Miracle-dz/UniFAR-FTUs huggingface dataset:
A Neural Network Approach to Hearthstone Win Rate Prediction

This paper describes a solution to the AAIA‘18 data mining challenge, which concerns prediction of win rates for decks in Hearthstone collectible card game. A neural network model assigning win rate to decks is learned based on maximisation of log probability of observed match results. A representation of deck contents is based on a second network, which performs the role of a dual-task encoder. Two tasks learned by the encoding networks are encoding decks in such a way that the full deck can be reconstructed, and encoding individual cards so that their specific properties can be decoded. Shared representation for these tasks allows the knowledge of individual cards to be taken into account.
Complex Power System Status Monitoring and Evaluation Using Big Data Platform and Machine Learning Algorithms: A Review and a Case Study

Efficient and valuable strategies provided by large amount of available data are urgently needed for a sustainable electricity system that includes smart grid technologies and very complex power system situations. Big Data technologies including Big Data management and utilization based on increasingly collected data from every component of the power grid are crucial for the successful deployment and monitoring of the system. This paper reviews the key technologies of Big Data management and intelligent machine learning methods for complex power systems. Based on a comprehensive study of power system and Big Data, several challenges are summarized to unlock the potential of Big Data technology in the application of smart grid. This paper proposed a modified and optimized structure of the Big Data processing platform according to the power data sources and different structures. Numerous open-sourced Big Data analytical tools and software are integrated as modules of the analytic engine, and self-developed advanced algorithms are also designed. The proposed framework comprises a data interface, a Big Data management, analytic engine as well as the applications, and display module. To fully investigate the proposed structure, three major applications are introduced: development of power grid topology and parallel computing using CIM files, high-efficiency load-shedding calculation, and power system transmission line tripping analysis using 3D visualization. The real-system cases demonstrate the effectiveness and great potential of the Big Data platform; therefore, data resources can achieve their full potential value for strategies and decision-making for smart grid. The proposed platform can provide a technical solution to the multidisciplinary cooperation of Big Data technology and smart grid monitoring.
Macrobenthic fauna from an upwelling coastal area of Peru (Warm Temperate South-eastern Pacific province -Humboldtian ecoregion)

Abstract Background A total of 162 species and subspecies of marine macroinvertebrates were recorded in the submerged soft and hard substrates around the PERU LNG marine terminal and surrounding area, in the central coast of Peru, 167 km south of Lima, Peru. The collection of specimens was carried out from June 2011 to June 2015 as part of the research studies conducted by the Biodiversity Monitoring and Assessment Program (BMAP) around the marine terminal. The area is part of the Humboldt Current Large Marine Ecosystem, one of the most important upwelling systems in the world. New information We identified specimens belonging to 83 families and seven phyla. The list was assembled from the taxonomic identifications made by the BMAP. We identified species and subspecies belonging to phyla Annelida, Arthropoda, Brachiopoda, Cnidaria, Echinodermata, Bryozoa and Mollusca. Phyla Annelida (60 spp.), Arthropoda (47 spp.)and Mollusca (45 spp.) exhibited the largest number of species.
Turbo MIMO-OFDM Receiver in Time-Varying Channels

This paper proposes an advanced turbo receiver with joint inter-carrier interference (ICI) self cancellation and channel equalization for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems over rapidly time-varying channel environment. The ICI caused by impairment of local oscillators and carrier frequency offset (CFO) is the major problem for MIMO-OFDM communication systems. The existing schemes (conjugate cancellation (CC) and phase rotated conjugate cancellation (PRCC)) that deal with the ICI cancellation and channel equalization can’t provide satisfactory performance over time-varying channels. In term of error rate performance and low computational complexity, ICI self cancellation is the best choice. So, this paper proposes a turbo receiver to deal with the problem of joint ICI self cancellation and channel equalization. We employ the adaptive phase rotations in the receiver to effectively track the CFO variations without feeding back the CFO estimate to the transmitter as required in traditional existing scheme. We also give some simulations to verify the proposed scheme. The proposed schene outperforms the existing schemes.
Cooperation of loss of NKX3.1 and inflammation in prostate cancer initiation

