Risk allocation in a public–private partnership: a case study of construction and operation of kindergartens in Kazakhstan

In Kazakhstan, a transitional nation in Central Asia, the development of public–private partnerships (PPPs) is at its early stage and increasingly of strategic importance. This case study investigates risk allocation in an ongoing project: the construction and operation of 11 kindergartens in the city of Karaganda in the concession form for 14 years. Drawing on a conceptual framework of effective risk allocation, the study identifies principal PPP risks, provides a critical assessment of how and in what way each partner bears a certain risk, highlights the reasons underpinning risk allocation decisions and delineates the lessons learned. The findings show that the government has effectively transferred most risks to the private sector partner, whilst both partners share the demand risk of childcare services and the project default risk. The strong elements of risk allocation include clear assignment of parties’ responsibilities, streamlined financing schemes and incentives to complete the main project phases on time. However, risk allocation has missed an opportunity to create incentives for service quality improvements and take advantage of economies of scale. The most controversial element of risk allocation, as the study finds, is a revenue stream that an operator is supposed to receive from the provision of services unrelated to childcare, as neither partner is able to mitigate this revenue risk. The article concludes that in the kindergartens’ PPP, the government has achieved almost complete transfer of risks to the private sector partner. However, the costs of transfer are extensive government financial outlays that seriously compromise the PPP value for money.

The trafficking pathway of a wheat storage protein in transgenic rice endosperm

Background and Aims The trafficking of proteins in the endoplasmic reticulum (ER) of plant cells is a topic of considerable interest since this organelle serves as an entry point for proteins destined for other organelles, as well as for the ER itself. In the current work, transgenic rice was used to study the pattern and pathway of deposition of the wheat high molecular weight (HMW) glutenin sub-unit (GS) 1Dx5 within the rice endosperm using specific antibodies to determine whether it is deposited in the same or different protein bodies from the rice storage proteins, and whether it is located in the same or separate phases within these. Methods The protein distribution and the expression pattern of HMW sub-unit 1Dx5 in transgenic rice endosperm at different stages of development were determined using light and electron microscopy after labelling with antibodies. Key results The use of HMW-GS-specific antibodies showed that sub-unit 1Dx5 was expressed mainly in the sub-aleurone cells of the endosperm and that it was deposited in both types of protein body present in the rice endosperm: derived from the ER and containing prolamins, and derived from the vacuole and containing glutelins. In addition, new types of protein bodies were also formed within the endosperm cells. Conclusions The results suggest that the HMW 1Dx5 protein could be trafficked by either the ER or vacuolar pathway, possibly depending on the stage of development, and that its accumulation in the rice endosperm could compromise the structural integrity of protein bodies and their segregation into two distinct populations in the mature endosperm.

Cashew cultivation, access to land and food security in Brong-Ahafo Region, Ghana: Preventing the intergenerational transmission of poverty

This research aimed to investigate the implications of changing agricultural land use from food production towards increased cashew cultivation for food security and poverty alleviation in Jaman North District, Brong-Ahafo Region of Ghana. Based on qualitative, participatory research with a total of 60 participants, the research found that increased cashew production had led to improvements in living standards for many farmers and their children over recent years. Global demand for cashew is projected to continue to grow rapidly in the immediate future and cashew-growing areas of Ghana are well placed to respond to this demand. Cashew farmers however were subject to price fluctuations in the value of Raw Cashew Nuts (RCN) due to unequal power relations with intermediaries and export buyer companies and global markets, in addition to other vulnerabilities that constrained the quality and quantity of cashew and food crops they could produce. The expansion of cashew plantations was leading to pressure on the remaining family lands available for food crop production, which community members feared could potentially compromise the food security of rural communities and the land inheritance of future generations.

On the application of optimal wavelet filter banks for ECG signal classification

This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier.

The effect of rapid changes in ionospheric flow on velocity vectors deduced from radar beam-swinging experiments

The effects on the horizontal ionospheric velocity vectors deduced from radar beam-swinging experiments, which occur when changes in the flow take place on short time scales compared with the experiment cycle time, are analysed in detail. The further complications which arise in the interpretation of beam-swinging data, due to longitudinal gradients in the flow and to field-aligned flows, are also considered. It is concluded that these effects are unlikely to seriously compromise statistical determinations of the response time of the flow, e.g. to changes in the north-south component of the IMF, such as have been recently reported by Etemadiet al. (1988, Planet. Space Sci.36, 471), using EISCAT ‘Polar’ data.

