nils-herrmann/clean_scirepeval huggingface dataset:
Power Consumption Reduction for Wireless Sensor Networks Using A Fuzzy Approach

The increasing complexity of Wireless Sensor Networks (WSNs) is leading towards the deployment of complex networked systems and the optimal design of WSNs can be a very difficult task because several constraints and requirements must be considered, among all the power consumption. This paper proposes a novel fuzzy logic based mechanism that according to the battery level and to the ratio of Throughput to Workload determines the sleeping time of sensor devices in a Wireless Sensor Network for environmental monitoring based on the IEEE 802.15.4 protocol. The main aim here is to find an effective solution that achieves the target while avoiding complex and computationally expensive solutions, which would not be appropriate for the problem at hand and would impair the practical applicability of the approach in real scenarios. The results of several real test bed scenarios show that the proposed system outperforms other solutions, significantly reducing the whole power consumption while maintaining good performance in terms of the ratio of throughput to workload. An implementation on off the shelf devices proves that the proposed controller does not require powerful hardware and can be easily implemented on a low cost device, thus paving the way for extensive usage in practice.
How Coercive and Legitimate Power Relate to Different Conflict Management Styles: A Case Study of Birjand High Schools

This study investigates the relationship between two sources of organizational power (i.e. coercive and legitimate power) and five conflict management styles (i.e. avoiding, accommodating, competing, collaborating, and compromising style) Results of this study revealed that principals' coercive power has a positive relationship with avoiding and competing conflict management styles. Since these two conflict management styles both require low levels of cooperation, therefore it is fair to claim that higher degrees of coercive power facilitate the use of conflict management styles that require low levels of cooperation. It was also found that principals' legitimate power is positively related to accommodating and collaborating conflict management styles. Since both of these styles are associated with high levels of cooperation, therefore it is fair to claim that higher degrees of legitimate power will facilitate the use of conflict management styles requiring high levels of cooperation.
Manager's power bases perception and organizational citizenship behavior: a case study on accommodation establishments.

In this study, it was aimed to determine the relationship between powerbases perception of managers and organizational citizenship behavior in accommodation establishments. As a result of analyzes it was determined that legal power and power based on knowledge highest and coercive power is the lowest perceived power by participant. According to correlation analysis, negative relationship was found between coercive power, legitimate power and altruism, courtesy, civicvirtue, conscientiousness. Also according to the results of a regression analysis, organizational citizenship behavior can be explained by the variability of the manager's powerbases. However, there is no significant difference between the manager's power supplies and gender, marital status, age, education, tourism education of employees who participated in this study. But there is significant difference between legal power and monthly income variable.
Manufacture of probiotic Minas Frescal cheese with Lactobacillus casei Zhang.
Venue: Journal of dairy science

In this study, the addition of Lactobacillus casei Zhang in the manufacture of Minas Frescal cheese was investigated. Minas Frescal cheeses supplemented with probiotic bacteria (Lactobacillus casei Zhang) were produced by enzymatic coagulation and direct acidification and were subjected to physicochemical (pH, proteolysis, lactic acid, and acetic acid) microbiological (probiotic and lactic bacteria counts) and rheological analyses (uniaxial compression and creep test) instrumental color determination (luminosity, yellow intensity, and red intensity) and sensory acceptance test. The addition of L. casei Zhang resulted in low pH values and high proteolysis indexes during storage (from 5.38 to 4.94 and 0.470 to 0.702, respectively) Additionally, the cheese protocol was not a hurdle for growth of L. casei Zhang, as the population reached 8.16 and 9.02 log cfu/g by means of the direct acidification and enzymatic coagulation protocol, respectively, after 21 d of refrigerated storage. The rheology data showed that all samples presented a more viscous like behavior, which rigidity tended to decrease during storage and lower luminosity values were also observed. Increased consumer acceptance was observed for the control sample produced by direct acidification (7.8) whereas the cheeses containing L. casei Zhang presented lower values for all sensory attributes, especially flavor and overall liking (5.37 and 4.61 for enzymatic coagulation and 5.57 and 4.72 for direct acidification, respectively) Overall, the addition of L. casei Zhang led to changes in all parameters and affected negatively the sensory acceptance. The optimization of L. casei Zhang dosage during the manufacturing of probiotic Minas Frescal cheese should be performed.
Metatranscriptomics reveals temperature driven functional changes in microbiome impacting cheese maturation rate
Venue: Scientific reports

