Effect of Different Tool Probe Profiles on Material Flow of Al-Mg-Cu Alloy Joined by Friction Stir Welding.

Friction Stir Welding (FSW) was utilized to butt-join 2024-T4 aluminum alloy plates of 1.9 mm thickness, using tools with conical and tapered hexagonal probe profiles. The characteristic effects of FSW using tools with tapered hexagonal probe profiles include an increase in the heat input and a significant modification of material flow, which have a positive effect on the metallurgical characteristics and mechanical performance of the weld. The differences in mechanical properties were interpreted through macrostructural changes and mechanical properties of the welded joints, which were supported by numerical simulation results on temperature distribution and material flow. The material flow resulting from the tapered hexagonal probe was more complicated than that of the conical probe. If in the first case, the dynamic viscosity and strain rate are homogeneously distributed around the probe, but in the case of the tapered hexagonal probe tool, the zones with maximum values of strain rates and minimum values of dynamic viscosity are located along the six tapered edges of the probe.

Classification of Spatiotemporal Data for Epidemic Alert Systems: Monitoring Influenza-Like Illness in France.

Surveillance data used by epidemic alert systems are typically fully aggregated in space at the national level. However, epidemics may be spatially heterogeneous, undergoing distinct dynamics in distinct regions of the surveillance area. We unveiled this in retrospective analyses by classifying incidence time series. We used Pearson correlation to quantify the similarity between local time series and then classified them using modularity maximization. The surveillance area was thus divided into regions with different incidence patterns. We analyzed 31 years (1985-2016) of data on influenza-like illness from the French Sentinelles system and found spatial heterogeneity in 19 of 31 influenza seasons. However, distinct epidemic regions could be identified only 4-5 weeks after a nationwide alert. The impact of spatial heterogeneity on influenza epidemiology was complex. First, when a nationwide alert was triggered, 32%-41% of the administrative regions of France were experiencing an epidemic, while the others were not. Second, the nationwide alert was timely for the whole surveillance area, but subsequently regions experienced distinct epidemic dynamics. Third, the epidemic dynamics were homogeneous in space. Spatial heterogeneity analyses can provide information on the timing of the peak and end of the epidemic, in various regions, for use in tailoring disease monitoring and control.

Bayesian Monitoring of Emerging Infectious Diseases.

We define data analyses to monitor a change in R, the average number of secondary cases caused by a typical infected individual. The input dataset consists of incident cases partitioned into outbreaks, each initiated from a single index case. We split the input dataset into two successive subsets, to evaluate two successive R values, according to the Bayesian paradigm. We used the Bayes factor between the model with two different R values and that with a single R value to justify that the change in R is statistically significant. We validated our approach using simulated data, generated using known R. In particular, we found that claiming two distinct R values may depend significantly on the number of outbreaks. We then reanalyzed data previously studied by Jansen et al. [Jansen et al. Science 301 (5634), 804], concerning the effective reproduction number for measles in the UK, during 1995-2002. Our analyses showed that the 1995-2002 dataset should be divided into two separate subsets for the periods 1995-1998 and 1999-2002. In contrast, Jansen et al. take this splitting point as input of their analysis. Our estimated effective reproduction numbers R are in good agreement with those found by Jansen et al. In conclusion, our methodology for detecting temporal changes in R using outbreak-size data worked satisfactorily with both simulated and real-world data. The methodology may be used for updating R in real time, as surveillance outbreak data become available.

Comparison of Seven Methods for Boolean Factor Analysis and Their Evaluation by Information Gain.

An usual task in large data set analysis is searching for an appropriate data representation in a space of fewer dimensions. One of the most efficient methods to solve this task is factor analysis. In this paper, we compare seven methods for Boolean factor analysis (BFA) in solving the so-called bars problem (BP), which is a BFA benchmark. The performance of the methods is evaluated by means of information gain. Study of the results obtained in solving BP of different levels of complexity has allowed us to reveal strengths and weaknesses of these methods. It is shown that the Likelihood maximization Attractor Neural Network with Increasing Activity (LANNIA) is the most efficient BFA method in solving BP in many cases. Efficacy of the LANNIA method is also shown, when applied to the real data from the Kyoto Encyclopedia of Genes and Genomes database, which contains full genome sequencing for 1368 organisms, and to text data set R52 (from Reuters 21578) typically used for label categorization.

