nils-herrmann/clean_scirepeval huggingface dataset:
Integration of Fluorescence and Reflectance Visible Near Infrared (VNIR) Hyperspectral Images for Detection of Aflatoxins in Corn Kernels

Aflatoxin contamination in agricultural products has been an important and long standing problem around the world. Produced by certain fungal species of the genus, aflatoxins are highly toxic and carcinogenic. This study investigated the integration of fluorescence and reflectance visible near infrared (VNIR) hyperspectral images to detect aflatoxins in whole corn kernels. Field inoculated corn ears were harvested, and kernels having different aflatoxin contamination levels were collected. Both fluorescence hyperspectral images under ultraviolet (UV) excitation and reflectance hyperspectral images under halogen illumination were recorded on the two sides of the kernels (endosperm and germ) Subsequent chemical analysis was performed on each kernel to provide reference aflatoxin concentration. Threshold values of 20 and 100 ppb were adopted separately to group kernels as contaminated or healthy. Contaminated kernels exhibited different fluorescence and reflectance spectral features compared with healthy kernels. Spectral datasets were compressed and interpreted using principal component analysis (PCA) Least squares support vector machines (LS SVM) and k nearest neighbor (KNN) classifiers were used on the fluorescence PC, reflectance PC, and integrated fluorescence and reflectance PC variables for classifying both sides of kernels as contaminated or healthy. The best overall prediction accuracy was 95.33% for the LS SVM model with the 100 ppb threshold on the germ side in the integrated analysis. Overall, the germ side performed better than the endosperm side, especially for the true positive rate (TPR) Fluorescence and reflectance image data generally achieved similar classification accuracy. The integrated analysis achieved better results than separate fluorescence or reflectance analysis on the germ side, and conspicuous improvement in the TPR of the germ side was observed after integration. The mean aflatoxin concentration in the prediction samples was reduced from 2662.01 ppb to 64.04, 87.33, and 7.59 ppb after removing samples that were classified as contaminated by fluorescence, reflectance, and integrated analysis, respectively, on the germ side. This study demonstrated the potential of the integrated technique for better screening of aflatoxin contaminated kernels and could lead to rapid and non destructive scanning based detection in the corn industry.
Solving the Set Covering Problem with a Binary Black Hole Inspired Algorithm
Venue: ICCSA

There are multiple problems in several industries that can be solved with combinatorial optimization. In this sense, the Set Covering Problem is one of the most representative of them, being used in various branches of engineering and science, allowing find a set of solutions that meet the needs identified in the restrictions that have the lowest possible cost. This paper presents an algorithm inspired by binary black holes (BBH) to resolve known instances of SPC from the OR Library. Also, it reproduces the behavior of black holes, using various operators to bring good solutions.
A Discrete Fruit Fly Optimization Algorithm for the Traveling Salesman Problem
Venue: PloS one

The fruit fly optimization algorithm (FOA) is a newly developed bio inspired algorithm. The continuous variant version of FOA has been proven to be a powerful evolutionary approach to determining the optima of a numerical function on a continuous definition domain. In this study, a discrete FOA (DFOA) is developed and applied to the traveling salesman problem (TSP) a common combinatorial problem. In the DFOA, the TSP tour is represented by an ordering of city indices, and the bio inspired meta heuristic search processes are executed with two elaborately designed main procedures: the smelling and tasting processes. In the smelling process, an effective crossover operator is used by the fruit fly group to search for the neighbors of the best known swarm location. During the tasting process, an edge intersection elimination (EXE) operator is designed to improve the neighbors of the non optimum food location in order to enhance the exploration performance of the DFOA. In addition, benchmark instances from the TSPLIB are classified in order to test the searching ability of the proposed algorithm. Furthermore, the effectiveness of the proposed DFOA is compared to that of other meta heuristic algorithms. The results indicate that the proposed DFOA can be effectively used to solve TSPs, especially large scale problems.
PubChem Substance and Compound databases
Venue: Nucleic Acids Res.

