Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimum GaN HEMT Oscillator Design Targeting Low Phase Noise

The thesis considers design of low phase noise oscillators, given the boundary condition of the used technology. Important conditions are the power handling of the active device, device noise floor, the quality factor of the resonator, bias settings, and low frequency noise. A particular focus in this study is optimization of the coupling factor between the resonator and the active device, which is the factor that is most easy to influence for a circuit designer. Resonators have to be well matched to the active device to ensure a good performance. As a measure on oscillator design efficiency, the thesis uses an effective noise figure that is compensated for the unloaded quality factor (Q0) of the resonator and the power consumption of the active device. The active device technology in this study is a 0.25 um GaN-HEMT process. All designs are based on a device with 400 um gate periphery that is processed either as a single-die HEMT assembled in a hybrid solution discrete on PCB, or in a MMIC-implementation with the amplifying part, or the complete oscillator on chip. Low-frequency-noise (LFN) measurements are performed and benchmarked versus other GaN HEMT devices as well as InGaP HBT and GaAs HEMT. It is found that the used device presents relatively low noise in comparison to other GaN HEMTs. It is also found that power-normalized far carrier noise, e.g., @100 kHz is comparable to levels in InGaP HBT devices. Three oscillators, based on similar reflection amplifiers but different resonators, are designed. The three resonators are: an external discrete LC-resonator with Q0≈49, a quasilumped on-chip MMIC resonator, Q0≈40, and an external metal cavity, Q0≈3800. For each resonator, the impedance level is chosen to match the active device. The fabricated oscillator test beds are made flexible so that the small-signal open loop gain can be experimentally tuned. It is demonstrated that the best phase noise is reached for a smallsignal open-loop gain close to unity. A too high gain margin is normally bad from a phase noise perspective. The discrete hybrid oscillator presents a phase noise of -123 dBc/Hz@100 kHz from a 1 GHz oscillation frequency; the MMIC oscillator presents a phase noise of -106 dBc/Hz@100 kHz from a 15 GHz oscillation frequency; and the cavity based oscillator presents an excellent phase noise of -145 dBc/Hz@100 kHz from a 10 GHz oscillation frequency. Normalizing these results versus Q0 and DC-power, results in effective noise figures of 16-22 dB. The effective noise figure is identified to originate primarily in finite DC to RF power efficiency and up-converted flicker noise.
DECCO: Deep-Learning Enabled Coverage and Capacity Optimization for Massive MIMO Systems

System capacity and service coverage are the most critical performance metrics in cellular wireless communication networks. Usually, system capacity enhancements are at the expense of service coverage degradations, and vice versa. This capacity-coverage tradeoff and the associated joint optimization problem becomes very challenging in massive multiple-input multiple-output (MIMO) wireless systems, due to a large amount of antenna tilt values to be configured and very sophisticated inter-cell interference conditions, under massive antenna scenarios. This paper proposes a novel approach, namely group alignment of user signal strength (GAUSS), to efficiently support the user scheduling for the massive MIMO system, and thus serve as an effective parameter for the coverage and capacity optimization (CCO) problem. Together with a unified threshold of Quality of Service, i.e. the minimum signal-to-interference-plus-noise ratio ( $\textit {SINR}_{min}$ ) for user satisfaction, GAUSS can effectively control the variance of signal strengths of multiple users in the neighborhood. Moreover, an intelligent and efficient deep-learning enabled coverage and capacity optimization (DECCO) algorithm is proposed and evaluated, which adopts a pre-trained deep policy gradient-based neural network to dynamically derive GAUSS and $\textit {SINR}_{min}$ during CCO. Furthermore, an inter-cell interference coordination (ICIC) is proposed to enhance the CCO performance. Analytical and simulation results show that the proposed DECCO algorithm can effectively achieve a much better performance balance between system capacity and service coverage than traditional fixed optimization (FO) and proportional fair optimization (PFO) algorithms. Specifically, DECCO significantly increases the overall spectrum efficiency by 24% and 40%, respectively, than FO and PFO in a typical massive MIMO system.
Predictive factors associated with mortality and discharge in intensive care units: a retrospective cohort study

