Miracle-dz/UniFAR-FTUs huggingface dataset:
Acts of God and Man: Ruminations on Risk and Insurance

Much has been written about the ups and downs of financial markets, from the lure of prosperity to the despair of crises. Yet a more fundamental and pernicious source of uncertainty exists in today's world: the traditional "insurance" risks of earthquakes, storms, terrorist attacks, and other disasters. Insightfully exploring these "acts of God and man," Michael R. Powers guides readers through the methods available for identifying and measuring such risks, financing their consequences, and forecasting their future behavior within the limits of science. A distinctive characteristic of earthquakes, hurricanes, bombings, and other insurance risks is that they impact the values of stocks, bonds, commodities, and other market-based financial products, while remaining largely unaffected by or "aloof" from the behavior of markets. Quantifying such risks given limited data is difficult yet crucial for achieving the financing objectives of insurance. Powers begins with a discussion of how risk impacts our lives, health, and possessions and proceeds to introduce the statistical techniques necessary for analyzing these uncertainties. He then considers the experience of risk from the perspectives of both policyholders and insurance companies, and compares their respective responses. The risks inherent in the private insurance industry lead naturally to a discussion of the government's role as both market regulator and potential "insurer of last resort. " Following a thoughtful and balanced analysis of these issues, Powers concludes with an interdisciplinary investigation into the nature of uncertainty, incorporating ideas from physics, philosophy, and game theory to assess science's limitations in predicting the ramifications of risk.
Impairments in High-Frequency Transmission, Synaptic Vesicle Docking, and Synaptic Protein Distribution in the Hippocampus of BDNF Knockout Mice

Brain-derived neurotrophic factor (BDNF) promotes long-term potentiation (LTP) at hippocampal CA1 synapses by a presynaptic enhancement of synaptic transmission during high-frequency stimulation (HFS). Here we have investigated the mechanisms of BDNF action using two lines of BDNF knockout mice. Among other presynaptic impairments, the mutant mice exhibited more pronounced synaptic fatigue at CA1 synapses during high-frequency stimulation, compared with wild-type animals. Quantitative analysis of CA1 synapses revealed a significant reduction in the number of vesicles docked at presynaptic active zones in the mutant mice. Synaptosomes prepared from the mutant hippocampus exhibited a marked decrease in the levels of synaptophysin as well as synaptobrevin [vesicle-associated membrane protein (VAMP-2)], a protein known to be involved in vesicle docking and fusion. Treatment of the mutant slices with BDNF reversed the electrophysiological and biochemical deficits in the hippocampal synapses. Taken together, these results suggest a novel role for BDNF in the mobilization and/or docking of synaptic vesicles to presynaptic active zones.
Immunohistochemical Localization of the Bradykinin B1 and B2 Receptors in Human Nasal Mucosa

Bradykinin (BK) has been tobe thought a potent mediator involved in allergic rhinitis because BK was recovered from the nasal lavage fluid of allergic rhinitis patients after allergen provocation and BK receptor antagonists relief nasal allergic symptoms. Two mammalian BK receptor subtypes, B1 and B2, have been defined based on their pharmacological properties. We investigated the localization of these receptors by immunohistochemistry. Human turbinates were obtained after turbinectomy from 12 patients with nasal obstruction refractory to medical therapy. The immunohistochemical study revealed that epithelial cells, submucosal glands, fibroblast, vascular smooth muscle, vascular endothelial cells, and macrophages showed immunoreactivity for both B1 and B2 receptors. The B2 receptor expression was found in peripheral nerve fibers, whereas the B1 expression was not observed in nerves. The results may have an important clinical implication for understanding the differential roles of BK receptor subtypes on upper airway diseases such as allergic rhinitis and nonallergic rhinitis.
The Design of High Gain Dipole Antenna with Metamaterial Cover