PubChem (https:/pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH) For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web based interfaces for textual and non textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF) formatted PubChem data for data sharing, analysis and integration with information contained in other databases.
Interface Engineering of MoS2 /Ni3 S2 Heterostructures for Highly Enhanced Electrochemical Overall Water Splitting Activity.
Venue: Angewandte Chemie

To achieve sustainable production of H2 fuel through water splitting, low cost electrocatalysts for the hydrogen evolution reaction (HER) and the oxygen evolution reaction (OER) are required to replace Pt and IrO2 catalysts. Herein, for the first time, we present the interface engineering of novel MoS2 /Ni3 S2 heterostructures, in which abundant interfaces are formed. For OER, such MoS2 /Ni3 S2 heterostructures show an extremely low overpotential of ca. 218 mV at 10 mA cm( 2) which is superior to that of the state of the art OER electrocatalysts. Using MoS2 /Ni3 S2 heterostructures as bifunctional electrocatalysts, an alkali electrolyzer delivers a current density of 10 mA cm( 2) at a very low cell voltage of ca. 1.56 V. In combination with DFT calculations, this study demonstrates that the constructed interfaces synergistically favor the chemisorption of hydrogen and oxygen containing intermediates, thus accelerating the overall electrochemical water splitting.
Geopolymer encapsulation of a chloride salt phase change material for high temperature thermal energy storage

In an effort to reduce the cost and increase the material compatibility of encapsulated phase change materials (EPCMs) a new encapsulated system has been proposed. In the current study a molten salt eutectic of barium chloride (53% wt. potassium chloride (28% wt. and sodium chloride (19% wt. has been identified as a promising candidate for low cost EPCM storage systems. The latent heat, melting point and thermal stability of the phase change material (PCM) was determined by DSC and was found to be in good agreement with results published in the literature. To cope with the corrosive nature of the PCM, it was decided that a fly ash based geopolymer met the thermal and economic constraints for encapsulation. The thermal stability of the geopolymer shell was also tested with several formulations proving to form a stable shell for the chosen PCM at 200degC and/or 600degC. Lastly several capsules of the geopolymer shell with a chloride PCM were fabricated using a variety of methods with several samples remaining stable after exposure to 600degC testing.
Three Dimensional Angiographic Evaluation of Middle Cerebral Artery Trunk Aneurysms: Demonstration of the Close Relationship Between the Early Frontal Cortical Branches and Lateral Lenticulostriate Arteries.
Venue: World neurosurgery

For the treatment planning of a patient with a middle cerebral artery (MCA) trunk aneurysm, understanding the anatomic relationship among the aneurysm, branching vessels, and lenticulostriate arteries (LSAs) is important. We aimed to demonstrate the branching vessel anatomy related to an MCA trunk aneurysm using 3 dimensional (3D) angiography.  We retrospectively reviewed 3D angiographic findings of 64 cases of MCA trunk aneurysms using a 3D workstation with various postprocessing conditions. We classified the aneurysms into 4 groups (early frontal cortical branch [EFCB] early temporal cortical branch [ETCB] LSA, and nonbranching aneurysms) and analyzed the relationship between the branching vessels and the LSAs.  There were 30 EFCB aneurysms, 25 ETCB aneurysms, 7 LSA aneurysms, and 2 nonbranching aneurysms. Twenty six (86.7% of the 30 EFCB aneurysms shared common origins and were associated with the LSAs, but none of the 25 ETCB aneurysms were. Three of 24 patients who received clipping for an EFCB aneurysm experienced a postoperative infarction in the LSA territory. In these 3 patients, the LSA originated from the EFCB and was closely related with the aneurysm.  We have identified a clinically important anatomic relationship between the MCA trunk aneurysm and branching vessels, including the LSAs. EFCB aneurysms show a close relationship with the LSAs. Pretreatment identification of the origin of the LSAs is important to obviate any perforator injury in EFCB aneurysms.
Representing Sparse Gaussian DAGs as Sparse R Vines Allowing for Non Gaussian Dependence

Modeling dependence in high dimensional systems has become an increasingly important topic. Most approaches rely on the assumption of a multivariate Gaussian distribution such as statistical models on directed acyclic graphs (DAGs) They are based on modeling conditional independencies and are scalable to high dimensions. In contrast, vine copula models accommodate more elaborate features like tail dependence and asymmetry, as well as independent modeling of the marginals. This flexibility comes however at the cost of exponentially increasing complexity for model selection and estimation. We show a novel connection between DAGs with limited number of parents and truncated vine copulas under sufficient conditions. This motivates a more general procedure exploiting the fast model selection and estimation of sparse DAGs while allowing for non Gaussian dependence using vine copulas. By numerical examples in hundreds of dimensions, we demonstrate that our approach outperforms the standard method for vine structure selection.
Boarding School Resistance Narratives: Haskell Runaway and Ghost Stories