Background and aim Accurate prediction of prognosis of patients admitted to intensive care units (ICUs) is very important for the clinical management of the patients. The present study aims to identify independent factors affecting death and discharge in ICUs using competing risk modeling. Methods This retrospective cohort study was conducted on enrolling 880 patients admitted to emergency ICU in Namazi hospital, Shiraz University of Medical Sciences, Shiraz, Iran during 2013–2015. The data was collected from patients’ medical records using a researcher-made checklist by a trained nurse. Competing risk regression models were fitted for the factors affecting the occurrence of death and discharge in ICU. Data analysis was conducted using STATA 13 and R 3.3. 3 software. Results Among these patients, 682 (77.5%) were discharged and 157 (17.8%) died in the ICU. The patients’ mean ± SD age was 48.90±19.52 yr. Among the study patients, 45.57% were female and 54.43% were male. In the competing risk model, age (Sub-distribution Hazard Ratio (SHR)) =1.02, 95% CI: 1.007–1.032), maximum heart rate (SHR=1.009, 95% CI: 1.001–1.019), minimum sodium level (SHR=1.035, 95% CI: 1.007–1.064), PH (SHR=7.982, 95% CI: 1.259–50.61), and bilirubin (SHR=1.046, 95% CI: 1.015–1.078) increased the risk of death, while maximum sodium level (SHR=0.946, 95% CI: 0.908–0.986) and maximum HCT (SHR=0.938, 95% CI: 0.882–0.998) reduced the risk of death. Conclusion In conclusion, the results of this study revealed several variables that were effective in ICU length of stay (LOS). The variables that independently influenced time-to-discharge were age, maximum systolic blood pressure, minimum HCT, maximum WBC, and urine output, maximum HCT and Glasgow coma score. The results also showed that age, maximum heart rate, maximum sodium level, PH, urine output, and bilirubin, minimum sodium level and maximum HCT were the predictors of death. Furthermore, our findings indicated that the competing risk model was more appropriate than the Cox model in evaluating the predictive factors associated with the occurrence of death and discharge in patients hospitalized in ICUs. Hence, this model could play an important role in managers’ and clinicians’ decision-making and improvement of the standard of care in ICUs.
Fast and automatic security test on cryptographic ICs against fault injection attacks based on design for security test

Fault injection attacks have constituted a serious threat against cryptographic integrated circuits (ICs). However, the security test nowadays is just sample test with workload statistics and experiences as the qualitative criterion, and results in costly, time-consuming and error-prone test procedures. This study presents a design for security test (DFST) method for cryptographic ICs against fault injection attacks. The DFST involves identifying the sensitive registers for various crypto modules, inserting the scan chains and generating the specific test patterns for security test. Then the security test is conducted on the manufactured cryptographic ICs with the industrial automatic test equipment. With this DFST method, a fast and automatic security test can be applied onto volume production of cryptographic ICs. Experimental results on an RSA implementation demonstrate the validity of this method.
The Morpho-syntactic Annotation of Animacy for a Dependency Parser

In this paper we present the annotation scheme and parser results of the animacy feature in Russian and Arabic, two morphologically-rich languages, in the spirit of the universal dependency framework (McDonald et al., 2013; de Marneffe et al., 2014). We explain the animacy hierarchies in both languages and make the case for the existence of ﬁve animacy types. We train a morphological analyzer on the annotated data and the results show a prediction f-measure for animacy of 95.39% for Russian and 92.71% for Arabic. We also use animacy along with other morphological tags as features to train a dependency parser, and the results show a slight improvement gained from animacy. We compare the impact of animacy on improving the dependency parser to other features found in nouns, namely, ‘gender’, ‘number’, and ‘case’. To our knowledge this is the ﬁrst contrastive study of the impact of morphological features on the accuracy of a transition parser. A portion of our data (1,000 sentences for Arabic and Russian each, along with other languages) annotated according to the scheme described in this paper is made publicly available ( https://lindat.mff.cuni.cz/repository/xmlui/handle/11234/1-1983 ) as part of the CoNLL 2017 Shared Task on Multilingual Parsing (Zeman et al., 2017).
Inactivated Trivalent Vaccine for Leptospira in Andhra Pradesh

