nils-herrmann/clean_scirepeval huggingface dataset:
The assessment of lichens as bioindicator of heavy metal pollution from motor vehicles activites
Year: 2011

The contamination of heavy metals released by traffic activities on roadside soils and crops are important problems in developed and developing countries for decades. An assessment of the extent of pollution in roadside soils is a key procedure to protect their ecological function and sustainable agriculture. The objectives of this study were to determine heavy metal contamination of roadside soils that originated from motor vehicles through the use of eight different lichens species situated along D 950 motorway in Erzurum. The results showed that the contamination of Pb, Cr, Cu, Cd, and Ni in roadside soils stemmed mainly from traffic activities, especially for Pb and Cd in this study area judging by their distribution patterns and their enrichment factors. Some of the lichen species such as Xanthoria candelaria (L. Th. Fr. Lecanora muralis (Schreb. Rabenh. and Xanthoria elegans (Link)Th. Fr. present in the region can be used to monitor pollution of traffic origin and X. candelaria, in particular, is a very good indicator of pollution of traffic origin. This kind of lichen could be an easy and cost effective means of air pollution monitoring.  Bioindicator, enrichment factor, heavy metal pollution, lichen, traffic pollution
Hepatoprotective Potential of Trichosanthes dioica Roxb in Hepatotoxicity Induced by Simvastatin and its consequences on Biochemical and Haematological Indices
Year: 2018

To evaluate hepatoprotective activity along with hematological and defensive recital of Trichosanthes dioica Roxb against simvastatin induced hepatotoxicity in experimental rodents.  In the present study, invivo hepatoprotective effect of 50% methanolic fruit extract of Trichosanthes dioica Roxb (TME 200 and 400 mg/kg body weight) was evaluated using experimental model, simvastatin (20 mg/kg, p.o. induced hepatotoxicity in experimental animals. The hepatoprotective activity was estimatedby interpreting using various biochemical parameters like SGOT, SGPT, ALP, total bilirubin, total protein and albumin along with the haematological and histopathological studies.  The treatment with TME significantly (P<0.05 P<0.001) and dose dependently reversed simvastatin induced elevation in serum level ofSGOT, SGPT, ALP, total bilirubin and restored the total protein and albumin level. Furthermore, TME also signify the blood parameters at dose of 1000 and 2000 mg/kg and restored the body defense mechanism. The histological examination revealed that TME at dose of 200 mg/kg showed regeneration of hepatocytes around central vein with near normal liver architecture.  The results of this study exhibited liver protective effect of Trichosanthes dioica Roxb against simvastatin induced liver injury and there by scientifically support its traditional use.
Unique role of Mossbauer spectroscopy in assessing structural features of heterogeneous catalysts
Year: 2018

Their wide availability in nature, low cost, high reactivity, and low toxicity make Fe based catalysts versatile in various catalysis fields, including photocatalysis, Fenton like reaction, electrocatalysis, Li ion batteries (LIBs) Fischer Tropsch synthesis (FTS) biomass conversion, N2O decomposition and etc. Mossbauer spectroscopy, a powerful technique that is able to give account of structural features for all iron species taking part in the catalysis process, is considered to be a crucial technique for determining catalyst phase, identifying active site, and investigating correlations between catalytic behavior and the coordination structure of catalysts, which are highly desirable for clarifying the catalytic mechanisms. Each kind of Fe based materials could be functionalized in the most suitable catalysis field, wherever Mossbauer technique may play a unique role. For instance, Fe N C based materials are extensively investigated as electrocatalysts for oxygen reduction reaction and Mossbauer spectroscopy application in this field has been utilized to identify the chemical nature of the active site on the Fe N C catalyst. Iron carbides are considered as the most active phase for FTS and Mossbauer technique is widely applied in determining the chemical phase of catalysts. Fe based silicates, phosphates or polyanionic compounds are recognized as promising cathode materials for LIBs, for which Mossbauer technique has been mainly applied for tracking of the oxidation state and coordination environment change of Fe between charged and discharged states of the batteries. Similar phenomena can also be found in other catalysis fields. To give a clear understanding of which field is most suitable for a certain Fe based catalyst and the best role of the Mossbauer technique in a certain catalysis field associated with the investigation of the mechanism, in this review, the recent advances of applying Mossbauer technique in catalysis are thoroughly summarized, including results from environmental catalysis and energy catalysis. Remarkable cases of study are highlighted and brief insight into applying Mossbauer technique for various Fe based materials in their special catalysis field is presented. Finally, the trends for future potential applications of Mossbauer technique are discussed.
Enhancing knowledge management for R&D innovation and firm performance: An integrative view
Year: 2010