The neurological underpinnings of cluttering: some initial findings

Background Cluttering is a fluency disorder characterised by overly rapid or jerky speech patterns that compromise intelligibility. The neural correlates of cluttering are unknown but theoretical accounts implicate the basal ganglia and medial prefrontal cortex. Dysfunction in these brain areas would be consistent with difficulties in selection and control of speech motor programs that are characteristic of speech disfluencies in cluttering. There is a surprising lack of investigation into this disorder using modern imaging techniques. Here, we used functional MRI to investigate the neural correlates of cluttering. Method We scanned 17 adults who clutter and 17 normally fluent control speakers matched for age and sex. Brain activity was recorded using sparse-sampling functional MRI while participants viewed scenes and either (i) produced overt speech describing the scene or (ii) read out loud a sentence provided that described the scene. Speech was recorded and analysed off line. Differences in brain activity for each condition compared to a silent resting baseline and between conditions were analysed for each group separately (cluster-forming threshold Z > 3.1, extent p < 0.05, corrected) and then these differences were further compared between the two groups (voxel threshold p < 0.01, extent > 30 voxels, uncorrected). Results In both conditions, the patterns of activation in adults who clutter and control speakers were strikingly similar, particularly at the cortical level. Direct group comparisons revealed greater activity in adults who clutter compared to control speakers in the lateral premotor cortex bilaterally and, as predicted, on the medial surface (pre-supplementary motor area). Subcortically, adults who clutter showed greater activity than control speakers in the basal ganglia. Specifically, the caudate nucleus and putamen were overactive in adults who clutter for the comparison of picture description with sentence reading. In addition, adults who clutter had reduced activity relative to control speakers in the lateral anterior cerebellum bilaterally. Eleven of the 17 adults who clutter also stuttered. This comorbid diagnosis of stuttering was found to contribute to the abnormal overactivity seen in the group of adults who clutter in the right ventral premotor cortex and right anterior cingulate cortex. In the remaining areas of abnormal activity seen in adults who clutter compared to controls, the subgroup who clutter and stutter did not differ from the subgroup who clutter but do not stutter. Conclusions Our findings were in good agreement with theoretical predictions regarding the neural correlates of cluttering. We found evidence for abnormal function in the basal ganglia and their cortical output target, the medial prefrontal cortex. The findings are discussed in relation to models of cluttering that point to problems with motor control of speech.

The pitfalls of ecological forecasting

Ecological forecasting is difficult but essential, because reactive management results in corrective actions that are often too late to avert significant environmental damage. Here, we appraise different forecasting methods with a particular focus on the modelling of species populations. We show how simple extrapolation of current trends in state is often inadequate because environmental drivers change in intensity over time and new drivers emerge. However, statistical models, incorporating relationships with drivers, simply offset the prediction problem, requiring us to forecast how the drivers will themselves change over time. Some authors approach this problem by focusing in detail on a single driver, whilst others use ‘storyline’ scenarios, which consider projected changes in a wide range of different drivers. We explain why both approaches are problematic and identify a compromise to model key drivers and interactions along with possible response options to help inform environmental management. We also highlight the crucial role of validation of forecasts using independent data. Although these issues are relevant for all types of ecological forecasting, we provide examples based on forecasts for populations of UK butterflies. We show how a high goodness-of-fit for models used to calibrate data is not sufficient for good forecasting. Long-term biological recording schemes rather than experiments will often provide data for ecological forecasting and validation because these schemes allow capture of landscape-scale land-use effects and their interactions with other drivers.

Effects of aluminium chloride and aluminium chlorohydrate on DNA repair in MCF10A immortalised non-transformed human breast epithelial cells

Use of underarm aluminium (Al)-based antiperspirant salts may be a contributory factor in breast cancer development. At the 10th Keele meeting, Al was reported to cause anchorage-independent growth and double strand DNA breaks in MCF10A immortalised non-transformed human breast epithelial cells. We now report that exposure of MCF10A cells to Al chloride or Al chlorohydrate also compromised DNA repair systems. Longterm (19–21 weeks) exposure to Al chloride or Al chlorohydrate at a 10−4 M concentration resulted in reduced levels of BRCA1 mRNA as determined by real-time RT-PCR and BRCA1 protein as determined by Western immunoblotting. Reduced levels of mRNA for other DNA repair genes (BRCA2, CHK1, CHK2, Rad51, ATR) were also observed using real-time RT-PCR. Loss of BRCA1 or BRCA2 gene function has long been associated with inherited susceptibility to breast cancer but these results suggest that exposure to aluminium-based antiperspirant salts may also reduce levels of these key components of DNA repair in breast epithelial cells. If Al can not only damage DNA but also compromise DNA repair systems, then there is the potential for Al to impact on breast carcinogenesis.