ABSTRACT Although it is known that inflammation plays a critical role in prostate tumorigenesis, the underlying processes are not well understood. Based on analysis of genetically engineered mouse models combined with correlative analysis of expression profiling data from human prostate tumors, we demonstrate a reciprocal relationship between inflammation and the status of the NKX3.1 homeobox gene associated with prostate cancer initiation. We find that cancer initiation in aged Nkx3.1 mutant mice correlates with enrichment of specific immune populations and increased expression of immunoregulatory genes. Furthermore, expression of these immunoregulatory genes is similarly increased in human prostate tumors having low levels of NKX3.1 expression. We further show that induction of prostatitis in Nkx3.1 mutant mice accelerates prostate cancer initiation, which is coincident with aberrant cellular plasticity and differentiation. Correspondingly, human prostate tumors having low levels of NKX3.1 have de-regulated expression of genes associated with these cellular processes. We propose that loss of function of NKX3.1 accelerates inflammation-driven prostate cancer initiation potentially via aberrant cellular plasticity and impairment of cellular differentiation. This article has an associated First Person interview with the first author of the paper. Summary: Chronic inflammation collaborates with loss of function of the prostate-specific tumor-suppressor NKX3.1 to promote prostate cancer initiation, increase cellular plasticity and impair cellular differentiation.
Γ-stochastic neighbour embedding for feed-forward data visualization

t-Distributed stochastic neighbour embedding is one of the most popular non-linear dimension-reduction techniques used in multiple application domains. In this article, we propose a variation on the embedding neighbourhood distribution, resulting in Γ-stochastic neighbour embedding, which can construct a feed-forward mapping using a radial basis function network. We compare the visualizations generated by Γ-stochastic neighbour embedding with those of t-distributed stochastic neighbour embedding and provide empirical evidence suggesting the network is capable of robust interpolation and automatic weight regularization.
End-Stage Kidney Disease following Surgical Management of Kidney Cancer.

BACKGROUND AND OBJECTIVES We investigated the incidence of ESKD after surgical management of kidney cancer in the Australian state of Queensland, and described patterns in the initiation of kidney replacement therapy resulting from kidney cancer across Australia. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS All newly diagnosed cases of kidney cancer in the Australian state of Queensland between January of 2009 and December of 2014 were ascertained through the Queensland Cancer Registry. There were 2739 patients included in our analysis. Patients who developed ESKD were identified using international classification of disease-10-coded hospital administrative data. Incidence rate and 3-year cumulative incidence were calculated, and multivariable Cox proportional hazards models were used to identify factors associated with ESKD. Additional descriptive analysis was undertaken of Australian population data. RESULTS The incidence rate of ESKD in all patients was 4.9 (95% confidence interval [95% CI], 3.9 to 6.2) per 1000 patient-years. The 3-year cumulative incidence was 1.7%, 1.9%, and 1.0% for all patients, and patients managed with radical or partial nephrectomy, respectively. Apart from preoperative kidney disease, exposures associated with increased ESKD risk were age≥65 years (adjusted hazard ratio [aHR], 2.0; 95% CI, 1.2 to 3.2), male sex (aHR, 2.3; 95% CI, 1.3 to 4.3), preoperative diabetes (aHR, 1.8; 95% CI, 1.0 to 3.3), American Society of Anesthesiologists classification ≥3 (aHR, 4.0; 95% CI, 2.2 to 7.4), socioeconomic disadvantage (aHR, 1.6; 95% CI, 0.9 to 2.7), and postoperative length of hospitalization ≥6 days (aHR, 2.1; 95% CI, 1.4 to 3.0). Australia-wide trends indicate that the rate of kidney replacement therapy after oncologic nephrectomy doubled between 1995 and 2015, from 0.3 to 0.6 per 100,000 per year. CONCLUSIONS In Queensland between 2009 and 2014, one in 53 patients managed with radical nephrectomy and one in 100 patients managed with partial nephrectomy developed ESKD within 3 years of surgery. PODCAST This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2018_09_28_CJASNPodcast_18_1_. mp3.
A low cost minimally invasive adhesive alternative for maxillary central incisor replacement

