80 research outputs found
The Socio-Economic Challenges Facing Asia Due to Insufficient Earnings and Employment
Despite inadequate earnings and employment, Asia continues to face socio economic challenges that existed prior to the pandemic and have contributed to the region's difficulty in creating decent jobs and advancing towards employment. From an Asian perspective, the purpose of this study is to examine, from an Asian perspective, the extent and influence of vulnerabilities among workers as well as the socio-economic challenges they pose to the economy. After a systematic analysis of literary sources and approaches to addressing the issue of vulnerable employment, a conclusion can be drawn that such employment is unsustainable. This is based on the analysis of literary sources and approaches. As a result, it does not promote a stable economy, a strong workforce, or a stable social environment. There has also been evidence to support the idea that the appearance of such a trend has the potential to cause social unrest as a result of such a tendency. In the Asian context, it is imperative that we examine the classical definition of vulnerable employment in the context of Asian markets in order to assess the relevance of this scientific problem. In addition to the study of the effects of certain socio-economic factors on the employment of vulnerable individuals, and/or strengthening the adverse effects of vulnerable employment on those already in need, we should also examine the effects of vulnerability on those already affected
The risk associated with iron deficiency anemia for simple febrile seizures in children: A case–control study
Background: Studies have postulated iron deficiency state to be a risk factor for febrile convulsions as it changes the threshold of neurons excitation which may lower the threshold for seizures in children. However, many other studies have reported a protective role for febrile convulsions by increasing the neuronal threshold. Objective: The objective of the study was to evaluate the association of iron deficiency anemia (IDA) as a risk factor for the occurrence of simple febrile seizures (FS) in children. Material and Methods: A case-control study was conducted in a tertiary teaching hospital from September 2015 to February 2017. A total of 240 cases with fever and simple FS were enrolled according to the inclusion and exclusion criteria. Another 100 cases of children without seizure but with short duration of fever were enrolled as controls. Blood samples were then taken for assessing the hematological indices of these patients. The results were statistically analyzed. Results: Incidence of IDA was found to be more in children with simple FS than controls but was not statistically significant (p=0.35). Furthermore, no association was found with other hematological indices with FS occurrence. Conclusion: We could not find any association of IDA as a risk factor for a simple FS
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Data pre-processing for the preterm prediction study MFMU dataset
Preterm birth is a major public health problem with profound implications on society. There would be extreme value in being able to identify women at risk of preterm birth during the course of their pregnancy. Previous research has largely focused on individual risk factors correlated with preterm birth (e.g. prior preterm birth, race, and infection) and less on combining these factors in a way to understand the complex etiologies of preterm birth. We attempt to address this gap by conducting a deeper analysis of the preterm prediction study data collected by the NICHD Maternal Fetal Medicine Units (MFMU) Network, a high-quality data for over 3,000 singleton pregnancies having detailed study visits and biospecimen collection at 24, 26, 28 and 30 weeks gestation. Reports from this dataset used relatively straightforward biostatitistical methodologies such as relative risk assessments to measure associations between risk factors and PTB (Maternal Fetal Medicine Units Net- work. Biostatistical Coordinating Center NICHD Networks, 1995). These methods include descriptive statistics, Pearson correlation, Fisher’s exact tests and linear/logistic regression where risk factors are studied independent of each other. In order to perform detailed experiments on this data using non-linear Support Vector Machines and other machine learning (ML) methodologies, it is necessary to complete several pre-processing steps that we describe in this report
Evaluation of safety, clinical outcomes, and patient-reported outcomes after meniscus repair using surestitch all inside meniscal repair implant: a retrospective and observational study
Background: Anterior cruciate ligament (ACL) injuries and meniscus injuries frequently co-occur, underscoring the interconnected nature of knee joint structures. Meniscus injuries, often caused by sports trauma or degenerative changes, necessitate careful management to preserve joint function and prevent complications like osteoarthritis. This retrospective observational study evaluates the safety, clinical outcomes, and patient-reported outcomes of meniscus repair using Surestitch all inside meniscal repair implant, a contemporary solution designed to optimize meniscal repair.
Methods: The study, approved by the institutional ethics committee, included patients aged 18-80 years who underwent meniscus repair with Surestitch between October 2020 and July 2022. Data on demographics, surgical details, and outcomes were collected from medical records and telephonic follow-ups.
Results: Among 36 subjects, the mean age was 36.89 years. The mean (SD) duration of follow-up was 364 days (127). There was no meniscus repair failure noted in any of the patients. Functional patient-reported outcomes assessed using international knee documentation committee (IKDC) with a score of (60.15±12.40), and Lysholm scores (77.03±14.45) demonstrated favorable results. The knee injury and osteoarthritis outcome score (KOOS) of (54.63) further indicated positive knee health across domains. There were no adverse events or reoperations.
