Online Estimation and Optimization of Utility-Based Shortfall Risk

Utility-Based Shortfall Risk (UBSR) is a risk metric that is increasingly popular in financial applications, owing to certain desirable properties that it enjoys. We consider the problem of estimating UBSR in a recursive setting, where samples from the underlying loss distribution are available one-at-a-time. We cast the UBSR estimation problem as a root finding problem, and propose stochastic approximation-based estimations schemes. We derive non-asymptotic bounds on the estimation error in the number of samples. We also consider the problem of UBSR optimization within a parameterized class of random variables. We propose a stochastic gradient descent based algorithm for UBSR optimization, and derive non-asymptotic bounds on its convergence

Prescience:Probabilistic Guidance on the Retraining Conundrum for Malware Detection

Malware evolves perpetually and relies on increasingly sophisticatedattacks to supersede defense strategies. Datadrivenapproaches to malware detection run the risk of becomingrapidly antiquated. Keeping pace with malwarerequires models that are periodically enriched with freshknowledge, commonly known as retraining. In this work,we propose the use of Venn-Abers predictors for assessingthe quality of binary classification tasks as a first step towardsidentifying antiquated models. One of the key bene-fits behind the use of Venn-Abers predictors is that they areautomatically well calibrated and offer probabilistic guidanceon the identification of nonstationary populations ofmalware. Our framework is agnostic to the underlying classificationalgorithm and can then be used for building betterretraining strategies in the presence of concept drift. Resultsobtained over a timeline-based evaluation with about 90Ksamples show that our framework can identify when modelstend to become obsolete

Beneficial impacts of biochar as a potential feed additive in animal husbandry

In the last decade, biochar production and use have grown in popularity. Biochar is comparable to charcoal and activated charcoal because it is a pyrogenic carbonaceous matter made by pyrolyzing organic carbon-rich materials. There is a lack of research into the effects of adding biochar to animal feed. Based on the reviewed literature, including its impact on the adsorption of toxins, blood biochemistry, feed conversion rate, digestion, meat quality, and greenhouse gas emissions, adding biochar to the diet of farm animals is a good idea. This study compiles the most important research on biochar's potential as a supplement to the diets of ruminants (including cows and goats), swine, poultry, and aquatic organisms like fish. Biochar supplementation improves animal growth, haematological profiles, meat, milk and egg yield, resistance to illnesses (especially gut pathogenic bacteria), and reduced ruminant methane emission. Biochar's strong sorption capacity also helps efficiently remove contaminants and poisons from the animals' bodies and the farm surroundings where they are raised. Animal farmers are predicted to make greater use of biochar in the future. Biochar could potentially be of value in the healthcare and human health fields; hence research into this area is encouraged. The present review highlights the potential benefits of biochar as an additive to animal feed and demonstrates how, when combined with other environmentally friendly practices, biochar feeding can extend the longevity of animal husbandry

The Distribution of Fecal Contamination in an Urbanized Tropical Lake and Incidence of Acute Diarrheal Disease

Aquatic ecosystems of tropical countries are vulnerable to fecal contamination that could cause spikes in the incidences of acute diarrheal disease (ADD) and challenge public health management systems. Vembanad lake, situated along the southwest coast of India, was monitored for one year (2018−2019). Escherichia coli, an indicator of fecal contamination, was prevalent in the lake throughout the year. Multiple antibiotic resistance among more than 50% of the E. coli isolates adds urgency to the need to control this contamination. The high abundance of E. coli and incidence of ADD were recorded during the early phase of the southwest monsoon (June−July), prior to the once-in-a-century floods that affected the region in the later phase (August). The extent of inundation in the low-lying areas peaked in August, but E. coli in the water peaked in July, suggesting that contamination occurred even prior to extreme flooding. During the COVID-19-related lockdown in March−May 2021, fecal contamination in the lake and incidence of ADD reached minimum values. These results indicate the need for improving sewage treatment facilities and city planning in flood-prone areas to avoid the mixing of septic sewage with natural waters during extreme climate events or even during the normal monsoon

Exploring and Exploiting Disease Interactions from Multi-Relational Gene and Phenotype Networks

The availability of electronic health care records is unlocking the potential for novel studies on understanding and modeling disease co-morbidities based on both phenotypic and genetic data. Moreover, the insurgence of increasingly reliable phenotypic data can aid further studies on investigating the potential genetic links among diseases. The goal is to create a feedback loop where computational tools guide and facilitate research, leading to improved biological knowledge and clinical standards, which in turn should generate better data. We build and analyze disease interaction networks based on data collected from previous genetic association studies and patient medical histories, spanning over 12 years, acquired from a regional hospital. By exploring both individual and combined interactions among these two levels of disease data, we provide novel insight into the interplay between genetics and clinical realities. Our results show a marked difference between the well defined structure of genetic relationships and the chaotic co-morbidity network, but also highlight clear interdependencies. We demonstrate the power of these dependencies by proposing a novel multi-relational link prediction method, showing that disease co-morbidity can enhance our currently limited knowledge of genetic association. Furthermore, our methods for integrated networks of diverse data are widely applicable and can provide novel advances for many problems in systems biology and personalized medicine

