Miracle-dz/UniFAR-FTUs huggingface dataset:
An extensive review of data security infrastructure and legislature

The last few decades have witnessed technology progress with leaps and bounds leading to the creation and global adoption of different types of digital devices and platforms that can make personalized recommendations to an individual. One of the consequences of the ubiquity of these devices is the daily generation of data in large quantities. This data includes the sensitive data of an individual as well as multinational organizations and therefore, it must be always kept confidential to prevent its theft and misuse by malicious parties. However, the large volumes of data generated make it difficult to create a robust security solution to safeguard the data from different types of cyberattacks. The paper contributes to the data security industry by consolidating numerous data security algorithms that change with the infrastructure that the data is amid and also outlines the regulations surrounding it. This review paper also aims to highlight the benefits and drawbacks of the security algorithms proposed by researchers to encourage further discussion and consideration of the algorithms for their potential implementation in appropriate domains and also inspire them to develop more powerful and robust security algorithms to cover the drawbacks of the existing ones.
News Credibility and Influence within the Financial Markets

Abstract How does information credibility, a subjective judgment of investors, affect empirical asset pricing in financial markets? Traditional economic theories are inadequate for interpreting market responses driven by people’s subjective thinking, as these cognitive processes are not encompassed by the concept of utility. We explore these effects by using computational linguistics and deep structured learning algorithms to analyze financial newspapers and social media posts. After controlling for factors related to content and market momentum in our narrative based credibility indicator, we find that news credibility is positively correlated with the returns on assets preferred by experts and negatively correlated with assets preferred by gamblers. Based on this finding, we point out that the efficient-market hypothesis (EMH) is not appropriate in the dominant market of gamblers in the short-term. In the long-term, however, investment motivation does not significantly affect the validity of the hypothesis.
LACI: Low-effort Automatic Calibration of Infrastructure Sensors

Sensor calibration usually is a time consuming yet important task. While classical approaches are sensor-specific and often need calibration targets as well as a widely overlapping field of view (FOV), within this work, a cooperative intelligent vehicle is used as callibration target. The vehicle is detected in the sensor frame and then matched with the information received from the cooperative awareness messages send by the coperative intelligent vehicle. The presented algorithm is fully automated as well as sensor-independent, relying only on a very common set of assumptions. Due to the direct registration on the world frame, no overlapping FOV is necessary. The algorithm is evaluated through experiment for four laserscanners as well as one pair of stereo cameras showing a repetition error within the measurement uncertainty of the sensors. A plausibility check rules out systematic errors that might not have been covered by evaluating the repetition error.
Waiting time and idle time of uncertain queueing system

Uncertain queueing system is a waiting line in which the interarrival times and service times are both modeled by uncertain variables. This paper investigates four important performance characteristics of uncertain queueing system, including waiting time, idle time, total idle time and total busy time. The analytical formulas of uncertainty distributions of those performance characteristics are also derived separately.
Investigation of the retention mechanisms of amlodipine besylate, bisoprolol fumarate, and their impurities on three different HILIC columns

Abstract Using theoretical models, retention mechanisms of amlodipine besilate and its impurities D, E, and F were tested, as well as bisoprolol fumarate and its impurities A, C, K, and L. Appropriate theoretical retention models for tested compounds were used, which enabled the determination of retention mechanisms responsible for the separation of tested compounds on three different HILIC column: silica, amino, and diol. In order to describe the effect of ratio of aqueous and organic portion of the mobile phase on the retention behavior of tested compounds, as well as the consideration of shares of partition and adsorption processes in HILIC retention mechanism in all three columns, partitioning and adsorption retention theoretical models were calculated. For this purpose, the water content was varied in the range from 4% to 29%, corresponding to the HILIC region of mobile phase composition. During the experiment, values of other factors of mobile phase were maintained at a constant level. Regression coefficients of partition and adsorption retention models and the corresponding determination coefficients were determined (R2). Partitioning models for all tested compounds on amino column had higher R2 values, while adsorption models for all compounds tested on silica and diol column had higher R2 value. Graphical Abstract
Orienting to the sun improves camouflage for bilaterally symmetrical prey

