nils-herrmann/clean_scirepeval huggingface dataset:
Casitone dependent transcriptional regulation of theprtP andprtM genes in the natural isolateLactobacillus paracasei subsp.paracasei
Venue: Folia Microbiologica
Year: 2008

prtM intergenic region ofLactobacillus paracasei subsp.paracasei BGHN14 was cloned and sequenced. The nucleotide sequence of theprtP prtM intergenic region in BGHN14, containing divergently orientated PprtP and PprtM promoters, was shorter by 35 bp in comparison with that in lactococci. The nucleotide sequence involved in casitone dependent transcriptional regulation of the lactococcalprt genes was not found in the BGHN14. The activity of PprtM inL. lactis NZ9000 was very low and insignificantly changed in the presence of casitone, whereas PprtP was completely inactive. WhenL. casei ATCC393T was used as host, both PprtP and PprtM were active and strongly regulated by casitone. The results strongly indicate that the mechanisms of the casitone dependent regulation of theprt genes in BGHN14 and lactococci are different.
The effect of clay organophilization on wood plastic composite (WPC) based on recycled high density polyethylene (HDPE) and coir fiber
Year: 2021

One way to optimize composite mechanical properties is through hybridization with small amounts of reinforcing fillers. Thus, this study investigates the effect of incorporation of 3 wt% of clay (BT) and organoclay (OBT) on the properties of a recycled wood plastic composite (WPC) based on HDPE and 20 wt% of coir fiber compounded with 5 wt% of maleic anhydride grafted polypropylene (PP g MA) as coupling agent, and 5 wt% of Struktol TPW 113, as lubricating agent. Raw materials were characterized by X ray fluorescence (XRF) Fourier transform infrared spectroscopy (FTIR) X ray diffraction (XRD) scanning electron microscopy (SEM) and thermogravimetric analysis (TGA) Coir fiber was characterized by optical microscopy and TGA. Wood plastic formulations (with clay and organoclay) were prepared in an internal mixer coupled to a torque rheometer operating at 190degC, 60 rpm for 10 min. Then, the mixtures were compression molded. Formulations were characterized by SEM, TGA, DSC, tensile and water absorption tests. FTIR analysis showed the characteristic bands of organophilic clay. XRD showed an increment in the interplanar distance of the clay, after the incorporation of quaternary ammonium salt (distearyl dimethyl ammonium chloride, Praepagen(r) WB) confirming the organoclay formation. Organophilization decreases the clay hydrophilic character and reduces the water uptake of WPC BT. Despite the fact that BT incorporation led to WPC nanocomposite with intercalated structure, this WPC clay composition did not show a significant increase in tensile strength and elongation at break. The poor interfacial adhesion between the raw materials and the polymer matrix, the low aspect ratio provided by coir fibers and also, the partially intercalated structure of composites have contributed to this behavior.
Monocular 3D Object Detection Using Feature Map Transformation: Towards Learning Perspective Invariant Scene Representations
Venue: 2020 Fourth IEEE International Conference on Robotic Computing (IRC)
Year: 2020

In this paper we propose to use a feature map transformation network for the task of monocular 3D object detection. Given a monocular camera image, the transformation network encodes features of the scene in an abstract, perspective invariant latent representation. This latent representation can then be decoded into a bird's eye view representation to estimate objects' position and rotation in 3D space. In our experiments on the Kitti object detection dataset we show that our model is able to learn to estimate objects' 3D position from a monocular camera image alone without having any explicit geometric model or other prior information on how to perform the transformation. While performing slightly worse than networks which are purpose built for this task, our approach allows feeding the same bird's eye view object detection network with input data from different sensor modalities. This can increase redundancy in a safety critical environment. We present additional experiments to gain insight into the properties of the learned perspective invariant abstract scene representation.
An Effective Network Traffic Classification Method with Unknown Flow Detection
Venue: IEEE Transactions on Network and Service Management
Year: 2013

