jimnoneill/paper-to-field-training huggingface dataset:
Learning About Sexuality ‘Between’ Home and School

Field: Social Sciences (Social Sciences)

This chapter is concerned with understanding how young people live religion, culture, and sexuality between home and school. It describes how Chana, a 16-year-old Muslim woman, makes sense of meanings about sexuality from her African family and school-based sexuality education. The chapter rethinks dominant framings of this experience, where youth from religious and cultural minorities are caught between conflicting sexual ideologies from home and school. Instead of reinscribing this scene, its terms of reference are shifted by drawing on Barad's (Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning, Duke University Press, 2007) notion of intra-activity to understand it in an ontologically different way. In an attempt at 'exorbitant deconstruction' (Lenz Taguchi, Reconceptualizing Educational Research Methodology, 1(1), 41–53, 2010), the idea that meanings from home and school are necessarily oppositional and something Chana must reconcile/negotiate is unravelled, opening space for new ways of thinking.
Multigene‐based phylogeny analyses of the controversial family Condylostomatidae (Ciliophora, Heterotrichea)

Field: Agricultural and Biological Sciences (Life Sciences)

Abstract Condylostoma , the type genus of the family Condylostomatidae, is a well‐known and taxonomically confusing genus with more than 30 nominal species. The phylogenetic relationships among congeners and related genera remain obscure despite the continuous discovery of new species and detailed redescription of known species over the past decades. Based on a total of 24 new sequences obtained from nine Condylostoma isolates, we conducted phylogenetic analyses by combining multiple marker genes. The molecular phylogenetic trees indicate that: (a) the monophyly of the family Condylostomatidae is supported by the rDNA locus and SSU rDNA sequences with high support value but is no longer sustained by both the ITS1‐5.8S‐ITS2 and LSU rDNA sequences; (b) Condylostoma is very likely a paraphyletic genus, and the possibility that it is a polyphyletic group cannot be denied, and (c) the genera Condylostentor and Chattonidium are suggested to evolve from a radiation of Condylostoma species. Furthermore, in an effort to provide better resolutions for understanding the evolutionary relationships of condylostomatids, the secondary structures of the variable regions 2 and 4 (V2 and V4) of SSU rDNA and ITS2 transcripts are predicted. The results revealed that the V2 and V4 structures are rather conserved at the genus level, while the ITS2 structures are much more variable.
[Mechanical ventilation: modern technics and respirators].

Field: Medicine (Health Sciences)

The techniques of ventilatory support have been improved during the last few years by two series of modifications: first, the introduction of the trigger and the IMV allows and stimulates greater participation of the patient in the regulation and work of respiration; second, higher levels of PEEP and CPAP produce an improvement in pulmonary gas exchange. The development and perfecting of these techniques has not increased the cost of modern ventilators. This article considers some of the advantages and shortcomings of a number of recent models.
Influence of the Phenological Stage and Harvest Date on the Bioactive Compounds Content of Green Pepper Fruit

Field: Agricultural and Biological Sciences (Life Sciences)

Green pepper fruit is often consumed before it is completely ripe. However, the influence of the phenological stage in which the green pepper is consumed as a potential influencing factor in its bioactive compounds content and antioxidant capacity remains unknown. In addition, no literature is available concerning the bioactive compounds changes in ‘Lamuyo’ green peppers along its developmental and growth cycle. For this, two different approaches have been carried out, one using twelve different phenological stages (S1 to S12), and in the other, seven different harvest dates (from 27 February to 20 April). Moreover, bioactive compounds changes during 21 days of postharvest storage at 8 °C were investigated. In this study, bioactive compounds (ascorbic acid, dehydroascorbic acid, and total phenolic content) and the total hydrophilic and lipophilic (TAA-H and TAA-L) antioxidant activity were analysed. In addition, total soluble solids, total acidity, individual sugars, and organic acids were determined. Vitamin C levels increased along the phenological stages and harvest dates due to significant increases in ascorbic and dehydroascorbic acid levels. Our results show that the total phenol content decreases as vegetables develop and subsequently increases both as ripening begins and by the last harvest date. Furthermore, TAA-H was also greater by the phenological stage S12 and the 20 April harvest date. In conclusion, the phenological stage and harvest date are key factors that significantly influence the bioactive compounds of green peppers, and those that appear by S12 and 20 April could be more beneficial to health.
Automatic Image Annotation Based on Deep Learning Models: A Systematic Review and Future Challenges

