Miracle-dz/UniFAR-FTUs huggingface dataset:
Waveguide Evanescent-Field Microscopy for Label-Free Monitoring of Biological Nanoparticles: Fabrication, Characterization and Application

The recent development of microscopy methods, biological assays and bioanalytical sensors has significantly advanced the understanding of biological systems. Surface-based bioanalytical sensors have in recent years gained increased interest thanks to improvements in sensitivity and simplicity to use. However, most of them, such as quartz crystal microbalance (QCM) and surface plasmon resonance (SPR), provide information based on ensemble averaging of biomolecular interactions. In contrast, with surface-sensitive microscopy methods, biological processes can be resolved down to the level of individual molecular interactions. Total internal reflection fluorescent microscopy is one commonly used surface-sensitive method, reaching sensitivities down to the level of single molecules, but it requires fluorescent labeling of at least one of the interaction partners and is often also hampered by photo bleaching processes. In this thesis, we introduce a new wide-field surface-sensitive microscopy platform, based on a nanofabricated planar optical waveguide design that is capable of label-free evanescent-field microscopy of biological nanoparticles well below 100 nm in diameter. The waveguide generates an evanescent-field at the interface between the core of the waveguide and an aqueous solution, providing a thin sheet of illumination that offers imaging with low background disturbance. The device is presented in two designs, being compatible with either upright or inverted microscopes. The work presented demonstrates how simultaneous monitoring of fluorescence and scattering signals can offer new information about the relation between scattering intensity, refractive index and lipid content of biological nanoparticles, such as exosomes. Further, the microfluidic design allowed not only for convenient liquid handling with dead volumes of a few microliter, it is also showed to aid label-free investigations of the interaction between proteins and individual lipid vesicles, with the latter serving as cell-membrane mimic. With the device also being compatible with formation of fluid supported lipid bilayers, preliminary results suggest that the design will open up a possibility to simultaneously determine the size, scattering intensity and fluorescence emission at the level of individual biological nanoparticles. With this realized, we foresee a broad applicability of the microscopy platform as multidimensional characterization tool for biological nanoparticles and beyond.
Back To RGB: Deep articulated hand pose estimation from a single camera image

In this work, we demonstrate a method called Deep Hand Pose Machine(DHPM) that effectively detects the anatomical joints in the human hand based on single RGB images. Current state-of-the-art methods are able to robustly infer hand poses from RGB-D images. However, the depth map from an infrared camera does not operate well under direct sunlight. Performing hand tracking outdoors using depth sensors results in unreliable depth information and inaccurate poses. For this reason we were motivated to create this method which solely utilizes ordinary RGB image without additional depth information. Our approach adapts the pose machine algorithm, which has been used in the past to detect human body joints. We perform pose machine training on synthetic data to accurately predict the position of the joints in a real hand image.
Two-Stream Multirate Recurrent Neural Network for Video-Based Pedestrian Reidentification

Video-based pedestrian reidentification is an emerging task in video surveillance and is closely related to several real-world applications. Its goal is to match pedestrians across multiple nonoverlapping network cameras. Despite the recent effort, the performance of pedestrian reidentification needs further improvement. Hence, we propose a novel two-stream multirate recurrent neural network for video-based pedestrian reidentification with two inherent advantages: First, capturing the static spatial and temporal information; Second,Author: Figure II is not cited in the text. Please cite it at the appropriate place. dealing with motion speed variance. Given video sequences of pedestrians, we start with extracting spatial and motion features using two different deep neural networks. Then, we explore the feature correlation which results in a regularized fusion network integrating the two aforementioned networks. Considering that pedestrians, sometimes even the same pedestrian, move in different speeds across different camera views, we extend our approach by feeding the two networks into a multirate recurrent network to exploit the temporal correlations. Extensive experiments have been conducted on two real-world video-based pedestrian reidentification benchmarks: iLIDS-VID and PRID 2011 datasets. The experimental results confirm the efficacy of the proposed method. Our code will be released upon acceptance.
In Ovo Administration of CpG ODN Induces Expression of Immune Response Genes in Neonatal Chicken Spleen

