Miracle-dz/UniFAR-FTUs huggingface dataset:
Attitudes, Perceptions and Behaviours associated with Hospital Admission Avoidance in High Risk Patients

Background There is little evidence documenting the attitudes, experiences and behavioural factors of high risk patients that are associated with avoiding hospital. Aim To explore the health, health care management and behavioural factors that contributes to enabling high risk patients to avoid unplanned hospital admissions. Design & Setting An in-depth qualitative interview study with patients who were registered on the Northumberland High Risk Patient Programme (NHRPP), in Northumberland, UK. Methods Thirty participants took part in the study; of which twenty-one were high risk patients and nine were carers, spouses or relatives. A grounded theory approach was used to explore themes that emerged from the semi-structured interviews. Results The majority of patients described having trust and confidence in their health care providers, and continuity of care was important to patients. Participants described physical enablers that helped them avoid hospital including medication, living aids and resting, however, the benefit of these may be challenged by patient decision making. Participants felt that support networks of family and friends helped them avoid hospital, although, the strain on the spouse should be considered. The strategies that patients used to cope with their health conditions included acceptance and positive reinterpretation and growth. Conclusion Reinforcing the importance of the physical enablers, as well as support networks to patients, carers and healthcare providers could help patients avoid hospital. Highlighting the coping strategies that patients use could help patients manage their health, while promoting continuity of care will also contribute to helping high risk patients avoid unplanned hospital admissions.
Urban-Rural Inequality of Opportunity in Health Care in China

This paper investigates the urban-rural inequality of opportunity in health care in China based on the theory of the EOp of Roemer (1998). Following the compensation principle proposed by Fleurbaey and Schokkaert (2011), this paper decomposes the fairness gap in the urban-rural health care utilization. The results shows that the ratios of the fairness gap to are 1.167 during 1997-2000 and 1.744 during 2004-2006. It implies that the degree of the essential inequity is underestimated. Meanwhile, upgrading the urban-rural reimbursement ratios is probably not sufficient to eliminate the inequality of opportunity in health care utilization between urban and rural residents. Under background of urban-rural dualistic social structure and the widening of urban-rural income gap, the pro-disadvantage policies will be more effective to promote the equality of opportunity in health care.
Multivariate Bernoulli Logit-Normal Model for Failure Prediction

The failures among connected devices that are geographically close may have correlations and even propagate from one to another. However, there is little research to model this prob- lem due to the lacking of insights of the correlations in such devices. Most existing methods build one model for one de- vice independently so that they are not capable of captur- ing the underlying correlations, which can be important in- formation to leverage for failure prediction. To address this problem, we propose a multivariate Bernoulli Logit-Normal model (MBLN) to explicitly model the correlations of devices and predict failure probabilities of multiple devices simulta- neously. The proposed method is applied to a water tank data set where tanks are connected in a local area. The results indicate that our proposed method outperforms baseline ap- proaches in terms of the prediction performance such as ROC.
ON THE USE OF HIGH-ORDER NUMERICAL METHODS FOR DNS AND LES OF COMPRESSIBLE ISOTROPIC TURBULENCE by

Title of Project: On the use of high-order numerical methods for DNS and LES of compressible isotropic turbulence Project supervised by: Prof. Abdellah Hadjadj Department of Mechanical Engineering The primary objective of this project is to modify a recently developed high order low dissipative multiscale 3-D Navier stokes code by B. Sjogreen(LLNL) and H. C. Yee(Nasa Ames) to incorporate Large Eddy Simulation as the turbulence modeling. The anisotropic part of the SGS stress is modeled by two ways ; Smagorinsky model and Germano-Lilly model. The isotropic part of the subgrid scale stress is modeled using Yozhizawa model. For the present simulations, high-order such as 8th, 6th compact and 4th order schemes are used. Direct numerical simulation is conducted for the case of homogenous isotropic turbulence in a periodic box with 128 grids in each directions. The results are filtered and are compared with the the solution obtained by the Large eddy simulation using both Smagorinsky and Germano-Lilly model for the anisotropic part of SGS term. For LES, 64 grids in all three directions are used. Statistical quantities like root mean square values of the density, temperature , pressure ,velocity derivative skewness etc are plotted. Temporal variation of turbulent kinetic energy, enstrophy, Reynolds number, Taylor microscale etc are plotted and the LES results are matching well with the filtered DNS results.
Exenatide regulates pancreatic islet integrity and insulin sensitivity in baboons.

