nils-herrmann/clean_scirepeval huggingface dataset:
A conservation of resources view of personal engagement in the development of innovative behavior and work family conflict

The purpose of this paper is to examine how personal engagement (PE) may be related with work family conflict (WFC) and innovative behavior (IB) at the same time.  This study tested the proposed model using a longitudinal data with 1,501 employees from R&D departments in information technology industry of Greater China at multiple points (Time 1 to Time 3) in time over a ten month period.  This study exhibits how charismatic leadership style, colleague support (CS) and self esteem (SE) are capable of predicting the PE, which, in turn, positively related to the IB and the WFC.  The present study proposed a model of the PE, but there are other variables that might also be important for the PE.  These finding suggests that managers not only must inspire and enable employees to apply their full energy to their work (e.g. PE) but must also alleviate the WFC.  The study drawn from Kahn's (1990) engagement theory and conservation of resources view to explain how the leadership style, CS, and SE can increase PE, which, in turn, increase positive organization behavior (IB) and negative organization behavior (WFC) at the same time.
Semantic Image Segmentation with Task Specific Edge Detection Using CNNs and a Discriminatively Trained Domain Transform
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Deep convolutional neural networks (CNNs) are the backbone of state of art semantic image segmentation systems. Recent work has shown that complementing CNNs with fully connected conditional random fields (CRFs) can significantly enhance their object localization accuracy, yet dense CRF inference is computationally expensive. We propose replacing the fully connected CRF with domain transform (DT) a modern edge preserving filtering method in which the amount of smoothing is controlled by a reference edge map. Domain transform filtering is several times faster than dense CRF inference and we show that it yields comparable semantic segmentation results, accurately capturing object boundaries. Importantly, our formulation allows learning the reference edge map from intermediate CNN features instead of using the image gradient magnitude as in standard DT filtering. This produces task specific edges in an end to end trainable system optimizing the target semantic segmentation quality.
Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks
Venue: 2016 Fourth International Conference on 3D Vision (3DV)

Multi scale deep CNNs have been used successfully for problems mapping each pixel to a label, such as depth estimation and semantic segmentation. It has also been shown that such architectures are reusable and can be used for multiple tasks. These networks are typically trained independently for each task by varying the output layer(s) and training objective. In this work we present a new model for simultaneous depth estimation and semantic segmentation from a single RGB image. Our approach demonstrates the feasibility of training parts of the model for each task and then fine tuning the full, combined model on both tasks simultaneously using a single loss function. Furthermore we couple the deep CNN with fully connected CRF, which captures the contextual relationships and interactions between the semantic and depth cues improving the accuracy of the final results. The proposed model is trained and evaluated on NYUDepth V2 dataset [23] outperforming the state of the art methods on semantic segmentation and achieving comparable results on the task of depth estimation.
Why The Dragon Can't Dance: an examination of Indian African Relations in Lovelace's "THE DRAGON CAN'T DANCE"

THIS PAPER EXAMINES the presentation of the Indian and of Indian African rela tions in Earl Lovelace's novel The Dragon Can't Dance (1979) Our concern is with part of the meaning or content, but in a great novel it is not easy to separate content from the artistic form which contains and shapes it; nor is it possible to pick up one theme without recognising its vital connections with others in the work. But these are lesser thorns threatening our grasp than tokens of the integrity of the content from which we seek to extract meanings. The populations of Trinidad and Guyana are fairly evenly divided between descen dants of Africans and descendants of Indians. Nearly one hundred years ago, an English historian, James Anthony Froude, wrote: "The African and Asiatic will not mix, and the African being the stronger will and must prevail in Trinidad as elsewhere in the West Indies" (The English in the West Indies, 1888, Chapter 6) and in 1963 the Bar badian poet, Edward Kamau Brathwaite could observe in Bim 37: "When most of us speak of 'the West Indian' we think of someone of African descent..we are thinking of..a more or less easily identifiable majority group, sharing, at least, a common his tory of slavery" Issues arising from the meeting of African and Indian peoples have never been the subject of open and rational discussion in these islands, and even twen ty five years after the death of the West Indian Federation, the presence of Indians as a major component in the structure of society in Trinidad and Guyana continues to be ignored in favour of a blind approach which makes itself respectable by taking an over all 'West Indian' view and regarding the Indians as minorities. The disappointments of Independence were covered up to some extent by the fast money that came to Trinidad and Tobago accidentally through the phenomenal in crease in the price of oil in the early 1970s, and then by an intemperate and uncir cumspect exploitation of the resource. But in the aftermath fundamental problems have begun to show. Independence as it arrived came as a kind of moral anti climax
Next environment friendly cars: Application of solar power as automobile energy source
Venue: 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC)