Traditional cheeses harbour complex microbial consortia that play an important role in shaping typical sensorial properties. However, the microbial metabolism is considered difficult to control. Microbial community succession and the related gene expression were analysed during ripening of a traditional Italian cheese, identifying parameters that could be modified to accelerate ripening. Afterwards, we modulated ripening conditions and observed consistent changes in microbial community structure and function. We provide concrete evidence of the essential contribution of non starter lactic acid bacteria in ripening related activities. An increase in the ripening temperature promoted the expression of genes related to proteolysis, lipolysis and amino acid/lipid catabolism and significantly increases the cheese maturation rate. Moreover, temperature promoted microbial metabolisms were consistent with the metabolomic profiles of proteins and volatile organic compounds in the cheese. The results clearly indicate how processing driven microbiome responses can be modulated in order to optimize production efficiency and product quality.
Microbial benefits and risks of raw milk cheese

Consumer preference for raw milk cheese is continually growing, owing to its more intense and varied flavor than pasteurized milk cheese. Flavor development in raw milk cheese is mainly governed by its naturally existing microbial community, which also contributes to the inhibition of food borne pathogenic bacterial growth. Lactic acid bacteria, the dominant indigenous microorganisms of raw milk cheese, produce pathogen inhibiting substances such as bacteriocin, organic acids, and hydrogen peroxide, and it is possible to manufacture cheese with desirable microbiological qualities. Nonetheless, outbreaks of food borne illnesses have been linked to the consumption of raw milk cheese, and concerns have been raised regarding the microbiological safety of cheese manufactured from raw milk. Consequently, efficient and accurate methods for detecting contaminated bacterial pathogens in raw milk cheese have been promptly developed, including conventional plating, PCR based technology, and immunoassay integrated methods. The microbiological risk of the cheese can be reduced by proper ripening processing. However, additionally, hygiene in the environments for milk production and cheesemaking and the post manufacturing stage needs to be constantly microbiologically monitored.
Outlining triple bottom line contexts in urban tourism regeneration

This viewpoint offers perspective on pressing issues concerning urban tourism planning, policy and development. This paper outlines how different approaches and contexts of urban tourism regeneration, planning and development are considered in relation to the triple bottom line. Triple bottom line approaches are widely recognized by scholars, teachers, planners and businesses in the area of tourism when planning for sustainable tourism futures. While notions of people, profit and planet are important to conceptually outline, it is important to reflect on the recent literature and examples that emphasise contexts of sustainability. It must be noted that sustainability is often regarded as a term that looks at the environment and financial growth. Increasingly, researchers are focusing on social impacts seeking to address opportunities such as new enterprises, volunteering, education and training, in addition to restored place and community pride. This viewpoint attempts to present perspectives and encourage directions to further consider in urban tourism research, with an emphasis on sustainability and regeneration.
Efficient block sparse model based algorithm for photoacoustic image reconstruction
Venue: Biomed. Signal Process. Control.

