Miracle-dz/UniFAR-FTUs huggingface dataset:
Model Predictive Control-Based Depth Control in Gliding Motion of a Gliding Robotic Dolphin

This article proposes a model predictive control (MPC)-based depth control system for the gliding motion of a gliding robotic dolphin. An injector-based buoyancy-driven mechanism is employed to achieve more precise control of net buoyancy. In the system, a novel framework of depth control is proposed on the basis of a simplified model, including a depth controller with improved MPC, a heading controller with velocity-based proportional-integral-derivative, and a sliding mode observer. Extensive simulation and experimental results demonstrate the effectiveness of the proposed control methods. In particular, a variety of slider-based experiments are also conducted to explore the performance of a movable slider in the depth control so as to better govern the gliding angle. The results obtained reveal that it is feasible to realize regular gliding angles via regulating the slider, which offers promising prospects for bio-inspired gliding robots playing a key role in ocean exploration.
Arguments for the cognitive social sciences

The overlap between the cognitive and social sciences has significantly increased in recent decades. New disciplines and research programs have arisen and expanded at the intersection of these two types of sciences. They include cognitive sociology, political psychology, behavioral economics and new research programs in cognitive anthropology. However, not all social scientists have been persuaded that the social sciences should be integrated with the cognitive sciences. Some of them are indifferent to these new integrative disciplines and research programs, assuming that they are not relevant to their research practices. Other social scientists consider them as overly reductionist and, thereby, as a threat to the identity of their disciplines. As a response, cognitive social scientists have provided arguments to convince all social scientists about the benefits of integrating the social sciences with the cognitive sciences. In this article, we analyze and evaluate these arguments for the cognitive social sciences.
The Relative Importance of Female Education on Fertility Desires in Sub-Saharan Africa: A Multi-Level Analysis

Scholars suggest that in high fertility settings where there is high wanted fertility, lowering the desired family size is a necessary precondition for fertility declines. Though accumulated evidence has linked socio-economic developments to changes in fertility desires, little efforts have taken to disentangle the relative importance of key socio-economic determinants such as education, income, and area of residence in a multi-level context. Combining individual and community-level data from Demographic and Health Surveys of 34 African countries to aggregate level indicators, we have quantified and compared the relative role of female education on fertility desire at the individual, community, and country levels. Results show that at the individual level, female education has a stronger effect compared to household wealth, and area of residence. The high levels of reported desired family size in the rural parts of SSA are mainly a consequence of their relatively lower levels of educational attainment compared to their urban counterparts. At the community level, the relative impact of female education is even more striking. The simulation results revealed that moving the most economically disadvantaged and illiterate woman from a low educated to a high-educated community would reduce her desired family size by about 20 percent. On the other hand, lifting the same woman from the poorest to the wealthiest community would reduce her family size desire only by 6 percent. Our findings are robust to alternative measures of fertility preferences. This study, thus, confirmed the findings of previous studies that have looked at the relationship and causal link between actual fertility and women’s level of educational attainment.
Predictive engineering and optimization of tryptophan metabolism in yeast through a combination of mechanistic and machine learning models

In combination with advanced mechanistic modeling and the generation of high-quality multi-dimensional data sets, machine learning is becoming an integral part of understanding and engineering living systems. Here we show that mechanistic and machine learning models can complement each other and be used in a combined approach to enable accurate genotype-to-phenotype predictions. We use a genome-scale model to pinpoint engineering targets and produce a large combinatorial library of metabolic pathway designs with different promoters which, once phenotyped, provide the basis for machine learning algorithms to be trained and used for new design recommendations. The approach enables successful forward engineering of aromatic amino acid metabolism in yeast, with the new recommended designs improving tryptophan production by up to 17% compared to the best designs used for algorithm training, and ultimately producing a total increase of 106% in tryptophan accumulation compared to optimized reference designs. Based on a single high-throughput data-generation iteration, this study highlights the power of combining mechanistic and machine learning models to enhance their predictive power and effectively direct metabolic engineering efforts.
Correlation between central obesity and blood pressure in an adult Nigerian population

