PLoS ONE最新文献

This paper presents a new framework based on nonlinear partial differential equations and statistics. For the nonlinear Phi-4 equation, the probability density function of the hyperbolic secant (HS) distribution has been obtained. Our model's density has various shapes, including left-skewed, symmetric, and right-skewed. Eight distinct estimation approaches have been employed to estimate the parameters of our model. Additionally, the behavior of the HS model parameters was investigated using randomly generated data sets using these estimation techniques. Furthermore, we illustrate the applicability of the HS distribution for modeling real data by applying our results to real data. As a result, it is expected that our proposal will be of significant assistance to the community investigating new distributions based on hyperbolic functions and their applications to real-world data sets.

Background: About half of the world's populations are infected with Helicobacter pylori, which may create atherogenic lipid profiles and contribute to atherosclerosis and related cardiovascular disease. Furthermore, it has been connected to hematological symptoms like anemia. Even though the high prevalence of H.pylori and its associated complications, including cardiovascular disease and anemia, in Ethiopia, there is little data regarding the risk factors associated with H.pylori infection, such as hematologic parameters, electrolyte imbalances, and lipid profiles.

Methods: A comparative cross-sectional study design with a consecutive sampling technique was employed at Jimma Medical Center among 108 dyspeptic patients. Five (5) ml of blood samples were collected from each participant, and serum was extracted and analyzed using a COBAS 6000 core for the lipid and electrolyte, and whole blood was used with a SYSMEX XN 550 to determine hematological parameters. Data were entered in to Epi-data version 4.6 and exported to SPSS version 25 for analysis. Simple descriptive statistics and chi-square test were used to present the socio-demographic characteristics of the study subjects. Student t-test was used for data comparison and p-value < 0.05 was considered statistically significant.

Results: H.pylori infected patients had significantly decreased levels of red blood cell count (p = 0.002), hemoglobin (p = 0.012), mean corpuscular hemoglobin concentration (p < 0.001), platelet count (p = 0.001), and sodium level (p = 0.006) when compared to the uninfected group. However, total cholesterol (p = 0.001), and low density lipoprotein (p = 0.021) were increased in H.pylori infected patients when compared to the uninfected group.

Conclusions: This study revealed that H.pylori infection can cause derangements of hematologic parameters, electrolyte imbalances, and alterations of lipid parameters which considered as risk factors for anemia and cardiovascular diseases.

The single-input-single-output technology experiences loss of data in the communication channel due to the receiving antenna undergoing fading of the signal impinged on it. Today's need is faster data transfer with multiple applications in the single antenna with multiple-identical radiating elements, leading to multiple-input-multiple-outputDWMB (MIMODWMB) technology. The MIMODWMB configuration with multi-band capability is the objective of the proposed work with applications ranging between microwave-millimeterWave bands. The four-port Dual-Wide Multi-Band (DWMB) MIMODWMB antenna radiating electro-magnetic-energy is proposed, which generates measured bandwidths of 7.27GHz-34.32GHz (Band 1) and 46.54GHz-71.52GHz (Band 2) including applications Up-link/Down-link Satellite System, X-Band, Ku-Band, ISM 24.0GHz (24.0GHz-24.25GHz), 24.0GHz UWB Band (21.65GHz-26.65GHz), n258, n257/n261 and n263 V-band. The proposed antenna technology is printed on Rogers's low permittivity substrate with a hexagon patch etched with dual merged-elliptical slot and three identical circular slots to achieve high impedance matching for Band 1. The partial-ground is etched by a rectangular slot for better impedance matching, and two-thin-etched rectangular slits generate 60.0GHz Band 2. The thin substrate, thickness 0.254mm, is utilized for flexible applications without compromising the operation of dual wide bandwidths. The flexible antenna is also subjected to analysis of Specific-Absorption-Rate (SAR) analysis at key frequencies within both the bands and found to be within the standard limit of 1.60W/Kg for 1g of the human tissue model and corresponds to 1.01W/Kg at 10.0GHz, 0.280W/Kg at 15.0GHz, 0.475W/Kg at 26.0GHz, 0.588W/Kg at 28.0GHz & 0.301W/Kg at 60.0GHz. The high diversity performance with Envelope Correlation Coefficient<0.50, Diversity Gain≈10.0dB, Total Active Reflection Coefficent<0dB, Channel Capacity Loss<0.40b/s/Hz and multi-band capability for mobile users make the proposed work suitable for flexible on-body applications in a wireless environment. The proposed work MIMODWMB antenna offers advantages such as reduced size (20mm×24mm: 0.61λ0×0.74λ0 at λ0 = 7.27GHz) and a wide range of impedance bandwidths, which are useful for several applications. Also, due to the flexible nature of the design, they can be used for future on-body wearable applications.

