nils-herrmann/clean_scirepeval huggingface dataset:
Agro Environmental Benefit and Risk of Manure and Bone Meal Derived Pyrogenic Carbonaceous Materials as Soil Amendments: Availability of PAHs, PTEs, and P
Year: 2019

The worldwide boom of biochar and pyrogenic carbonaceous material application as a potential soil additive has brought about not only agricultural benefits such as enhanced crop yield, nutrients supply (P) and soil organic carbon increase, but also, on the other hand, environmental risk of organic (polycyclic aromatic hydrocarbons (PAHs) and potentially toxic element (PTE) penetration into arable soils. Therefore, our study assessed pyrogenic carbonaceous materials (PCM) produced from the P rich feedstocks chicken manure (CM) and bone meal (BM) as promising and safe alternatives for inorganic P fertilizers. Pyrogenic materials produced in the process of slow pyrolysis at residence time 2 h, 400 and 500 degC, were characterized by determination of pH, electrical conductivity (EC) elemental analysis of total C, H, N, S scanning electron microscopy (SEM) total content of P, selected potentially toxic elements (PTEs) and available forms of PTEs and P by diethylenetriaminepentaacetic acid (DTPA) and calcium acetate lactate (CAL) extractions. CMPCM4, CMPCM5, BMPCM4, and BMPCM5 were characterized by determination of total 16 US EPA (U.S. Environmental Protection Agency) PAHs by toluene extraction protocol and available concentrations by Tenax resin approach. Additionally, CMPCM4, CMPCM4, BMPCM4, and BMPCM5 were tested in earthworm avoidance test with Eisenia foetita and short term rye seedling germination test. Obtained results showed decreasing of total carbon in the order of BM BMPCM4 BMPCM5 and increasing in the order of CM CMPCM4 CMPCM5. Total phosphorus content increased from 56.8 1.7 g kg 1 (BM) to 85.2 4.2 g kg 1 (BMPCM4) to 110.5 7.0 g kg 1 (BMPCM5) In the case of chicken manure derived pyrogenic materials, total phosphorus content increased in the order of CM (22.9 2.0 g kg 1) CMPCM4 (37.0 4.5 g kg 1) CMPCM5 (40.0 3.4 g kg 1) Availability of selected PTEs and P decreased in pyrogenic materials compared to feedstock. Total concentration of 16 US EPA PAHs in BMPCM4 and BMPCM5 was 3.92 mg kg 1; CMPCM4, 7.33 mg kg 1; and CMPCM, 6.69 mg kg 1. The Tenax available 16 PAHs showed concentrations of 0.53 mg kg 1 for BMPCM4, 0.26 mg kg 1 for BMPCM5, 1.13 mg kg 1 for CMPCM4, and 0.35 mg kg 1 for CMPCM5. Total P concentrations determined in rye aboveground tissues showed the highest accumulation ability in the case of CMPCM5 compared to other samples. Pyrogenic carbonaceous materials produced from chicken manure and bone meal at 400 and 500 degC have the potential to be P slow release fertilizers and may be ecologically safe.
Dynamic Balance Method for Grading the Chain Drive Double Threshing Drum of a Combine Harvester
Year: 2020

Although the individual threshing drum of a combine harvester was balanced on a dynamic balancing machine before it is assembled, there were still unbalances after multiple drums were assembled with the chain drive. In this paper, the double drums with a chain drive of a crawler combined harvester were selected as the research subject. The aim of this study was to develop a dynamic unbalance mode for grading chain drive double drums. Based on the dynamic unbalance characteristics of the main driven drum, the experimental research on the radial balance of the driven drum end face was carried out. It was known that the chain drive had a direct and obvious influence on the unbalanced phase of the drum. The unbalance of the drive load had an obvious effect on unbalanced amplitude of an active drum through the transfer characteristics of the chain drive. For the multi stage transmission characteristics of a combine harvester, a step by step balanced grading chain drive double drum dynamic balancing method was practiced. Results showed that the unbalanced amplitude after balancing threshing drum I chain transmission mode of the combine harvester can be reduced by a maximum of 91% Simultaneously, the unbalanced amplitude of threshing drum II can reduced by a maximum of 69.2% The size and position of the wrap angle of the chain drive would directly affect the phase of the two equivalent unbalanced masses.
Phenomenological ReseaRch methods in the Psychological study of sexuality
Year: 2013

