gebhart/patrepeval huggingface dataset:
Fooling PRNU-Based Detectors Through Convolutional Neural Networks (2018)

In the last few years, forensic researchers have developed a wide set of techniques to blindly attribute an image to the device used to shoot it. Among these techniques, those based on photo response non uniformity (PRNU) have shown incredibly accurate results, thus they are often considered as a reference baseline solution. The rationale behind these techniques is that each camera sensor leaves on acquired images a characteristic noise pattern. This pattern can be estimated and uniquely mapped to a specific acquisition device through a cross-correlation test. In this paper, we study the possibility of leveraging recent findings in the deep learning field to attack PRNU-based detectors. Specifically, we focus on the possibility of editing an image through convolutional neural networks in a visually imperceptible way, still hindering PRNU noise estimation. Results show that performing such an attack is possible, even though an informed forensic analyst can reduce its impact through a smart test.
77 GHz reconfigurable reflectarray with nematic liquid crystal (2007)

A 77 GHz liquid crystal microstrip reflectarray with beam reconfiguration capability in one dimension is presented. The free-standing reflector (without feed) has been characterized with respect to its reflection phase and magnitude. While it is possible to tune the reflection phase through almost 300°, the associated reflection losses are still quite high. Nevertheless the pattern measurements of the reflectarray showed distinct beam collimation towards different angles when appropriate DC control voltages are applied. (5 pages)
Intelligent Agent-Based e-Learning System for Adaptive Learning (2011)

Adaptive learning approaches support learners to achieve the intended learning outcomes through a personalized way. Previous studies mistakenly treat adaptive e-Learning as personalizing the presentation style of the learning materials, which is not completely correct. The main idea of adaptive learning is to personalize the earning content in a way that can cope with individual differences in aptitude. In this study, an adaptive learning model is designed based on the Aptitude-Treatment Interaction theory and Constructive Alignment Model. The model aims at improving students’ learning outcomes through enhancing their intrinsic motivation to learn. This model is operationalized with a multi-agent framework and is validated under a controlled laboratory setting. The result is quite promising. The individual differences of students, especially in the experimental group, have been narrowed significantly. Students who have difficulties in learning show significant improvement after the test. However, the longitudinal effect of this model is not tested in this study and will be studied in the future.
Modeling, History Matching, Forecasting and Analysis of Shale Reservoirs Performance Using Artificial Intelligence (2011)

Abstract Producing hydrocarbon from Shale plays has attracted much attention in the recent years. Advances in horizontal drilling and multi-stage hydraulic fracturing have made shale reservoirs a focal point for many operators. Our understanding of the complexity of the flow mechanism in the natural fracture and its coupling with the matrix and the induced fracture, impact of geomechanical parameters and optimum design of hydraulic fractures has not necessarily kept up with our interest in these prolific and hydrocarbon rich formations. In this paper we discuss using a new and completely different approach to modeling, history matching, forecasting and analyzing oil and gas production in shale reservoirs. In this new approach instead of imposing our understanding of the flow mechanism and the production process on the reservoir model, we allow the production history, well log, and hydraulic fracturing data to force their will on our model and determine its behavior. In other words, by carefully listening to the data from wells and the reservoir we developed a data driven model and history match the production process from Shale reservoirs. The history matched model is used to forecast future production from the field and to assist in planning field development strategies. We use the last several months of production history as blind data to validate the model that is developed. This is a unique and innovative use of pattern recognition capabilities of artificial intelligence and data mining as a workflow to build a full field reservoir model for forecasting and analysis of oil and gas production from shale formations. Examples of three case studies in Lower Huron and New Albany shale formations (gas producing) and Bakken Shale (oil producing) is presented in this paper.
Identifying Illicit Accounts in Large Scale E-payment Networks -- A Graph Representation Learning Approach (2019)