Field: Computer Science (Physical Sciences)

Recently, much attention has been given to image annotation due to the massive increase in image data volume. One of the image retrieval methods which guarantees the retrieval of images in the same way as texts are automatic image annotation (AIA). Consequently, numerous studies have been conducted on AIA, particularly on the classification-based and probabilistic modeling techniques. Several image annotation techniques that performed reasonably on standard datasets have been developed over the last decade. In this paper, a review of the image annotation method was conducted, focusing more on deep learning models. Automatic image annotation (AIA) methods were also classified into five categories, including i) Convolutional Neural Network (CNN) based on AIA, ii) Recurrent Neural Network (RNN) based on AIA, iii) Deep Neural Networks (DNN) based on AIA, iv) Long-Short-Term Memory (LSTM) based on AIA, and v) Stacked auto-encoder (SAE) based on AIA. An assessment of the five varieties of AIA methods was also offered based on their principal notion, feature mining technique, explanation precision, computational density, and examined aggregated data. Moreover, the evaluation metrics used to evaluate AIA methods were reviewed and discussed. The need for careful consideration of methods throughout the improvement of novel procedures and datasets for image annotation assignment was highly demanded. From the analysis of the achievements so far, it is certain that more attention should be paid to automatic image annotation.
Abundance and Parasitic Load of Housefly (Musca Domestica) in Amansea Area of Anambra State, Nigeria

Field: Agricultural and Biological Sciences (Life Sciences)

Houseflies (Musca domestica) are major transmitters of pathogenic organisms to humans worldwide. This study was carried out to determine the relative abundance of housefly and its parasitic load in four different sites in the Amansea area of Anambra state, Nigeria. The housefly samples were collected with the aid of fly trap and sweep net and analyzed using sedimentation methods. Data obtained was calculated and expressed as simple percentages while chi-square was used to test for differences in prevalence rates of parasites in the study areas. Out of the 259 houseflies examined, 74 were infested with a prevalence of 28.57%. Houseflies were more abundant in the abattoir 92(35.52) followed by market area 71(27.41%), refuse dump sites (19.69%) while holy family hostels recorded the lowest abundance (17.37) (P=0.000). Houseflies infested with parasites were mostly found in holy family hostel 31(68.89) while the market area had the least infested house flies 5(7.04%). Two protozoan parasites (Entamoeba histolytica and Entamoeba coli) and two nematodes (Strongyloides stercoralis and Ascaris lumbricoides) were the parasites seen from the microscopic examination of samples. E. histolytica (7.61%) and E. coli (5.43%) were the parasites seen in Abattoir while S. stercoralis (7.04%) was the only parasite in the market area. E. histolytica (17.78%) and A. lumbricoides (51.11%) were seen in holy family hostel while E. coli (11.76%), S. stercoralis (7.84%) and A. lumbricoides (31.37%) were the parasites recovered from the houseflies in the Refuse dump site. The infestation of houseflies in the area is a threat to human health due to their ability to act as mechanical vectors for transmission of infectious pathogens. Hence, proper disposal and prompt removal of waste by environmental officers should be prioritized in the area as well as mass education of the public on the health implications of poor hygiene and poor sanitary practices.
Photocarrier injection and photo-resistance in SrTiO

Field: Materials Science (Physical Sciences)