We investigate the benefits of utilizing solar power as an energy source for future automobiles. Since there are strict emission standards developed by governments, we must find an alternative energy source for the future automobiles. We show that replacing all passenger cars with hybrid vehicles equipped with a 800 W rated power solar module would reduce greenhouse gas (GHG) emission by 63% in Japan. We obtained an average power generation of 2.1 kWh/day over 100 days by solar modules installed on a Prius under the real environment, which was larger than the required power to achieve the GHG emission reduction. We also investigate an innovative statistic low concentrator with III V cells in order to reduce installation area for the automobiles. We show that our proposed design (asymmetric aspheric design) can expand the acceptance incident angle and increase the annual energy yield, while keeping thin structure, which is essential to automobile application.
The impact of a sense of self efficacy on the level of stress and the ways of coping with difficult situations in Polish nursing students.
Venue: Nurse education today

During their first practical classes at a clinical ward nursing students face a new environment; they take on new roles which is associated with stress and a need to handle it.  The aim of this study was to evaluate the effect of a sense of self efficacy on the level of stress and the ways of coping by Polish nursing students during the first practical classes at a clinical ward.  The study included 394 undergraduate subjects studying nursing at two universities in Southern Poland. The study used the method of diagnostic questionnaire and estimation. The research tools included: an original questionnaire, Stress Scale (PSS10) Inventory to measure coping with stress (Mini Cope) and Generalized Self efficacy Scale (GSES) Data analysis was performed using the IBM Statistical Package for Social Sciences, version 21 for Windows. The verification of differences between variables was performed using kh(2) independence test, Kruskal Wallis test, and Spearman rank correlation coefficient. The level of significance was accepted at a=0.005.  The level of stress and a sense of self efficacy in majority of tested nursing students were high. The people with low levels of perceived stress had a significantly higher sense of self efficacy (rhoSpearman= 0.196; p=0.0001) The people with a higher sense of self efficacy significantly more often used active strategies in stressful situations, such as Active coping (rhoSpearman=0.284; p<0.0001) Planning (rhoSpearman=0.318, p<=0.0001) Positive revaluation (rhoSpearman=0.228, p<0.0001) Acceptance (rhoSpearman=0.188; p=0.0002) Seeking Emotional Support (rhoSpearman=0.123; p=0.0143)  A sense of self efficacy had a significant impact on the level of stress and the ways of coping with difficult situations in nursing students.
The Common Sense Model of Self Regulation (CSM) a dynamic framework for understanding illness self management
Venue: Journal of Behavioral Medicine

The Common Sense Model of Self Regulation (the "Common Sense Model" CSM) is a widely used theoretical framework that explicates the processes by which patients become aware of a health threat, navigate affective responses to the threat, formulate perceptions of the threat and potential treatment actions, create action plans for addressing the threat, and integrate continuous feedback on action plan efficacy and threat progression. A description of key aspects of the CSM's history over 50 years of research and theoretical development makes clear the model's dynamic underpinnings, characteristics, and assumptions. The current article provides this historical narrative and uses that narrative to highlight dynamic aspects of the model that are often not evaluated or utilized in contemporary CSM based research. We provide suggestions for research advances that can more fully utilize these dynamic aspects of the CSM and have the potential to further advance the CSM's contribution to medical practice and patients' self management of illness.
Combining garden therapy and supported employment a method for preparing women on long term sick leave for working life.
Venue: Scandinavian journal of caring sciences

Women are overrepresented among the group people suffering from long term illness. In addition to their illness, suffering long term sick leave leads to economical restraints as well social distress. There are gaps in our understanding of the challenges these women face. There is also lack of knowledge about how these challenges can be effectively addressed in rehabilitation. This deficiency is problematic from an ethical, justice and a caring perspective. In this study, changes in health related quality of life (HRQoL) among women on long term sick leave were investigated during and after participating in a rehabilitation programme combining two validated methods, Garden Therapy and Supported Employment (SE) The study also discusses difficulties in realising research related to vulnerable under privileged people. From a population of 329 women who had reported their interest to participate, 245 were randomised to the programme. Of these 144 accepted participation in the research project and of these 123 women accepted to answer the SF 36 questionnaire. The participants were between 21 and 62 years with poor physical and mental health. They had received public financial support from <1 year to >10 years. The SF 36 measurement was carried out at baseline, after completion of Garden Therapy and after completion of SE. The results are based on data of respondents who participated at all the three occasions (n 52) When comparing HRQoL baseline with the following occasions, the participants' General Health (GH) Vitality (VT) Social Functioning (SF) and mental health had improved significantly. The Four Leaf Clover (FLC) programme could be an appropriate method for reducing socially induced suffering. However, to conduct intervention studies where vulnerable persons are involved, it is off vital importance to consider whether the participants have the strength to complete the intervention.
Design of evidence based gardens and garden therapy for neurodisability in Scandinavia: data from 14 sites.
Venue: Neurodegenerative disease management