Abstract Introduction: Due to their immunostimulatory properties TLR ligands are used prophylactically to protect against a variety of viral and bacterial pathogens in mammals. Knowledge of the molecular and functional aspects of TLRs is essential for a better understanding of the immune system and resistance to diseases in birds. For that reason, this study attempted to determine the impact of TLR21 stimulation by its synthetic ligand (CpG ODN, class B) on the chicken immune system. Material and Methods: Sixty embryonated chicken eggs were randomly allocated into three groups (control and two experimental groups). On day 18 of embryonic development, chickens in one experimental group were administered in ovo a low dose of CpG ODN and the birds of the second experimental group were given a high dose of the ligand. Spleens were collected at 1, 2, 5, and 10 days post-hatching (dph) for analysis of IFN-α, IFN-β, IFN-γ, IL-6, and IL-10 expression using qRT-PCR. Results: Significant differences were observed in mRNA expression levels of all the measured cytokines associated with the modulation and regulation of the immune response at different time points. Conclusion: The obtained data clearly demonstrate that immune response induction takes place after in ovo administration of class B CpG ODN, and that the ligand has the ability to induce cytokine responses in neonatal chicken spleen.
Information-Gathering and Therapeutic Models of Assessment: Complementary Paradigms

The authors reviewed the other articles in the special section and commented on the use of psychological assessment to plan treatment. They call this view of assessment the information-gathering paradigm, because the goal is to collect data that will aid in communication and decision making about clients. This contrasts with the therapeutic model of assessment, in which the major goal is to produce positive change in clients. The authors summarized evidence of the efficacy of assessment as a brief therapy and discussed its possible therapeutic mechanisms. The information-gathering and therapeutic models of assessment are complementary rather than mutually exclusive, and both speak to the utility of assessment. The current crisis in the clinical use of psychological assessment may be due in part to an overemphasis on the information-gathering model.
Short-Term Resveratrol Pretreatment Suppresses Noradrenaline-Induced Contractions in Human Saphenous Vein and Internal Mammary Artery Rings

The aim of the present study was to investigate whether short-term resveratrol pretreatment has a suppressive effect on the contraction to noradrenaline and whether this changes between human saphenous vein (SV) and internal mammary artery (IMA). The effects of endothelium removal and pretreatments with nitric oxide synthase inhibitor (L-NOARG) and cyclooxygenase inhibitor (indomethacin) were studied to explain the mechanism of action of resveratrol. SV and IMA samples were obtained from 38 patients undergoing coronary artery bypass operation. The contractile response-curves for noradrenaline (10-8-10-4 M) were obtained in SV and IMA rings. Pretreatment with resveratrol (10 and 30 mM) for 20 min significantly suppressed the contractions to noradrenaline in both vessel rings with endothelium. L-NOARG pretreatment completely abolished resveratrolinduced suppression on the contractions in SV, but not in IMA. Moreover, resveratrol has also inhibitory effect on the contractions in endothelium denuded rings from IMA. Resveratrol of 30 mM suppressed noradrenaline-induced maximal contractions by 40 % in both SV and IMA rings. This effect of resveratrol was mainly endothelium-dependent and mediated by nitric oxide in SV as different from that of IMA. The pretreatment with resveratrol could be a new method for preparation of grafts and prevention of vasospasm.
Interactive comment on “ Iodine speciation in rain , snow and aerosols and possible transfer oforganically bound iodine species from aerosol to droplet phases ” by B . S . Gilfedder et al .

