Miracle-dz/UniFAR-FTUs huggingface dataset:
Geographical Variations in the Clinical Management of Colorectal Cancer in Australia: A Systematic Review

Background In Australia, cancer survival is significantly lower in non-metropolitan compared to metropolitan areas. Our objective was to evaluate the evidence on geographical variations in the clinical management and treatment of colorectal cancer (CRC). Methods A systematic review of published and gray literature was conducted. Five databases (CINAHL, PubMed, Embase, ProQuest, and Informit) were searched for articles published in English from 1990 to 2018. Studies were included if they assessed differences in clinical management according to geographical location; focused on CRC patients; and were conducted in Australia. Included studies were critically appraised using a modified Newcastle–Ottawa Scale. PRISMA systematic review reporting methods were applied. Results 17 articles met inclusion criteria. All were of high (53%) or moderate (47%) quality. The evidence available may suggest that patients in non-metropolitan areas are more likely to experience delays in surgery and are less likely to receive chemotherapy for stage III colon cancer and adjuvant radiotherapy for rectal cancer. Conclusion The present review found limited information on clinical management across geographic regions in Australia and the synthesis highlights significant issues both for data collection and reporting at the population level, and for future research in the area of geographic variation. Where geographical disparities exist, these may be due to a combination of patient and system factors reflective of location. It is recommended that population-level data regarding clinical management of CRC be routinely collected to better understand geographical variations and inform future guidelines and policy.
Provisioning of 5 G Services Employing Machine Learning Techniques

This study proposes a modeling framework for optimal online 5G service provisioning, based on low computational complexity machine learning techniques such as Neural Network (NNs). NNs are trained to take optimal decisions adopting an offline Integer Liner Programming (ILP) model. This framework is used to solve the generic joint Fronthaul (FH) and Backhaul (BH) service provisioning problem over a converged high capacity and flexibility optical transport aiming at minimizing the overall energy consumption of the 5G infrastructure. Our modeling results indicate that the proposed approach adopting NN based real time service provisioning can provide very similar performance to the one derived adopting the high complexity but accurate ILP approach. Index Terms Machine Learning, Optimization, 5G, ILP, LSTM, MLP, optical transport.
Competitive Gains in Business Cooperation Networks in the State of Goiás

This research aims to study the competitive gains of some Business Cooperation Network (BCN) selected, in the State of Goias. This study aims to broaden the understanding of earnings and benefits provided by them. This research is characterized as qualitative and exploratory nature, and the method adopted for its implementation is the study of multiple cases. Three BCNs were analyzed in the State of Goias As a result, between competitive gains identified in the studied BCNs, are: bargaining power, market power, prospecting opportunities, shared activities, complementarity, transactional ease, new products and services.
The blockage mitigation in the link of SATCOM-on-the-move based on LT code

Luby Transform (LT) code is applied in satellite communications-on-the-move (SOTM) system to combat the blockage of the link to satellite. A mixed-blockage channel model combining traditional hard and soft blockage is proposed, over which the performance of LT code is compared with that of the fixed-rate LDPC code. Simulations results demonstrate that the former code is more robust than the later code for the SOTM system, which may experience great variety of channel conditions such as signal-to-noise ratio and the probability of blockage.
Global tracking passivity-based PI control for power converters: An application to the boost and modular multilevel converters

This paper deals with the problem of trajectory tracking of a class of power converters. To analyze the stability of these systems we consider the bilinear structure they admit. First, we propose the theoretical framework for which it is possible to ensure global tracking of trajectories. To do so, a construction of an output signal respect to which the incremental model becomes passive is carried out. This leads to a simple linear PI controller for the plant. Then, we apply this result in a realistic simulation for two well-known converters systems: the boost and the modular multilevel converter (MMC).
Replication of an Experimental Study Investigating the Efficacy of a Multisyllabic Word Reading Intervention With and Without Motivational Beliefs Training for Struggling Readers