An after hours lover shimmies down a window ledge, avoids the dorm matron's write up, but hears footsteps behind him. A spectral figure waves from a dark window. Lights flicker on and off when no one is near the light switches. A figure stands under a tree smoking, but disappears in an instant. These are a few of the stories that I have heard in twenty years of teaching at Haskell Indian Nations University. In this intertribal community, oral literature keeps the school's history in the minds of this generation. Haskell began as an intertribal boarding school in 1884, and since that first terrible year, when many children died, a complicated history has haunted the landscape. At the edge of campus, rows of gravestones are mute testimony to failed assimilation. Along with the physical monuments, other less tangible reminders of the children remain. Their spirits are as much a part of Haskell as the football stadium arch and the gazebo. These ghost stories have a subversive purpose. They allow the painful experiences of turn of the century Native peoples to remain alive in memory, despite their omission or elision in official history books. In English or tribal languages, Native people were able to use ghost stories for cultural preservation. Ghost stories appeared to be harmless folk tales, and so they were invisible to Bureau of Indian Affairs boarding school censorship. The physical reality of early boarding schools was harsh by any standards, and the students had few options besides the desperate choices of run away or give up life. The schools were modeled after military institutions, and the children were like military personnel who needed permission for any leave. Haskell Institute in Lawrence, Kansas, was located far away from most reservations in order to isolate children from their families and cultural continuity. The world champion decathlete Buster Charles' daughter Nola Lodge researched Haskell during the 1920's, the time her Oneida/Yakima father attended the school (Lodge 1999) She found letters from parents expressing concern that their children actually lost weight, because the food meant for children was sold in the surrounding community of Lawrence. The farming programs were, in practice, child labor. One of the most wrenching archival photographs from early Haskell years is a group of fourteen young children in drab uniforms and sheared hair. They sit
Development of a swarm control platform for educational and research applications

Swarm robotics is a new and quickly growing field of research that has many applications to the real world. The idea is to use a coordinated group of devices to perform tasks that are either unsafe or infeasible for a single device to accomplish. While a lot of research is being done on swarms, surprisingly, there are not many physical platforms available to apply these ideas to. Being able to take this research out of simulation will greatly improve the quality and feasibility of these ideas outside of nearperfect conditions. In this thesis we develop a new swarm control platform (that can function as either a Centralized or Distributed system) as well as potential research applications and educational exercises that can be created using this platform. The platform utilizes an open source NanoQuadcopter called the Crazyflie and uses the OptiTrack motion capture camera system for localization. It is designed for scalability using the Virtual Reality Peripheral Network (VRPN) a type of Multi Cast UDP protocol, to transmit localization data. We use this location data and set of nine nested PID controllers to command the Crazyflie to any location in space. It also supports flying multiple Crazyflies on one USB Radio, and multiple radios per computer, further reducing the scale up cost. As a proof of concept, we crafted a few applications for the Platform to demonstrate its abilities. These examples range from simple single Crazyflie autonomous flight, to more complex gesture controlled multi Crazyflie master slave 'follow the leader' type systems. We intend to extend these systems to test even more complex problems in optimization and stochastic lossy networks, as well as creating lab experiments and educational resources for students to learn more about controls.
ANALYSIS OF VARIOUS LOAD BALANCING TECHNIQUES IN CLOUD ENVIRONMENT

Cloud computing has paved a revolutionary path in direction of distributed environment for accomplishing optimized performance, shortest response time, network resource utilization, and adaptability of service level agreement. Cloud computing has multiple benefits as well as it is also accompanied with certain serious technical loopholes. The proposed paper has focused on one such issue of load balancing. Load balancing is one of the main challenges in cloud computing. It is required to distribute the dynamic local workload evenly across all the nodes to achieve a high user satisfaction and re source utilization ratio by making sure that every computing re source is distributed efficiently and fairly. Hence this paper illustrates various generic issues, and particularly to issues related to load balancing. Various techniques adopted in the past research work have been analyzed in this paper based on advantages and parameters used.
Analysis of Different Methods for Measuring the Performance of Database on Cloud Environment

Cloud computing become most adoptable technology over the past few years, it is widespread for both at organizational level or for the person who use the services that are offered in the cloud. There are several technocrats currently researched on cloud related issues and soon cloud represents the modern computing. The cloud gave the prospect for the enterprise and allowing them to center on their work by providing hardware and software solution without developing them own. Now a day the database has also moved to cloud computing so we will look into the fine points of database as a service and it's servicing. While storing data on cloud there is a need to balance the load on datacenters because if user base always sends request on single data center then it becomes overloaded so load balancing techniques are applied to manage this problem. To manage geographic distribution in terms of computing servers and data workloads a tool termed as CloudAnalyst is used which is based on cloudsim technique. CloudAnalyst helps developers with the vision of distributing applications among cloud infrastructures. Currently tool having three algorithms for load balancing round robin, throttled load balancer, equally spread current execution and the proposed algorithm is weighted round robin which works better as comparison to round robin in various aspects.
A Survey on High Efficiency Wireless Local Area Networks: Next Generation WiFi
Venue: IEEE Communications Surveys Tutorials

