nils-herrmann/clean_scirepeval huggingface dataset:
A Quality Research Analysis of Logistics Distribution Process of Fresh Meat Cold Chain in Beijing
Year: 2015

Beijing is a typical consumption oriented city, where the consumption of fresh food bears the characteristics of rich varieties and high quality. Cold chain logistics is the important guarantee for fresh food safety, so developing cold chain logistics makes great sense. At the same time, in the consumption structure of residents' daily life, the consumption of fresh meat holds a great proportion. Therefore, the team carries on an investigation in several representative slaughtering enterprises in Beijing, and the authors analyzed the resource allocation of meat cold chain logistics in Beijing and the quality of the cold chain distribution process with the quality management method of PDCA cycle, then in doing that the authors find out the main factors affecting the quality of raw meat cold chain logistics distribution process and optimizes the factors.
Solar power utility sector in india: Challenges and opportunities
Year: 2018

In the last decade the demand of power in India has increased manifold, therefore Government has announced the National Solar Mission of generating 100GW of solar power up to 2022. Around 60% of the total National Solar Mission target is allotted to the national/international large scale solar power developers/investors. Hence, it becomes important to know the ground reality of large scale solar PV developers/investors. This paper deeply analyzes the key barriers and bottlenecks faced by solar power developers in achieving the target and their growth. This article also suggests some motivational factors of solar energy which play an important role in attracting large solar players around the world to invest in Indian subcontinent. It concludes by highlighting some key policies of the Government that can help in addressing some identified barriers in order to ensure a secured sustainable energy future of India.
Blue LED Mediated Intramolecular C H Functionalization and Cyclopropanation of Tryptamines: Synthesis of Azepino[4, 5 b]indoles and Natural Product Inspired Polycyclic Indoles.
Venue: Organic letters
Year: 2020

We report a novel blue LED mediated intramolecular C H functionalization of tryptamine derivatives to generate azepino[4, 5 b]indoles (4) in moderate to good yields. By altering the substitution at the tryptamine nitrogen, intramolecular cyclopropanation is achieved in high yields under the same reactions condition to provide natural product inspired polycyclic indoles (6) which are further transformed to spiropiperidino (5 and 8) indoles in decent yields. The mechanism of formation of the compounds was investigated through DFT studies.
Developing a new class of UV curable polyurethane acrylate resins for coating applications
Venue: Egyptian Journal of Chemistry
Year: 2019

POLYESTER (PET) fabrics that containing nitrogen can be considered as a potential material for multipurpose applications. For this purpose, primary attention is given to introduce nitrogen containing functional group onto the surface of PET fabrics using synthesized UV curable polyurethane acrylate built in amine. Moreover, the effect of incorporation the amino groups on the printing behavior of polyester fabric was evaluated. Polyurethane acrylate built in amine resins were prepared either by one shot sonochemical polymerization or by using conventional thermal synthesis procedure. Then, UV curable coatings were prepared by mixing the prepared polyurethane acrylate built in amine resin with the main components of UV curable coatings such as monomer as a diluent and 2 Hydroxy 4` (2 hydroxyethoxy) 2 methylpropiophenone as photo initiator. The prepared built in amine photopolymers were characterized by (H1 NMR) (FTIR) and (GPC) The morphology of the cured coating was also examined by using scanning electron microscopy (SEM) In addition, fastness properties of the printed fabrics and color strength were carried out to assess the effectiveness of the incorporation of the nitrogen groups on the stability of the coating layer. The results showed that, the IR Spectra of vinyl terminated PU polymers has a characteristic peak of N H stretching at 3326 cm 1 accredited to the formation of urethane bond. It was also found that treatment of PET fabric with polyurethane acrylates resin containing built in amine results in an increase in the affinity to acid dyes. The current work opens up a novel opportunity to develop nitrogen containing PET fabrics.
Context Aware Deep Feature Compression for High Speed Visual Tracking
Venue: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
Year: 2018

We propose a new context aware correlation filter based tracking framework to achieve both high computational speed and state of the art performance among real time trackers. The major contribution to the high computational speed lies in the proposed deep feature compression that is achieved by a context aware scheme utilizing multiple expert auto encoders; a context in our framework refers to the coarse category of the tracking target according to appearance patterns. In the pre training phase, one expert auto encoder is trained per category. In the tracking phase, the best expert auto encoder is selected for a given target, and only this auto encoder is used. To achieve high tracking performance with the compressed feature map, we introduce extrinsic denoising processes and a new orthogonality loss term for pre training and fine tuning of the expert autoencoders. We validate the proposed context aware framework through a number of experiments, where our method achieves a comparable performance to state of the art trackers which cannot run in real time, while running at a significantly fast speed of over 100 fps.
The Hippocampal VTA Loop: The Role of Novelty and Motivation in Controlling the Entry of Information into Long Term Memory
Venue: Intrinsically Motivated Learning in Natural and Artificial Systems
Year: 2013

