Fish and macroinvertebrate assemblages reveal extensive degradation of the world's rivers.

Rivers suffer from multiple stressors acting simultaneously on their biota, but the consequences are poorly quantified at the global scale. We evaluated the biological condition of rivers globally, including the largest proportion of countries from the Global South published to date. We gathered macroinvertebrate- and fish-based assessments from 72,275 and 37,676 sites, respectively, from 64 study regions across six continents and 45 nations. Because assessments were based on differing methods, different systems were consolidated into a 3-class system: Good, Impaired, or Severely Impaired, following common guidelines. The proportion of sites in each class by study area was calculated and each region was assigned a Köppen-Geiger climate type, Human Footprint score (addressing landscape alterations), Human Development Index (HDI) score (addressing social welfare), % rivers with good ambient water quality, % protected freshwater key biodiversity areas; and % of forest area net change rate. We found that 50% of macroinvertebrate sites and 42% of fish sites were in Good condition, whereas 21% and 29% were Severely Impaired, respectively. The poorest biological conditions occurred in Arid and Equatorial climates and the best conditions occurred in Snow climates. Severely Impaired conditions were associated (Pearson correlation coefficient) with higher HDI scores, poorer physico-chemical water quality, and lower proportions of protected freshwater areas. Good biological conditions were associated with good water quality and increased forested areas. It is essential to implement statutory bioassessment programs in Asian, African, and South American countries, and continue them in Oceania, Europe, and North America. There is a need to invest in assessments based on fish, as there is less information globally and fish were strong indicators of degradation. Our study highlights a need to increase the extent and number of protected river catchments, preserve and restore natural forested areas in the catchments, treat wastewater discharges, and improve river connectivity.

Water Quality, Sanitation, and Hygiene Conditions in Schools and Households in Dolakha and Ramechhap Districts, Nepal: Results from A Cross-Sectional Survey.

This study assessed drinking water quality, sanitation, and hygiene (WASH) conditions among 708 schoolchildren and 562 households in Dolakha and Ramechhap districts of Nepal. Cross-sectional surveys were carried out in March and June 2015. A Delagua water quality testing kit was employed on 634 water samples obtained from 16 purposively selected schools, 40 community water sources, and 562 households to examine water quality. A flame atomic absorption spectrophotometer was used to test lead and arsenic content of the same samples. Additionally, a questionnaire survey was conducted to obtain WASH predictors. A total of 75% of school drinking water source samples and 76.9% point-of-use samples (water bottles) at schools, 39.5% water source samples in the community, and 27.4% point-of-use samples at household levels were contaminated with thermo-tolerant coliforms. The values of water samples for pH (6.8-7.6), free and total residual chlorine (0.1-0.5 mg/L), mean lead concentration (0.01 mg/L), and mean arsenic concentration (0.05 mg/L) were within national drinking water quality standards. The presence of domestic animals roaming inside schoolchildren's homes was significantly associated with drinking water contamination (adjusted odds ratio: 1.64; 95% confidence interval: 1.08-2.50; p = 0.02). Our findings call for an improvement of WASH conditions at the unit of school, households, and communities.

Use of Monte Carlo simulations for propagation of light in biomedical tissues.

In problems relating to light propagation in biomedical tissues, the tissue is generally modeled as a turbid medium and Monte Carlo (MC) simulation is employed to compute quantities such as diffuse reflectance, fluence, and transmittance. Two prescriptions are available in the literature for MC simulations. The first prescription considers all input quantities, including phase function, as an average over the particle size distribution, and the second prescription considers the phase function of each scatterer individually. The two prescriptions have been compared and contrasted in this paper for a given soft tissue model. It is demonstrated that, in general, the two recipes do not yield identical results. The source of this disagreement has been traced.