bluuebunny/crossref_metadata_2025_split huggingface dataset:
Why has ‘miracidium’ of Notocotylidae (Trematoda: Digenea) lost all stage-specific traits?
Authors: Smirnov Peter A. , Gonchar Anna 
Published: February 2024

Abstract
Digeneans of Notocotylidae family stand out of the range with their peculiar eggs. The eggs feature a pair of long filaments extending from their poles, and their content differs significantly from what we expect to observe in the eggs of digeneans. Instead of a ciliated larva miracidium, the egg of Notocotylidae contains a tiny few-celled mother sporocyst. This sporocyst infects a snail host following accidental ingestion of the egg. Previous transmission electron microscope studies elucidated the structure of the sporocyst and proposed a mechanism of the injection relying on the structure called opercular cord, but the data were insufficient to describe certain details. Here we present ultrastructural data on the egg of Paramonostomum sp., clarifying the nature of the injection apparatus and providing the missing details of the in-egg mother sporocyst structure. We found the opercular cord to be part of the eggshell associated with the vitelline membrane. We also elucidated the intertwining connection between the germ cells and the sporocyst’s tegument, and explored nuage granules present in the cytoplasm of the germ cells, providing evidence for identification of these cells as the germ ones. We discuss our findings in the context of transition of miracidia to a passive strategy of snail infection.
Early Childhood General Anesthesia and Intellectual Disability: A Pediatric Cohort Study
Authors: Sun Mingyang , Chen Wan-Ming , Wu Szu-Yuan , Zhang Jiaqiang 
Published: February 2024

Abstract
Background: The neurotoxicity of general anesthesia (GA) on the developing human brain is a topic of ongoing debate. In this study, we aimed to assess the association between GA exposure before the age of 3 and the risk of intellectual disability (ID).
Methods:We enrolled individuals aged 0 to 3 years who underwent GA and were hospitalized for more than one day in Taiwan between January 2004 and December 2014. The study's final follow-up date was December 31, 2021.
Results:Using propensity score matching, we identified 15,036 infants and toddlers (7,518 in the GA group and 7,518 in the no GA group). Cox regression analysis showed that the adjusted hazard ratio (aHR) for ID in the GA group was 2.38 (95% confidence interval [CI]: 1.94-2.91) compared to the no GA group. Children who underwent GA once and more than once had aHRs of ID of 1.98 (95% CI: 1.03-2.64) and 2.86 (95% CI: 1.52-3.11), respectively. The aHRs of ID for children who received GA for less than 3 hours and 3 hours or more were 1.86 (95% CI: 1.13-1.98) and 2.77 (95% CI: 1.44-2.92), respectively. The IRs of ID for the no GA group and GA group were 15.34 and 36.05 per 10,000 person-years, respectively.
Conclusions: Our findings suggest that GA exposure before the age of 3 is associated with an increased risk of ID. Furthermore, age at first GA, duration of GA, and number of GA exposures are all significant risk factors for ID.
Running Head: ID Risk in Children after GA
Polynomial quantum computing algorithms for solving the dualization problem for positive Boolean functions
Authors: Mezzini Mauro , Gomez Fernando Cuartero , Gonzalez Jose Javier Paulet , Calvo Hernan Indibil de la Cruz , Pascual Vicente , Pelayo Fernando L. 
Published: February 2024

Abstract

In this paper, we present quantum computing algorithms for solving the dualization problem in polynomial time with respect to the asymptotic dimensions of the positive irredundant Disjunctive Normal Form. Furthermore, we give a quantum annealing algorithm for solving the dualization problem using a quantum annealer. Moreover, we reduce the dualization problem to the problem of counting all the hitting sets of a hypergraph
Design Study of a Camera System for Earth Observation as a Payload on the Small Satellite Romeo
Authors: Starzmann Dominik , Loeffler Thorben , Petri Jona , Bargiel Damian , Eidmann David , Denk Michael , Conrad Christopher , Klinkner Sabine 
Published: February 2024