Background: Obesity has been recognised as a major risk factor in the pathogenesis of cardiovascular disease. The aim of this study is to determine the prevalence of central obesity [using waist–hip ratio (WHR) as an indicator] and the correlation between central obesity and blood pressure (BP) in adults seen in a Nigerian tertiary health facility. Materials and methods: The study was a cross-sectional design carried out between February and November 2015 at the General Outpatient Clinic of the Federal Medical Centre, Owerri, Nigeria. A total of 482 consenting adults aged 16–40 years formed the study population. Consecutive sampling was used in the recruitment of subjects, whereas data were collected by the use of an interviewer-administered questionnaire. Results: The mean age of the study population was 25.37 ± 5.49, whereas the mean WHR for men and women was 0.83 ± 0.04 and 0.82 ± 0.05, respectively. The prevalence of central obesity in the study population was 39.4% ( n = 190). Female respondents had a higher prevalence (59.2%) than male respondents (8.5%), and the relationship between central obesity and sex was statistically significant ( p = 0.001). Correlation analysis showed a positive correlation between WHR and BP (diastolic BP: r = 0.122, p = 0.008; systolic BP: r = 0.015, p = 0.742) in both sexes. Obese respondents were observed to be more likely to develop hypertension than the non-obese respondents. Conclusion: This study showed a correlation between central obesity and BP in adults aged 16–40 years.
Trends in cheetah
 
 Acinonyx jubatus
 
 density in north‐central Namibia

Department of Wildlife Management and Ecotourism, University of Namibia, Katima Mulilo, Namibia Department of Environmental Conservation, University of Massachusetts-Amherst, Amherst, Massachusetts U.S. Geological Survey, New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources, Cornell University, Ithaca, New York Ecology Division, Cheetah Conservation Fund, Otjiwarongo, Namibia Laboratório de Biologia Genômica e Molecular, Escola de Ciências, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil Instituto Pró-Carnívoros, Atibaia, Brazil
Household Strategies to Cope with the Economic Cost of Illness in Low and Middle Income Countries: A Review Study

Present study reviews the findings of various studies on coping strategies and distress financing of health care expenditure worldwide. More emphasis has been given to studies conducted in low and middle-income countries on households coping strategies but the relevant articles proceeded in high income countries on the same have also been considered. The main purpose of this review study is to recognize and examine the structure of coping strategies and distress financing used by households to pay health care expenditure and to encounter the prospective economic shocks from ill health in these countries. Findings analytically carried out from several studies show that wealthy households mainly use income and savings as a coping strategy for health care financing in low and middle-income countries. Whereas borrowings, sale of assets, contributions from relatives and other significant non-financial strategies such as intra-family labour reallocation, hiring and free community labour etc. have been found frequently used by poor households. Evidences from the studies conducted in India have also signified that along with savings/income, distress financing is playing a dominant role to cope up with financing health care in the country.
CNN-based Skip-Gram Method for Improving Classification Accuracy of Chinese Text

Text classification is one of the fundamental techniques in natural language processing. Numerous studies are based on text classification, such as news subject classification, question answering system classification, and movie review classification. Traditional text classification methods are used to extract features and then classify them. However, traditional methods are too complex to operate, and their accuracy is not sufficiently high. Recently, convolutional neural network (CNN) based one-hot method has been proposed in text classification to solve this problem. In this paper, we propose an improved method using CNN based skip-gram method for Chinese text classification and it conducts in Sogou news corpus. Experimental results indicate that CNN with the skip-gram model performs more efficiently than CNN-based one-hot method.
Malaria Community Health Workers in Eliminating Malaria in Banyumas Regency

Banyumas has not reached the elimination of malaria yet. One of the efforts is done by community empowerment by establishing malaria Community Health Workers (CHWs/JMD). JMD are people who conduct the discovery and medication of malaria in Active Case Detection (ACD). The research aims at describing JMDs attitude and knowledge towards the malaria elimination in Banyumas Regency in 2015. Quantitative research with cross sectional design was performed in the study. There were 15 JMDs spreading across in 7 public health centers/Puskesmas. The results show that most of JMDs were male with primary education background. They are mostly employed and do not join any training within 3 years. The average age of JMDs is 48.4 years old although there are some workers who are over 65 years old. 33.3% of JMDs are in low-medium categories, and there are 26.7% JMDs who have negative attitude to malaria. All JMDs have less skill such as not to do home visits as scheduled, not to do periodic reports, not to send blood preparations immediately and unstandardized of the blood preparation.
Influence of Sewage Water Irrigation on Soil Properties in Different Districts of Haryana

In this study, samples were collected from sewage and tube well water irrigated soil of various sites like Kaithal, Narwana and Jind district of Haryana state where these waters are directly used for irrigating the crops. Soil samples (0-15 and 15-30 cm) were also collected from fields irrigated with these waters and from nearby fields irrigated with non-sewage waters to determine the changes in soil chemical properties due to sewage irrigation. The mean value of pH (8.38) was found highest in the soils irrigated with sewage water of Jind. The mean value of EC (0.46 dSm -1 ) was found highest in the soils irrigated with sewage water of Jind. The mean value of SOC (0.91%) was found highest in soils irrigated with sewage water of Kaithal. The mean value of CaCO3 (3.57%) was found highest in the soils irrigated with sewage water of Narwana. The mean value of CEC (14.89 cmol (+) kg -1 ) was found highest in the soils irrigated with sewage water of Kaithal. The mean value of Ca 2+ (7.69) was found highest in the soils irrigated with sewage water of Jind. The mean value of Mg 2+ (3.89) and Na + (1.82) was found highest in the soils irrigated with sewage water of Kaithal. The mean value of K + (0.94) was found highest in the soils irrigated with sewage water of Narwana.
On the use of calcium deconvolution algorithms in practical contexts