OBJECTIVE The beneficial mechanical properties of zirconia, together with the adhesive techniques, provide a wide range of clinical applications, including the construction of thin structures and minimally invasive adhesive restorations. CLINICAL CONSIDERATIONS A periodontal disease-related missing maxillary central incisor, in a pregnant patient with chronic periodontal disease in the first trimester of pregnancy, and with type II diabetes treated with resin-bonded fixed partial denture using the missing tooth cemented to a zirconia framework and then bonded to the abutment teeth. CONCLUSIONS According to the systemic conditions presented in this case report, using a low-cost technology and the missing tooth it was possible to obtain an easier and satisfactory esthetic and functional result. CLINICAL SIGNIFICANCE The mechanical properties of zirconia made it possible to treat a pregnant patient with chronic periodontal disease in the first trimester of pregnancy, and with type II diabetes with a thin zirconia framework and minimally invasive adhesive restorations.
Extended Feature Spaces Based Classifier Ensembles for Sentiment Analysis of Short Texts

Sentiment classification has become very popular to analyze opinions about events, products, and so on, especially for social networks such as Twitter. Due to the size limitation of expressing ideas on social networks, the classification performance needs to be boosted by proposing various techniques. In this work, the enhancement of feature space with word embedding based features is proposed to deal with the size limitation issues and the classification success of sentiment analysis is improved by employing classifier ensembles. The contributions of this paper are fivefold. First, the representative capabilities of features are enriched by using a semantic word embedding model and followingly the conventional feature selection techniques are compared. Second, traditional machine learning algorithms, namely naive Bayes, support vector machine, and random forest are carried out to select baseline classifier for the proposed ensemble system. Third, three ensemble strategies namely, bagging, boosting and random subspace are introduced to ensure the diversity of ensemble learning. Fourth, experiments are conducted to compare the performance of the models with the word embedding baseline. Eventually, a wide range of comparative experiments on Twitter datasets demonstrate that the classification performance of the proposed model significantly outperforms the state of art studies DOI: http://dx.doi. org/10.5755/j01.itc. 47.3. 20935
Defending Non-control-data Attacks using Influence Domain Monitoring

As an increasing number of defense methods against control-data attacks are deployed in practice, control-data attacks have become challenging, and non-control-data attacks are on the rise. However, defense methods against non-control-data attacks are still deficient even though these attacks can produce damage as significant as that of control-data attacks. We present a method to defend against non-control-data attacks using influence domain monitoring (IDM). A definition of the data influence domain is first proposed to describe the characteristics of a variable during its life cycle. IDM extracts security-critical non-control data from the target program and then instruments the target for monitoring these variables’ influence domains to ensure that corrupted variables will not be used as the attackers intend. Therefore, attackers may be able to modify the value of one security-critical variable by exploiting certain memory corruption vulnerabilities, but they will be prevented from using the variable for nefarious purposes. We evaluate a prototype implementation of IDM and use the experimental results to show that this method can defend against most known non-control-data attacks while imposing a moderate amount of performance overhead.
Microbial spectrum and drug-resistance profile of isolates causing bloodstream infections in febrile cancer patients at a referral hospital in Addis Ababa, Ethiopia

