Urban water conundrums in Zimbabwe – the role of water policy and its implementation gaps

Zimbabwe's urban areas are experiencing a dearth of water services which is epitomized by acute water shortages and high morbidity due to waterborne diseases. The possible contribution of failures of water policy implementation to this state of affairs is explored. This review identifies and assesses 122 studies in Zimbabwe and in other countries that have analyzed water policies, in order to understand the factors which create gaps in policy implementation. It was found that these implementation gaps are mainly a result of capacity limitations in institutions; finances; social and technical/human resources. There is currently very limited literature available that analyses water policy in Zimbabwe. In order to overcome the water conundrums in Zimbabwe's urban areas it is recommended that a literature review combined with an empirical study of both qualitative and quantitative gaps between the ZNWP and its implementation be undertaken. In particular, the review and study should focus on capacity limitations in institutions; finances; social and technical/human resources in Zimbabwe.

Development and Approbation of Methodology Aimed to Define the Reasons for Turbine Unit Capacity Limitation Based on the Specified Mathematical Model of its Condenser

The purpose of this work is to develop and test the methodology of elucidation of the reasons for turbine unit capacity limitations based on a mathematical model of its condenser. This pur-pose is achieved by using a mathematical model of the condenser as part of the developed methodology, taking into account the separate effects of contamination of the heat exchange surfaces, air suction into the vacuum system and the operating mode of the main ejector. Based on operational data sampling, the value of the limiting pressure in the condenser, excess of which leads to limitation of turbine unit capacity, was determined. It was established that the cause of power limitation is the abnormal operation of the main ejector due to inadmissible high temperature in the intermediate cooler of its first stage. For regimes that were not pressure-limited, using a mathematical model, the degree of tubes contamination, its influence on the condenser pressure and the power generated by the turbine unit, and the influence of actual air suctions on the condenser pressure were determined. The most important result of the study is to determine the possibility and feasibility of using the developed and tested methodology for solv-ing similar problems for any type of turbine unit equipped with a condenser. The significance of the work lies in the fact that the proposed approach expands the possibilities of using mathemat-ical models of this class in terms of solving such problems.

Utilization of biogas as an untapped renewable energy source in Vietnam

In Asia, Vietnam is one of the countries severely affected by energy shortages and climate change. Development of renewable energy from livestock wastes, e.g., production of electricity from biogas, is a solution for reducing greenhouse gas emissions and pollution from untreated livestock wastes, as well as energy shortages. So that, biogas technology has been researched and applied in Vietnam since the 1960s. The development and state-of-art issue of household biogas, specifically, the opportunities and constraints of household biogas are presented in this paper. There are several opportunities for household biogas development, including, the availability of biogas fermentation materials, energy shortage issues, and policy support from the Government of Vietnam and international organizations. Besides, barriers encountered in household biogas development in Vietnam included technical barriers, financial policy barriers, awareness and capacity limitations. The capacity building should include the dissemination and update of policy to maintain transparency and credibility for attracting potential domestic investors. Training courses should be provided to technical staff of biogas digester on operation and maintenance. Measures should be taken to improve the policy and mechanisms, especially, financial mechanisms.

The assessment of capacity limitations in psychiatric work disability evaluations by the social functioning scale Mini-ICF-APP

Objective Insurers frequently commission medical experts to estimate the degree of the remaining work capacity (RWC) in claimants for disability benefits. The social functioning scale Mini-ICF-APP allows for a rating of activity and participation limitations in thirteen capacity domains, considered as particularly relevant for work ability. The current study sought to evaluate the role of the Mini-ICF-APP ratings in psychiatric work disability evaluations, by examining how the capacity limitation ratings varied with the claimants’ primary psychiatric diagnoses and how the ratings were related to RWC estimates. Methods Medical experts estimated the RWC of 946 claimants with mental disorders and rated their activity and participation limitations using the Mini-ICF-APP, with higher ratings reflecting more severe limitations. The ratings were compared between claimants with different psychiatric diagnoses by analyses of variance. The mean Mini-ICF-APP rating across all capacity domains as well as all capacity-specific ratings were entered in simple or multiple regression models to predict the RWC in an alternative job. Results The Mini-ICF-APP capacity limitation ratings in all domains but mobility were higher for claimants with personality and behavior disorders as compared to those with mood disorders or with neurotic, stress-related and somatoform disorders. The largest differences were observed in social capacities (e.g. group integration: F 2, 847 = 78.300, P < 0.001). In claimants with depression, all ratings increased with the severity of the diagnosis (all Fs 2, 203 > 16.393, all Ps < 0.001). In the overall sample, the mean Mini-ICF-APP rating showed a strong negative correlation with the estimated RWC (r = −.720, P < 0.001). Adding the capacity-specific ratings to the prediction model improved this prediction only marginally. Discussion The Mini-ICF-APP allows for documenting claimants’ activity and participation limitations, which is likely to increase the transparency of medical experts’ RWC estimates and enables them to check the plausibility of such estimates. However, our study showed that despite the strong association between RWC and Mini-ICF-APP ratings, half of the RWC variance was unrelated to the capacity limitations documented in the Mini-ICF-APP.