\n\nHeterojunctions composed of n-type oxygen-deficient SrTiO3−δ and p-type GaAs were fabricated using pulsed laser deposition method. The good crystallinity of SrTiO3−δ was confirmed by X-ray diffraction, reflection high-energy electron diffraction, and transmission electron microscopy. These heterojunctions exhibited excellent rectifying behavior from 40 K to room temperature. The photocarrier injection effect and a large photo-resistance were observed in a wide temperature range. The photo-resistance is nearly 100% at low temperatures and ∼40% at room temperature under −0.5 V bias. Strong dependences on both temperature and bias voltage were found as well, which might be understood by considering the band structure of the formed p-n junction.\n
Recovery from water stress in laurel plants: influence of short term potassium fertilization

Field: Agricultural and Biological Sciences (Life Sciences)

Plant xylem hydraulic conductance varies with changes in sap solute concentrations, particularly potassium, a phenomenon known as 'ionic effect'. In well-watered Laurus nobilis plants, short term potassium fertilization increased xylem sap potassium concentration, resulting in an increase in plant hydraulic conductance (Kplant), leaf-specific conductivity of the shoot (kshoot) and transpiration rate (Eplant). The ionic effect is enhanced in embolized stems, where it can compensate the cavitation-induced loss of hydraulic conductance. The aim of this work was to test if water-stressed potassium-starved laurel plants could recover earlier from stress when irrigated with a potassium solution instead of water. Two-year-old potted laurel seedlings, grown under potassium-starved conditions, were subjected to water stress by suspending irrigation until leaf conductance to water vapor (gL) dropped to less than 50% of its initial value and leaf water potential (YL) reached turgor loss point (YTLP). Plants were then irrigated either with water or 25 mM KCl and measurements were taken at 3, 6 or 24 hours after irrigation. No significant differences were found between the two groups of plants in terms of YL, gL, Eplant, Kplant or kshoot. Analysis of xylem sap potassium concentration showed there were no significant differences between treatments, and potassium levels were similar to those of potassium-starved well-watered plants. In conclusion, potassium uptake or release to xylem appeared to be impaired at least up to 24 hours after relief from water stress, so fertilization after the onset of stress did not result in any short term advantage for recovery from drought stress.
EUMerger Policy

Field: Social Sciences (Social Sciences)

Abstract The development of the regulatory control of mergers in the EU is presented in this article. The primary legal foundation, the 2004 EC Merger Regulation, is examined along with the reorganization of the EU's merger control unit and its procedures. The new standard for evaluating a proposed merger, which is the likelihood of the merger significantly impeding effective competition, is discussed along with some of its applications. Parallels and areas of continued divergence with US merger policy are also presented.
The role of the microbiome in the neurobiology of social behaviour

Field: Neuroscience (Life Sciences)

ABSTRACT Microbes colonise all multicellular life, and the gut microbiome has been shown to influence a range of host physiological and behavioural phenotypes. One of the most intriguing and least understood of these influences lies in the domain of the microbiome's interactions with host social behaviour, with new evidence revealing that the gut microbiome makes important contributions to animal sociality. However, little is known about the biological processes through which the microbiome might influence host social behaviour. Here, we synthesise evidence of the gut microbiome's interactions with various aspects of host sociality, including sociability, social cognition, social stress, and autism. We discuss evidence of microbial associations with the most likely physiological mediators of animal social interaction. These include the structure and function of regions of the ‘social' brain (the amygdala, the prefrontal cortex, and the hippocampus) and the regulation of ‘social’ signalling molecules (glucocorticoids including corticosterone and cortisol, sex hormones including testosterone, oestrogens, and progestogens, neuropeptide hormones such as oxytocin and arginine vasopressin, and monoamine neurotransmitters such as serotonin and dopamine). We also discuss microbiome‐associated host genetic and epigenetic processes relevant to social behaviour. We then review research on microbial interactions with olfaction in insects and mammals, which contribute to social signalling and communication. Following these discussions, we examine evidence of microbial associations with emotion and social behaviour in humans, focussing on psychobiotic studies, microbe–depression correlations, early human development, autism, and issues of statistical power, replication, and causality. We analyse how the putative physiological mediators of the microbiome–sociality connection may be investigated, and discuss issues relating to the interpretation of results. We also suggest that other candidate molecules should be studied, insofar as they exert effects on social behaviour and are known to interact with the microbiome. Finally, we consider different models of the sequence of microbial effects on host physiological development, and how these may contribute to host social behaviour.
Study on Kerberos protocol based on fuzzy control

