bluuebunny/crossref_metadata_2025_split huggingface dataset:
Novel control of house fly Musca domestica and bacterial isolates by ozone gas
Authors: Metwally Ahmed M. , Salem Salem S. , Hammad Kotb M. , Metwaly Khaled H. , Awad Mohamed A. 
Published: April 2023

AbstractOzone is a sturdy oxidant which canrub insects and microorganisms. Thus, it could be useful in eliminate the Housefly in hospitals. The purpose of test here is to determine degree of ozone exposure required to remove houseflies and reduction of pathogenic bacteria. Ozone was effective with housefly, requiring only low minutes of treatment (1 to 14 min.) at minimum concentrations of ozone gas O3 (0.125 g/m3 to 1 g/m3), the insects were eliminated the ozone. Thus, ozone exhibit potential as a fumigant for ousefly nesting materials, but moreover research is needed to evaluate its acceptability and efficacy in that field. The need for a dependable method to decontaminate housefly nesting materials as part of an overall ousefly (Musca domestica) system at hospitals sterilization is discussed. In this paper, we are using ozone gas as an alternative housefly pest and to remove house flies at hospitals, and we also illustrate data on the efficacy of ozone against the housefly (Musca domestica) and its effect on specific characteristics and properties of the treated zone application is currently attracting attention, particularly since. (a) There are no residues on the product. (b) There is no need for aeration to remove the gas. Green synthesis industrial applications and improvements in ozone technology together with new regulatory actions worldwide have emerged in last years, making it easier to use and applicable in a wide range - as the same with the pathogenic bacteria we are using ozone gas to control it, the numbers of bacterial cells remaining after ozone treatments were less than for untreated cells. The lowest dose of ozone gas for complete reduction of pathogenic bacteria was 0.125 g/m3 after 24 h of incubation.
Habitat type affects the diversity of dung beetle (Coleoptera: Scarabaeidae) assemblages in a neotropical mountainous region of Colombia
Authors: Salomão Renato Portela , Lopera-Toro Alejandro , Pulido-Herrera Luz Astrid , Arias-Buriticá Jorge Armando 
Published: April 2023

AbstractEcological communities of tropical regions respond to habitat configuration, being negatively affected by anthropogenic habitats. In the tropics, mountainous highland landscapes sustain ecological communities with contrasting responses to habitat transformation. This study assessed the effect of different habitats under different disturbance regimes on the dung beetle assemblage that inhabits a mountainous Andean landscape in Colombia. The habitat types surveyed were oak forest cores (low intervention), forest edges (medium intervention), and pastures (high intervention). A total of 3,810 dung beetles from ten species were collected. Dung beetle diversity was affected by habitat type, and forest cores and forest edges had higher diversity than pastures. Besides, each habitat type was characterized by a distinct dung beetle assemblage, with pastures showing the highest heterogeneity in the dung beetle assemblage. In conclusion, our study suggests that the dung beetles of a portion of Colombian Andean landscapes are sensitive to shifts of habitat quality. The higher dung beetle diversity in forested habitats indicates that pastures comprise limiting environments for their assemblages at this Andean region.
A nonenzymatic laser-induced flexible amperometric graphene electrode for glucose detection in saliva
Authors: Nugba Betty Edem , El-Moneim A. A. , Mousa Nahla O. , Osman Ahmed 
Published: April 2023

AbstractGraphene is a suitable transducer for wearable sensors because of its high conductivity, large specific surface area, flexibility, and other unique considerable features. Using a simple, fast galvanic pulse electrodeposition approach, a unique nonenzymatic glucose amperometric electrode was successfully developed based on well-distributed fine Cu nanoparticles anchored on the surface of 3D structure laser-induced graphene. The fabricated electrode allows glucose detection with a sensitivity of 2665 µA/mM/cm2, a response time of less than 5 s, a linear range of 0.03–4.5 mM, and a LOD of 0.023 µM. It also detects glucose selectively in the presence of interfering species such as ascorbic acid and urea. These provide the designed electrode the advantages for glucose sensing in saliva with 97% accuracy and present it among the best saliva-range non-enzymatic glucose sensors reported to date for real-life diagnostic applications.
A probabilistic multi-objective optimization mechanical design
Authors: Zheng Maosheng , Yu Jie 
Published: April 2023

