Long term dynamics for the restricted N-body problem with mean motion resonances and crossing singularities

We consider the long term dynamics of the restricted N -body problem, modeling in a statistical sense the motion of an asteroid in the gravitational field of the Sun and the solar system planets. We deal with the case of a mean motion resonance with one planet and assume that the osculating trajectory of the asteroid crosses the one of some planet, possibly different from the resonant one, during the evolution. Such crossings produce singularities in the differential equations for the motion of the asteroid, obtained by standard perturbation theory. In this work we prove that the vector field of these equations can be extended to two locally Lipschitz-continuous vector fields on both sides of a set of crossing conditions. This allows us to define generalized solutions, continuous but not differentiable, going beyond these singularities. Moreover, we prove that the long term evolution of the ’signed’ orbit distance (Gronchi and Tommei 2007) between the asteroid and the planet is differentiable in a neighborhood of the crossing times. In case of crossings with the resonant planet we recover the known dynamical protection mechanism against collisions. We conclude with a numerical comparison between the long term and the full evolutions in the case of asteroids belonging to the ’Alinda’ and ’Toro’ classes (Milani et al. 1989). This work extends the results in (Gronchi and Tardioli 2013) to the relevant case of asteroids in mean motion resonance with a planet

The Identification of Sustainability Assessment Indicators for Road Infrastructure Projects in Tanzania

The performance of sustainability in infrastructure projects continues to face challenges in its implementation and attainment in developing countries, one of which is the lack of appraisal tools and indicators for the assessment of sustainability. Studies indicate that there are no formal indicators for sustainability assessment on road infrastructure projects in Tanzania, the lack of which limits the determination of whether projects implemented are sustainable or not. Therefore, this study aimed at determining the key sustainability assessment indicators used for road infrastructure projects in Tanzania. A concurrent mixed research approach was adopted in which the sample was purposively selected. A content analysis and descriptive statistics using the Statistical Package for the Social Sciences (SPSS 20.0) were used to analyze qualitative and quantitative data, respectively. The findings indicate that 24 indicators are applicable to Tanzania. Among the highly ranked include “health and safety training to workers”, “health and safety personnel in the project team”, “site barriers and safety warning signs”, “personal protective equipment (PPE) provision”, and “waste collection”. The qualitative results further support the identified sustainability assessment indicators on road infrastructure projects in Tanzania, with one new indicator of “air quality” emerging. The findings inform the government and other relevant stakeholders in the construction industry including planners, designers, and project managers of the key sustainability assessment indicators for roads, which would influence regulation as well as policies to improve the sustainability performance of road projects in Tanzania

Barriers to the Integration of Building Information Modeling (BIM) in Modular Construction in Sub-Saharan Africa

The construction industry is constantly evolving through government policies, technologies, and innovative processes. BIM and modular construction are innovative concepts aimed at achieving sustainable smart cities by enhancing cost performance, efficiency, and sustainability. Despite growing global interest in their integration, there is a notable knowledge gap in sub-Saharan Africa. As a result, this research aims to explore the barriers to integrating BIM into modular construction in sub-Saharan Africa. The study adopted a non-experimental design, using a four-stage methodological framework. Initially, a literature review was carried out to conceptualize the study. Stage two involves a pilot survey to create an adequate data collection instrument. In the third stage, 81 registered companies were purposely selected, and data was collected through an online survey. Finally, the fourth stage uses descriptive and inferential techniques to make logical and informed conclusions. The top-ranked barriers are high initial costs, insufficient cross-field expertise, stakeholder collaboration problems, limited software interoperability, and skills shortages. Recommendations include early stakeholder collaboration, BIM execution plan development by modular companies, improved staff training, and increasing financial support from the government. Future research should explore country-specific barriers and case studies to aid the integration of the two innovative solutions in the region

oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data

The complexity and high dimensionality of neuroimaging data pose problems for decoding information with machine learning (ML) models because the number of features is often much larger than the number of observations. Feature selection is one of the crucial steps for determining meaningful target features in decoding; however, optimizing the feature selection from such high-dimensional neuroimaging data has been challenging using conventional ML models. Here, we introduce an efficient and high-performance decoding package incorporating a forward variable selection (FVS) algorithm and hyper-parameter optimization that automatically identifies the best feature pairs for both classification and regression models, where a total of 18 ML models are implemented by default. First, the FVS algorithm evaluates the goodness-of-fit across different models using the k-fold cross-validation step that identifies the best subset of features based on a predefined criterion for each model. Next, the hyperparameters of each ML model are optimized at each forward iteration. Final outputs highlight an optimized number of selected features (brain regions of interest) for each model with its accuracy. Furthermore, the toolbox can be executed in a parallel environment for efficient computation on a typical personal computer. With the optimized forward variable selection decoder (oFVSD) pipeline, we verified the effectiveness of decoding sex classification and age range regression on 1,113 structural magnetic resonance imaging (MRI) datasets. Compared to ML models without the FVS algorithm and with the Boruta algorithm as a variable selection counterpart, we demonstrate that the oFVSD significantly outperformed across all of the ML models over the counterpart models without FVS (approximately 0.20 increase in correlation coefficient, r, with regression models and 8% increase in classification models on average) and with Boruta variable selection algorithm (approximately 0.07 improvement in regression and 4% in classification models). Furthermore, we confirmed the use of parallel computation considerably reduced the computational burden for the high-dimensional MRI data. Altogether, the oFVSD toolbox efficiently and effectively improves the performance of both classification and regression ML models, providing a use case example on MRI datasets. With its flexibility, oFVSD has the potential for many other modalities in neuroimaging. This open-source and freely available Python package makes it a valuable toolbox for research communities seeking improved decoding accuracy

