nils-herrmann/clean_scirepeval huggingface dataset:
Effects of Sixteen Month Voice Training of Student Actors Applying the Linklater Voice Method.
Venue: Journal of voice official journal of the Voice Foundation
Year: 2020

This study investigates the perceptual and acoustic changes in student actors' voices after 16 months of Linklater Voice training, which is a holistic method to train actors' voices.  Eleven (n 11) actor students' text and Voice Range Profile (VRP) recordings were analyzed pretraining and 16 months posttraining. From text readings at comfortable performance loudness, both perceptual and acoustic analyses were made. Acoustic measures included sound pressure level (SPL) fundamental frequency (fo) and sound level differences between different frequency ranges derived from long term average spectrum. Sustained vowels [i: [o] and [e] abstracted from the text sample were analyzed for formant frequencies F1 F4 and the frequency difference between F4 and F3. The VRP was registered to investigate SPL of the softest and loudest phonations throughout the voice range.  The perceived pitch range during text reading increased significantly. The acoustic result showed a strong trend toward decreasing in minimum fo, and increasing in maximum fo and fo range. The VRP showed a significant increase in the fo range and dynamics (SPL range) Perceived voice production showed a trend toward phonation balance (neither pressed nor breathy) and darker voice color posttraining.  The perceptual and acoustic analysis of text reading and acoustic measures of VRP suggest that LV training has a positive impact on voice.
Capitalizing on Military Nurse Skills for Second Career Leadership and Staff Development Roles.
Venue: Journal of continuing education in nursing
Year: 2016

Nursing continues to face professional workforce and diversity shortage problems. This article advocates for examining an untapped resource the consideration of applicants for nursing leadership and educational positions in civilian health care organizations. This untapped resource is highly qualified, already retired (or going to be separated) military nurse officers (MNOs) who possess extensive health care knowledge, as well as distinctive ethnicity and gender composition. Clinical educators, as part of the organizational leadership, can play an important role in assisting the MNO civilian position assimilation because they come from a structured and unique cultural environment. Several innovative preparatory strategies are proposed to highlight the organization's support and commitment regarding preselection, recruiting, hiring, and mentoring, including the use of a specific navigational mentor to achieve the necessary acquired cultural assimilation for the MNO's success, satisfaction, and retention.
Four freedom degree single frame magnetic suspension control torque gyroscope
Year: 2014

A four freedom degree single frame magnetic suspension control torque gyroscope can serve as a gesture control execution mechanism of a large satellite, an earth observation platform, a space station and other large spacecrafts and is composed of a four freedom degree magnetic bearing, a high speed motor, a radial and axial integrated sensor, a radial sensor, an upper protective bearing, a lower protective bearing, a central spindle, a wheel body, a base, an upper sensor detection ring, a lower sensor detection ring, a shell, frame central spindles, a frame motor, a frame, mechanical bearings, an angle position sensor and an electric conduction sliding ring. The driving part of the four freedom degree magnetic bearing controls a gyroscope rotor to move in a translational mode and deflect, and the gyroscope rotor moves in a translational mode in the axial direction through the driven part of the four freedom degree magnetic bearing. All the components are compact in layout, the size and the weight are reduced, noise of a system is lowered, the size and the weight of the system are reduced, bearing friction force is eliminated, then the service life of the single frame control torque gyroscope is prolonged, and the control precision of the single frame control torque gyroscope is improved.
Affects of verbal hygiene: the impact of language activism at a Swedish high school
Year: 2020

This paper explores youths' language activism at a Swedish senior high school. Following Cameron (Verbal hygiene, Routledge,  1995) this paper investigates language activism as 'verbal hygiene' with a focus on the social dimension of students' attempts to change how language is used at the school. To capture how the politically motivated language activism came to produce political subjectivities and delineation between social groups, and also to impact the distribution of agency and voice in the local discursive regime, I combine Cameron's (Verbal hygiene, Routledge,  1995) notion of verbal hygiene with recent theorizing on affect (Ahmed in The cultural politics of emotion, Edinburgh University Press, Edinburgh, 2004; Sedgwick in Touching feeling: affect, pedagogy, performativity,  2003; Wetherell in Affect and emotion: a new social science understanding, Sage, London, 2012) Inspired by studies of semiotic landscapes (Jaworski and Thurlow in Semiotic landscapes: language, image, space, Bloomsbury Academic, London, 2011) the data includes posters and other signage in the high school, as well as recordings of naturally occurring interaction and interviews. The analysis shows how shame is pivotal in the processes of language activism at the school and how this activism, being an emancipatory project, both produces political subjectivities as well as new linguistic normativities and hierarchies.
Poly encoder based Task Adaptation for COVID 19 Question Answering System
Year: 2020

