Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of land use on water quality at different spatial scales in the middle reaches of Huaihe River

Abstract The impact of land use on water quality is spatially scale-dependent. Exploring the relationship between land use pattern and river water quality provides an important basis for water quality safety and land planning. This study explores the effect of land use patterns on surface water quality using land use data and water quality data of 16 sampling points in the middle reach of the Huai River. It investigates the water quality status of the middle reach of the Huai River and the relationship between land use patterns and water quality indices at 100, 500, and 1000 m and watershed scales utilising Spearman correlation, redundancy analysis (RDA), and multiple linear regression analysis. Multiple linear regression analysis showed that the water pollutants in the middle reach of the Huai River are mainly total nitrogen (TN) and total phosphorus (TP). Redundancy analysis (RDA) indicated that the impact of land use patterns on water quality is significant on watershed scales. Spearman correlation indicated that water quality and land use showed significant correlation differences, the building land was positively correlated with TP, TN and NH3-N, the cultivated land was positively correlated with TN, and the grassland was negatively correlated with TP and NH3-N. This studies have revealed that building land acts as a 'source’ of pollutants, grassland purifies the load of TP and NH3-N, and forest land has the effect of interception and deposition of pollutants. The results can provide important information for land use planning and water quality protection measures at multiple spatial scales.
Gypsum-hosted endolithic communities of the Lake St. Martin impact structure, Manitoba, Canada: spectroscopic detectability and implications for Mars

Abstract There is increasing evidence that Mars may have once been a habitable environment. Gypsum is targeted in the search for Martian biosignatures because it can host extensive cryptoendolithic communities in extreme terrestrial environments and is widespread on Mars. In this study the viability of using different spectroscopy-based techniques to identify the presence of gypsum endolithic communities was investigated by analysing various cryptoendoliths collected from the Lake St. Martin impact crater (LSM), a Mars analogue site found in Manitoba, Canada. Concurrently, the cryptoendolithic microbial community structure present was also analysed to aid in assigning spectroscopic features to microbial community members. Two main morphologies of endolithic communities were collected from gypsum deposits at LSM: true cryptoendolithic communities and annular deposits on partially buried boulders and cobbles <1 cm below the soil surface. Endolithic communities were found to be visibly present only in gypsum with a high degree of translucency and could occur as deep as 3 cm below the exterior surface. The bacterial community was dominated by a phylum (Chloroflexi) that has not been previously observed in gypsum endoliths. The exterior surfaces of gypsum boulders and cobbles are devoid of spectroscopic features attributable to organic molecules and detectable by reflectance, Raman, or ultraviolet-induced fluorescence spectroscopies. However, exposed interior surfaces show unique endolithic signatures detectable by each spectroscopic technique. This indicates that cryptoendolithic communities can be detected via spectroscopy-based techniques, provided they are either partially or fully exposed and enough photon–target interactions occur to enable detection.
Network Anomaly Intrusion Detection Based on Deep Learning Approach

The prevalence of internet usage leads to diverse internet traffic, which may contain information about various types of internet attacks. In recent years, many researchers have applied deep learning technology to intrusion detection systems and obtained fairly strong recognition results. However, most experiments have used old datasets, so they could not reflect the latest attack information. In this paper, a current state of the CSE-CIC-IDS2018 dataset and standard evaluation metrics has been employed to evaluate the proposed mechanism. After preprocessing the dataset, six models—deep neural network (DNN), convolutional neural network (CNN), recurrent neural network (RNN), long short-term memory (LSTM), CNN + RNN and CNN + LSTM—were constructed to judge whether network traffic comprised a malicious attack. In addition, multi-classification experiments were conducted to sort traffic into benign traffic and six categories of malicious attacks: BruteForce, Denial-of-service (DoS), Web Attacks, Infiltration, Botnet, and Distributed denial-of-service (DDoS). Each model showed a high accuracy in various experiments, and their multi-class classification accuracy were above 98%. Compared with the intrusion detection system (IDS) of other papers, the proposed model effectively improves the detection performance. Moreover, the inference time for the combinations of CNN + RNN and CNN + LSTM is longer than that of the individual DNN, RNN and CNN. Therefore, the DNN, RNN and CNN are better than CNN + RNN and CNN + LSTM for considering the implementation of the algorithm in the IDS device.
Non-local effects in the stability of flow between eccentric rotating cylinders

