Miracle-dz/UniFAR-FTUs huggingface dataset:
Postoperative adjuvant adoptive immunotherapy for hepatocellular carcinoma:A Meta-analysis

OBJECTIVE: To evaluate the efficacy and safety of adoptive immunotherapy(AIT) for patients with HCC postoperatively.METHODS: Sources such as MEDLINE,EMBASE,Cochrane Library database were searched.All randomized trials comparing hepatic resection or radiofrequency ablation alone with surgery plus AIT for HCC were identified.RESULTS: Four randomized controlled trials involving 423 patients were included.For the 1-year tumor recurrence rate,surgery plus AIT showed statistically significant less incidence of recurrence,with a pooled risk ratio(RR) of 0.51(95%CI=0.36-0.71,P=0.000 1). For 3-year tumor recurrence rate,the trials did not revealed statistically significant less incidence,with pooled risk ratio of 0.76(95%CI=0.56-1.02,P=0.07). For 1-year and 3-year mortality,AIT did not demonstrate statistically significant less incidence(RR=0.70,95%CI=0.31-1.61,P=0.41;RR=0.76,95%CI=0.38-1.49,P=0.42). Chilling/fever,headache,dizziness,nausea and tachycardia were reported as side-effects of AIT but were well tolerated by most patients.No infection,hepatic functional deterioration,autoimmune disorder or death case related to treatment were reported.CONCLUSION: Adjuvant AIT seems promising for patients with HCC after hepatic resection or radiofrequency ablation,but further trial is requires.
Evolutionary Genetics of Core Eudicot Inflorescence and Flower Development

The genetic basis of flowering is best understood in the model core eudicot species Arabidopsis thaliana (Brassicaceae), and involves the genetic reprogramming of shoot apical meristems, ending in the production of flowers. Although inflorescences and flowers of core eudicots share a common ground plan, variation in architecture, shape and ornamentation suggests repeated modifications to this ancestral plan. Comparative studies, primarily in Brassicaceae and Leguminoseae (rosids), and Asteraceae, Plantaginaceae and Solanaceae (asterids), have revealed a common developmental framework for flowering across core eudicots. This serves as a basis for understanding genetic changes that underlie the diversification of inflorescence and floral form. Recent work is starting to reveal the relative importance of regulatory versus protein coding changes in genes involved in diversification of inflorescence and flower development across core eudicots. Furthermore, these studies highlight the importance of phylogenetic history for understanding functional conservation of duplicated genes. _____________________________________________________________________________________________________________
BatchOut: Batch-level feature augmentation to improve robustness to adversarial examples

Machine Learning models are known to be susceptible to small but structured changes to their inputs that can result in wrong inferences. It has been shown that such samples, called adversarial samples, can be created rather easily for standard neural network architectures. These adversarial samples pose a serious threat for deploying state-of-the-art deep neural network models in the real world. We propose a feature augmentation technique called BatchOut to learn robust models towards such examples. The proposed approach is a generic feature augmentation technique that is not specific to any adversary and handles multiple attacks. We evaluate our algorithm on benchmark datasets and architectures to show that models trained using our method are less susceptible to adversaries created using multiple methods.
IJCAI 2019 Proceedings of the 5th Workshop on Semantic Deep Learning (SemDeep-5)

Multilingual speakers often switch between languages and generate enormous quantities of cross-language data. This phenomenon is more frequent observed in social media texts, where a large body of user generated data is produced every day. Such mix-lingual and informal texts lead to a challenge for partof-speech (POS) tagging, which is one fundamental task in natural language processing. In this paper, we propose a language-agnostic POS tagger for social media texts, which is able to learn from heterogeneous data with different genre and language type. Particularly, in order to comprehensively evaluate POS tagging performance, we propose a new tagging scheme including exclusive tags for special symbols in social media texts, and a humanannotated dataset of Chinese-English mixed social media texts is also developed. Experiments on both synthetic and real datasets show the validity and effectiveness of our model on social media texts where it outperforms stateof-the-art language-specific taggers.
A FUZZY-BASED SPEED CONTROLLER FOR IMPROVEMENT OF INDUCTION MOTOR'S DRIVE PERFORMANCE

Induction motors (IMs) are widely used in many industrial applications due to their robustness, low cost, simplicity and relative good efficiency. One of the major considerations for IMs is their speed control. PI (proportional-integrator) controllers are usually used as speed controller. Adjusting the gain of PI controller is time-consuming which needs thorough considerations. Hence, fuzzy controllers are proposed to overcome such problems. In this paper, firstly drive of a three-phase induction motor is designed based on PI controller and then fuzzy logic controller is implemented. This paper presents a novel speed control technique based on fuzzy logic with two inputs and one output for drive of an IM. The inputs are speed error and derivation of speed error and the output is speed. Finally comparison is done between the PI and fuzzy controllers which shows superiority of the fuzzy controller over PI controller.
Designing a Frame-Semantic Machine Translation Evaluation Metric

