Birth defect trends within Texas Public Health Region 11, 2000-2019: an analysis of Texas Department of State Health Services public data.

South Texas is a predominantly Hispanic region with high rates of chronic illness, poor healthcare access, and a history of birth defect clusters. Between 1986 and 1991, 47 cases of anencephaly in Cameron County were linked to elevated fumonisins in the region’s corn-based diet, prompting a series of ongoing public health efforts. This paper aims to identify changes in prevalence for CNS defects, in addition to cardiac, circulatory, gastrointestinal, and genitourinary defects in South Texas within the last two decades. Public data on 20 birth defects from the Texas Department of State Health Services were obtained for decades 2000-2010 and 2010-2019 in Texas Public Health Region 11 and the remaining regions of Texas. We report that Region 11 saw larger birth defect prevalences compared to the remainder of Texas in both decades studied. When looking at single regions between decades, there was an increase in the prevalences of microcephaly, ASD, pulmonary valve atresia or stenosis, PDA, and hypospadias within Region 11 in 2010-2019; the prevalences of these defects also increased in the remaining regions of Texas in 2010-2019, with the addition of 8 more: hydrocephaly, double outlet right ventricle, tetralogy of Fallot, VSD, tricuspid valve atresia or stenosis, coarctation of the aorta, stenosis or atresia of the small intestine, and renal agenesis/dysgenesis. Pyloric stenosis alone saw a significant decrease in prevalence in 2010-2019 for both regions in this study. Furthermore, it was found that the prevalences of anencephaly and spina bifida without anencephaly were unchanged in both regions

Tensile failure of blended spun yarns under dynamic condition: Part I –Yarn failure during warping

The failure behaviour of polyester/viscose blended ring, rotor and air-jet spun yarns has been studied on the basis of fibre failure coefficient, yarn broken end configuration and failure zone length. The failure behaviour of spun yarns under warping process is simulated in the dynamic tensile tester. The tensile failure behaviour of ring, rotor and air-jet yarns are found to be different owing to their difference in fibre consolidation mechanism. The yarn failure is observed to be more and more dominated by fibre slippage once moving from ring to rotor and finally to air-jet yarns. The study also reports mathematical modeling of spun yarn failure behaviour during warping process. The mathematical model indicates that the spun yarn failure is non-linearly related to yarn structural parameters

Effect of teaching games for understanding approach on students' cognitive learning outcome

The study investigated the effects of Teaching Games for Understanding approach on students' cognitive learning outcome. The study was a quasi-experimental non-equivalent pretest posttest control group design whereby 10 year old primary school students (n=72) were randomly assigned to an experimental and a control group. The experimental group students were exposed with TGfU approach and the control group with the Traditional Skill approach of handball game. Game Performance Assessment Instrument (GPAI) was used to measure students' tactical understanding and decision making in 3 versus 3 handball game situations. Analysis of covariance (ANCOVA) was used to analyze the data. The results reveal that there was a significant difference between the TGfU approach group and the traditional skill approach group students on post test score (F (1, 69) = 248.83, p < .05). The findings of this study suggested the importance of TGfU approach to improve primary student

The need for teaching games for understanding (TGfU) approach in primary physical education: A preliminary study

This is a preliminary study investigated the need for the Teaching Games for Understanding (TGfU) approach to be introduced to Primary Physical Education games teaching. A survey questionnaire and open ended questions were administrated to collect data on current teaching approach and the need for the TGfU as an alternative approach. Fifty eight primary school physical education teachers (21 male and 37 female) aged between 24 to 46 (SD) years responded in this study. Results indicated that 65.5 percent used a traditional teacher centered approach currently in teaching games. The findings also reported 53.5 percent of the respondents reported that all the lesson objectives could not be achieved and suggested a need for an alternative approach like TGfU in teaching games. The findings also proposed implementation of an approach that considers student interest and participation

Peat swamp forest conservation withstands pervasive land conversion to oil palm plantation in North Selangor, Malaysia

Tropical deforestation remains one of the major global challenges of the twenty-first century driven to a large extent by the conversion of land for agricultural purposes, such as palm oil production. Malaysia is one of the world’s largest palm oil producers and has seen widespread conversion to oil palm from primary forest, including peat swamp forest (PSF). This study investigates the rate and extent of pervasive oil palm expansion in and around North Selangor Peat Swamp Forest (NSPSF) over the last three decades, exploring how land conversion has affected the region’s tropical forests, and assessing the relative success of PSF conservation measures. Time-series Landsat imagery was used to assess thematic land cover change and improvement in vegetation condition since NSPSF was given protected status in 1990. The results show a near tripling in oil palm cover throughout North Selangor, from 24,930 ha in 1989 to 70,070 ha in 2016; while at the same time tropical forest cover shrank from 145,570 ha to 88,400 ha. Despite concerns over the sustainability and environmental impact of such rapid oil palm conversion at a regional level, at the local scale, NSPSF represents a relative conservation success story. Effective land stewardship by government and non-governmental organization (NGO) management actors has limited illegal encroachment of oil palm around the reserve boundary. PSF rehabilitation measures have also markedly improved vegetation condition in NSPFS’s interior. These findings have broad significance for how oil palm agriculture is managed and especially for PSF stewardship and conservation, and the approaches described here may be usefully adopted elsewhere in Southeast Asia and around the world

