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Analyzing the Centers for Disease Control and Prevention Mortality Data Using Weekly Exceedance in Mortality Count and Weekly Change in Mortality Indicator: A Time Series Study
No full textBackground and Aims
Cause-specific mortality (CSM) count prediction plays a vital role in the context of public health policy. In this study, we introduce a new analytical approach, which is divided into three phases to answer specific questions regarding CSM due to 14 specific causes by computing different simple, compound, and conditional probabilities.
Methods
A multivariate time series forecasting model was developed using the CDC weekly mortality count data. A binary data matrix was constructed for 14 causes of death (COD) as a function of weeks by combining the observed and forecasted mortalities. We introduced two new concepts: Weekly Exceedance in Mortality Count (WEMC) and Weekly Change in Mortality Indicator (WCMI), which were instrumental in computing various probabilities relating to all the CODs. To test the null hypothesis of no association between the COD and WEMC a chi-square test of independence was conducted whereas Cramer\u27s V statistic was used to check the strength of the association. Wilcoxon rank sum test, and correlation indices were used to validate the method.
Results
The results of chi-square test of independence indicated that there was no statistically significant association between COD and WEMC (p = 0.79). Furthermore, the effect size of this association between COD and WEMC was very small (Cramer\u27s V = 0.055). The results of Wilcoxon rank sum test indicated that there was no statistically significant difference between the observed and forecasted counts (p = 0.11) confirming the consistency of our analytical method. Probabilities associated with WCMIs were also computed as an illustration of the analytical method.
Conclusion
Utilizing this analytical approach, researchers and policymakers can compute the probabilities of any number of desired events related to different COD which can be helpful for public health interventions, resource allocation, informed decision-making and risk assessment, by controlling the underlying attributes responsible for the probabilities to surge and plummet
The Structure Function of the Free Neutron at High X-Bjorken
No full textUnderstanding the internal structure of nucleons is one of the primary goals of nuclear physicists. As protons and neutrons are only the bound state solution of the QCD lagrangian (at least inside atomic nuclei), studying protons and neutrons helps uncover nuclear structure. Due to its easy availability, many studies on protons have been done on a wide range of kinematics. However, free neutron targets are not readily achievable. So, any information on neutrons has to be extracted from neutron-rich nuclei, and some nuclear models have to be used to subtract the contributions from other nucleons to extract the information on neutrons. So, the Barely Off-shell Nucleon Structure (BONuS12) experiment at Jefferson Lab was conducted to overcome these challenges by using spectator tagging. The experiment effectively created a quasi-free neutron target by scattering electrons off a deuterium target and detecting low-momentum, backward-moving protons using a custom-built Radial Time Projection Chamber (RTPC). Selecting the low momentum and backward-moving spectators would enable us to minimize the model-dependent effects due to final state interactions and target fragmentation. The RTPC was a 40 cm-long cylindrical detector that worked on the principle of gaseous ionization. It had three layers of Gas Electron Multipliers (GEMs) for charge amplification and a surrounding readout pad. The scattered electrons were measured using the CLAS12 detector, and data were collected using a 10.4 GeV electron beam during Spring and Summer 2020. Using spectator tagging, we extracted the structure function ratio Fn2 of the quasi-free neutron in the deep inelastic scattering at high x, up to x ≈ 0.8. The result was extracted in the region with the invariant mass W \u3e 1.8 GeV/c2 , and Q2 in the range 1.3 to 11 GeV2 . This dissertation presents the methodology, event selection criteria and refinements, estimation and subtraction of backgrounds, and complete analysis of the extraction of Fn2 /Fp2 in a model-independent way. Systematic uncertainties in our final analysis will also be discussed in detail
The Role of Artificial Intelligence in Workforce Learning and Development: A Systematic Review
No full textThe purpose of this study is to investigate how artificial intelligence (AI) is currently employed in workforce learning and development. The study examined the types of AI employed and the affordances realized for organizations and employees. A PRISMA systematic review methodology was utilized to address the overarching problem statement and answer the three questions guiding the study. The PRISMA extension Preferred Reporting Items for Systematic Reviews and Meta Analysis for Protocols was used to direct each phase of the research. In addition, the Preferred Reporting Items for Systematic Reviews and Meta Analysis was used to conduct the article selection process. Findings revealed studies were distributed predominantly between Asia, Europe, and the United States. For types of AI, grounded coding resulted in three prominent trends: 1) Applied AI, 2) machine learning, and 3) natural language processing. Grounded coding revealed five trends for affordances: 1) learning approaches, 2) learner experience, 3) usability 4) organization efficiency and 5) cost. This systematic review is limited as it only examined peer-reviewed journal and conference publications available in English with reported organizational and learning outcomes. This study is unique in that it provides organizations and educators with the first systematic review examining AI’s role in the development and delivery of workforce training and development
Methodological and Clinical Concerns in the Study on Postpartum Hypertension Management
No full text[Introduction] We read with interest the recent study by Rosenfeld et al.¹ However, we have several clinical and methodological concerns about this study.¹
First, this study\u27s propensity score matching (PSM) lacked key clinical confounders, including perinatal risk factors and the highest systolic/diastolic blood pressures. Smoking, alcohol use, and multifetal gestation, which influence blood pressure during pregnancy,²,³ potentially affect both primary and secondary outcomes. Additionally, the authors did not report standardized mean differences before and after PSM, which are essential for assessing balance.
