nils-herrmann/clean_scirepeval huggingface dataset:
Farming system models for supporting farm resilience: Research needs, gaps and promising approaches

It is important to increase the resilience of food production systems in the face of a changing climate, land scarcity, and changing demographics and market conditions. As farm resilience is a high level system property emerged from social ecological interactions, its direct measurement is difficult because it requires measuring the thresholds or boundaries that separate alternate stability regimes of the farm system. However, agricultural systems modeling for supporting agricultural resilience is still a very young science. Through critical review of state of the art literature, this study aims at highlighting the new requirements of agricultural system modeling as they apply to management for farm resilience, limitations of contemporary agricultural systems modeling approaches, and promising directions for future research on the field. Although a great deal of knowledge and tools about biophysical or social processes exist, agricultural system model research hardly ever seeks to develop modelling frameworks and tools to support farm resilience management. We conceptualized nine criteria for evaluating models' suitability for farm resilience studies, which include: (1) representing social ecological complementariness) (2) having multiple performance dimensions, (3) explaining human behavioural change, (4) representing flexible multi scale feedbacks, (5) incorporating intra farm heterogeneity, (6) explaining farm's structural changes, (7) being sensitive to key drivers, (8) managing uncertainty, and (9) mediating effective participation. Using these criteria we evaluated a mass primary literature on farming systems models and found that none of developed farming system models are sufficient for supporting farm resilience regarding all criteria. The result of our meta analysis can serve as a reference matrix that helps identifying research directions towards supporting the resilience of agricultural systems. There is an emerging recognition in the scientific community of the capability and utility that multi agent simulations (MAS) offer a platform for understanding the complexity of energy, nutrient and material flows that result from rich interactions and feedback among social and natural processes. Although some great progress has been made in applying MAS to study land use change over the last decade, MAS models for investigating farm resilience and transition scenarios are still in a very early stage of development. Using the above mentioned criteria we also analyzed the current limitations of this model family and elaborate possible future developments as subjects of follow up studies. To better materialize our recommendations, we analyze our MAS modeling framework, entitled MANUS (Multi Agent system model for exploring sustainable smallholders' NUtrient management Strategies) as a demonstration case.
Mixed Integer Programming models for job shop scheduling: A computational analysis
Venue: Comput. Oper. Res.

In both industry and the research literature, Mixed Integer Programming (MIP) is often the default approach for solving scheduling problems. In this paper we present and evaluate four MIP formulations for the classical job shop scheduling problem (JSP) While MIP formulations for the JSP have existed since the 1960s, it appears that comprehensive computational studies have not been performed since then. Due to substantial improvements in MIP technology in recent years, it is of interest to compare the standard JSP models using modern optimization software. We perform a fully crossed empirical study of four MIP models using CPLEX, GUROBI and SCIP, focusing on both the number of instances that can be proved optimal and the solution quality over time. Our results demonstrate that modern MIP solvers are able to prove optimality for moderate sized problems very quickly. Comparing the four MIP models, the disjunctive formulation proposed by Manne performs best on both performance measures. We also investigate the performance of MIP with multi threading and parameter tuning using CPLEX. Noticeable performance gain is observed when compared to the results using only single thread and default parameter settings. Our results serve as a snapshot of the performance of modern MIP solvers for an important, well studied scheduling problem. Finally, the results of MIP is compared to constraint programming (CP) another common approach for scheduling, and the best known complete algorithm to provide a broad view among different approaches. HighlightsWe perform a complete empirical study of four MIP models for JSP.Our results demonstrate that the disjunctive MIP model is most efficient.Our results demonstrate that MIP is efficient for solving moderate size problems.We compare MIP to constraint programming and the best known algorithm.Our results serve as a snapshot of the performance of modern MIP solvers.
Exact Solutions of Inexact Linear Programs

3. R. W. CONWAY, "An Experimental Investigation of Priority Assignment in a Job Shop," RM 3789 PR, Rand Corporation, Santa Monica, Cal. (1964) 4. R. W. CONWAY, W. L. MAXWELL, AND L. W. MILLER, Theory of Scheduling, Addison Wesley, Reading, Mass. 1967. 5. J. E. DAY AND M. P. HOTTENSTEIN, "Review of Sequencing Research,"  (1970) 6. W. S. GERE, "Heuristics in Job Scheduling,"  (1966) 7. J. R. JACKSON, "An Extension of Johnson's Results on Job Lot Scheduling,"  201 203 (1956) 8. S. M. JOHNSON, "Optimal Twoand Three Stage Production Schedules with Set up Times Included,"  Log Quart, 1, 61 68 (1954) 9. A. S. MANNE "On the Job Shop Scheduling Problem,"  (1960)
Estimates of Genetic Variability, Heritability and Genetic Advance for Blast Resistance Gene Introgressed Segregating Population in Rice