Here, we investigate the camouflage consequences of animal orientation behaviour. Shadows can be a conspicuous cue to the presence of prey. For bilaterally symmetrical animals, light field modelling indicates that camouflage will be improved when an animal orients its longitudinal axis directly towards or away from the sun, because the appearance of shadows is minimized. We test this prediction with a field predation experiment, in which wild birds hunt for artificial camouflaged prey oriented with the longitudinal axis either parallel or perpendicular to the sun. We find that prey oriented parallel to the sun are 3.93 times more likely to survive than prey oriented perpendicular to the sun. This result demonstrates the strong orientation dependence of camouflage. Given the dramatic difference in survival of prey with different orientations, we suggest that camouflage should be investigated as an important determinant of the positional behaviour of animals.
Acute toxicity of sodium chloride to first and fourth instar Aedes albopictus larvae

e increase in the number of imported cases of dengue fever in Japan is of particular concern as Aedes albopictus is a vector of dengue fever. Due to the potential for insecticide resistance and the impact of insecticides on non-target species, increased attention is being paid to alternative methods of pest control. Placing salt in used tires has been recommended by the Ministry of Health, Labor and Welfare in Japan as a means of controlling mosquitoes. However, the e ectiveness of salt as a larvicide against Ae. albopictus are currently unclear. is study examined the acute toxicity of sodium chloride against rst and fourth larval instars of Ae. albopictus. Acute toxicity tests were conducted according to World Health Organization guidelines. e susceptibility of Ae. albopictus larvae was tested against 0.25%, 0.5%, 0.75%, 1.00%, 1.25% and 1.5% NaCl solutions. Larval mortality was correlated with an increase in NaCl concentration and exposure duration. First instar Ae. albopictus larvae were more sensitive to NaCl than fourth instar, and 72-h LC90 values for rst and fourth larval instars were 0.49% and 1.01% NaCl, respectively. Our results suggest that the application of 0.5% NaCl to a habitat for 3 days is e ective for Ae. albopictus
Detection of Cacao Mild Mosaic Virus (CaMMV) Using Nested PCR and Evidence of Uneven Distribution in Leaf Tissue

Distribution of improved germplasm of Theobroma cacao is essential for meeting the increased demand for cocoa beans. In cacao, the introduction of new diseases is prevented by exchanging material through a national and international quarantine system. In 2020, virus symptoms were observed on plants in a quarantine greenhouse, and Cacao mild mosaic virus (CaMMV) was detected in one plant using published diagnostic primers. However, no virus was detected in other symptomatic plants. To address high pathogen diversity and low virus titer in recently infected plants, a nested PCR test was developed based on 15 CaMMV sequences from Trinidad and Puerto Rico. The test was validated on a subset (n = 30) of plants in the greenhouse, of which 29 tested positive. Most infections are thought to have occurred during the later stage of the quarantine period, possibly due to spread by mealybugs. However, phylogenetic analysis revealed the presence of three strains, suggesting that it was introduced on scionwood from multiple sources. Results of PCR assays on different leaf tissues indicate that the virus is unevenly distributed and that petiole tissue should be used in molecular diagnostics. The movement of infected scionwood is a major dissemination pathway for CaMMV but can be managed through careful screening.
Extending a Large-scale Model to Better Represent Water Resources without Increasing the Model Complexity

A robust hydrological assessment is challenging in regions where human interference, within all aspects of the hydrological system, significantly alters the flow regime of rivers. The challenge was to extend a large-scale water resources model, GWAVA, to better represent water resources without increasing the model complexity. A groundwater and a regulated reservoir routine were incorporated into GWAVA using modifications of the existing AMBHAS-1D and Hanasaki methodologies, respectively. The groundwater routine can be varied in complexity when sufficient input data is available but fundamentally is driven by three input parameters. The reservoir routine was extended to account for the presence of large, regulated reservoirs using two calibratable parameters. The additional groundwater processes and reservoir regulation was tested in two highly anthropogenically influenced basins in India: the Cauvery and Narmada. The inclusion of the revised groundwater routine improved the simulation of streamflow in the headwater catchments and was successful in improving the representation of the baseflow component. In addition, the model was able to produce a time series of daily groundwater levels, recharge to groundwater and groundwater abstraction. The regulated reservoir routine improved the simulation of streamflow in catchments downstream of major reservoirs, where the streamflow was largely reflective of reservoir releases, when calibrated using downstream observed streamflow records. The model was able to provide a more robust representation of the annual volume and daily outflow released from the major reservoirs and simulate the major reservoir storages adequately. The addition of one-dimensional groundwater processes and a regulated reservoir routine proved successful in improving the model performance and traceability of water balance components, without excessively increasing the model complexity and input data requirements.
Review of Machine Learning Techniques for Detection of Routing Attacks in Wireless Sensor Network

Wireless sensor networks are widely applied in many fields like transportation, urban terrain tracking, healthcare, precision agriculture, etc. However, this deployment has introduced new security concerns. These security concerns involve two kinds of attacks on wireless sensor networks active and passive. Passive attacks are launched to observe the network without disrupting network functionality. Active attacks can disrupt the function of the network and can be initiated on layers of communication protocol. Active attacks that are related to network layer routing attacks are presented. For the last decade, machine learning algorithms have been used in many important applications, including detection of routing attacks. The objective of this paper is to review machine learning algorithms that can be used to detect routing attacks in wireless sensor networks. In this paper, evaluation parameters and challenges of applying machine learning algorithms in wireless sensor networks are also discussed. These challenges can serve as potential future research directions.
Dressed excitations, thermodynamics and relaxation in the XXZ Heisenberg model