I think this is a strong contribution to the interesting subject of iodine chemistry in marine aerosols. The authors have made a unique set of measurements, with the clear implication of the importance of organoiodine to the mass balance of aerosol iodine. Their results (along with Baker’s earlier work) challenge some long-held thoughts about the dominance of inorganic iodine in aerosols. I think the authors have done a nice job of placing this study into the context of prior research, and in pointing out directions for future research. I recommend the paper for publication, with consideration of the comments below.
Inhibition ability of probiotic, Lactococcus lactis , against A. hydrophila and study of its immunostimulatory effect in tilapia ( Oreochromis niloticus )

The present study was designed to investigate the inhibition ability of probiotic, Lactococcus lactis RQ516, against A. hydrophila in vitro and its immunostimulatory effect in tilapia, Oreochromis niloticus as growth promoter. Six tanks were used (T-1 and control treated with and without RQ516, respectively) and three replicates per treatment. The inhibition ability assay in vitro showed that the minimum diameter of the inhibition zone ( P P P P Lactococcus lactis RQ516 was beneficial for tilapia in terms of increasing final weight, DWG and the concentrations of serum protein and globulin and enhancing immune responses. International Journal of Engineering, Science and Technology, Vol. 2, No. 7, 2010, pp. 73-80
Molecular Diversity of Alkenal Double Bond Reductases in the Liverwort Marchantia paleacea

Alkenal double bond reductases (DBRs), capable of catalyzing the NADPH-dependent reduction of the α,β-unsaturated double bond, play key roles in the detoxication of alkenal carbonyls. Here, the isolation and characterization of two DBRs encoded by the liverwort species Marchantia paleacea are described. The two DBRs share a relatively low similarity, and phylogenetic analysis indicated that MpMDBRL is more closely related to microbial DBRs than to other plant DBRs, while MpDBR shares common ancestry with typical plant DBRs. Both DBR proteins exhibited hydrogenation ability towards hydroxycinnamyl aldehydes; however, their temperature optimums were strikingly different. MpMDBRL demonstrated slightly weaker catalytic efficiency compared to MpDBR, and the structural models of their active binding sites to the substrate may provide a parsimonious explanation. Furthermore, both DBRs significantly responded to phytohormone treatment. In conclusion, M. paleacea produces two distinct types of functional DBRs, both of which participate in the protection against environmental stress in liverwort. The presence of a microbial type of DBR in a plant is herein reported for the first time.
Climate change and sectors of the surface water cycle in CMIP 5 projections

Results from 10 global climate change models are synthesized to investigate changes in extremes, defined as wettest and driest deciles in precipitation, soil moisture and runoff based on each model’s historical 20th century simulated climatology. Under a moderate warming scenario, regional increases in drought frequency are found with little increase in floods. For more severe warming, both drought and flood become much more prevalent, with nearly the entire globe significantly affected. Soil moisture changes tend toward drying, while runoff trends toward flood. To determine how different sectors of society dependent on various components of the surface water cycle may be affected, changes in monthly means and interannual variability are compared to data sets of crop distribution and river basin boundaries. For precipitation, changes in interannual variability can be important even when there is little change in the long-term mean. Over 20 % of the globe is projected to experience a combination of reduced precipitation and increased variability under severe warming. There are large differences in the vulnerability of different types of crops, depending on their spatial distributions. Increases in soil moisture variability are again found to be a threat even where soil moisture is not projected to decrease. The combination of increased variability and greater annual discharge over many basins portends increased risk of river flooding, although a number of basins are projected to suffer surface water shortages.
Alien honeybees increase pollination risks for range‐restricted plants

Range‐restricted species are of high conservation concern, and the way in which they interact with more widespread species has implications for their persistence. Here, we determine how the specialization of mutualistic interactions varies with respect to the geographic range size of plants and pollinators and assess how they respond to the introduction of the alien honeybee. We also compare network characteristics (connectance, specialization and nestedness) between an invaded low mountain and non‐invaded high mountain network.
Performance Optimization Based on Relay-Aided Mode in Device-To-Device Communication