The model based algorithm for photoacoustic imaging (PAI) has been proved to be stable and accurate. However, its reconstruction is computationally burdensome which limits its application in the practical PAI. In this paper, we proposed a block sparse discrete cosine transform (BS DCT) model based PAI reconstruction algorithm in order to improve the computational efficiency of the model based PAI reconstruction. We adopted the discrete cosine transform (DCT) to eliminate the minor coefficients and reduce the data scale. A block sparse based iterative method was proposed to accomplish the image reconstruction. Due to its block independent nature, we used the CPU based parallel calculation implementation to accelerate the reconstruction. During the iterative reconstruction, the number of required iterations was reduced by adopting the fast converging optimization Barzilai Borwein method. The numerical simulations and in vitro experiments were carried out. The results has shown that the reconstruction quality is equivalent to the state of the art iterative algorithms. Our algorithm requires less number of iterations with a reduced data scale and significant acceleration through the parallel calculation implementation. In conclusion, the BS DCT algorithm may be an effectively accelerated practical algorithm for the PAI reconstruction.
Envision of Student's Concert Using Supervised Learning Techniques

Educational data mining is an emerging technology concerned with developing methods for exploring the various unique data that exists in the educational settings and uses them to understand the students as well as the domain in which they learn. Educational domain consists of a lot of data related to students, teachers and other learning strategies. Classification algorithms can be used on various educational data to mine the academic records. It can be used to predict student's outcome based on their previous academic performance. The various predictive algorithms like, C4.5, Random tree are applied on student's previous academic results to predict the outcome of the students in the university examination. The prediction would help the tutor in understanding the progress and attitude of the student towards the studies. It would also help them to identify the students who are constantly improving in their studies and help them to achieve a higher percentage. It also helps them to identify the underperformers so that extra effort can be taken to achieve a better result. The algorithms are analyzed based on their accuracy of predicting the result, the recall and the precision values. The accuracy of the algorithm is predicted by comparing the output generated by the algorithm with the original result obtained by the students in the university examination.
Alternative Roles of STAT3 and MAPK Signaling Pathways in the MMPs Activation and Progression of Lung Injury Induced by Cigarette Smoke Exposure in ACE2 Knockout Mice
Venue: International journal of biological sciences

Inflammation mediated abnormalities in the renin angiotensin system (RAS) and expression of matrix metalloproteinases (MMPs) are implicated in the pathogenesis of lung injury. Angiotensin converting enzyme II (ACE2) an angiotensin converting enzyme (ACE) homologue that displays antagonist effects on ACE/angiotensin II (Ang II) axis, could also play a protective role against lung diseases. However, the relationship between ACE2 and MMPs activation in lung injury is still largely unclear. The purpose of this study is to investigate whether MMPs activity could be affected by ACE2 and which ACE2 derived signaling pathways could be also involved via using a mouse model with lung injury induced by cigarette smoke (CS) exposure for 1 to 3 weeks. Wild type (WT; C57BL/6) and ACE2 KO mice (ACE2 were utilized to study CS induced lung injury. Increases in the resting respiratory rate (RRR) pulmonary immunokines, leukocyte infiltration and bronchial hyperplasia were observed in the CS exposed mice. Compared to WT mice, more serious physiopathological changes were found in ACE2 mice in the first week of CS exposure. CS exposure increased pulmonary ACE and ACE2 activities in WT mice, and significantly increased ACE in ACE2 mice. Furthermore, the activity of pulmonary MMPs was decreased in CS exposed WT mice, whereas this activity was increased in ACE2 mice. CS exposure increased the pulmonary p p38, p JNK and p ERK1/2 level in all mice. In ACE2 mice, a significant increase p STAT3 signaling was detected; however, no effect was observed on the p STAT3 level in WT mice. Our results support the hypothesis that ACE2 deficiency influences MMPs activation and STAT3 phosphorylation signaling to promote more pulmonary inflammation in the development of lung injury.
Pulmonary Angiotensin Converting Enzyme 2 (ACE2) and Inflammatory Lung Disease
Venue: Shock