The glucagon-like peptide 1 receptor agonist exenatide improves glycemic control by several and not completely understood mechanisms. Herein, we examined the effects of chronic intravenous exenatide infusion on insulin sensitivity, β- and α-cell function and relative volumes, islet cell apoptosis and replication in nondiabetic non-human primates (baboons). At baseline, baboons received a 2-step hyperglycemic clamp followed by an L-arginine bolus (HC/A). After HC/A, baboons underwent a partial pancreatectomy (tail removal) and received a continuous exenatide (n = 12) or saline (n = 12) infusion for 13 weeks. At the end of treatment, HC/A was repeated and the remnant pancreas (head-body) harvested. Insulin sensitivity increased dramatically after exenatide treatment and was accompanied by a decrease in insulin and C-peptide secretion, while the insulin secretion/insulin resistance (disposition) index increased by approximately 2-fold. β-, α-, and δ-cell relative volumes in exenatide-treated baboons were significantly increased compared to saline-treated controls, primarily as the result of increased islet cell replication. Features of cellular stress and secretory dysfunction were present in islets of saline-treated baboons and absent in islets of exenatide-treated baboons. In conclusion, chronic administration of exenatide exerts proliferative and cytoprotective effects on β-, α-, and δ-cells and produces a robust increase in insulin sensitivity in non-human primates.
Towards easy program migration using language virtualization

Migrating programs between language versions is a daunting task. A developer writes a program in a particular version of a language and cannot foresee future language changes. In this article, we explore a solution to gradual program migration based on virtualization at the programming language level. Our language virtualization approach adds a backwards-compatibility layer on top of a recent language version, allowing developers to load and run old programs on the more recent infrastructure. Developers are then able to migrate the program to the new language version or are able to run it as it is. Our virtualization technique is based on a dynamic module implementation and code intercession techniques. Migrated and non-migrated parts co-exist in the meantime allowing an incremental migration procedure. We validate it by migrating legacy Pharo programs, MuTalk and Fuel.
CMAR_A_213432 8799..8806

*These authors contributed equally to this work Purpose: Post-hepatectomy liver failure (PHLF) is a severe complication in hepatocellular carcinoma (HCC) patients who have undergone hepatectomy. This research aimed to investigate the combination of albumin–bilirubin (ALBI) score and aspartate aminotransferaseplatelet ratio index (APRI) as a novel approach in predicting PHLF risk in hepatitis B virus (HBV)-related HCC patients. Patients and methods: HBV-related HCC patients who underwent hepatectomy from January 2006 to October 2013 were enrolled in this study. A novel model was constructed using a combination of ALBI and APRI scores to predict PHLF risk, and the prognostic value of the model was evaluated and compared with Child-Pugh (C-P) grade, ALBI score and APRI score. Results: A total of 1,055 HCC patients were retrospectively studied, which included 151 experienced PHLF. Univariable and multivariate analyses showed that the ALBI and APRI scores were independent predictors of PHLF. The area under the ROC curve (AUC) of the ALBI score, APRI score, and C-P grade was 0.717, 0.720, and 0.602, respectively, with AUC (ALBI) > AUC (C-P) (P <0.001) and AUC (APRI) > AUC (C-P) (P <0.001). After ALBI was associated with APRI, the AUC (ALBI-APRI) was 0.766, and AUC (ALBIAPRI) > AUC (ALBI) (P <0.001), AUC (ALBI-APRI) > AUC (APRI) (P =0.047). Our results indicated that ALBI and APRI scores had higher discriminatory abilities than C-P grade in predicting the risk of PHLF, and the ALBI-APRI model could enhance the capability of predicting PHLF compared to ALBI or APRI alone. Conclusion: ALBI-APRI score is a novel and effective predictive model of PHLF for HBVrelated HCC patients, and its accuracy in predicting the risk of PHLF is better than that of CP, ALBI and APRI scores.
2019 1 Quality assessment 1 . 1 Time complexity

