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Postnatal care (PNC) refers to the care given to the mother and the newborn from the time of delivery until six weeks of age. Despite attempts, postnatal care (PNC) delivery still falls short of meeting mothers’ and newborns’ needs. With approximately 90% of mobile phone users coming from underdeveloped nations, there is more room for improved maternal and neonatal health interventions. With the aid of mobile technologies, this study attempts to boost PNC adoption. Studies showed that the case study area, Tanzania, had little evidence of PNC intervention frameworks and mobile applications. First, it was determined which factors affected how well health systems handled postpartum care (PNC). Data were gathered from health facilities at every level in Mbeya, Tanzania. Following the examination of descriptive statistics, postpartum women had lower levels of satisfaction with the advice given to them by healthcare professionals regarding clinical attendance (mean = 2.81). After giving birth, postpartum mothers who remained in the medical centre longer had an 85% lower likelihood of being happy with the health system. Higher educated postpartum women had less favourable sentiments about PNC delivery. The findings pointed to the necessity of raising PNC awareness in order to enhance both health worker performance and the well-being of a mother and her newborn. These findings were used to create a framework that also included PNC performance indicators from the WHO and services that might help the mother and the health worker. Using JavaScript’s React native technology and the SQLite database engine, the Afya Mama mobile application was created. This study is of considerable importance to communities in Tanzania as a whole as it improves the uptake of PNC

Late blight (LB) disease causes significant annual losses in tomato production. Early identification of this disease is crucial in halting its severity. This study aimed to leverage the strength of Convolutional Neural Networks (CNNs) in automated prediction of tomato LB. Through transfer learning, the MobileNetV3 model was trained on high-quality, well-labeled images from Kaggle datasets. The trained model was tested on different images of healthy and infected leaves taken from different real-world locations in Mbeya, Arusha, and Morogoro. Test results demonstrated the model's success in identifying LB disease, with an accuracy of 81% and a precision of 76%. The trained model has the potential to be integrated into an offline mobile app for real-time use, improving the efficiency and effectiveness of LB disease detection in tomato production. Similar methods could also be applied to detect other tomato infections. Keywords: MobileNets; convolutional neural networks; plant diseases detection; image classification; transfer learning

Clean water is a scarce resource for the human life and is subject to wastage due to leakage of the distribution pipes in large cities. Water pipe leakage is a big problem around the world of which most of the water distribution authorities faces difficulties to detect the location of the fault. This problem of leakage can be caused by several factors such as breakage of the pipelines due to aging or ongoing constructions in urban cities like Dar es salaam, consequently due to that case, the distribution authorities face hardship to identify the cause and enable them to take action. Therefore, the aim of this project was to develop an IoT-based system for water leakage detection. The prototype was developed comprising two sensors embedded at the source and destination points to measure the flow rate of water. The result indicated that the volume of water generated at the start point can be compared with the other end to determine if there is any leakage. A greater focus on distance calculation could produce interesting findings that account for more research on IoT monitoring systems.

Background and ObjectivesTask fMRI is a clinical tool for language lateralization, but has limitations, and cannot provide information about network-level plasticity. Additional methods are needed to improve the precision of presurgical language mapping. We investigate language resting-state functional connectivity (RS fMRI; FC) in typically developing children (TD) and children with epilepsy. Our objectives were to (1) understand how FC components differ between TD children and those with epilepsy; (2) elucidate how the location of disease (frontal/temporal epilepsy foci) affects FC; and (3) investigate the relationship between age and FC.MethodsOur sample included 55 TD children (mean age 12 years, range 7–18) and 31 patients with focal epilepsy (mean age 13 years, range 7–18). All participants underwent RS fMRI. Using a bilateral canonical language map as target, vertex-wise intrahemispheric FC map and interhemispheric FC map for each participant were computed and thresholded at top 10% to compute an FC laterality index (FCLI; [(L – R)/(L + R)]) of the frontal and temporal regions for both integration (intrahemispheric FC; FCLIi) and segregation (interhemispheric FC; FCLIs) maps.ResultsWe found FC differences in the developing language network based on disease, seizure foci location, and age. Frontal and temporal FCLIi was different between groups (t[84] = 2.82, p < 0.01; t[84] = 4.68, p < 0.01, respectively). Frontal epilepsy foci had the largest differences from TD (Cohen d frontal FCLIi = 0.84, FCLIs = 0.51; temporal FCLIi = 1.29). Development and disease have opposing influences on the laterality of FC based on groups. In the frontal foci group, FCLIi decreased with age (r = −0.42), whereas in the temporal foci group, FCLIi increased with age (r = 0.40). Within the epilepsy group, increases in right frontal integration FCLI relates to increased right frontal task activation in our mostly left language dominant group (r = 0.52, p < 0.01). Language network connectivity is associated with higher verbal intelligence in children with epilepsy (r = 0.45, p < 0.05).DiscussionThese findings lend preliminary evidence that FC reflects network plasticity in the form of adaptation and compensation, or the ability to recruit support and reallocate resources within and outside of the traditional network to compensate for disease. FC expands on task-based fMRI and provides complementary and potentially useful information about the language network that is not captured using task-based fMRI alone.

