nils-herrmann/clean_scirepeval huggingface dataset:
Role Of Ethics In Modern Business Paradigm
Venue: Think India
Year: 2019

Business ethics is the study of proper business policies and practices regarding potentially controversial issues such as corporate governance, Insider trading, bribery, discrimination, corporate social responsibility and fiduciary responsibilities .Business ethics simply we mean that the application of ethics in business. The study concentrates on how the modern businesses are accelerated by applying the code of conduct in the environment of the business. The article discusses the survival of modern in the present society. The results of this study would help the modern industries in achieving their targeted result in a smooth way. The existing companies can improve their practices and new business can comply with the results for better performance. This article also describes the ethical issues, which are vital to solving the problems related to business, and to give short preface to the moral issues drawn in the management of explicit problem areas in business.
Collaborative Multi Agent Dialogue Model Training Via Reinforcement Learning
Venue: SIGdial
Year: 2019

Some of the major challenges in training conversational agents include the lack of large scale data of real world complexity, defining appropriate evaluation measures, and managing meaningful conversations across many topics over long periods of time. Moreover, most works tend to assume that the conversational agent's environment is stationary, a somewhat strong assumption. To remove this assumption and overcome the lack of data, we take a step away from the traditional training pipeline and model the conversation as a stochastic collaborative game. Each agent (player) has a role "assistant" "tourist" "eater" etc. and their own objectives, and can only interact via language they generate. Each agent, therefore, needs to learn to operate optimally in an environment with multiple sources of uncertainty (its own LU and LG, the other agent's LU, Policy, and LG) In this work, we present the first complete attempt at concurrently training conversational agents that communicate only via self generated language and show that they outperform supervised and deep learning baselines.
Katie J. Patterson, Understanding metaphor through corpora: A case study of metaphors in nineteenth century writing (Routledge Advances in Corpus Linguistics) New York: Routledge, 2018. Pp. xv 236.
Venue: Journal of Linguistics
Year: 2019

elicitation tools. Finally, this collection puts forward proposals and improvements for future research at the end of each chapter, inspiring and kindling more research in the field. MSL is clear, concise and coherent. It makes an outstanding contribution to the field of motion event typology, both theoretically and empirically. It is highly recommended for graduates as well as researchers devoted to the study of relevant fields.
The relationship between emotional intelligence maximizing tendencies and business students perceptions of cheating
Year: 2018

Cheating in college is a serious and increasing phenomenon. Cheating among business students is even more concerning. Significant research investigated the psychological determinants of cheating. The current study investigates emotional intelligence and maximizing tendencies as potentially related to cheating ethics perception among business students. A sample of undergraduate business students in a large university was surveyed. The results indicate that students who are more emotionally intelligent and those scoring high on maximizing tendencies perceived cheating actions as more unethical compared to other students. Several demographic differences also appeared.
Grief in the workplace
Year: 2009

What do workplaces do when an employee is bereaved? What, if any, support and special provision do they make? The Irish Hospice Foundation surveyed 34 Irish organisations to explore their policies and procedures for supporting bereaved employees. While all the organisations had experienced employee related bereavement in the previous 12 months, only four had any kind of formal, written policy. The majority made some kind of provision for compassionate leave, but this varied widely, and decisions about further leave and support were sometimes left to line managers' discretion. This article outlines the key findings from the survey and suggests a template that could be adapted by workplaces to provide a clear and consistent bereavement policy that would benefit the organisation, line managers and the individual employee alike.
Identification of Single Nucleotide Non coding Driver Mutations in Cancer
Venue: Front. Genet.
Year: 2018

Recent whole genome sequencing studies have identified millions of somatic variants present in tumor samples. Most of these variants reside in non coding regions of the genome potentially affecting transcriptional and post transcriptional gene regulation. Although a few hallmark examples of driver mutations in non coding regions have been reported, the functional role of the vast majority of somatic non coding variants remains to be determined. This is because the few driver variants in each sample must be distinguished from the thousands of passenger variants and because the logic of regulatory element function has not yet been fully elucidated. Thus, variants prioritized based on mutational burden and location within regulatory elements need to be validated experimentally. This is generally achieved by combining assays that measure physical binding, such as chromatin immunoprecipitation, with those that determine regulatory activity, such as luciferase reporter assays. Here, we present an overview of in silico approaches used to prioritize somatic non coding variants and the experimental methods used for functional validation and characterization.
Recomendaciones eticas para la toma de decisiones dificiles en las unidades de cuidados intensivos ante la situacion excepcional de crisis por la pandemia por COVID 19: revision rapida y consenso de expertos
Venue: Medicina Intensiva
Year: 2020