Assume that n is the number of the vertices, d the average degree of the graph and k the number of communities in the graph before the refinement step. We assume that the graph is stored in the edge adjacency list form. This means, given a node u, we can find whether v is a neighbor of u or not in at most O(du) time and in O(d) time on average. Then ρ(u, v) for a pair (u, v) can be computed in O(d) time and maximum ρ(u, v) for a fixed u or v in O(d) time. Thus, the procedure CommGenerate would take O(nd) time. On the other hand the procedure CommRefine would take O(nk) time. Hence, the average complexity of NPCD algorithm is O(nd) +O(nk) = O(nd) or O(nk) as the case may be. To understand the actual speed of NPCD we run it on random networks with order (number of nodes) ranging from 10 to 10. We generate these networks with the command sample gnp(n, p = 5/n) of igraph package on R platform, with n in the above range. The actual running time in seconds is plotted in Fig. 1. It can be seen that NPCD runs super-linearly on this kind of networks.
Dirty hands and the romance of the ticking bomb terrorist: a Humean account

On Michael Walzer’s influential account, ‘dirty hands’ characterizes the political leader’s choice between absolutist moral demands (to abstain from torture) and consequentialist political reasoning (to do what is necessary to prevent the loss of innocent lives). The impulse to torture a ‘ticking bomb terrorist’ is therefore at least partly pragmatic, straining against morality, while the desire to uphold a ban on torture is purely and properly a moral one. I challenge this ‘Machiavellian’ view by reinterpreting the dilemma in the framework of the Humean theory of justice and moral sentiment. By interpreting the ticking bomb scenario as a dramatic narrative, I argue that it appeals to properly moral sensibilities, which speak in favour of the use of force against the terrorist. The absolute ban on torture, by contrast, is an ‘artificial virtue’ and a product of political prudence. On this account, the ticking bomb terrorist dilemma therefore imposes a different burden on the political leader from Walzer’s version: an ethic of political responsibility demands that the political leader be prepared to sacrifice her moral soul by upholding the law against moral but politically imprudent demands to break it; while the ticking bomb ‘romance’ appeals to her feelings of compassionate moral concern towards particular individuals. She dirties her hands morally, not by authorizing torture, but by allowing the terrorist’s bomb to detonate and take the lives of the innocent.
Recursive LSTM Tree Representation for Arc-Standard Transition-Based Dependency Parsing

We propose a method to represent dependency trees as dense vectors through the recursive application of Long Short-Term Memory networks to build Recursive LSTM Trees (RLTs). We show that the dense vectors produced by Recursive LSTM Trees replace the need for structural features by using them as feature vectors for a greedy Arc-Standard transition-based dependency parser. We also show that RLTs have the ability to incorporate useful information from the bi-LSTM contextualized representation used by Cross and Huang (2016) and Kiperwasser and Goldberg (2016b). The resulting dense vectors are able to express both structural information relating to the dependency tree, as well as sequential information relating to the position in the sentence. The resulting parser only requires the vector representations of the top two items on the parser stack, which is, to the best of our knowledge, the smallest feature set ever published for Arc-Standard parsers to date, while still managing to achieve competitive results.
Effective Analysis on Matched Filter Technique in Cognitive Radio

In cognitive-radio networks, the spectrum sensing mechanism aims to sense the idle spectrum-channels in virtue to utilize the RF-spectrum more effectively. Distinct methodologies have playing vital role in sensing criteria, alike as matched filter, feature detection and energy-detection. These sensing approaches are defined by sensing-threshold that plays the crucial role in performance of sensing. Most of existent models utilized the static-threshold. Nevertheless, the noise was random; thence the absolute-threshold should be effective. This paper suggested an efficient approach with dynamic and estimated sensing-threshold to maximize the efficiency level of sensing mechanism. The typical matchedfilter approach with the dynamic-threshold is simulated as well as its outcomes are correlated to alternative existent techniques.
An Overview on Opinion Mining Techniques and Sentiment Analysis

Now a days, customers opinions are plays the major role in the E-commerce applications such as Flipkart, Amazon, eBay etc. Based on customer feedback on the product or seller in the form reviews or comments are the difficulty process by potential buyers to choose a products through online. In the proposed system, the various sentiment analysis techniques to provide a solution in two main areas. 1) Extract customer opinions on specific product or seller. 2) Analyze the sentiments towards that specific product or seller. In this paper, we analyzed several opinion mining techniques and sentiment analysis and their correctness in the categories of opinions or sentiments.
Outbreak Of Klebsiella pneumoniae Carbapenemase-Producing Klebsiella aerogenes Strains In A Tertiary Hospital In China