A total of 14 Scandinavian therapy gardens were visited and data collected on plantings, therapeutic activities and assessment of effectiveness in Spring 2014.  Data were gathered by a questionnaire and by interviewing staff in Sweden, Denmark and Norway. The data collection structured proforma used the post occupation assessment method.  Gardening promoted physical movement, presented cognitive challenges and provided opportunities for social participation. Half the gardens were enclosed with sensory plants and 85% were adapted for wheelchairs. A total of 57% of gardens visited had simple designs with flowers, shrubs, lawns and trees. A social center was important especially for dementia clients. Planted pots were used in 79% of gardens. The effectiveness of therapy gardens was assessed at 71% of sites.
Semantic Based Model Analysis Towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain
Venue: SoCPaR

Process mining results can be enhanced by adding semantic knowledge to the derived models. Information discovered due to semantic enrichment of the deployed process models can be used to lift process analysis from syntactic level to a more conceptual level. The work in this paper corroborates that semantic based process mining is a useful technique towards improving the information value of derived models from the large volume of event logs about any process domain. We use a case study of learning process to illustrate this notion. Our goal is to extract streams of event logs from a learning execution environment and describe formats that allows for mining and improved process analysis of the captured data. The approach involves mapping of the resulting learning model derived from mining event data about a learning process by semantically annotating the process elements with concepts they represent in real time using process descriptions languages, and linking them to an ontology specifically designed for representing learning processes. The semantic analysis allows the meaning of the learning objects to be enhanced through the use of property characteristics and classification of discoverable entities, to generate inference knowledge which are used to determine useful learning patterns by means of the Semantic Learning Process Mining (SLPM) algorithm technically described as Semantic Fuzzy Miner. To this end, we show how data from learning processes are being extracted, semantically prepared, and transformed into mining executable formats to enable prediction of individual learning patterns through further semantic analysis of the discovered models.
Responses to Predictable versus Random Temporally Complex Stimuli from Single Units in Auditory Thalamus: Impact of Aging and Anesthesia
Venue: The Journal of Neuroscience

Human aging studies suggest that an increased use of top down knowledge based resources would compensate for degraded upstream acoustic information to accurately identify important temporally rich signals. Sinusoidal amplitude modulated (SAM) stimuli have been used to mimic the fast changing temporal features in speech and species specific vocalizations. Single units were recorded from auditory thalamus [medial geniculate body (MGB) of young awake, aged awake, young anesthetized, and aged anesthetized rats. SAM stimuli were modulated between 2 and 1024 Hz with the modulation frequency (fm) changed randomly (RAN) across trials or sequentially (SEQ) after several repeated trials. Units were found to be RAN preferring, SEQ preferring, or nonselective based on total firing rate. Significant anesthesia and age effects were found. The majority (86% of young anesthetized units preferred RAN SAM stimuli; significantly fewer young awake units (51% p 0.0001) preferred RAN SAM signals with 16% preferring SEQ SAM. Compared with young awake units, there was a significant increase of aged awake units preferring SEQ SAM (30% p 0.05) We examined RAN versus SEQ differences across fms by measuring selective fm areas under the rate modulation transfer function curve. The largest age related differences from awake animals were found for mid to high fms in MGB units, with young units preferring RAN SAM while aged units showed a greater preference for SEQ presented SAM. Together, these findings suggest that aged MGB units/animals employ increased top down mediated stimulus context to enhance processing of "expected" temporally rich stimuli, especially at more challenging higher fms.  Older individuals compensate for impaired ascending acoustic information by increasing use of cortical cognitive and attentional resources. The interplay between ascending and descending influences in the thalamus may serve to enhance the salience of speech signals that are degraded as they ascend to the cortex. The present findings demonstrate that medial geniculate body units from awake rats show an age related preference for predictable modulated signals relative to randomly presented signals, especially at higher, more challenging modulation frequencies. Conversely, units from anesthetized animals, with little top down influences, strongly preferred randomly presented modulated sequences. These results suggest a neuronal substrate for an age related increase in experience/attentional based influences in processing temporally complex auditory information in the auditory thalamus.
Functional redundancy as a tool for bioassessment: A test using riparian vegetation.
Venue: The Science of the total environment