In view of the exceptional public health situation caused by the COVID 19 pandemic, a consensus work has been promoted from the ethics group of the Spanish Society of the Spanish Society of Intensive, Critical Medicine and Coronary Units (SEMICYUC) with the objective of finding some answers from ethics to the crossroads between the increase of people with intensive care needs and the effective availability of means. In a very short period, the medical practice framework has been changed to a "catastrophe medicine" scenario, with the consequent change in the decision making parameters. In this context, the allocation of resources or the prioritization of treatment become crucial elements, and it is important to have an ethical reference framework to be able to make the necessary clinical decisions.For this, a process of narrative review of the evidence has been carried out, followed by u. Unsystematic consensus of experts, which has resulted in both the publication of a position paper and recommendations from SEMICYUC itself, and the consensus between 18 scientific societies and 5 institutes chairs of bioethics and palliative care of a framework document of reference for general ethical recommendations in this context of crisis.
Facile preparation of multifunctional Fe3O4@SiO2@LaVO4:Eu3+ nanocomposites as potential drug carriers
Year: 2016

In this paper, novel Fe 3 O 4 @SiO 2 @LaVO 4 :Eu 3+ composites were successfully synthesized with a two step method. Their structure and properties were analyzed and discussed. The as synthesized nanocomposites displayed well defined core shell structures. The particle size of the composites is about 200 nm which consists of the magnetic core with about 180 nm in diameter and a silica shell with an average thickness of about 20 nm. Significantly, the composites exhibited a high saturation magnetization (29.40 emu g 1 excellent luminescence properties and high specific surface area (34.03 m 2 g 1 which endow the nanoparticles with great potential applications in drug targeting, bioseparation and diagnostic analysis.
The Nerves of the Adductor Canal and the Innervation of the Knee: An Anatomic Study
Venue: Regional Anesthesia Pain Medicine
Year: 2016

Adductor canal block contributes to analgesia after total knee arthroplasty. However, controversy exists regarding the target nerves and the ideal site of local anesthetic administration. The aim of this cadaveric study was to identify the trajectory of all nerves that course in the adductor canal from their origin to their termination and describe their relative contributions to the innervation of the knee joint.  After research ethics board approval, 20 cadaveric lower limbs were examined using standard dissection technique. Branches of both the femoral and obturator nerves were explored along the adductor canal and all branches followed to their termination.  Both the saphenous nerve (SN) and the nerve to vastus medialis (NVM) were consistently identified, whereas branches of the anterior obturator nerve were inconsistently present. The NVM contributed significantly to the innervation of the knee capsule, through intramuscular, extramuscular, and deep genicular nerves. The SN had a relatively more modest contribution through superficial infrapatellar and posterior branches as well as contributing to the origin of the deep genicular nerves.  The results suggest that both the SN and NVM contribute to the innervation of the anteromedial knee joint and are therefore important targets of adductor canal block. Given the site of exit of both nerves in the distal third of the adductor canal, the midportion of the adductor canal is suggested as an optimal site of local anesthetic administration to block both target nerves while minimizing the possibility of proximal spread to the femoral triangle.
Marijuana use and service utilization among adolescents 7 years post substance use treatment.
Venue: Drug and alcohol dependence
Year: 2016

In an environment of increasingly liberal attitudes towards marijuana use and legalization, little is known about long term trajectories of marijuana use among clinical samples of adolescents, and how these trajectories relate to health services utilization over time.  Latent growth curve analysis was used to identify distinct trajectories of marijuana use in a clinical sample of adolescents (N=391) over 7 years post substance use treatment in an integrated health system. We examined psychiatric problems and polysubstance use associated with the identified trajectory groups using general linear models. Nonlinear mixed effects logistic regressions were used to examine associations between health services use and the trajectory groups.  We identified three marijuana use trajectory groups: (1) Abstinent (n=117) (2) Low/Stable use (n=174) and (3) Increasing use (n=100) Average externalizing and anxiety/depression scores were significantly lower over time for the Abstinent group compared to the Increasing and Low/Stable groups. The Low Stable and the Increasing group had fewer psychiatric visits over time (p<0.05) and the Low/Stable group used more substance use treatment services over time compared with the Abstinent group (p<0.001)  Treated adolescents showed distinct marijuana use patterns, one of which indicated a group of adolescents at risk of increased use over time. These individuals have greater psychiatric and polysubstance use over time, but may not be accessing needed services.
Learning to Cooperate: Application of Deep Reinforcement Learning for Online AGV Path Finding
Venue: AAMAS
Year: 2020