Rice is one of the most important stable cereal food crop in India. The total rice production was estimated at 103.61 million tones during 2015 16 (Government of India, Ministry of Agriculture) which is low as 1.87 million tones as compared to the year 2014 15 production (105.48 million tones) Rice blast is caused by fungal pathogen (Pyricularia grisea) which cause severe yield loss upto 50% world wide rice cultivable areas. (Scardaci et al. 1997; Shalini et al. 2016) Genetic variability is an important, where parental selection for hybridization (Chaudhary and Singh, 1982) and crop improvement primarily depends on genetic variability in base population (Adebisi et al. 2001) Segregating populations are essence for improvement of plant traits by adopting various breeding technologies for further improvement. Among all, F2 segregating generation has become more crucial and selection could be done meticulously. Prerequisite for any International Journal of Current Microbiology and Applied  (2016) pp. 672 677  http:/www.ijcmas.com
Hypoxia regulates Notch 3 mRNA and receptor activation in prostate cancer cells
Venue: Heliyon

The Notch 3 receptor is a recognized key regulator of vascular responses and is increasingly associated with tumorigenesis. Hypoxia inducible factors activate specific signaling pathways such as Notch in a number of cellular models. This study aimed to evaluate the regulation of Notch 3 by hypoxia in prostate cancer cells. Notch 3 gene and protein expression was established in a panel of aerobic and hypoxic prostate cell lines in vitro, the CWR22 xenograft model and RNA extracted from low grade (Gleason score 6) high grade (Gleason score 7) non hypoxic (low HIF, low VEGF) hypoxic (high HIF, high VEGF) patient FFPE specimens. NOTCH 3 was upregulated in PC3 (3 fold) 22Rv1 (4.1 fold) and DU145 (3.8 fold) but downregulated in LnCaP (12 fold) compared to the normal cell lines. NOTCH 3 expression was modified following hypoxic exposure in these cells. NOTCH 3 was upregulated (2.2 fold) in higher grade and hypoxic tumors, when compared to benign and aerobic pools. In the CWR22 xenograft model, Notch 3 expression was restored in castrate resistant tumors. Nuclear translocation of the Notch 3 intracellular domain was no longer detected following exposure of cells to hypoxia but not associated with a change in expression of HES 1. Our data further identifies Notch 3 as a potentially key hypoxic responsive member of the Notch pathway in prostate tumorigenesis.
Enhanced overexpression of hypoxia related miRNA 210 in primary tumor of metastatic prostate cancer.

miR 210 is a known transcriptional target of the hypoxia responsive HIF 1a signaling pathway. However, the association between the expression of miR 210 and the tumor progression in prostate cancer (PCa) remains unclear.  We isolated miRNA by miRNeasy FFPE kit (Qiagen, Hilden, Germany) from paraffin embedded tissues of 87 prostate specimens with adenocarcinoma of the prostate cancer in different tumor stages, with high grade prostatic intraepithelial neoplasia (HGPIN) and normal tissues. Organ confined PCa was defined as PCa with pT2 tumor stage, Gleason score 7a and PSA level 7a was defined as advanced PCa. PCa with pN1 were considered as metastatic diseases. Additionally, 3 cases with castration resistant prostate cancer (CRPC) were considered. Quantitative miR 210 expression data were acquired and analyzed using a real time TaqMan based PCR with the ABI Prism 7900HT (Life Technologies, Darmstadt, Germany) ANOVA and post hoc analysis acc.
Image Restoration Using Convolutional Auto encoders with Symmetric Skip Connections
Venue: ArXiv

Image restoration, including image denoising, super resolution, inpainting, and so on, is a well studied problem in computer vision and image processing, as well as a test bed for low level image modeling algorithms. In this work, we propose a very deep fully convolutional auto encoder network for image restoration, which is a encoding decoding framework with symmetric convolutional deconvolutional layers. In other words, the network is composed of multiple layers of convolution and de convolution operators, learning end to end mappings from corrupted images to the original ones. The convolutional layers capture the abstraction of image contents while eliminating corruptions. Deconvolutional layers have the capability to upsample the feature maps and recover the image details. To deal with the problem that deeper networks tend to be more difficult to train, we propose to symmetrically link convolutional and deconvolutional layers with skip layer connections, with which the training converges much faster and attains better results.
Baseline CNN structure analysis for facial expression recognition
Venue: 2016 25th IEEE International Symposium on Robot and Human Interactive Communication (RO MAN)