In this chapter, we review issues central to the use of phenomenological research methods in the psychological study of sexuality. Phenomenological methods are characterized by close attention to the details of participants' lived experience as well as an emphasis on participants' interpretation of their experience. This group of methods is essential in psychological research on sexuality because it helps researchers to understand the phenomenon of sexuality as it is experienced in everyday life and under constant change. Beginning with a summary of the epistemological foundations of phenomenological research methods in psychology, we present an overview of several popular approaches to data collection and analysis that facilitate phenomenological investigations of sexuality. Classical foundations, future directions, limitations, advantages, and clinical and policy relevance are discussed via key exemplar studies of sexuality related phenomena using phenomenological research methods.
Assessment of effectiveness of structured teaching programme on knowledge of the Anganwadi workers regarding prevention of malnutrition among under five children in selected ICDS centers at Jaipur
Year: 2017

Growth and development of children till the age of 5 6 years is very important. Any adverse influence in this period related to malnutrition can lead to severe limitation in their development. Anganwadi workers at the local level and supportive personnel from health departments administer services, which include the following: supplementary nutrition, immunization, health checkups, referral services, treatment of minor illnesses, nutrition and health education for women, preschool education for children aged 3 6 years, and co operation with improvement in supportive service such as water supply and sanitation. The present study was undertaken to assess the effectiveness of structured teaching programme on knowledge of the Anganwadi workers regarding prevention of malnutrition among under five children in selected ICDS centers. One group pre test post test research design, which is preexperimental design, was selected to assess the knowledge of Anganwadi workers and the population was 50 aganwadi workers by using purposive sampling technique. The tool used was structured knowledge questionnaire. The overall analysis of the data reveals that the maximum mean percentage obtained by the Anganwadi workers is found in the aspect of Type, Causes Clinical manifestation (51.33% followed by definition and nutrients (48.20% introduction (48% and least mean percentage obtained in the aspect of diagnosis, prevention, management complication (44.20% The overall Mean+ SD of pretest knowledge score was 19.06+ 6.94 and mean percentage of 47.65% The maximum mean percentage obtained by the Anganwadi workers is found in the aspect of Category of introduction (87.75% followed by definition nutrients (79.6% diagnosis, prevention, management complication (75.9% and least mean percentage obtained in the aspect of types, Causes and clinical manifestation (67.66) The overall Mean+ SD of post test knowledge score was 30.98+ 6.24 and mean percentage of 77.45% It is evident that the obtained "t" value 18.62 is greater than the table value at 0.05 level of significance. Therefore, "t" value is found to be significant. It means there is gain in knowledge level of Anganwadi workers regarding prevention of malnutrition.
Enhanced in plane thermoelectric figure of merit in p type SiGe thin films by nanograin boundaries.
Venue: Nanoscale
Year: 2015