Conclusions: The study demonstrated favorable safety, clinical outcomes, and patient-reported outcomes, yielding satisfactory results, and consequently establishing the safety and effectiveness of the Surestitch All inside meniscal repair implant in meniscus repair
Transcriptome analysis of lentil (Lens culinaris Medikus) in response to seedling drought stress
MSEA: Modified Symmetric Encryption Algorithm
In this article, a new symmetric block cipher named MSEA is proposed. MSEA is based on ARX cryptographic design technique. MSEA is simple in nature due to the use of combinations of elementary operations like modular addition, bit-wise rotation and bit-wise XOR. In MSEA, plain text block, secret key, and number of encryption rounds are variable in size, while the size of cipher text is double of size of plain text. Data-dependant rotation is the most vital feature of MSEA through which the unpredictability of encrypted text is increasing. Key formation and encryption/decryption schemes of MSEA are significantly fast
Analytics for Power Grid Distribution Reliability in New York City
We summarize the first major effort to use analytics for preemptive maintenance and repair of an electrical distribution network. This is a large-scale multiyear effort between scientists and students at Columbia University and the Massachusetts Institute of Technology and engineers from the Consolidated Edison Company of New York (Con Edison), which operates the world’s oldest and largest underground electrical system. Con Edison’s preemptive maintenance programs are less than a decade old and are made more effective with the use of analytics developing alongside them. Some of the data we used for our projects are historical records dating as far back as the 1880s, and some of the data are free-text documents typed by Con Edison dispatchers. The operational goals of this work are to assist with Con Edison’s preemptive inspection and repair program and its vented-cover replacement program. This has a continuing impact on the public safety, operating costs, and reliability of electrical service in New York City
Impact of a package of diagnostic tools, clinical algorithm, and training and communication on outpatient acute fever case management in low- and middle-income countries: protocol for a randomized controlled trial.
BACKGROUND: The management of acute febrile illnesses places a heavy burden on clinical services in many low- and middle-income countries (LMICs). Bacterial and viral aetiologies of acute fevers are often clinically indistinguishable and, in the absence of diagnostic tests, the 'just-in-case' use of antibiotics by many health workers has become common practice, which has an impact on drug-resistant infections. Our study aims to answer the following question: in patients with undifferentiated febrile illness presenting to outpatient clinics/peripheral health centres in LMICs, can we demonstrate an improvement in clinical outcomes and reduce unnecessary antibiotic prescription over current practice by using a combination of simple, accurate diagnostic tests, clinical algorithms, and training and communication (intervention package)? METHODS: We designed a randomized, controlled clinical trial to evaluate the impact of our intervention package on clinical outcomes and antibiotic prescription rates in acute febrile illnesses. Available, point-of-care, pathogen-specific and non-pathogen specific (host markers), rapid diagnostic tests (RDTs) included in the intervention package were selected based on pre-defined criteria. Nine clinical study sites in six countries (Burkina Faso, Ghana, India, Myanmar, Nepal and Uganda), which represent heterogeneous outpatient care settings, were selected. We considered the expected seasonal variations in the incidence of acute febrile illnesses across all the sites by ensuring a recruitment period of 12 months. A master protocol was developed and adapted for country-specific ethical submissions. Diagnostic algorithms and choice of RDTs acknowledged current data on aetiologies of acute febrile illnesses in each country. We included a qualitative evaluation of drivers and/or deterrents of uptake of new diagnostics and antibiotic use for acute febrile illnesses. Sample size estimations were based on historical site data of antibiotic prescription practices for malarial and non-malarial acute fevers. Overall, 9 semi-independent studies will enrol a minimum of 21,876 patients and an aggregate data meta-analysis will be conducted on completion. DISCUSSION: This study is expected to generate vital evidence needed to inform policy decisions on the role of rapid diagnostic tests in the clinical management of acute febrile illnesses, with a view to controlling the rise of antimicrobial resistance in LMICs. TRIAL REGISTRATION: Clinicaltrials.gov NCT04081051 . Registered on 6 September 2019. Protocol version 1.4 dated 20 December 2019
Neuromatch Academy: a 3-week, online summer school in computational neuroscience
Neuromatch Academy (https://academy.neuromatch.io; (van Viegen et al., 2021)) was designed as an online summer school to cover the basics of computational neuroscience in three weeks. The materials cover dominant and emerging computational neuroscience tools, how they complement one another, and specifically focus on how they can help us to better understand how the brain functions. An original component of the materials is its focus on modeling choices, i.e. how do we choose the right approach, how do we build models, and how can we evaluate models to determine if they provide real (meaningful) insight. This meta-modeling component of the instructional materials asks what questions can be answered by different techniques, and how to apply them meaningfully to get insight about brain function
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