Once the direct communication conditions are not satisfied between D2D pairs, relay-aided mode may play an important role in enhancing the reliability and reducing the transmit power of D2D communications. In order to obtain the maximum system capacity with a low computation complexity, this paper proposes a novel scheme by considering interference limit, optimal relay selection based on delineated area and optimal link selection based range division. Simulation results reveal that the proposed scheme is capable of substantially improving the system performance and reducing the computational complexity compared with either the existing brute- force technique or the area-division scheme.
An efficient statistical methodology for peptide 3D structure clustering

The analysis of proteins and peptides conformations is of crucial interest to gain insights on their biological functions; it has therefore been an active research topic over the past decades. However, analyzing conformations of small size and highly flexible peptides remains a challenge due to their instability and their large number of different shapes. In this paper, an efficient methodology is proposed to analyze 3D structures of highly flexible elastin-derived peptides and to find out their principal conformations using a clustering algorithm. This methodology is based on a special representation of peptide structures, which has the great advantage to be neither affected by peptides' translations nor rotations, hence, avoiding the use of a complex superposition method. In addition, the proposed approach uses for the first time Kernel PCA to remove outlier structures that are not frequently present and do not resemble any other peptide structures. Outlier removal is very important in this context because, due to the instability of those peptides, a small portion of very different conformations, that seldom occur, can heavily affect the ensuing clustering results. Finally, the proposed approach latest step consists in hierarchical clustering, used as a non-supervised classification method to gather together similar structures. Experimental results, obtained using an existing database, show the relevance and the efficiency of the proposed method.
Exegesis of Digital Text from the History of Economic Thought: A Comparative Exploratory Test

Textual material relevant to the history of economic thought is today readily available in various digitised forms. This raises the possibility of exegesis being undertaken with the aid of software designed for the purpose of textual analysis. This paper provides an exploratory test of Leximancer, a text analytics program that extracts the content of text, or collections of text, in order to quantify and display the conceptual structure of text content in a visually informative way. The relevance of one particular software product – Leximancer – as a tool enhancing textual exegesis undertaken for the history of economic thought is considered. The exploratory test is a comparative analysis of A.C. Pigou’s first chapter in Wealth and Welfare (1912) and the first chapter of The Economics of Welfare (1920).
Anti-inflammatory effects of Labisia pumila (Blume) F. Vill-Naves aqueous extract

This study was carried out to evaluate the anti- inflammatory effects of three concentrations of Labisia pumila(Blume)F. Vill-Naves aqueous leaf extract in rats. The effects of these extracts as anti-inflammatory agents were determined using two experiments namely formalin-induced paw licking and carrageenan-induced paw oedema test. The exposure of inflammation to various treatments resulted in significant differences between treatments in formalin-induced paw licking in rats experiment whereas in phase 2, 50 mg kg-1 of L. pumila extract showed the most significant inhibition of 82.12%, followed by 10 mg kg -1 with 76.00% and 25 mg kg-1 with 57.80%. Similarly, different treatments showed significant effects at p<0.05 in the carrageenan inducing paw oedema experiment. All treatments were able to suppress the oedema formation induced by carrageenan as compared with the control. It is evident that the anti-inflammtory effect of every concentration of L. pumila extract started as early as the first hour of carrageenan injection and showed the maximum inhibition during the fifth hour. Again, 50 mg kg-1 of L. pumila extract was found to be the best treatment that could reduce inflammation with highest inhibition of 64.59% followed by 25 mg kg-1 with 56.99% and 10 mg kg-1 with 5.55%. The result of this study has shown that these extracts of L. pumila can be effective for anti-inflammation purposes which supports and justifies traditional uses of this plant.
Deep actionlet proposals for driver's behavior monitoring