Field: Computer Science (Physical Sciences)

In order to prevent password attack and replay attack existing in Kerberos protocol, the traditional method was to make use of encryption techniques and authentication techniques on enhancing the security of protocol itself, but it was failure to prevent protocol's external factors of impacting on security. In this regard, this paper proposes to use of the method of fuzzy control to realize the security identification of Kerberos protocol by embedding three fuzzy controllers and a system health and safety validator (SHSV) in the protocol; wherein the SHSV is to collect the health and security information in the client, whereas the three fuzzy controllers are using to process and determine the external security factors of the relevant servers respectively. This proposed method can be able to effectively realize on assessment and prevention from the potential and existing threats caused by protocol's external factors of security.
A Survey on Deep Learning and Machine Learning for COVID-19 Detection

Field: Computer Science (Physical Sciences)

Coronaviruses are a type of virus that can cause a variety of disorders and exist in different types. COVID-19 is derived from a special type of a respiratory illness caused by the SARS-CoV-2 virus, discovered in 2019. Approximately two years ago, COVID-19 was discovered in the Chinese city of Wuhan, and it has since become a worldwide source of concern. A COVID-19 confirmed patient is experiencing symptoms such as fever, fatigue, and a dry cough. Based on the results of laboratory tests and/or chest X-rays, the COVID-19 diagnosis is established. When it comes to research using chest CT scans /X-ray for the diagnosis of COVID-19, which is based on medical imaging, Artificial Intelligence (AI) approaches are increasingly being applied in a variety of ways. Machine learning and deep learning are fields of artificial intelligence that can be used to analyze the data that was acquired in order to better understand the origins of COVID-19. The outcomes of applying such an approach will aid in a better understanding of the nature of the threat and how it might be mitigated. For this reason, this work gives an overview of deep learning and machine learning approaches for the detection of COVID-19. Several COVID-19 detection methods are discussed in detail, as well as the issues, current challenges associated with artificial intelligence and medical researchers' approaches to providing a comprehensive assessment of detecting COVID-19.
An Enhanced Deep Neural Network Approach for WiFi Fingerprinting-Based Multi-Floor Indoor Localization

Field: Computer Science (Physical Sciences)

WiFi fingerprinting based on the Received Signal Strength Indicator (RSSI) is a widely used technique for indoor localization. However, achieving the necessary precision for most smart applications has proven difficult due to various challenges, including the time-varying characteristics of indoor RSSI, device heterogeneity, and ambiguity in the positional fingerprints. To address these concerns, Artificial Intelligence (AI) techniques such as Machine Learning (ML) and Deep Learning (DL) have been used to classify and predict indoor locations. While these techniques have shown promising results, they face two significant challenges. First, their complex multilayer architecture requires extensive training iterations. Second, the distribution of the input layer fluctuates as the network’s parameters are updated. In this study, we propose a WiFi indoor localization framework based on Recursive Feature Elimination with Cross-Validation (RFECV) and Deep Neural Network with Batch Normalization (DNNBN). The CV process is repeated multiple times to assess the RFE’s generalization ability for optimal feature selection, and the BN algorithm is integrated into each layer of the DNN to ensure consistent activation value distribution and stabilization of the training process. Two datasets were used to assess the performance of the proposed RFECV-DNNBN method. The results show that the method addresses the challenges faced by existing AI techniques and outperforms current methods in classification and regression tasks. Our proposed framework achieved 100% accuracy in building classification and 94.69% and 96.39% in floor classification on the UJIIndoorLoc and UTSIndoorLoc datasets, respectively, demonstrating its effectiveness. Additionally, it achieved a Mean Absolute Error (MAE) of 5.08 m and 4.29 m for the respective datasets, highlighting its potential in multi-floored environments.
Effect of a Diet-Induced Obesity on the Progeny Response in a Murine Model