There is an urgent need to track how natural systems are responding to global change in order to better guide management efforts. Traditionally, taxonomically based metrics have been used as indicators of ecosystem integrity and conservation status. However, functional approaches offer promising advantages that can improve bioassessment performance. In this study, we aim to test the applicability of functional redundancy (FR) a functional feature related to the stability, resistance and resilience of ecosystems, as a tool for bioassessment, looking at woody riparian communities in particular. We used linear mixed effect models to investigate the response of FR and other traditional biomonitoring indices to natural (drought duration) and anthropogenic stress gradients (flow regulation and agriculture) in a Mediterranean basin. Such indices include species richness, a taxonomic index, and the Riparian Quality Index, which is an index of ecological status. Then, we explored the ability of FR and the other indices to discriminate between different intensities of human alteration. FR showed higher explanatory capacity in response to multiple stressors, although we found significant negative relationships between all the biological indices (taxonomic, functional and ecological quality) and stress gradients. In addition, FR was the most accurate index to discriminate among different categories of human alteration in both perennial and intermittent river reaches, which allowed us to set threshold values to identify undisturbed (reference condition) moderately disturbed and highly disturbed reaches in the two types of river. Using these thresholds and the best fitting model, we generated a map of human impact on the functional redundancy of riparian communities for all the stretches of the river network. Our results demonstrate that FR presents clear advantages over traditional methods, which suggests that it should be part of the biomonitoring toolbox used for environmental management so as to obtain better predictions of ecosystem response to environmental changes.
Laplacian Regularized Low Rank Representation and Its Applications
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence

Low rank representation (LRR) has recently attracted a great deal of attention due to its pleasing efficacy in exploring low dimensional subspace structures embedded in data. For a given set of observed data corrupted with sparse errors, LRR aims at learning a lowest rank representation of all data jointly. LRR has broad applications in pattern recognition, computer vision and signal processing. In the real world, data often reside on low dimensional manifolds embedded in a high dimensional ambient space. However, the LRR method does not take into account the non linear geometric structures within data, thus the locality and similarity information among data may be missing in the learning process. To improve LRR in this regard, we propose a general Laplacian regularized low rank representation framework for data representation where a hypergraph Laplacian regularizer can be readily introduced into, i.e. a Non negative Sparse Hyper Laplacian regularized LRR model (NSHLRR) By taking advantage of the graph regularizer, our proposed method not only can represent the global low dimensional structures, but also capture the intrinsic non linear geometric information in data. The extensive experimental results on image clustering, semi supervised image classification and dimensionality reduction tasks demonstrate the effectiveness of the proposed method.
A comparative study of conventional and supercritical fluid extraction methods for the recovery of secondary metabolites from Syzygium campanulatum Korth
Venue: Journal of Zhejiang University SCIENCE B

Syzygium campanulatum Korth is a plant, which is a rich source of secondary metabolites (especially flavanones, chalcone, and triterpenoids) In our present study, three conventional solvent extraction (CSE) techniques and supercritical fluid extraction (SFE) techniques were performed to achieve a maximum recovery of two flavanones, chalcone, and two triterpenoids from S. campanulatum leaves. Furthermore, a Box Behnken design was constructed for the SFE technique using pressure, temperature, and particle size as independent variables, and yields of crude extract, individual and total secondary metabolites as the dependent variables. In the CSE procedure, twenty extracts were produced using ten different solvents and three techniques (maceration, soxhletion, and reflux) An enriched extract of five secondary metabolites was collected using n hexane:methanol (1:1) soxhletion. Using food grade ethanol as a modifier, the SFE methods produced a higher recovery (25.5% 84.9% of selected secondary metabolites as compared to the CSE techniques (0.92% 66.00%.Zhong Wen Gai Yao Mu De Xun Qiu Yi Chong Zui Jia De Zhong Hua Pu Tao Ci Sheng Dai Xie Chan Wu De Cui Qu Fang Fa ,Yi Shi Xian Zai Gong Ye Shang De Ying Yong Chuang Xin Dian Quan Mian Shen Ru Di Bi Jiao Chuan Tong Rong Ji Ti Qu Fa He Chao Lin Jie Liu Ti Cui Qu Fa Dui Zhong Hua Pu Tao De Zhu Yao Ci Sheng Dai Xie Chan Wu De Hui Shou Lu Fang Fa Zai Chao Lin Jie Liu Ti Cui Qu Fa Zhong ,Ying Yong Box Behnken She Ji Yi Ya Li Wen Du He Cui Qu Li Jing Da Xiao Wei Zi Bian Liang ,Yi Cu Ti Qu Wu Ge Bie De He Zong De Ci Sheng Dai Xie Chan Wu De Bai Fen Bi Chan Liang Wei Yin Bian Liang Ling Wai ,Huan Yan Jiu Liao Diao Jie Ji Yi Chun Dui Chan Liang De Ying Xiang Zai Chuan Tong Rong Ji Ti Qu Zhong ,Jie He Shi Chong Bu Tong De Rong Ji He San Bu Tong De Ji Zhu