Novi aktivni leap-frog filtar trećeg reda

This paper presents the realization of third-order low-pass active-RC filters using a new Leap-Frog (LF) topology. New structure is a simplified LF structure with the elements calculated directly from the transfer function coefficients. Several versions of the circuits are presented and compared. The comparison to other common thirdorder filter sections is done, as well. The new LF filter has the reduced number of components, reduced complexity and straightforward design procedure compared to classical filters. As an illustration of the efficiency of the proposed new LF filter, the sensitivity analysis using Schoeffler sensitivity measure as well as output thermal noise analysis was performed on examples with Butterworth and Chebyshev 0.5dB pass-band ripple transfer functions. Using PSpice with a TL081 opamp model, the filter performance is simulated and the results compared and verified by measurements on a discrete-component breadboard filter. All equations needed for the step-by-step design are given.U radu je predstavljena realizacija nisko-propusnog aktivnog-RC filtra trećeg reda koji upotrebljava novu "leap-frog" (LF) topologiju. Nova struktura je pojednostavljena LF struktura s elementima koji se računaju direktno iz koeficijenata prijenosne funkcije. Nekoliko inačica krugova je prikazano i obavljena je usporedba. Napravljena je usporedba tako.er i s drugim uobičajenim filtarskim sekcijama trećeg reda. Novi LF filtar ima smanjeni broj komponenata, smanjenu kompleksnost i jednostavniji postupak projektiranja u usporedbi s klasičnim filtrima. Za ilustraciju učinkovitosti predstavljenog novog LF filtra, provedena je analiza osjetljivosti pomoću Schoefflerove mjere osjetljivosti i analiza termičkog šuma na izlazu na primjerima s prijenosnim funkcijama po Butterworthu i Chebyshevu s valovitošću u području propuštanja od 0.5 dB. Pomoću PSpice-a s modelom pojačala TL081, filtarska svojstva su simulirana, uspore.ena i potvr.ena mjerenjima na filtrima realiziranim pomoću diskretnih elemenata na štampanoj pločici. U radu su dane sve potrebne jednadžbe u postupku projektiranja korak po korak

Pediatric Bacterial Meningitis Surveillance in Niger: Increased Importance of Neisseria meningitidis Serogroup C, and a Decrease in Streptococcus pneumoniae Following 13-Valent Pneumococcal Conjugate Vaccine Introduction

Background: Meningitis is endemic in Niger. Haemophilus influenzae type b (Hib) vaccine and the 13-valent pneumococcal conjugate vaccine (PCV13) were introduced in 2008 and 2014, respectively. Vaccination campaign against Neisseria meningitidis serogroup A was carried out in 2010–2011. We evaluated changes in pathogen distribution using data from hospital-based surveillance in Niger from 2010 through 2016. Methods: Cerebrospinal fluid (CSF) specimens from children <5 years old with suspected meningitis were tested to detect vaccine-preventable bacterial pathogens. Confirmatory identification and serotyping/grouping of Streptococcus pneumoniae, N. meningitidis, and H. influenzae were done. Antimicrobial susceptibility testing and whole genome sequencing were performed on S. pneumoniae isolates. Results: The surveillance included 2580 patients with suspected meningitis, of whom 80.8% (2085/2580) had CSF collected. Bacterial meningitis was confirmed in 273 patients: 48% (131/273) was N. meningitidis, 45% (123/273) S. pneumoniae, and 7% (19/273) H. influenzae. Streptococcus pneumoniae meningitis decreased from 34 in 2014, to 16 in 2016. PCV13 serotypes made up 88% (7/8) of S. pneumoniae meningitis prevaccination and 20% (5/20) postvaccination. Neisseria meningitidis serogroup C (NmC) was responsible for 59% (10/17) of serogrouped N. meningitidis meningitis. Hib caused 67% (2/3) of the H. influenzae meningitis isolates serotyped. Penicillin resistance was found in 16% (4/25) of S. pneumoniae isolates. Sequence type 217 was the most common lineage among S. pneumoniae isolates. Conclusions: Neisseria meningitidis and S. pneumoniae remain important causes of meningitis in children in Niger. The decline in the numbers of S. pneumoniae meningitis post-PCV13 is encouraging and should continue to be monitored. NmC is the predominant serogroup causing N. meningitidis meningitis

Pediatric Bacterial Meningitis Surveillance in Nigeria From 2010 to 2016, Prior to and During the Phased Introduction of the 10-Valent Pneumococcal Conjugate Vaccine

Background: Historically, Nigeria has experienced large bacterial meningitis outbreaks with high mortality in children. Streptococcus pneumoniae (pneumococcus), Neisseria meningitidis (meningococcus), and Haemophilus influenzae are major causes of this invasive disease. In collaboration with the World Health Organization, we conducted longitudinal surveillance in sentinel hospitals within Nigeria to establish the burden of pediatric bacterial meningitis (PBM). Methods: From 2010 to 2016, cerebrospinal fluid was collected from children <5 years of age, admitted to 5 sentinel hospitals in 5 Nigerian states. Microbiological and latex agglutination techniques were performed to detect the presence of pneumococcus, meningococcus, and H. influenzae. Species-specific polymerase chain reaction and serotyping/grouping were conducted to determine specific causative agents of PBM. Results: A total of 5134 children with suspected meningitis were enrolled at the participating hospitals; of these 153 (2.9%) were confirmed PBM cases. The mortality rate for those infected was 15.0% (23/153). The dominant pathogen was pneumococcus (46.4%: 71/153) followed by meningococcus (34.6%: 53/153) and H. influenzae (19.0%: 29/153). Nearly half the pneumococcal meningitis cases successfully serotyped (46.4%: 13/28) were caused by serotypes that are included in the 10-valent pneumococcal conjugate vaccine. The most prevalent meningococcal and H. influenzae strains were serogroup W and serotype b, respectively. Conclusions: Vaccine-type bacterial meningitis continues to be common among children <5 years in Nigeria. Challenges with vaccine introduction and coverage may explain some of these finding. Continued surveillance is needed to determine the distribution of serotypes/groups of meningeal pathogens across Nigeria and help inform and sustain vaccination policies in the countr

Pediatric Bacterial Meningitis Surveillance in Nigeria From 2010 to 2016, Prior to and During the Phased Introduction of the 10-Valent Pneumococcal Conjugate Vaccine.

