Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical modelling of the destruction degree of cancer under the influence of a RF hyperthermia

The article presents the mathematical modeling of the phenomenon of artificial hyperthermia which is caused by the interaction of an electric field. The electric field is induced by the applicator positioned within the biological tissue with cancer. In addition, in order to estimate the degree of tumor destruction under the influence of high temperature an Arrhenius integral has been used. The distribution of electric potential in the domain considered is described by the Laplace system of equations, while the temperature field is described by the Pennes system of equations. These problems are coupled by source function being the additional component in the Pennes equation and resulting from the electric field action. The boundary element method is applied to solve the coupled problem connected with the heating of biological tissues.The article presents the mathematical modeling of the phenomenon of artificial hyperthermia which is caused by the interaction of an electric field. The electric field is induced by the applicator positioned within the biological tissue with cancer. In addition, in order to estimate the degree of tumor destruction under the influence of high temperature an Arrhenius integral has been used. The distribution of electric potential in the domain considered is described by the Laplace system of equations, while the temperature field is described by the Pennes system of equations. These problems are coupled by source function being the additional component in the Pennes equation and resulting from the electric field action. The boundary element method is applied to solve the coupled problem connected with the heating of biological tissues.
Double-Mass Curves

The double mass curve is used to check the consistency of many kinds of Jiydrologic data by comparing data for a single station with that of a pattern composed of the data from several other stations in the area. The double-mass curve can be used to adjust inconsistent precipitation data. The graph of the cumulative data of one variable versus the cumulative data of a related variable is a straight line so long as the relation between the variables is a fixed ratio. Breaks in the double-mass curve of such variables are caused by changes in the relation between the variables. These changes may be due to changes in the method of data collection or to physical changes that affect the relation. Applications of the double-mass curve to precipitation, streamflow, and sediment data, and to precipitation-runoff relations are described. A statistical test for significance of an apparent break in the slope of the double-mass curve is described by an example. Poor correlation between the variables can prevent detection of inconsistencies in a record, but an increase in the length of record tends to offset the effect of poor correlation. The residual-mass curve, which is a modification of the double-mass curve, magnifies imperceptible breaks in the double-mass curve for detailed study. Of the several methods of fitting a smooth curve to cyclic or periodic data, the moving-arc method and the double-integration method deserve greater use in hydrology. Both methods are described in this manual. The moving-arc method has general applicability, and the double integration method is useful in fitting a curve to cycles of sinusoidal form.
Bypassing shake, rattle and roll

The Tacoma Narrows Bridge is perhaps the most famous example of a bridge that collapsed unexpectedly in response to external forces. But new "wave bypass" technology – similar to that underpinning invisibility cloaks – could help avoid such disasters, as Michele Brun, Alexander Movchan, Ian Jones and Ross McPhedran explain.
KOF Working Papers

In this paper, we revisit the association between happiness and inequality. We argue that the perceived fairness of the income generation process affects this association. Building on a two-period model of individual life-time utility maximization, we predict that persons with higher perceived fairness will experience higher levels of life-time utility and are less in favor of income redistribution. In societies with a high level of actual social mobility, income inequality is perceived more positively with increased expected fairness. The opposite is expected for countries with low actual social mobility, due to an increasing relevance of a disappointment effect resulting from unsuccessful individual investments. Using the World Values Survey data and a broad set of fairness measures, we find strong support for the negative (positive) association between fairness perceptions and the demand for more equal incomes (subjective well-being). We also find strong empirical support for the disappointment effect in low social mobility countries. In contrast, the results for high-mobility countries turn out to be ambiguous.
Reinterpreting the Priddy Long Barrow, Mendip Hills, Somerset

The Priddy Long Barrow was partially excavated by UBSS in 1928, the first long barrow excavation to be undertaken by the Society. A very short report detailing some of the findings was published by Phillips and taylor in 1972 (with editor's comments), when it was suggested to be an artificial mound containing human bone of Late Neolithic date. Few other conclusions were drawn but intriguing details suggested that this was a complex monument, worthy of re-analysis. This paper details the results of an examination of the site archive and offers a new interpretation of the monument. It is argued that the Priddy long barrow is a non-megalithic long barrow dating to the Early Neolithic period. At least four phases of activity and construction are suggested. new information on the finds, destroyed during World War II, is also given amd new plans presented.
Effects of Crowding on the Social Behavior of Cuttlefish ( Sepia officinalis )