Traffic classification technique is an essential tool for network and system security in the complex environments such as cloud computing based environment. The state of the art traffic classification methods aim to take the advantages of flow statistical features and machine learning techniques, however the classification performance is severely affected by limited supervised information and unknown applications. To achieve effective network traffic classification, we propose a new method to tackle the problem of unknown applications in the crucial situation of a small supervised training set. The proposed method possesses the superior capability of detecting unknown flows generated by unknown applications and utilizing the correlation information among real world network traffic to boost the classification performance. A theoretical analysis is provided to confirm performance benefit of the proposed method. Moreover, the comprehensive performance evaluation conducted on two real world network traffic datasets shows that the proposed scheme outperforms the existing methods in the critical network environment.
Fully Convolutional Attention Localization Networks: Efficient Attention Localization for Fine Grained Recognition
Venue: ArXiv
Year: 2016

Fine grained recognition is challenging mainly because the inter class differences between fine grained classes are usually local and subtle while intra class differences could be large due to pose variations. In order to distinguish them from intra class variations, it is essential to zoom in on highly discriminative local regions. In this work, we introduce a reinforcement learning based fully convolutional attention localization network to adaptively select multiple task driven visual attention regions. We show that zooming in on the selected attention regions significantly improves the performance of fine grained recognition. Compared to previous reinforcement learning based models, the proposed approach is noticeably more computationally efficient during both training and testing because of its fully convolutional architecture, and it is capable of simultaneous focusing its glimpse on multiple visual attention regions. The experiments demonstrate that the proposed method achieves notably higher classification accuracy on three benchmark fine grained recognition datasets: Stanford Dogs, Stanford Cars, and CUB 200 2011.
Konsep al qur'an Terhadap dikotomi ilmu pengetahuan
Year: 2017

Al Qur'an sebagai pedoman serta petunjuk manusia dalam kehidupan di dunia dan di akhirat, Al Qur'an merupakan wahyu Allah yang mengandung ajaran dan petunjuk kehidupan manusia, baik berdimensi spiritual, maupun berdimensi social horizontal serta intelektual. Bukti konkrit yang menunjukan bahwa Al Qur'an berdimensi intelektual adalah banyaknya ayat ayat Al Qur'an yang memberikan isyarat ilmiah atau petunjuk tentang ilmu pengetahuan, Al Qur'an menerangkan tentang asal usul penciptaan alam semesta dan penciptaan manusia yang proses penciptaannya dijelaskan secara mendetail dan integral dibeberapa ayat dan surat didalamnya. Dengan demikian, bukti bukti tersebut nampak jelas mengindikasikan bahwa Al Qur'an merupakan sumber berbagai ilmu pengetahuan. Al Qur'an mengajak kepada manusia untuk selalu memahami dan mengkajinya, sebagaimana kata "iqra" pada wahyu pertama yang sesungguhnya bukan hanya menyuruh untuk membaca, tetapi lebih jauh mengajarkan untuk senantiasa mengadakan pengkajian terhadap setiap bentuk perputaran dan perubahan yang terjadi, baik pada gejala di alam semesta ataupun yang terjadi di antara sesama manusia. Menurut pandangan Islam baha Ilmu pengetahuan mempunyai signifikansi vertikal dan horisontal. Secara empiris dalam mengamati ayat ayat kauniyah dapat mengantarkan manusia untuk lebih dekat mengenal kepada Allah, dengan kata lain bahwa ilmu pengetahuan, dapat dijadikan sebagai "wasilah" untuk mengenal kemahakuasaan Allah SWT.
Different supervised and unsupervised classification approaches based on visible/near infrared spectral analysis for discrimination of microbial contaminated lettuce samples: Case study on E. coli ATCC
Year: 2020

