Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of selected trade classification algorithms on the warsaw stock exchange

Empirical equity market microstructure research often requires knowledge about tradesides. It is important to recognize the side that initiates the transaction and to distinguish between the so called buyer- and seller-initiated trades. Unfortunately, most data sets do not identifythe trade direction. Therefore, researchers rely on indirect trade classification rules to infer trade sides. The aim of this paper is to implement and compare four trade classification algorithms on the Warsaw Stock Exchange (WSE). The high-frequency data for the selected WSE-listed companies covers the period from January 3, 2005 to June 30, 2015. To check the robustness of empirical results to the choice of sample, three adjacent sub-periods of equal size: the pre-crisis, crisis, and post-crisis period are analysed. The Global Financial Crisis on the WSE is formally established as the period June 2007-February 2009.
Indirect Adaptive learning of Acceleration feedback control for Chained Multiple Mass-Spring-Damper Systems

An indirect iterative learning algorithm has shown to be able to update the parameters of an acceleration feedback controller for flexible manipulators. The fine estimation of the masses of a chain of mass-spring-dampers units allows the simultaneous tuning of both the feedback controller and the trajectory generation. This algorithm has been validated on an industrial robot arm.
Can a deep-rooted spring crop recover winter-deposited urine nitrogen ?

ISSN 2463-2872 (Print) ISSN 2463-2880 (Online) Abstract Grazing a winter forage crop can result in a substantial increase in soil nitrogen (N) from urine deposition, with a significant proportion leached below 30 cm during winter. If a follow-on crop can be used to recover this soil N before the following drainage season, N leaching risk could be reduced. We tested if faster growing, or deeper-rooted, spring-sown crops would be more effective at recovering winter-deposited N than ryegrass based pasture. Urea-N (800 kg N/ha) was applied in June to simulate a dairy cow urine patch and was subsequently leached down the soil profile. In the spring, the plots were sown with ryegrass, chicory and clover, or barley and harvested manually. The following autumn, the amount of N in the 60–90 cm depth (70 kg N/ha) was significantly less (P<0.05) under chicory and clover than under either barley (104 kg N/ha) or ryegrass (107 kg N/ha), suggesting that chicory was able to access the deep N pool. These data, and earlier measurements, provide evidence that chicory is a viable strategy for N recovery after winter grazing.
Twitter Content Eliciting User Engagement: A Case Study on Australian Organisations

Social media has become an important communication platform for all kinds of organisations, ranging from government departments to companies. When using social media, organisations are often keen to maximise engagements from their target audiences, that is, create posts to which their audience will react by, for example, replying, retweeting or liking. In this paper, we investigate the factors that characterise the posts with which an audience engages. While other work has looked at such factors for Twitter posts at large, we account for the effect of the organisation type. We find that the type of organisation (e.g., financial vs. telecommunications) has an impact on the characteristics of the posts associated with audience engagement. This is important as it can provide guidance to organisations on content creation strategies to maximise engagement.
Induction of Adipophilin-Specific Cytotoxic T Lymphocytes Using a Novel HLA-A2-Binding Peptide That Mediates Tumor Cell Lysis

Identification of tumor-associated antigens and advances in tumor immunology resulted in the development of vaccination strategies to treat patients with malignant diseases. Using a novel approach that combines DNA chip analysis of tumor samples with isolation of peptides on the surface of tumor cells, a HLA-A*0201-binding peptide derived from the adipophilin protein was identified. Adipophilin is involved in lipid storage and was thought to be expressed only in adipocytes, but it can be found in other cell types such as macrophages or tumor cells. In the present study, we analyzed the possible use of this peptide as a T-cell epitope presented by malignant cells. To accomplish this, we induced CTL responses using this HLA-A*0201-binding peptide. The in vitro-induced CTLs efficiently lysed cells pulsed with the adipophilin peptide and HLA-matched tumor cell lines in an antigen-specific and HLA-restricted manner. Finally, the induced CTLs recognized autologous dendritic cells (DCs) pulsed with the antigenic peptide or transfected with tumor RNA purified from an adipophilin-expressing tumor cell line. To further analyze the possible use of this peptide in immunotherapies of human malignancies, we induced adipophilin-specific CTLs using peripheral blood mononuclear cells and DCs from HLA-A*0201-positive patients with chronic lymphatic leukemia and plasma cell leukemia. The in vitro-generated CTLs recognized autologous chronic lymphatic leukemia cells and malignant plasma cells, whereas they spared nonmalignant resting or activated B and T lymphocytes, monocytes, or DCs. Our results demonstrate that this peptide might represent an interesting candidate for the development of cancer vaccines designed to target adipophilin-derived epitopes in a wide range of malignancies.
Dynamic sensor activation for maximizing network lifetime under coverage constraint