The role of dopamine has been strongly implicated in reward processes, but recent work shows an additional role as a signal that promotes the stable incorporation of novel information into long term hippocampal memory. Indeed, dopamine neurons, in addition to being activated by reward, can be activated by novelty in the absence of reward. The computation of novelty is thought to occur in the hippocampus and is carried to the dopamine cells of the VTA through a polysynaptic pathway. Although a picture of novelty dependent processes in the VTA and hippocampus is beginning to emerge, many aspects of the process remain unclear. Here, we will consider several issues: (1) What is relationship of novelty signals coming to the VTA from the superior colliculus, as compared to those that come from the hippocampus? (2) Can dopamine released by a reward enhance the learning of novel information? (3) Is there an interaction between motivational signals and hippocampal novelty signals? (4) What are the properties of the axons that generate dopamine release in the hippocampus? We close with a discussion of some of the outstanding open issues in this field.
Adversarial Attacks on Graph Neural Networks via Meta Learning
Year: 2019

Deep learning models for graphs have advanced the state of the art on many tasks. Despite their recent success, little is known about their robustness. We investigate training time attacks on graph neural networks for node classification that perturb the discrete graph structure. Our core principle is to use meta gradients to solve the bilevel problem underlying training time attacks, essentially treating the graph as a hyperparameter to optimize. Our experiments show that small graph perturbations consistently lead to a strong decrease in performance for graph convolutional networks, and even transfer to unsupervised embeddings. Remarkably, the perturbations created by our algorithm can misguide the graph neural networks such that they perform worse than a simple baseline that ignores all relational information. Our attacks do not assume any knowledge about or access to the target classifiers.
Recenze: Erzsebet Barat Patrick Studer Jiri Nekvapil (eds. Ideological Conceptualizations of Language: Discourses of Linguistic Diversity
Year: 2015

Erzsebet Barat, Patrick Studer, Jiri Nekvapil (eds. Ideological Conceptualizations of Language: Discourses of Linguistic Diversity. Frankfurt am Main, Bern, Bruxelles, New York, Oxford, Warszawa, Wien: Peter Lang, 2013. xi+283 pp. Prague Papers on Language, Society and Interaction, 3.
Witnessing Workplace Bullying and Employee Well Being: A Two Wave Field Study
Venue: Journal of occupational health psychology
Year: 2019

This article aims to (a) explore the impact of witnessing workplace bullying on emotional exhaustion, work related anxiety, and work related depression and (b) determine whether the resources of trait optimism, coworker support, and supportive supervisory style buffer the effects of witnessed bullying. In a two wave study involving 194 employees, we found that witnessing bullying undermined employees' well being (work related depression and anxiety) 6 months later, but only if the employees were low in optimism (personal resource) and lacked supervisor support (contextual resource) Strong coworker support weakened the relationship between witnessing bullying and well being (emotional exhaustion and work related depression) Our findings demonstrate for the first time some of the factors that protect against the impact of witnessing workplace bullying. Future research should focus on the development of workplace interventions that foster feelings of social support and optimism among employees.
Constructions en bois et habitat rural rupestre en Basse Provence au Moyen Age. Dendrologie, anthracologie et archeologie
Year: 2014

L'histoire de la foret au haut Moyen Age en Basse Provence est une question difficile a etudier en raison du manque de materiaux ligneux a disposition sur les sites archeologiques et du manque de textes traitant de la question. Une these a ete realisee sur le sujet dans le but de mieux connaitre l'emploi du bois dans l'architecture rupestre. Cette these utilise la pluridisciplinarite comme support d'etude en croisant l'etude architecturale des traces d'encastrement, l'anthracologie et la dendrochronologie. Le croisement des resultats obtenus dans le cadre de ce travail permet d'identifier les especes ligneuses utilisees sur les sites archeologiques, de determiner les dimensions des arbres utilises dans la construction et d'identifier les formations ligneuses d'ou ces arbres pourraient provenir.
Environmental impacts of forest biomass to energy conversion technologies: Grate furnace vs. fluidised bed furnace
Year: 2018

Electricity production from biomass has the potential to significantly contribute to the power mix in Portugal with lesser environmental impact than non renewable resources. This study focuses on electricity production from the combustion of residual forest biomass from eucalypt logging activities in Portugal using life cycle assessment. In Portugal, several power plants fuelled by residual forest biomass have been commissioned in the last few years. Most of the installations use fluidised bed furnaces, and the others use grate furnaces. This study aims to compare the environmental impacts associated with these two alternative combustion technologies. System boundaries include the stages of forest management, collection processing and transportation and energy conversion. The default impact assessment method used is that suggested in the International Reference Life Cycle Data System. In a sensitivity analysis, calculations are performed using the ReCiPe method. For all of the impact categories analysed, the fluidised bed presents the smallest environmental impact. Even when the grate furnace efficiency increases and the fluidised bed efficiency decreases in the sensitivity analysis, the fluidised bed has lower impacts than the grate technology and can be the best alternative in the implementation of new power plants.
Educating the Mindful Design Practitioner
Year: 2021