AbstractOptimization design of machinery is usually a multi-objective one inevitably. At present, the popular mechanical optimization design is limited by the intrinsic shortcomings of the previous multi-objective optimization methods, which leads to the difficulty of non-comprehensive and nonsystematic optimal solutions in the viewpoint of probability theory. In the linear weighting “additive” method, there is inherent problems of normalization and introduction of subjective factors, and the final results depend on the normalization method to a great extent; the Pareto solution set is a “set” instead of an exact solution. In this paper, the probability—based multi-objective optimization, discretization with uniform design and sequential optimization are combined to establish a new approach of multi-objective optimization mechanical design based on probability theory; the probabilistic multi-objective optimization is used to transform the multi-objective optimization problem into single-objective optimization one from the perspective of probability theory; the discretization by means of uniform design provides an effective sampling to simplify the mathematical processing, which is especially important for dealing with multi-objective optimization problems with continuous objective functions; the sequential optimization algorithm is used to conduct the successive deep optimization. Furthermore, the implementation steps are illustrated with two examples. The results show that the approach can not only give excellent optimization results, but also provide a relatively simple processing.
Trends in regional inequalities in childhood anemia in Ethiopia: evidence from the 2005–2016 Ethiopian Demographic and Health Surveys
Authors: Negussie Shiferaw Tessema , Nigatu Regassa Geda 
Published: April 2023

Abstract
Introduction
Globally, 269 million children aged 6–59 months were anemic in 2019. Of these, 103 million anemic children were from Africa. Childhood anemia is still a serious public health concern in SSA countries, including Ethiopia. In Ethiopia, the prevalence of childhood anemia largely varies by geographic administration regions. This study is aimed to examine trends in regional inequalities in childhood anemia in Ethiopia over the period 2005–2016.

Method
This cross-sectional study was based on a pooled total sample of 17,766 children aged 6–59 months drawn from three rounds of the Ethiopian Demography and Health Surveys (2005–2016). We employed multilevel binary logistic regression analysis to identify the determinants of childhood anemia among children aged 6–59 months. We also used Theil and multivariate decomposition analyses to examine the levels and trends in relative regional inequalities in childhood anemia.

Result
A combination of individual-, household- and community-level factors were significantly (p < 001) associated with childhood anemia. From the pooled data, the highest childhood anemia was observed in Somali (78.68%) followed by Afar region (72.76%) while the lowest childhood anemia was in Amhara (41.01%), Addis Ababa (42.64%) and SNNPR (44%) between 2005 and 2016. The total relative inequality declined from 0.620 in 2005 to 0.548 in 2016. Overall, one-third of change in regional inequalities in childhood anemia was due to the differential resulted from the difference in observable characteristics of the subjects.

Conclusion
Overall progress made in Ethiopia was very slow with only a 13.14% reduction in the relative regional inequalities in childhood anemia over 11 years. The present study underscores addressing the existing disparities in socioeconomic status, maternal anemia and maternal employment status between emerging and non-emerging regions to reduce regional inequality in childhood anemia.
Machine Learning Driven Mental Stress Detection on Reddit Posts Using Natural Language Processing
Authors: Inamdar Shaunak , Chapekar Rishikesh , Gite Shilpa , Pradhan Biswajeet 
Published: April 2023