Wireless sensor networks consist of a large number of sensors equipped with limited energy and processing capabilities. They are deployed in a field to measure physical variables or detect events. In critical surveillance applications, sensors are used to monitor a geographical area and usually a full, or high, area coverage is required as a Quality-of-Service (QoS) parameter. In dense networks, sensors detection ranges usually overlap. Therefore, only a covering subset of sensors can be turned on while other sensors are put in a very low-power Sleep state. In this paper, we address the problem of maximizing the sensor network lifetime under area coverage constraint. For that, we propose a mechanism that dynamically activates an optimal covering subset of sensors, based on residual energies. We first model this problem as an Integer Linear Programming (ILP) problem that we resolve using CPLEX. Then, we propose a greedy heuristic to tackle the exponentially-increasing processing times of the exact solution. We show that the proposed heuristic provides for acceptable solutions while having a polynomial O(N2) complexity, suitable for large-scale networks.
Image-based catheter tip tracking during cardiac ablation therapy

Image-based catheter tip tracking has the potential to support electro-physiological interventions by additional information such as the three-dimensional position and orientation of the catheters. However, curve deformation algorithms commonly used to reconstruct elongated objects from biplane X-ray fluoroscopy images do not guarantee a correct detection of the tip position. The proposed approach combines a curve deformation algorithm and a biplane template matching technique which is based on virtual reconstructions of the catheter tip projection. It allows for an accurate and robust threedimensional tracking of the catheter tip and orientation with a mean position error of 0.80±0.61 mm and a mean tip distance of 0.72±0.52 mm for 94 % of all frames. This is demonstrated on patient data sets by a comparison to previously published approaches.
MOBINET: Mobility management across different wireless sensor networks

Although mobility management within a network of wireless sensors is a relatively new subject, we envision that a mobile sensor will move through different networks. However, it is very likely that the routing protocol supported in a visited network is different from the one supported by the mobile sensor. In a convergecast communication model, it would suffice for mobile sensors to broadcast its messages into the visited network to have them forwarded to the sink. Though, this can lead to duplication of messages and therefore increase the network traffic in the visited network. In this article, we propose Mobinet whose objective is to enable mobile sensors to detect surrounding sensors in the visited network through passive listening in order to select one of them to transmit messages. We particularly focus on the energy consumption of the mobile sensors and consequently introduce various listening processes to limit the extra energy consumption resulting from the detection of surrounding sensors. Mobinet has been evaluated by simulation. Simulation results show the benefits of Mobinet in terms of message delivery and a lower energy consumption through the listening processes. They also highlight guidelines for future research.
Blotch Detection Based on Texture Matching and Adaptive Multi-threshold

Blotch is a typical artifact in old films and the detection of them is an important step in film restoration. The existing simplified rank-ordered difference detector achieves higher detection rates by reducing the value of threshold. However, the corresponding higher number of false alarms is undesirable. To maximize the ratio between correct detections and false alarms, this paper proposes an improved blotch detector based on adaptive multi- threshold. According to different objects of blotches, the proposed detector can achieve the most appropriate threshold by convergence confinement. Meanwhile, texture matching is introduced to avoid the possible deviation caused by motion vector estimation in the regions with blotches. Performance evaluation is taken to the image sequences with both real blotches and artificially corrupted ones. The experimental results indicate higher correct detection rates and fewer false alarms simultaneously.
COMPUTATIONAL SIMULATION OF MOLTEN TITANIUM-ALUMINIUM METAL AND ALLOYS

Mintek has produced 35-40% Ti-Al alloys in DC Arc Furnace campaigns, however, process difficulties encountered appear related to poor understanding of the alloys' physical properties. Making measurements at around 1500°C is often impractical or expensive Atomistic Computational Modelling (Embedded Atom Method, EAM) is ideal for studying alloys, leading to process improvements (efficiency/reducing environmental impact). Physical properties predicted include density, enthalpy, thermal expansion and heat capacity. EAM showed Ti-rich alloys to be the densest, most stable and highest melting – agreeing with experimental findings of furnace campaigns. Furthermore, modelling suggests 1859% Ti-Al alloys have stronger amorphous propensities than other Ti-Al alloys.
The Role of Interface Domain Interactions on Thermal Stability of DNA polymerase I ITB-1

