nils-herrmann/clean_scirepeval huggingface dataset:
Comparing the Effects of Cognitive Stimulation, Reminiscence, and Aroma Massage on Agitation and Depressive Mood in People With Dementia.
Venue: Journal of the American Medical Directors Association

Cognitive stimulation therapy (CST) reminiscence therapy (RT) and aroma massage therapy (AT) are believed to be beneficial for people with dementia (PwD) However, the comparing effects of these interventions have not been reported in previous studies. The purpose of this research was thus to compare the effects of these 3 interventions on alleviating agitation and depressive mood in PwD.  A cohort study with pre and post tests was conducted.  A total of 102 PwD from 10 long term care facilities were allocated to RT (n 43) CST (n 29) or AT (n 29) groups. The participants received the interventions once a week for 8 to 10 consecutive weeks. The participants were evaluated using the Chinese version of the Cohen Mansfield Agitation Inventory and the Cornell Scale for Depression in Dementia before and shortly after the intervention. One way ANOVA and ANCOVA were used to analyze the data.  Significant differences in the effects on agitation and depressive symptoms in PwD were found among the 3 interventions (P .013 and P .001, respectively) Post hoc analysis showed that AT was more effective than RT and CST in improving agitated behaviors (P .006 and P .001, respectively) and was also more effective than CST and RT in alleviating depressive symptoms (both P .001) CONCLUSIONS Our findings indicate that among the 3 alternative remedies, AT can be a more effective intervention than CST and RT with regard to alleviating the agitated behavior and depressive symptoms of PwD. Given that agitated behavior and depressive mood are common among institutionalized PwD, and staff working in long term care facilities often lack knowledge and time to manage such behaviors, the findings of this study can contribute to future clinical practice in long term care facilities. In addition, aroma massage has the advantage of being an easy to learn intervention for staff working with PwD.
Ringed Structures of the HD 163296 Protoplanetary Disk Revealed by ALMA.
Venue: Physical review letters

We present Atacama Large Millimeter and Submillimeter Array observations of the protoplanetary disk around the Herbig Ae star HD 163296 that trace the spatial distribution of millimeter sized particles and cold molecular gas on spatial scales as small as 25 astronomical units (A.U. The image of the disk recorded in the 1.3 mm continuum emission reveals three dark concentric rings that indicate the presence of dust depleted gaps at about 60, 100, and 160 A.U. from the central star. The maps of the {12}CO, {13}CO, and C^{18}O J=2 1 emission do not show such structures but reveal a change in the slope of the radial intensity profile across the positions of the dark rings in the continuum image. By comparing the observations with theoretical models for the disk emission, we find that the density of CO molecules is reduced inside the middle and outer dust gaps. However, in the inner ring there is no evidence of CO depletion. From the measurements of the dust and gas densities, we deduce that the gas to dust ratio varies across the disk and, in particular, it increases by at least a factor 5 within the inner dust gap compared to adjacent regions of the disk. The depletion of both dust and gas suggests that the middle and outer rings could be due to the gravitational torque exerted by two Saturn mass planets orbiting at 100 and 160 A.U. from the star. On the other hand, the inner dust gap could result from dust accumulation at the edge of a magnetorotational instability dead zone, or from dust opacity variations at the edge of the CO frost line. Observations of the dust emission at higher angular resolution and of molecules that probe dense gas are required to establish more precisely the origins of the dark rings observed in the HD 163296 disk.
Integrated genomics and proteomics to define huntingtin CAG length dependent networks in HD Mice
Venue: Nature Neuroscience

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock in mice with increasing CAG repeat lengths. We found repeat length dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo.
Who and how? Preservice teachers as active agents developing professional identities

This study is part of an ongoing action research project with preservice class teachers in Finland. The study aims to better understand the forms agency takes in preservice teachers' professional identity development. Through the dialogical analysis of student assignments, this study outlines how student teachers are active within their own development and the way in which experiences are drawn on as preservice teachers exert their identity agency. The results of this study provide a relational picture of identity development highlighting the way in which identity agency is contextualized, potentially nourished by the relationships between self and other and dependent on experience.
Passive Wireless Frequency Doubling Antenna Sensor for Strain and Crack Sensing
Venue: IEEE Sensors Journal