We present a baseline convolutional neural network (CNN) structure and image preprocessing methodology to improve facial expression recognition algorithm using CNN. To analyze the most efficient network structure, we investigated four network structures that are known to show good performance in facial expression recognition. Moreover, we also investigated the effect of input image preprocessing methods. Five types of data input (raw, histogram equalization, isotropic smoothing, diffusion based normalization, difference of Gaussian) were tested, and the accuracy was compared. We trained 20 different CNN models (4 networks x 5 data input types) and verified the performance of each network with test images from five different databases. The experiment result showed that a three layer structure consisting of a simple convolutional and a max pooling layer with histogram equalization image input was the most efficient. We describe the detailed training procedure and analyze the result of the test accuracy based on considerable observation.
CFD study on prediction of vortex shedding in draft tube of Francis turbine and vortex control techniques

Francis Turbine when operated at part load suffers flow instability due to swirl component of the velocity attached with exiting flow downstream the runner. The swirling flow at runner outlet generates corkscrew shaped draft tube vortex invites undesirable flow features like pressure pulsation, fluctuation in torque, axial and radial forces and structure vibration causing the turbine. This paper presents the results obtained from the numerical analysis regarding prediction of unsteady vortex behavior at the draft tube and flow instabilities specific to Francis hydro turbines occurring at the part load operating regime, using ANSYS CFX. The RNG k e turbulence model is adopted for turbulence treatment and better prediction of the non cavitating vortex core and its effects. A single part load operating condition is chosen to analyze the vortex breakdown. To minimize vortex shedding and flow instability, two vortex control techniques viz. Misaligned Guide Vanes (MGVs) and J grooves in draft tube are evaluated numerically. Two different MGV angles were selected and four different depths of J grooves were analyzed separately to see their effect on flow features. The use of MGV did not help much in minimizing swirl intensity whereas the use of J groove showed better swirl control and flow enhancement in the draft tube.
Infrastructure, Representation, and Historiography in BBN's Arpanet Maps
Venue: IEEE Annals of the History of Computing

The earliest and most widespread representation of the Arpanet were network graphs or maps that, arguably, remain its most prominent artifact. In an earlier article, the authors analyzed how the maps were created, what they represented, and how histories of the network parallel their emphases and omissions. Here, the authors begin a retooling of the maps to highlight further what is missing from them: communication flows, gateways to other networks, and hierarchies between its nodes.
Fordyce spots masquerading as penile warts.
Venue: Medical journal, Armed Forces India

Fordyce spots are heterotopic sebaceous glands that can occur on the vermillion border of the lips, within the oral mucosa, on the penile shaft usually the ventral surface, scrotum, areolar region of the breast, and labia minora. It was first described by John Addison Fordyce, an American dermatologist in 1896 and the condition is named after him. Fordyce spots in the oral mucosa are very common. Especially when these occur on the male genitalia, usually after puberty, it is a matter of great concern for the patient and can at times confuse the untrained eye and appear like genital warts. Treatment is not necessary since it is an anatomical variation and a benign condition. However, for cosmetic
Inference Machines for Nonparametric Filter Learning
Venue: IJCAI

Data driven approaches for learning dynamic models for Bayesian filtering often try to maximize the data likelihood given parametric forms for the transition and observation models. However, this objective is usually nonconvex in the parametrization and can only be locally optimized. Furthermore, learning algorithms typically do not provide performance guarantees on the desired Bayesian filtering task. In this work, we propose using inference machines to directly optimize the filtering performance. Our procedure is capable of learning partially observable systems when the state space is either unknown or known in advance. To accomplish this, we adapt PREDICTIVE STATE INFERENCE MACHINES (PSIMS) by introducing the concept of hints, which incorporate prior knowledge of the state space to accompany the predictive state representation. This allows PSIM to be applied to the larger class of filtering problems which require prediction of a specific parameter or partial component of state. Our PSIM+HINTS adaptation enjoys theoretical advantages similar to the original PSIM algorithm, and we showcase its performance on a variety of robotics filtering problems.
Learning to Filter with Predictive State Inference Machines
Venue: ICML

Latent state space models are a fundamental and widely used tool for modeling dynamical systems. However, they are difficult to learn from data and learned models often lack performance guarantees on inference tasks such as filtering and prediction. In this work, we present the PREDICTIVE STATE INFERENCE MACHINE (PSIM) a data driven method that considers the inference procedure on a dynamical system as a composition of predictors. The key idea is that rather than first learning a latent state space model, and then using the learned model for inference, PSIM directly learns predictors for inference in predictive state space. We provide theoretical guarantees for inference, in both realizable and agnostic settings, and showcase practical performance on a variety of simulated and real world robotics benchmarks.
Open box muscle computer interface: introduction to human computer interactions in bioengineering, physiology, and neuroscience courses.
Venue: Advances in physiology education

a muscle computer interface (muCI) is a human machine system that uses electromyographic (EMG) signals to communicate with a computer. Surface EMG (sEMG) signals are currently used to command robotic devices, such as robotic arms and hands, and mobile robots, such as wheelchairs [4][1]
Thickness invariant permittivity determination of materials from calibration independent measurements
Venue: 2016 IEEE Middle East Conference on Antennas and Propagation (MECAP)