To evaluate the effect of crowding on cuttlefish ( Sepia officinalis ), a benthic cephalopod, the behavior of captive-reared cuttlefish was monitored for a period of 1 month . One group of 6 cuttlefish was housed in a tank 6.1 m in diameter (4.87 m 2 per cuttlefish); another group of 6 was housed in a tank 1.5 m in diameter (0.29 m 2 per cuttlefish). Cuttlefish spaced themselves within each tank so as to avoid other cuttlefish. Those in the small tank hovered more and sat on the bottom less, showed more zebra patterns and Intense Zebra Displays (associated with aggression), ate less food, and were displaced by other cuttlefish 3 times as often as those in the large tank. Most aggression resulting in displacement was directed at females by males and sometimes resulted in physical injury to the females. Subjects’ body patterns were highly predictable, using the following variables: activity, sex, tank, and number of nearby cuttlefish. Analysis of results indicated that behavior was strongly affected by housing conditions and suggested that this species is probably semi-solitary in natural conditions.
The Graphical Query Language: a tool for analysis of gene expression time-courses

UNLABELLED The Graphical Query Language (GQL) is a set of tools for the analysis of gene expression time-courses. They allow a user to pre-process the data, to query it for interesting patterns, to perform model-based clustering or mixture estimation, to include subsequent refinements of clusters and, finally, to use other biological resources to evaluate the results. Analyses are carried out in a graphical and interactive environment, allowing expert intervention in all stages of the data analysis. AVAILABILITY The GQL package is freely available under the GNU general public license (GPL) at http://www.ghmm. org/gql
Data and text mining CFinder : locating cliques and overlapping modules in biological networks

Summary:Most cellular tasks are performednot by individual proteins, but by groups of functionally associated proteins, often referred to as modules. In a protein assocation network modules appear as groups of densely interconnected nodes, also called communities or clusters. These modules often overlap with each other and form a network of their own, in which nodes (links) represent the modules (overlaps). We introduce CFinder, a fast program locating and visualizing overlapping, densely interconnected groups of nodes in undirected graphs, and allowing the user to easily navigate between the original graph and thewebof thesegroups.Weshow that in gene (protein) association networks CFinder can be used to predict the function(s) of a single protein and to discover novel modules. CFinder is also very efficient for locating the cliques of large sparse graphs. Availability: CFinder (for Windows, Linux and Macintosh) and its manual can be downloaded from http://angel.elte. hu/clustering. Supplementary information: Supplementary data are available on Bioinformatics online. Contact: cfinder@angel.elte. hu
X-PACS: eXPlaining Anomalies by Characterizing Subspaces

Anomaly detection has numerous critical applications in finance, security, etc. and has been vastly studied. In this paper, we tap into a gap in the literature and consider a complementary problem: anomaly description. Interpretation of anomalies has important implications for decision makers, from being able to troubleshoot and prioritize their actions to making policy changes for prevention. We present a new method called X-PACS which “reverse-engineers” the known anomalies in a dataset by identifying a few anomalous patterns that they form along with the characterizing subspace of features that separates them from normal instances. From a descriptive data mining perspective, our solution has five key desired properties. It can unearth anomalous patterns (i) of multiple different types, (ii) hidden in arbitrary subspaces of a high dimensional space, (iii) interpretable by the end-users, (iv) succinct, providing the shortest data description, and finally (v) different from normal patterns of the data. There is no existing work on anomaly description that satisfy all of these desiderata simultaneously. While not our primary goal, anomalous patterns X-PACS finds can further be seen as multiple, interpretable ‘signatures’ and can be used for detection. We show the effectiveness of X-PACS in explanation as well as detection tasks on 9 real-world datasets.
Funding Liquidity, Market Liquidity and TED Spread: A Two-Regime Model

We study the effect of market liquidity on equity-collateralized funding, accounting for endogeneity. Theory suggests market liquidity can affect funding liquidity in stabilizing and destabilizing manners. Using a new proxy for equity-collateralized funding liquidity of S&P 500 stocks over the period of July 2006–May 2011, we show that we can separate the two regimes using the yield spread of Eurodollars over T-bills (TED spread) and that a regime switch occurs near a TED spread of 48 basis points.
Local to regional methane emissions from the Upper Silesia Coal Basin (USCB) quantified using UAV-based atmospheric measurements

