Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical Characteristics and Treatment of Immune-Related Adverse Events of Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICIs) have been changing the paradigm of cancer treatment. However, immune-related adverse effects (irAEs) have also increased with the exponential increase in the use of ICIs. ICIs can break up the immunologic homeostasis and reduce T-cell tolerance. Therefore, inhibition of immune checkpoint can lead to the activation of autoreactive T-cells, resulting in various irAEs similar to autoimmune diseases. Gastrointestinal toxicity, endocrine toxicity, and dermatologic toxicity are common side effects. Neurotoxicity, cardiotoxicity, and pulmonary toxicity are relatively rare but can be fatal. ICI-related gastrointestinal toxicity, dermatologic toxicity, and hypophysitis are more common with anti- CTLA-4 agents. ICI-related pulmonary toxicity, thyroid dysfunction, and myasthenia gravis are more common with PD-1/PD-L1 inhibitors. Treatment with systemic steroids is the principal strategy against irAEs. The use of immune-modulatory agents should be considered in case of no response to the steroid therapy. Treatment under the supervision of multidisciplinary specialists is also essential, because the symptoms and treatments of irAEs could involve many organs. Thus, this review focuses on the mechanism, clinical presentation, incidence, and treatment of various irAEs.
The Simulation of Atherosclerosis by the 3–Layered Growthing Cylinder

The present study deals with problem of the residual stresses calculations in human blood vessel under pathological growth processes. The vessels are simulated by the thin-walled long circular cylinder. The boundary value problem of the surface growth of an elastic thin-walled vessels is solved. The analytical solution is obtained in terms of velocities of stress strain state parameters. The condition of thinness allows us to study finite displacements of cylinder surfaces by means of infinitesimal deformations. The stress-strain state characteristics are numerically computed and graphically analysed by various mechanical parameters of the pathological growth processes.
Sum-Capacity of Massive MIMO Systems Using Vandermonde Matrices

In this paper, we use a series expansion to calculate the sum-capacity of a massive Multiple-Input MultipleOutput (MIMO) system under propagation environment described by a dominant line-of-sight. The sum-capacity is written as Taylor’s series where each term is a function of the mean trace of k-th power of the channel matrix W. We analytically derive the mean trace of first, second, third, and fourth moments of W. Although the series is infinite, our numerical results show that only a few terms can tightly approximate the exact sum capacity. Numerical results corroborate our analytical expressions.
The Association of Stage 1 Hypertension Defined by the 2017 ACC/AHA Guideline with Stroke and Its Subtypes among Elderly Chinese

Background The 2017 American College of Cardiology and American Heart Association hypertension guideline updated stage 1 hypertension definition as systolic blood pressure range from 130 to 139 mmHg or diastolic blood pressure from 80 to 89 mmHg. However, the association of stage 1 hypertension with stroke and its subtypes among the older population in rural China remains unclear. Methods This population-based cohort study consisted of 7,503 adults aged ≥60 years with complete data and no cardiovascular disease at baseline from rural areas of Fuxin County, Liaoning province, China. Follow-up for the new cases of stroke was conducted from the end of the baseline survey to the end of the third follow-up survey (January 1, 2007–December 31, 2017). Adjusted Cox proportional hazards models were used to estimate hazard ratios and 95% confidence intervals with the normal blood pressure as a reference, and calculated population attributable risk was based on prevalence and hazard ratios. Results During a median follow-up of 12.5 years, we observed 1,159 first-ever incident stroke (774 ischemic, 360 hemorrhagic, and 25 uncategorized). With the blood pressure <120/<80 mmHg as a reference, stage 1 hypertension showed the adjusted hazard ratios (95% confidence intervals) of 1.45 (1.11–1.90) for all stroke, 1.65 (1.17–2.33) for ischemic stroke, and 1.17 (0.74–1.85) for hemorrhagic stroke, respectively. In this study, the population attributable risk values of stage 1 hypertension were 10.22% (2.64%–18.56%) for all stroke and 14.34% (4.23%–25.41%) for ischemic stroke. Conclusion Among adults aged ≥60 years in rural China, stage 1 hypertension defined by 2017 American College of Cardiology and American Heart Association hypertension guideline was independently associated with the increased risk of all stroke and ischemic stroke, excluding hemorrhagic stroke.
Students Satisfaction on Blended Learning in the School of Sport Sciences