Automated cell phone usage detection systems are a privilege for traffic law enforcement to avoid increasing death toll due to irresponsible drive behavior This paper presents a computer vision based approach to automatically monitor driver's behavior during driving especially focusing on irresponsible behavior like use of mobile phone. Majority of the earlier work is based on the camera system inside the vehicle. Our framework however, is based on traffic monitoring cameras on the road. At first, we learn deep action specific features based on pose and appearance representation and train an SVM, named deep actionlet. We then use action-let activations from input images to get candidate actionlet proposals. Finally, we integrate these proposals into a Faster spectral-RCNN replacing region proposal network. The spectral domain provides a significant speedup with underlying model unchanged. The proposed approach is evaluated on the challenging Strategic Highway Research Program (SHRP2) and internally developed Driver in the Wild dataset. Detailed experimental results show that our approach achieves better performance compared to the state-of-the art approaches.
The Impact of Grid Connected Photovoltaic Generation System to Voltage Rise in Low Voltage Network

Photovoltaic (PV) generation is now growing rapidly throughout the world with most new PV installations are grid-connected small-scale system. From power utility point of view, the main issue and concern related to PV grid-interconnection is voltage rise or over voltage in their network. This paper describes the simulation studies focus on the aspect of PV penetration level in low voltage (LV) networks before violating its voltage limit. Many scenarios for LV networks such as different network configuration and different loading conditions are modeled and analyzed using commercially available power system software to determine the PV penetration level. Total capacity of PV systems that can be accommodated at the connection points of LV network with respect to the loads is determined. Key-Words: Photovoltaic (PV), low voltage (LV), voltage rise, PV penetration
On Secrecy Performance of Relay Assisted Millimeter Wave C-RAN

Millimeter wave (mmWave) and cloud radio access network (C-RAN) are identiﬁed as major components of ﬁfth generation (5G) network architecture. Moreover, relays can be used in mmWave C-RAN to improve the communication coverage and reliability. In this paper, we propose a cooperative transmis- sion scheme and investigate physical layer security performance of a relay assisted mmWave C-RAN. In particular, the proposed scheme enjoys cooperative diversity gains and signiﬁcantly improves the network coverage probability. Furthermore, the ergodic secrecy rate is analyzed by using tools from stochastic geometry, and corresponding lower and upper bounds are presented. Numerical results indicate that directional beamforming in mmWave C- RAN can enhance the secrecy performance, and ergodic secrecy rate can be maximized by deploying relays with an optimal density.
A Meshless Method for Solving the 2D BrusselatorReaction-Diffusion System

: In this paper, the two-dimensional (2D) Brusselator reaction-diffusion system is simulated numerically by the method of lines. The proposed method is implemented as a meshless method based on spatial trial functions in the reproducing kernel Hilbert spaces. For efﬁciency and stability reasons, we use the Newton basis introduced recently by Müller and Schaback. The method is shown to work in all interesting situations described by Hopf bifurcations and Turing patterns
Vector Magnetometer Using Rb Vapor

This project demonstrates an optical method for measuring the strength and direction of a magnetic field using electromagnetically induced transparency (EIT) in rubidium vapor. In rubidium atoms, the Zeeman effect causes atomic states to shift when an external magnetic field is applied. The magnitude of these shifts, and consequently the strength of the magnetic field, can be measured by recording electromagnetically induced transparency resonances with tuned laser fields. Furthermore, since the atom's interaction with the laser field is dependent on the direction of the magnetic field and the laser polarization, we are able to determine the direction as well as the strength of the magnetic field by analyzing relative intensities of EIT resonances. With a feasible precision down to 10 picoTesla and the possibility of complete field mapping, this magnetometer can be useful for medical, geophysical, and materials testing applications.
Replicating a Trading Strategy by Means of LSTM for Financial Industry Applications

This paper investigates the possibility of learning a trading rule looking at the relationship between market indicators and decisions undertaken regarding entering or quitting a position. As means to achieve this objective, we employ a long short-term memory machine, due its capability to relate past and recent events. Our solution is a first step in the direction of building a model-free robot, based on deep learning, able to identify the logic that links the market mood given by technical indicators to the undertaken investment decisions. Although preliminary, experimental results show that the proposed solution is viable and promising.