Purpose This study aimed to evaluate the molecular characteristics and prevalence of clinical carbapenem-resistant Klebsiella aerogenes (CRKA), collected during an outbreak in a Chinese tertiary hospital. Methods Antimicrobial susceptibility test, using 17 antibiotics, was performed on 14 CRKA isolates. The strains were examined for the presence of β-lactamase genes by PCR, and efflux pump phenotype was determined by efflux pump inhibition test. Presence of outer-membrane porins was examined. Clonal relatedness among the isolates was investigated by pulsed-field gel electrophoresis (PFGE). S1 nuclease-PFGE and plasmid incompatibility group analysis were performed to determine plasmids, and the genetic environment of blaKPC-2 was analyzed. Epidemiological data were collected via chart review. Results The 14 CRKA isolates were all resistant to carbapenems; five distinct groups (PFGE types A–E) were observed. All 14 isolates carried the blaKPC-2 gene. S1 nuclease-PFGE indicated the size of blaKPC-2-carrying plasmids to range from 20 kb to 200 kb, and the 14 plasmids belonged to various incompatibility groups. The most frequent genetic environment of blaKPC-2 was Tn1721- blaKPC-2-ΔTn3-IS26. PFGE type A group, including 11 KPC-2-producing clinical isolates, was primarily responsible for dissemination. Conclusion Our findings suggest both transposons and vertical transmission to contribute to the transformation of blaKPC-2. The results strongly suggest strict implementation of infection control of CRKA, in healthcare facilities.
C L ] 2 2 O ct 2 01 9 Transductive Parsing for Universal Decompositional Semantics

We introduce a transductive model for parsing into Universal Decompositional Semantics (UDS) representations, which jointly learns to map natural language utterances into UDS graph structures and annotate the graph with decompositional semantic attribute scores. We also introduce a strong pipeline model for parsing UDS graph structure, and show that our parser can perform comparably while additionally performing attribute prediction.
A Review on Dimension Based Parking System

Parking facilities and management of traffic is the key aspects of crowed cities. In recent times finding parking slots in metropolitan cities is always a crucial task. As number of private car users increases, gradually parking becomes harder in traditional parking system with the issues that deals with the traffic congestion, safety and narrow car parking facilities. This idea of smart parking becomes achievable due to the evolution of IoT. The IoT field has increases the productivity and reliability of infrastructure in urban areas by locating the empty place in parking lots as well as conveying such information to the car owners, many researchers in their various works elaborated significantly the problem of implementing reliable parking guidance and information systems. This study lists out the limitations of the existing parking system and provides research directions in smart parking system.
Masters Thesis: Shaping Methods to Accelerate Reinforcement Learning:

Reinforcement learning (RL) is an attractive solution for deriving an optimal control policy by on-line exploration of the control task. In reinforcement learning there is no need to specify how the task is to be achieved. In fact, RL is a way of programming the agents by specifying a reward function. At every time step, the controller (agent) receives the process (environment) state, takes an action, and consequently the process changes its state. The controller then receives a reward signal indicating the quality of its action, and the whole cycle repeats. The control goal is to maximize the cumulative reward (the return) over the course of interaction. The agent uses the reward to improve its policy, and evetually to find an optimal policy. Conventional reinforcement learning methods are not efficient when the task at hand is too complex to learn from scratch. As a result, these algorithms fail to find the optimal policy, and they may even find a suboptimal policy. This issue raises the need for new methods for reinforcement learning that can handle complex tasks. As humans, we simplify a difficult task, by trying to learn certain simplified versions of the task before trying to solve the original one. The main idea of simplifying the original task can also be used in reinforcement learning. The simplification or abstraction that is used in human learning can help the agent to solve the problem faster and in a more efficient way. The idea of starting from simpler tasks and gradually increasing complexity, until the original task is solved, can also be exploited in RL, where it is called shaping. The idea behind shaping is borrowed from behavioral psychology. The main principle of shaping is to start from a simpler task and gradually increase the complexity until the desired (target) task is solved. There are different approaches to shape a certain task (from easy to challenging); modifying the dynamics, modifying the reward function, modifying the action space, modifying the initial state, extending the time horizon, and finally modifying the internal parameters. Unfortunately, experimental data on how shaping works and how it improves the speed of learning are scarce in the literature. To address this shortcoming, in the first stage of this project, we have implemented different methods of shaping in a gridworld problem. Subsequently , we have investigated the effects of shaping on speeding up the learning process. The gridworld example …
Impact of BMI on the technical difficulty with Laparoscopic total extraperitoneal hernia repair