In this unprecedented era of COVID 19, there is a huge information need for truthful answers to questions relating to all aspects of the Coronavirus. In this paper, we adapt the PolyEncoder (Humeau et al. 2020) informational retrieval from FAQs. We show that after finetuning the Poly encoder we achieve higher recall at the same level of precision. We compare several models on the task of answer or question selection on evaluation sets and demonstrate superior performance. We make our code publicly available for other researchers to use.
Did I Get the Best Discount? Counterfactual Thinking of Tourism Products
Year: 2018

Current trends in the tourism industry indicate that most potential travelers purchase tourism products from online travel agents that provide price promotions. Even though the range of price promotions often varies, the tourism literature does not address potential travelers' perceptions after purchasing products at various discount rates. This study examined the relationships among different discount rates, temporal distance, and counterfactual thinking a mental undoing of existing outcomes. Results showed that the relationship between discount rate and counterfactual thinking had a U shaped curve. Furthermore, the shape differed by temporal distance. The optimal discount rate for minimizing counterfactual thinking was 29.62% when the reservation was made 15 days prior to departure but rose to 33.33% when the reservation was made three months prior to departure. This study suggested that counterfactual thinking mediates the relationship between discount rate and perceived regret.
Incidental Findings Suggestive of COVID 19 in Asymptomatic Patients Undergoing Nuclear Medicine Procedures in a High Prevalence Region
Venue: The Journal of Nuclear Medicine
Year: 2020

Infection with the novel severe acute respiratory syndrome coronavirus 2 (SARS CoV 2) may remain asymptomatic, leading to under recognition of the related disease, coronavirus disease, 2019 (COVID 19) and to incidental findings in nuclear imaging procedures performed for standard clinical indications. Here, we report about our local experience in a region with high COVID 19 prevalence and dynamically increasing infection rates.  Within the 8 d period of March 16 24, 2020, hybrid imaging studies of asymptomatic patients who underwent 18F FDG PET/CT or 131I SPECT/CT for standard oncologic indications at our institution in Brescia, Italy, were analyzed for findings suggestive of COVID 19. The presence, radiologic features, and metabolic activity of interstitial pneumonia were identified, correlated with the subsequent short term clinical course, and described in a case series.  Six of 65 patients (9% who underwent PET/CT for various malignancies showed unexpected signs of interstitial pneumonia on CT and elevated regional 18F FDG avidity. Additionally, 1 of 12 patients who received radioiodine for differentiated thyroid carcinoma also showed interstitial pneumonia on SPECT/CT. Five of 7 patients had subsequent proof of COVID 19 by reverse transcriptase polymerase chain reaction. The remaining 2 patients were not tested immediately but underwent quarantine and careful monitoring.  Incidental findings suggestive of COVID 19 may not be infrequent in hybrid imaging of asymptomatic patients in regions with an expansive spread of SARS CoV 2. Nuclear medicine services should prepare accordingly.
A NARRATIVE INQUIRY OF NURSE PATIENT COMMUNICATION
Year: 2019

Identify to the explores: the main causes of verbal abuse of patients by nurses and nurses by patients and to steps needed to promote positive nurse patient interaction at hospitals.  A qualitative study. Place and Duration of Study: The study was conducted in the University of Health Sciences, Lahore for a period of one week, in Aug 2017.  A sample of six senior nurses pursuing Master degree in Health Sciences was selected to address the research questions. In addition to this, a sample comprising six patients and faculty members was taken to counter check the narratives told by the senior nurses.  The study revealed that verbal abuses by nurses and/or patients are situational and fragmented. Lack of time and space, lack of resources and lack of training were the predisposing factors leading up to the verbal abuse of patients by nurses.  The study recommends introducing professional training program of nurses in communication skills for nurse patient conflict resolution. Moreover, the State must provide an environment complete with resources that can be conducive for an efficient health care delivery.
Curriculum Learning with Diversity for Supervised Computer Vision Tasks
Venue: MRC@ECAI
Year: 2020

Curriculum learning techniques are a viable solution for improving the accuracy of automatic models, by replacing the traditional random training with an easy to hard strategy. However, the standard curriculum methodology does not automatically provide improved results, but it is constrained by multiple elements like the data distribution or the proposed model. In this paper, we introduce a novel curriculum sampling strategy which takes into consideration the diversity of the training data together with the difficulty of the inputs. We determine the difficulty using a state of the art estimator based on the human time required for solving a visual search task. We consider this kind of difficulty metric to be better suited for solving general problems, as it is not based on certain task dependent elements, but more on the context of each image. We ensure the diversity during training, giving higher priority to elements from less visited classes. We conduct object detection and instance segmentation experiments on Pascal VOC 2007 and Cityscapes data sets, surpassing both the randomly trained baseline and the standard curriculum approach. We prove that our strategy is very efficient for unbalanced data sets, leading to faster convergence and more accurate results, when other curriculum based strategies fail.
Stock Market Prediction with Deep Learning: A Character based Neural Language Model for Event based Trading
Venue: ALTA
Year: 2017