BACKGROUND: Schistosomiasis elimination has gained renewed priority in the WHO guidance documents published in 2020 and 2022. The SchistoBreak project, implemented in Pemba, Tanzania between 2020 and 2024, aims to assess new tools and strategies for shifting from elimination as a public health problem towards interruption of transmission. Here we report our baseline findings and discuss implications for future interventions. METHODS: In 2020, human water contact sites (HWCSs) in the study area were geolocated and snail surveys were conducted. A parasitological and questionnaire cross-sectional baseline survey was implemented in 20 communities and their 16 primary schools between November 2020 and February 2021. Urine samples were collected at the school and household levels from individuals aged >/= 4 years. Schistosoma haematobium infection was detected by urine filtration microscopy. Snail, parasitological and questionnaire-derived data were analyzed descriptively, spatially and with generalized estimated equation models. RESULTS: The intermediate host snail Bulinus globosus was detected in 19.8% (33/167) of HWCSs. The overall S. haematobium prevalence was 1.2% (26/2196) in school-aged children and 0.8% (31/3893) in community members, with 0.2% (4/2196) and 0.1% (3/3893) heavy-intensity infections, respectively. Children who studied 2 km away (odds ratio [OR]: 5.0; 95% confidence interval [CI]: 2.3-11.1). Individuals living in a house located 2 km distance (OR: 18.0; 95% CI: 2.9-111.0). Self-reported praziquantel treatment coverage was 83.2% (2015/2423) in schoolchildren in the mass drug administration (MDA) conducted in August 2020. Coverage among adult community members was 59.9% (574/958), but only 34.8% (333/958) took praziquantel correctly. CONCLUSIONS: While the S. haematobium prevalence is very low in Pemba, there are many HWCSs with B. globosus situated close to schools or houses that pose a considerable risk of recrudescence. To maintain and accelerate the progress towards interruption of transmission, targeted and cost-effective interventions that are accepted by the community are needed; for example, snail control plus focal MDA, or test-and-treat in schools and households near infested waterbodies.

Background Global elimination of schistosomiasis as a public health problem is set as target in the new World Health Organization’s Neglected Tropical Diseases Roadmap for 2030. Due to a long history of interventions, the Zanzibar islands of Tanzania have reached this goal since 2017. However, challenges occur on the last mile towards interruption of transmission. Our study will investigate new tools and strategies for breaking schistosomiasis transmission. Methods The study is designed as an intervention study, documented through repeated cross-sectional surveys (2020–2024). The primary endpoint will be the sensitivity of a surveillance-response approach to detect and react to outbreaks of urogenital schistosomiasis over three years of implementation. The surveys and multi-disciplinary interventions will be implemented in 20 communities in the north of Pemba island. In low-prevalence areas, surveillance-response will consist of active, passive and reactive case detection, treatment of positive individuals, and focal snail control. In hotspot areas, mass drug administration, snail control and behaviour change interventions will be implemented. Parasitological cross-sectional surveys in 20 communities and their main primary schools will serve to adapt the intervention approach annually and to monitor the performance of the surveillance-response approach and impact of interventions. Schistosoma haematobium infections will be diagnosed using reagent strips and urine filtration microscopy, and by exploring novel point-of-care diagnostic tests. Discussion Our study will shed light on the field applicability and performance of novel adaptive intervention strategies, and standard and new diagnostic tools for schistosomiasis elimination. The evidence and experiences generated by micro-mapping of S. haematobium infections at community level, micro-targeting of new adaptive intervention approaches, and application of novel diagnostic tools can guide future strategic plans for schistosomiasis elimination in Zanzibar and inform other countries aiming for interruption of transmission. Trial registration ISRCTN, ISCRCTN91431493. Registered 11 February 2020, https://www.isrctn.com/ISRCTN91431493