BACKGROUND: Historically, Nigeria has experienced large bacterial meningitis outbreaks with high mortality in children. Streptococcus pneumoniae (pneumococcus), Neisseria meningitidis (meningococcus), and Haemophilus influenzae are major causes of this invasive disease. In collaboration with the World Health Organization, we conducted longitudinal surveillance in sentinel hospitals within Nigeria to establish the burden of pediatric bacterial meningitis (PBM). METHODS: From 2010 to 2016, cerebrospinal fluid was collected from children <5 years of age, admitted to 5 sentinel hospitals in 5 Nigerian states. Microbiological and latex agglutination techniques were performed to detect the presence of pneumococcus, meningococcus, and H. influenzae. Species-specific polymerase chain reaction and serotyping/grouping were conducted to determine specific causative agents of PBM. RESULTS: A total of 5134 children with suspected meningitis were enrolled at the participating hospitals; of these 153 (2.9%) were confirmed PBM cases. The mortality rate for those infected was 15.0% (23/153). The dominant pathogen was pneumococcus (46.4%: 71/153) followed by meningococcus (34.6%: 53/153) and H. influenzae (19.0%: 29/153). Nearly half the pneumococcal meningitis cases successfully serotyped (46.4%: 13/28) were caused by serotypes that are included in the 10-valent pneumococcal conjugate vaccine. The most prevalent meningococcal and H. influenzae strains were serogroup W and serotype b, respectively. CONCLUSIONS: Vaccine-type bacterial meningitis continues to be common among children <5 years in Nigeria. Challenges with vaccine introduction and coverage may explain some of these finding. Continued surveillance is needed to determine the distribution of serotypes/groups of meningeal pathogens across Nigeria and help inform and sustain vaccination policies in the country

Agriculture urbaine comme réponse au chômage à Kinshasa, République Démocratique du Congo

L’agriculture urbaine est une activité qui fait vivre de nombreuses familles à Kinshasa (République Démocratique du Congo). Elle peut donc contribuer au développement durable des villes africaines sous certaines conditions dont notamment par sa professionnalisation, le non-recours aux intrants chimiques et la distribution équitable des terres arables. Le cas de Kinshasa illustre bien que cette agriculture demeure une solution palliative aux contraintes sociales de survie (absence de salaire rémunérateur et manque d’emplois durables). Ce cas montre qu’il n’y a pas de honte à pratiquer le maraîchage urbain, car même les universitaires le font (5 % seulement le font par tradition familiale) ; il s’y pose le problème du choix des sites et d’encadrement. En effet, mal encadrés, les maraîchers cultivent le long des routes à intenses trafics motorisés, exposant ainsi les légumes aux contaminations diverses, notamment au plomb.Urban agriculture is an important livelihood activity at Kinshasa (Democratic Republic of Congo). Many families live on it. Urban agriculture might lead to African cities sustainable development under certain conditions, namely its professionalization, limited use of chemicals and the equitable distribution of fertile lands. Kinshasa case study reveals that the urban agriculture remains a secondary activity as a social response for survival (due to the lack of safe salary and sustainable jobs). This survey also revealed that urban agriculture is practiced by various classes including university graduates (only 5 % are practicing by traditions). The site selection is posing problem and vegetable growers are now exploiting free spaces along roads with intensive motorized traffic which negatively impacts the product quality

The seasonal influence of climate and environment on yellow fever transmission across Africa

Background: Yellow fever virus (YFV) is a vector-borne flavivirus endemic to Africa and Latin America. Ninety per cent of the global burden occurs in Africa where it is primarily transmitted by Aedes spp, with Aedes aegypti the main vector for urban yellow fever (YF). Mosquito life cycle and viral replication in the mosquito are heavily dependent on climate, particularly temperature and rainfall. We aimed to assess whether seasonal variations in climatic factors are associated with the seasonality of YF reports. Methodology/Principal findings: We constructed a temperature suitability index for YFV transmission, capturing the temperature dependence of mosquito behaviour and viral replication within the mosquito. We then fitted a series of multilevel logistic regression models to a dataset of YF reports across Africa, considering location and seasonality of occurrence for seasonal models, against the temperature suitability index, rainfall and the Enhanced Vegetation Index (EVI) as covariates alongside further demographic indicators. Model fit was assessed by the Area Under the Curve (AUC), and models were ranked by Akaike’s Information Criterion which was used to weight model outputs to create combined model predictions. The seasonal model accurately captured both the geographic and temporal heterogeneities in YF transmission (AUC = 0.81), and did not perform significantly worse than the annual model which only captured the geographic distribution. The interaction between temperature suitability and rainfall accounted for much of the occurrence of YF, which offers a statistical explanation for the spatio-temporal variability in transmission. Conclusions/Significance: The description of seasonality offers an explanation for heterogeneities in the West-East YF burden across Africa. Annual climatic variables may indicate a transmission suitability not always reflected in seasonal interactions. This finding, in conjunction with forecasted data, could highlight areas of increased transmission and provide insights into the occurrence of large outbreaks, such as those seen in Angola, the Democratic Republic of the Congo and Brazil