This randomized control trial examined the efficacy of an intervention aimed at improving multisyllabic word reading (MWR) skills among fourth- and fifth-grade struggling readers (n = 109, 48.6% male), as well as the relative effects of an embedded motivational beliefs training component. This study was a closely aligned replication of our earlier work. The intervention was replicated with a three-condition design: MWR only, MWR with a motivational beliefs component, and business-as-usual control. Students were tutored in small groups for 40 lessons (four 40-min lessons each week). When we combined performance of students in both MWR conditions, intervention students significantly outperformed controls on proximal measures of affix reading and MWR, as well as standardized measures of decoding, spelling, and text comprehension. Furthermore, there was a noted interaction between English learner status and treatment on spelling performance. There were no statistically significant main effects between the MWR groups on proximal or standardized measures of interest. Findings are discussed in terms of their relevance to MWR instruction for students with persistent reading difficulties and considerations for future research related to the malleability of motivation.
Integration of a large-scale photovoltaic plant using a multilevel converter topology and virtual synchronous generator control

This work investigates the integration of large-scale photovoltaic (PV) plants to the grid. In particular it presents a case study where a cascaded H-bridge topology based on single-phase current-source inverters (CHB-CSI) is used as the grid interface of the PV plant and a control technique named virtual synchronous generator (VSG) is used in order to contribute to the stability of the grid by providing inertial response and primary frequency control to the PV plant. For all the three simulated cases the proposed control strategy for the PV plant was always capable to perform the VSG functions (inertial response and damping), even when one of the PV arrays output power went down to 10 %. However, simulation results also showed that in some cases the voltage variations were close to 100 % and even 300 % of its nominal value. Even though the execution of the VSG was always successful, the obtained results indicate that voltage loops are needed in order to keep the output voltages at a safe level.
CORPORATE RISK MANAGEMENT RATIONALES: EVIDENCE FROM CROATIAN COMPANIES

According to the Capital Asset Pricing Model and the Modigliani-Miller theorem, corporate risk management is irrelevant to the value of the fi rm. However, it is apparent that managers are constantly engaged in hedging activities that are directed at the reduction of corporate risks. As an explanation for this clash between theory and practice, imperfections in the capital market are used to argue for the relevance of corporate risk management function. This paper analyses corporate risk management practices and decision to hedge in large Croatian non-fi nancial companies. By using univariate and multivariate analysis, it explores if decision to hedge corporate risks in the analysed companies is a function of several fi rm’s characteristics that have been proven as relevant in making risk management decisions.
Merit: A Union View

years was carried into office with the FDR victory. With jobs a scarce commodity, Democrats in the executive and the legislature wasted little time before turning to the business at hand: finding work in state government for the faithful. The state's civil service system, enacted in 1905 and one of the best in the country at the time, was to be chopped up at the expense of the cadre of career civil service employees assembled during the LaFollette Progressive Republican years. To fend off this assault, state employees, with support from LaFollette administrators who were genuinely opposed to the spoils system, banded together into what became the Wisconsin State Employees Association. Through lobbying and political activity they saved the civil service system. The association stayed together and prospered. Today it is the nation's largest public employee union-the American Federation of State, County, and Municipal Employees (AFSCME). The phenomenal growth of the union in recent years and the ballyhooed "new militancy" of the public worker has shaded over those modest beginnings. There has been a common assumption among many students of public employee labor relations, including many who are actively involved, that the rising chant for full collective bargaining on wages, hours, and working conditions by public workers inevitably amounts to capital punishment for civil service as a personnel tool in public administration. It isn't true. The emphasis that AFSCME and a few other unions have placed on collective bargaining should not be seen as an abandonment of the merit ideal. It merely reflects a firming-up into policy of a view which has been held for many of us who have been intimately involved with the civil service during the past 20 years: that the civil service or merit system is first, second, and finally, management's personnel tool. What Is Merit?
Empagliflozin as add‐on to linagliptin in a fixed‐dose combination in Japanese patients with type 2 diabetes: Glycaemic efficacy and safety profile in a 52‐week, randomized, placebo‐controlled trial