Abstract

The importance of a safe food supply has increased due to climate change and its consequences. The number and severity of floods, droughts and plant diseases are rising which causes massive crop failures. Early and precise detection of plant diseases can lower crop failures as it enables early containment. Moreover, it promotes the targeted use of pesticides to protect the biodiversity. Satellite sensors improve the detection of plant diseases by enabling frequent and extensive vegetation observation. Hence, we present the design of a camera system for Earth observation on small satellites with a focus on the detection of plant diseases. The disease detection of sugar beets was chosen as the primary objective due to their importance for the German agriculture. This work is divided into two parts. First, the spectra of sugar beets are analyzed to determine spectral channels for a camera system. Second, a camera system is defined to capture spectral information within the previously defined wavelength ranges. The spectra of healthy and diseased sugar beets were measured in fields for agricultural research in Central Germany using a portable spectroradiometer. The investigated diseases are Cercospora leaf spot and virus yellows, which are among the most important pathogens worldwide. Based on the measured data, the so-called Normalized Difference Sugar Beet Index (NDSBI) is defined, which is a custom index to detect these diseases. We can prove that this index enables more precise detection of these sugar beet diseases than existing indices like the Normalized Difference Vegetation Index (NDVI). The camera system is designed as a payload for the small satellite Research and Observation in Medium Earth Orbit (ROMEO), which is being developed at the University of Stuttgart’s (US) Institute of Space Systems (IRS). The proposed design fulfills the high radiation requirements as well as the system constraints of mass and volume. Three different options for the camera system are developed: two designs for the development at the US, one with lens optics and one with mirror optics, and an adjusted commercial camera system. All defined camera systems permit the measurement of the NDSBI to precisely detect sugar beet diseases.
Prediction of rubber fatigue life using an assimilation-based learning approach and incremental crack propagation model
Authors: Fang Congzhuo , Chen Yanfu , Yang Zihao , Zhang Yiyuan , He Xindang 
Published: February 2024

Abstract
Accurately and efficiently predicting the fatigue life of rubber materials has beena long-standing challenge due to limited understanding of the fatigue mechanism.In this study, a variational assimilation-based machine learning method assistedwith incremental crack propagation model is proposed to predict the fatigue lifeof rubber materials. Firstly, according to the fracture mechanics theory, a newrubber fatigue life prediction model based on incremental crack propagation andsparse experimental data is established, which owns higher accuracy than theclassical crack energy density model. Further, a rubber fatigue life solver coupled incremental crack propagation model and nonlinear finite element method isintroduced to generate a dense fatigue life dataset of rubber materials with highaccuracy. Finally, the artificial neural network model is trained, cross-validatedand tested using the dense dataset, and the three-dimensional variational assimilation model is employed to merge the predicted values of artificial neural networkwith experimental data. By comparing against the experimental data, the effectiveness of the proposed method was verified, thereby we offer an accurate andefficient approach to predict the rubber fatigue life.
Innovative Engine Test Bench Setup for Testing of Exhaust Gas Aftertreatment and detailed Gas Species Analysis for CNG-SI-Operation
Authors: Tomin Sebastian , Keller Kevin , Wagner Uwe , Lott Patrick , Koch Thomas , Deutschmann Olaf 
Published: February 2024

Abstract
For an efficient reduction of methane slip, a precise understanding of exhaust gas aftertreatment under real conditions is essential. Since it is not possible to produce catalytic converters in near-series geometry on a laboratory scale, it is necessary to resort to significantly smaller sample catalysts. Therefore, an engine test bench was designed to ensure real operating conditions for such samples with the help of space velocity and temperature control. A comparison between the actual and reference values of the space velocity results in a small deviation of 0.1% on average. Furthermore, the pressure conditions at the catalyst have been measured showing a propagation of pressure oscillations from the engine outlet which in combination with the space velocity regulation show that real conditions could be applied to the catalyst sample. Subsequently the exhaust gas concentrations were monitored with a Fourier transform infrared spectrometer. The catalyst material used is Pd on Al2O3 common for methane oxidation. The measurements show that the CH4 conversion is higher under lean conditions, but is below complete conversion. In a final comparison between purely stoichiometric operation and dithering, the course of the CH4 conversion rate over the test period is examined more closely. In addition to sampling pre- and post-catalyst, the exhaust gas composition is measured spatially resolved within a catalyst channel using special measurement technology. In the temporal course of the CH4 emissions, a stabilising effect due to the change of the operating mode can be seen showing that dithering seems to prevent further deactivation.
Intelligent Feature Engineering Based Intrusion
Detection System for IoT Network Security
Authors: Sadhwani Sapna , Sriwast Asmi , Muthalagu Raja , Pawar Pranav M 
Published: February 2024

