Using pneumococcal and rotavirus surveillance in vaccine decision-making: A series of case studies in Bangladesh, Armenia and the Gambia.

Pneumonia and diarrhea are the leading causes of child morbidity and mortality globally and are vaccine preventable. The WHO-coordinated Global Rotavirus and Invasive Bacterial Vaccine-Preventable Disease Surveillance Networks support surveillance systems across WHO regions to provide burden of disease data for countries to make evidence-based decisions about introducing vaccines and to demonstrate the impact of vaccines on disease burden. These surveillance networks help fill the gaps in data in low and middle-income countries where disease burden and risk are high but support to sustain surveillance activities and generate data is low. Through a series of country case studies, this paper reviews the successful use of surveillance data for disease caused by pneumococcus and rotavirus in informing national vaccine policy in Bangladesh, Armenia and The Gambia. The case studies delve into ways in which countries are leveraging and building capacity in existing surveillance infrastructure to monitor other diseases of concern in the country. Local institutions have been identified to play a critical role in making surveillance data available to policymakers. We recommend that countries review local or regional surveillance data in making vaccine policy decisions. Documenting use of surveillance activities can be used as advocacy tools to convince governments and external funders to invest in surveillance and make it a priority immunization activity

PERAN ARTIFICIAL INTELLIGENCE TERHADAP EFISIENSI MANAJEMEN SUMBER DAYA MANUSIA UNTUK PERSONIL MILITER INDONESIA DEMI MEMPERKUAT PERTAHANAN NEGARA

Kecerdasan buatan (Artificial Intelligence) diharapkan mampu untuk mentransformasi tatanan semua sektor tak terkecuali di bidang manajemen sumber daya manusia (SDM). Atas nama efisiensi, penggunaan AI dianggap dapat memainkan peran untuk meningkatkan otomatisasi secara cerdas yang memungkinkan para manajer untuk mengedepankan kemampuan manusia secara eksklusif namun menempatkan teknologi sebagai basisnya. Ide yang terkandung dalam kecerdasan buatan untuk efisiensi sumber daya manusia selaras dengan salah satu pokok pemikiran ilmu manajemen pertahanan, dimana manajemen pertahanan mengacu kepada pengelolaan sumber daya untuk melaksanakan kegiatan pertahanan negara yang dituntut harus melibatkan strategi yang kuat, alokasi sumber daya termasuk sumber daya manusia secara efektif demi terwujudnya kesiapan operasional yang mumpuni. Sebagai personil militer nasional, TNI sudah pasti mengharuskan untuk bisa menyerap talenta terbaik bangsa demi memperkokoh strategi pertahanan negara. Disinilah kecerdasan buatan dalam manajemen sumber daya manusia berperan. Penelitian ini menggunakan metode studi literatur dengan pendekatan deskriptif kualitatif sebagai pendekatan penulisan utama dan menggunakan data sekunder berdasarkan tinjauan yang dilakukan secara komprehensif terhadap jurnal, laporan serta arsip (data dokumenter). Artikel ini akan menjelaskan tentang masalah manajemen sumber daya manusia jenis apa saja yang bisa diselesaikan dengan melibatkan kecerdasan buatan serta terdapat ancaman apa yang terkandung didalamnya untuk bisa diwaspadai serta bagaimana solusi ini bisa memperkokoh sistem manajemen sumber daya manusia di dalam TNI. Artikel ini menemukan bahwa penggunaan kecerdasan buatan dalam manajemen sumber daya manusia dapat mengurangi beban departemen SDM sehingga mereka dapat memanfaatkan waktunya untuk pengambilan keputusan strategis lainnya atau memecahkan masalah penting dan juga AI berperan sebagai alat untuk mengidentifikasi, memprioritaskan, dan memilih inisiatif misi baru secara sistemati

Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41

Protein-based biological materials such as albumin, casein and collagen are found in various cultural heritage (CH) artefacts. This study focuses on the study of protein binders from easel paintings media. Proteins have complex structures which are difficult to identify with non-invasive spectroscopic methods (FT-IR, Raman, UV). Immunoassays such as ELISA determine the protein’s source of origin which is necessary for art objects. To increase the detection and identification of proteins by immunoassays, the efficiency of micro-extraction of proteins from heritage materials is a crucial step. Extractions mediated by cycles of orbital agitation and ultrasonic radiation give the possibility to extract proteins from easel painting sample. In this work, protein-based paint models coupled with silica nanoparticles were used for micro-extraction. Nanoparticles possess high surface-to-volume ratios that can attach bioactive molecules such as proteins and increase the total protein recovered from microsamples. Protein extracts were quantified with Bradford Assay in the presence of Coomassie blue. The protein recovery results were statistically computed, and the SPSS analysis shows significant (p <0.05) increase in protein recovery, above 1.3 times for NPSiO2 and above 1.6 times for MCM-41. The statistical data shows evidence that silica nanoparticles intensify the total protein recovered from paint microsamples. Finally, ELISA was realized on the protein extracts to verify and compare the immunodetection of protein from the paint models with and without the use of silica nanoparticles

Effectiveness of the online 'Dialogue Circles' nursing intervention to increase positive mental health and reduce the burden of caregivers of patients with complex chronic conditions. Randomized clinical trial