Trend analysis of atmospheric aerosols enhances confidence in the evaluation of both direct and indirect effects of aerosols on regional climate change. To comprehensively achieve this over East Africa, it’s important to understand aerosols temporal characteristics over well selected sites namely Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0°S - 0.6°S; 35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). In this context, trend analysis (annual (in Aerosol Optical Depth (AOD) at 550 nm and &#197ngstr&#246m Exponent Anomaly (&#197EA) at 470 - 660 nm) and seasonal (AOD)) from Moderate Resolution Imaging Spectroradiometer (MODIS) were performed following the weighted least squares (WLS) fitting method for the period 2000 to 2013. The MODIS AOD annual trends were ground-truthed by AErosol RObotic NETwork (AERONET) data. Tropical Rainfall Measurement Mission (TRMM) was utilized to derive rainfall rates (RR) in order to assess its influence on the observed aerosol temporal characteristics. The derived annual AOD trends utilizing MODIS and AERONET data were consistent with each other. However, monthly AOD and RR were found to be negatively correlated over Nairobi, Mbita, Mau forest complex and Malindi. There was no clear relationship between the two trends over Kampala and Mount Kilimanjaro, which may imply the role of aerosols in cloud modulation and hence RR received. Seasonality is evident between AOD and &#197EA annual trends as these quantities were observed to be modulated by RR. AOD was observed to decrease over East Africa except Nairobi during the study period as a result of RR during the study period. Unlike the other study sites, Nairobi shows positive trends in AOD that may be attributed to increasing populace and fossil fuel, vehicular-industrial emission and biomass and refuse burning during the study period. Negative trends over the rest of the study sites were associated to rain washout. The AOD and &#197EA derived annual trends were found to meet the statistical significance of 95% confidence level over each study site.

Development of a task-free method for presurgical mapping of language function is important for use in young or cognitively impaired patients. Resting state connectivity fMRI (RS-fMRI) is a task-free method that may be used to identify cognitive networks. We developed a voxelwise RS-fMRI metric, Functional Connectivity Hemispheric Contrast (FC-HC), to map the language network and determine language laterality through comparison of within-hemispheric language network connections (Integration) to cross-hemispheric connections (Segregation). For the first time, we demonstrated robustness and efficacy of a RS-fMRI metric to map language networks across five groups (total N = 243) that differed in MRI scanning parameters, fMRI scanning protocols, age, and development (typical vs pediatric epilepsy). The resting state FC-HC maps for the healthy pediatric and adult groups showed higher values in the left hemisphere, and had high agreement with standard task language fMRI; in contrast, the epilepsy patient group map was bilateral. FC-HC has strong but not perfect agreement with task fMRI and thus, may reflect related and complementary information about language plasticity and compensation.

The improved use of Electronic Health Record (EHR) Systems provides an opportunity to improve the overall efficiency and quality of care of patients with epilepsy. Tools and strategies that may be incorporated into the use of EHRs include utilizing patient generated data, clinical decision support systems and natural language processing systems. Standardization of data from EHR systems may lead to improvement in clinical research through the creation of data collections and multi-center collaborations. Challenges to collaborative use of EHR Systems across centers include costs and the diversity of EHR systems.

In the last decades, several endangered breeds of livestock species have been re-established effectively. However, the successful revival of the Dutch and Danish Landrace goats involved crossing with exotic breeds and the ancestry of the current populations is therefore not clear. We have generated genotypes for 27 FAO-recommended microsatellites of these landraces and three phenotypically similar Nordic-type landraces and compared these breeds with central European, Mediterranean and south-west Asian goats. We found decreasing levels of genetic diversity with increasing distance from the south-west Asian domestication site with a south-east-to-north-west cline that is clearly steeper than the Mediterranean east-to-west cline. In terms of genetic diversity, the Dutch Landrace comes next to the isolated Icelandic breed, which has an extremely low diversity. The Norwegian coastal goat and the Finnish and Icelandic landraces are clearly related. It appears that by a combination of mixed origin and a population bottleneck, the Dutch and Danish Land-races are separated from the other breeds. However, the current Dutch and Danish populations with the multicoloured and long-horned appearance effectively substitute for the original breed, illustrating that for conservation of cultural heritage, the phenotype of a breed is more relevant than pure ancestry and the genetic diversity of the original breed. More in general, we propose that for conservation, the retention of genetic diversity of an original breed and of the visual phenotype by which the breed is recognized and defined needs to be considered separately., Stichting Zeldzame Huisdierassen