Leptopsirosis, the world wide zoonosis is considered as re-emerging disease. Besides economic losses caused by Leptopsira to animal production, its zoonotic character makes it an important public health problem Seroepidemiological studies conducted using MAT indicated the dominance of L.hardjo, L.grripotyposa and L. autumnalis in the state. Hence, serovars hardjo, grripotyposa and autumnalis were selected as vaccine candidates for the preparation of trivalent vaccine. The homology and purity of the vaccine candidates were checked using reference antisera procured from ICMR, Port Blair, Center for Diagnosis and typing of leptospira, Andaman and Nicobar Islands and also using hyper immune sera raised against the respective serovars in the present study. The candidate vaccine strains were adopted to low protein medium containing 0.2 percent Bovine serum albumin (BSA) and adjusted the concentration to 2x10 cells/ml. The leptospiral organisms were inactivated with 0.5 percent formalin and adjuvanted with aluminum hydroxide (vaccine-I and Montanide (vaccine-II). The vaccines prepared were evaluated for sterility, safety and potency tests. The immune responses were studied in rabbits using both the types of adjuvanted vaccines and could not find any significant differences between the vaccines. The immune response was found to be satisfactory with both the types of vaccines up to 150 days of post vaccinated period tested. The present work has been carried out during 2006 to 2010.
Simultaneous Nash Equilibrium Seeking and Social Cost Minimization in Graphical $N$-coalition Non-cooperative Games

This paper aims to reduce the communication and computation costs of the Nash equilibrium seeking strategy for the $N$-coalition non-cooperative games proposed in [YEAT]. The objective is achieved in two manners: 1). the Nash equilibrium seeking strategy is re-designed and a new Nash equilibrium seeking algorithm that yields less communication and computation costs, is proposed. 2). an interference graph is introduced to describe the interactions among the agents in each coalition. The newly proposed seeking strategy is then adapted for the $N$-coalition non-cooperative games on the interference graph. A sufficient condition on the interference and communication graphs is provided to ensure that the players' actions converge to the Nash equilibrium by utilizing the proposed seeking strategy. Several special cases where there is only one coalition and/or there are coalitions with only one agent are considered. The results for the special cases demonstrate that the proposed seeking strategy achieves the solution seeking for non-cooperative games, social cost minimization problems and single-agent optimization problems in a unified framework. Numerical examples are presented to support the analytical results.
Mindfulness-Based Smoking Cessation Enhanced With Mobile Technology (iQuit Mindfully): Pilot Randomized Controlled Trial