Escherichia coli is a main cause of microbial contamination in lettuce. Detection of microbial contamination is the essential key to ensure the consumption of fresh lettuce. In this investigation, the potential of Vis/NIR spectroscopy system with chemometrics analysis was probed for detecting different microbial loads (0.1, 0.2 and 0.3 ml concentration of E. coli solution) on the lettuce samples in the wavelength range of 350 1100 nm. Five different chemometrics analyses consist of soft independent modeling of class analogies (SIMCA) support vector machine (SVM) Partial least Squares Discriminant Analysis (PLS DA) (supervised techniques) principal component analysis (PCA) and hierarchical cluster analysis (HCA) (unsupervised techniques) were used. The results proved that HCA were correctly clustered unsafe samples with 0.2 ml and 0.3 ml microbial contamination. However, some overlapping was observed between safe and unsafe samples with 0.1 ml microbial contamination. Vis/NIR spectral data with pattern recognition methods (SIMCA and SVM) can be obtained acceptable degree of classification (87.1% and 89.39% accuracy, respectively) between safe and unsafe samples. Compare with 5 different methods, the best model was recommended by PLS DA using standard normal variate (SNV) second derivate (D2) pre processing methods in 6 optimal selected wavelengths (520, 670, 700, 750, 900, 970 nm) with the minimum standard error of cross validation (SECV 0.176) Besides, a good correlation (rc 0.989) between Vis/NIR spectral data and E. coli contamination proved the possibility of using Vis/NIR spectroscopy system to detection and evaluation of microbial contamination in lettuce.
Travel Time Prediction Model for Regional Bus Transit
Year: 2011

Over the past decade, the popularity of regional bus services has grown in large North American cities owing to more people living in suburban areas and commuting to the Central Business District to work every day. Estimating journey time for regional buses is challenging because of the low frequencies and long commuting distances that typically characterize such services. This research project developed a mathematical model to estimate regional bus travel time using artificial neural networks (ANN) ANN outperformed other forecasting methods, namely historical average and linear regression, by an average of 35 and 26 seconds respectively. The ANN results showed, however, overestimation by 40% to 60% which can lead to travellers missing the bus. An operational strategy is integrated into the model to minimize stakeholders' costs when the model's forecast time is later than the scheduled bus departure time. This operational strategy should be varied as the commuting distance decreases.
Ethnobotanical survey of traditionally used medicinal plants for infections of skin, gastrointestinal tract, urinary tract and the oral cavity in Borabu sub county, Nyamira county, Kenya.
Venue: Journal of ethnopharmacology
Year: 2015

ETHNOPHARMACOLOGICAL RELEVANCE Different communities throughout the world have specialized and profound knowledge on the use medicinal plants for various diseases. However, the detailed information on the respective use may extinct in near future as this knowledge is passed only orally among generations in most of the communities.  The present survey aimed to document the use of medicinal plants by traditional healers from the Kisii community, Borabu sub county in Nyamira county, Kenya, to treat infections of the urinary tract, oral cavity, gastrointestinal system and the skin and to evaluate the social context in which the healers work and practice.  Validated questionnaires were applied to 50 traditional healers in the study region, followed by interviews and structured conversations. Information on the relevant traditionally used medicinal plants and their use were documented, including sampling and identification of voucher specimens.  The ethnopharmacological survey revealed 25 medicinal plant species belonging to 19 families. It got evident that most of these species will be extinct in the near future unless appropriate measures are taken, as it turned out difficult to collect some of the wild growing species. Elaeodendron buchananii Loes, Erlangea marginata S. Moore, Acacia gerrardii Benth. Balanites orbicularis Sprague, Solanum renschii Vatke and Orthosiphon hildebrandtii Vatke have not been described before for its medicinal use. Among the 25 species collected from the various regions of Borabu sub county Urtica dioica L. was the only medicinal plant that was collected from all regions. In contrast Erythrina abyssinica and Rhus natalensis were found in only two regions of the study area.  The traditional medicinal use of the reported plants for infections should be documented and a great need of awareness from scientists and local government for improved preservation or field cultivation of some species is obvious.
Multifunctional MnO2 nanoparticles for tumor microenvironment modulation and cancer therapy.
Venue: Wiley interdisciplinary reviews. Nanomedicine and nanobiotechnology
Year: 2021