This paper presents the design, simulation, and validation experiments of a passive (battery free) wireless frequency doubling antenna sensor for strain and crack sensing. Since the length of a patch antenna governs the antenna's resonance frequency, a patch antenna bonded to a structural surface can be used to measure mechanical strain or crack propagation by interrogating resonance frequency shift due to antenna length change. In comparison with previous approaches such as radio frequency identification, the frequency doubling scheme is proposed as a new signal modulation approach for the antenna sensor. The proposed approach can easily distinguish backscattered passive sensor signal (at the doubled frequency $2{f} from environmental electromagnetic reflections (at original reader interrogation frequency $f$ To accurately estimate the performance of the frequency doubling antenna sensor, a multi physics coupled simulation framework is proposed to aid the sensor design while considering both the mechanical and electromagnetic behaviors. Two commercial software packages, COMSOL and Advanced Design System (ADS) are combined to leverage the features from each other. The simulated performance of the frequency doubling antenna sensor is further validated by experiments. The results show that the sensor is capable of detecting small strain changes and the growth of a small crack.
Battery free slotted patch antenna sensor for wireless strain and crack monitoring

In this research, a slotted patch antenna sensor is designed for wireless strain and crack sensing. An offthe shelf RFID (radiofrequency identification) chip is adopted in the antenna sensor design for signal modulation. The operation power of the RFID chip is captured from wireless reader interrogation signal, so the sensor operation is completely battery free (passive) and wireless. For strain and crack sensing of a structure, the antenna sensor is bonded on the structure surface like a regular strain gage. Since the antenna resonance frequency is directly related with antenna dimension, which deforms when strain occurs on the structural surface, the deformation/strain can be correlated with antenna resonance frequency shift measured by an RFID reader. The slotted patch antenna sensor performance is first evaluated through mechanics electromagnetics coupled simulation. Extensive experiments are then conducted to validate the antenna sensor performance, including tensile and compressive strain sensing, wireless interrogation range, and fatigue crack sensing.
The Role of Social Media in Crisis Communication and Crisis Management

Social media and social media tools have improved rapidly and started to influence society especially in recent years. This influence has forced businesses to revolutionize their communication with the external environment. The fact that Web 2.0 has an influence on consumer behavior, and that it makes the consumers stronger; requires faster, more flexible and more sensitive communication processes in businesses. Especially during a time of crisis, a business' communication with the external environment is quite critical. For this reason, the way how the crisis communication is managed through social media is vital for businesses. In this article, the perceptions of how to manage businesses during a time of crisis so that they make minimum loss, is shared.
Crisis management at General Motors and Toyota: An analysis of gender specific communication and media coverage

This study applied the genderlect theory to analyze General Motors' and Toyota's senior executive crisis communication. The discrepancies in the two companies' crisis responses were explained through female vs. male specific communication. Further, the study applied the situational crisis communication theory to analyze the news valence in the media coverage of the crises. While a direct correlation between gender specific communication and news valence was beyond the purpose of this study, the current analysis can serve as a basis for future research on best crisis communication strategies as informed by gender differences.
Crisis Management in Nonprofit Organizations: A Case Study of Crisis Communication and Planning

A real crisis experienced by a national nonprofit organization is used in this case study to help students apply concepts associated with crisis management planning (CMP) Students are introduced to crisis planning, management, and communication strategies to help them develop the skills necessary to lead a nonprofit organization through a crisis. Concepts introduced in the theoretical background of the case provide students with a theoretical and a practical understanding of crisis, crisis management, crisis communication planning, and crisis communication strategies. Communication strategies presented are focused on image restoration strategies. The case is appropriate for undergraduate and graduate students preparing to work in the nonprofit sector. Instructors are encouraged to use this case in conjunction with discussions of public relations, crisis management, or crisis communication strategies. The sample assignments and discussion questions allow students to connect crisis management theory to a practical organizational crisis within a classroom setting.
The evidence for 'flipping out' A systematic review of the flipped classroom in nursing education.
Venue: Nurse education today

