nils-herrmann/clean_scirepeval huggingface dataset:
The green, blue and grey water footprint of crops and derived crops products
Year: 2010

This study quantifies the green, blue and grey water footprint of global crop production in a spatially explicit way for the period 1996 2005. The assessment improves upon earlier research by taking a high resolution approach, estimating the water footprint of 126 crops at a 5 by 5 arc minute grid. We have used a grid based dynamic water balance model to calculate crop water use over time, with a time step of one day. The model takes into account the daily soil water balance and climatic conditions for each grid cell. In addition, the water pollution associated with the use of nitrogen fertilizer in crop production is estimated for each grid cell. The crop evapotranspiration of additional 20 minor crops is calculated with the CROPWAT model. In addition, we have calculated the water footprint of more than two hundred derived crop products, including various flours, beverages, fibres and biofuels. We have used the water footprint assessment framework as in the guideline of the Water Footprint Network. Considering the water footprints of primary crops, we see that the global average water footprint per ton of crop increases from sugar crops (roughly 200 m3 ton 1) vegetables (300 m3 ton 1) roots and tubers (400 m3 ton 1) fruits (1000 m3 ton 1) cereals (1600 m3 ton 1) oil crops (2400 m3 ton 1) to pulses (4000 m3 ton 1) The water footprint varies, however, across different crops per crop category and per production region as well. Besides, if one considers the water footprint per kcal, the picture changes as well. When considered per ton of product, commodities with relatively large water footprints are: coffee, tea, cocoa, tobacco, spices, nuts, rubber and fibres. The analysis of water footprints of different biofuels shows that bio ethanol has a lower water footprint (in m3 GJ 1) than biodiesel, which supports earlier analyses. The crop used matters significantly as well: the global average water footprint of bio ethanol based on sugar beet amounts to 51 m3 GJ 1, while this is 121 m3 GJ 1 for maize. The global water footprint related to crop production in the period 1996 2005 was 7404 billion cubic meters per year (78 green, 12 blue, 10 grey) A large total water footprint was calculated for wheat (1087 Gm3 yr 1) rice (992 Gm3 yr 1) and maize (770 Gm3 yr 1) Wheat and rice have the largest blue water footprints, together accounting for 45 of the global blue water footprint. At country level, the total water footprint was largest for India (1047 Gm3 yr 1) China (967 Gm3 yr 1) and the USA (826 Gm3 yr 1) A relatively large total blue water footprint as a result of crop production is observed in the Indus river basin (117 Gm3 yr 1) and the Ganges river basin (108 Gm3 yr 1) The two basins together account for 25 of the blue water footprint related to global crop production. Globally, rain fed agriculture has a water footprint of 5173 Gm3 yr 1 (91 green, 9 grey) irrigated agriculture has a water footprint of 2230 Gm3 yr 1 (48 green, 40 blue, 12 grey)
Unsupervised Feature Learning for Audio Analysis
Venue: ICLR
Year: 2017

Identifying acoustic events from a continuously streaming audio source is of interest for many applications including environmental monitoring for basic research. In this scenario neither different event classes are known nor what distinguishes one class from another. Therefore, an unsupervised feature learning method for exploration of audio data is presented in this paper. It incorporates the two following novel contributions: First, an audio frame predictor based on a Convolutional LSTM autoencoder is demonstrated, which is used for unsupervised feature extraction. Second, a training method for autoencoders is presented, which leads to distinct features by amplifying event similarities. In comparison to standard approaches, the features extracted from the audio frame predictor trained with the novel approach show 13 better results when used with a classifier and 36 better results when used for clustering.
Persistent Inequality in Guinea Bissau: The Role of France, the CFA Franc, and Long Term Currency Imperialism
Year: 2020