Innovation is key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies such as the Internet of Things (IoT) is not a luxury but a necessity. This article tackles the formidable task of identifying and comprehensively evaluating the impediments to IoT adoption in the Bangladeshi manufacturing industry. We delve deeply into the complex terrain of IoT adoption challenges by synthesizing expert insights and a meticulously selected body of contemporary literature. We employ a robust methodology combining the Delphi method with the fuzzy Analytical Hierarchy Process to systematically analyze and prioritize these challenges. Using this methodology, we leveraged the combined expertise of domain specialists and subsequently employed fuzzy logic techniques to address the inherent ambiguities and uncertainties within the data. Our findings highlight this clear path. They reveal that among the myriad barriers, "Lack of top management commitment to implementing new technology" (B10), "High initial implementation investment costs" (B9), and "Risks associated with switching to a new business model" (B7) loom most extensive, demanding immediate attention. These insights are not confined to academia but serve as a pragmatic guide for industrial managers. Armed with the knowledge gleaned from this study, managers can craft tailored strategies, set well-informed priorities, and embark on a transformational journey toward harnessing the vast potential of IoT in the Bangladeshi industrial sector. This article provides a comprehensive understanding of IoT adoption challenges and industry leaders with the tools necessary to navigate these challenges effectively. This strategic navigation, in turn, contributes significantly to enhancing the competitiveness and sustainability of Bangladeshi manufacturing in the IoT era.

This study aims to develop a cost-effective and reliable motion monitoring device capable of comprehensive fatigue analysis. It achieves this objective by integrating surface electromyography (sEMG) and accelerometer (ACC) signals through a feature fusion strategy. The study introduces a multi-level attention mechanism for classification, leveraging convolutional neural networks (CNNs). The preprocessing phase involves a local feature attention mechanism that enhances local waveform features using the amplitude envelope. A dual-scale attention mechanism, operating at both channel and neuron levels, is employed to enhance the model's learning from high-dimensional fused data, improving feature extraction and generalization. The local feature attention mechanism significantly improves the model's classification accuracy and convergence, as demonstrated in ablation experiments. The model, optimized with multi-level attention mechanisms, excels in accuracy and generalization, particularly in handling data with pseudo-artifacts. Computational analysis indicates that the proposed optimization algorithm has minimal impact on CNN's training and testing times. The study achieves recognition accuracies of 92.52%, 92.38%, and 92.30%, as well as F1-scores of 91.92%, 92.13%, and 92.29% for the three fatigue states, affirming its reliability. This research provides technical support for the development of affordable and dependable wearable motion monitoring devices.

Objectives: Symptomatic vestibulopathy impairs patients' lives. However, few studies have explored the lives of patients with compensated or asymptomatic vestibulopathy. This study investigated the quality of life (QOL), psychological health, and physical function of patients with vestibulopathy.

Materials and methods: Using the eighth Korea National Health and Nutrition Examination Survey database, we included individuals with data on demographic factors, diabetes, hypertension, dizziness experiences, pure-tone audiometry, video head impulse test (vHIT), Health-related Quality of Life Instrument with 8 Items, General Anxiety Disorder 7-item scale, stress, and walking and sitting times. Participants were classified into the following groups: an uncompensated group with abnormal vHIT result and chronic dizziness, a compensated group with abnormal vHIT result and a history of dizziness, an asymptomatic group with abnormal vHIT result and no history of dizziness, and a normal group without abnormal vHIT result or a history of dizziness.