Abstract

Internet-of-Things (IoT) helps create smart systems by allowing physical environments to be controlled or monitored by users through extensive sensor networks. Such networks are heavily resource constrained due to the low processing power and decentralized placement of sensors. Having been implemented in several backbone sectors such as industry, healthcare, etc, they often deal with sensitive information. Thus, there is an imminent need to secure IoT networks using lightweight intrusion detection systems. To this end, existing works that use BiLSTM for network intrusion detection are explored. Experiments involving the UNSW-NB15 dataset are recreated, and the results are compared. Early stopping is implemented to improve model performance and enable better analysis of the results. Finally, a novel machine learning and feature engineering-based intelligent network intrusion detection framework, dubbed FEIIDS, is proposed. Its working is explained in depth and its time complexity is analyzed. It is tested on the UNSW-NB15 dataset and found to be competitive with existing works, achieving classification accuracies up to 98.8%. Discussions on the results reveal that FEIIDS is more stable, transparent, and lightweight than deep learning models. In fact, FEIIDS can process 2,032,038 records of the dataset in 280.44 seconds, whereas BiLSTM requires 1901.2 seconds to process just 14,000 records. A case study on FEIIDS’s real-world application is also presented. Finally, it is concluded that FEIIDS is highly suitable for use as a real-time intrusion detection system in resource-constrained IoT networks, and its possible future applications are listed.
Leishmania infantum (Trypanosomatida: Trypanosomatidae) detection in Nyssomyia neivai (Diptera: Psychodidae) and dogs in Southern Brazil
Authors: Cardoso Sabrina Fernandes , Guesser João Victor Costa , Rodrigues Andressa Alencastre Fuzari , Brazil Reginaldo Peçanha , Rona Luísa Damazio Pitaluga , Pitaluga André Nóbrega 
Published: February 2024

Abstract
Background
The sand fly Nyssomyia neivai is one of the most abundant species in Southern Brazil. It has been frequently found in visceral leishmaniasis foci in Santa Catarina (Brazil), a region where Lutzomyia longipalpis, the main vector of Leishmania infantum and the etiological agent of visceral leishmaniasis in the Americas, has not been identified. In the absence of the main Leishmania vector, this study aimed to identify the sand fly fauna and diagnose any potential Leishmania spp. infection in sand flies and dogs in a region with a recent canine visceral leishmaniasis outbreak in the South of Brazil.
Methods
We report here a sand fly fauna survey on the Zoonosis Control Center of Tubarão Municipality (Santa Catarina, Brazil). We also conducted molecular testing to detect Leishmania spp. natural infection on captured sand flies using polymerase chain reaction (PCR). In positive females, in addition to morphological identification, molecular analysis through DNA barcoding was performed to determine the sand fly species. Additionally, the dogs were tested for the presence of Leishmania spp. using a non-invasive technique for the collection of biological material, followed by PCR.
Results
We collected 3,419 specimens from five sand flies genera. Nyssomyia neivai (85.75%) was the most abundant species, followed by Migonemyia migonei (13.31%), Pintomyia fischeri (0.82%), Evandromyia edwardsi (0.03%), and the genus Brumptomyia spp. (0.09%). Leishmania infantum DNA was detected in two of the 509 analyzed females, yielding a natural infection rate of 0.4%. The L. infantum infected sand flies’ specimens were morphologically and molecularly identified as Ny. neivai. We analyzed 47 dogs’ conjunctival swabs for Leishmania spp. with two positive individuals for L. infantum (infection rate of 4.2%).
Conclusions
Our results confirm the presence of Ny. neivai naturally infected with L. infantum in an area where dogs were also infected by the parasite, suggesting its potential role as a vector in Southern Brazil. We emphasize the significance of DNA barcoding in supporting the sand flies’ identification, and the conjunctival swab technique proved effective in obtaining enough biological material for detecting L. infantum in dogs.
Impact of Earliness, Flowering Time and Plant Design on Late Sown Cotton Production
Authors: Khan Muhammad Rizwan Jamil , Ullah Kalim , Khan Muhammad Mohibullah , Khan Rashid 
Published: February 2024