Background. Blended learning requires a virtual learning and online environment (VLE), which make available a process for establishing learning communities. The Faculty of Physical Education at the University of Jordan designed a number of courses which incorporate blended learning with contact classes and online components on an e-learning models. Objectives. Of the present study is to investigate if modes of BL possible influence on students’ perceived achievement goals and satisfaction. Methods. The research model is tested using a questionnaire survey. Eighty-three undergraduate sport students participated in the courses (Motor Learning) offered by the University’s Faculty of Physical Education the participants were divided in two groups. Results. Indicated that students were satisfied with blended program and online learning environment; satisfaction was generally high with 83.4%. The results also show that BL rotation type (students rotate between online and traditional content on fixed schedule) significantly affects learning satisfaction. Moreover, the quality of the teaching received the highest satisfaction level where interaction significantly affected self-study. Conclusion. The feedback of students who are amongst the key stake holders is essential to ensure a successful implementation of bended learning.
A Screen Location Method for Treating American Hyphantria cunea Larvae Using Convolutional Neural Network

Chemical control is the major approach to handle the American Hyphantria cunea issue; however, it often causes chemical pollution and resource waste. How to precisely apply pesticide to reduce pollution and waste has been a difficult problem. The premise of accurate spraying of chemicals is to accurately determine the location of the spray target. In this paper, an algorithm based on a convolutional neural network (CNN) is proposed to locate the screen of American Hyphantria cunea. Specifically, comparing the effect of multicolor space-grouping convolution with that of the same color space-grouping convolution, the better effect of different color space-grouping convolution is first proved. Then, RGB and YIQ are employed to identify American Hyphantria cunea screen. Moreover, a noncoincident sliding window method is proposed to divide the image into multiple candidate boxes to reduce the number of convolutions. That is, the probability of American Hyphantria cunea is determined by grouping convolution in each candidate box, and two thresholds (E and Q) are set. When the probability is higher than E, the candidate box is regarded as excellent; when the probability is lower than Q, the candidate box is regarded as unqualified; when the probability is in between, the candidate box is regarded as qualified. The unqualified candidate box is eliminated, and the qualified candidate box cannot exit the above steps until the number of extractions of the candidate box reaches the set value or there is no qualified candidate box. Finally, all the excellent candidate boxes are fused to obtain the final recognition result. Experiments show that the recognition rate of this method is higher than 96%, and the processing time of a single picture is less than 150 ms.
Patient Health Monitoring in ICU using Internet of Things

—In the modern era, IoT has massive application domains in civil and military environments. IoT shelters critical infrastructures such as, defense, healthcare, energy, transportation, and manufacturing under its umbrella. With the advancement of technology and the convergence of multiple technologies, the conception of the Internet of Things (IoT) has evolved. IoT enables various systems to communicate with each other without human involvement. Intensive Care Units (ICU) are a critical domain of medical wards in hospitals, where patients suffering from drastic and fatal injuries and illnesses are treated. Once the patients are in the out-of-danger state, they are either discharged or admitted to a normal ward for further treatment. ICU is divergent in its explicit environment as compared to other healthcare bailiwicks because it includes extraordinary dependency and provisions, relentless care, close observation to rescue a life from an existential threat. This paper is comprised of a comprehensive study and analysis of modern IoT based patient monitoring techniques with their design and security issues in ICU. In the light of analysis, particular challenges in this domain are discovered, and some disadvantages and shortcomings of topical technologies are identiﬁed. In the consideration of those ﬁndings, several suggestions are proposed to improve system efﬁciency and response.
Service Oriented Machine-learning Application for Reconfigurable Predictive Maintenance System

—Successfully deploying AI models for a reconfigurable AI-driven enterprise is a challenge. This work focuses on the design and implementation of a reconfigurable machine learning data analytics tool supporting flexible and automatic configurability in manufacturing. This tool provides a user interface and RESTful API to be used by other components of the architecture for deployment and use of machine learning and statistical models as a service for the purpose of predictive maintenance. This tool supports text classification to label unstructured data and uses machine-learning models based on decision-trees to predict failure of the production machines.
Identification of Risk of Cyberbullying from Social Network Messages

—Social networks have revolutionalized how people communicate. People can create content while others can share, react to, or express opinions about the content. Since communication can take place more freely and more anonymously, social network users are more vulnerable to cyberbullying. The problem is a threat to the victim’s several mental and physical health conditions such as low self-esteem, depression, drug and alcohol abuse, and suicidal thoughts. In Thailand, cyberbullying is a widespread problem as the number of incidents is among the top lists in the world. To increase awareness and try to prevent the problem, this paper presents a method to identify risk of cyberbullying to an individual via an analysis of social network messages in Thai. The presented method collected training data from Twitter and used several machine learning algorithms to classify textual tweets into four cyberbullying categories, i.e. sexual harassment, insult and threat, race and religion, and intelligence, appearance, and social status. An experiment showed that Logistic Regression performed best when the problem of imbalanced data set was handled with the F1 score of 73.89 and accuracy of 73.61. In addition, a tool to visualize cyberbullying incidents of any individual has been implemented. The method and accompanying tool can help to monitor potential risk of cyberbullying to an individual so that appropriate care can be sent in a timely manner.
Embedding quasi-static time series within a genetic algorithm for stochastic optimization: the case of reactive power compensation on distribution systems