Temperature-induced unfolding of Klenow-like DNA Pol I ITB-1 was investigated by molecular dynamic simulation, focusing on the key factors that stabilizing the protein. The result showed that the protein unfolded initially by disruptions of the interface between of 5' 3'polymerase and 3' 5' exonuclease domains. Several amino acid residues, Lys374-Glu489 and Lys381-Glu487, form salt bridges at the interface domain and played an important role in the contact between the two domains. These interactions were examined through in silico mutation by comparing the free-energy solvation changes between the wild type and the mutants. The disruption of salt bridges by replacing Glu to Gln at position 487 and 489 caused positive value of ��G solv, suggesting that the proteins were more unstable. While the substitution of Glu to Asp at position 487 and 489 preserved the electrostatic interaction. The last two mutants showed negative value of ��G solv, suggesting that the proteins were more stable. All the data suggested that the salt bridges between Lys374-Glu489 and Lys381-Glu487 have an essential role in maintaining the stability of the interface domain of DNA Pol I ITB-1, and thus, the whole structure of the protein.
Detecting early response to therapy in liver cancer treatment : 3 D metastases segmentation using graph-cuts with a modified prior

Accurate 3D liver metastasis extraction is one of the most important steps in treatment planning for patients with advanced colorectal cancer. In this paper we present a semi-automatic segmentation algorithm based on graph cuts theory with a prior which uses both intensity values and local phase information. The segmentation method is tested on images from three patients and the new results are compared to manual segmentations and previously proposed methods. A Dice coefficient accuracy of 83-92 % is achieved. Advantages of this semi-automated method over existing RECIST estimations include non-subjective volume assessment over time for patients undergoing treatment and minimal user interaction.
Designing accelerated ageing experiments to study silk deterioration in historic houses

Abstract An accelerated ageing methodology to study silk deterioration is presented. This draws on approaches used in paper and photographic conservation, although the references are not widely available within conservation. The experiments were designed based on the English Heritage silk collection and its display environment. The selection of different light and humidity conditions for ageing will be discussed, including the experimental parameters and equipment. Details on how the ageing time was related to an equivalent display time will be demonstrated. Some of the key observations and problems which occurred during the project will also be outlined. Some of the advantages and disadvantages of using accelerated ageing experiments to study deterioration reactions will be reported.
Hopf bifurcation analysis in a neutral predator–prey model with age structure in prey

We show a detailed study on the dynamics of a neutral delay differential population model with age structure in the prey species. By selecting the mature delay as a bifurcation parameter, we obtain the stability and Hopf bifurcations of the coexistence equilibrium. Moreover, by computing the normal form on the center manifold, we give the formulas determining the stability of periodic solutions and the direction of Hopf bifurcation. Finally, we give some numerical simulations to support and strengthen the theoretical results.
Face De-identification with perfect privacy protection

The rising concern for privacy protection and the associated legal and social responsibilities have led to extensive research into the field of face de-identification over the last decade. To date, the most successful algorithms developed for face de-identification are those based on the k-Same de-identification, which guarantee a recognition rate lower than 1/k. However, the current k-Same solutions such as k-Same-Eigen and k-Same-M all rely on a decent value of k to deliver a good privacy protection. This paper proposes a departure from a fundamental aspect shared by the current k-Same solutions and thereby introduces a new member to the family which achieves perfect privacy protection for any original face regardless of the value of k.
Author's response to reviews Title: Inflammation gene variants and susceptibility to albuminuria in the U.S. population: analysis in the Third National Health and Nutrition Examination Survey (NHANES III), 1991-1994 Authors:

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Hashing Spatial Content over Peer-to-Peer Networks

The Internet has become the common medium for content distribution. Searching content using keywords is well-known. But there are many shortcomings to it. Users cannot search within the content and on many of the attributes of the content, i.e., other than its name. Content is also becoming increasingly decentralized. New mechanisms allowing access to complex distributed content is needed. We introduce a hashing-based method for accessing complex content over large dynamic networks such as peer-to-peer networks, which uses distributed hash tables in a novel way. In particular, we are interested in spatial content that is becoming popular in databases. Our method is scalable, addressing the needs of todays networks.
The effect of nonrecurring alcohol administration on pain perception in humans: a systematic review