This double‐blind, randomized, placebo‐controlled trial (ClinicalTrials.gov NCT02453555) evaluated the efficacy and safety of empagliflozin (Empa) 10 or 25 mg as add‐on to linagliptin (Lina) 5 mg (fixed‐dose combination, Empa/Lina 10/5 or 25/5) in insufficiently controlled Japanese type 2 diabetes patients.
DART: A Large Dataset of Dialectal Arabic Tweets

In this paper, we present a new large manually-annotated multi-dialect dataset of Arabic tweets that is publicly available. The Dialectal ARabic Tweets (DART) dataset has about 25K tweets that are annotated via crowdsourcing and it is well-balanced over five main groups of Arabic dialects: Egyptian, Maghrebi, Levantine, Gulf, and Iraqi. The paper outlines the pipeline of constructing the dataset from crawling tweets that match a list of dialect phrases to annotating the tweets by the crowd. We also touch some challenges that we face during the process. We evaluate the quality of the dataset from two perspectives: the inter-annotator agreement and the accuracy of the final labels. Results show that both measures were substantially high for the Egyptian, Gulf, and Levantine dialect groups, but lower for the Iraqi and Maghrebi dialects, which indicates the difficulty of identifying those two dialects manually and hence automatically.
The Influence of Education and Apolipoprotein ε4 on Mortality in Community-Dwelling Elderly Men and Women

We investigated the risk of death in relation to the apolipoprotein ε4 allele and evaluated how it interacts with education in 504 elderly adults (mean age 73 years, 65.3% women) who were enrolled in 1993 into the New Mexico Aging Process Study. During 9 years of follow-up, apolipoprotein ε2 appeared to be associated with a lower risk for all-cause mortality (hazard ratio (HR) = 0.73, 95% confidence interval (CI): 0.30–1.71) compared to apolipoprotein ε3 carriers in models adjusted for age, sociodemographic variables, medical conditions, adiposity, and lifestyle factors. The apolipoprotein ε4 allele conferred almost a threefold elevated risk of mortality (HR = 2.76, CI: 1.42–5.37). An interaction between education and apolipoprotein e4 (p=0.027) was observed with the HR of mortality among e4 carriers compared to noncarriers being 1.59 (0.64–3.96) for those with ≥college education; 6.66 (1.90–23.4) for those with some college or trade; and 14.1 (3.03–65.6) for participants with ≤high school education. No significant interaction was identified between apolipoprotein E genotype and cognitive function for mortality risk. These findings suggest that genetic (apolipoprotein ε4) and environmental (education) factors act interactively to influences survival in the elderly with higher education attenuating the adverse effect of apolipoprotein ε4 on mortality.
Asymptotically stable biped gait generation based on stability principle of rimless wheel

SUMMARY We investigated and identified the conditions necessary for stable dynamic gait generation in biped robots from the mechanical energy balance point of view. The equilibrium point at impact in a dynamic gait is uniquely determined by two conditions; keeping the restored mechanical energy constant and settling the relative hip-joint angle to the desired value before impact. The generated gait then becomes asymptotically stable around the equilibrium point determined by these conditions. This is shown by a simple recurrence formula of the kinetic energy immediately before impact. We verified this stability theorem using numerical simulation of virtual passive dynamic walking. The results were compared with those for a rimless wheel and an inherent stability principle was derived. Finally, we derived a robust control law using a reference mechanical energy trajectory and demonstrated its effectiveness numerically.
Vision-based Automated Bridge Component Recognition Integrated With High-level Scene Understanding