In the last few years, machine learning has become a very popular tool for analyzing financial text data, with many promising results in stock price forecasting from financial news, a development with implications for the E cient Markets Hypothesis (EMH) that underpins much economic theory. In this work, we explore recurrent neural networks with character level language model pre training for both intraday and interday stock market forecasting. In terms of predicting directional changes in the Standard Poor's 500 index, both for individual companies and the overall index, we show that this technique is competitive with other state of the art approaches.
More green space is linked to less stress in deprived communities: Evidence from salivary cortisol patterns
Year: 2012

Green space has been associated with a wide range of health benefits, including stress reduction, but much pertinent evidence has relied on self reported health indicators or experiments in artificially controlled environmental conditions. Little research has been reported using ecologically valid objective measures with participants in their everyday, residential settings. This paper describes the results of an exploratory study (n 25) to establish whether salivary cortisol can act as a biomarker for variation in stress levels which may be associated with varying levels of exposure to green spaces, and whether recruitment and adherence to the required, unsupervised, salivary cortisol sampling protocol within the domestic setting could be achieved in a highly deprived urban population. Self reported measures of stress and general wellbeing were also captured, allowing exploration of relationships between cortisol, wellbeing and exposure to green space close to home. Results indicate significant relationships between self reported stress (P 0.01) diurnal patterns of cortisol secretion (P 0.05) and quantity of green space in the living environment. Regression analysis indicates percentage of green space in the living environment is a significant (P 0.05) and independent predictor of the circadian cortisol cycle, in addition to self reported physical activity (P 0.02) Results also show that compliance with the study protocol was good. We conclude that salivary cortisol measurement offers considerable potential for exploring relationships between wellbeing and green space and discuss how this ecologically valid methodology can be developed to confirm and extend findings in deprived city areas to illuminate why provision of green space close to home might enhance health.
Adversarially Adaptive Normalization for Single Domain Generalization
Venue: ArXiv
Year: 2021

Single domain generalization aims to learn a model that performs well on many unseen domains with only one domain data for training. Existing works focus on studying the adversarial domain augmentation (ADA) to improve the model's generalization capability. The impact on domain generalization of the statistics of normalization layers is still underinvestigated. In this paper, we propose a generic normalization approach, adaptive standardization and rescaling normalization (ASR Norm) to complement the missing part in previous works. ASR Norm learns both the standardization and rescaling statistics via neural networks. This new form of normalization can be viewed as a generic form of the traditional normalizations. When trained with ADA, the statistics in ASR Norm are learned to be adaptive to the data coming from different domains, and hence improves the model generalization performance across domains, especially on the target domain with large discrepancy from the source domain. The experimental results show that ASR Norm can bring consistent improvement to the state of the art ADA approaches by 1.6% 2.7% and 6.3% averagely on the Digits, CIFAR 10 C, and PACS benchmarks, respectively. As a generic tool, the improvement introduced by ASR Norm is agnostic to the choice of ADA methods.
The Influence of Manager Analyst Interactions on Street Earnings: Evidence from Conference Calls and Excluded Analysts
Year: 2019

We investigate how interactions between analysts and managers influence (1) analyst disagreement about the definition of forecasted street earnings and (2) shifts in the definition of actual street earnings. Textual analysis of conference call transcripts indicates that more discussion about non GAAP earnings and exclusions is associated with larger street earnings exclusions, consistent with prior evidence that both managers and analysts influence street earnings. To measure disagreement among analysts about the definition of forecasted street earnings, we introduce a new measure based on the number of analysts whose forecasts are excluded from the consensus. We find that the discussion of non GAAP earnings in the question and answer (Q&A) section of the conference call is significantly associated with this measure, indicating that the dialog between managers and analysts about non GAAP performance metrics is associated with disagreement about how core performance should be defined. We also find that when more analysts are excluded from the consensus, the market response to positive earnings surprises is significantly muted, suggesting that analyst disagreement in defining performance influences a firm's information environment. Finally, we employ three proxies to capture shifts in the consensus definition of actual street earnings and find that definition shifts are associated with both (1) manager analyst non GAAP discussions in conference calls and (2) our new proxy for analyst disagreement about the definition of street earnings. Our results provide a more comprehensive view of the roles played by managers and analysts in determining street earnings.
Persuasive Function in Food and Beverage Service: A Sociolinguistics Approach
Year: 2019