In response to infectious and, in some instances, noninfectious insults, the affected tissues/cells of the host undergo inflammation. However, uncontrolled inflammation could be detrimental to the host, resulting in inflammatory disease, such as inflammatory lung disease. Although the etiology of the disease is well defined, the underling pathogenesis is still incompletely understood. The renin angiotensin system (RAS) one of the primary cardiovascular regulatory systems, has been proposed to be involved in the pathogenesis of inflammatory lung disease. In particular, the RAS has been implicated as advances in the understanding of the multifunctionality of individual components of the system have been made, and by the fact that the RAS acts not only systemically, but also locally in a variety of tissues, including the lung. Angiotensin converting enzyme 2 (ACE2) a relatively new member of the RAS, has drawn extensive attention since 2003, because of the findings that ACE2 is the receptor for SARS Corona virus and that maintenance of normal ACE2 levels in the lung is beneficial for the host to combat inflammatory lung disease. Nevertheless, the mechanism through which ACE2 plays a role in inflammatory lung disease has not been clearly identified. In an attempt to summarize current literature findings and progress made in uncovering the role of ACE2 in inflammatory lung disease, this review will focus on recent studies examining pulmonary ACE2 biology, its roles in inflammatory lung disease pathogenesis and possible underlying mechanisms. Finally, we will discuss pulmonary ACE2 as a potential therapeutic target for inflammatory lung disease.
Activation of angiotensin converting enzyme 2 (ACE2) attenuates allergic airway inflammation in rat asthma model.
Venue: Toxicology and applied pharmacology

Angiotensin I converting enzyme (ACE) is positively correlated to asthma, chronic obstructive pulmonary disease (COPD) acute respiratory distress syndrome (ARDS) and is highly expressed in lungs. ACE2, the counteracting enzyme of ACE, was proven to be protective in pulmonary, cardiovascular diseases. In the present study we checked the effect of ACE2 activation in animal model of asthma. Asthma was induced in male wistar rats by sensitization and challenge with ovalbumin and then treated with ACE2 activator, diminazene aceturate (DIZE) for 2weeks. 48h after last allergen challenge, animals were anesthetized, blood, BALF, femoral bone marrow lavage were collected for leucocyte count; trachea for measuring airway responsiveness to carbachol; lungs and heart were isolated for histological studies and western blotting. In our animal model, the characteristic features of asthma such as altered airway responsiveness to carbachol, eosinophilia and neutrophilia were observed. Western blotting revealed the increased pulmonary expression of ACE1, IL 1b, IL 4, NF kB, BCL2, p AKT, p p38 and decreased expression of ACE2 and IkB. DIZE treatment prevented these alterations. Intraalveolar interstitial thickening, inflammatory cell infiltration, interstitial fibrosis, oxidative stress and right ventricular hypertrophy in asthma control animals were also reversed by DIZE treatment. Activation of ACE2 by DIZE conferred protection against asthma as evident from biochemical, functional, histological and molecular parameters. To the best of our knowledge, we report for the first time that activation of ACE2 by DIZE prevents asthma progression by altering AKT, p38, NF kB and other inflammatory markers.
Influence of light exposure at nighttime on sleep development and body growth of preterm infants
Venue: Scientific reports

Previous studies have demonstrated that a light dark cycle has promoted better sleep development and weight gain in preterm infants than constant light or constant darkness. However, it was unknown whether brief light exposure at night for medical treatment and nursing care would compromise the benefits brought about by such a light dark cycle. To examine such possibility, we developed a special red LED light with a wavelength of >675 nm which preterm infants cannot perceive. Preterm infants born at <36 weeks' gestational age were randomly assigned for periodic exposure to either white or red LED light at night in a light dark cycle after transfer from the Neonatal Intensive Care Unit to the Growing Care Unit, used for supporting infants as they mature. Activity, nighttime crying and body weight were continuously monitored from enrolment until discharge. No significant difference in rest activity patterns, nighttime crying, or weight gain was observed between control and experimental groups. The data indicate that nursing care conducted at 3 to 4 hour intervals exposing infants to light for <15 minutes does not prevent the infants from developing circadian rest activity patterns, or proper body growth as long as the infants are exposed to regular light dark cycles.
Development of a noninvasive system for monitoring dairy cattle sleep.
Venue: Journal of dairy science