Abstract
Extremely diversified cropping environments prevails in most of the cotton growing areas of the country due to the prevailing rainfed conditions and thus cotton is cultivated over a prolonged period. This study examined the production and growth pattern of 8 cotton genotypes to find out the most effective strategies that could be transformed into breeding traits. Four experiments were conducted in 2018 and 2019 at two locations in Dera Ismail Khan to associate the 8 genotypes at 3 planting densities and two sowing dates. Various attributes like days to 1st flower opening, affective time of flowering, monopodial branches per plant, height of plant at the time of harvesting, ratio of height to node length of fruiting branch and average number of bolls retained at the 1st site of fruiting branch were investigated. Results revealed two ideotypes which performed better than the others. Genotype CIM-632 yielded better in late sowing-high plant density and regarded as by less growth of vegetative branches and early start of flowering, short flowering duration and less bolls retained at the 1st position of sympodia. Genotype CIM-663 and CIM-343 performed outstandingly in early sowing-low plant density and regarded by more growth of vegetative branches, delayed flowering, lengthy flowering duration and more bolls retained at 1st position. Based on these attributes, a breeding scheme for these ideotypes is proposed with high heritability for flower opening, height of plant at the time of harvesting, ratio of height to node and fruiting branch length and medium heritability for monopodial branches, effective flowering time and bolls retained at 1st position of sympodia (fruit branch).
GIS-based Hotspot Assessment of Solar Energy Potentials: African Countries Clustering
Authors: Gwani Alhaji Abdullahi , Sek Siok Kun , Gwani Alhaji Abdullahi 
Published: February 2024

Abstract

This study introduces an approach to quantify solar energy potential and identify hotspot areas; cluster map the solar energy high potential countries in Africa for sustainable development of solar PV technology-based power using GIS spatial analysis. The research integrated geographical GHI, and DNI data, and other geospatial information to evaluate the total solar potential in the African region. The results revealed that Africa, with a total land area of 3.41X107 km2, was found to have substantial potential as high of SEGHI at 7.41X1010 kWh, and SEDNI at 2.72X109 kWh. These results affirm Africa's solar energy potential as a valuable resource to address energy demands, foster economic growth, and reduce greenhouse gas emissions. Additionally, Moran’s I was employed to analyses autocorrelation in countries' solar energy resources, revealing spatial patterns. Wealthy solar energy clusters were identified around countries such as Algeria, Chad, South Africa, Niger, Nigeria, Egypt, Sudan, Ethiopia, Central African Republic, South Sudan, and Libya. The study emphasizes the significance of harnessing solar energy to meet Africa's increasing demand for clean and sustainable energy sources. It provides a GIS analysis of Africa's solar energy potential, estimating the sky-available solar energy. This research offers invaluable insights for engineers, technologists, policymakers, investors, and energy planners by detailing the solar energy potential in various African regions and identifying the wealthiest solar energy clusters. This research supports the promotion of solar energy adoption and the utilization of abundant, untapped solar resources, contributing to a cleaner and more sustainable energy landscape in Africa. The implementation of solar photovoltaic systems in the continent presents a substantial economic opportunity, due to its environmental benefits and relative advantages compared to alternative energy generation methods.
Epidemiology of necrotizing enterocolities and its predictors among preterm newborns in Ethiopia: a systematic review protocol
Authors: Mersha Abera , Awoke Nefsu , Shibiru Shitaye 
Published: February 2024