Tumor microenvironment (TME) is generally featured by low pH values, high glutathione (GSH) concentrations, overproduced hydrogen peroxide (H2 O2 and severe hypoxia. These characteristics could provide an interior environment for origination and residence of tumor cells and would lead to tumor progression, metastasis, and drug resistance. Therefore, the development of TME responsive smart nanosystems has shown significant potential to enhance the efficacy of current cancer treatments. Manganese dioxide (MnO2 based nanosystems have attracted growing attentions for applications in cancer treatment as an excellent TME responsive theranostic platform, due to their tunable structures/morphologies, pH responsive degradation, and excellent catalytic activities. In this review, we mainly summarize the strategies of MnO2 and its nanocomposites to modulate TME, such as tumor hypoxia relief, excessive GSH depletion, glucose consumption, and tumor immunosuppressive microenvironment moderation. Such MnO2 based TME modulation would be beneficial for a wide range of cancer therapies including photodynamic therapy, radiotherapy, sonodynamic therapy, chemodynamic therapy, starvation therapy, and immunotherapy. Next, some representative designs of MnO2 based nanoplatforms in other tumor therapies are highlighted. Moreover, we will discuss the challenges and future perspectives of these MnO2 based nanosystems for enhanced tumor treatment. This article is categorized under: Therapeutic Approaches and Drug Discovery Nanomedicine for Oncologic Disease.
Effects of latency and age structure on the dynamics and containment of COVID 19
Venue: medRxiv
Year: 2020

In this paper we develop an SEIR type model of COVID 19, with account for two particular aspects: non exponential distribution of incubation and recovery periods, as well as age structure of the population. For the mean field model, which does not distinguish between different age groups, we demonstrate that including a more realistic Gamma distribution of incubation and recovery periods may not have an effect on the total number of deaths and the overall size of an epidemic, but it has a major effect in terms of increasing the peak numbers of infected and critical care cases, as well as on changing the timescales of an epidemic, both in terms of time to reach the peak, and the overall duration of an outbreak. In order to obtain more accurate estimates of disease progression and investigate different strategies for introducing and lifting the lockdown, we have also considered an age structured version of the model, which has allowed us to include more accurate data on age specific rates of hospitalisation and COVID 19 related mortality. Applying this model to three comparable neighbouring regions in the UK has delivered some fascinating insights regarding the effect of quarantine in regions with different population structure. We have discovered that for a fixed quarantine duration, the timing of its start is very important in the sense that the second epidemic wave after lifting the quarantine can be significantly smaller or larger depending on the specific population structure. Also, the later the fixed duration quarantine is introduced, the smaller is the resulting final number of deaths at the end of the outbreak. When the quarantine is introduced simultaneously for all regions, increasing quarantine duration postpones and slightly reduces the epidemic peak, though without noticeable differences in peak magnitude between different quarantine durations.
Biofilm Formation by Streptococcus mutans is Enhanced by Indole via the Quorum Sensing Pathway
Venue: Microbes and environments
Year: 2020

Interspecies interactions among oral microorganisms in the pathogenic biofilms causing dental caries have not yet been elucidated in detail. We herein demonstrated that indole and its derivatives induced biofilm formation by Streptococcus mutans. Indole is an intercellular signaling molecule that is produced by oral bacteria other than S. mutans. The amounts of biofilm and extracellular DNA were significantly increased by the addition of indole and 4 hydroxyindole (4 HI) An examination with quorum sensing mutants showed that the induction of biofilm formation by indole and 4 HI required a quorum sensing system. These results suggest that this intercellular signaling molecule plays a role in pathogenic biofilm formation.
Use of mobile apps and technologies in child and adolescent mental health: a systematic review
Venue: Evidence Based Mental Health
Year: 2019