In this note, we discuss the low and high temperature contribution of thermodynamic Bethe ansatz (TBA) dressed excitations in the thermodynamics and energy-magnetization relaxation within the generalized hydrodynamics approach in the linear response regime. In particular, we show how the temperature dependent dispersions of the excitations reproduce well known behavior of the specific heat, magnetic susceptibility, spin and energy Drude weights. In this context, we derive a further formulation of the Drude weights from the finite wavevector relaxation. Furthermore, we contrast the TBA description of thermodynamics and dynamics in terms of a multitude of string excitations to that in terms of a single quasi-particle in low energy effective theories.
On Optimum Solar Wind‐Magnetosphere Coupling Functions for Transpolar Voltage and Planetary Geomagnetic Activity

Using 65,133 hourly averages of transpolar voltage (ΦPC) from observations made over 25 yr by the SuperDARN radars, with simultaneous SML and interpolated am geomagnetic indices, we study their optimum interplanetary coupling functions. We find mean lags of 18, 31, and 45 min for ΦPC, am, and SML, respectively, and fit using a general coupling function with three free fit exponents. To converge to a fit, we need to average interplanetary parameters and then apply the exponent which is a widely used approximation: we show how and why this is valid for all interplanetary parameters, except the factor quantifying the effect of the clock angle of the interplanetary magnetic field, sind(θ/2), which must be computed at high time resolution and then averaged. We demonstrate the effect of the exponent d on the distribution, and hence weighting, of samples and show d is best determined from the requirement that the coupling function is a linear predictor, yielding d of 2.50 ± 0.10, 3.00 ± 0.22, and 5.20 ± 0.41 for ΦPC, am, and SML, respectively. To check for overfitting, fits are made to half the available data and tested against the other half. Ensembles of 1,000 fits are used to study the effect of the number of samples on the distribution of errors in individual fits and on systematic biases in the ensemble means. We find only a weak dependence of solar wind density for ΦPC and SML but a significant one for am. The optimum coupling functions are shown to be significantly different for ΦPC, am, and SML.
Dancing after homelessness

ABSTRACT Dance as an artform touches the biopsychosocial dimensions of people and as such is increasingly used as a vehicle to improve the quality of life of diverse populations in the community. Yet little is known about how dance classes are experienced by marginalized populations. The purpose of this action research was to explore the potential of dance to contribute to the recovery of women having experienced homelessness. The objectives were to describe: 1) the artistic content (the ‘what’) and the pedagogical approach (the ‘how’) of the classes, and 2) the experiences of all the people involved in the action research (women, workers at the women’s home, dance facilitators and researcher). Over a three-year period, weekly classes were offered in a women’s home. Data was collected through individual interviews, focus groups and observations. A thematic analysis revealed eleven categories of dance activities which were subsequently associated with indicators of recovery. The pedagogical approach was driven by a set of values clearly embedded in the classes; the facilitators deployed numerous adaptations to answers the women’s needs. Sufficient evidence supports the claim that dance is a promising practice for individual women’s process of recovery. Implications for future research and practice are discussed.
Promoting Athlete Mental Health: The Role of Emotion Regulation

This study investigated the relationship between reappraisal and suppression with depression and mental well-being among university athletes. It was hypothesized reappraisal would associate with lower depression and greater mental well-being, whereas suppression would associate with greater depression and reduced mental well-being. Employing a cross-sectional design, 427 participants (Mage = 20.18, SD = 1.52; 188 males and 239 females) completed questionnaires assessing mental health and strategy use. Hierarchical multiple regressions revealed reappraisal was positively associated, and suppression negatively associated with mental well-being, ΔR2 = 4.8%, ΔF(2, 422) = 17.01, p ≤ . 001; suppression, β = −0.08, p = . 028; reappraisal, β = 0.21, p ≤ . 001, but neither were associated with depression, ΔR2 = 0.4%, ΔF(2, 422) = 1.33, p = . 267; suppression, β = 0.06, p = . 114; reappraisal, β = 0.03, p = . 525. Results highlight reappraisal as correlated with mental well-being in student-athletes, and therefore, reappraisal could be beneficial for managing stress in sport. Reappraisal may implicate how well-being is promoted through sport, but future experimental research is needed to confirm causal relationships.
Real-Time Optimal Resource Allocation and Constraint Negotiation Applied to A Subsea Oil Production Network

