nils-herrmann/clean_scirepeval huggingface dataset:
Ventral fronto parietal contributions to the disruption of visual working memory storage
Venue: NeuroImage

The ability to maintain information in visual working memory (VWM) in the presence of ongoing visual input allows for flexible goal directed behavior. Previous evidence suggests that categorical overlap between visual distractors and the contents of VWM is associated with both the degree to which distractors disrupt VWM performance and activation among fronto parietal regions of cortex. While within category distractors have been shown to elicit a greater response in ventral fronto parietal regions, to date, no study has linked distractor evoked response of these regions to VWM performance costs. Here we examined the contributions of ventral fronto parietal cortex to the disruption of VWM storage by manipulating memoranda distractor similarity. Our results revealed that the degree of activation across cortex was graded in a manner suggesting that similarity between the contents of VWM and visual distractors influenced distractor processing. While abrupt visual onsets failed to engage ventral fronto parietal regions during VWM maintenance, objects sharing categorical (Related objects) and feature overlap (Matched objects) with VWM elicited a significant response in the right TPJ and right AI. Of central relevance, the magnitude of activation in the right AI elicited by both types of distractor objects subsequently predicted costs to binding change detection accuracy. In addition, Related and Matched distractors differentially affected ventral dorsal connectivity between the right AI and dorsal parietal regions, uniquely contributing to disruption of VWM storage. Together, our current results implicate activation of ventral fronto parietal cortex in disruption of VWM storage, and disconnection between ventral frontal and dorsal parietal cortices as a mechanism to protect the contents of VWM.
The critical role of phase difference in gamma oscillation within the temporoparietal network for binding visual working memory
Venue: Scientific reports

How does the brain enable us to remember two or more object representations in visual working memory (VWM) without confusing them? This "gluing" process, or feature binding, refers to the ability to join certain features together while keeping them segregated from others. Recent neuroimaging research has reported higher BOLD response in the left temporal and parietal cortex during a binding VWM task. However, less is known about how the two regions work in synchrony to support such process. In this study, we applied transcranial alternating current stimulation (tACS) over the left temporal and parietal cortex in gamma and theta frequency, with a phase difference of either 0deg (in phase) or 180deg (anti phase) to account for the different ways through which neural synchronization may occur. We found no facilitatory or inhibitory effect from sham, theta, and in phase gamma stimulation. Importantly, there was an enhancement effect from anti phase gamma tACS that was binding specific, and such effect was only apparent in low performing individuals who had room for improvement. Together, these results demonstrate that binding VWM is supported by a temporally precise oscillatory mechanism within the gamma frequency range, and that the advantageous 180deg apart phase relationship also implies a possible temporal driver to receiver time lag between the temporal and parietal cortex.
An oil production forecast for China considering economic limits

In recent years, it has become apparent that oil prices may not rise endlessly. Unconventional oil is likely to be especially affected by low prices because it tends to be high priced to extract. To estimate the impact prices might have on future Chinese oil production, we develop a model in which only future unconventional oil production is affected by price. We analyze three price scenarios: Stays Low, Best Estimate, and Ever Rising Prices. In these scenarios, remaining Ultimate Recoverable Resources (URR) are estimated to be 10% 50% and 90% of remaining Technically Recoverable Resources, respectively. Since oil price can be expected to affect the shape of the extraction curve, we spread estimated URR to year using models that do not assume that future production will ultimately produce a symmetric Hubbert type curve (Multi Cycle Generalized Weng Model and Stochastic Resource Constrained Growth Model) In the Best Estimate Scenario, China's oil production is expected to reach a maximum of 226.79 million tons in 2020. In the Ever Rising Prices Scenario, China's maximum oil production occurs in 2023. In the Stays Low Scenario, maximum production has already been reached.
Modeling and Statistical Inference on Generalized Inverse Weibull Software Reliability Growth Model

In this paper we introduce the generalized inverse Weibull finite failure software reliability model which includes both increasing and decreasing nature of the hazard function. The increasing/decreasing behaviour of the failure occurrence rate fault is taken into account by the hazard of generalized inverse Weibull distribution. The model parameters are estimated using maximum likelihood method for interval domain data and numerical examples are provided to illustrate the estimation technique. The proposed model is compared with the standard existing models through error sum of squares, mean sum of squares, predictive ratio risk and Akaikes information criteria using different data sets. The result showed that the proposed model performs satisfactorily better than the existing finite failure category models.
Regime elites and transitions from authoritarian rule: a comparative analysis of the Tunisian and Egyptian uprisings