The flipped classroom has generated interest in higher education providing a student centred approach to learning. This has the potential to engage nursing students in ways that address the needs of today's students and the complexity of contemporary healthcare. Calls for educational reform, particularly in healthcare programs such as nursing, highlight the need for students to problem solve, reason and apply theory into practice. The drivers towards student based learning have manifested in team, problem and case based learning models. Though there has been a shift towards the flipped classroom, comparatively little is known about how it is used in nursing curricula.  The aims of this systematic review were to examine how the flipped classroom has been applied in nursing education and outcomes associated with this style of teaching.  Five databases were searched and resulted in the retrieval of 21 papers: PubMed, CINAHL, EMBASE, Scopus and ERIC.  After screening for inclusion/exclusion criteria, each paper was evaluated using a critical appraisal tool. Data extraction and analysis were completed on all included studies.  This systematic review screened 21 titles and abstracts resulting in nine included studies. All authors critically appraised the quality of the included studies. Five studies were identified and themes identified were: academic performance outcomes, and student satisfaction implementing the flipped classroom.  Use of the flipped classroom in higher education nursing programmes yielded neutral or positive academic outcomes and mixed results for satisfaction. Engagement of students in the flipped classroom model was achieved when academics informed and rationalised the purpose of the flipped classroom model to students. However, no studies in this review identified the evaluation of the process of implementing the flipped classroom. Studies examining the process and ongoing evaluation and refinement of the flipped classroom in higher education nursing programmes are warranted.
Post Weld Heat Treatment for High Strength Steel Welded Connections

In this study, experiments were conducted to investigate the effect of post weld heat treatment (PWHT) on the reheated, quenched and tempered (RQT) grade S690 high strength steel welded connections. Firstly, the effect of PWHT on the mechanical properties after welding is investigated. It is found that the loss of both strength and ductility after welding could be serious but PWHT could be able to improve the ductility of the affected specimens at the expense of strength. Secondly, four Y shape plate to plate (Y PtP) and nine T stub RQT S690 joints are fabricated to study the effect of PWHT on the residual stress level near the weld toe and the tensile behavior of the joints, respectively. The hole drilling tests employed to study the residual stress reveal that PWHT is able to decrease the residual stress level near the weld toe significantly. The tensile test results show that proper PWHT could improve both the ductility and the maximum resistance while the reduction of plastic resistance can be kept in a negligible level. However, it is found that if the specimens are overheated, although the ductility could still be increased, the reduction of load carrying capacity was severe.
Speech Emotion Recognition Based on Deep Belief Networks and Wavelet Packet Cepstral Coefficients

A wavelet packet based adaptive filter bank construction combined with Deep Belief Network(DBN) feature learning method is proposed for speech signal processing in this paper. On this basis, a set of acoustic features are extracted for speech emotion recognition, namely Coiflet Wavelet Packet Cepstral Coefficients (CWPCC) CWPCC extends the conventional MelFrequency Cepstral Coefficients (MFCC) by adapting the filter bank structure according to the decision task. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre trained layer by layer and then fine tuned using back propagation algorithm. The well trained deep neural networks are capable of modeling complex and non linear features of input training data and can better predict the probability distribution over classification labels. Speech emotion recognition system is constructed with the feature set, DBNs feature learning structure and Support Vector Machine as classifier. Experimental results on Berlin emotional speech database show that the Coiflet Wavelet Packet is more suitable in speech emotion recognition than other acoustics features and proposed DBNs feature learning structure combined with CWPCC improve emotion recognition performance over the conventional emotion recognition method.
Feature Fusion Methods for Robust Speech Emotion Recognition Based on Deep Belief Networks
Venue: ICNCC '16

The speech emotion recognition accuracy of prosody feature and voice quality feature declines with the decrease of SNR (Signal to Noise Ratio) of speech signals. In this paper, we propose novel sub band spectral centroid weighted wavelet packet cepstral coefficients (W WPCC) for robust speech emotion recognition. The W WPCC feature is computed by combining the sub band energies with sub band spectral centroids via a weighting scheme to generate noise robust acoustic features. And Deep Belief Networks (DBNs) are artificial neural networks having more than one hidden layer, which are first pre trained layer by layer and then fine tuned using back propagation algorithm. The well trained deep neural networks are capable of modeling complex and non linear features of input training data and can better predict the probability distribution over classification labels. We extracted prosody feature, voice quality features and wavelet packet cepstral coefficients (WPCC) from the speech signals to combine with W WPCC and fused them by Deep Belief Networks (DBNs) Experimental results on Berlin emotional speech database show that the proposed fused feature with W WPCC is more suitable in speech emotion recognition under noisy conditions than other acoustics features and proposed DBNs feature learning structure combined with W WPCC improve emotion recognition performance over the conventional emotion recognition method.
Implementation of SPWM technique for 3 Ph VSI using STM32F4 discovery board interfaced with MATLAB
Venue: 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems (ICPEICES)