Limited research has been conducted to assess sleep in production livestock primarily because of limitations with monitoring capabilities. Consequently, biological understanding of production circumstances and facility options that affect sleep is limited. The objective of this study was to assess if data collected from a proof of concept, noninvasive 3 axis accelerometer device are correlated with sleep and wake like behaviors in dairy cattle. Four Holstein dairy cows housed at the University of Kentucky Coldstream Dairy in September 2013 were visually observed for 2 consecutive 24 h periods. The accelerometer device was attached to a harness positioned on the right side of each cow's neck. Times of classified behaviors of wake (standing, head up, alert, eyes open) or sleep like behaviors (lying, still, head resting on ground, eyes closed) were recorded continuously by 2 observers who each watched 2 cows at a time. The radial signal was extracted from 3 different axes of the accelerometer to obtain a motion signal independent of direction of movement. Radial signal features were examined for maximizing the performance of detecting sleep like behaviors using a Fisher's linear discriminant analysis classifier. The study included 652min of high activity wake behaviors and 107min of sleep like behavior among 4 cows. Results from a bootstrapping analysis showed an agreement between human observation and the linear discriminant analysis classifier, with an accuracy of 93.7+ 0.7% for wake behavior and 92.2+ 0.8% for sleep like behavior 95% confidence interval).This prototype shows promise in measuring sleep like behaviors. Improvements to both hardware and software should allow more accurate determinations of subtle head movements and respiratory movements that will further improve the assessment of these sleep like behaviors, including estimates of deep, light, and rapid eye movement sleep. These future studies will require simultaneous electroencephalography and electromyography measures and perhaps additional measures of arousal thresholds to validate this system for measuring true sleep.
MODELING AND ANALYSIS OF OUTER SHELL OF CRUISE MISSILE

The advent of the modern cruise missile, with less radar detection and the ability to fly at low altitudes in sub sonic speeds with precise navigation, placed an extensive liability on all weapon systems in defence.The purpose of this project is to present a preliminary analysis and design of a cruise missile which fulfill the mission requirements. This design project comprises the concept exploration and development stages of the full design process. While designing we should take dimensions as per our requirements and should have tolerances to design parts. CATIA V5 is used as design tool. The inlet temperature, pressure, density and altitude are the parameters to analyze the flow properties. The analysis done in the ANSYS WORKBENCH 14.5.This paper discuss the flow of the designed model. In this paper we are going to discuss key aspects in aerodynamics of wing and fin.
Multi target human gait classification using deep convolutional neural networks on micro doppler spectrograms
Venue: 2016 European Radar Conference (EuRAD)

This paper presents the use of a deep convolutional neural network (DCNN) in distinguishing between absence of human gait and the presence of single or multiple instances of human gait by applying the DCNN to micro Doppler spectrograms. The approach is evaluated for various radar frequencies and SNR levels using model data, while final validation is performed using X band CW radar measurements. Satisfactorily results are obtained by the DCNN while outperforming a few conventional classifiers, showing the possible benefits of deep learning approaches in human gait classification.
Human Detection and Activity Classification Based on Micro Doppler Signatures Using Deep Convolutional Neural Networks
Venue: IEEE Geoscience and Remote Sensing Letters

We propose the use of deep convolutional neural networks (DCNNs) for human detection and activity classification based on Doppler radar. Previously, proposed schemes for these problems remained in the conventional supervised learning paradigm that relies on the design of handcrafted features. Whereas these schemes attained high accuracy, the requirement for domain knowledge of each problem limits the scalability of the proposed schemes. In this letter, we present an alternative deep learning approach. We apply the DCNN, one of the most successful deep learning algorithms, directly to a raw micro Doppler spectrogram for both human detection and activity classification problem. The DCNN can jointly learn the necessary features and classification boundaries using the measured data without employing any explicit features on the micro Doppler signals. We show that the DCNN can achieve accuracy results of 97.6% for human detection and 90.9% for human activity classification.