We propose a metric for machine translation evaluation based on frame semantics which does not require the use of reference translations or human corrections, but is aimed at comparing original and translated output directly. The metrics is described on the basis of an existing manual frame-semantic annotation of a parallel corpus with an English original and a Brazilian Portuguese and a German translation. We discuss implications of our metrics design, including the potential of scaling it for multiple languages.
1 Islamic Banking and Finance : Philosophical Underpinnings

By now, a good deal of intellectual effort has been undertaken by a number of specialists in Islamic economics to explore different aspects of Islamic banking and finance. Even some conventional economists, intentionally or unintentionally, have dealt with the subjects, which may be considered closely akin to it. It is an undeniable fact that Islamic financial institutions have had only a marginal existence during the last 300 years. They did not get the same chance as western financial institutions to gradually evolve their institutional structure, tools and modus operandi to their full potential. Therefore, such evolutionary process of Islamic banking and finance must be done through serious intellectual work by economists rather than observing institutions at work. However, Islamic banking and finance has now been in the arena for more than a quarter of a century. It has taken a
Atomic diffusion and mixing in old stars

Aims. We attempt to constrain the efficiency of additional transport or mixing processes that reduce the effect of atomic diffusion in stellar atmospheres. Methods. We apply spectral synthesis methods to spectra observed with the GIRAFFE spectrograph on the VLT to estimate abundances of Mg, Ti, Fe, and Ba in stars in the metal-poor globular cluster M 30. To the abundances we fit trends of abundances predicted by stellar evolution models assuming different efficiencies of additional transport or mixing processes. The fitting procedure attempts to take into account the effects of parameter-dependent systematic errors in the derived abundances. Results. We find that the parameter T0, which describes the efficiency of additional transport or mixing processes, can almost certainly be constrained to the narrow range log10(T0/[K]) between 6.09 and 6.2. This corresponds to decreased abundances for stars at the main sequence turn-off point compared to the red giant branch by 0.2 dex for Mg, 0.1 dex for Fe, and 0.07 dex for Ti. We also find that while our estimates do have non-negligible systematic errors stemming from the continuum placement and the assumed microturbulence, our method can take them into account. Conclusions. Our results partly amend the results of an earlier paper in this article series, that tentatively used a value of log10(T0/[K]) = 6.0 when modelling the Spite plateau of lithium. To more easily distinguish physical effects from systematic errors, we recommend that studies of this kind focus on elements for which the expected surface abundances as functions of effective temperature have a distinct structure and cover a wide range.
The Byar: An Ethnographic and Empirical Study of a Balinese Musical Moment

HE repertoire of the Balinese gamelan gong kebyar ensemble (see Tenzer 2000 and the glossary provided in Appendix A) is marked by virtuosic, unmetered tutti passages, referred to as kebyar, that often introduce pieces or function as transitions within compositions. The kebyar itself often begins with a sudden, fortissimo byar, a single, tutti chord that is performed by the majority of the ensemble. The sheer virtuosity and power of this famous repertoire is encapsulated in the expert execution of a byar, in which twenty to thirty musicians, without the aid of notation, a conductor, or beat entrainment, synchronize to produce a shockingly precise and loud eruption of sound.
Deforestation and Connectivity among Protected Areas of Tanzania

Protected Areas (PAs) in Tanzania had been established originally for the goal of habitat, landscape and biodiversity conservation. However, human activities such as agricultural expansion and wood harvesting pose challenges to the conservation objectives. We monitored a decade of deforestation within 708 PAs and their unprotected buffer areas, analyzed deforestation by PA management regimes, and assessed connectivity among PAs. Data came from a Landsat based wall-to-wall forest to non-forest change map for the period 2002–2013, developed for the definition of Tanzania’s National Forest Reference Emissions Level (FREL). Deforestation data were extracted in a series of concentric bands that allow pairwise comparison and correlation analysis between the inside of PAs and the external buffer areas. Half of the PAs exhibit either no deforestation or significantly less deforestation than the unprotected buffer areas. A small proportion (10%; n = 71) are responsible for more than 90% of the total deforestation; but these few PAs represent more than 75% of the total area under protection. While about half of the PAs are connected to one or more other PAs, the remaining half, most of which are Forest Reserves, are isolated. Furthermore, deforestation inside isolated PAs is significantly correlated with deforestation in the unprotected buffer areas, suggesting pressure from land use outside PAs. Management regimes varied in reducing deforestation inside PA territories, but differences in protection status within a management regime are also large. Deforestation as percentages of land area and forested areas of PAs was largest for Forest Reserves and Game Controlled areas, while most National Parks, Nature Reserves and Forest Plantations generally retained large proportions of their forest cover. Areas of immediate management concern include the few PAs with a disproportionately large contribution to the total deforestation, and the sizeable number of PAs being isolated. Future protection should account for landscapes outside protected areas, engage local communities and establish new PAs or corridors such as village-managed forest areas.
Integrated framework for game design