Field: Agricultural and Biological Sciences (Life Sciences)

Diet-induced obesity could have detrimental effects on adults and their progeny. The aim of this study was to determine the effect of a high-energy diet on both F1 mice body weight and tissue/organ weight and F2 offspring growth. A simple murine model for obesity was developed using a high-energy diet and mice reared in litters of five or ten, from 30 dams receiving a cafeteria diet of either commercial chow (low energy), or a mixture of commercial chow, chocolate (50% cacao), and salty peanuts (high energy). This diet continued from mating until weaning, when the pups were allocated according to sex into eight groups based on maternal diet, litter size, and post-weaning diet. On day 74, the males were slaughtered, and the females were bred then slaughtered after lactation. As a result, the high-energy maternal diet increased the F1 offspring growth during lactation, while the high-energy post-weaning diet increased the F1 adult body weight and tissue/organ weight. The high-energy maternal diet could negatively affect the onset of the F1 but not the maintenance of breastfeeding of F1 and F2 offspring. For F2 offspring growth, the high energy overlapped the low-energy post-weaning diet, due to problems of gaining weight during lactation.
Chapter 5. What Is ‘Appropriate’ Legal Protection Before As Well As After Birth?

Field: Social Sciences (Social Sciences)

Appropriate legal protection for every child before as well as after birth must be non-discriminatory. The term before as well as after birth is irrevocably embedded in the foundation framework for protecting the human rights of every child, and Article 2 of the Universal Declaration prohibits discrimination of any kind in the entitlement to those rights, including discrimination on the grounds of birth or other status. The right to legal protection is recognized for the child before birth, as well as the child after birth. Legal protection is to provide a special safeguard, formulated appropriately, designed especially for the needs of children before as well as after birth. There is an urgent need for major human rights education in order to raise sensitivity to the poignant vulnerability of the child in that critical stage of life between conception and birth.Keywords: birth; child; human rights; legal protection
Lunar High Alumina Basalts in Mare Imbrium

Field: Earth and Planetary Sciences (Physical Sciences)

High-alumina (HA) mare basalts play a critical role in lunar mantle differentiation. Although remote sensing methods have speculated their potential presence regions based on sample FeO and TiO2 compositions, the location and distribution characteristics of HA basalts have not been provided. In this study, the compositions of exposed rocks in Mare Imbrium were determined using Lunar Reconnaissance Orbiter (LRO) Diviner oxides and Lunar Prospector Gamma-Ray Spectrometer (LP-GRS) Thorium (Th) products. The exposed HA basalts were identified based on laboratory lithology classification criteria and Al2O3 abundance. The HA basalt units were mapped based on lunar topographic data, and their morphological geological characteristics were calculated based on elevation data. The results show that there are 8406 HA basalt pixels and 17 original units formed by volcanic eruptions in Mare Imbrium. The statistics of their morphology characteristics show that the HA basalts are widely distributed in the northern part of Mare Imbrium, and their compositions have a large range of variation. These units have different area and volume, and the layers formed were discontinuous. The characteristic analysis shows that the aluminum-bearing volcanic activities in Mare Imbrium were irregular. The eruptions of four different source regions occurred in three phases, and the scale and extent of the eruptions were different. The results in this study provide reliable evidence for the heterogeneity of the lunar mantle and contribute valuable information to the formation process of early lunar mantle materials.