Results: Uncompensated vestibulopathy was more common in older individuals and women. The uncompensated group showed impairments in climbing stairs (P < 0.001), pain (P < 0.001), vitality (P = 0.001), working (P < 0.001), depression (P < 0.001), sleep (P = 0.001), happiness (P = 0.002), anxiety (P = 0.006), and stress (P = 0.003). The compensated group showed deficits in pain (P < 0.001), work (P = 0.006), sleep (P = 0.001), and happiness (P = 0.001). The asymptomatic group had no deficits in QOL, psychological health, or physical function. These tendencies were similar after controlling for age and gender.

Conclusion: Vestibulopathy with a history of dizziness has a long-lasting impact on QOL and emotional status, even after compensation. Uncompensated vestibulopathy has a significant effect on QOL and mental health. Notably, though, the compensated group also showed a reduction in QOL. Appropriate interventions for each category of patients should be provided based on their impaired functions.

In the era of digital intelligence empowerment, the data-driven approach to the mining and organization of humanistic knowledge has ushered in new development opportunities. However, current research on allusions, an important type of humanities data, mainly focuses on the adoption of a traditional paradigm of humanities research. Conversely, little attention is paid to the application of auto-computing techniques to allusive resources. In light of this research gap, this work proposes a model of allusive word sentiment recognition and application based on text semantic enhancement. First, explanatory texts of 36,080 allusive words are introduced for text semantic enhancement. Subsequently, the performances of different deep learning-based approaches are compared, including three baselines and two optimized models. The best model, ERNIE-RCNN, which exhibits a 6.35% improvement in accuracy, is chosen for the sentiment prediction of allusive words based on text semantic enhancement. Next, according to the binary relationships between allusive words and their source text, explanatory text, and sentiments, the overall and time-based distribution regularities of allusive word sentiments are explored. In addition, the sentiments of the source text are inferred according to the allusive word sentiments. Finally, the LDA model is utilized for the topic extraction of allusive words, and the sentiments and topics are fused to construct an allusive word-sentiment theme relationship database, which provides two modes for the semantic association and organization of allusive resources. The empirical results show that the proposed model can achieve the discovery and association of allusion-related humanities knowledge.

Introduction: The coexistence of under-nutrition and over-nutrition in developing countries like Ethiopia results in the "mother-child pair double burden of malnutrition," with children experiencing either stunting, wasting or underweight while mothers face overweight or obesity. This poses a major public health challenge, prompting global health organizations to prioritize the issue and urge governments to act quickly. Despite this, there is a lack of research in Ethiopia on the double burden of malnutrition among mother-child pairs at the household level and the factors that worsen it.

Objective: To assess the magnitude of double burden of malnutrition and its associated factors among mother-child pair at household level in East Ethiopia, 2022.

Method: A community-based cross-sectional study was conducted in East Ethiopia from April 15 to June 11, 2022. Multi-stage sampling was used, and data were collected through structured interviews. Child nutrition indicators were processed using WHO Anthro software. Binary logistic regression analysis was performed, calculating both crude and adjusted odds ratios to assess associations. Variables with a P value <0.05 in multivariable analysis were deemed statistically significant.

Result: The study revealed that coexisting malnutrition rates for (OM/SC), (OM/WC), and (OM/UC) were 8.5%, 7.0%, and 7.9% respectively. The double burden of malnutrition among mother-child pairs was found to be 12.3% [95% CI: 10.7, 13.7]. Marital status (divorced) [AOR = 1.80; 95% CI: 1.15, 2.82], child birth order (fourth or above) [AOD = 1.88; 95% CI:1.08, 3.26], number of under-five children in the household (five or more under-five children) [AOR = 1.58; 95% CI: 1.04, 2.39], poor maternal and child dietary diversity score [AOR = 2.76; 95% CI: 1.71, 4.45] and [AOR = 8.66; 95% CI: 4.85, 15.44], respectively, household food security status (food insecurity) [AOR = 3.68; 95% CI: 2.36, 5.75], and maternal stature (short stature) [AOR = 2.39; 95% CI: 1.65,3.45] were factors significantly associated with this burden.

Conclusion: The study emphasized the double burden of malnutrition affecting both mothers and children, a major public health concern in the area. Early-life nutrition is vital in preventing childhood under nutrition and adult obesity, leading to this dual burden. Breaking the cycle of malnutrition across generations is crucial. Policy makers should prioritize improving child nutrition and maternal health, stressing early-life nutrition to address the mother-child double burden of malnutrition.