Dynamics of Vibrio cholerae in a Typical Tropical Lake and Estuarine System: Potential of Remote Sensing for Risk Mapping

Vibrio cholerae, the bacterium responsible for the disease cholera, is a naturally-occurring bacterium, commonly found in many natural tropical water bodies. In the context of the U.N. Sus�tainable Development Goals (SDG) targets on health (Goal 3), water quality (Goal 6), life under water (Goal 14), and clean water and sanitation (Goal 6), which aim to “ensure availability and sustain�able management of water and sanitation for all”, we investigated the environmental reservoirs of V. cholerae in Vembanad Lake, the largest lake in Kerala (India), where cholera is endemic. The response of environmental reservoirs of V. cholerae to variability in essential climate variables may play a pivotal role in determining the quality of natural water resources, and whether they might be safe for human consumption or not. The hydrodynamics of Vembanad Lake, and the man-made barrier that divides the lake, resulted in spatial and temporal variability in salinity (1–32 psu) and temperature (23 to 36 ◦C). The higher ends of this salinity and temperature ranges fall outside the preferred growth conditions for V. cholerae reported in the literature. The bacteria were associated with filtered water as well as with phyto- and zooplankton in the lake. Their association with benthic organisms and sediments was poor to nil. The prevalence of high laminarinase and chitinase enzyme expression (more than 50 µgmL−1 min−1 ) among V. cholerae could underlie their high association with phyto- and zooplankton. Furthermore, the diversity in the phytoplankton community in the lake, with dominance of genera such as Skeletonema sp., Microcystis sp., Aulacoseira sp., and Anabaena sp., which changed with location and season, and associated changes in the zooplankton community, could also have affected the dynamics of the bacteria in the lake. The probability of presence or absence of V. cholerae could be expressed as a function of chlorophyll concentration in the water, which suggests that risk maps for the entire lake can be generated using satellite-derived chlorophyll data. In situ observations and satellite-based extrapolations suggest that the risks from environmental V. cholerae in the lake can be quite high (with probability in the range of 0.5 to 1) everywhere in the lake, but higher values are encountered more frequently in the southern part of the lake. Remote sensing has an important role to play in meeting SDG goals related to health, water quality and life under water, as demonstrated in this example related to cholera

Dynamics of Vibrio cholerae in a Typical Tropical Lake and Estuarine System: Potential of Remote Sensing for Risk Mapping

Vibrio cholerae, the bacterium responsible for the disease cholera, is a naturally-occurring bacterium, commonly found in many natural tropical water bodies. In the context of the U.N. Sustainable Development Goals (SDG) targets on health (Goal 3), water quality (Goal 6), life under water (Goal 14), and clean water and sanitation (Goal 6), which aim to “ensure availability and sustainable management of water and sanitation for all”, we investigated the environmental reservoirs of V. cholerae in Vembanad Lake, the largest lake in Kerala (India), where cholera is endemic. The response of environmental reservoirs of V. cholerae to variability in essential climate variables may play a pivotal role in determining the quality of natural water resources, and whether they might be safe for human consumption or not. The hydrodynamics of Vembanad Lake, and the man-made barrier that divides the lake, resulted in spatial and temporal variability in salinity (1–32 psu) and temperature (23 to 36 °C). The higher ends of this salinity and temperature ranges fall outside the preferred growth conditions for V. cholerae reported in the literature. The bacteria were associated with filtered water as well as with phyto- and zooplankton in the lake. Their association with benthic organisms and sediments was poor to nil. The prevalence of high laminarinase and chitinase enzyme expression (more than 50 µgmL−1 min−1) among V. cholerae could underlie their high association with phyto- and zooplankton. Furthermore, the diversity in the phytoplankton community in the lake, with dominance of genera such as Skeletonema sp., Microcystis sp., Aulacoseira sp., and Anabaena sp., which changed with location and season, and associated changes in the zooplankton community, could also have affected the dynamics of the bacteria in the lake. The probability of presence or absence of V. cholerae could be expressed as a function of chlorophyll concentration in the water, which suggests that risk maps for the entire lake can be generated using satellite-derived chlorophyll data. In situ observations and satellite-based extrapolations suggest that the risks from environmental V. cholerae in the lake can be quite high (with probability in the range of 0.5 to 1) everywhere in the lake, but higher values are encountered more frequently in the southern part of the lake. Remote sensing has an important role to play in meeting SDG goals related to health, water quality and life under water, as demonstrated in this example related to cholera

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy