Miracle-dz/UniFAR-FTUs huggingface dataset:
TFR: A Tourist Food Recommender System based on Collaborative Filtering

A Nowadays using recommender systems (systems that help you to choose something) is so widespread that we can say their usage is one of the most vital necessities of human being. These systems have been made to help the users to choose the best alternative on the basis of their preferences. On the other hand, in the tourism industry, as one of the most profit-making industries, most tourists are not familiar with the foods of the countries that they have travelled to, so it is possible that they choose a kind of food that they don’t like or it is dangerous for their health because of possible disease that they suffer from. In this paper, a system is proposed for solving this problem of tourism industry, called TFR. The purpose of this system is to recommend foods to tourists according to their preferences. Moreover, TFR is able to recommend a special food to a tourist in case he/she has a special diet. To evaluate the presented system which is based on collaborative filtering, it has been used by some real users. The results show that the accuracy of TFR is 86.3%, indicating the suitable efficiency of the system.
A Damage Level Assessment Model for Extra High Voltage Transmission Towers

: Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.
Circle actions on simply connected 4-manifolds

Locally smooth S'-actions on simply connected 4-manifolds are studied in terms of their weighted orbit spaces. An equivariant classification theorem is proved, and the weighted orbit space is used to compute the quadratic form of a given simply connected 4-manifold with S '-action. This is used to show that a simply connected 4-manifold which admits a locally smooth 5'-action must be homotopy equivalent to a connected sum of copies of S4, CP2, - CP2, and S2 x S2.
Prescription Opioids and Labor Market Pains: The Effect of Schedule II Opioids on Labor Force Participation and Unemployment

ABSTRACT:We examine the effect of prescription opioids on county labor market outcomes, using data from the Prescription Drug Monitoring Programs of ten U.S. states and labor data from the Bureau of Labor Statistics. We achieve causal identification by exploiting plausibly exogenous variation in the concentration of high-volume prescribers as instruments (using Medicare Part D prescriber data). We find strong adverse effects on labor force participation rates, employment-to-population ratios, and unemployment rates. Notably, a 10 percent increase in prescriptions causes a 0.53 percentage point reduction in labor force participation, similar to the drop attributed to the 1984 liberalization of Disability Insurance.
UvA-DARE ( Digital Academic Repository ) Efficient , almost exact simulation of the Heston stochastic volatility model

We deal with several efficient discretization methods for the simulation of the Heston stochastic volatility model. The resulting schemes can be used to calculate all kind of options and corresponding sensitivities, in particular the exotic options that cannot be valued with closed-form solutions. We focus on to the (computational) efficiency of the simulation schemes: though the Broadie and Kaya (2006) paper provided an exact simulation method for the Heston dynamics, we argue why its practical use might be limited. Instead we consider efficient approximations of the exact scheme, which try to exploit certain distributional features of the underlying variance process. The resulting methods are fast, highly accurate and easy to implement. We conclude by numerically comparing our new schemes to the exact scheme of Broadie and Kaya, the almost exact scheme of Smith, the Kahl-Jäckel scheme, the Full Truncation scheme of Lord et al. and the Quadratic Exponential scheme of Andersen.
Effects of competition on tree radial‐growth vary in importance but not in intensity along climatic gradients

1. Plant interactions play a central role in regulating plant communities and this role can be altered by abiotic stress. With increasing stress, ecological theory predicts that the role of competition decreases whilst that of facilitation increases. Such predictions have been tested with short‐term plant removal experiments using two distinct indices evaluating the role of plant interactions: the intensity (absolute impact) and the importance (impact relative to that of other abiotic constraints) of plant interactions.
PREVALENCE OF MEDIAL MENISCAL TEARS WITH ARTHROSCOPIC ASSISTED TIBIAL 1 PLATEAU LEVELING OSTEOTOMY 2 3

