning electron microscopy and Fourier transform infrared. The use of the MR in EP process has improved the efficiency and the selectivity for Cd2+ removal from Cd2+ (88, 46%), Na+ (81, 41%) to Cd2+ (96, 98%), Na+ (51, 47%). The effect of current density and concentration of the electro-regeneration electrolyte on the Cd2+ removal efficiency was investigated. Abbreviations AEM, anion-exchange membrane; AG, alginate; CEM, cation-exchange membrane; DS, desorption solution; DVB, divinylbenzene; EDI, electrodeionization; ED, electrodialysis; EP, electropermutation; ERE, electroregeneration electrolyte; FTIR, Fourier transforms infrared; IER, ion-exchange resins; LG, glucuronic acid; MR, modified resin; SEM, scanning electron microscopic; UMR, unmodified resin; DM, D-mannuronic.
Wearable Biofeedback Suit to Promote and Monitor Aquatic Exercises: A Feasibility Study

Aquatic exercises have been demonstrated to benefit the facilitation of motor recovery and the enhancement of well-being in middle-aged adults and the elderly. Personalization, immersiveness, and biofeedback are key for amplifying and accelerating any rehabilitation process in neurological and orthopedic patients. However, a therapist can neither properly visualize nor monitor rehabilitation exercises executed under water, nor can he/she measure them. Therefore, this paper aims to provide adaptive biofeedback during aquatic exercises in order to enhance the training’s effectiveness. A wearable biofeedback suit equipped with wearable underwater-resistant sensor nodes has been designed, produced, and tested. A dedicated algorithm for quantitatively extracting joint angles has been developed and validated against the optical tracking system. Multiple biofeedback modalities are proposed based on visual feedback: amplitude control with set target angles; velocity-amplitude control with set target angles and angular velocity; and velocity tutor with set target angles, a frequency value, and a rest period. Joint angles estimated using the sensor network are compared to those estimated using an optical tracking system with the root-mean-squared angle error between the two systems ranging from 4.0° to 6.3° and a significant correlation coefficient that is always greater than 0.99. Pilot tests during aquatic exercises executed in a thermal environment demonstrate the feasibility and usability of the complete system in the final working environment. The relevant angles are correctly calculated and monitored online during the exercises, and the tested subjects understand the implemented biofeedback modalities easily and follow them well as the SUS evaluation indicates.
Psychoanalysis And The Aesthetic Dimension: Commentary On Lisa Cataldo’s “Where God Is Between Us”

In inviting this contemplation on spirituality and psychoanalysis, Cataldo highlights two interrelated questions: how we face the unknown and how, in spite of that fear, we sustain respect for the otherness of the other. Cataldo’s language is couched in the terms of relational psychoanalysis, whereas my own perspective is drawn from object relations theories, with salient metaphors from Bion and Lacan. Bion suggested that bi-nocular vision, seeing through more than one lens, was an important tool for learning. I hope that adding my own lenses will further illuminate the field she has so richly developed.
Building a Computer Poker Agent with Emphasis on Opponent Modeling

In this thesis, we present a computer agent for the game of no-limit Texas Hold'em Poker for two players. Poker is a partially observable, stochastic, multi-agent, sequential game. This combination of characteristics makes it a very challenging game to master for both human and computer players. We explore this problem from an opponent modeling perspective, using data mining to build a database of player styles that allows our agent to quickly model the strategy of any new opponent. The opponent model is then used to develop a robust counter strategy. A simpler version of this agent modified for a three player game was able to win the 2011 MIT Poker Bot Competition. Thesis Supervisor: Leslie P. Kaelbling Title: Professor of Computer Science and Engineering
® and the effect on heat stress in dairy cows

One of the great challenges that the dairy industry faces, especially during the summer month, is heat stress. Increase in temperature, together with an increase in humidity, results in a decrease in milk production, feed intake, feed efficiency and even reduced growth rate in heifers (West, 1999). Reproduction and health are also negatively affected by heat stress (St Pierre et al., 2003). Different management systems are used to reduce the effect of heat stress on dairy cows, for example, fans with water sprayers or dairy cow housing (shading). However, not all dairies are able to implement these kind of management systems, and even with these, cows still experience a certain amount of heat stress, depending on the environment.
Changing Perceptions of Pre-Service Educators through Service-Learning.

