Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantifying Lodging Percentage and Lodging Severity Using a UAV-Based Canopy Height Model Combined with an Objective Threshold Approach

Unmanned aerial vehicles (UAVs) open new opportunities in precision agriculture and phenotyping because of their flexibility and low cost. In this study, the potential of UAV imagery was evaluated to quantify lodging percentage and lodging severity of barley using structure from motion (SfM) techniques. Traditionally, lodging quantification is based on time-consuming manual field observations. Our UAV-based approach makes use of a quantitative threshold to determine lodging percentage in a first step. The derived lodging estimates showed a very high correlation to reference data (R2 = 0.96, root mean square error (RMSE) = 7.66%) when applied to breeding trials, which could also be confirmed under realistic farming conditions. As a second step, an approach was developed that allows the assessment of lodging severity, information that is important to estimate yield impairment, which also takes the intensity of lodging events into account. Both parameters were tested on three ground sample distances. The lowest spatial resolution acquired from the highest flight altitude (100 m) still led to high accuracy, which increases the practicability of the method for large areas. Our new lodging assessment procedure can be used for insurance applications, precision farming, and selecting for genetic lines with greater lodging resistance in breeding research.
Spectral signatures for non-rigid 3D shape retrieval

This thesis addresses problems associated with computing spectral shape signatures for non-rigid 3D object retrieval. More specifically, we use spectral shape analysis tools to describe the characteristics of different 3D object representations. This thesis tries to answer whether spectral shape analysis tools can enhance classical shape signatures to improve the performance of the non-rigid shape retrieval problem. Furthermore, it describes the stages of the framework for composing non-rigid shape signatures, built from the shape Laplacian. This thesis presents four methods to improve each part of the framework for computing spectral shape signatures. The first stage comprises computing the right shape spectrum to describe 3D objects. We introduce the Kinetic Laplace-Beltrami operator which computes enhanced spectral components from 3D meshes specific to non-rigid shape retrieval and we also introduce the Mesh-Free Laplace Operator which computes more precise and robust spectral components from 3D point clouds. After computing the shape spectrum, we propose the Improved Wave Kernel Signature, a more discriminative local descriptor built from the Laplacian eigenfunctions. This descriptor is used throughout this thesis and it achieves, in most cases, state-of-the-art performances. Then, we define a new framework for encoding sparse local descriptors into shape signatures that can be compared to each other. Here, we show how to use the Fisher Vector and Super Vector to encode spectral descriptors and also how to compute dissimilarities between shape signatures using the Efficient Manifold Ranking. Furthermore, we describe the construction of the Point-Cloud Shape Retrieval of Non-Rigid Toys dataset, aimed in testing non-rigid shape signatures on point clouds, after we evidenced a lack of point-cloud benchmarks in the literature. With these ingredients, we are able to construct shape signatures which are specially built for non-rigid shape retrieval.
Mapping Maize Water Stress Based on UAV Multispectral Remote Sensing

Mapping maize water stress status and monitoring its spatial variability at a farm scale are a prerequisite for precision irrigation. High-resolution multispectral images acquired from an unmanned aerial vehicle (UAV) were used to evaluate the applicability of the data in mapping water stress status of maize under different levels of deficit irrigation at the late vegetative, reproductive and maturation growth stages. Canopy temperature, field air temperature and relative humidity obtained by a handheld infrared thermometer and a portable air temperature/relative humidity meter were used to establish a crop water stress index (CWSI) empirical model under the weather conditions in Ordos, Inner Mongolia, China. Nine vegetation indices (VIs) related to crop water stress were derived from the UAV multispectral imagery and used to establish CWSI inversion models. The results showed that non-water-stressed baseline had significant difference in the reproductive and maturation stages with an increase of 2.1 °C, however, the non-transpiring baseline did not change significantly with an increase of 0.1 °C. The ratio of transformed chlorophyll absorption in reflectance index (TCARI) and renormalized difference vegetation index (RDVI), and the TCARI and soil-adjusted vegetation index (SAVI) had the best correlations with CWSI. R2 values were 0.47 and 0.50 for TCARI/RDVI and TCARI/SAVI at the reproductive and maturation stages, respectively; and 0.81 and 0.80 for TCARI/RDVI and TCARI/SAVI at the late reproductive and maturation stages, respectively. Compared to CWSI calculated by on-site measurements, CWSI values retrieved by VI-CWSI regression models established in this study had more abilities to assess the field variability of crop and soil. This study demonstrates the potentiality of using high-resolution UAV multispectral imagery to map maize water stress.
Human adipose tissue H3K4me3 histone mark in adipogenic, lipid metabolism and inflammatory genes is positively associated with BMI and HOMA-IR