This paper presents a methodology for the optimal placement and sizing of reactive power compensation devices in a distribution system (DS) with distributed generation. Quasi-static time series is embedded in an optimization method based on a genetic algorithm to adequately represent the uncertainty introduced by solar photovoltaic generation and electricity demand and its effect on DS operation. From the analysis of a typical DS, the reactive power compensation rating power results in an increment of 24.9% when compared to the classical genetic algorithm model. However, the incorporation of quasi-static time series analysis entails an increase of 26.8% on the computational time required.
Open Government on Disaster Information Management in Regional Disaster Management Agency of South Sulawesi

This study is aimed to discuss open government in the context of disaster information management in Disaster Management Agency (BPBD) of South Sulawesi. The study employs qualitative method and data was collected by interview, document study and observation. The informants of the study are BPBD and NGO which work in the disaster management sector. The result of the study shows that the principles of open government have been implemented in the disaster information management in BPBD, though not covering all stages of information management. The principle of transparency, participation and collaboration have been visible in the stage of collecting disaster information. In contrast, those initial principles are not visible in the stage of classifying information. In the stage of documenting and information service, these are found to be the principle of collaboration. Generally, BPBD does not maintain information transparency via website like others but focuses more on utilizing more accessible and practical media for users and disaster information sources like radios, flags, and social media. The openness of BPBD in disaster information management is influenced by some factors such as: (1) sources of disaster information are provided by various parties beside government (2) BPBD eagers to collaborate with other agencies. Lastly, disaster management needs a wide variety of specific skills.
A Conceptual Discourse on Consumer’s Preference of Brandy

Background: Liquor industry is growing to become a global giant by empowering its competitiveness. Nowadays, alcohol has been accepted and welcomed as a normal part of everyday life with innovatively embedded alcohol development and promotion. Alcohol products consist of a range of offerings including Gin, wine, vodka and Scotch, among which brandy has been gaining higher importance. Objectives: This paper explores the consumers’ preferences for brandy, their knowledge on brandy and also the factors determining the consumer choice on consumption of brandy.This study aims to contribute to the brandy consumer behavior-responsive managerial implications, especially in hospitality industry by identifying the attributes that are perceived important for the marketing of brandy to a large segment of dynamic market. Methods: The academic discourse on this paper includes exploration of multiple dimensions related to the study of consumer behavior. Theories concerning consumer preferences, with specific focus on Reasoned Action Theory, Engel Kollat Blackwell Model, Hybrid Choice Model, Hedonic Price Model, Consumer Perception Factor Model and Conjoint Analysis are reviewed.The study on brandy, along with the differences from other alcoholic beverages, has also been included. Findings: Brandy represents a wide category and the bases of differences among types of brandy are studied along with the review of brandy products available worldwide. This study highlights brandy consumption practices in the world, benefits of brandy consumption and people’s perception towards brandy among other alcoholic beverages. Conclusions: Alcohol is the fastest growing industry and requires consumer preference for the promotions and penetration of the product into the market, and for developingthe product and improving it further.
Towards a Balanced CSR Performance Measurement Framework

In order to evaluate the real contribution of Corporate Social Responsibility (CSR) to a company as well as to its stakeholders, it must be measurable. The difficult task of measuring the results of CSR has been a matter of long discussion both by academics and practitioners. Some of the literature on Corporate Social Responsibility combines CSR with stakeholder theory introducing corporate social performance. The literature has attempted to describe emerging models of the issues that lead to a coherent model of what would represent corporate social performance. However, it is the case that social aspects are ‘‘soft’’ in nature, therefore being difficult to quantify. Innovated methods of performance measurement such as this of Balanced Scorecard has lately been introduced in some companies in their attempt to include non-financial indicators to give more balance and forecasting power to the traditional financial performance assessment system, but the view of Corporate Social Responsibility is rarely taken into account. On the other hand, management frameworks that try to cover social and environmental aspects, such as Global Reporting Initiative (GRI) by
Vendor Managed Inventory System Adaptability: A supply chain management analysis

The VMI (Vendor Managed Inventory) system has been used as a sophisticated logistics system to provide adequate assistance to some large retailers. Despite this, the VMI system is currently limited to the retail industry and does not have access to the VMI system in other industries. In order to make up for this gap, this paper analyzes the feasibility of the VMI system in other industries and companies, and further determines the VMI system as a boost for other industries through three conditions. This article provides sufficient evidence for the research method through case analysis to further determine the feasibility and correctness of the research method. As the results of the study show, companies that meet these three conditions can significantly improve the company's logistics efficiency and reduce the company's storage costs when using the VMI system. Keywords—VMI system; logistics; company efficiency;
On the Nature of Give-idioms*1)