Background: Although Ethiopia has substantial improvements in various health indicators such as maternal and child mortality, the burden of neonatal mortality remains high. Between 2016 and 2019, neonatal mortality increased from 29 deaths per 1,000 live births to 33 deaths per 1,000 live births. This study aimed to explore the spatial patterns and factors contributing to neonatal mortality in Ethiopia.

Methods: Data from the Ethiopian Demographic and Health Surveys (EDHS) for the years 2000, 2005, 2011, 2016, and 2019 were analyzed. The EDHS sampling design uses a two-stage cluster sampling technique, considering census enumeration areas as primary sampling units and households as secondary sampling units. We used the Spatial Scan analysis in SaTScan and Getis-Ord Gi* statistic in Geographic Information System (GIS), to analyse the spatiotemporal patterns of neonatal mortality. Maternal, newborn and health service-related factors contributing to neonatal mortality were also analyzed using a multilevel logistic regression model. Adjusted Odds Rios (AOR) with corresponding 95% CI were presented as a measure of association and a P-value of 0.05 was used to declare statistical significance.

Results: During the initial three consecutive surveys, there was a consistent pattern of hot spot clusters in the Amhara and Benshangul Gumuz regions, along with certain parts of the Oromia region. However, in later surveys, these clusters shifted to the eastern parts of the country, notably including the Somali region. Early initiation of breast feeding was associated with reduced chances of neonatal death (Adjusted Odds Ratio [AOR]) = 0.27; 95% Confidence Interval [CI]: 0.23, 0.32). Neonates born at home (AOR = 1.46; 95% CI: 1.16, 1.82) and male babies had a higher likelihood of mortality during the neonatal period compared to their counterparts (AOR = 1.36; 95% CI: 1.24, 1.51). The odds of neonatal mortality increased with the number of children a mother had ever given birth to (AOR = 1.36; 95% CI: 1.24, 1.51). In contrast, longer birth intervals were associated with a reduced risk of neonatal mortality (AOR = 0.76; 95% CI: 0.68, 0.83).

Conclusion: The central southern, central-western, north-western, and northern parts of Ethiopia had most of the neonatal death clusters in the first three rounds of DHS while eastern Ethiopia had the highest neonatal mortality clusters in the latest two surveys. Our results underscore the importance for policymakers and health administrators to reassess intervention approaches and reallocate resources to regions identified as hot spots for neonatal mortality. Enhancing the initiation of breastfeeding within the first hour of birth would improve newborn survival rates. Special attention and care need to be given to babies born of smaller sizes.

Background and objectives: Cognitive impairment is a core feature of schizophrenia, and it is now clear that there is a link between nutritional indicators and cognitive functioning. This study aimed to investigate correlations between three nutritional indicators (prognostic nutritional index [PNI], geriatric nutritional risk index [GNRI], and controlling nutritional status score [CONUT]) and cognitive function in hospitalized patients with stable schizophrenia.

Methods: A total of 235 patients who were hospitalized with stable schizophrenia were included. Patient demographic information was collected through self-reports or electronic medical records, and cognitive function was assessed using the Montreal Cognitive Assessment in China (MoCA-C). Information on serum albumin and total cholesterol levels, lymphocyte counts, and body mass index during the stable stage of schizophrenia was collected to calculate the PNI, GNRI, and CONUT scores, according to their respective calculation criteria. Covariate-adjusted linear regression model and ordered logistic regression model were constructed to determine the relationship between nutritional indicators and cognitive function.

Results: Overall, 90.2% of the patients were under the age of 60 years, and males comprised 60% of all patients. The median scores for MoCA-C, PNI, GNRI, and CONUT in hospitalized patients with stable schizophrenia were 18 (12,23), 52.85 (50.25,55.90), 110.85 (105.80,116.21), and 3 (3,3), respectively. The results of the correlation analysis showed that only PNI was associated with MoCA-C scores (r = 0.15, P = 0.021). This relationship was further confirmed by covariate-adjusted linear regression modeling (β = 0.147, 95%CI:0.049-0.351, p = 0.01) and ordered logistic regression modeling (OR = 0.054, 95%CI:0.001-0.106, p = 0.046).

Conclusions: The findings revealed a significant correlation between PNI scores and MoCA-C scores in hospitalized patients with stable schizophrenia.