In this paper the linear stability of the flow between two long eccentric rotating circular cylinders is considered. The problem, which is of interest in lubrication technology, is an extension of the classical Taylor problem for concentric cylinders. The basic flow has components in the radial and azimuthal directions and depends on both of these co-ordinates. As a consequence the linearized stability equations are partial differential equations rather than ordinary differential equations. Thus standard methods of stability theory are not immediately useful. However, there are two small parameters in the problem, namely δ, the clearance ratio, and ε, the eccentricity. By letting these parameters tend to zero in such a way that δ½ is proportional to ε, a global solution to the stability problem is obtained without recourse to the concept of ‘local instability’, or ‘parallel-flow’ approximation, so commonly used in boundary-layer stability theory. It is found that the predictions of the present theory are at variance with what is given by a ‘local’ theory. First, the Taylor-vortex amplitude is found to be largest at about 90° downstream of the region of ‘maximum local instability’. This result is given support by some experimental observations of Vohr (1968) with δ = 0·1 and ε = 0·475, which yield a corresponding angle of about 50°. Second, the critical Taylor number rises with ε, rather than initially decreasing with ε as predicted by local stability theory using the criteria of maximum local instability. The present prediction of the critical Taylor number agrees well with Vohr's experiments for ε up to about 0·5 when δ = 0·01 and for ε up to about 0·2 when δ = 0.1.
Random sampling methods for two-view geometry estimation

This thesis treats efficient estimation algorithms for the epipolar geometry, the model underlying two views of the same scene or object. The epipolar geometry is computed from image correspondences that are found by local feature matching. These correspondences are used to calculate the fundamental matrix, which is the mathematical representation of the epipolar geometry. Since there are outliers among the correspondences, the fundamental matrix is usually calculated by the robust RANSAC (RANdom SAmple Consensus) algorithm which is very well suited for this purpose. A disadvantage of the algorithm, however, is that it shows a considerable complexity for higher outlier ratios. This hampers its application in vision algorithms dealing with many views. In this thesis we investigate techniques for faster fundamental matrix estimation using RANSAC. The first approach that is taken is the computation of inlier probabilities for the correspondences, that are used during sampling in the RANSAC algorithm to stimulate the selection of inliers. The second approach is the reduction of the required number of RANSAC samples by the selection of fewer correspondences per sample. The fundamental matrix hypotheses are then completed using the remaining correspondences.
Momentum transfer of a Boltzmann-lattice fluid with boundaries

We study the velocity boundary condition for curved boundaries in the lattice Boltzmann equation (LBE). We propose a LBE boundary condition for moving boundaries by combination of the “bounce-back” scheme and spatial interpolations of first or second order. The proposed boundary condition is a simple, robust, efficient, and accurate scheme. Second-order accuracy of the boundary condition is demonstrated for two cases: (1) time-dependent two-dimensional circular Couette flow and (2) two-dimensional steady flow past a periodic array of circular cylinders (flow through the porous media of cylinders). For the former case, the lattice Boltzmann solution is compared with the analytic solution of the Navier–Stokes equation. For the latter case, the lattice Boltzmann solution is compared with a finite-element solution of the Navier–Stokes equation. The lattice Boltzmann solutions for both flows agree very well with the solutions of the Navier–Stokes equations. We also analyze the torque due to the momentum transf.
Stochastic Surrogates for Measurements and Computer Models of Fluids