This thesis proposes an explanation for why elites in authoritarian regimes withdraw their support for incumbents when faced with mass popular uprisings. Building upon the substantial scholarship on MENA (Middle East and North Africa) elites, I argue that the elite cadres supporting the region's incumbents are drawn from three distinct elite constituencies: the military, the ruling party, and, the incumbent's extended personal network and the security services, each of which possess their own distinct interests and preferences regarding regime change. The argument is tested against two endogenous and exogenous variables, synthesised from the authoritarian resilience literature. Through the use of an analytic narrative this thesis finds that the withdrawal of elite support during the mass uprisings was the result of long term processes in both regimes. First, the increasing personalisation of both regimes contributed to withdrawal of elite support from both countries' ruling parties and militaries. And second, the implementation of structural adjustment programmes accelerated this personalisation and inhibited the abilities of both countries' ruling parties to mobilise support for the regime during the uprisings. The thesis further finds that the degree of military involvement in the formal political sphere contributed to shaping the divergent outcomes experienced by both Tunisia and Egypt in the immediate aftermath of the ouster of Ben Ali and Mubarak.
Estimation of Poverty Rate and Quintile Share Ratio for Domains and Small Areas

In the article, we consider the estimation of indicators on poverty and social exclusion for population subgroups or domains and small areas. For at risk of poverty rate, we discuss indirect design based estimators including model assisted logistic generalized regression estimators and model calibration estimators. Logistic mixed models are used in these methods. For quintile share ratio, indirect model based percentile adjusted predictor methods using linear mixed models are considered. Unit level auxiliary data are incorporated in the estimation procedures. For quintile share ratio, we present a method called frequency calibration or n calibration to be used in cases where aggregate level auxiliary data only are available. Design based direct estimators that do not use auxiliary data and models are used as reference methods. Design bias and accuracy of estimators are evaluated with design based simulation experiments using real register data maintained by Statistics Finland and semi synthetic data generated from the EU SILC survey.
The Engineering Design Process

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Multidisciplinary Design Process of a 6 Slot 2 Pole High Speed Permanent Magnet Synchronous Machine
Venue: IEEE Transactions on Industrial Electronics

High speed permanent magnet synchronous machines (HS PMSMs) are a popular topology among modern electrical machines. Suitable applications for such machines are low power vacuum pumps, compressors, and chillers. This paper describes a systematic design methodology for an HS PMSM using two case studies. The design process for such high speed (HS) machines is multidisciplinary and highly iterative due to the complex interaction of the many design variables involved. Consequently, no single optimum solution exists, and multiple possible solutions can meet the customer requirements. Practical solutions should be within acceptable thermal limits, should be energy efficient, and should be rigid enough to withstand the forces exerted during operation. The proposed design flow is divided into steps that are presented in this paper in the form of a flowchart with emphasis on mechanical aspects. Each step represents a task for a thermal, mechanical, or electrical engineer. The features of each step and the prerequisites for moving to the next step are discussed. The described methodology was implemented in the design of two HS PMSMs. The output performance results of the design flow are compared with measured results of the prototypes. The design process described in this paper provides a straightforward procedure for the multidisciplinary design of HS permanent magnet electrical machines.
The value network optimization research based on the Analytic Hierarchy Process method and the dynamic programming of cloud manufacturing

Cloud manufacturing has experienced a rapid development in the past several years. The research on its theories, technologies, and applications still keeps attracting attentions from more and more researchers. One of the most important issues to its improvements and quality of manufacturing service is the optimization of value network. This paper researched the optimization method of cloud manufacturing value network based on the Analytic Hierarchy Process (AHP) method and the dynamic programming of business decisions computing model. According to the function of decision making model, this paper used the AHP and dynamic programming method to establish the mathematical model of cloud manufacturing service value network for seeking the best value chain, and on this basis, established a different model to get the optimal result under the different conditions by time, cost, and resources.
Ovid, Amores (Book 1)

Although influenced by poets such as Catullus, Ovid demonstrates a much greater awareness of the funny side of love than any of his predecessors. The Amores is a collection of romantic poems centered on the poet's own complicated love life. This edition of the first book of the collection contains the complete Latin text of Book 1, along with commentary, notes, full vocabulary and embedded audio files of the original text read aloud by Aleksandra Szypowska.
Data Centric Computing Frontiers: A Survey On Processing In Memory
Venue: MEMSYS