Since the mid-nineties there has been efforts to define a formal language for game design. The MDA Framework, published in 2004, quickly became the most used guideline, mostly in academic environments. It presents a definition for mechanic, but does not elaborate on the steps to design one. This work intends to complement the MDA along with other formal tools published since, to provide a game designer with a clear step-by-step guide on how to design a video game from scratch. Within this study two new tools are presented, the 5-Part Model for mechanic design, and the Risk/Reward Model for difficulty balance.
Everyday Life Reflection: Exploring Media Interaction with Balance, Cogito & Dott

Reflection is of increasing interest in HCI as it has many potential benefits in design, education and everyday life. In this paper, we explore media-supported reflection through the design and deployment of three concepts. In contrast to prevalent reflective approaches that are based on system-collected data, we explore how user-created media can support personal reflection. Three interactive prototypes were developed, focusing on different modalities: Balance uses audio, Cogito uses text, and Dott uses visual media. We evaluate these concepts in an in-thewild study that is both explorative and comparative. We found that the open-ended systems primarily supported reflection during the creation of media and that the use depended on opportunity and triggers. We conclude the paper with a discussion of our findings regarding the method and the implications of our findings for the broader area of design for reflection.
Explore the Influence of Politics on Cultural Attention Based on Sentiment Analysis of Social Network Data

With the increasingly frequent cultural exchanges between China and foreign countries, more and more Chinese people advocate western festivals. Foreign culture has invaded China and our traditional culture has been neglected seriously, which results in the more servere sense of loss of traditional culture. Therefore, Chinese government has stepped up efforts to spread traditional culture and issued relevant documents to make the public pay more attention to the inheritance and development of traditional culture. By mining relevant festival data in Sina Weibo which is sent before and after the policy release, this paper use Chinese word segmentation technology and naive bayes classifier to analyze the change of public sentiment value and the distribution of emotional tendency to explore whether the Policy can promote the spread of culture and the positive significance of policy for the transmission of traditional culture.
Motion Planning of a 14 DOF Biped Robot For Crossing an Irregular Shape Ditch Using a New Speed Function Incorporating Terrain Features and Biped Dynamics

In this paper, a new method has been proposed to plan a path between an initial point and goal point on a terrain containing an irregular shape ditch. The path planner models this problem as a wavefront propagation in a Nonuniform medium. The Eikonal equation is a mathematical representation of this problem. To solve this equation a speed function value at each node of discretized terrain surface is defined by using the local geometry of terrain and the ditch in the vicinity of node and dynamic behavior of biped robot at that node. The solution of the eikonal equation gives a potential surface of the terrain. Gradient descent algorithm provides a path on this potential surface. A dataset which consists of a collection of energy optimal and dynamically balanced gaits (hip and foot trajectories) of a 14 DOF biped robot for walking on uneven terrain is created by using a genetic algorithm. This dataset is generalized by using a feedforward neural-network by training the network with stochastic conjugate gradient algorithm. The footstep planner sequentially plans the feasible footsteps along the obtained path with minimum deviation by geometric method. The trained neural network estimates the hip and foot trajectories for each step along the path so that the biped robot can follow the path by crossing the encountered ditch successfully in an energy-optimal way. The proposed method is validated by simulation of a 14 DOF biped robot for the walk between an initial point and goal point on a terrain containing an irregular shape ditch.
Effective Patient Similarity Computation for Clinical Decision Support Using Time Series and Static Data

This paper presents a technique for computing patient similarity using time series data effectively combined with static data. Time series data of inpatients, such as heart rate, blood pressure, Oxygen saturation, respiration are measured at regular intervals, especially for inpatients in intensive care unit (ICU). The static data are mainly patient background and demographic data, including age, weight, height and gender. The similarity computation is done in unsupervised way. It is therefore free from data labeling requirement. However, such patient similarity can be very useful in developing various clinical decision support systems including treatment, medication, hospital admission and diagnosis. Our proposed technique works in three main steps. First, patient similarity is computed for each individual time series. Second, patients are grouped by clustering the static data. Finally, similarities from individual time series are combined and effectively blended with the patient group information to create a nearest neighborhood model. This model consists of a collection of the nearest neighbors for a given patient. We encounter several challenges for this task, including dealing with multi-variate time series data, variable sampling quantities and rates, missing values, and combining time-series with static data. We evaluate the proposed technique on a real patient database on two target features, namely, ‘diagnosis’ and ‘admission type’. Notable performance is recorded for both targets, achieving f1-score as high as 0.8. We believe this technique can effectively combine different types of clinical data and develop an efficient unsupervised framework for computing patient similarity to be utilized for clinical decision support systems.
Analysis of technology adoption model on health monitoring via smartwatches and fitness bands across generations in Indonesia