Background Mindfulness training shows promise for improving smoking cessation and lapse recovery, and between-session mobile health messages could enhance treatment engagement and effectiveness. Personalized, in-the-moment text messaging support could be particularly useful for low-income smokers with fewer smoking cessation resources. Objective This pilot study examined the feasibility of a text messaging program (iQuit Mindfully) as an adjunct to in-person Mindfulness-Based Addiction Treatment (MBAT) for smoking cessation. Methods A total of 71 participants were randomly assigned to MBAT (n=33) or iQuit Mindfully (n=38; MBAT + between-session text messages); of these, 70% (50/71) were African American, and 61% (43/71) had an annual household income of US $30,000 or less. All participants received 8 weekly therapist-led group counseling sessions, nicotine patches, and self-help materials. Outcomes were feasibility (attrition, engagement, and participants’ ratings), participants’ feedback regarding the text messaging intervention, and smoking cessation (assessed in person). Results Strong retention was achieved (76% [54/71] at the end of treatment, and 89% [63/71] at 1-month follow-up). In the iQuit Mindfully group, engagement was high (88% [29/33] indicated reading all or most texts, and 89% [34/38] engaged in interactive texting), and participants provided positive ratings (on a 1-10 scale, average rating for recommending the program to others was 8.4 [SD 2.5]). Participants indicated benefiting from the texts (eg, appreciating encouraging reminders, coping strategies, and social support) and suggested improvements (eg, more personalization). Overall, biochemically confirmed smoking cessation rates were 22% (12/55) at the end of treatment and 19% (12/62) at 1-month follow-up, with no differences between conditions. Living below the poverty level predicted worse cessation outcomes at 1-month follow-up among participants receiving in-person only treatment (P=.03) but not among those receiving iQuit Mindfully. Conclusions Text messaging appears to be a feasible and acceptable modality for supporting mindfulness-based smoking cessation treatment. The availability of 24/7 text messaging might be particularly helpful for low-income smokers who have access to fewer cessation resources and experience significant day-to-day barriers to quitting. Trial Registration ClinicalTrials.gov NCT03029819; https://clinicaltrials.gov/ct2/show/NCT03029819
Three-Way Street: Strategic Reciprocity in World Politics

How can the world's most powerful nations cooperate despite their conflicting interests? In "Three-Way Street," Joshua S. Goldstein and John R. Freeman analyze the complex intersection defined by relations among the United States, the Soviet Union, and China over the past forty years. The authors demonstrate that three major schools of international relations theory all game-theoretic, psychological, and quantitative-empirical approaches have all advocated a strategy that employs cooperative initiatives and reciprocal responses in order to elicit cooperation from other countries. Critics have questioned whether such approaches can model how countries actually behave, but Goldstein and Freeman provide a wealth of detailed empirical evidence showing the existence and effectiveness of strategic reciprocity among the three countries between 1948 and 1989. Specifically, they establish that relations among the three countries have improved in recent decades through a "two steps forward, one step back" pattern. Their innovative and remarkably accessible synthesis of leading theoretical perspectives brilliantly illuminates the nature and workings of international cooperation. "
Features Analysis of Online Shopping System Using WCM

Data mining techniques being used for web information extraction are unbelievable systems and suggested for the protection of extremely susceptible data. By the web sources huge amount of data is maintained and can be easily retrieved by using the web mining techniques as the techniques are applied exactly based on the needs of the users. ECommerce and online shopping noticed a huge growth in business industry. This facility has been mostly employed in western countries during the last two decades. In east online shopping is increasing as most of the business is running through web site as well as in west. This business can be boost by feature analysis of different successful running online web stores. This study is going to present analysis of different features of successful online business website and of those which are not that much popular and accessed infrequently, their features will be extracted and compared to get the reasons of popularity of frequently accessed online shopping websites and after that recommendations will be made to increase the traffic of unpopular online shopping websites to dominate online business in Pakistan. According to the presented work it has been concluded that unpopular websites lack some features that are included in popular websites such as brands, as people are more conscious about brands and labels so they visit and shop from the websites which offer them best quality famous brands, moreover it has been observed that unpopular websites have less categories they must broaden their variety of products especially related to sports, fitness, bathroom accessories, technology and cosmetics. Apart from these another interesting fact that has been found is that popular websites mostly attract their customers by giving them offers such as buy one get one free, free home delivery and free gifts, such offers are always attracting new and more customers. Unpopular websites can improve their business by including the features discussed above. The results of research on this dataset also show that the Naïve bayes is better than j48 in terms of efficiency and accuracy respectively.
Molecular testing in holoprosencephaly