Chang, Kyungchul. 2009. On the Nature of Give-idioms. Linguistic Research 26(3), 129-146. This article explores the nature of those give-idioms which have the variable X, as in give X the boot ('dismiss'). It is argued that these idioms are a phrase-level (or V') category, and that the verb and noun phrase combine to form a predicate. The resulting complex predicate is a basically semantic unit between whose parts an object is interposed. The article proposes an analysis of the unit as a concrete form of constructional idiom. The form is stored in the lexicon as a V' with a specific meaning and is combined with an object at phrasal syntax to form a discontinuous VP. Other syntactic and semantic elaborations on this particular VP are considered cases of overgeneralisation that should be banned by a usage-based model of grammar. (Catholic University of Daegu)
Compost and Vermicompost as Soil Amendments to Immobilize Cu and Cd Under Wheat Growth Conditions

Field experiment was conducted during wheat cropping season on a calcareous soil to assess the efficacy of vermicompost and compost to immobilize copper (Cu) and cadmium (Cd) in soil. The soil amendments applied alone and in combinations with mineral fertilizers to compare their efficacy for metals immobilization. Both of amendments significantly reduced extractable Cu and Cd in soil at wheat harvest. Copper and cadmium fractionation showed significant decreases in the extractable fractions by the vermicompost 47.06% and 98.81% in untreated with heavy metals soil whereas 46.46% and 80.06% in treated soil with heavy metals respectively or compost 22.35% and 79.17% in untreated with heavy metals soil whereas 20.56% and 73.05% in treated soil with heavy metals respectively. Vermicompost and compost amendments enhanced metals immobilization which reduces their expected uptake by plant and subsequent accumulation in the grains of wheat, particularly with vermicompost. In conclusion, the results indicated that compost and vermicompost have great potential to remediate Cu and Cd contaminated soils.
Development, Implementation, and Evaluation of a Faculty Development Workshop to Enhance Debriefing Skills Among Novice Facilitators

Introduction Effective debriefing during simulation-based training (SBT) is critical to promote learning outcomes. Despite debriefing’s central role in learning and various published debriefing methods and techniques, little is known about faculty development structure for debriefing training among novice facilitators. Continuing medical education courses often use simulation-based methods but provide minimal training in debriefing techniques to novice facilitators. We describe the development, implementation, and evaluation of a structured debriefing training workshop for novice facilitators. Methods Designed and conducted by simulation debriefing experts, a debriefing workshop was provided to novice facilitators serving as faculty during the simulation-based Sedation Provider Course (PC) at the 2018 Society of Pediatric Sedation conference. Emphasizing evidence-based key elements of effective debriefing, the workshop was divided into three components: 1) an introductory 30 minute didactic, 2) 75 minutes role modeling of simulated effective and ineffective debriefing 3) 120 minutes repetitive deliberate practice sessions with summative and formative feedback. Effective transfer of learned debriefing skills was assessed during facilitators’ PC debriefing using the Objective Structured Assessment of Debriefing (OSAD) tool, facilitators’ self-efficacy, and PC student learners’ evaluation of facilitator debriefings during the PC. Results Sixteen facilitators participated in the 4-h workshop and the next day served as PC faculty. The median OSAD score was 31 (13-40) for all facilitators. OSAD components with lowest and highest performance were “Establishing Learning Environment” with a median score of 1 (1-5) and “Engagement of Learners,” with a median score of 4.75 (2.5-5). Facilitators' self- assessment in debriefing significantly improved on the 5-point Likert scale pre- and post-workshop, respectively. PC student learners’ evaluations revealed high degrees of satisfaction with debriefing quality. Conclusions A proposed model integrating full-length debriefing and repetitive practice paired with summative and formative feedback provides a feasible and effective approach for debriefing training of novice facilitators for simulation-based educational courses.
Framing effects as a semantic puzzle: Putting the alignment-assumption account to a test

Framing effects are effects of linguistic variation (e.g. stating the amount of lives saved vs. lives lost) on judgments and decisions. This paper deals with a semantic-pragmatic account of framing effects as offered by Geurts’ (2013) alignment-assumption account. The account radically differs from extant accounts by explaining framing effects in terms of counterfactual alternatives and alignment of scales. I report two experiments that tested predictions derived from the alignment-assumption account and that related to the effect of upward- vs. downward entailing comparative quantifiers. The results provide preliminary experimental support for the alignment-assumption account and pose challenges for other accounts of framing effects.
Privacy Delegate: a browser-based tool for privacy self-management in social networks

—This position paper presents a user-centric schema for self-managed privacy that enables users to use a dashboard to find out which user information a social network provider has shared with and to rule the way such a sharing procedure is done, according to some privacy policies set by the user. The proposal is implemented as a browser plug-in and works on the OAuth protocol.