In this paper, we analyze a metamaterial cover based on metal wire array, and use it to increase the gain of dipole from 2.15 dB to 14.5 dB, with narrow beam and low side-lobe levels. And then provide the use of metal strips etched by printed circuit board (PCB) process to substitute the metal wires in order to reduce the weight and be easy in processing. The structure of metal strip array can also greatly increase the gain of dipole and possess good practical engineering application.
CCA Fuzzy Land Cover: a new method for classifying vegetation types and coverages and its implications for deforestation analysis

Land cover has been evaluated and classified on the basis of general features using reflectance or digital levels of photographic or satellite data. One of the most common methodologies based on CORINE land cover (Coordination of Information on the Environment) data, which classifies natural cover according to a small number of categories. This method produces generalizations about the inventoried areas, resulting in the loss of important floristic and structural information about vegetation types present (such as palm groves, tall dense mangroves, and dense forests). This classification forfeits relevant information on sites with high heterogeneity and diversity. Especially in the tropics, simplification of coverage types reaches its maximum level with the use of deforestation analysis, particularly when it is reduced to the two classes of forests and nonforests. As this paper demonstrates, these results have considerable consequences for political efforts to conserve the biodiversity of megadiverse countries. We designed a new methodological approach that incorporates biological distinctiveness combined with phytosociological classification of vegetation and its relation to physical features. This approach is based on parameters obtained through canonical correspondence analysis on a fuzzy logic model, which are used to construct multiple coverage maps. This tool is useful for monitoring and analyzing vegetation dynamics, since it maintains the typological integrity of a cartographic series. The methodology creates cartographic series congruent in time and scale, can be applied to multiple and varied satellite inputs, and always evaluates the same model parameters. We tested this new method in the southwestern Colombian Caribbean region and compared our results with those from what we believe are outdated tools used in other analyses of deforestation around the world.
Structural Examination of 6-Methylsulphonylphenanthro-[9,10-C]-furan-1(3H)-one—A Rofecoxib Degradation Product

In the attempt to discover a new polymorph of rofecoxib (Vioxx®), an unexpected product resulted. The product was characterised by chemical composition, thermal behaviour and structure and found to be 6-methylsulphonylphenanthro-[9,10-C] furan-1(3H)-one, a photo-cyclization degradation product of rofecoxib. This is a significant finding because it indicates that without appropriate control of the recrystallisation procedures, the structural integrity of rofecoxib may be seriously compromised.
Reconstruction of erythemal UV-doses for two stations in Austria: a comparison between alpine and urban regions

The aim of this study is the reconstruction of past UV-doses for two stations in Austria, Hoher Sonnblick and Vienna, using a physical radiation transfer model. The method uses the modeled UV-dose under clear-sky conditions, cloud modification factors and a correction factor as input variables. To identify the influence of temporal resolution of input data and modification factors, an ensemble of four different modelling approaches was calculated, each with hourly or daily resolution. This is especially important because we found no other study describing the influence of the temporal resolution of input data on model performance. Following the results of the statistical analysis of the evaluation period the model with the highest temporal resolution (HMC) was chosen for the reconstruction of UV-doses. A good agreement between modelled and measured values of erythemally effective UV-doses was found at both stations. In relation to the reference period 1976–1985 an increase in the erythemal UV-dose in Vienna of 11% is visible in the period 1986–1995 and an increase of 17% in the period 1996–2005 can be seen. At Hoher Sonnblick the corresponding increase is 2% and 9%. For the different seasons the strongest increase in erythemal UV-dose has been found for winter and spring season at both stations. Further the influences of total ozone and cloudiness on changes in erythemal UV-doses were analyzed. This analysis showed for both stations, that changes in total ozone had a larger influence on erythemal UV-doses than changes in cloudiness.
Decomposition of POLSAR Image Applied to Wet Land Monitoring

A scheme for four-component scattering power decomposition has been developed for polarimetric SAR image analysis based on the coherency matrix. The four-component consists of surface scattering, double bounce scattering, volume scattering, and helix scattering power. This decomposition scheme is applied to the Land X-band polarimetric data acquired by the airborne Pi-SAR system and is used to monitor seasonal change of wetland area, a lake “SAKATA” in Niigata, Japan. It is shown that the four-component powers represent typical seasonal feature of vegetation near by the lake.
The Information Content of Quarterly Dividend Changes