Holoprosencephaly (HPE) is a structural brain anomaly characterized by failure of the forebrain to separate during early embryogenesis. Both genetic and environmental etiologies of HPE have been discovered over the last three decades. Traditionally, the genetic workup for HPE has been a karyotype, chromosomal microarray, and/or Sanger sequencing of select genes. The recent increased availability of next‐generation sequencing has changed the molecular diagnostic landscape for HPE, associating new genes with this disorder such as FGFR1. We conducted a systematic review of the medical literature for the molecular testing of HPE for studies published in the last 20 years. We also queried known commercial diagnostic laboratories and used information on their websites to construct a list of available commercial testing. Our group released its first recommendations in 2010 and this update incorporates the technology shifts and gene discoveries over the last decade. These recommendations provide a guide for genetic diagnosis of HPE, which is paramount for patients and their families for prognosis, treatment, and genetic counseling.
The Analysis of Relationship between the Rate of Stock Return and Interest Rate with Nonlinear Methods: The Case of Turkey

In this study, it was analyzed the structure of stationary of Istanbul Stock Exchange return rate and interest rate series and whether it’s are linear in the period of 1986:01-2012:07. It was used linearity and unit root tests developed by Caner and Hansen (2002). As a result of these tests, it was concluded that the series are non-linear and both of series have two regimes. Besides, it was concluded that both of two regimes have unit root in the series of interest rate and first regime has stationary, second regime has also unit root in Istanbul Stock Exchange return rate series. Finally, the model in which Istanbul Stock Exchange is dependent variable, interest rate is explanatory variable was analyzed whether there is a co integration with Hansen-Seo (2002) test. As a result of analysis it was determined the co integration relationship between the interest rate and Istanbul Stock Exchange return rate.
Group 47 Twitter Political Influence - Presidential Election 2012

With the growing use of online social media, it’s use in politics is starting to become extremely important. Analysis of the wealth of data contained in these online social networks can be used to gather more data about people’s political leanings than ever before. In this paper, we analyze the spread of information during the 2012 presidential election to determine the most important topics to the US population. We want to be able to determine which political issue has larger outbreaks during the political campaigns and is thus more important in determining the presidential election. Ranking the importance of political issues to the US population will reveal how to better maximize a political campaign and possibly predict election results. Gathering twitter data on 8 different topics from the most recent presidential election we analyze what the data can tell us, and how it may possibly be used. We see that by measuring the number of mentions of specific topics we can accurately match the top issues identified in the independent research polls. We also identify the size of the graphs for all political issues as following a power law distribution. We then perform some sentiment analysis and show that the public’s opinion on a candidates issues can be analyzed from the tweets gathered. Finally we show that using the temporal data associated with all of the tweets we can see trends that demonstrate peaks of interest in the campaign, and could possibly be used to help predict the outcome of elections.
Ethic vs. Business, Religion vs. Task

There are issues that are still taboo and displaying them in other than normal situations and stereotypes appears to be controversial. This research study deals with ethics in advertising with a focus on displaying religious symbols in controversial advertising campaigns. Religious motifs are often used with the intent to shock and creators often insensitive cross borders of decency with the intention to provoke, to be different, assume, or sell. The main aim of this research study is to highlight attitudes of advertising agencies toward to clients briefs with ideas or task balanced at the edge of ethics, contracting controversial or inflammatory advertising messages, analyse approaches creators of advertising campaigns and to identify barriers to the acceptance of the sensitivity of these briefs. Research sample includes 7 pre- selected advertising agencies whose representatives on various job positions through copywriters, account managers, executive staff, PR managers, marketing managers responded to the interview questions relating to the processing of sensitive subjects and religious themes in advertising or PR. This study points out the results of the research from the side of advertising creators who have to adapt to issues such as display religious themes in marketing communications. The research points what is in term of controversial or sensitive issue still acceptable and what they do not want to allow to regulate similar topics. We find if the values and principles of creators can affect the final form of advertising or PR article that gets to the public. Research was conducted via online interviews. Via e-mail we sent out 9 questions about the attitude of creators to ethics, personal values and the use of Christian themes in advertising. The selection criteria were that the worker has to work directly on advertising content according to the clients brief and he or she has to have at least 3 years practice in this area. Index Terms - religious themes and motives; ad creators; values and opinions