9 Objective: 10 To determine the incidence of medial meniscal tears in dogs with naturally occurring cranial cruciate 11 ligament (CCL) disease treated with arthroscopy and tibial plateau leveling osteotomy (TPLO). 12 Study design: 13 Retrospective case series 14 Sample population: 15 Canine Stifles (n=357) with naturally occurring CCL disease treated with arthroscopic assisted TPLO 16 Methods: 17 Medical records (November 2006 – November 2009) were reviewed for all dogs with CCL disease treated 18 with arthroscopic CCL debridement, meniscal probing and TPLO. We investigated the significance of the 19 preoperative variables; age, weight, tibial plateau angle (TPA), sex and the preoperative condition of the 20 CCL on the incidence of concurrent meniscal tears (CMT) and late onset meniscal tears (LMT). 21 Results: 22 The prevalence of CMT and LMT was 32.2% and 5.6% respectively. A significant difference between age of 23 those with CMT and those without was demonstrated. There was a significantly lower incidence of CMT and 24 LMT in patients that presented with a partial CCL tear, compared with those that presented with a complete 25 CCL tear. All patients with LMT treated with partial meniscectomy returned to peak postoperative limb 26 function following partial meniscectomy (PMM) based on client assessed outcomes. 27
A Study of Gaps in Network Knowledge Synthesis

Abstract : Network knowledge synthesis (NKS) refers to effective use of network defense information for cyber assessment and management. The vision of NKS is to achieve better informed situational awareness leading to superior cyber defense. Five major components are necessary to achieve this vision: sensor placement, data collection, data filtering, data analysis and sense making, and information sharing. By reviewing the state of the art for each of these components, we identify high-priority, short-term research objectives for NKS components, which include collection of small, indicative, and symptomatic network data; connecting identities at multiple layers; ensuring the authenticity of collected data; identifying the ideal semantic layer for each type of data; developing scalable and decentralized filters; developing fast analysis algorithms that can operate in a malicious environment; testing such algorithms in real-world networks; and sharing properly anonymized network knowledge rather than raw data. These efforts will constitute the basic blocks of an effective NKS system.
Para‐Hermitian Geometry, Dualities and Generalized Flux Backgrounds

We survey physical models which capture the main concepts of double field theory on para‐Hermitian manifolds. We show that the geometric theory of Lagrangian and Hamiltonian dynamical systems is an instance of para‐Kähler geometry which extends to a natural example of a Born geometry. The corresponding phase space geometry belongs to the family of natural almost para‐Kähler structures which we construct explicitly as deformations of the canonical para‐Kähler structure by non‐linear connections. We extend this framework to a class of non‐Lagrangian dynamical systems which naturally encodes the notion of fluxes in para‐Hermitian geometry. In this case we describe the emergence of fluxes in terms of weak integrability defined by the D‐bracket, and we extend the construction to arbitrary cotangent bundles where we reproduce the standard generalized fluxes of double field theory. We also describe the para‐Hermitian geometry of Drinfel'd doubles, which gives an explicit illustration of the interplay between fluxes, D‐brackets and different polarizations. The left‐invariant para‐Hermitian structure on a Drinfel'd double in a Manin triple polarization descends to a doubled twisted torus, which we use to illustrate how changes of polarizations give rise to different fluxes and string backgrounds in para‐Hermitian geometry.
Canonical quantization of the electromagnetic field interacting with a moving dielectric medium

The electromagnetic field is canonically quantized in the presence of a linear, dispersive, and dissipative medium that is in uniform motion. Specifically we calculate the change in the normal modes of the coupled matter-field system and find a Hamiltonian that contains negative-energy normal modes. We interpret these modes as the origin of phenomena such as quantum friction and find that a detector initially in its ground state and coupled to the electromagnetic field in the vicinity of, or within, a uniformly moving medium has a nonzero probability of excitation at $T=0$ K.
MORPHO-PHYSIOLOGICAL RESPONSES OF GRASS PEA (LATHYRUS SATIVUS L.) GENOTYPES TO SALT STRESS AT GERMINATION AND SEEDLING STAGES