This paper shows that dividend changes reveal new information about future earnings levels and are mixed with regard to future earnings variance. Revisions of Value Line earnings forecasts spanning up to five quarters have a positive association with unexpected dividend changes. Consistent with the negative association documented between dividend changes and future earnings variance, these revisions also exhibit greater cross-sectional dispersion following dividend decreases than following dividend increases. The relation between stock returns and earnings forecast errors following dividend announcements shows that dividend announcements convey information to the market about earnings in the next quarter and the quarter one year hence, but are not consistent with dividends revealing new information about the variance of future earnings.
EFFECTS OF CANNABIDIOL AND CANNABIS EXTRACTS IN MODELS OF CONVULSION AND EXCITOTOXICITY

Science is a wonderful thing if one does not have to earn one's living at it. Introduction 1 INTRODUCTION Cannabis sativa L. Cannabis sativa is an herb that has been used by humans for millenniums for its fibre, known as hemp, for its psychological and physiological effects and for the nourishment of its oil-bearing seeds. The fibre of the plant, cultivated as hemp, has numerous textile uses. Its seed is a valuable source of protein and unsaturated oils. The flowers (and to a lesser extent the leaves and stems) contain psychoactive and physiologically active chemical compounds known as cannabinoids that are consumed for recreational, medicinal, and spiritual purposes. When so used, preparations of flowers (marijuana) and leaves and preparations derived from resinous extract (hashish) are consumed by smoking, vaporizing and oral ingestion. The major biologically active chemical compound in Cannabis is Δ-9-tetrahydrocannabinol, commonly referred to as THC. The major difference between the variety grown for industrial use and the one primarily used for production of recreational and medicinal drugs, is the amount of Δ-9-tetrahydrocannabinol (THC) secreted in a resinous mixture by epidermal hairs called glandular trichomes. Ingestion of Cannabis sativa preparations results in an intoxication characterized by sedation, cognitive dysfunction, failure to consolidate short-term memory, alteration in time assessment, perceptual changes, motor in-coordination and poor executive function Most of these effects are due to the action of THC, the main psychoactive substance found in the Cannabis plant. THC was isolated by Raphael Mechoulam and co-workers in 1964, and its mechanism of action was disclosed in 1990, when the first cannabinoid receptor (CB 1) was cloned (Matsuda et al., 1990) In fact many of the pharmacological actions of THC result from its binding to the cannabinoid receptor CB 1. The four symptoms that are often used to define cannabinoid intoxication in the rodent-hypothermia, rigid immobility, Introduction 2 analgesia and decreased motor activity (Adams and Martin, 1996)-are absent in mice in which the cb1 gene has been deleted by targeted recombination (Ledent et al., 1999; Zimmer et al., 1999). Cannabinoids are the most distinctive and specific class of compounds known to exist only in the cannabis plant. They are a group of terpenophenolic compounds, with very low solubility in water, but good solubility in most organic solvents. Other natural cannabinoids are cannabinol (CBN), cannabidiol (CBD), one of the most promising cannabinoid the researchers are investigating on, cannabigerol (CBG), cannabichromene (CBC), and delta-8-tetrahydrocannabinol …
P 2 P Decentralized Population Census

We describe a framework and investigate techniques for running decentralized census processes that enable observers to independently verify governmental data. Census is a process impacting important issues such as the amount of funding that a community will get from a central government and its representation in the Congress. Correct census is essential for detecting vote stuffing. Census has been historically run by governments, but citizens and NGOs need to be able to verify it. Classical census is expensive and beyond the reach of these players, hence the need for affordable citizen-driven census technology. Various citizens have different opinions as to what information should be gathered and what makes a person eligible to be accounted for in statistics. Using as inputs the official preferences of a given government should enable the verification of the data of that government. The reported work formalizes this problem and introduces a framework and techniques for running a fully decentralized citizen-driven census based on peer-to-peer technology. An addressed challenge is to quantify the uncertainty and the trust in the data provided by P2P users, as well as to develop techniques for reducing this uncertainty. We report on techniques to reason and to extract census-related conclusions based on the available data. Probabilistic models with various approximations are experimented for evaluating the census results in this context.
Efficient contour shape description by using fractal interpolation functions