Forgetting Enhances Episodic Control with Structured Memories

Forgetting is a normal process in healthy brains, and evidence suggests that the mammalian brain forgets more than is required based on limitations of mnemonic capacity. Episodic memories, in particular, are liable to be forgotten over time. Researchers have hypothesized that it may be beneficial for decision making to forget episodic memories over time. Reinforcement learning offers a normative framework in which to test such hypotheses. Here, we show that a reinforcement learning agent that uses an episodic memory cache to find rewards in maze environments can forget a large percentage of older memories without any performance impairments, if they utilize mnemonic representations that contain structural information about space. Moreover, we show that some forgetting can actually provide a benefit in performance compared to agents with unbounded memories. Our analyses of the agents show that forgetting reduces the influence of outdated information and states which are not frequently visited on the policies produced by the episodic control system. These results support the hypothesis that some degree of forgetting can be beneficial for decision making, which can help to explain why the brain forgets more than is required by capacity limitations.

Under-resourced or overloaded? Rethinking working memory deficits in developmental language disorder

Dominant theoretical accounts of developmental language disorder (DLD) are unanimous in assuming working memory capacity limitations. In the current report, we present an alternative view: That working memory in DLD is not under-resourced but overloaded due to operating on speech representations with low discriminability. This account is developed through computational simulations involving deep convolutional neural networks trained on spoken word spectrograms in which frequency information is either retained to mimic typical development or degraded to mimic spectral processing deficits identified among children with DLD. We assess not only spoken word recognition accuracy and predictive probability and entropy (i.e., predictive distribution spread), but also use mean-field-theory based manifold analysis to assess; (i) internal speech representation dimensionality, and (ii) classification capacity, a measure of networks’ ability to isolate any given internal speech representation that is used as a proxy for attentional control. We show that instantiating a low-level frequency discrimination deficit results in the formation of internal speech representations with atypically high dimensionality, and that classification capacity is exhausted due to low representation separability. These representation and control deficits underpin not only lower performance accuracy but also greater uncertainty even when making accurate predictions in a simulated spoken word recognition task (i.e., predictive distributions with low maximum probability and high entropy), which replicates the response delays and word finding difficulties often seen in DLD. Overall, these simulations demonstrate an integrated theoretical account of speech representation and processing in DLD in which working memory capacity limitations play no causal role.

Response of Poverty Pockets to the Right-based Demand-driven MGNREGA Programme

Forerunning programmes of the Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA), which were designed as poverty elimination programmes, took notice of geographical pockets of poverty and incorporated formula-based fund allocation mechanisms to poorer states and regions. The MGNREGA programme, in contrast, used a right-based ‘self-selection’ approach— relying on the initiative of households’ demand-driven strengths—to allocate need-based resources to states and regions within states. This article examines how well the demand-driven, right-based programme with self-selection allocated resources to states and regions according to their respective needs, and to what extent the benefits reached the poverty pockets and catered to the poorest, weakest and neediest households. We find that adequate resources did not reach the poorest states and regions, substantial numbers of poor households remained outside the programme or were deemed underserved, and there was a pronounced programme capture by elite states. The article explores causes and consequences of capacity limitations and low absorption pulls among states, and points to policy implications and ways forward.

The Impact of Upcoming Treatments in Huntington’s Disease: Resource Capacity Limitations and Access to Care Implications

Background: The most advanced disease-modifying therapies (DMTs) in development for Huntington’s disease (HD) require intrathecal (IT) administration, which may create or exacerbate bottlenecks in resource capacity. Objective: To understand the readiness of healthcare systems for intrathecally administered HD DMTs in terms of resource capacity dynamics and implications for patients’ access to treatment. Methods: Forty HD centres across 12 countries were included. Qualitative and quantitative data on current capacity in HD centres and anticipated capacity needs following availability of a DMT were gathered via interviews with healthcare professionals (HCPs). Data modelling was used to estimate the current capacity gap in HD centres. Results: From interviews with 218 HCPs, 25% of HD centres are estimated to have the three components required for IT administration (proceduralists, nurses and facilities). On average, 114 patients per centre per year are anticipated to receive intrathecally administered DMTs in the future. At current capacity, six of the sampled centres are estimated to be able to deliver DMTs to all the anticipated patients based on current resources. The estimated waiting list for IT administration at current capacity will average 60 months (5 years) by the second year after DMT availability. Conclusion: Additional resources are needed in HD centres for future DMTs to be accessible to all anticipated patients. Timely collaboration by the HD community will be needed to address capacity gaps. Healthcare policymakers and payers will need to address costs and navigate challenges arising from country- or region-specific healthcare delivery schemes.