Speciation dynamics of metals in dispersion of nanoparticles with discrete distribution of charged binding sites.

We report a comprehensive theory to evaluate the kinetics of complex formation between metal ions and charged spherical nanoparticles. The latter consist of an ion-impermeable core surrounded by a soft shell layer characterized by a discrete axisymmetric 2D distribution of charged sites that bind metal ions. The theory explicitly integrates the conductive diffusion of metal ions from bulk solution toward the respective locations of the reactive sites within the particle shell volume. The kinetic constant k for outer-sphere nanoparticle-metal association is obtained from the sum of the contributions stemming from all reactive sites, each evaluated from the corresponding incoming flux of metal ions derived from steady-state Poisson-Nernst-Planck equations. Illustrations are provided to capture the basic intertwined impacts of particle size, overall particle charge, spatial heterogeneity in site distribution, type of particle (hard, core-shell or porous) and concentration of the background electrolyte on k. As a limit, k converges with predictions from previously reported analytical expressions derived for porous particles with low and high charge density, cases that correspond to coulombic and mean-field (smeared-out) electrostatic treatments, respectively. The conditions underlying the applicability of these latter approaches are rigorously identified in terms of (i) the extent of overlap between electric double layers around charged neighbouring sites, and (ii) the magnitude of the intraparticulate metal concentration gradient. For the first time, the proposed theory integrates the differentiated impact of the local potential around the charged binding sites amidst the overall particle field, together with that of the so-far discarded intraparticulate flux of metal ions.

Production of extracellular glycogen by Pseudomonas fluorescens: spectroscopic evidence and conformational analysis by biomolecular recognition.

Glycogen is mainly found as the principal storage form of glucose in cells. Many bacteria are able to synthesize large amounts of glycogen under unfavorable life conditions. By combining infrared spectroscopy, single molecule force spectroscopy (SMFS) and immuno-staining technique, we evidenced that planktonic P. fluorescens (Pf) cells are also able to produce glycogen as an extracellular polymeric substance. For this purpose, Pf suspensions were examined at 3 and 21 h of growth in nutritive medium (LB, 0.5 g/L). The conformation of the extracellular glycogen, revealed through its infrared spectral signature, has been investigated by SMFS measurements using Freely Jointed Chain model. The analysis of force versus distance curves showed over growth time that the increase of glycogen production was accompanied by an increase in glycogen contour lengths and ramifications. These results demonstrated that the production of extracellular bacterial glycogen can occur even if the cells are not subjected to unfavorable life conditions.

Elasticity and physico-chemical properties during drinking water biofilm formation.

Atomic force microscope techniques and multi-staining fluorescence microscopy were employed to study the steps in drinking water biofilm formation. During the formation of a conditioning layer, surface hydrophobic forces increased and the range of characteristic hydrophobic forces diversified with time, becoming progressively complex in macromolecular composition, which in return triggered irreversible cellular adhesion. AFM visualization of 1 to 8 week drinking water biofilms showed a spatially discontinuous and heterogeneous distribution comprising an extensive network of filamentous fungi in which biofilm aggregates were embedded. The elastic modulus of 40-day-old biofilms ranged from 200 to 9000 kPa, and the biofilm deposits with a height >0.5 µm had an elastic modulus <600 kPa, suggesting that the drinking water biofilms were composed of a soft top layer and a basal layer with significantly higher elastic modulus values falling in the range of fungal elasticity.

Bacterial surface appendages strongly impact nanomechanical and electrokinetic properties of Escherichia coli cells subjected to osmotic stress.

The physicochemical properties and dynamics of bacterial envelope, play a major role in bacterial activity. In this study, the morphological, nanomechanical and electrohydrodynamic properties of Escherichia coli K-12 mutant cells were thoroughly investigated as a function of bulk medium ionic strength using atomic force microscopy (AFM) and electrokinetics (electrophoresis). Bacteria were differing according to genetic alterations controlling the production of different surface appendages (short and rigid Ag43 adhesins, longer and more flexible type 1 fimbriae and F pilus). From the analysis of the spatially resolved force curves, it is shown that cells elasticity and turgor pressure are not only depending on bulk salt concentration but also on the presence/absence and nature of surface appendage. In 1 mM KNO(3), cells without appendages or cells surrounded by Ag43 exhibit large Young moduli and turgor pressures (∼700-900 kPa and ∼100-300 kPa respectively). Under similar ionic strength condition, a dramatic ∼50% to ∼70% decrease of these nanomechanical parameters was evidenced for cells with appendages. Qualitatively, such dependence of nanomechanical behavior on surface organization remains when increasing medium salt content to 100 mM, even though, quantitatively, differences are marked to a much smaller extent. Additionally, for a given surface appendage, the magnitude of the nanomechanical parameters decreases significantly when increasing bulk salt concentration. This effect is ascribed to a bacterial exoosmotic water loss resulting in a combined contraction of bacterial cytoplasm together with an electrostatically-driven shrinkage of the surface appendages. The former process is demonstrated upon AFM analysis, while the latter, inaccessible upon AFM imaging, is inferred from electrophoretic data interpreted according to advanced soft particle electrokinetic theory. Altogether, AFM and electrokinetic results clearly demonstrate the intimate relationship between structure/flexibility and charge of bacterial envelope and propensity of bacterium and surface appendages to contract under hypertonic conditions.

Automated force volume image processing for biological samples.

Atomic force microscopy (AFM) has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature) which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image.

Study of the soret effect in hydrocarbon chain/aromatic compound mixtures.

We studied the thermal diffusion behavior of equimolar mixtures of hydrocarbon chains in cyclohexane, p-xylene, and o-xylene experimentally and by reverse nonequilibrium molecular dynamics. The hydrocarbon chains heptane, 2,3-dimethylpentane, 2,4-dimethylpentane, 2-ethyl-3-methyl butadiene, and 2,4-dimethylpentadiene-1,3 with the same number of carbon atoms were considered in order to conserve the mass contribution and to investigate the shape influence on the Soret coefficient. Compared to the experimental data, the simulation results show the same trend. With increasing degree of branching, the Soret coefficient becomes larger. The negative Soret coefficient of the hydrocarbon chains indicates the enrichment in the warm side. We were able to find an empirical correlation between the properties of the pure components and the Soret coeffcients of the considered mixtures.

Recurrent-neural-network-based Boolean factor analysis and its application to word clustering.

The objective of this paper is to introduce a neural-network-based algorithm for word clustering as an extension of the neural-network-based Boolean factor analysis algorithm (Frolov , 2007). It is shown that this extended algorithm supports even the more complex model of signals that are supposed to be related to textual documents. It is hypothesized that every topic in textual data is characterized by a set of words which coherently appear in documents dedicated to a given topic. The appearance of each word in a document is coded by the activity of a particular neuron. In accordance with the Hebbian learning rule implemented in the network, sets of coherently appearing words (treated as factors) create tightly connected groups of neurons, hence, revealing them as attractors of the network dynamics. The found factors are eliminated from the network memory by the Hebbian unlearning rule facilitating the search of other factors. Topics related to the found sets of words can be identified based on the words' semantics. To make the method complete, a special technique based on a Bayesian procedure has been developed for the following purposes: first, to provide a complete description of factors in terms of component probability, and second, to enhance the accuracy of classification of signals to determine whether it contains the factor. Since it is assumed that every word may possibly contribute to several topics, the proposed method might be related to the method of fuzzy clustering. In this paper, we show that the results of Boolean factor analysis and fuzzy clustering are not contradictory, but complementary. To demonstrate the capabilities of this attempt, the method is applied to two types of textual data on neural networks in two different languages. The obtained topics and corresponding words are at a good level of agreement despite the fact that identical topics in Russian and English conferences contain different sets of keywords.

Investigation of the Soret effect in aqueous and non-aqueous mixtures by the thermal lens technique.