Guinea Bissau is among the world's most unequal countries. Its use of the CFA currency, pegged to the euro and controlled by France, raises continuing concern This paper investigates the impact of joining the C.F.A zone (1997) on Guinea Bissau per capita GDP, fisheries capture, and rice yields. In the absence of randomization, we apply a synthetic control method SCM (Abadie and Gardeazabal, 2003) to build a counterfactual using a weighted combination of potential countries as control units and estimate the effects of entering the CFA zone on economic growth. The SCM results for Guinea Bissau suggested that joining the CFA union contributed substantially to the decline of per capita GDP, fisheries capture, and rice yields. Other economic indicators such as cotton seed net per capita production and cashew nuts yields included in our study were inconclusive. Overall, Guinea Bissau did not show evidence of economic growth after it entered the Franc zone. The country has been in long term decline since then.
KEPEMIMPINAN PERILAKU ORGANISASI (Konsep dan Perkembangan)
Year: 2020

Dalam pembentukan perilaku organisasi yang baik, banyak hal yang dilakukan oleh manajemen organisasi mulai dari mendiagnosa masalah SDM, menanamkan secara kuat budaya organisasi, shaping behavior (pembentukan perilaku) menerapkan percepatan organisasi ke AGILE, dan lain sebagainya. Kajian perilaku organisasi ditujukan dalam rangka meningkatkan keahlian individu dan pemberdayaan karyawan atau anggota organisasi, yang bertujuan untuk memberikan stimulus dan upaya inovasi dalam rangka menciptakan perubahan, memperluas jaringan organisasi, membantu karyawan menyeimbangkan antar kehidupan pribadi dengan lingkungan kerja, dan meningkatkan prilaku positif yang sesuai dengan standar etika organisasi atau profesi. Sedangkan kajian kepemimpinan organisasi salah satunya adalah bagaimana mewujudkan hal hal tersebut.
Exact solutions of fractional heat like and wave like equations with variable coefficients
Year: 2014

This paper aims to apply fractional variational iteration method using He's polynomials (FVIMHP) to obtain exact solutions for variable coefficient fractional heat like and wave like equations with fractional order initial and boundary conditions.  The approach is based on FVIMHP. The authors choose as some examples to illustrate the validity and the advantages of the method.  The results reveal that the FVIMHP method provides a very effective, convenient and powerful mathematical tool for solving fractional differential equations.  The variable coefficient fractional heat like and wave like equations with fractional order initial and boundary conditions are solved first. Illustrative examples are included to demonstrate the validity and applicability of the method.
The diagnosis value of Color Doppler Flow Imaging in Nodular Goiter
Year: 2006

To explore the diagnostic value of Color Doppler Ultrasound in nodular goiter(NG).Methods Review 88 cases NG of Image,analyze and compare the characteristics of Image with pathology results. 88 cases as NG were confirmed by operation pathology diagnosis,by Ultrasound before operation,79 cases were diagnosed NG(diagnosis accuracy rate 90%,misdiagnosis is Thyroid adenoma 6 cases,Thyroid carcinoma 2 cases,Subacute thyrioditis 1 case,for promote diagnostic accuracy rate of NG.Conclusion The imaging of NG is complex,we should grasp its characteristics although the imaging have some specificity,and we should pay attention to the differential diagnosis.
Lesions of the Head Direction Cell System Increase Hippocampal Place Field Repetition
Venue: Current Biology
Year: 2017

A central tenet of systems neuroscience is that the mammalian hippocampus provides a cognitive map of the environment. This view is supported by the finding of place cells, neurons whose firing is tuned to specific locations in an animal's environment, within this brain region. Recent work, however, has shown that these cells repeat their firing fields across visually identical maze compartments [1, 2] This repetition is not observed if these compartments face different directions, suggesting that place cells use a directional input to differentiate otherwise similar local environments [3, 4] A clear candidate for this input is the head direction cell system. To test this, we disrupted the head direction cell system by lesioning the lateral mammillary nuclei and then recorded place cells as rats explored multiple, connected compartments, oriented in the same or in different directions. As shown previously, we found that place cells in control animals exhibited repeated fields in compartments arranged in parallel, but not in compartments facing different directions. In contrast, the place cells of animals with lesions of the head direction cell system exhibited repeating fields in both conditions. Thus, directional information provided by the head direction cell system appears essential for the angular disambiguation by place cells of visually identical compartments.
Surface Enhanced Raman Scattering from an Ag Nanorod Array Substrate: The Site Dependent Enhancement and Layer Absorbance Effect
Year: 2009