Background The spectrum of pathogens causing bloodstream infections (BSIs) in cancer patients has shown significant fluctuations in different geographical areas and time. We studied the microbial spectrum and drug-resistance profile of pathogens causing BSIs in febrile cancer patients at a referral hospital in Ethiopia. Methods This cross-sectional study was conducted between December 2011 and June 2012 at Tikur Anbessa Hospital in Addis Ababa. Blood cultures from febrile cancer patients (n=107) were performed. Bacterial and fungal pathogens were identified and antimicrobial susceptibility testing done for the bacterial isolates using the Kirby–Bauer disk diffusion method. Results A total of 82 pathogens were isolated from 112 blood culture tests of the 76 patients: 71 (86.6%) of the isolates were bacteria and 11 (13.4%) were fungi. The majority (60.5% [43 of 71]) of the isolates were Gram-positive bacteria, where Staphylococcus aureus was predominant (72% [31 of 43]), and 68% of S. aureus isolates were resistant to ceftriaxone and oxacillin. Gram-negative bacteria accounted for 39.5% (28 of 71) of the isolates. Stenotrophomonas maltophilia (17.9% [five of 28]) was the most frequent Gram-negative isolate. In Gram-negative bacteria, the highest rates of resistance were observed in amoxicillin–clavulanic acid (80% [12 of 15]), followed by ceftriaxone (73.3%) and trimethoprim–sulfamethoxazole (73.3%). Multidrug resistance (resistance to three or more types of antibiotics, in this case to ceftriaxone, tetracycline, and trimethoprim-sulfamethoxazole) was observed in 26.3% (13 of 43) of Gram-positive and 40% (six of 16) of Gram-negative bacteria. Neutropenia was an independent risk factor for BSIs (P=0.02). Conclusion Gram-positive bacteria were the predominant etiologic agents of BSIs in Ethiopian patients with cancer. Both Gram-positive and Gram-negative bacteria showed an increasing level of resistance for most of the antibiotics used for empiric therapy. Routine bacterial surveillance and study of their resistance patterns must be an essential component of cancer-related infection control and care in our setting.
Prevalence and associated factors of depressive symptoms among elderly inpatients of a Chinese tertiary hospital

Background Depression in the elderly is a serious and often underdiagnosed psychiatric disorder that has been linked to adverse outcomes in the hospital setting. This study aims to evaluate the prevalence of depressive symptoms and associated factors among elderly hospital inpatients. Methods The cross-sectional study included 411 consecutively hospitalized patients aged 60 years and older. Participants were evaluated within 48 hours of admission using an interviewer-administered questionnaire including the Geriatric Depression Scale and comprehensive geriatric assessment to provide basic demographic and clinical information. Results Most of the participants were male (64.5%), with a mean (SD) age of 75.9 (8.1) years between 60 and 97 years. The prevalence of depressive symptoms was 32.8%. Univariate analysis showed significant associations between depressive symptoms and older age, female gender, lower body mass index, number of chronic diseases, impaired family function, impaired cognition, malnutrition, increased frailty, and decreased ability to perform activities of daily living. After logistic regression, variables that remained significantly associated with depression were cognitive decline (odds ratio =1.97, 95% CI: 1.09–3.55), poor family function (odds ratio =2.01, 95% CI: 1.10–3.66), and frailty (odds ratio =5.07, 95% CI: 1.95–13.20). Depressive symptoms were independently associated with prolonged hospital length. Conclusion Depressive symptoms were prevalent among hospitalized elderly and independently associated with cognitive decline, poor family function, and frailty. Therefore, it is essential to screen for depression and perform a comprehensive geriatric assessment in these patients to identify and manage depressive symptoms.
Performance Analysis of MRT-Based Dual-Polarized Massive MIMO System with Space-Polarization Division Multiple Access