Abstract. Coal mining accounts for ~ 12 % of the total anthropogenic methane emissions worldwide. The Upper Silesian Coal Basin, Poland, where large quantities of CH4 are emitted to the atmosphere via ventilation shafts of underground hard coal (anthracite) mines, is one of the hot spots of methane emissions in Europe. However, coalbed CH4 emissions into the atmosphere are poorly characterized. As part of the Carbon Dioxide and CH4 mission 1.0 (CoMet 1.0) that took place in May – June 2018, we flew a recently developed active AirCore system aboard an unmanned aerial vehicle (UAV) to obtain CH4 and CO2 mole fractions 150–300 m downwind of five individual ventilation shafts in the USCB. In addition, we also measured δ13C-CH4, δ2H-CH4, ambient temperature, pressure, relative humidity, surface wind speeds and directions. We have used 34 UAV flights and two different approaches (inverse Gaussian approach and mass balance approach) to quantify the emissions from individual shafts. The quantified emissions were compared to both annual and hourly inventory data, and were used to derive the estimates of CH4 emissions in the USCB. We found a high correlation (R2 = 0.7 – 0.9) between the quantified and hourly inventory data-based shaft-averaged CH4 emissions, which in principle would allow regional estimates of CH4 emissions to be derived by upscaling individual hourly inventory data of all shafts. Currently, such inventory data is available only for the five shafts we quantified though. As an alternative, we have developed three upscaling approaches, i.e., by scaling the E-PRTR annual inventory, the quantified shaft-averaged emission rate, and the shaft-averaged emission rate that are derived from the hourly emission inventory. These estimates are in the range of 325 – 447 kt CH4/year for the inverse Gaussian approach and 268 – 347 kt CH4/year for the mass balance approach, respectively. This study shows that the UAV-based active AirCore system can be a useful tool to quantify local to regional point source methane emissions.
GECKO: Reconciling Privacy, Accuracy and Efficiency in Embedded Deep Learning

Embedded systems demand on-device processing of data using Neural Networks (NNs) while conforming to the memory, power and computation constraints, leading to an efficiency and accuracy tradeoff. To bring NNs to edge devices, several optimizations such as model compression through pruning, quantization, and off-the-shelf architectures with efficient design have been extensively adopted. These algorithms when deployed to real world sensitive applications, requires to resist inference attacks to protect privacy of users training data. However, resistance against inference attacks is not accounted for designing NN models for IoT. In this work, we analyse the three-dimensional privacy-accuracy-efficiency tradeoff in NNs for IoT devices and propose Gecko training methodology where we explicitly add resistance to private inferences as a design objective. We optimize the inference-time memory, computation, and power constraints of embedded devices as a criterion for designing NN architecture while also preserving privacy. We choose quantization as design choice for highly efficient and private models. This choice is driven by the observation that compressed models leak more information compared to baseline models while off-the-shelf efficient architectures indicate poor efficiency and privacy tradeoff. We show that models trained using Gecko methodology are comparable to prior defences against black-box membership attacks in terms of accuracy and privacy while providing efficiency.
A novel theoretical model for the temperature dependence of band gap energy in semiconductors

We report a novel theoretical model without any fitting parameters for the temperature dependence of band gap energy in semiconductors. This model relates the band gap energy at the elevated temperature to that at the arbitrary reference temperature. As examples, the band gap energies of Si, Ge, AlN, GaN, InP, InAs, ZnO, ZnS, ZnSe and GaAs at temperatures below 400 K are calculated and are in good agreement with the experimental results. Meanwhile, the band gap energies at high temperatures (T > 400 K) are predicted, which are greater than the experimental results, and the reasonable analysis is carried out as well. Under low temperatures, the effect of lattice expansion on the band gap energy is very small, but it has much influence on the band gap energy at high temperatures. Therefore, it is necessary to consider the effect of lattice expansion at high temperatures, and the method considering the effect of lattice expansion has also been given. The model has distinct advantages compared with the widely quoted Varshni’s semi-empirical equation from the aspect of modeling, physical meaning and application. The study provides a convenient method to determine the band gap energy under different temperatures.
Global stability of traveling wave fronts for a reaction–diffusion system with a quiescent stage on a one-dimensional spatial lattice

ABSTRACT This paper is concerned with the stability of traveling wave fronts for a coupled system of non-local delayed lattice differential equations with a quiescent stage. It shows that under certain conditions all non-critical traveling wave fronts are globally exponentially stable, and critical ftraveling wave fronts are globally algebraically stable by applying the weighted energy method and the semi-discrete Fourier transform.
Mathematical Modelling of Batch Distillation Columns: A Comparative Analysis of Non-Linear and Fuzzy Models

Distillation is the process most commonly used in industry to separate chemical mix- tures; its applications range from cosmetic and pharmaceutical to petrochemical indus-tries. The equipment required to perform the distillation process is known as distillation column. Since initial investment and maintenance costs for distillation columns are very high it is necessary to have an appropriate mathematical model that allows improving the comprehension of the column dynamics, especially its thermal behaviour, in order to enhance the control and safety of the process. This chapter presents a general panorama of the mathematical modelling of distillation columns, having as a specific case of study the comparison of a space-state non-linear model and a Takagi-Sugeno fuzzy model for a batch distillation column using a binary mixture (Ethanol-Water).
The Influence of Developments in Tissue Engineering and Regenerative Medicine on Healthcare Advancement and Evolution