Both measurements and computer simulations of fluids introduce a prediction problem. A Particle Image Velocimetry (PIV) measurement of a flow field results in a discrete grid of velocity vectors, from which we aim to predict the velocity field or related quantities. In Computational Fluid Dynamics (CFD), the output of the computer code depends on the input parameters, and we aim to propogate the uncertainty of the input parameters or aim to determine the choice of input parameters that optimizes the output. Presently, we discuss a general framework that uses a stochastic surrogate to address the prediction problem. In flow measurement, we predict the velocity field conditional on the discrete set of PIV data. For uncertainty propagation and optimization, we construct a surrogate of the CFD output, conditional on a discrete set of solves. As a surrogate we use Kriging, derived in a Bayesian framework. This approach has two main advantages. Firstly, when adjoint-based gradient information is available from the CFD solver, the gradient information can be included in the surrogate, reducing the computational cost of higher-dimensional uncertainty propagation and optimization problems. Secondly, measurement uncertainty of PIV data, CFD output, and CFD gradient output can be represented through the likelihood: notably, PIV data can have local variations of measurement uncertainty due to imperfect experimental conditions, while CFD gradient output is often considerably noisy|to the extent of detoriating results instead of improving them when the noise is not properly accounted for. Before applying the Kriging predictor, two well-known problems are addressed. Firstly, robustness of the Kriging predictor is found not to be related to conditioning| as is often suggested|but to numerical positive definitness of part of the gain matrix. We provide analytical estimates for conditions under which the Kriging predictor is robust. Secondly, estimating the hyperparameters becomes expensive for larger data sets, such as PIV measurements. We discuss two FFT-based methods that reduce the cost of hyperparameter estimation.
Locality and complexity in simulations of complex quantum systems

1 Introduction 2 Locality and complexity in lattice systems 2.1 Introduction to Lieb-Robinson bounds and their implications 2.2 Generalizing Hamiltonian complexity results to open quantum systems 2.2.1 A dissipative Church-Turing theorem from generalizing the Trotter-Suzuki decomposition 2.2.2 Lieb-Robinson bounds and quasi-locality of time evolution 2.3 Locality of temperature from a new thermal Lieb-Robinson type bound 2.4 On state space structures 2.4. 1 Real- space renormalization yields finite correlations 2.4. 2 A hard and an undecidable problem for translation invariant 1D systems 3 Quantum simulations and the verification problem 3.1 Indication that classical efficient Boson- Sampling verification is impossible 3.2 Reliable quantum verification for photonic quantum technologies 4 Conclusions Bibliography A Appendix: Terminology A.1 Concepts from computational complexity theory A.2 Concepts from quantum (information) theory B Appendix: Other publications generated during this thesis C Back matter C.1 Acknowledgements C.2 Abstract C.3 Zusammenfassung C.4 Liste der Publikationen des Verfassers C.5 Anteil des Autors bei Konzeption, Durchfuhrung und Berichtsabfassung C.6 Eigenstandigkeitserklarung
Individualism, Collectivism, and Allocation Behavior: Evidence from the Ultimatum Game and Dictator Game

Studies have demonstrated the influence of the cultural values of individualism and collectivism on individuals’ economic behavior (e.g., competition and trade). By using individualistic and collectivistic texts to prime participants’ minds in a lab experiment, we investigated the impact of the cultural values of individualism and collectivism on allocation behavior in an ultimatum game (UG) and dictator game (DG). In the dictator game, we found that participants in the collectivism-priming condition reported a slightly higher mean offer than in the individualism-priming condition, and participants had an average higher acceptance rate of the proposers’ offer in the collectivism-priming (vs. individualism-priming) condition in the ultimatum game. Our findings suggest that participants exhibit more altruistic allocation behavior and are more tolerant of unfair allocation behavior after being primed by the collectivistic (vs. individualistic) texts. In comparison with participants who did not undergo initiation, we also found that Chinese participants who had been influenced by collectivist values for a long time remained unaffected after the initiation of collectivism, but shifted their allocation behavior (i.e., showed decreased altruistic allocation behavior and reduced tolerance of unfair allocation behavior) when individualism was primed.
Naringin Protects against Tau Hyperphosphorylation in Aβ25–35-Injured PC12 Cells through Modulation of ER, PI3K/AKT, and GSK-3β Signaling Pathways