Mindfulness applications are increasing exponentially across many disciplines. However, mindfulness theory and practice within design pedagogy is relatively scarce. What are the operational concepts and applications of mindfulness for acquiring design skills and ethical awareness? We explore these questions through a theoretical framework and two university based studies where design students engaged in various mindfulness activities. Results show that meditation practices (formal mindfulness) and adopting a mindful approach to design tasks (informal mindfulness) can facilitate exploratory and creative thinking, increase sensory and spatial awareness, 'free up' one's inner critic, and expand students' empathetic horizons. These outcomes suggest mindfulness training is fruitful for the holistic development of students, supporting them to be truly reflective practitioners who creatively attend to the wellbeing of others and themselves.
MobiFace: A Lightweight Deep Learning Face Recognition on Mobile Devices
Venue: 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS)
Year: 2019

Deep neural networks have been widely used in numerous computer vision applications, particularly in face recognition. However, deploying deep neural network face recognition on mobile devices has recently become a trend but still limited since most high accuracy deep models are both time and GPU consumption in the inference stage. Therefore, developing a lightweight deep neural network is one of the most practical solutions to deploy face recognition on mobile devices. Such the lightweight deep neural network requires efficient memory with small number of weights representation and low cost operators. In this paper, a novel deep neural network named MobiFace, a simple but effective approach, is proposed to productively deploy face recognition on mobile devices. The experimental results have shown that our lightweight MobiFace is able to achieve high performance with 99.73% on LFW database and 91.3% on large scale challenging Megaface database. It is also eventually competitive against large scale deep networks face recognition while significant reducing computational time and memory consumption.
Internal Control, Cross border Mergers, Cultural Integration and Merger Performance
Year: 2018

Select the 2015 2016 takeover of listed companies have already completed the merger of enterprises in transnational mergers and acquisitions as the sample, the system of internal control quality on the influence of culture integration in transnational merger and acquisition ability and performance of cross border mergers and acquisitions, the empirical analysis shows that the higher the quality of internal control, enterprise transnational merger and acquisition of cultural integration ability is strong, the better the performance of cross border mergers and acquisitions, that related to cross border mergers Acquisitions of transnational mergers and acquisitions, internal control and enterprise performance is positive. This paper presents the internal control mechanism of the integration of cross border mergers and acquisitions culture, expansion and development of the theory of internal control field, enrich the research related to the transnational merger and acquisition performance, discusses the important status of internal control in enterprises in cross border mergers and acquisitions, to study the relationship between transnational merger and acquisition activities and internal control system and has a certain practical significance.
Adaptive Consensus Control of Linear Multiagent Systems With Dynamic Event Triggered Strategies
Venue: IEEE Transactions on Cybernetics
Year: 2020

This paper is concerned with event triggered consensus of general linear multiagent systems (MASs) in leaderless and leader following networks, respectively, in the framework of adaptive control. A distributed dynamic event triggered strategy is first proposed, in which an auxiliary parameter is introduced for each agent to regulate its threshold dynamically. The time varying threshold ensures less triggering instants, compared with the traditional static one. Then under the proposed event triggered strategy, a distributed adaptive consensus protocol is formed including the updating law of the coupling strength for each agent. Some criteria are derived to guarantee leaderless or leader following consensus for MASs with general linear dynamics, respectively. Moreover, it is proved that the triggering time sequences do not exhibit Zeno behavior. Finally, the effectiveness of the proposed dynamic event triggered control mechanism combined with adaptive control is validated by two examples.
Refractoriness to pharmacological treatment for tics: A multicentre European audit
Venue: Journal of the Neurological Sciences
Year: 2016