A major shift from compute centric to data centric computing systems can be perceived, as novel big data workloads like cognitive computing and machine learning strongly enforce embarrassingly parallel and highly efficient processor architectures. With Moore's law having surrendered, innovative architectural concepts as well as technologies are urgently required, to enable a path for tackling exascale and beyond even though current computing systems face the inevitable instruction level parallelism, power, memory, and bandwidth walls. As part of any computing system, the general perception of memories depicts unreliability, power hungriness and slowness, resulting in a future prospective bottleneck. The latter being an outcome of a pin limitation derived by packaging constraints, an unexploited tremendous row bandwidth is determinable, which off chip diminishes to a bare minimum. Building upon a shift towards data centric computing systems, the near memory processing concept seems to be most promising, since power efficiency and computing performance increase by co locating tasks on bandwidth rich in memory processing units, whereas data motion mitigates by the avoidance of entire memory hierarchies. By considering the umbrella of near data processing as the urgent required breakthrough for future computing systems, this survey presents its derivations with a special emphasis on Processing In Memory (PIM) highlighting historical achievements in technology as well as architecture while depicting its advantages and obstacles.
Incorporation of activity sensitivity measures into buffer management to manage project schedule risk
Venue: Eur. J. Oper. Res.

Critical Chain Scheduling and Buffer Management (CC/BM) has shown to provide an effective approach for building robust project schedules and to offer a valuable control tool for coping with schedule variability. Yet, the current buffer monitoring mechanism faces a problem of neglecting the dynamic feature of the project execution and related activity information when taking corrective actions. The schedule risk analysis (SRA) method in a traditional PERT framework, on the other hand, provides important information about the relative activity criticality in relation to the project duration which can highlight management focus. It is implied, however, that control actions are independent from the current project schedule performance. This paper attempts to research these defects of both tracking methods and proposes a new project schedule monitoring framework by introducing the activity cruciality index as a trigger for effective expediting to be integrated into the buffer monitoring process. Furthermore, dynamic action threshold settings that depend on the project progress as well as the buffer penetration are presented and examined in order to exhibit a more accurate control system. Our computational experiment demonstrates the relative dominance of the integrated schedule monitoring methods compared to the predominant buffer management approach in generating better control actions with less effort and an increased tracking efficiency, especially when the increasing buffer trigger point is combined with decreasing sensitivity action threshold values.
Influence of cowpea and soybean intercropping pattern and time of planting on yield and gross monetary value of sorghum

The form of agriculture and cropping system found throughout the world are the results of variation in local climate, soil type, and a range of socio economic and biological factor that are the main determinants of the physical ability of crops to grow and cropping system to exist. Field experiment was conducted at Mechara Agricultural Research Center during 2013; to determine the effect of cowpea and soybean intercropping pattern on Land Equivalent Ratio (LER) and Gross Monetary Value (GMV) on system productivity. The treatments included two legume crops (soybean and cowpea) their planting time (simultaneously and at first weeding of sorghum),three planting patterns of legumes (double alternate plants within sorghum plants, two rows in between two rows of sorghum and both double alternate plants and two rows in between two rows of sorghum) along with sole crops (sorghum, soybean and cowpea) The experiment was conducted in randomized complete block design with three replications. Intercropping of cowpea in sorghum depressed sorghum yield. There was a variable response yield of soybean and cowpea due to legume planting time, planting pattern and their interaction. However, grain yields of both the legumes were significantly p <0.05) influenced by time of planting and planting pattern. Simultaneously planting proved significantly better than planting at first weeding of sorghum, while combination of double alternate plants within sorghum plants with two rows in between sorghum rows proved significantly better in enhancing the yield in case of both the legumes. Partial and total LER (1.55) was significantly higher in sorghum/soybean intercropping. Highest gross monetary benefit (20561Ethiopian birr) was accrued from planting two rows of cowpea with the first weeding of sorghum in between the two rows of sorghum however, it was at par with simultaneous planting of cowpea in double alternate plants within sorghum plants along with two rows of cowpea in between sorghum rows and two rows of soybean planted in between two rows of sorghum with first weeding in sorghum. K ey w o r d s: Cowpea, Gross Monetary Value, Intercropping, Land Equivalent Ratio Planting pattern, Sorghum, System productivity
Ability, Motivation and Opportunity as Determinants of Green Human Resources Management Innovation