This paper presents a novel representation method for contour shape using fractal interpolation functions (FIF). In the traditional idea of the FIF, the scope of its application has been limited to the case where the signal is represented by a single-valued function. Therefore, the traditional FIF cannot be applicable to multiple-valued signals. The proposed method can model a multiple-valued signal with an extended FIF derived by introducing new parameters to the traditional one. Furthermore, the proposed method utilizes the fractal dimension known as a measure of complexity to determine the parameters in the FIF and thereby can model the signal based on its complexity. Experimental results show the validity of the proposed method.
Assessment of Urinary Interleukin-18 and Serum Amyloid A Efficacies against C-Reactive Protein in Diagnosis and Follow-up of Neonatal Sepsis

Objective: infection is a leading cause of morbidity and mortality in neonates. The aim of this study was to evaluate the diagnostic and prognostic performances of urinary interleukin-18 (uIL-18) and serum amyloid A (SAA) in neonatal sepsis parallel to C- reactive protein (CRP). Subjects and methods: A total of 275 neonates were included in this case-control study. This study was conducted in neonatal intensive care unit at both Minia University Hospital for obstetric and pediatrics as well as Qena University hospital (Egypt). Among those 275 neonates, 150 non septic neonates - who had neither clinical signs nor laboratory findings suggestive of sepsis - were involved as a non-septic control group (Group II) and 125 septic neonates were classified as a septic group (group I). Blood and urine samples were obtained before initiation of antibiotic therapy. Full sepsis screen was performed at the time of sepsis onset plus measurement of SAA and uIL-18 by Enzyme Immune Assay (EIA). A second blood and urine samples were collected 72 hours later. The effectiveness of these 3 biomarkers as diagnostic ones was determined by using receiver operating characteristic (ROC) curve analysis. We also calculated the sensitivity, specificity, and positive, and negative predictive values. Results: The levels of uIL-18 and SAA were significantly elevated in septic neonates than in control group. The two markers showed significant decrease in their levels after 72 hours which matched with clinical improvement but not CRP. Moreover, very high levels of these markers were observed in neonates who died later on. The area under ROC curve (AUC) was used to evaluate the diagnostic efficacies of these markers. The superiority of SAA over both uIL-18 and CRP was obvious in the diagnosis of neonatal sepsis [AUC: 0.995] versus [AUC: 0.934 (uIL-18) and 0.871 (CRP)]. However in discriminating late onset sepsis (LOS), both uIL-18 and SAA have equal diagnostic capacities [AUC: 44 0.991] which are better than that of CRP [AUC: 0.866]. As to EOS, SAA has the most efficient performance as well but CRP is advanced than uIL-18. The specificities and sensitivities of either SAA or uIL-18 were higher than that of CRP in differentiating neonatal sepsis mainly LOS from controls. Conclusion: Both uIL-18 and SAA have enhanced performance over CRP for distinguishing neonatal sepsis mostly for LOS. Thus, they could be promising biomarkers for the screening and follow up of neonatal sepsis. This warrants further assessment of their prognostic values.
Cortical lesions in multiple sclerosis: inflammation versus neurodegeneration.