Multi agent path finding (MAPF) naturally exists in applications like picking up and dropping off parcels by automated guided vehicles (AGVs) in the warehouse. Existing algorithms, like conflictbased search (CBS) windowed hierarchical cooperative A* (WHCA) and other A* variants, are widely used to find the shortest paths in different manners. However, in real world environments, MAPF cases are dynamically generated and need to be solved in real time. In this work, a decentralized multi agent reinforcement learning (MARL) framework with multi step ahead tree search (MATS) strategy is proposed to make efficient decisions. Through performing experiments on a 30 x 30 grid world and a real world warehouse case, our proposed MARL policy is proved to be capable of: 1) scaling to a large number of agents in real world environment with online response time within acceptable levels; 2) outperforming existing algorithms with shorter path length and solution time, as the number of agents increases.
Aero optical effects simulation technique for starlight transmission in boundary layer under high speed conditions
Year: 2020

Aero optical effects for starlight transmission in the high speed flow field will reduce the accuracy of the star sensor on an aircraft. Numerical simulations for aero optical effects usually require plenty of calculations, which cause difficulties when designing a celestial navigation system for a high speed aircraft. In this study, an Aero Optical Simulator For Starlight Transmission (AOSST) in the boundary layer is developed. It effectively reduces the computational burden compared to that of the widely used CFD simulation, and it achieves satisfactory accuracy. In this simulator, gas ellipsoids satisfying certain design rules are used to simulate coherent density structures in boundary layers. Design rules for the gas ellipsoids are found from published experimental and high fidelity CFD simulation results. The generated wavefront distortion by AOSST is anchored with the scale law for aero optical distortion in the boundary layer by determining some control parameters, which enables the simulator to output reliable results over a wide range of flight states. Four numerical examples are provided to verify the performance of AOSST. The results demonstrate that AOSST is able to simulate the directional dependence of aero optical distortions in boundary layers, the variation trend of distorted wavefront shapes with Reynolds number, and the grayscale distribution on the disturbed star map.
Between instrumental and developmental learning: ambivalence in student values and identity positions in marketized UK higher education
Year: 2015

The move towards a market driven HE system in the UK and active policy promotion of students as consumers has generated much commentary on the ways in which students' expectations and experiences have been transformed. This article introduces and develops a conceptualization of contemporary higher students' views of their relationship to higher education within the new institutional conditions of marketization in the UK. This is based on a UK based study which examined at the impacts of recent reforms on students' attitudes to HE, this study utilizes the concept of social ambivalence to illustrate the complexity of their perspectives. Focusing on three key areas in which ambivalence frames attitudes and perceptions, it shows that students' values and approaches are often characterized by competing and co existent positions. Whilst the study found evidence of instrumental goals and values, often in contrast with developmental ones, there was also a discernible ambivalent ground between the two. The article argues that this may be largely influenced by the wider context of marketized higher education also operating at a time of wider structural changes.
Precision Agriculture Techniques and Practices: From Considerations to Applications
Venue: Sensors
Year: 2019

Internet of Things (IoT) based automation of agricultural events can change the agriculture sector from being static and manual to dynamic and smart, leading to enhanced production with reduced human efforts. Precision Agriculture (PA) along with Wireless Sensor Network (WSN) are the main drivers of automation in the agriculture domain. PA uses specific sensors and software to ensure that the crops receive exactly what they need to optimize productivity and sustainability. PA includes retrieving real data about the conditions of soil, crops and weather from the sensors deployed in the fields. High resolution images of crops are obtained from satellite or air borne platforms (manned or unmanned) which are further processed to extract information used to provide future decisions. In this paper, a review of near and remote sensor networks in the agriculture domain is presented along with several considerations and challenges. This survey includes wireless communication technologies, sensors, and wireless nodes used to assess the environmental behaviour, the platforms used to obtain spectral images of crops, the common vegetation indices used to analyse spectral images and applications of WSN in agriculture. As a proof of concept, we present a case study showing how WSN based PA system can be implemented. We propose an IoT based smart solution for crop health monitoring, which is comprised of two modules. The first module is a wireless sensor network based system to monitor real time crop health status. The second module uses a low altitude remote sensing platform to obtain multi spectral imagery, which is further processed to classify healthy and unhealthy crops. We also highlight the results obtained using a case study and list the challenges and future directions based on our work.
Cancer incidence and mortality patterns in Europe: Estimates for 40 countries and 25 major cancers in 2018.
Venue: European journal of cancer
Year: 2018