An upgrade on the rabbit model of anthracycline-induced cardiomyopathy: shorter protocol, reduced mortality, and higher incidence of overt dilated cardiomyopathy

Current protocols of anthracycline-induced cardiomyopathy in rabbits present with high premature mortality and nephrotoxicity, thus rendering them unsuitable for studies requiring long-term functional evaluation of myocardial function (e.g., stem cell therapy). We compared two previously described protocols to an in-house developed protocol in three groups: Group DOX2 received doxorubicin 2 mg/kg/week (8 weeks); Group DAU3 received daunorubicin 3 mg/kg/week (10 weeks); and Group DAU4 received daunorubicin 4 mg/kg/week (6 weeks). A cohort of rabbits received saline (control). Results of blood tests, cardiac troponin I, echocardiography, and histopathology were analysed. Whilst DOX2 and DAU3 rabbits showed high premature mortality (50% and 33%, resp.), DAU4 rabbits showed 7.6% premature mortality. None of DOX2 rabbits developed overt dilated cardiomyopathy; 66% of DAU3 rabbits developed overt dilated cardiomyopathy and quickly progressed to severe congestive heart failure. Interestingly, 92% of DAU4 rabbits showed overt dilated cardiomyopathy and 67% developed congestive heart failure exhibiting stable disease. DOX2 and DAU3 rabbits showed alterations of renal function, with DAU3 also exhibiting hepatic function compromise. Thus, a shortened protocol of anthracycline-induced cardiomyopathy as in DAU4 group results in high incidence of overt dilated cardiomyopathy, which insidiously progressed to congestive heart failure, associated to reduced systemic compromise and very low premature mortality.

Comparing finite state machine test coverage criteria

To plan testing activities, testers face the challenge of determining a strategy, including a test coverage criterion that offers an acceptable compromise between the available resources and test goals. Known theoretical properties of coverage criteria do not always help and, thus, empirical data are needed. The results of an experimental evaluation of several coverage criteria for finite state machines (FSMs) are presented, namely, state and transition coverage; initialisation fault and transition fault coverage. The first two criteria focus on FSM structure, whereas the other two on potential faults in FSM implementations. The authors elaborate a comparison approach that includes random generation of FSM, construction of an adequate test suite and test minimisation for each criterion to ensure that tests are obtained in a uniform way. The last step uses an improved greedy algorithm.

En studie om rehabilitering - en skamgörande process

The purpose of this essay is using theories about labeling and social bonds to study whether a measure of rehabilitation for the psychically disabled contributes to a return to a normal status as not-labeled. Partly we examine whether the activities organized by the regulation-ruled authorities during the work of rehabilitation lead to shame or pride, and partly how these activities are organized regarding the processes that lead to the emotions pride or shame among the participants. Method: qualitative semi-structured face-to-face interviews with professional rehabilitation-actors at the Public Employment Office (PEO), the Social Insurance Office (SIO), the Social Service (SOS), the Psychiatry and the Division of Labour Market (AME).Conclusions: the Psychiatry clients are treated with respect, may participate, and communication is characterized by attunement, therefore strong social bonds can be built. On the contrary, among the other examined activities, we found many elements that arouse shame. Since these are more ruled by regulations, the result is engulfment and demands on conformity, because the compromise-possibilities are almost non-existent. Psychically disabled persons are met by prejudice, ignorance, disrespect and a non-solidarity-language. To get help, the individual has to accept a label in form of a diagnosis, and this labeling leads to a negative self-image. Furthermore the psychically disabled persons are falling between two chairs because of a weak cooperation between the rehabilitation-actors. Bimodal alienation and triangulation contributes to the difficulties in cooperation.Result: the social bonds are not strong enough to achieve a rehabilitation-effect. Even if the treatment from each administrator is important, we find the explanation-level primarily in laws, rules and government, because the structure rules the rehabilitation-measures, with shame as a consequence. Since we found elements of shame institutionalized in the way of working at PEO, SIO, SOS and AME, it means that social bonds can never reach a level good enough for achieving pride and normalization from a deviance or labeled identity.

The Compromised Researcher : Issues in Feminist Research Methodologies

This article centres on issues of vulnerability and being compromised in feminist research where the focus has frequently been on researching the same. Compromise, here used in its pejorative sense, may for instance occur in terms of one’s research topic, the methods one utilizes, or the participants chosen for a study. Drawing on a range of examples including the methodological work of Ann Oakley (1981, 2000) as well as three articles on researching men that appeared in the journal Signs in 2005, I argue that feminist researchers, possibly because they work in an identity-based discipline, may be diversely vulnerable when researching the same and/or researching the different, and can be compromised both by how they are treated by those whom they encounter in their research and by their own behaviour in that context. I suggest that these concerns are under-articulated in feminist research and conclude with a series of questions that need to be raised. 

