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يلعب المال دورا محوريا في حياة البشر جميعا مهما قل أو أكثر، ونحن جميعا نعتقد بأن المال بإمكانه أن يحل جميع مشاكلنا وأن يحقق أحلامنا. أننا نحسد من يملك منه الكثير ونرثي لحال من لا يملك منه إلا القليل، ونحلم بأن نمتلك منه المزيد لكننا نشعر بالذنب إذا حدث ذلك، ورغم ذلك لا نكف عن التفكير فيه. يرتبط المال، بشكل أو بآخر، بكل شيء نفعله في حياتنا وبالكثير مما نؤمن به، وهذا الكتاب يتناول المال، من خلال التفكير والمناقشة. والمرح والأسئلة التي تحفز على التفكير.

A fully coupled meteorology-chemistry-aerosol model (WRF-Chem) is applied to simulate mineral dust and its shortwave (SW) radiative forcing over North Africa. Two dust emission schemes (GOCART and DUSTRAN) and two aerosol models (MADE/SORGAM and MOSAIC) are adopted in simulations to investigate the modeling sensitivities to dust emissions and aerosol size treatments. The modeled size distribution and spatial variability of mineral dust and its radiative properties are evaluated using measurements (ground-based, aircraft, and satellites) during the AMMA SOP0 campaign from 6 January to 3 February of 2006 (the SOP0 period) over North Africa. Two dust emission schemes generally simulate similar spatial distributions and temporal evolutions of dust emissions. Simulations using the GOCART scheme with different initial (emitted) dust size distributions require ~40% difference in total emitted dust mass to produce similar SW radiative forcing of dust over the Sahel region. The modal approach of MADE/SORGAM retains 25% more fine dust particles (radius<1.25 μm) but 8% less coarse dust particles (radius>1.25 μm) than the sectional approach of MOSAIC in simulations using the same size-resolved dust emissions. Consequently, MADE/SORGAM simulates 11% higher AOD, up to 13% lower SW dust heating rate, and 15% larger (more negative) SW dust radiative forcing at the surface than MOSAIC over the Sahel region. In the daytime of the SOP0 period, the model simulations show that the mineral dust heats the lower atmosphere with an average rate of 0.8 ± 0.5 K day−1 over the Niamey vicinity and 0.5 ± 0.2 K day−1 over North Africa and reduces the downwelling SW radiation at the surface by up to 58 W m−2 with an average of 22 W m−2 over North Africa. This highlights the importance of including dust radiative impact in understanding the regional climate of North Africa. When compared to the available measurements, the WRF-Chem simulations can generally capture the measured features of mineral dust and its radiative properties over North Africa, suggesting that the model is suitable for more extensive simulations of dust impact on regional climate over North Africa.

Few studies have focused on post-traumatic stress disorder (PTSD) remission in the population, none have modelled remission beyond age 54 years and none have explored in detail the correlates of remission from PTSD. This study examined trauma experience, symptom severity, co-morbidity, service use and time to PTSD remission in a large population sample. Data came from respondents (n=8841) of the 2007 Australian National Survey of Mental Health and Wellbeing (NSMHWB). A modified version of the World Health Organization's World Mental Health Composite International Diagnostic Interview (WMH-CIDI) was used to determine the presence and age of onset of DSM-IV PTSD and other mental and substance use disorders, type, age, and number of lifetime traumas, severity of re-experiencing, avoidance and hypervigilance symptoms and presence and timing of service use. Projected lifetime remission rate was 92% and median time to remission was 14 years. Those who experienced childhood trauma, interpersonal violence, severe symptoms or a secondary anxiety or affective disorder were less likely to remit from PTSD and reported longer median times to remission compared to those with other trauma experiences, less severe symptoms or no co-morbidity. Although most people in the population with PTSD eventually remit, a significant minority report symptoms decades after onset. Those who experience childhood trauma or interpersonal violence should be a high priority for intervention.