Response of eight different grass pea (Lathyrus sativus L.) genotypes to salinity (0, 50, 100, 150 and 200 mM NaCl)-induced stress was studied at both germination and seedling growth stages. Among the genotypes, significant decrease in germination, dry weight, K content and accumulation of Na occurred in HL and LSP-1 from 100 mM and in BioR-231, BioR-202 and BioL-203 from 150 mM treatment. In contrast, nearly normal growth and dry weight in ML, B1 and BioL-212 even at 200 mM treatment might be attributed to maintenance of normal cellular equilibrium of K+/Na+ ratio and leaf photosynthetic pigments at elevated treatment level. This resulted in better tolerance of these three genotypes to high salt stress than the other five genotypes. On the basis of the performance, the treatment of 150 mM NaCl was detected as critical to most of the grass pea genotypes under salt stress.
Miscellanea : Evaluation of the haematocrit centrifuge and other techniques for the field diagnosis of human trypanosomiasis and filariasis

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Inflationary Finance and the Welfare Cost of Inflation

This paper applies previous theoretical and empirical results on inflation and demand for money to a study of inflationary finance and the welfare cost of inflation. The amount of revenue generated by a steady inflation is derived as a function of the inflation rate and some underlying parameters. Empirically, the revenue-maximizing rate is on the order of 140 percent per month with the corresponding revenue approximating 15 percent of national income. It is argued that hyper-inflations become unstable when the revenue-maximizing rate is exceeded. Because inflation leads to higher transaction costs (resulting from greater payment frequencies and reduced use of "money" as a payments medium), there is a net social cost attached to inflationary finance. The model implies that marginal collection costs of inflationary finance exceed 50 percent for all positive rates of inflation-hence, alternative means of raising revenue should be socially preferable. The analysis also provides estimates of the social gain from moving to the optimum quantity of money as 1-3 percent of income.
A Comparison of the Effects of Toys versus Live Animals on the Communication of Patients with Dementia of the Alzheimer's Type

Abstract The purpose of this study was to determine the effect of toy versus live cat stimuli on the verbal communication of elderly nursing home residents with dementia. The subjects' verbal communication was analyzed for total number of words, meaningful information units, and initiations. The measurements were recorded in three conditions: without stimuli, in the presence of two toy cats, and in the presence of two live cats. Six female nursing home residents with moderate dementia were randomly assigned into two groups to counterbalance the order of the conditions. The results indicated that live cats had the greatest influence on average subject performance across all three measurements.
Biomechanics of Cartilage and Osteoarthritis

PKB, NF-kB, and MAPK, which act to regulate gene expression, cell function and survival/apoptosis. The release and paracrine/autocrine activity of the anti-inflammatory cytokine IL-4 has beneficial effects in regulating an anabolic re‐ sponse with enhanced expression of aggrecan and inhibition of MMP expression. In contrast production of IL-1β, as seen in OA, has a catabolic outcome with activation of pathways resulting in increased expression of COX2 and MMPs.
Stochastic Decomposition for Two-Stage Stochastic Linear Programs with Random Cost Coefficients

Stochastic decomposition (SD) has been a computationally effective approach to solve large-scale stochastic programming (SP) problems arising in practical applications. By using incremental sampling, this approach is designed to discover an appropriate sample size for a given SP instance, thus precluding the need for either scenario reduction or arbitrary sample sizes to create sample average approximations (SAA). When compared with the solutions obtained using the SAA procedure, SD provides solutions of similar quality in far less computational time using ordinarily available computational resources. However, previous versions of SD were not applicable to problems with randomness in second-stage cost coefficients. In this paper, we extend its capabilities by relaxing this assumption on cost coefficients in the second stage. In addition to the algorithmic enhancements necessary to achieve this, we also present the details of implementing these extensions, which preserve the computational edge of SD. Finally, we illustrate the computational results obtained from the latest implementation of SD on a variety of test instances generated for problems from the literature. We compare these results with those obtained from the regularized L-shaped method applied to the SAA function of these problems with different sample sizes.
Sediment and Shallow Coastal Water Detection Utilizing MODIS Land Channels over Gulf of Martaban