Image data has a great potential of helping conventional visual inspections of civil engineering structures due to the ease of data acquisition and the advantages in capturing visual information. A variety of techniques have been proposed to detect damages, such as cracks and spalling on a close-up image of a single component (columns and road surfaces etc.). However, these techniques commonly suffer from severe false-positives especially when the image includes multiple components of different structures. To reduce the false-positives and extract reliable information about the structures' conditions, detection and localization of critical structural components are important first steps preceding the damage assessment. This study aims at recognizing bridge structural and non-structural components from images of urban scenes. During the bridge component recognition, every image pixel is classified into one of the five classes (non-bridge, columns, beams and slabs, other structural, other nonstructural) by multi-scale convolutional neural networks (multi-scale CNNs). To reduce false-positives and get consistent labels, the component classifications are integrated with scene understanding by an additional classifier with 10 higher-level scene classes (building, greenery, person, pavement, signs and poles, vehicles, bridges, water, sky, and others). The bridge component recognition integrated with the scene understanding is compared with the naive approach without scene classification in terms of accuracy, false-positives and consistencies to demonstrate the effectiveness of the integrated approach.
Interrelationships among Fatty Acid Composition, Staphyloxanthin Content, Fluidity, and Carbon Flow in the Staphylococcus aureus Membrane

Fatty acids play a major role in determining membrane biophysical properties. Staphylococcus aureus produces branched-chain fatty acids (BCFAs) and straight-chain saturated fatty acids (SCSFAs), and can directly incorporate exogenous SCSFAs and straight-chain unsaturated fatty acids (SCUFAs). Many S. aureus strains produce the triterpenoid pigment staphyloxanthin, and the balance of BCFAs, SCSFAs and staphyloxanthin determines membrane fluidity. Here, we investigated the relationship of fatty acid and carotenoid production in S. aureus using a pigmented strain (Pig1), its carotenoid-deficient mutant (Pig1ΔcrtM) and the naturally non-pigmented Staphylococcus argenteus that lacks carotenoid biosynthesis genes and is closely related to S. aureus. Fatty acid compositions in all strains were similar under a given culture condition indicating that staphyloxanthin does not influence fatty acid composition. Strain Pig1 had decreased membrane fluidity as measured by fluorescence anisotropy compared to the other strains under all conditions indicating that staphyloxanthin helps maintain membrane rigidity. We could find no evidence for correlation of expression of crtM and fatty acid biosynthesis genes. Supplementation of medium with glucose increased SCSFA production and decreased BCFA and staphyloxanthin production, whereas acetate-supplementation also decreased BCFAs but increased staphyloxanthin production. We believe that staphyloxanthin levels are influenced more through metabolic regulation than responding to fatty acids incorporated into the membrane.
CEFR-based Lexical Simplification Dataset

This study creates a language dataset for lexical simplification based on Common European Framework of References for Languages (CEFR) levels (CEFR-LS). Lexical simplification has continued to be one of the important tasks for language learning and education. There are several language resources for lexical simplification that are available for generating rules and creating simplifiers using machine learning. However, these resources are not tailored to language education with word levels and lists of candidates tending to be subjective. Different from these, the present study constructs a CEFR-LS whose target and candidate words are assigned CEFR levels using CEFR-J wordlists and English Vocabulary Profile, and candidates are selected using an online thesaurus. Since CEFR is widely used around the world, using CEFR levels makes it possible to apply a simplification method based on our dataset to language education directly. CEFR-LS currently includes 406 targets and 4912 candidates. To evaluate the validity of CEFR-LS for machine learning, two basic models are employed for selecting candidates and the results are presented as a reference for future users of the dataset.
High-protein diets during pregnancy: healthful or harmful for offspring?