Calcium imaging is a powerful tool for capturing the simultaneous activity of large populations of neurons. Here we determine the extent to which our inferences of neural population activity, correlations, and coding depend on our choice of whether and how we deconvolve the calcium time-series into spike-driven events. To this end, we use a range of deconvolution algorithms to create nine versions of the same calcium imaging data obtained from barrel cortex during a pole-detection task. Seeking suitable values for the deconvolution algorithms’ parameters, we optimise them against ground-truth data, and find those parameters both vary by up to two orders of magnitude between neurons and are sensitive to small changes in their values. Applied to the barrel cortex data, we show that a substantial fraction of the processing methods fail to recover simple features of population activity in barrel cortex already established by electrophysiological recordings. Raw calcium time-series contain an order of magnitude more neurons tuned to features of the pole task; yet there is also qualitative disagreement between deconvolution methods on which neurons are tuned to the task. Finally, we show that raw and processed calcium time-series qualitatively disagree on the structure of correlations within the population and the dimensionality of its joint activity. Collectively, our results show that properties of neural activity, correlations, and coding inferred from calcium imaging are sensitive to the choice of if and how spike-evoked events are recovered. We suggest that quantitative results obtained from population calcium-imaging be verified across multiple processed forms of the calcium time-series.
Lessons learned from the large-scale application of Driver Feedback Signs in an urban city

Abstract The City of Edmonton has invested in the installation of Driver Feedback Signs (DFSs) throughout the city starting from 2011. DFSs are dynamic speed display signs aimed at providing positive guidance to drivers with the goal of improving compliance to posted speed limits. Given the city’s extensive history with DFS installation, the goal of this study is to evaluate the safety performance of DFSs and to identify factors that can help in determining the future DFS sites selection. A before-and-after evaluation with Empirical Bayes (EB) adjustment was used to account for regression-to-mean bias and other confounding factors. Local safety performance functions and yearly calibration factors were developed using data from a set of reference urban roads. The EB method analysis was utilized to investigate the effect of DFS on different road and intervention types. Results showed significant collision reductions in all scenarios ranging from 31.0% to 41.6%. DFSs were more effective in reducing collisions for arterials compared to collectors. Also, the combined use of DFS and mobile photo enforcement had a slightly higher effect on safety. Initial collision frequencies, traffic volumes, road lengths and the presence of shoulders were found to impact the reduction in collisions for most collision types.
Cardiac biomarkers in dialysis

Abstract Cardiovascular disease is the major cause of death, accounting for approximately 40 percent of all-cause mortality in patients receiving either hemodialysis or peritoneal dialysis. Cardiovascular risk stratification is an important aspect of managing dialysis patients as it enables early identification of high-risk patients, so therapeutic interventions can be optimized to lower cardiovascular morbidity and mortality. Biomarkers can detect early stages of cardiac injury so timely intervention can be provided. The B-type natriuretic peptides (Brain Natriuretic peptide [BNP] and N-terminal pro-B-type natriuretic peptide [NT-proBNP]) and troponins have been shown to predict mortality in dialysis patients. Suppression of tumorigenicity 2 (ST2) and galectin-3 are new emerging biomarkers in the field of heart failure in both the general and dialysis populations. This article aims to discuss the current evidence regarding cardiac biomarker use to diagnose myocardial injury and monitor the risk of major adverse cardiovascular events in patients undergoing dialysis.
Perspectives in the treatment of cardiovascular disease : from prognostic parameters to therapeutic modalities

Over the last decade, a tremendous progress has been made in cardiovascular medicine. The progress includes the treatment of coronary artery disease (CAD) and peripheral artery disease. In CAD, several advances have been made in the management of patients with acute myocardial infarction (AMI) such as: 1) the importance of networking in the treatment of AMI; 2) perspectives on how to improve the results of primary percutaneous coronary intervention (PCI) procedures including: (i) the administration of a glycoprotein IIb/ IIIa inhibitor (GPI); (ii) strategies for “fighting” the coronary thrombus during primary PCI; (iii) choice of vascular access site (radial versus femoral artery approach) for primary PCI; (iv) choice of stents (drug eluting versus bare metal stent) for patients with acute ST-segment elevation myocardial infarction (STEMI); and 3) the use of intra-aortic balloon pump (IABP) in acute coronary syndrome (ACS) patients. Another important perspective related to patients with AMI is the utilization of simple, inexpensive but accurate biomarkers with prognostic value such as plasma uric acid concentration and leukocyte count, which are particularly useful in a rural area when other established markers are not available.
Heart Rate and Blood Pressure Assessment by Physical Therapists in the Outpatient Setting—An Observational Study