Abstract
People’s mental conditions are often reflected in their social media activity due to the internet's anonymity. Psychiatric issues are often detected through such activities and can be addressed in their early stages, potentially preventing the consequences of unattended mental disorders like depression and anxiety. In this paper, the authors have implemented machine learning models and used various embedding techniques to classify posts from the famous social media blog site Reddit as stressful and non-stressful. The dataset used contains user posts that can be analyzed to detect patterns in the social media activity of those diagnosed with mental disorders. This paper uses different NLP (Natural Language Processing) tools such as ELMo (Embeddings from Language Models) word embeddings, BERT (Bidirectional Encoder Representations from Transformers) tokenizers, and BoW (Bag of Words) approach to create word/sentence data that can be fed to machine learning models. The results of each method have been discussed. The results achieved a top F1 score of 0.76, a Precision score of 0.71, and a Recall of 0.74 using only the preprocessed texts and machine learning algorithms to classify the posts. The results achieved by this paper are significant and have the potential to be applied in real-world scenarios to analyze mental stress among social media users. Although this paper focuses on data from Reddit, the techniques used can be transferred to similar social media platforms and could help solve the growing mental health crisis.
How fast do we forget our past social interactions? Understanding memory retention with parametric decays in relational event models
Authors: Arena Giuseppe , Mulder Joris , Leenders Roger Th. A.J. 
Published: April 2023

AbstractIn relational event networks, endogenous statistics are used to summarize the past activity between actors. Typically, it is assumed that past events have equal weight on the social interaction rate in the (near) future regardless of the time that has transpired since observing them. Generally, it is unrealistic to assume that recently past events affect the current event rate to an equal degree as long-past events. Alternatively one may consider using a prespecified decay function with a prespecified rate of decay. A problem then is that the chosen decay function could be misspecified yielding biased results and incorrect conclusions. In this paper, we introduce three parametric weight decay functions (exponential, linear, and one-step) that can be embedded in a relational event model. A statistical method is presented to decide which memory decay function and memory parameter best fit the observed sequence of events. We present simulation studies that show the presence of bias in the estimates of effects of the statistics whenever the decay, as well as the memory parameter, are not properly estimated, and the ability to test different memory models against each other using the Bayes factor. Finally, we apply the methodology to two empirical case studies.
First records of two rays and three bony fishes for the Galapagos Islands
Authors: Mossbrucker Magdalena E. , Acuña-Marrero David , Cundy Megan E. , Fierro-Arcos Denisse , Suárez-Moncada Jenifer M. , Rastoin-Laplaine Etienne , Salinas-de-León Pelayo 
Published: April 2023

Abstract
The Galapagos Islands lie within the oceanic ecoregion of the Tropical Eastern Pacific, which has a unique fish assemblage composition due to the influence of several ocean currents and El Niño Southern Oscillation (ENSO) events. In the El Niño phase of these events, water temperature changes facilitate the movement of fish species between oceanic ecoregions, as well as across the Eastern Pacific Barrier. Here, we present five new fish records for the Galapagos Marine Reserve based on underwater imagery. These include two rays (Mobula thurstoni and Myliobatis longirostris) and three bony fishes (Lobotes pacifica, Lutjanus colorado and Sphyraena stellata). Of these, the first species is proposed as potentially resident to the Galapagos, and the latter four as vagrant species in the Galapagos until further sightings can conclusively determine their status. The effects of ENSO, the use of underwater video technology, and the importance of up-to-date and accurate species listings to understand the impact of the climate crisis are discussed.
Plasma mid-regional proadrenomedullin level in children with pulmonary hypertension associated with CHD
Authors: Elesawy Shimaa A. , El-Serogy Hesham A. , Sorour Esraa A. , Zoair Amr M. 
Published: April 2023

AbstractAdrenomedullin has been shown to inhibit proliferation in pulmonary artery smooth muscle cells and to alleviate pulmonary artery collagen accumulation in pulmonary hypertension. We aimed to assess mid-regional proadrenomedullin level in children with pulmonary hypertension due to CHDs. The current study was conducted in the Pediatric Cardiology Unit, Tanta University Hospital, on 50 children with CHDs: twenty-five patients had a complication of pulmonary hypertension and the other 25 patients without pulmonary hypertension. Another 25 children without CHDs were concluded as a control group. We performed complete history taking, full clinical assessment, chest X-ray, electrocardiogram, and echocardiographic assessment. Plasma level of mid-regional proadrenomedullin was assessed using a sandwich enzyme-linked immunosorbent assay test. Our results showed that the mean plasma level of mid-regional proadrenomedullin was significantly increased in patients with pulmonary hypertension. Significant positive correlation was found between mid-regional proadrenomedullin and mean pulmonary artery pressure. The best cut-off point of mid-regional proadrenomedullin as a diagnostic biomarker to discriminate patients with CHDs complicated with pulmonary hypertension was 199.22 nmol/l. Mid-regional proadrenomedullin significantly increased in patients with pulmonary hypertension who died as compared to patients who survived, with the best cut-off point was 428,8 nmol/l. We concluded that plasma levels of mid-regional proadrenomedullin were significantly elevated in children with pulmonary hypertension complicated by the CHDs. It could be used as a cardiac biomarker in these patients, with good diagnostic and prognostic value.
How Extreme Events in China Would Be Affected by Global Warming—Insights From a Bias‐Corrected CMIP6 Ensemble
Authors: Guo Junhong , Wang Xiuquan , Fan Yurui , Liang Xi , Jia Hongtao , Liu Lvliu 
Published: April 2023