Introduction Adipose tissue is considered an important metabolic tissue, in charge of energy storage as well as being able to act in systemic homeostasis and inflammation. Epigenetics involves a series of factors that are important for gene regulation or for chromatin structure, mostly DNA methylation and histone-tail modifications, which can be modified by environmental conditions (nutrition, lifestyle, smoking…). Since metabolic diseases like obesity and diabetes are closely related to lifestyle and nutrition, epigenetic deregulation could play an important role in the onset of these diseases and vice versa. However, little is known about histone marks in human adipose tissue. In a previous work, we developed a protocol for chromatin immunoprecipitation (ChIP) of frozen human adipose tissue. By using this method, this study investigates, for the first time, the H3K4 trimethylation (H3K4me3) mark (open chromatin) on the promoter of several factors involved in adipogenesis, lipid metabolism and inflammation in visceral adipose tissue (VAT) from human subjects with different degrees of body mass index (BMI) and metabolic disease. Methodology VAT was collected and frozen at -80°C. 100 mg VAT samples were fixed in 0.5% formaldehyde and homogenized. After sonication, the sheared chromatin was immune-precipitated with an anti-H3K4me3 antibody linked to magnetic beads and purified. H3K4me3 enrichment was analyzed by qPCR for LEP, LPL, SREBF2, SCD1, PPARG, IL6, TNF and E2F1 promoters. mRNA extraction on the same samples was performed to quantify gene expression of these genes. Results H3K4me3 was enriched at the promoter of E2F1, LPL, SREBF2, SCD1, PPARG and IL6 in lean normoglycemic compared to morbid obese subjects with prediabetes. Accordingly H3K4me3 mark enrichment at E2F1, LPL, SREBF2, SCD1, PPARG and IL6 promoters was positively correlated with the BMI and the HOMA-IR. Regression analysis showed a strong relationship between the BMI with H3K4me3 at the promoter of E2F1 and LPL, and with mRNA levels of LEP and SCD. In the case of HOMA-IR, the regression analysis showed associations with H3K4me3 enrichment at the promoter of SCD1 and IL6, and with the mRNA of LEP and SCD1. Moreover H3K4me3 at the E2F1 promoter was positively associated to E2F1 mRNA levels. Conclusions H3K4me3 enrichment in the promoter of LEP, LPL, SREBF2, SCD1, PPARG, IL6, TNF and E2F1 is directly associated with increasing BMI and metabolic deterioration. The H3k4me3 mark could be regulating E3F1 mRNA levels in adipose tissue, while no associations between the promoter enrichment of this mark and mRNA levels existed for the other genes studied.
An Integrated Decision-Making Method Based on Neutrosophic Numbers for Investigating Factors of Coastal Erosion

The recent boom of various integrated decision-making methods has attracted many researchers to the field. The recent integrated Analytic Network Process and Decision Making Trial and Evaluation Laboratory (ANP–DEMATEL) methods were developed based on crisp numbers and fuzzy numbers. However, these numbers are incapable of dealing with the indeterminant and inconsistent information that exists in real-life problems. This paper proposes improvements to the integrated ANP–DEMATEL method by bringing together the neutrosophic numbers, the ANP method, and the DEMATEL method, which are later abbreviated to NS-DANP. The proposed NS-DANP method can handle the indeterminacy elements in the decision-making environment, as the single-valued neutrosophic numbers are used in the decision analysis. This proposed NS-DANP modification method includes linguistic variables representing the single-valued neutrosophic numbers (SVNNs), and also introduces the single-valued neutrosophic weighted averaging (SVNWA) aggregation operator to aggregate the decision makers’ judgments instead of the typical averaging method. The applicability of the proposed method is illustrated by a case study of the coastal erosion problem along the Peninsular Malaysia coastline, where 12 factors were considered. Three experts of coastal erosion from different organizations were invited to elicit their linguistic judgments on the cause–effect of the coastal erosion. The seven-step decision approach was developed to acquire the weightage of each coastal erosion factor. The outcome of this study reveals that coastal development is the riskiest factor toward coastal erosion. The weight of factors and the cause–effect diagram could be very helpful for government and stakeholders to project a better mitigation plan for the coastal erosion problem. Comparative analysis is also provided to check the feasibility of the proposed method.
A detector’s eye view (DEV)-based OSEM algorithm for benchtop x-ray fluorescence computed tomography (XFCT) image reconstruction

In this study, we developed a detector’s eye view (DEV)-based ordered subsets expectation maximization (OSEM) algorithm for more accurate reconstruction of benchtop x-ray fluorescence computed tomography (XFCT) images. The proposed approach was tested using two sets of benchtop XFCT imaging data derived from a newly performed gold nanoparticle (GNP)-containing phantom imaging study and a previously published postmortem benchtop XFCT imaging study of a tumor-bearing mouse injected with GNPs. DEV-based OSEM resulted in higher spatial resolution (up to ~20% decrease in the full width at half maximum values of the regions of interest), compared with filtered back-projection (FBP) and traditional OSEM. It also resulted in up to an order of magnitude smaller background noise in the reconstructed images than FBP, while producing consistently less background noise than traditional OSEM.
Left atrial spontaneous echo contrast: relationship with clinical and echocardiographic parameters