The emerging paradigm of the Internet of Everything, along with the increasing demand of Internet services everywhere, results in a remarkable and continuous growth of the global Internet traffic. As a cost effective Internet access solution, WiFi networks currently generate a major portion of the global Internet traffic. Furthermore, the number of WiFi public hotspots worldwide is expected to increase by more than sevenfold by 2018. To face this huge increase in the number of densely deployed WiFi networks, and the massive amount of data to be supported by these networks in indoor and outdoor environments, it is necessary to improve the current WiFi standard and define specifications for high efficiency wireless local area networks (HEWs) This paper presents potential techniques that can be applied for HEWs, in order to achieve the required performance in dense HEW deployment scenarios, as expected in the near future. The HEW solutions under consideration includes physical layer techniques, medium access control layer strategies, spatial frequency reuse schemes, and power saving mechanisms. To accurately assess a newly proposed HEW scheme, we discuss suitable evaluation methodologies, by defining simulation scenarios that represent future HEW usage models, performance metrics that reflect HEW user experience, traffic models for dominant HEW applications, and channel models for indoor and outdoor HEW deployments. Finally, we highlight open issues for future HEW research and development.
Shear Behavior of Sand Silt Mixtures: A Laboratory Investigation of Coastal Silty Sand Soils of Mostaganem

In recent years, interest in understanding the mechanisms of mechanical instability of porous media, leading to catastrophic failure has been continuously revised to include, new porous media parameters generating the phenomenon of liquefaction under static or dynamic loadings. Results from experimental test programs have concluded too many physical concepts based on material intrinsic properties, initial states, and other characteristics. Despite the great progress on the subject, these concepts do not allow a unified treatment of such porous media. The assessment of critical shear strength of sandy soils as porous media under undrained conditions is a major challenge in stability analysis. Such strength serves to evaluate the occurrence of flow deformation under liquefaction phenomena. The determination of the critical undrained strength is essentially fundamental for the design of soil structures such as earth dams, bridge supports, building foundations as well as soil densification process to avoid catastrophic failure due to soil instability manifested by failure or large displacement such as settlement. In this work, experimental program on reconstituted loose and medium dense specimens of terrigenous silica sands with different specified fine contents was carried out to analyze its mechanical behavior under undrained conditions. The present article is an attempt to experimentally describe mechanical behavior and theoretically justify such response of loose and medium dense sand by means of critical state soil parameters.
Nurses' perceptions, acceptance, and use of a novel in room pediatric ICU technology: testing an expanded technology acceptance model
Venue: BMC Medical Informatics and Decision Making

BackgroundThe value of health information technology (IT) ultimately depends on end users accepting and appropriately using it for patient care. This study examined pediatric intensive care unit nurses' perceptions, acceptance, and use of a novel health IT, the Large Customizable Interactive Monitor.MethodsAn expanded technology acceptance model was tested by applying stepwise linear regression to data from a standardized survey of 167 nurses.ResultsNurses reported low moderate ratings of the novel IT's ease of use and low to very low ratings of usefulness, social influence, and training. Perceived ease of use, usefulness for patient/family involvement, and usefulness for care delivery were associated with system satisfaction (R2 70% Perceived usefulness for care delivery and patient/family social influence were associated with intention to use the system (R2 65% Satisfaction and intention were associated with actual system use (R2 51%.ConclusionsThe findings have implications for research, design, implementation, and policies for nursing informatics, particularly novel nursing IT. Several changes are recommended to improve the design and implementation of the studied IT.
Robust Markowitz mean variance portfolio selection under ambiguous covariance matrix

This paper studies a robust continuous time Markowitz portfolio selection pro\ blem where the model uncertainty carries on the covariance matrix of multiple risky assets. This problem is formulated into a min max mean variance problem over a set of non dominated probability measures that is solved by a McKean Vlasov dynamic programming approach, which allows us to characterize the solution in terms of a Bellman Isaacs equation in the Wasserstein space of probability measures. We provide explicit solutions for the optimal robust portfolio strategies and illustrate our results in the case of uncertain volatilities and ambiguous correlation between two risky assets. We then derive the robust efficient frontier in closed form, and obtain a lower bound for the Sharpe ratio of any robust efficient portfolio strategy. Finally, we compare the performance of Sharpe ratios for a robust investor and for an investor with a misspecified model.