Purpose Alcohol is believed to have pain-dampening effects and is often used as self-medication by persons with pain problems; however, experimental evidence confirming this effect is scarce. We conducted a systematic review of experimental studies on the effects of nonrecurring alcohol administration on pain perception in healthy human subjects and the underlying mechanisms. Method Three databases (PubMed, PsycINFO, and Web of Science) were searched for relevant studies using a predefined algorithm. In a next step, irrelevant articles were excluded by screening titles and abstracts. Finally, articles were checked regarding a set of methodological criteria; only publications meeting these criteria were selected for this review. A total of 14 experimental studies were identified. Results Overall, most of the studies were able to show a pain-dampening effect of alcohol. However, many of them had methodological shortcomings (eg, lack of placebo control, insufficient blinding, or very small sample sizes). In addition, comparability is limited due to considerable variations in alcohol administration and pain measurement. More importantly, potential mechanisms of action and moderating variables have scarcely been investigated. Conclusion Despite the frequent use of alcohol as self-medication by persons with pain problems, there are to date only a few experimental investigations of alcohol effects on pain perceptions. The results of these studies suggest that alcohol does in fact have pain-dampening effects. However, the mechanisms implicated in these effects are still unknown, and experimental research has been limited to pain-free subjects. Future research should provide more knowledge about alcohol effects on pain, especially in chronic pain patients.
Combining Hadamard matrix, discrete wavelet transform and DCT features based on PCA and KNN for image retrieval

Image retrieval is one of the most applicable image processing techniques which have been used extensively. Feature extraction is one of the most important procedures used for interpretation and indexing images in content-based image retrieval (CBIR) systems. Reducing dimension of feature vector is one of challenges in CBIR systems. There are many proposed methods to overcome these challenges. However, the rate of image retrieval and speed of retrieval is still an interesting field of researches. In this paper we propose a new method based on combination of Hadamard matrix, discrete wavelet transform (HDWT2) and discrete cosine transform (DCT) and we used principal component analysis (PCA) to reduce dimension of feature vector and K-nearest neighbor (KNN) for similarity measurement. The precision at percent recall and ANR are considered as metrics to evaluate and compare different methods. Obtaining results show that the proposed method provides better performance in comparison with other methods.
Optimum Goodput-Oriented Power Allocation Policy for BIC-OFDM Packet Transmissions

In this contribution we study the optimal power allocation scheme for a coded multicarrier transmission. Specifically, we focus on a bit interleaved coded modulation (BICM) packet transmission implemented with orthogonal frequency division multiplexing (OFDM) and in the presence of automatic repeat request (ARQ) protocol. Based on a simple lower-bound of the rate of information bits received without any error, the so called goodput, we develop a power allocation strategy among the different subcarriers so that the system goodput performance metric is maximized. We also demonstrate the optimality of the solution for the proposed objective function under the given power constraint. The effectiveness of the power allocation policy is numerically testified for BIC-OFDM transmission in the context of typical indoor environment.
Iron is a signal for Stenotrophomonas maltophilia biofilm formation, oxidative stress response, OMPs expression, and virulence

Stenotrophomonas maltophilia is an emerging nosocomial pathogen. In many bacteria iron availability regulates, through the Fur system, not only iron homeostasis but also virulence. The aim of this work was to assess the role of iron on S. maltophilia biofilm formation, EPS production, oxidative stress response, OMPs regulation, quorum sensing (QS), and virulence. Studies were done on K279a and its isogenic fur mutant F60 cultured in the presence or absence of dipyridyl. This is the first report of spontaneous fur mutants obtained in S. maltophilia. F60 produced higher amounts of biofilms than K279a and CLSM analysis demonstrated improved adherence and biofilm organization. Under iron restricted conditions, K279a produced biofilms with more biomass and enhanced thickness. In addition, F60 produced higher amounts of EPS than K279a but with a similar composition, as revealed by ATR-FTIR spectroscopy. With respect to the oxidative stress response, MnSOD was the only SOD isoenzyme detected in K279a. F60 presented higher SOD activity than the wt strain in planktonic and biofilm cultures, and iron deprivation increased K279a SOD activity. Under iron starvation, SDS-PAGE profile from K279a presented two iron-repressed proteins. Mass spectrometry analysis revealed homology with FepA and another putative TonB-dependent siderophore receptor of K279a. In silico analysis allowed the detection of potential Fur boxes in the respective coding genes. K279a encodes the QS diffusible signal factor (DSF). Under iron restriction K279a produced higher amounts of DSF than under iron rich condition. Finally, F60 was more virulent than K279a in the Galleria mellonella killing assay. These results put in evidence that iron levels regulate, likely through the Fur system, S. maltophilia biofilm formation, oxidative stress response, OMPs expression, DSF production and virulence.