A Comparison of Conversational Chatbots and the Internet for Consumer Information Search
No full textThis study compares consumer perceptions of conversational chatbots and the internet for information search. While the internet is a mature platform, conversational chatbots represent an emerging technology, and insight into how consumers view them in relation to the internet for information search is lacking. Drawing on the information source utility perspective, the study builds a comparative model based on four key dimensions: information currency, information customisation, information trustworthiness, and media richness. Additionally, the study investigates consumers’ prior experience with conversational chatbots as a moderating factor. Data was collected from 191 respondents recruited through MTurk. Paired sample t-tests assessed mean differences between the internet and conversational chatbots along the four dimensions of information source utility, while ANOVA assessed the effect of prior experience on the mean differences. The findings show that the internet is perceived as a superior platform across all four dimensions. Perceived gaps were wider for the information currency and media richness dimensions, but were narrower for the information customisation and information trustworthiness dimensions. Furthermore, consumers with greater prior chatbot experience perceived narrower gaps between the internet and conversational chatbots across all four dimensions than those with less experience. The theoretical and practical implications of these findings are discussed
Assessing the Possibilities and Speculations of Blended Teaching-Learning (BTL) Based on the Online Teaching-Learning (OTL) Experience during COVID-19 in Bangladesh
No full textThis research paper investigates the potential and viability of implementing Blended Teaching Learning (BTL) in Bangladesh, drawing on the lessons learned from the COVID-19 Online Teaching Learning (OTL) practice experiences. The study specifically focuses on examining the advantages and challenges encountered by teachers and students in online classes during the pandemic. Through a mixed-methods approach, including questionnaire surveys, interviews, and focus group discussions (FGDs), data was collected from secondary-level teachers and students in Bangladesh. The findings highlight the dedicated efforts made by educators and students in embracing and adapting to online education during the COVID-19 crisis. Furthermore, the study identifies hindering factors, such as inadequate infrastructure, limited network availability in rural areas, lack of access to devices, insufficient training and skills, and socioeconomic disparities among guardians. Despite these challenges, the research underscores the willingness of teachers and students to embrace the BTL approach in the new normal educational landscape. Overall, this study provides insights into the potential for implementing BTL in secondary schools in Bangladesh, highlighting both the opportunities and obstacles that need to be addressed for its successful implementation
Short-Term Removal of Exercise Impairs Flow-Mediated Dilation Similarly in Older and Younger Adults
No full textAIMS: To investigate and compare the effects of 5 days of removal of exercise on endothelial function in older and younger active adults. METHODS: Older (n=12, 63.8±2.2 years) and younger (n=12, 23.9±0.7 years) active (≥90 min/week of exercise) adults underwent 7 days of habitual exercise (EX) and 5 days of removal of exercise (NOEX). Endothelial function was assessed via brachial and popliteal artery flow-mediated dilation (FMD) on the day following the EX-phase and on days 3 and 5 of the NOEX-phase. RESULTS: Steps per day were reduced in both older (EX: 6,687.9±639.3; NOEX: 3,155.3±364.6; ppp=0.035) and peak diameter (Old: EX: 4.02 ± 0.18cm; NOEX: 3.97 ± 0.17cm; Young: EX: 4.40 ± 0.14cm; NOEX: 4.28 ± 0.15cm; pp\u3e0.05), although a significant interaction was observed for time x age (pp=0.014) and peak diameter (Old: EX 5.74 ± 0.37cm; NOEX: 5.62 ± 0.38cm; Young: EX: 6.07 ± 0.27cm; NOEX: 5.92 ± 0.26cm; pp\u3e0.05). CONCLUSIONS: Older and younger active subjects experience similar impairments in brachial and popliteal artery FMD following short-term (5 days) removal of exercise
Chronic Urinary Schistosomiasis Presenting as Hydronephrosis in a 26 Year-old Male
No full textIntroduction/Case Presentation:
A 26-year-old male who recently immigrated to the United States from Mauritania presented to the ED with one day of worsening left flank pain accompanied by nausea, vomiting, and chills. He reported a past medical history of kidney stones which had always passed spontaneously, as well as a history of gross hematuria as a child. A CT scan showed a 5mm obstructing stone in the left distal ureter with severe left hydroureteronephrosis, along with small, layering stones in the mid- and distal right ureter without hydronephrosis. Additionally, it revealed circumferential calcifications along the dome of the bladder, suspicious for urinary schistosomiasis. Urology was consulted and he was discharged from the ED on medical expulsive therapy with outpatient urology follow-up. Three days later, he returned to the ED with continued uncontrolled left flank pain and nausea. CT findings were unchanged from previous, and he was admitted for surgical stone management. Cystoscopy revealed numerous submucosal calcifications consistent with schistosomiasis exposure, and left retrograde pyelogram showed a 5mm pinpoint distal ureteral stricture. Attempts to navigate through the stricture failed, so a nephrostomy tube was placed for temporary decompression. He was given one dose of praziquantel for empiric treatment of schistosomiasis and Schistosoma antibodies were drawn, which came back negative. Two months later, a ureteral reimplantation was performed for definitive management of the stricture, and the excised stricture was sent to pathology, which revealed chronic granulomatous inflammation, fibrosis, and calcified schistosome eggs. He was then referred to our Infectious Disease clinic for outpatient follow-up for the diagnosis of chronic urinary schistosomiasis.