Rapid and massive adoption of mobile/ online payment services has brought new challenges to the service providers as well as regulators in safeguarding the proper uses such services/ systems. In this paper, we leverage recent advances in deep-neural-network-based graph representation learning to detect abnormal/ suspicious financial transactions in real-world e-payment networks. In particular, we propose an end-to-end Graph Convolution Network (GCN)-based algorithm to learn the embeddings of the nodes and edges of a large-scale time-evolving graph. In the context of e-payment transaction graphs, the resultant node and edge embeddings can effectively characterize the user-background as well as the financial transaction patterns of individual account holders. As such, we can use the graph embedding results to drive downstream graph mining tasks such as node-classification to identify illicit accounts within the payment networks. Our algorithm outperforms state-of-the-art schemes including GraphSAGE, Gradient Boosting Decision Tree and Random Forest to deliver considerably higher accuracy (94.62% and 86.98% respectively) in classifying user accounts within 2 practical e-payment transaction datasets. It also achieves outstanding accuracy (97.43%) for another biomedical entity identification task while using only edge-related information.
Role of Salt-Induced Kinase 1 in Androgen Neuroprotection against Cerebral Ischemia (2010)

Androgens within physiological ranges protect castrated male mice from cerebral ischemic injury. Yet, underlying mechanisms are unclear. Here, we report that, after middle cerebral artery occlusion (MCAO), salt-induced kinase 1 (SIK1) was induced by a potent androgen-dihydrotestosterone (DHT) at protective doses. To investigate whether SIK1 contributes to DHT neuroprotection after cerebral ischemia, we constructed lentivirus-expressing small interference RNA (siRNA) against SIK1. The SIK1 knockdown by siRNA exacerbated oxygen-glucose deprivation (OGD)-induced cell death in primary cortical neurons, suggesting that SIK1 is an endogenous neuroprotective gene against cerebral ischemia. Furthermore, lentivirus-mediated SIK1 knockdown increased both cortical and striatal infarct sizes in castrated mice treated with a protective dose of DHT. Earlier studies show that SIK1 inhibits histone deacetylase (HDAC) activities by acting as a class IIa HDAC kinase. We observed that SIK1 knockdown decreased histone H3 acetylation in primary neurons. The SIK1 siRNA also exacerbated OGD-induced neuronal death in the presence of trichostatin A (TSA), an HDAC inhibitor, and decreased histone H3 acetylation at 4 hours reoxygenation in TSA-treated neurons. Finally, we showed that DHT at protective doses prevented ischemia-induced histone deacetylation after MCAO. Our finding suggests that SIK1 contributes to neuroprotection by androgens within physiological ranges by inhibiting histone deacetylation.
Optimization of Hybrid Filters for Distributed Harmonic and Reactive Compensation (2006)

An energy-related definition of reactive power is introduced first, which is conservative in every network and applies even under non-sinusoidal conditions. Following, a theoretical background to analyze and control a system of distributed harmonic and reactive compensators is provided, which is based on a suitable line current decomposition. Application examples related to hybrid power filters and distributed compensators are finally discussed
Thermoelectrics with Distributed Transport Properties for Higher SWaP-C Electronic Deep Cooling and Thermal Management (2022)

Thermoelectric (TE) devices (i.e., solid-state heat pumps with no moving parts or refrigerants) can be highly reliable, low in cost, compact and extremely light weight, and provide vibration-free operation. Conventional TE (CTE) devices have limited cooling capacity and, in some cases, cannot reach the deep cooling temperatures required to operate sensitive electronic components. Recently developed Distributed Transport Properties (DTP) TE technology has the prospect of achieving lower operating temperatures and significantly-improved efficiency and heat pumping capacity. The combined benefits can enable practical, inexpensive, light-weight, and highly-reliable cooling for LiDAR, CMOS, and other temperature-sensitive electronic systems. We discuss experimental laboratory measurements and modeling results for single-stage TE devices operating at a maximum temperature differential that exceeds the state-of-the-art TE modules by more than 7% and has greater than 50% higher heat pumping capacity and/or greater than 35% higher coefficient of performance (COP) under typical design operating conditions. We show that DTP TE devices require less TE material compared to conventional TE devices and have superior performance at both nominal and off-nominal operating conditions. Through further optimization of transport property distribution within the TE materials, we describe a path to achieve a 35% gain in the single-stage temperature differential and increases in COP and cooling power of greater than 40% and 100%, respectively, at high temperature differentials.
Molecular taxonomy of Magnaporthe and Pyricularia species : DP-4 (2013)