Application of clear waters (Case 1) algorithm to satellite imagery acquired with Moderate Resolution Imaging Spectroradiometer (MODIS) over turbid coastal waters (Case 2) often results in negative water-leaving radiances over extended areas. Also, the maximum reflectances for ocean color channels are significantly smaller than those for the land channels at similar wavelengths. Because of that, at the bright coastal water areas, ocean color channels (0.488, 0.531 and 0.551 µm) often saturate. The saturation of these channels will contribute to the lost of geophysical and biological activities in the data. So, in order to overcome this circumstance, it is reasonable to use MODIS land and atmosphere channels (1 to 7) to derive an algorithm for the detections of turbid and shallow coastal water areas. In order to improve chlorophyll retrieving algorithm over the ocean, an algorithm to mask out the turbid coastal water area needs to be developed. In this paper, a simple algorithm to identify and mask shallow coastal water and high amounts of suspended sediment area in the Gulf of Martaban using MODIS L1B image is suggested and demonstrated. This algorithm uses log10 ratio of two MODIS solar channels originally designed for remote sensing over land and cloud properties centered at 0.47 and 0.55 µm (bands 3 and 4 respectively). Shallow coastal water and the area with high amount of suspended sediment detected by our algorithm were then masked. The result of this algorithm was then evaluated by comparing each masked area with the corresponding mask generated by using other established technique.
Lyapunov-based Safe Policy Optimization

In many reinforcement learning applications, it is crucial that the agent interacts with the environment only through safe policies, i.e., policies that do not take the agent to certain undesirable situations. These problems are often formulated as a constrained Markov decision process (CMDP) in which the agent’s goal is to optimize its main objective while not violating a number of safety constraints. In this paper, we propose safe policy optimization algorithms that are based on the Lyapunov approach to CMDPs, an approach that has well-established theoretical guarantees in control engineering. We first show how to generate a set of state-dependent Lyapunov constraints from the original CMDP safety constraints. We then propose safe policy gradient (PG) algorithms that train a neural network policy using deep deterministic policy gradient (DDPG) or proximal policy optimization (PPO), while guaranteeing near-constraint satisfaction at every policy update by projecting either the policy parameter or the action onto the set of feasible solutions induced by the linearized Lyapunov constraints. Unlike the existing (safe) constrained policy gradient algorithms, ours are more data efficient as they are able to utilize both on-policy and off-policy data. Furthermore, the action-projection version of our algorithms often leads to less conservative policy updates and allows for natural integration into an end-to-end PG training pipeline. We evaluate our algorithms and compare them with constrained policy optimization (CPO) and the Lagrangian method on several high-dimensional continuous state and action simulated robot locomotion tasks, in which the agent must satisfy certain safety constraints while minimizing its expected cumulative cost.
New Financial Development Indicators: With a Critical Contribution to Inequality Empirics

The employment of financial development indicators without due consideration to country/regional specific financial development realities remains an issue of substantial policy relevance. Financial depth in the perspective of money supply is not equal to liquid liabilities in every development context. This paper introduces complementary indicators to the existing Financial Development and Structure Database (FDSD). Dynamic panel system GMM estimations are applied. Different specifications, non-overlapping intervals and control variables are used to check the consistency of estimated coefficients. Our results suggest that from an absolute standpoint (GDP base measures), all financial sectors are pro-poor. However, three interesting findings are drawn from measures of sector importance. (1) The expansion of the formal financial sector to the detriment of other financial sectors has a disequalizing income effect. (2) Growth of informal and semi-formal financial sectors at the expense of the formal financial sector has an income equalizing effect. (3) The positive income redistributive effect of semi-formal finance in financial sector competition is higher than the corresponding impact of informal finance. It unites two streams of research by contributing at the same time to the macroeconomic literature on measuring financial development and responding to the growing field of economic development by means of informal financial sector promotion and microfinance. The paper suggests a practicable way to disentangle the effects of the various financial sectors on economic development. The equation of financial depth in the perspective of money supply to liquid liabilities has put on the margin the burgeoning informal financial sector in developing countries. The phenomenon of mobile banking is such an example.
Adding Psychological Value to Heritage Tourism Experiences

Abstract This study employed an under-utilized methodology known as the Hierarchical Value Map (HVM) technique to explore the underlying motives and needs of visitors to a heritage site. Drawing from a small sample of visitors to a preserved 18th century plantation, the analysis revealed that most respondents were looking for a satisfying leisure experience where pleasure and learning are complementary. In addition the results support the notion that there is a specialized tourist segment (e.g., heritage tourists) that as a group has unique motives and needs. Implications for both optimizing the visitors experience as well as projecting an effective image and marketing communications are discussed.