Alzheimer's disease (AD) is the most common form of dementia and a significant social and economic burden. Estrogens can exert neuroprotective effects and may contribute to the prevention, attenuation, or even delay in the onset of AD; however, long-term estrogen therapy is associated with harmful side effects. Thus, estrogen alternatives are of interest for countering AD. Naringin, a phytoestrogen, is a key active ingredient in the traditional Chinese medicine Drynaria. Naringin is known to protect against nerve injury induced by amyloid beta-protein (Aβ) 25–35, but the underlying mechanisms of this protection are unclear. To investigate the mechanisms of naringin neuroprotection, we observed the protective effect on Aβ25–35-injured C57BL/6J mice's learning and memory ability and hippocampal neurons. Then, an Aβ25–35 injury model was established with adrenal phaeochromocytoma (PC12) cells. We examined the effect of naringin treatment on Aβ25–35-injured PC12 cells and its relationship with estrogen receptor (ER), phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT), and glycogen synthase kinase (GSK)-3β signaling pathways. Estradiol (E2) was used as a positive control for neuroprotection. Naringin treatment resulted in improved learning and memory ability, the morphology of hippocampal neurons, increased cell viability, and reduced apoptosis. We next examined the expression of ERβ, p-AKT (Ser473, Thr308), AKT, p-GSK-3β (Ser9), GSK-3β, p-Tau (Thr231, Ser396), and Tau in PC12 cells treated with Aβ25–35 and either naringin or E2, with and without inhibitors of the ER, PI3K/AKT, and GSK-3β pathways. Our results demonstrated that naringin inhibits Aβ25–35-induced Tau hyperphosphorylation by modulating the ER, PI3K/AKT, and GSK-3β signaling pathways. Furthermore, the neuroprotective effects of naringin were comparable to those of E2 in all treatment groups. Thus, our results have furthered our understanding of naringin's neuroprotective mechanisms and indicate that naringin may comprise a viable alternative to estrogen therapy.
Hospital-wide reactive scheduling of nurses with preference considerations

This paper presents a new methodology for reactively scheduling nurses in light of shift-by-shift imbalances in supply and demand. In most hospitals, the nursing staff is given a midterm schedule that specifies their work assignments for up to 6 weeks at a time. However, emergencies, call-outs, and normal fluctuations in personnel requirements can play havoc with the schedule. As a result, it is necessary to make short-term adjustments, either by reallocating resources when shortages exist or by cancelling assignments when demand drops. The need to take into account individual preferences further complicates the process. The problem associated with making the daily adjustments is formulated as an Integer Program (IP) and solved within a rolling horizon framework. The idea is to consider 24 hours at a time, but to only implement the results for the first 8 hours. The IP is then re-solved for the next 24 hours after several hours have elapsed and new data are available, and so on. Initial attempts to solve 50-nurse problems with a commercial code proved to be unsuccessful and led to the development of a branch-and-price algorithm. Included in the algorithm are a feasibility heuristic to find the upper bounds and a cut generation procedure to improve the lower bound computations. A set-covering-type IP was used to find upper bounds and mixed-integer rounding cuts were used to tighten the relaxed feasible region. Although the effectiveness of all but the set covering heuristic proved to be marginal, most problem instances with up to 200 nurses were solved within 10 minutes.
Spurious microwave fields in caesium atomic beam frequency standards: symmetry considerations and model calculations

Spurious microwave fields can be a cause of systematic frequency offsets and excessive frequency instability in caesium atomic beam frequency standards. In this contribution, we present helpful results to distinguish this type of disturbance in frequency standards from others. We have treated the interaction in the Ramsey cavity and an additional interaction with a spurious microwave field inside the beam tube as weak interactions and also with realistic parameters using full quantum mechanical calculations. We obtain the clock frequency shifts in dependence on amplitude and phase of the spurious field, and on the modulation parameters.
Detection of the X-ray-heated companion of X1822-371