Demyelinated lesions in the cerebral cortex and cortical atrophy have recently been recognized as important components of multiple sclerosis pathology. Although it has consistently been recognized in studies on the pathology of multiple sclerosis that demyelination may not only affect white matter but also the cortex and deep grey matter nuclei (Brownell and Hughes, 1962; Lumsden, 1970; Kidd et al. , 1999; Cifelli et al. , 2002), only the application of modern techniques for immunocytochemical detection of myelin antigen has revealed its extent, particularly in patients who died during the progressive stage of the disease (Peterson et al. , 2001; Kutzelnigg et al. , 2005). Three types of cortical lesions have been identified: combined cortico/subcortical lesions, perivascular intracortical lesions and band-like subpial lesions, which affect the cerebral cortex over several adjacent gyri and sulci (Bo et al. , 2003 a ). In particular, the subpial lesions can be very extensive, affecting >60% of the cortical ribbon in the cerebrum (Kutzelnigg et al. , 2005), the cerebellum (Kutzelinigg et al. , 2007) and the hippocampus (Geurts et al. , 2007). In the early descriptions of cortical lesions in patients with progressive disease, it was emphasized that they differ from white matter lesions by the absence of perivascular and parenchymal infiltrates of T- and B-lymphocytes, vascular inflammation and blood–brain barrier …
Youth at Risk for Obesity Show Greater Activation of Striatal and Somatosensory Regions to Food

Obese humans, compared with normal-weight humans, have less striatal D2 receptors and striatal response to food intake; weaker striatal response to food predicts weight gain for individuals at genetic risk for reduced dopamine (DA) signaling, consistent with the reward-deficit theory of obesity. Yet these may not be initial vulnerability factors, as overeating reduces D2 receptor density, D2 sensitivity, reward sensitivity, and striatal response to food. Obese humans also show greater striatal, amygdalar, orbitofrontal cortex, and somatosensory region response to food images than normal-weight humans do, which predicts weight gain for those not at genetic risk for compromised dopamine signaling, consonant with the reward-surfeit theory of obesity. However, after pairings of palatable food intake and predictive cues, DA signaling increases in response to the cues, implying that eating palatable food contributes to increased responsivity. Using fMRI, we tested whether normal-weight adolescents at high- versus low-risk for obesity showed aberrant activation of reward circuitry in response to receipt and anticipated receipt of palatable food and monetary reward. High-risk youth showed greater activation in the caudate, parietal operculum, and frontal operculum in response to food intake and in the caudate, putamen, insula, thalamus, and orbitofrontal cortex in response to monetary reward. No differences emerged in response to anticipated food or monetary reward. Data indicate that youth at risk for obesity show elevated reward circuitry responsivity in general, coupled with elevated somatosensory region responsivity to food, which may lead to overeating that produces blunted dopamine signaling and elevated responsivity to food cues.
Diagnostics based principal component analysis for robust plane fitting in laser data

Plane fitting and obtaining characteristics (e.g., normal) from the estimated plane are fundamental tasks in many applications in which laser scanner 3D data is used. Unfortunately, laser data are not free from outliers. Principal Component Analysis (PCA) is a popular method for plane fitting, but it is known that PCA is very sensitive to outliers and gives misleading non-robust results. We present a robust plane fitting algorithm based on PCA coupled with an outlier detecting diagnostic statistical approach. In this method, the recently introduced robust scatter matrix is used to calculate robust statistical distance for finding outliers. After excluding outliers, PCA is performed on the outlier free data which is used for fitting planar surfaces and to estimate robust normal and other parameters. Demonstration of the new algorithm through several synthetic and vehicle based laser scanning data show that the proposed method is efficient, and gives robust estimates. Results outperform Least Squares (LS), PCA and are significantly better than the well-known RANSAC in terms of time, accuracy and robustness. This method has great potential for robust segmentation, surface reconstruction, and other point cloud processing tasks.
Zero- and low-bias control designs for active magnetic bearings

In this paper, we present several nonlinear control designs for a single one-degree-of-freedom (1-DOF) active magnetic bearing (AMB). The primary control objective is to globally asymptotically stabilize the mechanical states of an AMB while reducing the AMB power losses. This suggests operation with zero- or low-bias (ZB/LB) flux. We derive a flux-based model for an AMB using a generalized complementary flux condition. This condition is imposed both for ZB and LB operations. A convenient model structure results, in which the ZB mode is a special case of the more general LB mode of operation. We next derive control laws for LB and ZB AMB operation. The control designs borrow ideas from the theory of control Lyapunov functions (clfs) and passivity. The performance of each proposed control design is evaluated via numerical simulations with a high-fidelity AMB model. Implementation issues are also discussed.