Background. We report on the epidemiology of post-traumatic stress disorder (PTSD) in the Australian community, including information on lifetime exposure to trauma, 12-month prevalence of PTSD, sociodemographic correlates and co-morbidity. Methods. Data were obtained from a stratified sample of 10641 participants as part of the Australian National Survey of Mental Health and Well-being. A modified version of the Composite International Diagnostic Interview was used to determine the presence of PTSD, as well as other DSM-IV anxiety, affective and substance use disorders. Results. The estimated 12-month prevalence of PTSD was 1·33%, which is considerably lower than that found in comparable North American studies. Although females were at greater risk than males within the subsample of those who had experienced trauma, the large gender differences noted in some recent epidemiological research were not replicated. Prevalence was elevated among the never married and previously married respondents, and was lower among those aged over 55. For both men and women, rape and sexual molestation were the traumatic events most likely to be associated with PTSD. A high level of Axis 1 co-morbidity was found among those persons with PTSD Conclusions. PTSD is a highly prevalent disorder in the Australian community and is routinely associated with high rates of anxiety, depression and substance disorders. Future research is needed to investigate rates among other populations outside the North American continent.

The impacts of global environmental change have precipitated numerous approaches that connect the health of ecosystems, non-human organisms and humans. However, the proliferation of approaches can lead to confusion due to overlaps in terminology, ideas and foci. Recognising the need for clarity, this paper provides a guide to seven field developments in environmental public health research and practice: occupational and environmental health; political ecology of health; environmental justice; ecohealth; One Health; ecological public health; and planetary health. Field developments are defined in terms of their uniqueness from one another, are historically situated, and core texts or journals are highlighted. The paper ends by discussing some of the intersecting features across field developments, and considers opportunities created through such convergence. This field guide will be useful for those seeking to build a next generation of integrative research, policy, education and action that is equipped to respond to current health and sustainability challenges.

Auditory temporal processing is a vital component of auditory stream segregation, or the process in which complex sounds are separated and organized into perceptually meaningful objects. Temporal processing can degrade prior to hearing loss, and is suggested to be a contributing factor to difficulties with speech-in-noise perception in normal-hearing listeners. The current study tested this hypothesis in middle-aged adults—an under-investigated cohort, despite being the age group where speech-in-noise difficulties are first reported. In 76 participants, three mechanisms of temporal processing were measured: peripheral auditory nerve function using electrocochleography, subcortical encoding of periodic speech cues (i.e., fundamental frequency; F0) using the frequency following response, and binaural sensitivity to temporal fine structure (TFS) using a dichotic frequency modulation detection task. Two measures of speech-in-noise perception were administered to explore how contributions of temporal processing may be mediated by different sensory demands present in the speech perception task. This study supported the hypothesis that temporal coding deficits contribute to speech-in-noise difficulties in middle-aged listeners. Poorer speech-in-noise perception was associated with weaker subcortical F0 encoding and binaural TFS sensitivity, but in different contexts, highlighting that diverse aspects of temporal processing are differentially utilized based on speech-in-noise task characteristics.

Although perceived social support is thought to be a strong predictor of psychological outcomes following trauma exposure, the temporal relationship between perceived positive and negative social support and post-traumatic stress disorder (PTSD) symptoms has not been empirically established. This study investigated the temporal sequencing of perceived positive social support, perceived negative social support, and PTSD symptoms in the 6 years following trauma exposure among survivors of traumatic injury. Participants were 1132 trauma survivors initially assessed upon admission to one of four Level 1 trauma hospitals in Australia after experiencing a traumatic injury. Participants were followed up at 3 months, 12 months, 24 months, and 6 years after the traumatic event. Latent difference score analyses revealed that greater severity of PTSD symptoms predicted subsequent increases in perceived negative social support at each time-point. Greater severity of PTSD symptoms predicted subsequent decreases in perceived positive social support between 3 and 12 months. High levels of perceived positive or negative social support did not predict subsequent changes in PTSD symptoms at any time-point. Results highlight the impact of PTSD symptoms on subsequent perceived social support, regardless of the type of support provided. The finding that perceived social support does not influence subsequent PTSD symptoms is novel, and indicates that the relationship between PTSD and perceived social support may be unidirectional.