The Effect of Switching to Second-Line Antiretroviral Therapy on the Risk of Opportunistic Infections Among Patients Infected With Human Immunodeficiency Virus in Northern Tanzania

Background. Due to the unintended potential misclassifications of the World Health Organization (WHO) immunological failure criteria in predicting virological failure, limited availability of treatment options, poor laboratory infrastructure, and healthcare providers’ confidence in making switches, physicians delay switching patients to second-line antiretroviral therapy (ART). Evaluating whether timely switching and delayed switching are associated with the risk of opportunistic infections (OI) among patients with unrecognized treatment failure is critical to improve patient outcomes

Clinical Performance of an Automated Reader in Interpreting Malaria Rapid Diagnostic Tests in Tanzania.

Parasitological confirmation of malaria is now recommended in all febrile patients by the World Health Organization (WHO) to reduce inappropriate use of anti-malarial drugs. Widespread implementation of rapid diagnostic tests (RDTs) is regarded as an effective strategy to achieve this goal. However, the quality of diagnosis provided by RDTs in remote rural dispensaries and health centres is not ideal. Feasible RDT quality control programmes in these settings are challenging. Collection of information regarding diagnostic events is also very deficient in low-resource countries. A prospective cohort of consecutive patients aged more than one year from both genders, seeking routine care for febrile episodes at dispensaries located in the Bagamoyo district of Tanzania, were enrolled into the study after signing an informed consent form. Blood samples were taken for thick blood smear (TBS) microscopic examination and malaria RDT (SD Bioline Malaria Antigen Pf/PanTM (SD RDT)). RDT results were interpreted by both visual interpretation and DekiReaderTM device. Results of visual interpretation were used for case management purposes. Microscopy was considered the "gold standard test" to assess the sensitivity and specificity of the DekiReader interpretation and to compare it to visual interpretation. In total, 1,346 febrile subjects were included in the final analysis. The SD RDT, when used in conjunction with the DekiReader and upon visual interpretation, had sensitivities of 95.3% (95% CI, 90.6-97.7) and 94.7% (95% CI, 89.8--97.3) respectively, and specificities of 94.6% (95% CI, 93.5--96.1) and 95.6% (95% CI, 94.2--96.6), respectively to gold standard. There was a high percentage of overall agreement between the two methods of interpretation. The sensitivity and specificity of the DekiReader in interpretation of SD RDTs were comparable to previous reports and showed high agreement to visual interpretation (>98%). The results of the study reflect the situation in real practice and show good performance characteristics of DekiReader on interpreting malaria RDTs in the hands of local laboratory technicians. They also suggest that a system like this could provide great benefits to the health care system. Further studies to look at ease of use by community health workers, and cost benefit of the system are warranted

Practical and clinical utility of non-invasive vagus nerve stimulation (nVNS) for the acute treatment of migraine. A post hoc analysis of the randomized, sham-controlled, double-blind PRESTO trial