Recently, a consensus definition of treatment responsiveness for obsessive compulsive disorder has been reached through Delphi survey methodology, showing great potential for practical application in clinical care  A standardized definition of refractoriness to pharmacological treatment of tics in TD (chronic tic disorders including Tourette Syndrome) would aid decisions on drug switch, psychological treatment or access to invasive treatments like functional surgery [2,3] We conducted a European audit survey in order to: i) explore the main features that would define refractoriness of tics to pharmacological treatment, and ii) assess how consistently these features are taken into account in routine clinical practice. Itemsdefining treatment refractoriness in TDwas discussedwithin a panel of seven expert clinicians (panel clinicians) across different European countries. All panel members were invited to rate each item according to whether the domain measured was 'essential' or not for the definition of refractoriness. Only those items for which a unanimous judgement of 'essential'was reachedwere then considered for the audit survey. This procedure yielded the following list of 'essential' items: duration of treatment (weeks) dichotomous judgement of improvement of tic severity (improved/not improved) documented change of the Yale Global Tic Severity Scale (YGTSS) 0 50 severity score; reason for themaximum dose reached; number of single doses missed on average over a 10 day period. A clinical questionnaire (Appendix file) was used to collect information related to the selected items from other seven European expert clinicians (survey clinicians) The questionnaire was completed by survey clinicians related to outpatients with a diagnosis of TD (according to DSM\\V) who had been previously judged by the clinician as refractory to an anti tic monotherapy. A judgement of refractoriness implied that the clinician had already decided either to discontinue that particular anti tic monotherapy, or to change the regime by adding on another treatment. With respect to the main reason for the refractoriness judgement, refractoriness was categorised either as due to lack of efficacy at the highest tolerated dose or as due to lack of tolerability at initial or effective dosage. This studywas selectively based on the clinical information carried out as part of the routine clinical care of the patients. Sixty eight TD patients (56male, median age: 14 years; range 8 44) were enrolled consecutively across 7 European tertiary centres for TD; at each participating centre, all patients were identified by the same clinician throughout a period of 18 months. The median age at tic onset
Emergent Sentiment in Financial Markets: Sentiment Flow from Social Media to Mass Media
Year: 2019

Over the past two decades, substantial research has established the importance of sentiment in financial markets. We know that sentiment impacts investor decisions; because of advanced text mining and sentiment analysis techniques, automated trading strategies based on sentiment are prevalent. However, we know little about how sentiment emerges. The news media, the markets, and social media are all understood to contribute to overall sentiment, but the exact mechanisms at play remain largely unknown. Understanding the mechanism of sentiment emergence is critical to build systems to support investors' decision making and to ensure that markets function well and are resistant to attempts to manipulate sentiment. We studied one piece of the puzzle and examined sentiment flow from social media to mass media. We studied two years (2013 to 2014) of data from Sina Weibo and Sina Finance. After controlling for the direction of influence from mass media to social media and also for stock performance, we found that in the stock market, social media sentiment affects mass media sentiment the next day. Moreover, this impact is stronger for attention grabbing stocks. The implications of these findings are discussed in relation to sentiment emergence and a broader demand driven media bias perspective.
Implementing neural machine translation with bi directional GRU and attention mechanism on FPGAs using HLS
Venue: ASP DAC
Year: 2019

Neural machine translation (NMT) is a popular topic in Natural Language Processing which uses deep neural networks (DNNs) for translation from source to targeted languages. With the emerging technologies, such as bidirectional Gated Recurrent Units (GRU) attention mechanisms, and beam search algorithms, NMT can deliver improved translation quality compared to the conventional statistics based methods, especially for translating long sentences. However, higher translation quality means more complicated models, higher computation/memory demands, and longer translation time, which causes difficulties for practical use. In this paper, we propose a design methodology for implementing the inference of a real life NMT (with the problem size 172 GFLOP) on FPGA for improved run time latency and energy efficiency. We use High Level Synthesis (HLS) to build high performance parameterized IPs for handling the most basic operations (multiply accumulations) and construct these IPs to accelerate the matrix vector multiplication (MVM) kernels, which are frequently used in NMT. Also, we perform a design space exploration by considering both computation resources and memory access bandwidth when utilizing the hardware parallelism in the model and generate the best parameter configurations of the proposed IPs. Accordingly, we propose a novel hybrid parallel structure for accelerating the NMT with affordable resource overhead for the targeted FPGA. Our design is demonstrated on a Xilinx VCU118 with overall performance at 7.16 GFLOPS.
Local Anomaly Detection
Venue: AISTATS
Year: 2012

Anomalies with spatial and temporal stamps arise in a number of applications including communication networks, traffic monitoring and video analysis. In these applications anomalies are temporally or spatially localized but otherwise unknown. We propose a novel graph based statistical notion that unifies the idea of temporal and spatial locality. This notion lends itself to an elegant characterization of optimal decision rules and in turn suggests corresponding empirical rules based on local nearest neighbor distances. We compute a single composite score for the entire spatio temporal data sample based on the local neighborhood distances. We declare data samples as containing local anomalies based on the composite score. We show that such rules not only asymptotically guarantee desired false alarm control but are also asymptotically optimal. We also show that our composite scoring scheme overcomes the inherent resolution issues of alternative multi comparison approaches that are based on fusing the outcomes of location by location comparisons. We then verify our algorithms on synthetic and real data sets.