Discussion:
This case offers an opportunity to review the epidemiology and management of schistosomiasis, a parasitic flatworm infection that is extremely common in endemic areas but a relatively rare finding in the United States. The infection is spread via unbroken skin contact with contaminated freshwater when schistosome larvae penetrate human skin and invade the bloodstream. Schistosomiasis has an acute and chronic form: acute schistosomiasis syndrome is a systemic hypersensitivity reaction to schistosome antigens and immune complexes. Chronic infection can occur in a variety of organs depending on the tropism of the species present and is the result of egg deposition and subsequent immune response. Our patient’s findings of fibrosis and calcification of the ureteral and bladder wall is consistent with longstanding infection by S. haematobium or an S. haematobium-hybrid species. Several different tools can be used to diagnose infection and monitor for successful treatment, including microscopic identification of eggs, antigen and antibody tests, imaging, and biopsy, but appropriate knowledge is needed on how to use and interpret these tests properly to guide management. In our case, serology may have been negative due to the use of S. mansonii antigens, which has lower sensitivity for S. haematobium antibodies. As praziquantel is not 100% effective at eliminating infection, it is vital to know when repeat treatment is needed, as risks of longstanding infection include bladder neck or ureteral obstruction, as seen in our patient, as well as bladder cancer, classically squamous cell carcinoma
Therapy-Based Strategies to Support Tummy Time in Infants Post-Hospital Discharge: A Scoping Review Protocol
No full textTummy time is essential for infant development, yet many caregivers face significant challenges with adherence due to behavioral and contextual barriers. While numerous tummy time interventions exist, a limited understanding of their behavioral components hinders effective replication and implementation. This scoping review aims to identify multidisciplinary interventions used to promote tummy time in infants aged 0–12 months, evaluate their impact on adherence, developmental and health outcomes, and examine the behavior change techniques employed using the Theoretical Domains Framework (TDF). Following the Joanna Briggs Institute (JBI) methodology, a comprehensive search will be conducted in MEDLINE (PubMed), Web of Science Core Collection, CINAHL (EBSCOhost), ClinicalTrials.gov, and gray literature sources for relevant studies published in English between January 1994 and January 2025. Eligible studies will include experimental research involving infants aged 0–12 months who received targeted tummy time interventions following hospital discharge across various early intervention settings. Data extraction will be performed by two independent reviewers using a customized tool, with results presented as a narrative summary, tabular form, or diagrams, as appropriate. Findings from this review will inform the development of behaviorally grounded, clinically feasible tummy time strategies that are better aligned with caregiver needs
TL-ConvLSTM: A Transfer-Learning-Based Convolutional LSTM to Identify and Forecast Traffic in the NextG Environments
No full textForecasting and categorizing cellular traffic flows and their types are essential functions in intelligent network systems to ensure efficient network optimization. The ever-evolving nature of 5G networks results in fluctuations in traffic patterns over time, leading to a phenomenon known as model drift. Consequently, accurately predicting and identifying cellular traffic patterns becomes a complex task. To tackle this challenge, this article introduces an innovative approach called TL-ConvLSTM, which combines transfer learning with convolutional long short-term memory (ConvLSTM) to effectively combat model drift and provide precise forecasting and recognition of cellular traffic within the network. To accomplish this, we initiate the training of TL-ConvLSTM by estimating its parameters from the source domain. We then employ the Kolmogorov–Smirnov method to adapt the model within the target domain, fine tuning its weights. To improve the precision of this model adaptation, we systematically explore optimal learning windows. This exploration includes adjusting window size for time-series data and feature dimensions to capture dynamic traffic patterns in a 5G environment. Furthermore, we make use of the Amarisoft 5G testbed in our lab to create a 12-day time-series dataset. This dataset includes various features related to traffic flows and their patterns. We showcase the effectiveness of our approach through a set of experiments