In the present work we investigate the thermal diffusion behavior of three different binary mixtures with a thermal lens (TL) setup. In the setup used in this study we avoid the addition of a dye for systems, such as aqueous mixtures, with a weak absorption band at a wavelength of 980 nm. In some aqueous systems with a complex phase behavior the addition of dye significantly affects the apparent measured thermal diffusion properties. The studied systems are dimethylsulfoxide (DMSO) in water, the ionic liquid 1-ethyl-3-methylimidazolium ethylsulfate (EMIES) in butanol and a non-ionic surfactant hexaethylene glycol monododecyl ether (C(12)E(6)) in water. The Soret coefficients of the selected systems cover a range of two orders of magnitude. For DMSO in water with a very low Soret coefficient of the order of S(T) approximately 10(-3) K(-1) we find for a low DMSO content (c = 0.33) a reasonable agreement with previous measurements, while the weak thermal lens signal for the DMSO-rich mixture (c = 0.87) leads to 20% too large Soret coefficients with an uncertainty of more than 30%. Secondly we studied a liquid salt 1-ethyl-3-methylimidazolium ethylsulfate (EMIES) in butanol with a roughly ten times higher Soret coefficient of S(T) approximately 10(-2) K(-1). For this system we performed additional measurements with another experimental technique, the classical thermal diffusion forced Rayleigh scattering (TDFRS), which requires the addition of a small amount of dye to increase the absorption. In the entire investigated concentration range the results obtained with the TL and classical TDFRS technique agree within the error bars. As a third system we studied a non-ionic surfactant hexaethylene glycol monododecyl ether (C(12)E(6)) in water with a Soret coefficient of the order of S(T) approximately 10(-1) K(-1). For this system we find good agreement with previous measurements. We conclude that the TL technique is a reliable method for systems with a strong optical contrast and fairly large Soret coefficient of the order of S(T) approximately 10(-2) K(-1).

Reverse nonequilibrium molecular dynamics calculation of the Soret coefficient in liquid heptane/benzene mixtures.

We studied the thermal diffusion behavior of mixtures of benzene and heptane isomers by reverse nonequilibrium molecular dynamics. For n-heptane/benzene mixtures, we investigated the concentration dependence of the Soret coefficient. The Soret coefficient for equimolar mixtures of the three heptane isomers 3-methylhexane, 2,3-dimethylpentane, and 2,4-dimethylpentane in benzene has been calculated. Compared to the experimental data, the simulation results show the same trend in dependence of the mole fraction and degree of branching. The negative Soret coefficient indicates the enrichment of alkanes in the warm side. In the case of the heptane isomers in benzene, we could study the influence of the difference in shape and size on the thermal diffusion behavior at constant mass. In the simulation as well as in the experiment, we found that the Soret coefficients become higher with increasing degree of branching. Such behavior cannot be explained only by mass and size effects. The effect of the molecular shape needs to be considered additionally.

Thermal diffusion and molecular diffusion values for some alkane mixtures: a comparison between thermogravitational column and thermal diffusion forced rayleigh scattering.

In the present work we studied the thermal diffusion behavior of n-decane in various alkanes by thermogravitational column (TC) technique and the thermal diffusion forced Rayleigh scattering (TDFRS) method. The investigated lighter alkanes compared to n-decane are n-pentane, n-hexane, n-heptane, n-octane, and the heavier ones are n-tetradecane, n-pentadecane, n-hexadecane, n-heptadecane, n-octadecane, and n-eicosane. The binary mixture n-decane/ n-pentane we investigated at several different concentrations; all other mixtures were only investigated at a mass fraction of 50%. Even for the volatile n-pentane/ n-decane mixture the deviations between the thermal diffusion coefficients determined by the different methods agreed within the error bars. Typically the agreement between the two methods was in the order of 5%. In comparison to recently published TC and TDFRS data we found deviations in the order of 30% up to 40%. We analyze and discuss the possible reasons for the discrepancies for the present and the past publications.

Systematic study of the thermal diffusion in associated mixtures.