This review will aim to critically evaluate the currently available literature concerning the use of online mobile based applications and interventions in the detection, management and maintenance of children and young people's mental health and well being. Study selection and analysis A systematic literature search of six electronic databases was conducted for relevant publications until May 2019, with keywords pertaining to mental health, well being and problems, mobile or internet apps or interventions and age of the study population. The resulting titles were screened and the remaining 92 articles were assessed against the inclusion and exclusion criteria with a total of 4 studies included in the final review.  In general, young people seem to engage very well with this type of tools, and they demonstrate some positive effects in emotional self awareness. There have been some studies about this issue and many of the outcomes were notstatistically significant. However, it is still a sparsely documented area, and more research is needed in order to prove these effects.  Mental health apps directed at young people have the potential to be important assessment, management and treatment tools, therefore creating easier access to health services, helping in the prevention of mental health issues and capacitating to self help in case of need. However, a limited number of studies are currently available, and further assessments should be made in order to determine the outcomes of this type of interventions.
Analysis of zig zag scan based modified feedback convolution algorithm against differential attacks and its application to image encryption
Venue: Applied Intelligence
Year: 2020

In this paper, a novel zig zag scan based feedback convolution algorithm for image encryption against differential attacks is proposed. The two measures Number of Pixel Change Rate (NPCR) and Unified Average Changed Intensity (UACI) are commonly utilized for analyzing the differential attacks. From the study of the existing papers, even though high Number of Pixel Change Rate and Unified Average Changed Intensity values are obtained, a few values lie in the critical range of a level significance which in turn increase the possibility of differential attacks. To overcome differential attacks, two aspects of scanning with different test cases are analyzed and from these analyses, it is concluded that zig zag scan based feedback convolution in forward and reverse direction achieves good Number of Pixel Change Rate and Unified Average Changed Intensity without critical values. Zig zag scan based feedback convolution in forward and reverse direction is enforced for key sequence generation and applied in diffusion process to achieve high level of security. Moreover, plain image related initial seed is also generated to overcome the chosen/known plain text attacks. Both numerical and theoretical analyses are performed to prove that the proposed encryption method is resistant to differential attacks. General security measures are carried out for the proposed method to validate its security level. From the simulations, it is shown that the proposed methodology has good keyspace, high key sensitivity, good randomness, and uniform distribution of cipher image pixels.
Equivalent heat source approach in a 3D transient heat transfer simulation of full penetration high power laser beam welding of thick metal plates
Year: 2018

A three dimensional multi physics numerical model was developed for the calculation of an appropriate equivalent volumetric heat source and the prediction of the transient thermal cycle during and after fusion welding. Thus the modelling process was separated into two studies. First, the stationary process simulation of full penetration keyhole laser beam welding of a 15 mm low alloyed steel thick plate in flat position at a welding speed of 2 m min 1 and a laser power of 18 kW was performed. A fixed keyhole with a right circular cone shape was used to consider the energy absorbed by the workpiece and to calibrate the model. In the calculation of the weld pool geometry and the local temperature field, the effects of phase transition, thermo capillary convection, natural convection and temperature dependent material properties up to evaporation temperature were taken into account. The obtained local temperature field was then used in a subsequent study as an equivalent heat source for the computation of the transient thermal field during the laser welding process and the cooling stage of the part. The system of partial differential equations, describing the stationary heat transfer and the fluid dynamics, were strongly coupled and solved with the commercial finite element software COMSOL Multiphysics 5.0. The energy input in the transient heat transfer simulation was realised by prescription of the nodes temperature. The prescribed nodes reproduced the calculated local temperature field defining the equivalent volumetric heat source. Their translational motion through the part was modelled by a moving mesh approach. An additional remeshing condition and helper lines were used to avoid highly distorted elements. The positions of the elements of the polygonal mesh were calculated with the Laplace's smoothing approach. Good correlation between the numerically calculated and the experimentally observed weld bead shapes and transient temperature distributions was found.