Previous researches have examined the relationships among variables such as knowledge management (KM) innovation and performance. However, most empirical studies have investigated the relationships among these variables in isolation. A gap thus exists in the literature and to fill this gap, the current study develops a research model that links these variables. The model establishes the relationships among KM capability, research and development (R&D) innovation and firm performance. The findings suggest that CEOs should manage knowledge based resource and assess whether the firm has the KM capability to create, maintain and exploit the knowledge based synergies for superior innovation of R&D departments.  Knowledge management, innovation, firm performance.
Noniterative Hyperspectral Image Reconstruction From Compressive Fused Measurements
Venue: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Year: 2019

Compressive spectral imaging (CSI) enables the acquisition of spectral and spatial information of a scene using fewer projected measurements than traditional scanning approaches. Recently, research efforts have focused on obtaining high resolution spectral images via expensive detectors and sophisticated CSI devices. Alternatively, high resolution spectral images can be obtained using side information or fusion of compressed measurements, without significantly increasing acquisition costs. Indeed, these approaches retrieve improved resolution images applying iterative and computationally expensive algorithms. This paper proposes the fusion of compressed measurements obtained from two state of the art CSI systems, the single pixel camera (SPC) and the three dimensional coded aperture snapshot imaging system (3D CASSI) such that high resolution images can be obtained by exploiting detailed spectra provided by the SPC and high spatial resolution of the 3D CASSI. Specifically, a noniterative reconstruction algorithm is proposed, based on the fact that the spatial spectral data lie in a low dimensional subspace. In contrast to related works, the proposed approach relies on implementable CSI systems. Simulations and experimental results show the effectiveness of the proposed method compared to similar approaches, both in reconstruction quality and complexity. Specifically, the proposed method is up to 5.6 times faster than its counterparts and provides comparable quality of attained reconstructions.
Beware of Imitations: All about Eve (1950)
Year: 2017

Joseph L. Mankiewicz's film All About Eve (1950) offers a useful case study through which to examine the relationship between genre and psychology in adaptation studies, particularly as they relate to performance. In this anti biopic, the eponymous young star does not know how to adapt, that is, how to discover new relationships between the self and the outside world. Instead, Eve imitates the mannerisms of an established star, rehearsing and rehashing the perspectives of others in her acting. The fact that she receives a prestigious award for imitation, and not for a truly adaptive performance, allows us to reflect critically on adaptation as a psychological as well as a textual process and the purposes of theatre and film awards.
Smarter Password Guessing Techniques Leveraging Contextual Information and OSINT
Venue: 2020 International Conference on Cyber Security and Protection of Digital Services (Cyber Security)
Year: 2020

In recent decades, criminals have increasingly used the web to research, assist and perpetrate criminal behaviour. One of the most important ways in which law enforcement can battle this growing trend is through accessing pertinent information about suspects in a timely manner. A significant hindrance to this is the difficulty of accessing any system a suspect uses that requires authentication via password. Password guessing techniques generally consider common user behaviour while generating their passwords, as well as the password policy in place. Such techniques can offer a modest success rate considering a large/average population. However, they tend to fail when focusing on a single target especially when the latter is an educated user taking precautions as a savvy criminal would be expected to do. Open Source Intelligence is being increasingly leveraged by Law Enforcement in order to gain useful information about a suspect, but very little is currently being done to integrate this knowledge in an automated way within password cracking. The purpose of this research is to delve into the techniques that enable the gathering of the necessary context about a suspect and find ways to leverage this information within password guessing techniques.
A GPU memory efficient speed up scheme for training ultra deep neural networks: poster
Venue: PPoPP
Year: 2019