P Type polycrystalline silicon germanium (SiGe) thin films are grown by low pressure chemical vapor deposition (LPCVD) and their thermoelectric properties are characterized from 120 K to 300 K for potential application in integrated microscale cooling. The naturally formed grain boundaries are found to play a crucial role in determining both the charge and thermal transport properties of the films. Particularly, the grain boundaries create energy barriers for charge transport which lead to different dependences of charge mobility on doping concentration and temperature from the bulk counterparts. Meanwhile, the unique columnar grain structures result in remarkable thermal conductivity anisotropy with the in plane thermal conductivities of SiGe films about 50% lower than the cross plane values. By optimizing the growth conditions and doping level, a high in plane figure of merit (ZT) of 0.2 for SiGe films is achieved at 300 K, which is about 100% higher than the previous record for p type SiGe alloys, mainly due to the significant reduction in the in plane thermal conductivity caused by nanograin boundaries. The low cost and excellent scalability of LPCVD render these high performance SiGe films ideal candidates for thin film thermoelectric applications.
A context sensitive chunk BPTT approach to training deep LSTM/BLSTM recurrent neural networks for offline handwriting recognition
Venue: 2015 13th International Conference on Document Analysis and Recognition (ICDAR)
Year: 2015

We propose a context sensitive chunk based back propagation through time (BPTT) approach to training deep (bidirectional) long short term memory (B)LSTM) recurrent neural networks (RNN) that splits each training sequence into chunks with appended contextual observations for character modeling of offline handwriting recognition. Using short context sensitive chunks in both training and recognition brings following benefits: (1) the learned (B)LSTM will model mainly local character image dependency and the effect of long range language model information reflected in training data is reduced; (2) mini batch based training on GPU can be made more efficient; (3) low latency BLSTM based handwriting recognition is made possible by incurring only a delay of a short chunk rather than a whole sentence. Our approach is evaluated on IAM offline handwriting recognition benchmark task and performs better than the previous state of the art BPTT based approaches.
Efficient Multi Accuracy Computations of Complex Functions with Complex Arguments
Year: 2018

We present an efficient multi accuracy algorithm for the computations of a set of special functions of a complex argument, z=x+iy. These functions include the complex probability function w(z) and closely related functions such as the error function erf(z) complementary error function erfc(z) imaginary error function erfi(z) scaled complementary error function, erfcx(z) the plasma dispersion function Z(z) Dawson s function Daw(z) and Fresnel integrals S(z) and C(z) Computational results from the present algorithm are compared with results from competitive algorithms and widely used software packages showing superior accuracy and efficiency of the present algorithm. In particular, the present results highlight concerns about the accuracy of evaluating such special functions using commercial packages like Mathematica and free/open source packages like the MIT C+ package.
Soil and Freshwater Micro Algae as a Food Source for Invertebrates in Extreme Environments
Year: 2007

Dr. Alena Lukesova is currently the senior scientist at the Institute of Soil Biology, Biological Centre, Academy of Sciences of the Czech Republic. She obtained her PhD from the Academy of Sciences of the Czech Republic in 1990. She deals with the taxonomy, ecology and ecophysiology of soil algae and cyanobacteria. Alena Lukesova's scientific interests are in the areas of the role algae and cyanobacteria in colonization and succession processes, biological crust formation, algae invertebrate interactions, algae of extreme habitats, low temperature stress and cryopreservation of soil algae and cyanobacteria.
Multi modal Dense Video Captioning
Venue: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Year: 2020

Dense video captioning is a task of localizing interesting events from an untrimmed video and producing textual description (captions) for each localized event. Most of the previous works in dense video captioning are solely based on visual information and completely ignore the audio track. However, audio, and speech, in particular, are vital cues for a human observer in understanding an environment. In this paper, we present a new dense video captioning approach that is able to utilize any number of modalities for event description. Specifically, we show how audio and speech modalities may improve a dense video captioning model. We apply automatic speech recognition (ASR) system to obtain a temporally aligned textual description of the speech (similar to subtitles) and treat it as a separate input alongside video frames and the corresponding audio track. We formulate the captioning task as a machine translation problem and utilize recently proposed Transformer architecture to convert multi modal input data into textual descriptions. We demonstrate the performance of our model on ActivityNet Captions dataset. The ablation studies indicate a considerable contribution from audio and speech components suggesting that these modalities contain substantial complementary information to video frames. Furthermore, we provide an in depth analysis of the ActivityNet Caption results by leveraging the category tags obtained from original YouTube videos. Code is publicly available: github.com/v iashin/MDVC.
Retinal Lesion Detection With Deep Learning Using Image Patches
Venue: Investigative ophthalmology visual science
Year: 2018