Background: The PRESTO study of non-invasive vagus nerve stimulation (nVNS; gammaCore®) featured key primary and secondary end points recommended by the International Headache Society to provide Class I evidence that for patients with an episodic migraine, nVNS significantly increases the probability of having mild pain or being pain-free 2 h post stimulation. Here, we examined additional data from PRESTO to provide further insights into the practical utility of nVNS by evaluating its ability to consistently deliver clinically meaningful improvements in pain intensity while reducing the need for rescue medication. Methods: Patients recorded pain intensity for treated migraine attacks on a 4-point scale. Data were examined to compare nVNS and sham with regard to the percentage of patients who benefited by at least 1 point in pain intensity. We also assessed the percentage of attacks that required rescue medication and pain-free rates stratified by pain intensity at treatment initiation. Results: A significantly higher percentage of patients who used acute nVNS treatment (n = 120) vs sham (n = 123) reported a ≥ 1-point decrease in pain intensity at 30 min (nVNS, 32.2%; sham, 18.5%; P = 0.020), 60 min (nVNS, 38.8%; sham, 24.0%; P = 0.017), and 120 min (nVNS, 46.8%; sham, 26.2%; P = 0.002) after the first attack. Similar significant results were seen when assessing the benefit in all attacks. The proportion of patients who did not require rescue medication was significantly higher with nVNS than with sham for the first attack (nVNS, 59.3%; sham, 41.9%; P = 0.013) and all attacks (nVNS, 52.3%; sham, 37.3%; P = 0.008). When initial pain intensity was mild, the percentage of patients with no pain after treatment was significantly higher with nVNS than with sham at 60 min (all attacks: nVNS, 37.0%; sham, 21.2%; P = 0.025) and 120 min (first attack: nVNS, 50.0%; sham, 25.0%; P = 0.018; all attacks: nVNS, 46.7%; sham, 30.1%; P = 0.037). Conclusions: This post hoc analysis demonstrated that acute nVNS treatment quickly and consistently reduced pain intensity while decreasing rescue medication use. These clinical benefits provide guidance in the optimal use of nVNS in everyday practice, which can potentially reduce use of acute pharmacologic medications and their associated adverse events. Trial registration: ClinicalTrials.gov identifier: NCT02686034

The pharmacological regulation of cellular mitophagy

Small molecules are pharmacological tools of considerable value for dissecting complex biological processes and identifying potential therapeutic interventions. Recently, the cellular quality-control process of mitophagy has attracted considerable research interest; however, the limited availability of suitable chemical probes has restricted our understanding of the molecular mechanisms involved. Current approaches to initiate mitophagy include acute dissipation of the mitochondrial membrane potential (ΔΨm) by mitochondrial uncouplers (for example, FCCP/CCCP) and the use of antimycin A and oligomycin to impair respiration. Both approaches impair mitochondrial homeostasis and therefore limit the scope for dissection of subtle, bioenergy-related regulatory phenomena. Recently, novel mitophagy activators acting independently of the respiration collapse have been reported, offering new opportunities to understand the process and potential for therapeutic exploitation. We have summarized the current status of mitophagy modulators and analyzed the available chemical tools, commenting on their advantages, limitations and current applications

Strange Attractors in Dissipative Nambu Mechanics : Classical and Quantum Aspects

We extend the framework of Nambu-Hamiltonian Mechanics to include dissipation in $R^{3}$ phase space. We demonstrate that it accommodates the phase space dynamics of low dimensional dissipative systems such as the much studied Lorenz and R\"{o}ssler Strange attractors, as well as the more recent constructions of Chen and Leipnik-Newton. The rotational, volume preserving part of the flow preserves in time a family of two intersecting surfaces, the so called {\em Nambu Hamiltonians}. They foliate the entire phase space and are, in turn, deformed in time by Dissipation which represents their irrotational part of the flow. It is given by the gradient of a scalar function and is responsible for the emergence of the Strange Attractors. Based on our recent work on Quantum Nambu Mechanics, we provide an explicit quantization of the Lorenz attractor through the introduction of Non-commutative phase space coordinates as Hermitian $N \times N$ matrices in $R^{3}$. They satisfy the commutation relations induced by one of the two Nambu Hamiltonians, the second one generating a unique time evolution. Dissipation is incorporated quantum mechanically in a self-consistent way having the correct classical limit without the introduction of external degrees of freedom. Due to its volume phase space contraction it violates the quantum commutation relations. We demonstrate that the Heisenberg-Nambu evolution equations for the Quantum Lorenz system give rise to an attracting ellipsoid in the $3 N^{2}$ dimensional phase space.Comment: 35 pages, 4 figures, LaTe

LIN-44/Wnt Directs Dendrite Outgrowth through LIN-17/Frizzled in C. elegans Neurons

Nervous system function requires proper development of two functional and morphological domains of neurons, axons and dendrites. Although both these domains are equally important for signal transmission, our understanding of dendrite development remains relatively poor. Here, we show that in C. elegans the Wnt ligand, LIN-44, and its Frizzled receptor, LIN-17, regulate dendrite development of the PQR oxygen sensory neuron. In lin-44 and lin-17 mutants, PQR dendrites fail to form, display stunted growth, or are misrouted. Manipulation of temporal and spatial expression of LIN-44, combined with cell-ablation experiments, indicates that this molecule is patterned during embryogenesis and acts as an attractive cue to define the site from which the dendrite emerges. Genetic interaction between lin-44 and lin-17 suggests that the LIN-44 signal is transmitted through the LIN-17 receptor, which acts cell autonomously in PQR. Furthermore, we provide evidence that LIN-17 interacts with another Wnt molecule, EGL-20, and functions in parallel to MIG-1/Frizzled in this process. Taken together, our results reveal a crucial role for Wnt and Frizzled molecules in regulating dendrite development in vivo