Magnaporthe species cause serious diseases on grasses. Magnaporthe oryzae (previously named Pyricularia oryzae by Cavara in 1891, Pyricularia grisea and Magnaporthe grisea by Rossman in 1990) is responsible for rice blast disease and foliar diseases of wheat, barley, Panicum, Eleusine and Setaria. Magnaporthe grisea is responsible for foliar diseases of Digitaria. Magnaporthe poae causes summer patch of turf grass. The asexual genus Pyricularia encompasses species isolated from various monocots that produce pyriform, tri-cellular conidia from conidiophores. Pyricularia higginsii was isolated from infected Cyperus, while P. zingiberi was isolated from ginger, P. penniseti from Pennisetum, P. zizaniicola from Zizania, P. juncicola from Juncus and P. commelinicola from Commelina. Here we present the phylogenetic relationships among isolates from a wide range of Magnaporthe/Pyricularia species based on partial DNA sequences of multiple genes including LSU, ITS, RPB1, actin and calmodulin. Our extensive analysis reveals a large diversity within the genus Pyricularia. Almost all Pyricularia species belong to a clade that includes all Magnaporthe oryzae/M. grisea isolates tested. This clade is clearly distinct from Gaeumannomyces/Magnaporthiopsis clades for all the sequences tested. A few Pyricularia species (e.g. P. parasitica, P. lauri) are unrelated to the Magnaporthaceae. This strongly suggests that the conidium morphology defining this genus is polyphyletic and cannot be used as taxonomical criterion without phylogenetic data. Magnaporthe oryzae/M. grisea isolates cluster in numerous related clades, one of which corresponds to M. oryzae. This clade includes isolates from rice (specific to this clade), wheat (specific), Setaria (specific) and Eleusine (specific) as well as isolates from other plants found as hosts also represented in other clades such as Echinocloa, Cenchrus or Lolium. Another clade corresponds to M. grisea and consists of isolates from Digitaria (specific to this clade). In addition, we identified four clades that could correspond to novel species, two of which were already described as distinct clades in previous phylogenetic analyses of this genus. These novel species are more related to M. oryzae/M. grisea clades than Pyricularia species clades. A re-evaluation of generic and species concepts within the Magnaporthe/Pyricularia clade is suggested and potential novel names will be proposed for discussion. (Texte intégral)
<title>High-yield microfabrication process for biomimetic artificial haircell sensors</title> (2002)

We have developed artificial haircell sensors based on an improved plastic deformation magnetic assembly (PDMA) method. The PDMA method is uniquely capable of realizing 3D microstructures in an efficient, IC-compatible manner. We have improved the design of the PDMA structure to significantly increase the yield by eliminating stress concentration. The robustness of the fabricated devices is enhanced using conformal Parylene deposition. The PDMA process uses magnetic force to bend surface micromachiend cantilever beams. If the bending is significant, the beams would enter plastic deformation regime and maintains permanently bent position even after the magnetic field is removed. Previously, the PDMA process is associated with appreciable yield loss during het magnetic assembly. The failure mechanisms is believed to be stress concentration at sharp corners defined by edges of sacrificial layers. In the new design, a structure enhancement feature is added to the surface micromachiend assembly and hence eliminating any sharp features. Haircells sensors are modular sensory units widely found in the biological world. Haircells are responsible for hearing, flow sensing, and for balancing/equilibrium. We are developing artificial haircell sensors using advanced micromachining technology. The artificial haircell sensors have similar physical scale compared with biological ones.
An Orange-Emitting, Long-Persistent Phosphor, Ca2Si5N8:Eu,Tm (2009)