To develop an automated method of localizing and discerning multiple types of findings in retinal images using a limited set of training data without hard coded feature extraction as a step toward generalizing these methods to rare disease detection in which a limited number of training data are available.  Two ophthalmologists verified 243 retinal images, labeling important subsections of the image to generate 1324 image patches containing either hemorrhages, microaneurysms, exudates, retinal neovascularization, or normal appearing structures from the Kaggle dataset. These image patches were used to train one standard convolutional neural network to predict the presence of these five classes. A sliding window method was used to generate probability maps across the entire image.  The method was validated on the eOphta dataset of 148 whole retinal images for microaneurysms and 47 for exudates. A pixel wise classification of the area under the curve of the receiver operating characteristic of 0.94 and 0.95, as well as a lesion wise area under the precision recall curve of 0.86 and 0.64, was achieved for microaneurysms and exudates, respectively.  Regionally trained convolutional neural networks can generate lesion specific probability maps able to detect and distinguish between subtle pathologic lesions with only a few hundred training examples per lesion.
Police social work and community policing
Year: 2016

Social work as a discipline has made progress in many areas, including school social work, military social work, and mental health, to name a few. Conversely, police social work has seen a reduction in advancement within the last three decades. Police departments and social workers have traditionally worked together to deal with community problems. In fact effective prevention, intervention, and stabilization require more than police action and goes beyond the capability of any single agency. Studies show that social services provision has always been a key part of policing, operating alongside service to victims of crimes and the enforcement of the law against offenders. The purpose of this study is twofold: (1) to explore whether police departments in the state of Minnesota provide social services to crime victims and witnesses and to residents seeking social service assistance in non crime situations; and (2) to explore strategies for hiring social workers within the agency, and to enhance effective collaboration with the new hires during specific types of responses to interventions, such as mental health crises and domestic violence. A case study design methodology, specifically involving in depth interviews of 40 Minnesota police chiefs and the utilization of documentations are employed in this study.
Developmental Changes in Genetic Relationships Between Traits and Disease: Analyses of Genetic Overlaps Between Social communication Difficulties, Autism Spectrum Disorders and Schizophrenia
Year: 2015

The phenotypic overlap between Autism Spectrum Disorders (ASD) and schizophrenia is complex and dates back to Kanner in 1943, including symptomatic similarities such as social withdrawal, communication impairment, and poor eye contact. Recent theories proposed a "continuum of psychosis" despite differences between disorders, based on shared genetic susceptibility among psychiatric conditions and genetic overlap with milder symptoms in unaffected individuals from the general population. Symptoms of ASD however typically occur during early childhood, whereas the first signs of schizophrenia appear during adolescence and early adulthood. Thus, genetic links with population based traits may also follow a developmental pattern. Our study was conducted to investigate genetic relationships between social communication difficulties during childhood and adolescence and both common variation in clinical ASD and schizophrenia.
Energy and Delay Tradeoff for Application Offloading in Mobile Cloud Computing
Venue: IEEE Systems Journal
Year: 2017

Recent work shows that offloading a mobile application from mobile devices to cloud servers can significantly reduce the energy consumption of mobile devices, thus extending the lifetime of mobile devices. However, previous work only considers the energy saving of mobile devices while ignoring the execution delay of mobile applications. To reduce the energy consumption of mobile devices, one may offload as many mobile applications as possible. However, offloading to cloud servers may incur a large execution delay because of the waiting time at the servers or the communication delay from the mobile devices to the servers. Thus, to balance the tradeoff between energy consumption and execution delay of mobile applications, it is necessary to determine whether the mobile application should be offloaded to the cloud server or run locally at the mobile devices. In this paper, we first formulate a joint optimization problem, which minimizes both the energy consumption at the mobile devices and the execution delay of mobile applications. We prove that the proposed problem is NP hard. For a special case with unlimited residual energy at the mobile device and the same amount of resources required by each mobile application, we present a polynomial time optimal solution. We also propose an efficient heuristic algorithm to solve the general case of the problem. Finally, simulation results demonstrate the effectiveness of the proposed scheme.
Vehicular traffic analysis from social media data
Venue: 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Year: 2016