In this paper; Design and development of control circuit algorithm of 3 Ph Voltage Source Inverter (VSI) using Unipolar Sinusoidal Pulse Width Modulation (SPWM) techniques is proposed using STM32F407VGTx discovery board interfaced with MATLAB Simulink Environment. For implementing 3 Ph VSI; this method is most useful as it will eliminate complexity of control circuit algorithm occurred due to analog circuit; reduces cost; size of filter required and improved overall inverter efficiency. Pulse width modulated voltage source inverter is preferred for high performance AC drives. The proposed control scheme and the result obtained by embedded simulations interfaced with STM32F4 microcontroller are presented and discussed. A simple hardware implementation is proposed and experimental results of SPWM based VSI are also shown. The Simulation results of the proposed scheme have excellent performance and compared with hardware results.
A Novel Transformer Less SPWM Inverter using DC DC Boost Converter with Coupled Inductor for Standalone Applications
Venue: 2016 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC)

The rapid developments in solar energy conversion technologies, researchers emerged with an idea of live evacuation of energy into the grid using PV modules. Standalone systems are designed for sensitive AC loads which require pure sine wave as input. According to the simulation results in Power SIM simulator, this paper proposes A Novel Transformer Less SPWM Inverter using DC DC Boost Converter with Coupled Inductor for Standalone Applications, name only indicates that it is a transformer less topology and for the stand alone applications. From the pure sine wave inverter for standalone applications has been implemented obtains a reduced ripple topology with the less (5% total harmonic distortion (THD) Switching signal is generating by using the PIC16F876 Microcontroller for SPWM technique and also it controls the gates of the power switches. The design analysis of the proposed boost converter with the coupled inductor circuit is to boost up the lower voltage to the higher voltages respect to the load requirements (30 to 50 times of the input voltage) From this proposed analysis enhances the efficiency of the system with lower cost. It is a transformer less topology. This converter operates with 12Vdc available at the solar panel, and generate regulated output voltage of 340Vdc.To obtain higher gain in voltage the converter output terminals and boost output terminals are cascaded with the isolated inductor. The design is analyzed using PSIM simulator tool.
Effectuation in SPWM technique for 3 Ph VSI using STM32F4 discovery board interfaced with MATLAB
Venue: 2016 IEEE 7th Power India International Conference (PIICON)

In this paper, Design and development of control circuit algorithm of 3 Ph Voltage Source Inverter (VSI) using Unipolar Sinusoidal Pulse Width Modulation (SPWM) techniques is proposed using STM32F407VGTx discovery board interfaced with MATLAB Simulink Environment. For implementing 3 Ph VSI, this method is most useful as it will eliminate complexity of control circuit algorithm occurred due to analog circuit, reduces cost, size of filter required, and improved overall inverter efficiency. Pulse width modulated voltage source inverter is preferred for high performance AC drives. The proposed control scheme and the result obtained by embedded simulations interfaced with STM32F4 microcontroller are presented and discussed. A simple hardware implementation is proposed and experimental results of SPWM based VSI are also shown. The Simulation results of the proposed scheme have excellent performance and compared with hardware results.
A Multi Task Learning Formulation for Survival Analysis
Venue: KDD

Predicting the occurrence of a particular event of interest at future time points is the primary goal of survival analysis. The presence of incomplete observations due to time limitations or loss of data traces is known as censoring which brings unique challenges in this domain and differentiates survival analysis from other standard regression methods. The popularly used survival analysis methods such as Cox proportional hazard model and parametric survival regression suffer from some strict assumptions and hypotheses that are not realistic in most of the real world applications. To overcome the weaknesses of these two types of methods, in this paper, we reformulate the survival analysis problem as a multi task learning problem and propose a new multi task learning based formulation to predict the survival time by estimating the survival status at each time interval during the study duration. We propose an indicator matrix to enable the multi task learning algorithm to handle censored instances and incorporate some of the important characteristics of survival problems such as non negative non increasing list structure into our model through max heap projection. We employ the L2,1 norm penalty which enables the model to learn a shared representation across related tasks and hence select important features and alleviate over fitting in high dimensional feature spaces; thus, reducing the prediction error of each task. To efficiently handle the two non smooth constraints, in this paper, we propose an optimization method which employs Alternating Direction Method of Multipliers (ADMM) algorithm to solve the proposed multi task learning problem. We demonstrate the performance of the proposed method using real world microarray gene expression high dimensional benchmark datasets and show that our method outperforms state of the art methods.