Management of SARS-CoV-2 Infection: Key Focus in Macrolides Efficacy for COVID-19

Macrolides (e.g., erythromycin, fidaxomicin, clarithromycin, and azithromycin) are a class of bacteriostatic antibiotics commonly employed in medicine against various gram-positive and atypical bacterial species mostly related to respiratory tract infections, besides they possess anti-inflammatory and immunomodulatory effects. Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by the severe acute respiratory syndrome of coronavirus 2 (SARS-CoV-2). It was first detected in Wuhan, Hubei, China, in December 2019 and resulted in a continuing pandemic. Macrolides have been extensively researched as broad adjunctive therapy for COVID-19 due to its immunostimulant abilities. Among such class of drugs, azithromycin is described as azalide and is well-known for its ability to decrease the production of pro-inflammatory cytokines, including matrix metalloproteinases, tumor necrosis factor-alpha, interleukin (IL)-6, and IL-8. In fact, a report recently published highlighted the effectiveness of combining azithromycin and hydroxychloroquine for COVID-19 treatment. Indeed, it has been underlined that azithromycin quickly prevents SARS-CoV-2 infection by raising the levels of both interferons and interferon-stimulated proteins at the same time which reduces the virus replication and release. In this sense, the current review aims to evaluate the applications of macrolides for the treatment of COVID-19.NC-M acknowledges the Portuguese Foundation for Science and Technology under the Horizon 2020 Program (PTDC/PSI-GER/28076/2017)

Soil and aquifer salinization: toward an integrated approach for salinity management of groundwater

Degradation of the quality of groundwater due to salinization processes is one of the key issues limiting the global dependence on groundwater in aquifers. As the salinization of shallow aquifers is closely related to root-zone salinization, the two must be considered together. This chapter initially describes the physical and chemical processes causing salinization of the root-zone and shallow aquifers, highlighting the dynamics of these processes and how they can be influenced by irrigation and drainage practices, thus illustrating the connectivity between soil and groundwater salinization. The processes leading to aquifer salinization in both inland and coastal areas are discussed. The roles of extractive resource industries, such as mining and coal bed methane operations, in causing aquifer salinization are also outlined. Hydrogeochemical changes occurring during salinization of aquifers are examined with the aid of Piper and Mixing Diagrams. The chapter then illustrates the extent of the problem of groundwater salinization as influenced by management and policy using two case studies. The first is representative of a developing country and explores management of salt-affected soils in the Indus Valley, Pakistan, while the second looks at a developed country, and illustrates how through monitoring we can deducecauses of shallow aquifer salinity in the Namoi Catchment of NSW, Australia. Finally, there is a section on integration and conclusions where we illustrate how management to mitigate salinization needs to be integrated with policy to diminish the threat to productivity that occurs with groundwater degradation

Evaluation of Microwave Steam Bags for the Decontamination of Filtering Facepiece Respirators

Reusing filtering facepiece respirators (FFRs) has been suggested as a strategy to conserve available supplies for home and healthcare environments during an influenza pandemic. For reuse to be possible, used FFRs must be decontaminated before redonning to reduce the risk of virus transmission; however, there are no approved methods for FFR decontamination. An effective method must reduce the microbial threat, maintain the function of the FFR, and present no residual chemical hazard. The method should be readily available, inexpensive and easily implemented by healthcare workers and the general public. Many of the general decontamination protocols used in healthcare and home settings are unable to address all of the desired qualities of an efficient FFR decontamination protocol. The goal of this study is to evaluate the use of two commercially available steam bags, marketed to the public for disinfecting infant feeding equipment, for FFR decontamination. The FFRs were decontaminated with microwave generated steam following the manufacturers' instructions then evaluated for water absorption and filtration efficiency for up to three steam exposures. Water absorption of the FFR was found to be model specific as FFRs constructed with hydrophilic materials absorbed more water. The steam had little effect on FFR performance as filtration efficiency of the treated FFRs remained above 95%. The decontamination efficacy of the steam bag was assessed using bacteriophage MS2 as a surrogate for a pathogenic virus. The tested steam bags were found to be 99.9% effective for inactivating MS2 on FFRs; however, more research is required to determine the effectiveness against respiratory pathogens

Feature importance in machine learning models: A fuzzy information fusion approach

With the widespread use of machine learning to support decision-making, it is increasingly important to verify and understand the reasons why a particular output is produced. Although post-training feature importance approaches assist this interpretation, there is an overall lack of consensus regarding how feature importance should be quantified, making explanations of model predictions unreliable. In addition, many of these explanations depend on the specific machine learning approach employed and on the subset of data used when calculating feature importance. A possible solution to improve the reliability of explanations is to combine results from multiple feature importance quantifiers from different machine learning approaches coupled with re-sampling. Current state-of-the-art ensemble feature importance fusion uses crisp techniques to fuse results from different approaches. There is, however, significant loss of information as these approaches are not context-aware and reduce several quantifiers to a single crisp output. More importantly, their representation of “importance” as coefficients may be difficult to comprehend by end-users and decision makers. Here we show how the use of fuzzy data fusion methods can overcome some of the important limitations of crisp fusion methods by making the importance of features easily understandable