Two hypotheses of autism spectrum disorder (ASD) propose that this condition is characterized by deficits in Theory of Mind and by hypoconnectivity between remote cortical regions with hyperconnectivity locally. The default mode network (DMN) is a set of remote, functionally connected cortical nodes less active during executive tasks than at rest and is implicated in Theory of Mind, episodic memory, and other self-reflective processes. We show that children with ASD have reduced connectivity between DMN nodes and increased local connectivity within DMN nodes and the visual and motor resting-state networks. We show that, like the trajectory of synaptogenesis, internodal DMN functional connectivity increased as a quadratic function of age in typically developing children, peaking between, 11 and 13 years. In children with ASD, these long-distance connections fail to develop during adolescence. These findings support the “developmental disconnection model” of ASD, provide a possible mechanistic explanation for the Theory-of-Mind hypothesis of ASD, and show that the window for effectively treating ASD could be wider than previously thought.

The effectiveness of whole or powdered leaves (botanicals) from four locally grown plant species applied at a rate of 1.5 kg per 100 kg beans ( Phaseolus vulgaris ) against Acanthoscelides obtectus and Zabrotes subfasciatus was compared under laboratory and farm conditions. In the laboratory, Chenopodium ambrosioides , applied as powder or as whole leaves, was the most effective, with 100% mortality of adult insects in less than three days and no progeny. Less C. ambrosioides (about 200 g per 100 kg beans) still resulted in 100% mortality within 24 h. Tagetes minuta applied as powder also increased mortality and reduced oviposition and progeny production significantly. The other treatments – T. minuta applied as leaves, and Azadirachta indica or Cupressus lusitanica applied as powder or as whole leaves – had no significant effects upon mortalities, oviposition rate, or progeny production compared with control treatments. When the rate of application was increased to about 8.3 kg per 100 kg beans, there was a slight increase in mortality using T. minuta and A. indica , but not with C. lusitanica . An additional trial with C. ambrosioides from different collections and with plants at different stages of development revealed considerable variations in the efficacy of the treatment. In the on-farm trials, A. indica -seed powder was the most effective treatment, followed respectively by leaf powders of C. ambrosioides , C. lusitanica and T. minuta . All treatments were significantly more effective than the control in reducing the numbers of live insects; they also reduced numbers of damaged beans and maintained germination rates after 5 months of storage. The results of evaluations of the treatments made by farmers just after the trials and five years later are reported.

Novel deception detection techniques have been in creation for centuries. Functional magnetic resonance imaging (fMRI) is a neuroscience technology that non-invasively measures brain activity associated with behavior and cognition. A number of investigators have explored the utilization and efficiency of fMRI in deception detection. In this study, 18 subjects were instructed during an fMRI "line-up" task to either conceal (lie) or reveal (truth) the identities of individuals seen in study sets in order to determine the neural correlates of intentionally misidentifying previously known faces (lying about recognition). A repeated measures ANOVA (lie vs. truth and familiar vs. unfamiliar) and two paired t-tests (familiar vs. unfamiliar and familiar lie vs. familiar truth) revealed areas of activation associated with deception in the right MGF, red nucleus, IFG, SMG, SFG (with ACC), DLPFC, and bilateral precuneus. The areas activated in the present study may be involved in the suppression of truth, working and visuospatial memories, and imagery when providing misleading (deceptive) responses to facial identification prompts in the form of a "line-up".

Neural networks for processing language often are reorganized in patients with epilepsy. However, the extent and location of within and between hemisphere re-organization are not established. We studied 45 patients, all with a left hemisphere seizure focus (mean age 22.8, seizure onset 13.3), and 19 normal controls (mean age 24.8) with an fMRI word definition language paradigm to assess the location of language processing regions. Individual patient SPM maps were compared to the normal group in a voxel-wise comparison; a voxel was considered to be significant if its z-value exceeded mid R:2mid R:. Subsequently, we used principal component analysis with hierarchical clustering of variance patterns from individual difference maps to identify four patient sub-groups. One did not differ from normal controls; one had increased left temporal activation on the margin of regions activated in controls; two others had recruitment in right inferior frontal gyrus, middle frontal gyrus and temporal cortex. Right hemisphere activation in these two groups occurred in homologues of left hemisphere regions that sustained task activation. Our study used novel data driven methods to find evidence for constraints on inter-hemispheric reorganization of language in recruitment of right homologues, and, in a subpopulation of patients, evidence for intra-hemispheric reorganization of language limited to the margins of typical left temporal regional activation. These methods may be applied to investigate both normal and pathological variance in other developmental disorders and cognitive domains.