Ultra deep neural network(UDNN) tends to yield higher quality model but its training process is often difficult to handle. Scarce GPU DRAM capacity is the primary bottleneck that limits the depth of neural network and the range of trainable minibatch size. In this paper, we present a scheme that dedicates to make the utmost use of finite GPU memory resource to speed up the training process for UDNN. Firstly, a performance model guided dynamic swap out/in strategy between GPU and host memory is carefully orchestrated to tackle the out of memory problem without introducing performance penalty. Then, a hyperparameter (minibatch size, learning rate) tuning policy is designed to explore the optimal configuration after applying the swap strategy from the perspectives of training time and final accuracy simultaneously. Finally, we verify the effectiveness of our scheme in both single and distributed GPU mode.
Arthropod Borne Diseases
Venue: Journal of the American Mosquito Control Association
Year: 2017

The book promises to provide health professional and the general public information of vector borne diseases worldwide. The book focuses on vectorborne pathogenic diseases; it purposely leaves out venomous biting and stinging arthropods such as spiders, scorpions, as they are discussed elsewhere in the literature. The book is divided into four parts spread over 38 chapters written by 57 subject experts. Part I: Introduction is composed of four chapters dealing with 1) generalities and importance of vector borne diseases, 2) epidemiology, 3) arthropod borne diseases and history, and 4) blood sucking, vector parasite relationship, and transmission of diseases. Part II: Diseases Transmitted by Arthropods is the longest section, consisting of 26 chapters. The section covers chapter 5) arboviruses, 6) Flavivirus, 7) dengue, 8) yellow fever, 9) Togaviridae, 10) Bunyaviridae, 11) plague and tularemia, 12) rickettsial and Bartonella infections, 13) borreliosis, 14) ehrlichiosis, 15) anaplasmosis, 16) leishmaniasis, 17) Chagas disease (American trypanosomiasis) 18) sleeping sickness and nagana disease, 19) other major trypanosomiasis, 20) malaria, 21) babesiosis, 22) theileriosis, 23) hepatozoonosis, 24) lymphatic filariasis, 25) onchocerciasis, 26) mansonelliasis, 27) loiasis, 28) dirofilariosis, 29) thelaziosis, and 30) habronemosis. Each chapter starts with an abstract, followed by discussion on the pathogen, disease symptoms, diagnosis, treatment, epidemiology, control, protection, and references. Part III: Diseases Caused by Arthropods has six chapters. These include chapter 31) flies, 32) sucking and chewing lice, 33) fleas and diseases, 34) diseases caused by Acari (ticks and mites) 35) other irritating arthropods (beetles, bugs, centipedes) and 36) allergy to hematophagous arthropod bites. Each chapter in this section varies in composition and layout. Part IV: Additional Considerations covers the last two chapters, the first of which is chapter 37 on geoprocessing and expected distribution of diseases, including deforestation and global warming. The second and last chapter 38 deals with Wolbachia: influence on pathogeny, treatment, and control of arthropod diseases. The general layout of the book and its contents are quite appealing. All sections and subsections are numbered by chapter with ample use of tables, figures, and other illustrations in color, thus making the reading easier. Each disease topic presents a historical background of the disease, followed by epidemiology, transmission cycle, treatment, prevention, and control. Finally, the book is well organized and generally well written with plenty of old and contemporary information on vector borne diseases. It is a good addition to the literature in medical and veterinary entomology and vector ecology. The book will be useful to students and professionals in medical entomology, vector ecology, environmental heath, epidemiology, and public health.
Performance comparison of image keypoint detection, description, and matching methods
Venue: 2016 IEEE 5th Global Conference on Consumer Electronics
Year: 2016