The area of regenerative therapy will undergo a revolution thanks to 3D bioprinting, which holds enormous potential for the bioprinting of artificial tissue and organs. The present research explores the potential sy - nergies between 3D bioprinting and current developments in tissue engineering and regenerative medicine. Before 3D bioprinting is extensively used in organotypic structures for regenerative medicine, a number of obstacles must be solved. This places a significant burden on society in terms of providing care for those who have deteriorating organs and debilitating diseases. Researchers and medical experts are developing medications and technology that can repair tissues and even generate fresh ones in order to solve this problem. Tissue engineering and regenerative medicine strive to create new tissues and organs while also curing damaged or sick ones by fusing technology and biological principles. substantial breakthroughs in these domains have a substantial influence on 3D bioprinting of tissues and organs. The area of regenerative medicine might undergo a radical transformation thanks to the use of 3D bioprinting, which makes it possible to build new tissues and organs. The relationship between recent developments in tissue engineering, 3D bioprinting, and regenerative medicine is investigated in this paper. Before 3D bioprinting can be widely used to produce organotypic structures for regenerative medicine, a number of problems must be overcome.
Time-Varying Wind Load Identification Based on Minimum-Variance Unbiased Estimation

A minimum-variance unbiased estimation method is developed to identify the time-varying wind load from measured responses. The formula derivation of recursive identification equations is obtained in state space. The new approach can simultaneously estimate the entire wind load and the unknown structural responses only with limited measurement of structural acceleration response. The fluctuating wind speed process is investigated by the autoregressive (AR) model method in time series analysis. The accuracy and feasibility of the inverse approach are numerically investigated by identifying the wind load on a twenty-story shear building structure. The influences of the number and location of accelerometers are examined and discussed. In order to study the stability of the proposed method, the effects of the errors in crucial factors such as natural frequency and damping ratio are discussed through detailed parametric analysis. It can be found from the identification results that the proposed method can identify the wind load from limited measurement of acceleration responses with good accuracy and stability, indicating that it is an effective approach for estimating wind load on building structures.
Electroacupuncture in Treatment of Acute Gastrointestinal Injury in Patients with Severe Traumatic Brain Injury: A Multicenter Randomized Controlled Trial

ABSTRACT ObjectiveObjective : To evaluate whether electroacupuncture (EA) would improve gastrointestinal function : To evaluate whether electroacupuncture (EA) would improve gastrointestinal function and clinical prognosis in patients with severe traumatic brain injury (TBI) 28-d The secondary endpoints serum levels of D-lactic acid diamine oxidase (DAO), lipopolysaccharide (LPS), motilin (MTL) and intra-abdominal diamine oxidase (DAO), lipopolysaccharide (LPS), motilin (MTL) and gastrin (GAS), intra-abdominal pressure (IAP), bowel sounds, abdominal circumference, AGI grade, scores of gastrointestinal failure pressure (IAP), bowel sounds, abdominal circumference, AGI grade, scores of gastrointestinal failure Glasgow Coma Scale (GCS), Acute Physiology and Chronic Health Evaluation (APACHE Sequential Organ Glasgow Coma Scale (GCS), Acute Physiology and Chronic Health Evaluation (APACHE Sequential Organ Failure Assessment (SOFA), and Multiple Organ Dysfunction Syndrome mechanical time, Failure Assessment (SOFA), and Multiple Organ Dysfunction Syndrome lower acupuncture at GIF, APACHE Ⅱ , MODS D-lac, the acupuncture showed lower GIF, APACHE Ⅱ , SOFA, MODS scores, D-lac, DAO, LPS, IAP, and abdominal circumference and higher GCS score, MTL, GAS, and bowel sound frequency (all DAO, LPS, IAP, and abdominal circumference and higher GCS score, MTL, GAS, and bowel sound frequency P<0.05). In addition, the above indices showed simillar changes at 7 d compared with days 1 and 3 (all <0.05). In addition, the above indices showed simillar changes at 7 d compared with days 1 and 3 (all P<0.05) <0.05) in the EA group. in the EA group. ConclusionConclusion : Early EA can improve gastrointestinal function and clinical prognosis in patients : Early EA can improve gastrointestinal function and clinical prognosis in patients with severe TBI complicated by AGI. (Registration No. ChiCTR2000032276) with severe TBI complicated by AGI. (Registration No. ChiCTR2000032276)