We have designed experiments to put Raman probe molecules on different locations of Ag nanorod array substrates and found that the apparent enhancement factor for surface enhanced Raman scattering (SERS) is about 50 200 times from the surface of the nanorods than that from the Ag thin film surface under an Ag nanorods array. When excited from the top of Ag nanorod array substrates, the ratio of SERS intensity excited by s polarization to that excited by p polarization is 1.8 to 2.2, while when excited from the bottom of Ag nanorod array substrates, this ratio becomes 0.77. These effects cannot be interpreted directly by the local electric field enhancement effect. By combining the local electric field effect calculated by the three dimensional finite difference time domain method and the anisotropic optical absorbance of the SERS signal from the anisotropic Ag nanorod array, the numerical calculations semiquantitatively agree with the experimental results.
Economic Freedom, Country Risk and Cost Efficiency in Jordan and the GCC Countries
Year: 2020

Using data from 2003 to 2010, we examine the impact of economic freedom and country risks on the bank costs of potential Gulf Cooperation Council (GCC) union. In estimating a common frontier, this article employs Stochastic Frontier Approach (SFA) to control for country specific variables, that is, economic freedom, country risk, macroeconomic conditions, bank accessibility and bank structure, for an unbalanced panel of 90 Jordanian and the GCC countries' banks. This article further estimates bank efficiency levels in the potential GCC union member countries to shed some light on the capability and capacity of the banks to compete and survive within the future GCC union. We find that economic freedom helps in reducing potential bank costs. Enhancing economic freedom is crucial for the region to attract more investments and create a viable banking system. In order for the GCC members to have a successful union and achieve the objectives faster, it is important to have a similar level of economic performance, in particular in the banking sector.
Testing ERE Cycle in Teaching Business Communication Courses: Experiential Learning Strategies
Venue: Journal of Education and Educational Development
Year: 2019

Effective communication skills demonstrate the capacity and efficacy of any business graduate; however, the business industries have continuously raised their concerns on the lack of effective business communication (BC) skills, to serve the requirements of rapidly growing communication within and outside the organizations. Among many factors, teaching methods at higher education have been identified as a major factor that does not allow working skills to be developed. Scholars and researchers have tried to explore and test Experiential Learning (EL) techniques in teaching different courses of business administration programs. EL theory presents a playfield where learners can learn the best by doing (Kolb, 1984) Although business education around the world has already inculcated EL strategies into its system, in Pakistan EL theory is at its initial stage. In this regard, the researcher developed an ERE cycle which was based on Kolb's (1984) EL theory and tested its impact on the grades of the students of oral and written communication skills. The study was conducted using one sample t test in the paradigm of quantitative research. Three classes of BBA and MBA from oral and written communication courses were selected for this study. This research compared mean scores of these classes with the population mean over the last three years. The results showed a significant positive difference between the sample mean scores and population mean. The study proved that EL based ERE cycle could prove very effective in the enhancement of the skills of business communication students that were reflected in their performance in exams. The study aimed to provide communication faculty, trainers and institutes the opportunity to explore and utilize the effectiveness of the ERE cycle and perform further researches to extend the utilities of EL based teaching methods.
Embedding Based Speaker Adaptive Training of Deep Neural Networks
Venue: INTERSPEECH
Year: 2017

An embedding based speaker adaptive training (SAT) approach is proposed and investigated in this paper for deep neural network acoustic modeling. In this approach, speaker embedding vectors, which are a constant given a particular speaker, are mapped through a control network to layer dependent element wise affine transformations to canonicalize the internal feature representations at the output of hidden layers of a main network. The control network for generating the speaker dependent mappings is jointly estimated with the main network for the overall speaker adaptive acoustic modeling. Experiments on large vocabulary continuous speech recognition (LVCSR) tasks show that the proposed SAT scheme can yield superior performance over the widely used speaker aware training using i vectors with speaker adapted input features.
Single Step FRET Based Detection of Femtomoles DNA
Venue: Sensors
Year: 2019