A new orange-emitting, long-persistent phosphor, Ca2Si5N8:Eu2+,Tm3+, was developed. Long afterglow results from electron traps formed by Tm3+ at Ca2+ site. Origin of two main thermoluminescence (TL) glow peaks at 220K and 350K is discussed based on their dependence on Eu or Tm concentration and Ca/Si atomic ratio. Enhancement of TL is observed by excitation in Eu2+ 4f-5d transition at room temperature followed by the fundamental absorption of the host at low temperature.
Supplementary Figure 2 from Epigenetic Inactivation of a Cluster of Genes Flanking <i>MLH1</i> in Microsatellite-Unstable Colorectal Cancer (2023)

Supplementary Figure 2 from Epigenetic Inactivation of a Cluster of Genes Flanking &lt;i&gt;MLH1&lt;/i&gt; in Microsatellite-Unstable Colorectal Cancer
Interaction of convective flow generated by human body with room ventilation flow: impact on transport of pollution to the breathing zone (2014)

This study aims to investigate the interaction between the human convective boundary layer (CBL) and uniform airflow from two directions and with different velocities. The study has two objectives: first, to characterize the velocity field in the breathing zone of a thermal manikin under its interaction with opposing flow from above and assisting flow from below; and secondly, implication of such a flow interaction on the particle transport from the feet to the breathing zone is examined. The results reveal that the human body heat transports the pollution to the breathing zone and increases concentration by factor of 5.5. Downward flow of 0.175 m/s does not change airflow patterns and pollutant concentration in the breathing zone, while the velocity of 0.425 m/s offsets the thermal plume and minimizes the concentration. Since the downward flow at 0.30 m/s collides with the CBL at the forehead level, it prolongs particle dwell time and consequently, increases the concentration in the breathing zone by 106%. Adding the assisting flow dilutes the pollution and reduces the concentration compared to case of a pure CBL. Findings that the assisting flow of 0.30 m/s and above reduces the velocity in the breathing zone due to the blocking effect of the chair suggest that furniture should be carefully considered in numerical results predictions and optimal air distribution.
The catalase-peroxidase of Synechococcus PCC 7942: purification, nucleotide sequence analysis and expression in Escherichia coli (1996)

Synechococcus PCC 7942, a cyanobacterium, possesses catalaseperoxidase as the sole hydrogen peroxide-scavenging system. The enzyme has been purified to electrophoretic homogenenity from the cells. The native enzyme had a molecular mass of 150 kDa and was composed of two identical subunits of molecular mass 79 kDa. The apparent Km value of the catalase activity for H2O2 was 4.2 +/- 0.27 mM and the kcat value was 2.6 x 10(4) s-1. The enzyme contained high catalase activity and an appreciable peroxidase activity with o-dianisidine and pyrogallol. The catalase activity was not inhibited by 3-amino-1,2,4-triazole but by KCN and NaN3 (apparent Ki values 19.3 +/- 0.84 and 20.2 +/- 0.95 microM respectively). The enzyme showed an absorption spectrum of typical protohaem and contained one protohaem molecule per dimer. The gene encoding catalase-peroxidase was cloned from the chromosomal DNA of Synechococcus PCC 7942. A 2160 bp open reading frame (ORF), coding a catalase-peroxidase of 720 amino acid residues (approx. 79.9 kDa), was observed. The deduced amino acid sequence coincided with that of the N-terminus of the purified enzyme and showed a remarkable similarity to those of a family of catalase-peroxidases of prokaryotic cells. Escherichia coli BL21 (DE3)plysS, harbouring a recombinant plasmid containing the catalase-peroxidase gene, produced a large amount of proteins that co-migrated on SDS/PAGE with the native enzyme. The recombinant enzyme showed the same ratio of catalase activity to peroxidase activity with o-dianisidine and the same Km for H2O2 as the native enzyme.
Multicomponent determination of flavour enhancers in food preparations by partial least squares and principal component regression modelling of spectrophotometric data (1993)