Abstract
Background
Necrotizing enterocolitis is a serious intestinal inflammation that can lead to tissue death in premature infants. It is most common in infants born before 37 weeks of pregnancy. Globally, a significant number of premature babies affected by this problem with the great variation across countries due to different factors. Evidence on the epidemiology and predictors of necrotizing enterocolitis is essential for policymakers and program planners to improve prevention and treatment strategies. Therefore, this systematic review aims to evaluate the epidemiology of necrotizing enterocolitis and its predictors among preterm newborns in Ethiopia.
Methods
This systematic review will search for and extract data from the JBI Database, Cochrane Database, MEDLINE, CINAHL, EMBASE, PEDro, POPLINE, Proquest, OpenGrey (SIGLE), Google Scholar, Google, APA PsycInfo, Web of Science, Scopus, and HINARI. Unpublished studies and grey literature will also be searched from different sources. The review will include quantitative observational studies and experimental studies that report on the prevalence or incidence of necrotizing enterocolitis in Ethiopia from January 1, 1990 to September 30, 2023. The Newcastle–Ottawa Quality Assessment Scale will be used to select eligible studies. Two researchers will independently assess the quality of the included studies and extract the data. They will resolve any discrepancies through discussion. Heterogeneity, or variation between the studies, will be assessed using forest plots and the I2 statistic. If there is a lot of heterogeneity, a random-effects model will be used to pool the data. Subgroup analysis will be used to explore the possible sources of this heterogeneity. Publication bias, or the tendency for studies with positive results to be more likely to be published, will be assessed using funnel plots and Egger's regression test. The statistical software package STATA version 17 will be used to conduct the meta-analysis. An association will be considered statistically significant if the p-value is less than 0.05.
Discussion
Necrotizing enterocolitis is a significant problem in Ethiopia that affects premature newborns and can have severe consequences. More recent systematic reviews are needed to develop effective prevention and treatment strategies.
Systematic review registration number in PROSPERO:
CRD42023459199
Biosynthesis of Lactic Acid by Mutagenetic Lactic Acid Bacteria Strains Isolated From Processed Milk
Authors: OSHO Michael Bamitale , AWOSILE Precious Jesuferanmi , ALABA Gbemisola Mary 
Published: February 2024

Abstract

Lactic acid, a valuable weak natural organic acid extensively utilized in various industries has been conventionally synthesized through chemical processes. However, the growing demand for sustainable and eco-friendly production methods has stimulated interest in microbial synthesis. The study was to explore the potential of multi-strain lactic acid bacteria isolated from processed liquid milk to synthesize lactic acid. Microorganisms were isolated and screened on deMan Rogosa Sharpe (MRS) agar and were identified according to morphological and biochemical characteristics. Mutagenesis of positive isolate using chemical and physical means, quantitative and qualitative production using High-Performance Liquid Chromatography (HPLC) were investigated. The isolate was discovered to have a clear zone on MRS agar, which allowed for its identification as Lactobacillus sp. It was then chosen for mutagenesis using ethidium bromide (EB) and UV light. Thirteen mutants were identified, and three of those were examined to see if they could generate lactic acid using various substrates. HPLC confirmed mutants and parent strain to produce significant homo-fermentative lactic acid in cheese whey substrate. The parent strain gave a significant yield of 2004.87ugml-1 as compared to UV and EB mutant strains with 1457.67ugml-1 and 239.10ugml-1 respectively. Optimum lactic acid yields were produced at 37°C, pH 4.5, and 150 rpm 16 h fermentation period. This study showed that mutagenesis did not influence optimum lactic acid production. The yield improvement that occurred via mutations might have diverted the metabolism from lactic acid production towards mixed acid fermentation, hence produce reduced levels of lactic acid.