Sensitive detection of nucleic acids and identification of single nucleotide polymorphism (SNP) is crucial in diagnosis of genetic diseases. Many strategies have been developed for detection and analysis of DNA, including fluorescence, electrical, optical, and mechanical methods. Recent advances in fluorescence resonance energy transfer (FRET) based sensing have provided a new avenue for sensitive and quantitative detection of various types of biomolecules in simple, rapid, and recyclable platforms. Here, we report single step FRET based DNA sensors designed to work via a toehold mediated strand displacement (TMSD) process, leading to a distinct change in the FRET efficiency upon target binding. Using single molecule FRET (smFRET) we show that these sensors can be regenerated in situ, and they allow detection of femtomoles DNA without the need for target amplification while still using a dramatically small sample size (fewer than three orders of magnitude compared to the typical sample size of bulk fluorescence) In addition, these single molecule sensors exhibit a dynamic range of approximately two orders of magnitude. Using one of the sensors, we demonstrate that the single base mismatch sequence can be discriminated from a fully matched DNA target, showing a high specificity of the method. These sensors with simple and recyclable design, sensitive detection of DNA, and the ability to discriminate single base mismatch sequences may find applications in quantitative analysis of nucleic acid biomarkers.
Ultra micro liquid volume measurement system based on potentiometrie titration principle
Venue: 2016 International Conference on Integrated Circuits and Microsystems (ICICM)
Year: 2016

In order to overcome the shortcoming that influences of evaporation capacity on the gravimetric method, and meet the requirement of online measurement, a non gravimetric method is introduced for measuring micro liquid volume. According to Faraday's law and Karl Fischer electrochemical principle, the Karl Fischer potentiometric titration method (KFCT method) is also investigated for micro liquid volume measurement, which calculates micro water content by measuring consumed electric quantity in electrolytic process, and obtains the micro liquid volume by combining liquid density. Due to pressure variation the correction is used for micro liquid volume calculation. Comparing with gravimetric method, experimental systems for non gravimetric method is designed. The experiment indicated that the test result obtained by using KFCT method is in good agreement with that the test result obtained by using gravimetric method, and meets the technical requirements of ISO 8655, but the measured result of KFCT method is slightly higher. Comparing with gravimetric method, the non gravimetric method provides a better solution for micro liquid volume measurement, which has lower requirements on the measurement environment, is easier to implement on line calibration, and effectively reduce the impact of the liquid evaporation.
Extreme Trust Region Policy Optimization for Active Object Recognition
Venue: IEEE Transactions on Neural Networks and Learning Systems
Year: 2018

In this brief, we develop a deep reinforcement learning method to actively recognize objects by choosing a sequence of actions for an active camera that helps to discriminate between the objects. The method is realized using trust region policy optimization, in which the policy is realized by an extreme learning machine and, therefore, leads to efficient optimization algorithm. The experimental results on the publicly available data set show the advantages of the developed extreme trust region optimization method.
Prevalence and Therapies of Antibiotic Resistance in Staphylococcus aureus
Venue: Frontiers in Cellular and Infection Microbiology
Year: 2020