In this paper we investigate the methods for image keypoint detection, description, and matching. We compare four methods, including SIFT, SURF, ORB, and BRISK. The datasets used for evaluation cover different changes and transformations in imaging conditions, such as zoom, rotation, blur, viewpoint, light, and JPEG compression. We also compare the computational speed of these four methods.
Hybrid green nanocomposites of poly(lactic acid) reinforced with banana fibre and nanoclay
Year: 2014

Green nanocomposites of poly(lactic acid)/banana fibre/nanoclay were successfully prepared using melt blending technique followed by injection moulding. Untreated and chemically modified banana fibres and organically modified nanoclay (Cloisite 30B) were used as reinforcing agent within the poly(lactic acid) matrix. The banana fibres were subjected to various chemical modifications such as mercerization, silane treatment, sodium lauryl sulphate treatment, permanganate treatment and combination of mercerization and silane treatment. The biocomposites and bionanocomposites were subjected to characterization tests i.e. mechanical properties, dynamic mechanical analysis, differential scanning calorimetry, thermogravimetric analysis, heat deflection temperature (HDT) morphological properties using scanning electron microscopy and transmission electron microscope and water absorption studies to evaluate the effect of chemical modification of banana fibre and incorporation of nanoclay. Silane treated fibre reinforced poly(lactic acid) composites and its bionanocomposites displayed optimum tensile and flexural properties than that of virgin poly(lactic acid) resin, whereas the impact strength of composites showed a reverse order due to the brittle nature of matrix. Dynamic mechanical analysis result shows that the storage modulus of the bionanocomposites increases with respect to the virgin poly(lactic acid) and biocomposites. Differential scanning calorimetry results revealed that the glass transition was not significantly changed; however, the incorporation of both silane treated fibre and C30B nanoclay enhanced the nucleation of poly(lactic acid) crystallites as well as increased the melting temperatures. The results of thermogravimetric analysis depicted that fibre modification and incorporation of nanoclay can improve the degradation temperature of the composites. Scanning electron micrographs demonstrated improper dispersion of untreated fibres and proper dispersion of treated fibres within the poly(lactic acid) matrix, thereby revealing the interfacial adhesion between the fibres and matrix. Additionally, the composites were subjected to water absorption studies, which revealed that bionanocomposites exhibited better water resistance than biocomposites.
Calcaneal osteochondroma masquerading as plantar fasciitis: An approach to plantar heel pain A case report and literature review
Venue: World journal of orthopedics
Year: 2019

Heel pain is a common orthopaedic complaint, and if left untreated can be a source of chronic morbidity. Accurate diagnosis can be challenging, owing to the complex anatomy and multiple pain generators present in the foot. We aim to share our clinical experience managing an unusual case of chronic heel pain secondary to osteochondroma.  A 41 year old obese male who works as a porter presented with a long standing history of left plantar heel pain. He was assessed to have point tenderness over the plantar insertion of the calcaneus as well as a positive Silfverskiold test. He was treated for plantar fasciitis and tight gastrocnemius but failed conservative therapies as well as surgical intervention. Magnetic resonance imaging revealed the presence of a pedunculated bony protrusion over the plantar aspect of the calcaneus. The decision was made for excision of the osteochondroma, and the patient has been pain free since.  Osteochondromas are rarely symptomatic in skeletally mature patients. While most are benign with a very low risk of malignant transformation, surgical excision can yield excellent results and significant pain relief in symptomatic patients.
Antibioprophylaxie en chirurgie et medecine interventionnelle (patients adultes) Actualisation 2017
Venue: Anesthesie Reanimation
Year: 2019