: Despite the worldwide increasing prevalence of students with disabilities (SWD) in the general education environment, pre-service educators (PSE) are still reporting negative attitudes before and after taking coursework regarding SWD. Service-learning may be one method for improving the perceptions of PSEs towards SWD. Prior research has not investigated service-learning for PSE with SWD using change and transformative theory to understand changes. The purpose of this mixed methods study was to determine whether a service-learning activity positively influences PSE perceptions regarding the inclusion of SWD in the general education environment using a modified sentiments, attitudes, and concerns protocol. Results indicate that PSEs can positively change their perceptions concerning SWD in their future classrooms.
Adaptive Antennas and Mimo Systems for Wireless Communications

Multiple-antenna systems, denoted multipleinput multiple-output systems, promise huge performance gains over conventional singleantenna systems. Many MIMO transmission schemes proposed in the literature are, however, based on idealized assumptions. Several effects that may occur in a practical system, such as intersymbol interference, nonperfect channel knowledge, fast fading, and correlation between the individual transmission paths, significantly influence system performance. On the basis of two particularly simple but nonetheless efficient MIMO transmission schemes, the above effects are illustrated, and possible countermeasures are discussed. Boosting the Performance of Wireless Communication Systems: Theory and Practice of Multiple-Antenna Techniques
A Label Noise Robust Stacked Auto-Encoder Algorithm for Inaccurate Supervised Classification Problems

In real applications, label noise and feature noise are two main noise sources. Similar to feature noise, label noise imposes great detriment on training classification models. Motivated by successful application of deep learning method in normal classification problems, this paper proposes a new framework called LNC-SDAE to handle those datasets corrupted with label noise, or so-called inaccurate supervision problems. The LNC-SDAE framework contains a preliminary label noise cleansing part and a stacked denoising auto-encoder. In preliminary label noise cleansing part, the K-fold cross-validation thought is applied for detecting and relabeling those mislabeled samples. After being preprocessed by label noise cleansing part, the cleansed training dataset is then input into the stacked denoising auto-encoder to learn robust representation for classification. A corrupted UCI standard dataset and a corrupted real industrial dataset are used for test, both of which contain a certain proportion of label noise (the ratio changes from 0% to 30%). The experiment results prove the effectiveness of LNC-SDAE, the representation learnt by which is shown robust.
Forecasting the Direction of Agricultural Commodity Price Index through ANN, SVM and Decision Tree: Evidence from Raisin

tahminlenmesi ekonomik aktorlere dogru alim satim kararlari verebilmeleri icin fayda saglamaktadir. Turkiye’deki ticaret borsalarinda islem goren tarimsal urunlerden biri olan kuru uzum fiyatlarinin oynak degiskenler kullanilarak tahminlenmesinin incelendigi calismada uc temel soru uzerinde durulmustur. Ic karisikligin yuksek oldugu ulkelerde sosyal ve politik olaylar kuru uzum fiyatlarini etkiler mi? Oynakligi yuksek olan degiskenler kullanilarak kuru uzum fiyat endeksleri tahminlenebilir mi? Son olarak, bu tip bir calismada Yapay Sinir Aglari (YSA), Karar Agaci ve Destek Vektor Makineleri (DVM) yontemlerinden hangisinin tahmin performansi daha yuksektir? Bu amacla olusturulan tahmin modeline YSA, KA ve DVM yontemleri uygulanmis ve yontemlerin tahmin performanslari karsilastirilmistir. Uygulama sonuclari, oynak degiskenler ile sosyal ve politik olaylarin kuru uzum fiyatlarinin tahminlenmesinde kullanilabilecegini ve ilgili modelde DVM yonteminin en yuksek dogruluk oranini verdigini gostermistir.
Is telomere shortening reversible? A clue from NASA's Twin study.

There have been a number of human space programs conducted in order to study the environmental effects on human body. NASA’s recent twin study reveals a plethora of such changes in a long space mission. This study has provided an important clue about reversing of the telomere shortening. Such studies can provide us a better understanding of the effects of environment and space on human health.
Multiple Sequence Alignment Optimization Using Meta-Heuristic Techniques

Sequence alignment is a vital process in many biological applications such as Phylogenetic trees construction, DNA fragment assembly and structure/function prediction. Two kinds of alignment are pairwise alignment which align two sequences and Multiple Sequence alignment (MSA) that align sequences more than two. The accurate method of alignment is based on Dynamic Programming (DP) approach which suffering from increasing time exponentially with increasing the length and the number of the aligned sequences. Stochastic or meta-heuristics techniques speed up alignment algorithm but with near optimal alignment accuracy not as that of DP. Hence, This chapter aims to review the recent development of MSA using meta-heuristics algorithms. In addition, two recent techniques are focused in more deep: the first is Fragmented protein sequence alignment using two-layer particle swarm optimization (FTLPSO). The second is Multiple sequence alignment using multi-objective based bacterial foraging optimization algorithm (MO-BFO).