In this paper, we address the problem of vehicular traffic congestion occurring in densely populated cities. Towards this we propose to provide a framework for optimal vehicular traffic solution using social media live data. Typically, the traffic congestion problem addressed in literature focuses on usage of dedicated traffic sensors and satellite information which is quite expensive. However, many urban commuters tend to post updates about traffic on various social media in the form of tweets or Facebook posts. With the copious amount of data made available upon traffic problems on social media sites, we collect historical data about traffic posts from specific cities and build a sentiment classifier to monitor commuters' emotions round the clock. The knowledge is used to analyze and predict traffic patterns in a given location. Also we identify the probable cause of a traffic congestion in a particular area by analyzing the collected historical data. Through our work, we are able to present an uncensored, economical and alternative approach to traditional methods for monitoring traffic congestion.
Solution Classification With Portable Smartphone Based Spectrometer System Under Variant Shooting Conditions by Using Convolutional Neural Network
Venue: IEEE Sensors Journal
Year: 2020

The rapid development of smartphone based devices has facilitated on site measurements, which approach to laboratory level instrument performance. However, the reliability of these instruments is inevitably limited by the external environment factors. Here, we report on a portable smartphone spectrometer without any external power supply. Using this spectrometer to analyze the diffractive patterns of multiple samples under variant shooting conditions, we verify the influence of external parameters on spectrum. Convolutional neural network is proposed here to perform solution classification under variant shooting conditions and the classification prediction accuracy is more than 99.5%
Achievements and challenges in power and signal integrity analyses of Set Top Box products
Venue: 2016 IEEE 20th Workshop on Signal and Power Integrity (SPI)
Year: 2016

Electrical Co design of IC package PCB products for Set Top Box applications has been changing quickly in the past years. The new generation of processors (A53, A57. is indeed bringing interesting challenges as the business seems to be looking for the most power efficient CPU architectures (DMIPS/W) Moreover standards of high speed interfaces are being released with increasing speeds (HDMI2.1, USB3.1, LP/DDR4. This paper presents the achievements and the challenges in the field of IC package PCB electrical simulation and co design, based on examples of recent product developments. Correlations between simulations and measurements are presented as it plays an important role in the development of the simulation methodologies. The main focus of this paper is on power analysis, power integrity (PI) studies and performance prediction. Then a case of signal integrity (SI) studies is briefly discussed. Conclusions on links between physical IC package PCB co design and EM/PI/SI are presented.
Bio ecology of rice moth Corcyra cephalonica (Stainton) on groundnut seeds
Year: 2020

Biology of rice moth, Corcyra cephalonica (Stainton) was studied under controlled conditions at a temperature of 27 1.8 0C and 70 4.5% relative humidity in laboratory on groundnut variety GG 20, respectively. The mean length of eggs, full grown larva, pupa and adult wing span were 0.39 0.03, 9.37 0.71, 8.56 0.55, 17.45 1.37 (male) and 18.37 1.66 (female) mm, respectively. Duration of egg, larva, pupa and adult ranged from 4.16 0.80, 43.65 4.52, 9.1 0.96, 7.85 0.87 (male) and 8.55 0.94 (female) days, respectively. The average fecundity of rice moth was 202.2 44.57 eggs with a 94% hatching. The survival percentage (S) mean development period (D) and growth index were 90 percent, 58.36 days and 1.54, respectively. The sex ratio of rice moth was 1:1.05.