This paper presents a new method for extracting relative complex permittivity (er) of dielectric materials by eliminating calibration standards. To validate proposed method it is compared with well known three techniques in literature. All measurements are done by using waveguide measurement techniques which is broadband over X band (8.2GHz 12.4GHz) frequency range with VNA. While these three methods necessitate calibration standards, proposed method is calibration independent (free) Experimental results of proposed method are in good agreement when compared with other methods in literature. Moreover, this new proposed technique can be implemented for extraction of material characterization of new studies in the future.
Monostatic and thickness independent material characterisation based on microwave ellipsometry
Venue: 2016 German Microwave Conference (GeMiC)

Material characterization utilizing microwave ellipsometry is based on the fact that the reflection coefficients of a wave impinging on a material depend on the incident fields polarization. Due to multiple reflections that occur in case of a material slab with finite dimensions these coefficients also strongly depend on the materials thickness. This paper describes an approach to determine the electromagnetic properties of a material under test by applying an ellipsometric measurement without knowledge of the materials thickness. The paper shows that the additional measurement of the transmission coefficients allows to perform an exact measurement of the complex permittivity since the thickness dependencies in reflection and transmission coefficients are removed. The measurements are done in the frequency range from 22 GHz to 26 GHz by using a vector network analyzer setup with a conical horn antenna.
Efficient one pot, three component synthesis of new I+ aminophosphonates and investigation of their antimicrobial activity

A convenient one pot synthesis of new a aminophosphonates (4a h) containing ethyl acetate moiety was accomplished via Kabachnik Fields reactions in good yield. All synthesized compounds were characterized by IR, 1H NMR, 13C NMR, 31P NMR and Mass spectroscopy and investigated their antimicrobial activity
Telecollaboration in the secondary language classroom: case study of adolescent interaction and pedagogical integration

This study builds on research examining the in school technology practices of adolescent language learners by exploring the patterns of classroom literacy practices that emerge when a telecollaborative project is introduced into a conventional secondary language classroom. We draw on the conceptual frameworks and discourse analytical tools developed by researchers of online communication practices at the post secondary level and turn this lens to examine how an international online exchange project might contribute to the creation of an in school learning environment in which adolescents use technology to interact with distally located peers through telecollaboration. The particular contribution of this study is twofold: to offer insight into patterns that characterize the literacy practices that emerge through the introduction of telecollaboration into the learning environment and to document the types of pedagogical decision making that such projects introduce into the secondary context. Using a case study design, we explored two central areas: (1) What patterns of interaction emerge in the literacy practices of adolescent students as they build relationships with their intercultural partners? (2) How do teachers address the pedagogical issues that are foregrounded when introducing innovative literacy practices such as telecollaboration into the secondary learning environment? Our premise is that online exchanges might offer a different kind of learning experience that provides opportunities for adolescents to engage with language in ways that do not typically get enacted in conventional language classrooms. Our interest therefore is grounded both in providing a rich, descriptive inventory of how adolescents engage with telecollaboration in the classroom context, as well as in documenting the types of pedagogical issues that are introduced. We offer a linguistically grounded portrait of what constitutes the interactional patterns and pedagogical issues in a classroom learning environment shaped by the introduction of an online intercultural project. Using a case study approach, therefore, we provide close documentation and analyses of a 15 week, classroom based telecollaboration project through student transcripts and focal teacher interviews. We conclude with a discussion of the empirical and pedagogical implications associated with integrating telecollaboration into secondary language classroom contexts.
Sustainability of fiber reinforced polymers (FRPs) as a construction material

Fiber reinforced polymer (FRP) composites have emerged as a relatively new construction material that is used both in new construction and in repair applications and that address many of the drawbacks of traditional construction materials. Primarily, FRP materials are resistant to electro chemical corrosion, have high strength to weight and stiffness to weight ratios, and provide installation flexibility making them relatively easy to install in repair applications where access is limited. As such, they have emerged as a sustainable and durable material for the repair of deteriorated concrete structures, including for flexural strengthening and repair, shear strengthening and repair, and confinement of columns. Based on the success of using FRP materials for the repair of concrete structures, they have also been investigated as an alternative repair material for steel structures and have demonstrated promise in this market. In new construction, composites have been used as corrosion resistant reinforcements for concrete structures and have been adopted in all FRP structural components, such as bridge decks. In all of these applications, composites represent a promising alternative to traditional construction materials and techniques for a sustainable and durable infrastructure.