Resume L'infection est un risque pour toute intervention et, par exemple, en chirurgie l'on retrouve des bacteries pathogenes dans plus de 90 des plaies operatoires, lors de la fermeture. Ceci existe quelle que soit la technique chirurgicale et quel que soit l'environnement (le flux laminaire ne supprime pas completement ce risque) Ces bacteries sont peu nombreuses mais peuvent proliferer. Elles trouvent dans la plaie operatoire un milieu favorable (hematome, ischemie, modification du potentiel d'oxydoreduction. et l'intervention induit des anomalies des defenses immunitaires. En cas d'implantation de materiel etranger le risque est majore. L'objectif de l'antibioprophylaxie (ABP) est de s'opposer a la proliferation bacterienne afin de diminuer le risque d'infection du site de l'intervention. La consultation preoperatoire represente un moment privilegie pour decider de la prescription d'une ABP. Il est possible d'y definir le type d'intervention prevu, le risque infectieux qui s'y rapporte (et donc la necessite ou non d'une ABP) le moment de la prescription avant l'intervention et d'eventuels antecedents allergiques pouvant modifier le choix de la molecule antibiotique selectionnee.
Remote Sensing Image Classification Based on a Cross Attention Mechanism and Graph Convolution
Year: 2020

An attention mechanism assigns different weights to different features to help a model select the features most valuable for accurate classification. However, the traditional attention mechanism algorithm often allocates weights in a one way fashion, which can result in a loss of feature information. To obtain better hyperspectral data classification results, a novel cross attention mechanism and graph convolution integration algorithm are proposed in this letter. First, principal component analysis is used to reduce the dimensionality of hyperspectral images to obtain low dimensional features that are more expressive. Second, the model uses a cross (horizontal and vertical directions) attention algorithm to allocate weights jointly based on its two strategies; then, it adopts a graph convolution algorithm to generate the directional relationships between the features. Finally, the generated deep features and the relationship between the deep features are used to complete the prediction of hyperspectral data. Experiments on three well known hyperspectral data sets Indian Pines, the University of Pavia, and Salinas show that the proposed algorithm achieves better performances than do other well known algorithms using different methods of training set division.
Impact of different layers on performance of OLED
Year: 2018

This paper explores how different layers in an organic light emitting diode (OLED) impacts its performance. Here, different layers of OLED similar to hole/electron injection layer, transport layer, and block layers are analyzed. Four experimental devices are taken into consideration and their results are compared to one over another to analyze the impact of every layer. Inside depth analysis is also performed on the device to inspect what really is happening Innermost of the OLED. It is noticed that hole and electron block layer are instrumental in improving the device luminescence performance and efficiency. There is an improvement of 16, 37 and 38% in the luminescence of the device when hole block layers and electron block layers are added. Internal device analysis reveals that increase in charge carrier concentration and carrier confinement are the reason for this improvement.
Social Identity, Self Esteem, and Mental Health in Autism
Year: 2017

We investigated Autism social identity and mental health in autistic people. Autistic people have social and communication deficits, and experience social stigma factors that could interfere with the development of positive social identity. Indeed, autistic participants (N 272) had significantly lower personal self esteem, and higher levels of depression and anxiety than typically developing controls (N 267) Autism social identification was positively associated with personal self esteem, and this relationship was mediated by collective self esteem (perceived positivity of Autism identity) Furthermore, there were significant negative indirect effects between Autism identification and anxiety, and between Autism identification and depression, through increases in collective self esteem and personal self esteem. Thus, while autistic participants reported poorer mental health than average, having a positive Autism social identity appeared to offer a protective mechanism. This implies that to improve mental health in the Autism population, clinical approaches should aim to facilitate development of positive Autism identities.
CKshare: secured cloud based knowledge sharing blockchain for injection mold redesign
Venue: Enterp. Inf. Syst.
Year: 2019

This paper proposes a trustable mold redesign knowledge sharing platform, known as CKshare, based on private cloud and blockchain technology. Firstly, we use private cloud to store the mold redesign knowledge of each party to meet its own privacy and data format requirements. Secondly, a blockchain network is used for recording the knowledge and its transactions to ensure security and trustfulness. Thirdly, a simple retrieval mechanism is developed based on k nearest neighbors for retrieving the codified knowledge on the platform. To realize CKshare, a prototype platform has been developed and explained based on real data from the case mold company.