AbstractIn recent years, concurrent climate extreme conditions (i.e., hot‐dry, cold‐dry, hot‐wet, and cold‐wet) have led to various unprecedented natural disasters (e.g., floods, landslide, wildfire, droughts, etc.), causing significant damages to human societies and ecosystems. This is especially true for China where many unprecedented natural disasters have been reported due to the recent warming in local climate. In this paper, we focus on the issue of ultra‐extreme events (1‰ threshold) and address how future global warming would affect the climate extreme conditions in China. Specifically, to reduce the uncertainties from models, we use a downscaled and bias‐corrected CMIP6 ensemble under two continuously‐warming scenarios to evaluate the impact of global warming on ultra‐extreme events over China. The results show that, under both SSP245 and SSP585 scenarios, extreme hot conditions would become dominant in most regions of China and some regions are likely to experience over 50 extreme hot days at future warming levels. The frequency of extreme cold events is projected to be small. More frequent extreme hot‐wet events with concurrence in the same month and year would be expected for China under the continuously‐warming scenarios. This is particularly obvious for the west where more than 6 hot‐wet months are likely to take place under future warming scenarios. This may imply that more extreme heat waves and flooding events would coincide in the same month or year for China in the future. For univariate ultra‐extreme events, both extreme hot events and extreme wet events would drop by above 25% from 2.0°C to 1.5°C global warming level, particularly under the SSP245 scenario. When the global mean temperature is limited to 1.5°C rather than 2°C, the avoided impacts of hot‐wet and cold‐wet extremes concurring in the same month will be larger than those of dry‐related compound extremes. Overall, the results suggest that slowing down global warming can reduce the frequency of concurrent climate extreme conditions in China, highlighting the importance of immediate action toward carbon emission reduction.
Spectroscopic Approach Toward Unraveling the Electrical Signature of Roots
Authors: Ehosioke Solomon , Garré Sarah , Huisman Johan Alexander , Zimmermann Egon , Placencia‐Gomez Edmundo , Javaux Mathieu , Nguyen Frédéric 
Published: April 2023

AbstractGeoelectrical methods are increasingly used to investigate soil‐plant interactions in an agricultural context. For this, it is essential to quantify root electrical properties, since they influence the bulk electrical signal of vegetated soil. This quantification has to be done at the root segment scale with attention for the variability of root properties in time and space as well as within and across plant species. In this study, we investigated the frequency‐dependent electrical properties in terms of conduction and polarization of single root segments of Brachypodium (Brachypodium distachyon L.) and Maize (Zea mays L.). A sample holder to investigate the electrical properties of root segments was designed and tested on ideal resistors. We found that it is suitable to assess the electrical properties of crop root segments of 1–5‐cm length in a frequency range between 1 Hz and 45 kHz. The system was then used to obtain the complex electrical response of Brachypodium and Maize root segments at 10 different ages. It was found that the electrical properties of the root segments varied with age and species. This variation was linked to root anatomy based on the microscopic analysis of root sections.
Opening the Black Box of the Radiation Belt Machine Learning Model
Authors: Ma Donglai , Bortnik Jacob , Chu Xiangning , Claudepierre Seth G. , Ma Qianli , Kellerman Adam 
Published: April 2023