Maternal diet during pregnancy can induce developmental adaptations that permanently alter offspring physiology and metabolism (1). Fetal programming is an important risk factor for obesityand adiposity-related noncommunicable diseases in adult life (1). The influence of maternal dietary protein during pregnancy on offspring phenotype and health is generating research interest (2, 3). Both low-protein (LP) and higher-protein (HP) diets during pregnancy have been associated with detrimental effects on offspring (3), suggesting a quadratic (U-shaped) relation and that macronutrient ratio may influence offspring health and disease. Research evaluating the optimal macronutrient ratio is required. In this issue of the Journal, Maslova et al (4) present observations from a prospective Danish birth cohort of pregnant women recruited in 1988–1989 with offspring follow-up at age 19–21 y. This study is novel because it examines the long-term impact of maternal protein intake and protein quality during pregnancy on offspring anthropometric measures and biomarkers of adiposity and glucose metabolism. The study observed associations between higher maternal intakes of animal protein when substituted for carbohydrate [ie, higher animal protein-to-carbohydrate (P:C) ratio] with higher offspring BMI, primarily among females (4). This relation strengthened when models were adjusted for maternal age, education, parity, prepregnancy BMI, smoking, and sibling overweight. However, no associations were found between maternal protein intake and waist circumference or biomarkers of adiposity (4). Mean maternal protein intake [16% of energy (%E)] was comparable to that reported by pregnant women in developed countries (5). However, large variations in protein intake (9.5– 40%E) during pregnancy have been recorded.
Recognizing Behavioral Factors while Driving: A Real-World Multimodal Corpus to Monitor the Driver’s Affective State

The presented study concentrates on the collection of emotional multimodal real-world in-car audio, video and physiological signal recordings while driving. To do so, three sensor systems were integrated in the car and four emotional relevant states of the driver were defined: neutral, positive, frustration and anxiety. To gather as natural as possible emotional data of the driver, the subjects needed to be unbiased and were therefore kept unaware of the detailed research objective. The emotions were induced using so-called Wizard-of-Oz experiments, where the drivers believed to be interacting with an automated technical system, which in fact was controlled by a human. Additionally, on board interviews while driving were conducted by an instructed psychologist. To evaluate the collected data, questionnaires were filled out by the subjects before, during and after the data collection. These include monitoring of the drivers perceived state of emotion, stress, sleepiness and thermal sensation but also detailed questionnaires on their driving experience, attitude towards technology and big five OCEAN personality traits. Afterwards, the data was annotated by expert labelers. The statistical analyses of these results will be presented in the full paper.
Source Mechanisms of Mine-Related Seismicity, SavukaMine, South Africa

We report full moment tensor solutions for 76 mine tremors with moment magnitudes (Mw) between 0.5 and 2.6 recorded by a network of 20 high-frequency geophones in a deep gold mine in South Africa. Source mechanisms convey important information on how in-mine stresses are relaxed, and understanding the nature of such mechanisms is essential for improving our assessment of rock mass response to mining. Our approach has consisted of minimizing the L2 norm of the difference between observed and predicted P, SV, and SH spectral amplitudes, with visually assigned polarities, to constrain all six independent components of the seismic moment tensor. Our results reveal the largest principal stresses in the mine are com- pressive, oriented near vertically, and relaxed through a mix of volumetric closure and normal faulting, consistent with a gravity-driven closure of the mined-out areas. Pre- vious moment tensor studies in deep mines had suggested that the distribution of seis- mic sources in terms of the volumetric-shear mix was bimodal. A bimodal distribution is compatible with our moment tensor solutions only for moment magnitudes above 2.2. Events in the 0:5 <Mw <2:2 moment magnitude range display a continuous distribution of their volumetric-shear mix. Online Material: Focal parameters for mine tremors at Savuka.
Handling Dynamic Sets of Reactions in Stochastic Simulation Algorithms

Reaction selection is a major and time consuming step of stochastic simulation algorithms. Current approaches focus on constant sets of reactions. However, in the case of multiple agents whose behaviors are governed by diverse reactions at multiple levels, where the number and structure of agents and the number of reactions varies during simulation. Therefore, we equip different variants of stochastic simulation algorithms with strategies to handle dynamic sets of reactions. We implement the next reaction method with a heap and the direct reaction method with two tree-based selection strategies, compare their performance, and discuss open questions for future research.