Language is an arbitrary symbol of sound system, which is used for social interaction, consists of form, meaning, and expression. The study of language (Linguistics) focuses on both aspects of micro and macro linguistics. This current paper belonged to the later, i.e. Sociolinguistics, as it discussed about the use of language in society. Specifically, this study was aimed to identify the use of persuasive functions in the context of Food and Beverage Service. The persuasive function is used for persuading and affecting the hearer (i.e. the customers) to try or buy the products offered. Focusing on the study of English for Tourism and Hospitality (ETH) this paper applied the phenomenology qualitative methods. The data were collected through observation, and analyzed using text analysis. The findings of the paper showed that persuasive functions were represented through micro functions, i.e. 'recommending' 'offering' 'promising' 'suggesting' and 'persuading' Keywords English for Tourism and Hospitality, Persuasive Function, Language Functions, Food and Beverage Service
Parent child cohesion, friend companionship and left behind children's emotional adaptation in rural China.
Venue: Child abuse neglect
Year: 2015

Using cross sectional data from rural left behind children aged 10 17 years in the Henan Province of China, the present study examined the roles of father child cohesion, mother child cohesion, and friend companionship in emotional adaptation (loneliness, depression, and life satisfaction) among children left behind by both of their rural to urban migrant parents compared to those with only a migrating father. The results indicated that the children with two migrating parents were disadvantaged according to their demonstration of depression but not in loneliness or life satisfaction. Both parent child cohesion and friend companionship were directly associated with, to varying extents, the left behind children's emotional outcomes. Moreover, friend companionship moderated the association between father child cohesion and emotional outcomes among children with two migrating parents, but the moderating effects of friend companionship did not exist among children with only a migrating father. The implications of these findings for interventions directed at left behind children are discussed.
Product sales forecasting using macroeconomic indicators and online reviews: a method combining prospect theory and sentiment analysis
Venue: Soft Comput.
Year: 2020

Macroeconomic conditions and users' word of mouth have significant impacts on the purchase decisions of consumers, and they can be potentially used to conduct better sales forecasts, but study on this aspect is relatively scarce. In this paper, a novel method for forecasting product sales based on macroeconomic indicators and online reviews is developed. Firstly, an algorithm is given to select proper macroeconomic indicators to capture the long term trends of sales. Subsequently, an algorithm for sentiment analysis is given to convert textual online reviews into numerical digits, and the word of mouth effect is calculated by incorporating the data related to online reviews (e.g. ratings, browsing numbers, and approval numbers) The sentiment index of word of mouth effect is measured based on the prospect theory, which can accurately reflect the phenomenon whereby negative reviews seriously affect the purchasing decisions of consumers. Further, according to the selected macroeconomic indicators and the obtained sentiment index, a logarithmic autoregressive model for product sales forecasting is constructed, and the model parameters are estimated by the Adam optimizer. Finally, experimental studies on forecasting the sales volume of the Audi A6L in the next three quarters are conducted. The experimental results show that the performance of the proposed method is significantly better than the existing methods.
Optimizing multi VM migration by allocating transfer and compression rate using Geometric Programming
Venue: Simul. Model. Pract. Theory
Year: 2021

Live VM migration has emerged as a core technology for resource management activities and objectives like fault tolerance, reduced energy consumption, load balancing, and system maintenance. Pre copy migration strategy is frequently used by most of the existing hypervisors for live VM migration. However, it requires a considerable amount of data transfer. In the case of low network bandwidth availability, the migration process gets adversely affected. Thereby degrading the performance of applications running on migrated VMs. Migrating multiple VMs even requires more data to be transferred, which further faces the challenge of sharing the available network bandwidth. This motivates for designing a better strategy for the live migration of multiple VMs. Moreover, to reduce the amount of data that needs to be transferred, memory compression techniques can be utilized efficiently by providing fast and stable VM memory migration without sacrificing any service quality. This paper presents a new model using Geometric Programming that allocates transfer and compression rates to each VM to minimize the total migration time. We have found that: (a) Memory compression, along with pre copy migration, improves the performance of the live migration of multiple virtual machines by reducing the total migration time and downtime. (b) The compression rate is dynamically allocated according to the available network bandwidth. So, in an adverse environment, when available bandwidth is less, the memory is compressed using slow compression algorithms to optimize the total migration time. In contrast, when more bandwidth is available, it uses a fast compression algorithm to transfer the data quickly. (c) With the proposed approach, more number of VMs can be migrated in parallel with considerably reduced migration time and downtime when compared with existing strategies.