10) 목적 : 복강경 서혜부 탈장 교정술은 기술적인 어려움으로 인하여 학습곡선이 가파르며 진 입 장벽이 높다 이에 저자들은 복강경 및 개복 탈장 교정술의 수술 난이도를 예측할 수 있 . 는 인자들을 확인하고자 하였다. 방법 : 년 월에서 년 월까지 양산부산대학교병원에서 단측 서혜부 탈장 교정술 2009 1 2013 6 을 시행받은 명의 환자를 대상으로 하였다 서혜부 탈장을 위하여 개복 수술을 시행하 256 . 는 경우 술식을 주로 이용하였고 복강경 수술에서는 전복막외 탈장교정술을 Lichtenstein , 이용하였다 개복 수술군과 복강경 수술군과 임상적 특성을 알아 보았으며 개복 수술과 복 . 10)본 연구는 년도 양산부산대학교병원 임상연구비 지원으로 이루어졌음 2013 . 박병수 유동연 조용훈 김해영 손경모 , , , , 302 강경 수술의 난이도와 관련된 임상 인자들을 분석하였다 수술 난이도가 높은 경우는 수술 . 시간의 분포도에서 상위 이상인 경우 혹은 복강경 수술 중 개복 수술로의 전환이 시 30% , 행된 경우로 정의하였다. 결과 : 서혜부 탈장 환자 명 중 명에서 복강경 탈장교정술을 시행하였으며 명에서 256 98 158 개복 탈장수술을 시행하였다 복강경 수술군에서 평균 연령과 복부 수술의 과거력의 빈도가 . 유의하게 낮았다 수술시간은 개복 수술군 보다 복강경 수술군에서 유의하게 연장 (p<0.05). 되었다 복강경 수술군에서 수술 난이도가 높은 환자에서 체질량지수 (p<0.001). ( 25 ≥ 의 빈도는 로 나와 수술 난이도가 낮은 환자군의 보다 유의하게 높았다 kg/m2) 51.5% 27.7% 수술 난이도에 따라 체질량지수를 비교한 결과 고난이도 환자와 저난이도 환자 (p=0.016). 의 평균 체질량지수는 각각 와 이었다 하지만 개복 수술군 24.9kg/m2 22.4kg/m2 (p=0.001). 에서 수술 난이도와 체질량지수는 통계적 상관성이 없었다 다변량 분석에서 복 (p=0.558). 강경 전복막외 탈장교정술의 수술 난이도와 관련이 있는 독립인자는 체질량지수( 25 ≥ 수술 습득과정 초기 수술 례 으로 분석되었다 반면 개복 수술군에서는 체질량 kg/m2), ( 10 ) . , 지수 와 수술 난이도의 통계학적인 연관관계를 없었다 ( 25 kg/m2) . ≥ 결론 : 복강경 전복막외 탈장교정술에서 체질량지수( 25 kg/m ≥ 2 수술의 초기 습득과정은 ), 수술의 난이도를 가중시키는 독립인자로 분석되었다 그러므로 복강경 탈장 교정술을 도입 . 하는 초기 단계에서 탈장 환자의체질량지수는 술식 선택의 기준 가운데 하나로 적용될 가능 성이 있으며 이에 대한 더 많은 연구가 진행되어야 하겠다 , .
Business Analytics in the Finance Department – A Literature Review

Business analytics has become more and more relevant to practitioners and academics over the past few years. With vast amounts of data from inand outside an organization and the availability of fast enough hardware to process it, all functions in an organization aim to benefit from analytics. We conduct a literature review looking at the finance department, i.e. financial and management accounting, and identify hotspots of current and potential future research. We summarize our findings in a framework for literature classification with the two dimensions accounting activity and rationale for business analytics. On this grid, better organization performance and better decision outcomes for most management accounting activities have been covered the most, while support of strategic and tactical goals as well as obtaining value from data should be considered more in detail by future research.
A Review on Emotion Recognition of Speech Signal using Multiclass SVM

Speech is the most natural form of communication between human beings. In the field of Human Computer Interaction(HCI) speech emotion recognition system is used. Researchers have been trying to develop a system more like human , emotion recognizing robots is an example of it. By using the speech features emotions are recognized from speech signals. Various speech features are MFCC(Mel Frequency Cepstral Coefficient), pitch, energy, intensity, speaking rate, voice quality, etc. Speech has many parameters which have great weightage in recognizing emotion namely prosodic and acoustic features. SVM(Support Vector Machine) is used as a classifier, which is used to classify the different emotions like happy, angry, sad, fear, neutral, etc. With the help of multiclass SVM, obtain more than two emotions.