Three multivariate calibration methods, partial least squares (PLS-1 and PLS-2) and principal component regression (PCR), were applied to the simultaneous determination of three flavour enhancers (inosine 5'-monophosphate, guanosine 5'-monophosphate and monosodium glutamate), in mixtures by ultraviolet/visible absorption spectrophotometry. The absorption and first- and second-derivative absorption spectra of the ternary mixtures were used to perform the optimization of the calibration matrices by the PLS and PCR methods. The results obtained by the application of the different chemometric approaches are discussed and compared. No significant advantages were found for the prior differentiation step. The proposed method was applied satisfactorily to the determination of inosine 5'-monophosphate and guanosine 5'-monophosphate in several food preparations, in the presence of monosodium glutamate.
A model to assess survival mechanisms of parasites in a genetically defined host system (1986)

We examined a host system (peromyscus maniculatus) in which a single autosomal gene controls susceptibility or resistance to infection by the cestode parasite Hymenolepis citelli. Parasite deaths of both primary and secondary (challenge) infections were examined, using a probabilistic model, to see if deaths were random and uncorrelated within each genotype. Within susceptible hosts, post-patent survival of primary worms was not random and heterogeneity was due to among-host effects rather than parasite-age effects, suggesting a second genetic or immunological process. Secondary infections in susceptible hosts appear to be lost randomly, independent of primary infection age or burden. The loss rate is similar to that for primary worms. The lack of correlation or alteration in (susceptible) host response to primary and secondary infections suggests that the latter are eliminated by a process that differs from that acting on primary worms. In resistant hosts, parasite survival rates suggest that the immunological process elicited by the primary infection also acts to eliminate the secondary infection more rapidly. Suggestions are made for improving experimental methods when dealing with mixed genotype populations. Experiments should permit direct estimation of genotype frequency and of parasite death rates within each genotype. This separation of host type is particularly important when studying correlation of successive worm burdens since any host or treatment mixture (genotype, age, sex, size or infection dose) may induce correlations that could be mistakenly interpreted.
Output-relevant fault reconstruction based on total PLS (2010)

Process monitoring is critical for efficient operations of industrial processes. When a fault occurs, relevant measured data are affected by the fault, which leads to poor quality of products consequently. This paper proposes a new output-relevant index for detecting faults that affect the output or quality, and studies the fault detectability based on total projection to latent structures (T-PLS). Given a fault subspace, fault-free data are reconstructed and the fault magnitude is estimated based on the new index. A simulation example is used to show the effectiveness of the proposed methods.
Employing Unmanned Aerial Vehicles for Improving Handoff Using Cooperative Game Theory (2020)

Heterogeneous wireless networks that are used for seamless mobility are expected to face prominent problems in future fifth generation (5G) cellular networks. Due to their proper flexibility and adaptable preparation, remote-controlled unmanned aerial vehicles (UAVs) could assist heterogeneous wireless communication. However, the key challenges of current UAV-assisted communications consist in having appropriate accessibility over wireless networks via mobile devices with an acceptable Quality of Service grounded on the users’ preferences. To this end, we propose a novel method based on cooperative game theory to select the best UAV during handover process and optimize handover among UAVs by decreasing the i) end-to-end delay, ii) handover latency, and iii) signaling overheads. Moreover, the standard design of software-defined network with media-independent handover is used as forwarding switches in order to obtain seamless mobility. Numerical results derived from the real data are provided to illustrate the effectiveness of the proposed approach in terms of number of handovers, cost, and delay.
Inhibition of Induced Lymphocyte Proliferation by Lipid and Protein Components of the Syncytiotrophoblast Plasma Membrane (1995)

These results are discussed generally in the context of the immunoregulatory role of membrane lipids and proteins and in relation to the local properties of syncytiotrophoblast plasma membrane components in fetal graft tolerance.
Cover Image (2022)

The cover image is based on the Invited Review Small particles with large impact: Insights into the unresolved roles of innate immunity in extracellular vesicle-mediated cardiovascular calcification by Mandy E Turner et al., https://doi.org/10.1111/imr.13134