We have detected the companion starinX1822 - 371 from the behaviour of the HeI A5876 in absorption around phase 0.5 and find a lower limit for the radial velocity of Kc > 225±23 kIns- l . The irradiation-induced dominant component within the HeI }'5876 absorption profile is the only detected spectral signature of the companion star. Ha shows a narrow double-peaked emission profile embedded in a wider absorption profile. There is no evidence of any binary motion (i.e., rotational disturbance during eclipse) probably implying a vertically extended region obscuring the inner disc. The Ha emission distribution is centred towards the disc bulge at phase 0.8 rather than towards the compact object. Detection of Fe II A6516, in the region of phase 0.8, suggests an 'iron-curtain' related to the impact region of the gas stream with supersonic velocities of Mach -20 ± 8(T/104 K) for the absorbing gas.
On the robustness of central composite designs when missing two observations

Quite often, many situations arise in experimental work where some experimental runs that may not be feasible because of certain circumstances or existing constraints in the system under investigation. A lot of work has been done in studying classical designs, such as the central composite designs (CCDs), with missing observations. In this paper our interest is to research the losses that may occur when one or two observations are missing. The general formulas for missing two observations are presented in a closed form as a function of α, where α is the value used in the axial part in the CCDs. These are calculated explicitly for CCDs up to k=10$k=10$ factors, for the first time in this paper, and are displayed in tables for practitioners to use. The losses for any value of α, in the axial points of the design, can be derived by simply replacing α with the desirable value in the provided formulas. A detailed comparison between our findings and results already known in the literature also been made.
Frustrated magnetism and cooperative phase transitions in spinels

The spinel crystal system, AB 2 O 4 , has been fertile ground in studying the effects of magnetic and orbital frustration. The experimental findings, with primary focus on neutron and synchrotron x-ray scattering techniques, are hereby reviewed in spinels with magnetic B ions. Highlighted are novel collective phenomena, such as the zero-energy excitation mode in the spin liquid phase, zero-field and field-induced novel phase transitions, the emergence of complex local spin entities, and heavy fermionic behaviors. Such a diversity in the exotic properties stems from their close proximity to critical points among degenerate states and a delicate balance among different degrees of freedom such as spin, orbital, and lattice.
A case of EBUS-TBNA in a Total Laryngectomy Patient using High Flow Nasal Oxygen

Endobronchial Ultrasound transbronchial needle aspiration (EBUS-TBNA) is currently considered as the gold standard technique for the assessment of mediastinal, hilar and centrally located lymph nodes and tumours. However, the ideal approach to sedation and oxygen supplementation during the procedure has not been clearly defined especially in particular clinical scenarios like total laryngectomy patients. In the following article we present the case of an EBUS-TBNA in a total laryngectomy patient done under moderate sedation and oxygenation using a heated High Flow Nasal Oxygen canula. The purpose of this case report is to shed light on the feasibility of the procedure under moderate sedation and the utility of the HFNO in special patients as those having a total laryngectomy.
Diabetic Muscle Infarction—A Rare Diabetic Complication: Literature Review and Case Report

We present a case of a 31-year-old patient with type 1 diabetes diagnosed at the age of 6. Diabetes is complicated with neuropathy, retinopathy, and nephropathy. He has been admitted to the diabetes ward due to inadequate diabetes control. Gastroscopy and abdominal CT were performed, and gastroparesis was confirmed as an explanation for postprandial hypoglycemia. During hospitalization, the patient reported sudden pain localized on the lateral, distal part of his right thigh. The pain occurred at rest and was aggravated by movement. Diabetic muscle infarction (DMI) is a rare complication of long-lasting, uncontrolled diabetes mellitus. It usually occurs spontaneously, without any previous infection or trauma, and is often misdiagnosed clinically as an abscess, neoplasm, or myositis. DMI patients suffer from pain and swelling of the affected muscles. Radiological examinations, including MRI, CT, and USG, are most important for the diagnosis, assessing the extent of involvement and differentiating DMI from other conditions. However, sometimes a biopsy and histopathological examination are necessary. The optimal treatment has still not been determined. There is also a potential risk of DMI recurrence.