This paper considers the problem of steady-state optimal resource allocation in an industrial symbiotic oil production network, or in general, a large-scale oil production system network, where different organizations share common resources. These allocation problems are typically solved in a distributed optimization framework, where the optimization problem is decomposed into smaller subproblems, a central coordinator is used to coordinate the different subproblems. However, the use of a central coordinator may introduce additional practical challenges, such as impartiality issues, or additional operating costs, which is undesirable even in the technological selection phase. To eliminate the need for a central coordinator, this paper proposes a consensus-based optimal resource allocation, where each subproblem or organization is locally optimized, and the coupling constraints are negotiated among the different organizations over a fixed communication network with limited information exchange. The proposed approach is applied to a large-scale subsea oil production system, where the different wells are operated by different organizations. The simulation results of the application show that the proposed approach can optimally allocate the shared resources.
Grouping-Based Joint Active User Detection and Channel Estimation With Massive MIMO

This paper considers an uplink massive machine-type communication scenario with a massive number of antennas, where a large number of user devices are connected to a base station (BS) and the user traffic is sporadic. We propose a novel hybrid message passing (HMP) algorithm to achieve joint active detection and channel estimation (JADCE) by exploiting the channel characteristics in both the angular domain and user domain, which is expected to enhance the performance of JADCE compared with the conventional approaches without the knowledge of such a consideration. The user grouping is performed simultaneously with JADCE, which provides the prerequisites of the joint spatial division and multiplexing to achieve significant savings both in the downlink training and feedback of channel state information at the transmitter. Based on the acquired knowledge of user grouping, we further propose a per-group processing based JADCE (PGP-JADCE) approach. It significantly reduces the computational overhead for JADCE and the BS is capable to process all the user groups in parallel. Further, the analysis of detection error probabilities and channel estimation error of PGP-JADCE is provided.
Milking practices on commercial Holstein-Friesian farms

ABSTRACT The objective of this study was to survey and analyze milking practices of commercial Holstein-Friesian farms. A total of 43 Hungarian dairy farms with 31,430 cows was surveyed by using a questionnaire via personal interviews. Furthermore, seven in-depth, individual interviews were conducted with farm managers. In the statistical analysis, we used ANOVA models. The results showed that 57.8% of the milking parlors had a herringbone design, followed by parallel (20.0%) and rotary (17.8%) milking systems. For the interviewed farm managers, gentle (71.4%) and quick milking (57.1%) as well as herd size (57.1%) were the most important factors in determining the milking system design. In 62.8% of the farms, cows were milked twice a day, and the average milking time was 5.0 h with an average of 3.1 laborers. The average daily milking time per cow was 15 min and the average daily walking time per cow to the milking parlor and back was 24 min. Furthermore, 85.4% of the farms used traditional elastic milk liners, whereas 14.6% used silicone ones. In total, 57.1% of the interviewed farm managers said that the ideal teat liner should fit the teats correctly and provide gentle milking. Prior to milking, 65.1% of the farms used disinfectant dip and 11.6% used a disinfectant wash, whereas 23.3% still washed the udder with water. The udder was wiped with paper towels in 73.8% of the herds and with cloth in 26.2% of the herds. Forestripping was performed in all herds: 51.2% onto the floor, 46.5% into a cup, and in 2.3% into a paper towel. Further, 85.7% of the interviewed farm managers considered the use of a cup to be the ideal method, but 57.1% deemed a dark-colored piece of rubber/flooring to be similarly acceptable. Cows with mastitis were milked separately in 91.9% of the farms.
DTM Extraction and building detection in DSMs having large holes

Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) are crucial for automatic detection of buildings and other ground features in urban areas. They are the basis for numerous geospatial applications, such as 3D city modelling, 3D mapping infrastructures, drainage pattern studies, etc. LiDAR based DSMs usually contain less holes than image-based DSMs. This is mainly because of the mismatching error acquired due to occlusion in photogrammetry. However, if high-rise buildings are present in the scene, large holes are most likely to occur in LiDAR derived DSM. In this research, a modified algorithm for LiDAR-based DSM to DTM filtering approach is presented. The algorithm deals with the original DSM without aiming for precise outcomes. Firstly, pixels representing holes are automatically detected and labelled with unique value. Since available DTM extraction algorithms are mainly based on finding pixels having minimal elevation, this unique value must belong to the off-terrain to avoid using them as minima. Afterwards, the Network of Ground Points algorithm is applied for extracting DTM from DSM to be further used for building detection purposes. The proposed method is tested on the benchmark dataset for Toronto city provided by the ISPRS working group III / 4. The evaluation analysis was applied based on calculating correctness and completeness of the detected building segments. Results showed the practical effectiveness of the proposed technique in achieving average correctness of 91 %.