Infectious diseases are the second most important cause of human death worldwide; Staphylococcus aureus (S. aureus) is a very common human pathogenic microorganism that can trigger a variety of infectious diseases, such as skin and soft tissue infections, endocarditis, osteomyelitis, bacteremia, and lethal pneumonia. Moreover, according to the sensitivity to antibiotic drugs, S. aureus can be divided into methicillin sensitive Staphylococcus aureus (MSSA) and methicillin resistant Staphylococcus aureus (MRSA) In recent decades, due to the evolution of bacteria and the abuse of antibiotics, the drug resistance of S. aureus has gradually increased, the infection rate of MRSA has increased worldwide, and the clinical anti infective treatment for MRSA has become more difficult. Accumulating evidence has demonstrated that the resistance mechanisms of S. aureus are very complex, especially for MRSA, which is resistant to many kinds of antibiotics. Therefore, understanding the drug resistance of MRSA in a timely manner and elucidating its drug resistance mechanism at the molecular level are of great significance for the treatment of S. aureus infection. A large number of researchers believe that analyzing the molecular characteristics of S. aureus can help provide a basis for designing effective prevention and treatment measures against hospital infections caused by S. aureus and further monitor the evolution of S. aureus. This paper reviews the research status of MSSA and MRSA, the detailed mechanisms of the intrinsic antibiotic resistance and the acquired antibiotic resistance, the advanced research on anti MRSA antibiotics and novel therapeutic strategies for MRSA treatment.
Intramolecular Co reaction Accelerated Electrochemiluminescence of Polypeptide biomineralized Gold Nanoclusters for Targeted Detection of Biomarkers.
Venue: Analytical chemistry
Year: 2020

The development of label free electrochemiluminescence (ECL) based sensing technology for biomarkers detection has a congenital defect compare with non competitive sandwich type biosensor due to the lack of detection antibody conjugated with signal label. Nevertheless, it is still not difficult to realize ultrasensitive analysis benefit from the exploration of efficient sensing substrates and signal transducers. In this work, an innovative sensing system is purposed utilizing Fe2O3 nanoarrays (Fe2O3 NAs) as well ordered co reaction accelerator and polypeptide biomineralized gold nanoclusters (Au NCs) as signal transducer. Bifunctional peptide ligands of H2N MMYYHFRRHL COOH (MYH 10) is self designed, it can not only play a role of reductant and coupling reagent for clusters formation using MMYY sequence root in N terminal, but also act as connection for coupling carriers and immune molecules via HFRRHL region of C terminal. Additional intramolecular ECL emission between Au NCs and tris(3 aminoethyl)amine (TAEA) all strategies undoubtedly reduces the spatial hindrance of the sensing interface and increases the effectiveness of electron transfer and immune recognition. With CYFRA21 1 as target, the biosensor exhibits linear ECL response in a wide range (10 fg mL 1 100 ng mL 1) and an ultralow detection limit of 1.33 fg mL 1 (S/N=3) With convincing experimental data, these innovative strategies will be more eye catching in peptide based nanocluster synthesis and expansion of more novel thought for sensing platform fabrication.
The Tipping Point In Social Networks: Investigating the Mechanism Behind Viral Information Spreading
Venue: 2020 IEEE Sixth International Conference on Big Data Computing Service and Applications (BigDataService)
Year: 2020

A social network represents ties between people. Modeling social interactions to understand the underlying mechanism of herd behavior has been a topic of interest for the past several decades. Our focus in this work is to investigate the phenomenon of extreme, unexpected growth and gain in a social network, and how different diffusion models can be used to identify the "key players" in such a process. In social network analysis, it is a tedious task to find the most influential entities, and how ideas or news spread through the network. A popular method to solve this task is to represent the social network as a graph. In a dynamic or an ever growing social graph, discovering when an idea starts spreading, and not when it started first, reflects the real nature of how viral ideas catch on in society. Also, instead of locating the root of an idea, it is crucial to see who propelled the idea to the surface, and triggered the spread. In this paper, we develop a method to identify the set of nodes who are responsible for extraordinary change in graph growth. We propose a methodology that allows us to identify the phenomenon called "tipping point" both in terms of the the role of a node or a community in graph growth, but also with respect to the time frame it occurred. Our framework is employing different influence propagation approaches, to locate critical nodes or communities and indicate their role in the early stages of the sudden graph growth. We demonstrate how the methodology is applied using a real life social network. We aspire that the proposed framework will help researchers better understand this phenomenon and be able to identify agents responsible for spreading trends, beliefs, opinions, etc. in society.