With Indonesia's increasingly aging population, emerges a social burden that is the growing need for elderly healthcare---a burden that can be eased with the utilization of smartwatches and fitness bands. To facilitate and encourage said utilization among various age groups, this research investigates dominant factors in the continued intention to use smartwatches and fitness bands, along with its acceptance models, for people in different generation categories: Baby Boomers, Generation X, and Generation Y, developed using structural equation modeling. This model was validated with 327 survey samples collected from a population of people aged 17 to 74 years old. The results show that six hypotheses, based on SWAM, were accepted on all generations: that PSR negatively affects customer PEOU, PR negatively affects customer PEOU, health negatively affects customer PU, PSR negatively affects customer PU, PSR negatively affects customer IU, and PR negatively affects customer IU.
Interactive Clustering

In this survey, 105 papers related to interactive clustering were reviewed according to seven perspectives: (1) on what level is the interaction happening, (2) which interactive operations are involved, (3) how user feedback is incorporated, (4) how interactive clustering is evaluated, (5) which data and (6) which clustering methods have been used, and (7) what outlined challenges there are. This article serves as a comprehensive overview of the field and outlines the state of the art within the area as well as identifies challenges and future research needs.
Automatic Event Log Abstraction to Support Forensic Investigation

Abstraction of event logs is the creation of a template that contains the most common words representing all members in a group of event log entries. Abstraction helps the forensic investigators to obtain an overall view of the main events in a log file. Existing log abstraction methods require user input parameters. This manual input is time consuming due to the need to identify the best parameters, especially when a log file is large. We propose an automatic method to facilitate event log abstraction avoiding the need for the user to manually identify suitable parameters. We model event logs as a graph and propose a new graph clustering approach to group log entries. The abstraction is then extracted from each cluster. Experimental results show that the proposed method achieves superior performance compared to existing approaches with an F-measure of 95.35%.
Electronic bracelet to facilitate navigation in smartphones to people with motor and visual impairment

In this paper, we analyze the physical characteristics of a user with both visual and motor impairment, as well as the user's context of smartphone use. Based on these factors, we designed a bracelet to facilitate navigation through gestures that are easy to do by users with motor and visual impairment. We present the low fidelity prototype of the bracelet and the proposed user gestures.
VR salsa: learning to dance in virtual reality

VR Salsa is a virtual reality environment designed to teach users to dance salsa so they can memorize the basic steps and execute them naturally inside a sequence. This is accomplished through the visual representation of the basic steps using an avatar and spherical volumes that describe the movements the feet should follow. We show how previous work on motor learning can be applied to this field. The result is an interface that successfully teaches basic salsa dance moves, that is both comfortable and entertaining according to users.
Song Recommendation System Using Collaborative Filtering Methods

Currently, digital online music increase significantly, both in terms of content and users. Increasing the number of digital music content every month conduce a lot of song catalog data and becoming unstructured and making it difficult for users to choose the songs they want to listen to. To make it easier for users to optimize a large number of subscribed music catalogs, a user-centric music recommendation system is needed that allows users to be able to manage catalogs of digital music content according to their needs. This study examines how to implement song recommendation system using collaborative filtering method in digital online music. This study uses 20,000 users, 6,000 songs and 470,000 transactions rating. Through those research, it is discovered that user-based collaborative technique that could make one system for clients will gather those playlist they really want to hear.
Automatic Joint Calibration of odometry and sensor parameters

Robotic calibration allows for the fusion of data from multiple sensors such as odometers, cameras, and lidars by providing appropriate transformational relationships between the corresponding reference frames. For wheeled robots equipped with exteroceptive sensors, calibration entails learning the motion model of the sensor or the robot in terms of the odometric data, and must generally be performed prior to performing tasks such as simultaneous localization and mapping (SLAM). Within this context, the current trend is to carry out simultaneous calibration of odometry and sensor without the use of any additional hardware. Building upon the existing simultaneous calibration algorithms, we put forth a robust joint calibration methodology using scan matching framework that can handle outliers due to non-systematic errors in an automated manner. Leveraging the alternating minimization technique, the proposed approach not only has superior performance as compared to the state-of-the-art methods but also does not require any manual trimming of outliers. Detailed experiments are performed to demonstrate the accuracy, usefulness, and flexibility of the proposed scheme.