Purpose:Although physical therapists (PTs) are equipped and trained with the knowledge of the importance of vital sign assessment and cardiovascular risk factors, there seems to be a discrepancy between the practice guidelines and the actual practice in the clinic. Therefore, the purpose of this study was to observe the frequency with which PTs take and record heart rate (HR) and blood pressure (BP) in the orthopedic outpatient setting during therapy sessions. Methods:Physical therapists from 6 area clinics were observed, including 15 licensed PTs, during 74 patient sessions. The frequency with which the PTs measured patients' BP and HR during initial assessment and/or follow-up treatment sessions was documented. Physical therapist demographics and patient diagnosis, comorbidities, age, and sex were recorded. Results:Of the 74 patient sessions, 15 were initial visits, 54 were follow-up, and 5 were discharge sessions. Although 26% (n = 19) of the patients had hypertension as a comorbidity, initial HR and BP were only taken in 2 sessions, and only once taken after exercise. Conclusions:Within our limited sample, PTs in outpatient settings were not following HR and BP screening or exercise monitoring practice guidelines. This could put patients at risk for cardiovascular incidents during therapy sessions.
Endogenous effects and cluster transition: a conceptual framework for cluster policy

ABSTRACT The clustering of firms in related fields has a positive impact on economic performance and innovative behaviour. The cluster lifecycle model provides a framework in order to add a temporal dimension to this ongoing debate. This model conjectures that clusters undergo various phases, in each of which they exhibit distinct characteristics in terms of size, economic performance and knowledge sourcing pattern. While there is strong evidence of a dynamic interplay between knowledge networks and clusters, we know little about how the structural configurations of a knowledge network engender cluster transition, and how these dynamics can be captured and integrated into policies. First, this paper contributes to this debate by providing a conceptual framework that accounts for cluster evolution based on endogenous micro-forces that are immanent in a knowledge sourcing structure. Secondly, this article underlines the failures of recent network-related cluster policies and discusses how the developed framework alleviates these issues.
Functional loss of a noncanonical BCOR–PRC1.1 complex accelerates SHH-driven medulloblastoma formation

Medulloblastoma is a childhood brain tumor arising from the developing cerebellum. In Sonic Hedgehog (SHH)-subgroup medulloblastoma, aberrant activation of SHH signaling causes increased proliferation of granule neuron progenitors (GNPs) and predisposes these cells to tumorigenesis. A second, cooperating genetic hit is often required to push these hyperplastic cells to malignancy and confer mutation-specific characteristics associated with oncogenic signaling. Somatic loss-of-function mutations of the transcriptional co-repressor BCOR are recurrent and highly enriched in SHH-medulloblastoma. To investigate BCOR as a putative tumor suppressor, we used a germline genetically engineered mouse model to delete exons 9/10 of Bcor (BcorΔE9-10) in GNPs during development. This leads to reduced expression of C-terminally truncated BCOR (BCORΔE9-10). While BcorΔE9-10 alone did not promote tumorigenesis or affect GNP differentiation, BcorΔE9-10 combined with loss of the SHH-receptor gene Ptch1 resulted in highly penetrant medulloblastomas. In Ptch1+/-;BcorΔE9-10 tumors, the growth factor gene Igf2 was aberrantly upregulated, and ectopic Igf2 overexpression was sufficient to drive tumorigenesis in Ptch1+/- GNPs. BCOR directly regulates Igf2, likely through the PRC1.1 complex; the repressive histone mark H2AK119Ub is decreased at the Igf2 promoter in Ptch1+/-;BcorΔE9-10 tumors. Overall, our data suggests that BCOR-PRC1.1 disruption leads to Igf2 overexpression, which transforms preneoplastic cells to malignant tumors.
The (Non-) Effect of Opportunity Zones on Housing Prices

Will the Opportunity Zone program, America’s largest new place-based policy in decades, generate neighborhood change? We compare single-family housing price growth in Opportunity Zones with price growth in areas that were eligible but not included in the program. We also compare Opportunity Zones to their nearest geographic neighbors. All estimates rule out price impacts greater than 1.3 percentage points with 95% confidence, suggesting that, so far, home buyers don’t believe that this subsidy will generate major neighborhood change. Opportunity Zone status reduces prices in areas with little employment, perhaps because buyers think that subsidizing new investment will increase housing supply.