We performed systematic temperature and concentration dependent measurements of the Soret coefficient in different associated binary mixtures of water, deuterated water, dimethyl sulfoxide (DMSO), methanol, ethanol, acetone, methanol, 1-propanol, 2-propanol, and propionaldehyde using the so-called thermal diffusion forced Rayleigh scattering method. For some of the associating binary mixtures such as ethanol/water, acetone/water, and DMSO/water, the concentration xw+/- at which the Soret coefficient changes its sign does not depend on temperature and is equal to the concentration xw x where the Soret coefficient isotherms intersect. For others such as 1-propanol/water, 2-propanol/water, and ethanol/DMSO, the sign change concentration is temperature dependent, which is the typical behavior observed for nonassociating mixtures. For systems with xw+/-=xw x, we found that xw+/- depends linearly on the ratio of the vaporization enthalpies of the pure components. Probably due to the similarity of methanol and DMSO, we do not observe a sign change for this mixture. The obtained results are related to structural changes in the fluid observed by nuclear magnetic resonance, mass spectrometric, and x-ray experiments in the literature. Furthermore, we discuss the influence of hydrophilic and hydrophobic interactions and the solubility on thermal diffusion behavior.

Thermal diffusion measurements and simulations of binary mixtures of spherical molecules.

Thermal diffusion forced Rayleigh scattering measurements on binary mixtures of carbon tetrabromide (CBr(4)), tetraethylsilane, and di-tert-butylsilane in carbon tetrachloride (CCl(4)) are reported at different temperatures and concentrations. The Soret coefficient of CBr(4) in CCl(4) is positive and S(T) of both silanes in CCl(4) is negative, which implies that the heavier component always moves to the cold side. This is the expected behavior for unpolar simple molecules. Both silanes have the same mass so the influence of the difference in shape and moment of inertia could be studied. For all three systems, S(T) decreases with decreasing CCl(4) concentration. The results are discussed in the framework of thermodynamic theories and the Hildebrand parameter concept. Additionally, the Soret coefficients for both silaneCCl(4) systems were determined by nonequilibrium molecular-dynamics calculations. The simulations predict the correct direction of the thermophoretic motion and reflect the stronger drive toward the warm side for di-tert-butylsilane compared to the more symmetric tetraethylsilane. The values deviate systematically between 9% and 18% from the experimental values.

Boolean factor analysis by attractor neural network.

A common problem encountered in disciplines such as statistics, data analysis, signal processing, textual data representation, and neural network research, is finding a suitable representation of the data in the lower dimension space. One of the principles used for this reason is a factor analysis. In this paper, we show that Hebbian learning and a Hopfield-like neural network could be used for a natural procedure for Boolean factor analysis. To ensure efficient Boolean factor analysis, we propose our original modification not only of Hopfield network architecture but also its dynamics as well. In this paper, we describe neural network implementation of the Boolean factor analysis method. We show the advantages of our Hopfield-like network modification step by step on artificially generated data. At the end, we show the efficiency of the method on artificial data containing a known list of factors. Our approach has the advantage of being able to analyze very large data sets while preserving the nature of the data.

Study of the thermal diffusion behavior of alkane/benzene mixtures by thermal diffusion forced rayleigh scattering experiments and lattice model calculations.

In this work the thermal diffusion behavior of binary mixtures of linear alkanes (heptane, nonane, undecane, tridecane, pentadecane, heptadecane) in benzene has been investigated by thermal diffusion forced Rayleigh scattering (TDFRS) for a range of concentrations and temperatures. The Soret coefficient ST of the alkane was found to be negative for these n-alkane/benzene mixtures indicating that the alkanes are enriched in the warmer regions of the liquid mixtures. For the compositions investigated in this work, the magnitude of the Soret coefficient decreases with increasing chain length and increasing alkane content of the mixtures. The temperature dependence of the Soret coefficient depends on mixture composition and alkane chain length; the slope of ST versus temperature changes from positive to negative with increasing chain length at intermediate compositions. To study the influence of molecular architecture on the Soret effect, mixtures of branched alkanes (2-methylhexane, 3-methylhexane, 2,3-dimethylpentane, 2,4-dimethylpentane, 2,2,3-trimethylbutane, and 2,2,4-trimethylpentane) in benzene were also investigated. Our results for the Soret coefficients show that the tendency for the alkanes to move to the warmer regions of the fluid decreases with increasing degree of branching. The branching effect is so strong that for 2,2,4-trimethylpentane/benzene mixtures the Soret coefficient changes sign at high alkane content and that equimolar 2,2,3-trimethylbutane/benzene mixtures have positive Soret coefficients in the investigated temperature range. In order to investigate the effect of molecular interactions on thermal diffusion, we adapted a recently developed two-chamber lattice model to n-alkane/benzene mixtures. The model includes the effects of chain-length, compressibility, and orientation dependence of benzene-benzene interactions and yields good qualitative predictions for the Soret effect in n-alkane/benzene mixtures. For the branched isomers, we find some correlations between the moments of inertia of the molecules and the Soret coefficients. PACS numbers: 66.10.Cb, 61.25.Hq.