Europe contains 9% of the world population but has a 25% share of the global cancer burden. Up to date cancer statistics in Europe are key to cancer planning. Cancer incidence and mortality estimates for 25 major cancers are presented for the 40 countries in the four United Nations defined areas of Europe and for Europe and the European Union (EU 28) for 2018.  Estimates of national incidence and mortality rates for 2018 were based on statistical models applied to the most recently published data, with predictions obtained from recent trends, where possible. The estimated rates in 2018 were applied to the 2018 population estimates to obtain the estimated numbers of new cancer cases and deaths in Europe in 2018.  There were an estimated 3.91 million new cases of cancer (excluding non melanoma skin cancer) and 1.93 million deaths from cancer in Europe in 2018. The most common cancer sites were cancers of the female breast (523,000 cases) followed by colorectal (500,000) lung (470,000) and prostate cancer (450,000) These four cancers represent half of the overall burden of cancer in Europe. The most common causes of death from cancer were cancers of the lung (388,000 deaths) colorectal (243,000) breast (138,000) and pancreatic cancer (128,000) In the EU 28, the estimated number of new cases of cancer was approximately 1.6 million in males and 1.4 million in females, with 790,000 men and 620,000 women dying from the disease in the same year.  The present estimates of the cancer burden in Europe alongside a description of the profiles of common cancers at the national and regional level provide a basis for establishing priorities for cancer control actions across Europe. The estimates presented here are based on the recorded data from 145 population based cancer registries in Europe. Their long established role in planning and evaluating national cancer plans on the continent should not be undervalued.
Bio Inspired Speed Curve Optimization and Sliding Mode Tracking Control for Subway Trains
Venue: IEEE Transactions on Vehicular Technology
Year: 2019

Operation optimization for modern subway trains usually requires the speed curve optimization and speed curve tracking simultaneously. For the speed curve optimization, a multi objective seeking issue should be addressed by considering the requirements of energy saving, punctuality, accurate parking, and comfortableness at the same time. But most traditional searching methods lack in efficiency or tend to fall into the local optimum. For the speed curve tracking, the widely applied proportional integral differential (PID) and fuzzy controllers rely on complicated parameter tuning, whereas robust adaptive methods can hardly ensure the finite time convergence strictly, and thus are not suitable for applications in fixed time intervals of trains. To address the above mentioned two problems, this paper presents a novel approach for speed curve seeking and tracking control. First, we present the random reinforcement genetic algorithm (GA) algorithm to avoid the local optimum efficiently. Then, a sliding mode controller is developed for speed curve tracking with bounded disturbance. The Lyapunov theory is adopted to prove that the system can be stabilized in the finite time. Finally, using the real datasets of Yizhuang Line in Beijing Subway, the proposed approach is validated, demonstrating its effectiveness and superiorities for the operation optimization.
The evolution of phosphotriesterase for decontamination and detoxification of organophosphorus chemical warfare agents.
Venue: Chemico biological interactions
Year: 2019

The organophosphorus chemical warfare agents were initially synthesized in the 1930's and are some of the most toxic compounds ever discovered. The standard means of decontamination are either harsh chemical hydrolysis or high temperature incineration. Given the continued use of chemical warfare agents there are ongoing efforts to develop gentle environmentally friendly means of decontamination and medical counter measures to chemical warfare agent intoxication. Enzymatic decontamination offers the benefits of extreme specificity and mild conditions, allowing their use for both environmental and medical applications. The most promising enzyme for decontamination of the organophosphorus chemical warfare agents is the enzyme phosphotriesterase from Pseudomonas diminuta. However, the catalytic activity of the wild type enzyme with the chemical warfare agents falls far below that seen with its best substrates, and its stereochemical preference is for the less toxic enantiomer of the chiral phosphorus center found in most chemical warfare agents. Rational design efforts have succeeded in the dramatic improvement of the stereochemical preference of PTE for the more toxic enantiomers. Directed evolution experiments, including site saturation mutagenesis, targeted error prone PCR, computational design, and quantitative library analysis, have systematically improved the catalytic activity against the chemical warfare nerve agents. These efforts have resulted in greater than 4 orders of magnitude improvement in catalytic activity and have led to the identification of variants that are highly effective at detoxifying both G type and V type nerve agents. The best of these variants have the ability to prevent intoxication when delivered as a post exposure treatment for VX and as a pre exposure treatment for G agent intoxication with observed protective factors up to 60 fold. Combining the best variant, H257Y/L303T, with a PCB polymer coating has enabled the development of a long lasting circulating prophylactic treatment that is highly effective against sarin.