AbstractMany Machine Learning (ML) systems, especially deep neural networks, are fundamentally regarded as black boxes since it is difficult to fully grasp how they function once they have been trained. Here, we tackle the issue of the interpretability of a high‐accuracy ML model created to model the flux of Earth's radiation belt electrons. The Outer RadIation belt Electron Neural net (ORIENT) model uses only solar wind conditions and geomagnetic indices as input features. Using the Deep SHAPley additive explanations (DeepSHAP) method, for the first time, we show that the “black box” ORIENT model can be successfully explained. Two significant electron flux enhancement events observed by Van Allen Probes during the storm interval of 17–18 March 2013 and non‐storm interval of 19–20 September 2013 are investigated using the DeepSHAP method. The results show that the feature importance calculated from the purely data‐driven ORIENT model identifies physically meaningful behavior consistent with current physical understanding. This work not only demonstrates that the physics of the radiation belt was captured in the training of our previous model, but that this method can also be applied generally to other similar models to better explain the results and to potentially discover new physical mechanisms.
Programmable microfluidics for dynamic multiband camouflage
Authors: Feng Chunzao , Mao Mingran , Zhang Xiaohui , Liao Yutian , Xiao Xiaohui , Liu Huidong , Liu Kang 
Published: April 2023

AbstractAchieving multiband camouflage covering both visible and infrared regions is challenging due to the broad bandwidth and differentiated regulation demand in diverse regions. In this work, we propose a programmable microfluidic strategy that uses dye molecules in layered fluids to manipulate visible light- and infrared-semitransparent solvent to manipulate infrared light. With three primary fluid inputs, we achieve 64 chromaticity values and 8 emissivities from 0.42 to 0.90. In view of the wide tuning range, we demonstrate that the microfluidic film can dynamically change its surface reflectance to blend into varying backgrounds in both visible and infrared images. Moreover, we fabricate the microfluidic device in a textile form and demonstrate its ability to match exactly with the colors of natural leaves of different seasons in the full hyperspectrum range. Considering the broadband modulation and ease of operation, the programmable microfluidic strategy provides a feasible approach for smart optical surfaces in long-span optical spectra.
Temperament & Character account for brain functional connectivity at rest: A diathesis-stress model of functional dysregulation in psychosis
Authors: Zwir Igor , Arnedo Javier , Mesa Alberto , del Val Coral , de Erausquin Gabriel A. , Cloninger C. Robert 
Published: April 2023

AbstractThe human brain’s resting-state functional connectivity (rsFC) provides stable trait-like measures of differences in the perceptual, cognitive, emotional, and social functioning of individuals. The rsFC of the prefrontal cortex is hypothesized to mediate a person’s rational self-government, as is also measured by personality, so we tested whether its connectivity networks account for vulnerability to psychosis and related personality configurations. Young adults were recruited as outpatients or controls from the same communities around psychiatric clinics. Healthy controls (n = 30) and clinically stable outpatients with bipolar disorder (n = 35) or schizophrenia (n = 27) were diagnosed by structured interviews, and then were assessed with standardized protocols of the Human Connectome Project. Data-driven clustering identified five groups of patients with distinct patterns of rsFC regardless of diagnosis. These groups were distinguished by rsFC networks that regulate specific biopsychosocial aspects of psychosis: sensory hypersensitivity, negative emotional balance, impaired attentional control, avolition, and social mistrust. The rsFc group differences were validated by independent measures of white matter microstructure, personality, and clinical features not used to identify the subjects. We confirmed that each connectivity group was organized by differential collaborative interactions among six prefrontal and eight other automatically-coactivated networks. The temperament and character traits of the members of these groups strongly accounted for the differences in rsFC between groups, indicating that configurations of rsFC are internal representations of personality organization. These representations involve weakly self-regulated emotional drives of fear, irrational desire, and mistrust, which predispose to psychopathology. However, stable outpatients with different diagnoses (bipolar or schizophrenic psychoses) were highly similar in rsFC and personality. This supports a diathesis-stress model in which different complex adaptive systems regulate predisposition (which is similar in stable outpatients despite diagnosis) and stress-induced clinical dysfunction (which differs by diagnosis).