[Ocular injuries related to Independence Day celebrations].

BACKGROUND: Each year, following Israel's Independence Day celebrations, patients are referred to the Soroka University Medical Center as a result of ocular injuries from items such as artificial snow spray, fireworks, plastic hammers and stick-lights (plastic tubes filled with fluorescent liquid). This study aims to describe and characterize the ocular injuries that are directly related to the use of these devices. PATIENTS AND METHODS: The files of all patients who were referred to the Department of Ophthalmology in the Soroka University Medical Center, between the years 1998 and 2005, during the period of Israel's Independence Day, were screened. If a patient sustained an injury from a device used during the celebration, then data relating to the age, sex, injured eye, diagnosis, the device that caused the injury and treatment were collected. RESULTS: A total of 437 patients were included in this study; fifty-two patients had suffered an ocular injury directly due to a celebration device. The patients' mean age was 17.6 years; 61.5% of the patients were male. The three most common ocular injuries were corneal erosions, conjuctival erosions, and superficial punctate keratitis (38.5%, 28.9%, and 23.0%, respectively). Other injuries included corneal and conjuctival foreign bodies, traumatic iritis, elevated intraocular pressure, and subconjuctival hemorrhage. The devices responsible for most of the injuries were artificial snow spray and fireworks. Ocular injuries from stick-light liquid, plastic hammers, and balloon explosions were seen as well. Almost all patients (96.1%) required medical treatment. Patients injured by celebration devices accounted for 27.9% of all patients seen during this period in our Ophthalmology Department; after several years, the rate approached 40%. CONCLUSION: Strict enforcement of rules and legislation regarding the use of celebration devices must be upheld. The public's awareness of the harm that these devices can cause should be strengthened.

The effect of the Dead Sea environment on uveitis.

BACKGROUND: Uveitis is an acute or chronic inflammatory process of the uvea caused by a number of etiologies. In many patients the etiology is unknown. OBJECTIVE: To investigate the effect of the Dead Sea environment (climatotherapy) on the signs, symptoms and clinical course of chronic uveitis. METHODS: Fifty-five patients with chronic uveitis were examined at the beginning and end of a 3-4 week stay at the Dead Sea region and on repeat visits to the region. Study data included demographic information, medical history, etiology, diagnosis, medication, and a complete ophthalmic examination. RESULTS: Statistically significant improvements were seen between the two examinations within each visit in four parameters (negative values indicate improvement): a) visual acuity for near and far: Jaeger (-0.98 +/- 0.18, P < or = 0.001) and best corrected visual acuity (-0.22 +/- 0.04, P < or = 0.0001); b) anterior chamber flare (-0.18 +/- 0.06, P < or = 0.01); c) anterior chamber cells (-0.12 +/- 0.03, P < or = 0.0001); and d) vitreous cells (-0.17 +/- 0.05, P < or = 0.001). There was a significant mean improvement during visits to the Dead Sea area and a slight dissipation of the effect during the intervals between visits. Sixty-four percent of the patients reported that they required less medication and had fewer and milder attacks of uveitis following the visits. CONCLUSIONS: The results of this study provide evidence of short- and possibly long-term improvement in the signs and symptoms of uveitis following exposure to the Dead Sea environment.