The buzzing world of sustainability has led to soaring growth of literature on green marketing, green accounting, green retailing, green supply chain management and green general management. Green Human Resource Management (GHRM) studies on how this field contributes to preserving the environment is hardly found. The polarization between "Best fit" and best practice in HRM make difficult to measure human resource management output. Drawing on the classical Ability Motivation Opportunity (AMO) framework emphasizing the necessity of employees to possess abilities, motivation and be given opportunity to perform, Structural Equation Modelling (SEM) is used to spot the terrain for further study on green human resources management as an innovation in Malaysian setting. As most innovations are related to product development, this study highlights GHRM practices as a process innovation in responding to the current trend shifting from pro economic to pro social then pro environment. This way, under the AMO concept, this study scrutinizes the necessity to initiate GHRM practices in manufacturing companies of Malaysia as a process innovation by integrating people, process, technology and the organization. Finally, the model is expected to support the recent National Green Policy.
Anomaly Detection of User Behavior for Database Security Audit Based on OCSVM
Venue: 2016 3rd International Conference on Information Science and Control Engineering (ICISCE)

In view of the defects of safety monitoring and comprehensive audit in information network boundaries of State Grid Corporation of China(SGCC) a kind of security audit technology based on one class support vector machine(OCSVM) is proposed for the security audit of user access behavior. Firstly, feature selection, syntax parsing of SQL statements and numerical processing of audit log are completed to obtain the feature vector of user behavior, which can be trained and identified by OCSVM. Then the audit logs that reflect the rules of normal behavior in the long term operation of the database are used as the OCSVM's training input, after the training to obtain the OCSVM classifier, so as to construct the detection pattern library of user behavior. Finally, we use the OCSVM classifier to detect the abnormal behavior of database operations, and realize the security audit of database user access behavior.
Autoclave mediated one pot one minute synthesis of AgNPs and Au Ag nanocomposite from Melia azedarach bark extract with antimicrobial activity against food pathogens
Venue: Chemistry Central Journal

BackgroundThe increasing use of nanoparticles and nanocomposite in pharmaceutical and processed food industry have increased the demand for nontoxic and inert metallic nanostructures. Chemical and physical method of synthesis of nanostructures is most popular in industrial production, despite the fact that these methods are labor intensive and/or generate toxic effluents. There has been an increasing demand for rapid, ecofriendly and relatively cheaper synthesis of nanostructures.MethodsHere, we propose a strategy, for one minute green synthesis of AgNPs and a one pot one minute green synthesis of Au Ag nanocomposite, using Melia azedarach bark aqueous extract as reducing agent. The hydrothermal mechanism of the autoclave technology has been successfully used in this study to accelerate the nucleation and growth of nano crystals.ResultsThe study also presents high antimicrobial potential of the synthesized nano solutions against common food and water born pathogens. The multistep characterization and analysis of the synthesized nanomaterial samples, using UV visible spectroscopy, ICP MS, FT IR, EDX, XRD, HR TEM and FE SEM, also reveal the reaction dynamics of AgNO3, AuCl3 and plant extract in synthesis of the nanoparticles and nanocomposite.ConclusionsThe antimicrobial effectiveness of the synthesized Au Ag nanocomposite, with high gold to silver ratio, reduces the dependency on the AgNPs, which is considered to be environmentally more toxic than the gold counterpart. We hope that this new strategy will change the present course of green synthesis. The rapidity of synthesis will also help in industrial scale green production of nanostructures using Melia azedarach.
Real time Raman based approach for identification of biofouling

This study describes a proof of concept for a compact real time surface enhanced Raman spectroscopy (SERS) online sensing approach for detection of biofouling in drinking water membrane filtration. In this study we created a custom designed flow cell that mimics a cross flow membrane filtration system. This enables one to measure changes in surface foulants, such as Brevundimonas dimiuta (BD) bacteria and adenine, under conditions that are similar to conventional membrane filtration systems. For measurements we used a common portable Raman spectrometer with a laboratory Raman probe in combination with a specially developed gold nanoparticle (Au NP) SERS sensing area on filter membranes. This allowed real time detection of low concentrations of surface foulants immediately after inoculation into an ultra pure water reservoir under pressure driven filtration conditions. We compared these online results with static measurements from an offline, sample taking approach, using a confocal Raman laboratory microscope. The developed Au NP SERS sensing area on the membranes proved to be stable over a long period of surface fouling investigations and to suppress the strong interfering Raman signal originating from the composition layer of most filtration membranes.