In recent years, one of the most remarkable 5G technologies is massive multiple-input and multiple-output (MIMO) system which increases spectral efficiency by deploying a large number of transmit-antennas (eg. tens or hundreds transmit-antennas) at base station (BS). However, conventional massive MIMO system using single-polarized (SP) transmit-antennas increases the size of the transmit-array proportionally as the number of transmit-antennas increases. Hence, size reduction of large-scale transmit-array is one of the major concerns of massive MIMO system. To reduce the size of the transmit-array at BS, dual-polarized (DP) transmit-antenna can be the solution to halve the size of the transmit-array since one collocated DP transmit-antenna deploys vertical and horizontal transmit-antennas compared to SP transmit-antennas. Moreover, proposed DP massive MIMO system increases the spectral efficiency by not only in the space domain but also in the polarization domain whereas the conventional SP massive MIMO system increases the spectral efficiency by space domain only. In this paper, the comparative performance of DP and SP massive MIMO systems is analyzed by space division multiple access (SDMA) and space-polarization division multiple access (SPDMA) respectively. To analyze the performance of DP and SP massive MIMO systems, DP and SP spatial channel models (SCMs) are proposed which consider depolarized propagation channels between transmitter and receiver. The simulation results show that the performance of proposed 32 transmitter (Tx) DP massive MIMO system improves the spectral efficiency by about 91% for a large number of user equipments (UEs) compare to 32Tx SP massive MIMO system for identical size of the transmit-array.
Queueing Theoretic Approach to Playout Buffer Model for HTTP Adaptive Streaming

HTTP-based adaptive streaming (HAS) has recently been widely deployed on the Internet. In the HAS system, a video content is encoded at multiple bitrates and the encoded video content is segmented into small parts of fixed durations. The HAS client requests a video segment and stores it in the playout buffer. The rate adaptation algorithm employed in HAS clients dynamically determines the video bitrate depending on the time-varying bandwidth. Many studies have shown that an efficient rate adaptation algorithm is critical to ensuring quality-of-experience in HAS systems. However, existing algorithms have problems estimating the network bandwidth because bandwidth estimation is performed on the client-side application stack. Without the help of transport layer protocols, it is difficult to achieve accurate bandwidth estimation due to the inherent segment-based transmission of the HAS. In this paper, we propose an alternative approach that utilizes the playout buffer occupancy rather than using bandwidth estimates obtained from the application layer. We start with a queueing analysis of the playout buffer. Then, we present a buffer-aware rate adaptation algorithm that is solely based on the mean buffer occupancy. Our simulation results show that compared to conventional algorithms, the proposed algorithm achieves very smooth video quality while delivering a similar average video bitrate.
Dual Targeting of Aurora Kinases with AMG 900 Exhibits Potent Preclinical Activity Against Acute Myeloid Leukemia with Distinct Post-Mitotic Outcomes

Aurora kinase A and B have essential and non-overlapping roles in mitosis, with elevated expression in a subset of human cancers, including acute myeloid leukemia (AML). In this study, pan-aurora kinase inhibitor (AKI) AMG 900 distinguishes itself as an anti-leukemic agent that is more uniformly potent against a panel of AML cell lines than are isoform-selective AKIs and classic AML drugs. AMG 900 inhibited AML cell growth by inducing polyploidization and/or apoptosis. AMG 900 and aurora-B–selective inhibitor AZD1152-hQPA showed comparable cellular effects on AML lines that do not harbor a FLT3-ITD mutation. AMG 900 was active against P-glycoprotein–expressing AML cells resistant to AZD1152-hQPA and was effective at inducing expression of megakaryocyte-lineage markers (CD41, CD42) on human CHRF-288-11 cells and mouse Jak2V617F cells. In MOLM-13 cells, inhibition of p-histone H3 by AMG 900 was associated with polyploidy, extra centrosomes, accumulation of p53 protein, apoptosis, and cleavage of Bcl-2 protein. Co-administration of cytarabine (Ara-C) with AMG 900 potentiated cell killing in a subset of AML lines, with evidence of attenuated polyploidization. AMG 900 inhibited the proliferation of primary human bone marrow cells in culture, with a better proliferation recovery profile relative to classic antimitotic drug docetaxel. In vivo, AMG 900 significantly reduced tumor burden in a systemic MOLM-13 xenograft model where we demonstrate the utility of 3′-deoxy-3′-18F-fluorothymidine [18F]FLT positron emission tomographic (PET)–CT imaging to measure the antiproliferative effects of AMG 900 in skeletal tissues in mice.