Viruses that originate in bats may be the most notorious emerging zoonoses that spill over from wildlife into domestic animals and humans. Understanding how these infections filter through ecological systems to cause disease in humans is of profound importance to public health. Transmission of viruses from bats to humans requires a hierarchy of enabling conditions that connect the distribution of reservoir hosts, viral infection within these hosts, and exposure and susceptibility of recipient hosts. For many emerging bat viruses, spillover also requires viral shedding from bats, and survival of the virus in the environment. Focusing on Hendra virus, but also addressing Nipah virus, Ebola virus, Marburg virus and coronaviruses, we delineate this cross-species spillover dynamic from the within-host processes that drive virus excretion to land-use changes that increase interaction among species. We describe how land-use changes may affect co-occurrence and contact between bats and recipient hosts. Two hypotheses may explain temporal and spatial pulses of virus shedding in bat populations: episodic shedding from persistently infected bats or transient epidemics that occur as virus is transmitted among bat populations. Management of livestock also may affect the probability of exposure and disease. Interventions to decrease the probability of virus spillover can be implemented at multiple levels from targeting the reservoir host to managing recipient host exposure and susceptibility.

Cloud Fraction (CF) is the dominant modulator of radiative fluxes. In this study, we evaluate CF simulated in the IPCC AR4 GCMs against ARM long-term ground-based measurements, with a focus on the vertical structure, total amount of cloud and its effect on cloud shortwave transmissivity. Comparisons are performed for three climate regimes as represented by the Department of Energy Atmospheric Radiation Measurement (ARM) sites: Southern Great Plains (SGP), Manus, Papua New Guinea and North Slope of Alaska (NSA). Our intercomparisons of three independent measurements of CF or sky-cover reveal that the relative differences are usually less than 10% (5%) for multi-year monthly (annual) mean values, while daily differences are quite significant. The total sky imager (TSI) produces smaller total cloud fraction (TCF) compared to a radar/lidar dataset for highly cloudy days (CF > 0.8), but produces a larger TCF value than the radar/lidar for less cloudy conditions (CF < 0.3). The compensating errors in lower and higher CF days result in small biases of TCF between the vertically pointing radar/lidar dataset and the hemispheric TSI measurements as multi-year data is averaged. The unique radar/lidar CF measurements enable us to evaluate seasonal variation of cloud vertical structures in the GCMs. Both inter-model deviation and model bias against observation are investigated in this study. Another unique aspect of this study is that we use simultaneous measurements of CF and surface radiative fluxes to diagnose potential discrepancies among the GCMs in representing other cloud optical properties than TCF. The results show that the model-observation and inter-model deviations have similar magnitudes for the TCF and the normalized cloud effect, and these deviations are larger than those in surface downward solar radiation and cloud transmissivity. This implies that other dimensions of cloud in addition to cloud amount, such as cloud optical thickness and/or cloud height, have a similar magnitude of disparity as TCF within the GCMs, and suggests that the better agreement among GCMs in solar radiative fluxes could be a result of compensating effects from errors in cloud vertical structure, overlap assumption, cloud optical depth and/or cloud fraction. The internal variability of CF simulated in ensemble runs with the same model is minimal. Similar deviation patterns between inter-model and model-measurement comparisons suggest that the climate models tend to generate larger biases against observations for those variables with larger inter-model deviation. The GCM performance in simulating the probability distribution, transmissivity and vertical profiles of cloud are comprehensively evaluated over the three ARM sites. The GCMs perform better at SGP than at the other two sites in simulating the seasonal variation and probability distribution of TCF. However, the models remarkably underpredict the TCF at SGP and cloud transmissivity is less susceptible to the change of TCF than observed. In the tropics, most of the GCMs tend to underpredict CF and fail to capture the seasonal variation of CF at middle and low levels. The high-level CF is much larger in the GCMs than the observations and the inter-model variability of CF also reaches a maximum at high levels in the tropics, indicating discrepancies in the representation of ice cloud associated with convection in the models. While the GCMs generally capture the maximum CF in the boundary layer and vertical variability, the inter-model deviation is largest near the surface over the Arctic.