Real time video segmentation for recognising paint marks on bad wooden railway sleepers

Wooden railway sleeper inspections in Sweden are currently performed manually by a human operator; such inspections are based on visual analysis. Machine vision based approach has been done to emulate the visual abilities of human operator to enable automation of the process. Through this process bad sleepers are identified, and a spot is marked on it with specific color (blue in the current case) on the rail so that the maintenance operators are able to identify the spot and replace the sleeper. The motive of this thesis is to help the operators to identify those sleepers which are marked by color (spots), using an “Intelligent Vehicle” which is capable of running on the track. Capturing video while running on the track and segmenting the object of interest (spot) through this vehicle; we can automate this work and minimize the human intuitions. The video acquisition process depends on camera position and source light to obtain fine brightness in acquisition, we have tested 4 different types of combinations (camera position and source light) here to record the video and test the validity of proposed method. A sequence of real time rail frames are extracted from these videos and further processing (depending upon the data acquisition process) is done to identify the spots. After identification of spot each frame is divided in to 9 regions to know the particular region where the spot lies to avoid overlapping with noise, and so on. The proposed method will generate the information regarding in which region the spot lies, based on nine regions in each frame. From the generated results we have made some classification regarding data collection techniques, efficiency, time and speed. In this report, extensive experiments using image sequences from particular camera are reported and the experiments were done using intelligent vehicle as well as test vehicle and the results shows that we have achieved 95% success in identifying the spots when we use video as it is, in other method were we can skip some frames in pre-processing to increase the speed of video but the segmentation results we reduced to 85% and the time was very less compared to previous one. This shows the validity of proposed method in identification of spots lying on wooden railway sleepers where we can compromise between time and efficiency to get the desired result.

A data driven approach for automating vehicle activated signs

Vehicle activated signs (VAS) display a warning message when drivers exceed a particular threshold. VAS are often installed on local roads to display a warning message depending on the speed of the approaching vehicles. VAS are usually powered by electricity; however, battery and solar powered VAS are also commonplace. This thesis investigated devel-opment of an automatic trigger speed of vehicle activated signs in order to influence driver behaviour, the effect of which has been measured in terms of reduced mean speed and low standard deviation. A comprehen-sive understanding of the effectiveness of the trigger speed of the VAS on driver behaviour was established by systematically collecting data. Specif-ically, data on time of day, speed, length and direction of the vehicle have been collected for the purpose, using Doppler radar installed at the road. A data driven calibration method for the radar used in the experiment has also been developed and evaluated. Results indicate that trigger speed of the VAS had variable effect on driv-ers’ speed at different sites and at different times of the day. It is evident that the optimal trigger speed should be set near the 85th percentile speed, to be able to lower the standard deviation. In the case of battery and solar powered VAS, trigger speeds between the 50th and 85th per-centile offered the best compromise between safety and power consump-tion. Results also indicate that different classes of vehicles report differ-ences in mean speed and standard deviation; on a highway, the mean speed of cars differs slightly from the mean speed of trucks, whereas a significant difference was observed between the classes of vehicles on lo-cal roads. A differential trigger speed was therefore investigated for the sake of completion. A data driven approach using Random forest was found to be appropriate in predicting trigger speeds respective to types of vehicles and traffic conditions. The fact that the predicted trigger speed was found to be consistently around the 85th percentile speed justifies the choice of the automatic model.

Triggering Solar-Powered Vehicle Activated Signs using Self Organising Maps with K-means

Solar-powered vehicle activated signs (VAS) are speed warning signs powered by batteries that are recharged by solar panels. These signs are more desirable than other active warning signs due to the low cost of installation and the minimal maintenance requirements. However, one problem that can affect a solar-powered VAS is the limited power capacity available to keep the sign operational. In order to be able to operate the sign more efficiently, it is proposed that the sign be appropriately triggered by taking into account the prevalent conditions. Triggering the sign depends on many factors such as the prevailing speed limit, road geometry, traffic behaviour, the weather and the number of hours of daylight. The main goal of this paper is therefore to develop an intelligent algorithm that would help optimize the trigger point to achieve the best compromise between speed reduction and power consumption. Data have been systematically collected whereby vehicle speed data were gathered whilst varying the value of the trigger speed threshold. A two stage algorithm is then utilized to extract the trigger speed value. Initially the algorithm employs a Self-Organising Map (SOM), to effectively visualize and explore the properties of the data that is then clustered in the second stage using K-means clustering method. Preliminary results achieved in the study indicate that using a SOM in conjunction with K-means method is found to perform well as opposed to direct clustering of the data by K-means alone. Using a SOM in the current case helped the algorithm determine the number of clusters in the data set, which is a frequent problem in data clustering.