The personal demands involved in caring for a chronically ill person can lead to emotional and physical exhaustion in caregivers. The aim of this study was to evaluate the effectiveness of an online nursing intervention called 'dialogue circles' designed to reduce caregiver overload and enhance positive mental health (PMH) in family caregivers. We used a pre-post design. The sample consisted of 86 family caregivers of patients with complex chronic conditions, randomly assigned to the intervention group (n = 43) or the control group (n = 43). All participants completed the Zarit scale and the Positive Mental Health Questionnaire 15 days before starting the intervention and 30 days after its completion. Comparison of the post-test changes revealed statistically significant differences between the two groups in PMH and overload, with the intervention group showing greater positive changes in all dimensions of PMH after the intervention and lower scores on overload. In conclusion, the results suggest that incorporating dialogue circles as an online nursing intervention in the caregivers of patients with complex chronic conditions can enhance PMH and decrease caregiver overload, especially in settings where face-to-face encounters are not possible

Development of a fast, urban chemistry metamodel for inclusion in global models

A reduced form metamodel has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net export flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used to develop the metamodel, and its coefficients, so that it is applicable under a broad range of present-day and future conditions. The inputs upon which this metamodel have been formed are based on a combination of physical properties (average temperature, diurnal temperature range, date, and latitude), anthropogenic properties (patterns and amounts of emissions), and the nature of the surrounding environment (background concentrations of species). The metamodel development involved using probability distribution functions (PDFs) of the inputs to run a detailed parent chemical and physical model, the Comprehensive Air Quality Model with Extensions (CAMx), thousands of times. Outputs from these runs were used in turn to both determine the coefficients of and test the precision of the metamodel, as compared with the detailed parent model. It was determined that the deviations between the metamodel and the parent mode for many important species (O[subscript 3], CO, NO[subscript x], and black carbon (BC)) were found to have a weighted RMS error less than 10 % in all cases, with many of the specific cases having a weighted RMS error less than 1 %. Some of the other important species (VOCs, PAN, OC, and sulfate aerosol) usually have their weighted RMS error less than 10 % as well, except for a small number of cases. In these cases, the complexity and non-linearity of the physical, chemical, and meteorological processing is too large for the third order metamodel to give an accurate fit. Finally, sensitivity tests have been performed, to observe the response of the 16 metamodels (4 different meteorologies and 4 different urban types) to a broad set of potential inputs. These results were compared with observations of ozone, CO, formaldehyde, BC, and PM[subscript 10] from a few well observed urban areas, and in most of the cases, the output distributions were found to be within ranges of the observations. Overall, a set of efficient and robust metamodels have been generated which are capable of simulating the effects of various physical, chemical, and meteorological processing, and capable of determining the urban concentrations, mole fractions, and fluxes of species, important to human health and the global climate.Massachusetts Institute of Technology. Joint Program on the Science & Policy of Global ChangeUnited States. Dept. of Energy. Office of Biological and Environmental Research (grant DE-FG02-94ER61937)United States. Dept. of Energy. Office of Biological and Environmental Research (grant DE-FG02-93ER61677

Three-Dimensional Structural Analysis of Temple 16 and Rosalila at Copan Ruinas

Temple 16 is an ancient Maya structure located at the heart of the Copán Ruinas Acropolis in Western Honduras. Temple 16 contains several earlier structures within it that were built on top of each other throughout Copán’s history. One of these earlier structures, Rosalila, is one of the most culturally significant structures within the Acropolis due to its preservation. An intricate series of archeological tunnels have been excavated throughout Temple 16 to allow for its study. However, significant cracking has been observed within Rosalila and several tunnels have experienced partial collapse. This not only poses a life safety issue for those utilizing the tunnels, but also demonstrates the risk to invaluable cultural heritage. To this end, this thesis aims to provide a rigorous structural assessment of Temple 16 and the buried Rosalila structure, accounting for its complex 3D tunnel system, to understand the leading causes of tunnel collapse and structure deterioration. Geometric data was collected of the acropolis, Temple 16, Rosalila, and the complex network of tunnels using a combination of ground-based lidar and uncrewed aerial systems. The resulting point clouds were vectorized to yield a series of connected surfaces, which were then meshed as a solid to facilitate finite element analysis. Analyses were conducted to understand both the current stress distribution within Temple 16 as well as to study the impact of various hypothetical tunnel backfilling scenarios to provide recommendations for preservation and tunnel safety. The generated finite element models were analyzed under three water saturation levels to account for the impact of heavy rainy seasons and water infiltration on the stress levels of the tunnels. From the analyses, sixty-three highly stressed areas were identified among the current tunnel system, with most of them being close or directly underneath Rosalila. From the tested hypothetical backfilling scenarios, it was found that, backfilling excavated sections can improve or worsen these stress concentrations depending on the location of the tunnel within the system. Finally, by analyzing Rosalila’s current geometry, it was observed that the structure experiences high levels of stress on its southern side due to its location within Temple 16. From this, it was concluded that fixing exposed areas of Rosalila that were affected by excavation on its southern side can significantly alleviate the existing deterioration and improve the stress flow in these areas. Advisors: Christine E. Wittich & Richard L. Wood