Spontaneous echo contrast (SEC) indicates blood stasis in cardiac chambers and major vessels, and is a known precursor of thrombus formation. Transesophageal echocardiography plays a pivotal role in detecting and grading SEC in the left atrial (LA) cavity. Assessing LA SEC can identify patients at increased risk for thromboembolic events. LA SEC also develops in patients who have sinus rhythm, especially in those with heart failure. Detection of LA SEC is not uncommon in subjects who have multiple cardiovascular comorbidities, although mechanisms behind this association are not fully understood. In patients with atrial fibrillation, the role of mitral regurgitation in counteracting LA SEC and subsequent thromboembolism is controversial. Moreover, alterations of blood coagulability and elevated levels of certain biological markers in the blood contribute to occurrence of LA SEC. This review describes the pathogenesis and assessment of SEC, in addition to the relationship between LA SEC and clinical, biological and echocardiographic parameters.
Modelling social media popularity of news articles using headline text

The way we formulate headlines matters -- this is the central tenet of this thesis. Headlines play a key role in attracting and engaging online audiences. With the increasing usage of mobile apps and social media to consume news, headlines are the most prominent -- and often the only -- part of the news article visible to readers. Earlier studies examined how readers' preferences and their social network influence which headlines are clicked or shared on social media. However, there is limited research on the impact of the headline text on social media popularity. To address this research gap we pose the following question: how to formulate a headline so that it reaches as many readers as possible on social media. To answer this question we adopt an experimental approach to model and predict the popularity of news articles on social media using headlines. First, we develop computational methods for an automatic extraction of two types of headline characteristics. The first type is news values: Prominence, Sentiment, Magnitude, Proximity, Surprise, and Uniqueness. The second type is linguistic style: Brevity, Simplicity, Unambiguity, Punctuation, Nouns, Verbs, and Adverbs. We then investigate the impact of these features on popularity using social media popularity on Twitter and Facebook, and perceived popularity obtained from a crowdsourced survey. Finally, using these features and headline metadata we build prediction models for global and country-specific social media popularity. For the country-specific prediction model we augment several news values features with country relatedness information using knowledge graphs. Our research established that computational methods can be reliably used to characterise headlines in terms of news values and linguistic style features; and that most of these features significantly correlate with social media popularity and to a lesser extent with perceived popularity. Our prediction model for global social media popularity outperformed state-of-the-art baselines, showing that headline wording has an effect on social media popularity. With the country-specific prediction model we showed that we improved the features implementations by adding data from knowledge graphs. These findings indicate that formulating a headline in a certain way can lead to wider readership engagement. Furthermore, our methods can be applied to other types of digital content similar to headlines, such as titles for blog posts or videos. More broadly our results signify the importance of content analysis for popularity prediction.
Video media in the hyperconnected age: investigating emergent viewing practices

Recent technological developments have changed the way video is consumed. The uptake of fast internet connections and ubiquitous mobile devices mean that people can watch via on demand services, and that viewers often media multitask with phones and tablets during viewing. This thesis examines on-demand viewing and media multitasking with mobile devices in detail. Two situated studies extend our understanding of these behaviours through video observation and diary studies. It was found that using mobile devices while viewing was common, though subject to different usage patterns and individual differences. Self-reported media multitasking propensity correlated with observational data, suggesting that some people consistently media multitask more than others. People valued the freedom and choice provided by on-demand services, which drove their popularity. Viewing occurred in a range of contexts and on a variety of devices. However, some were concerned that it was difficult to limit their viewing. In order to quantify viewer experience, a questionnaire was developed to measure immersion. This was used in two lab experiments investigating specific behaviours that were previously observed: watching on screens of different sizes; and being interrupted by notifications while watching. It was found that both watching on small screens and interruptions from notifications negatively affected immersion. The findings of this research affect viewers, content producers, and TV networks. To preserve and improve viewing experiences, stakeholders should be mindful of both positive and negative effects when considering personal usage and the development of new viewing technologies.
Statistical models discriminating between complex samples measured with microfluidic receptor-cell arrays

Data analysis for flow-based in-vitro receptomics array, like a tongue-on-a-chip, is complicated by the relatively large variability within and between arrays, transfected DNA types, spots, and cells within spots. Simply averaging responses of spots of the same type would lead to high variances and low statistical power. This paper presents an approach based on linear mixed models, allowing a quantitative and robust comparison of complex samples and indicating which receptors are responsible for any differences. These models are easily extended to take into account additional effects such as the build-up of cell stress and to combine data from replicated experiments. The increased analytical power this brings to receptomics research is discussed.
D1-Dopamine Receptor Availability in First-Episode Neuroleptic Naive Psychosis Patients

Abstract Background Positron emission tomography studies examining differences in D1-dopamine receptor binding between control subjects and patients with schizophrenia have been inconsistent, reporting higher, lower, and no difference in the frontal cortex. Exposure to antipsychotic medication has been suggested to be a likely source of this heterogeneity, and thus there is a need for studies of patients at early stages of the disorder who have not been exposed to such drugs. Methods Here, we compared 17 healthy control subjects and 18 first-episode neuroleptic naive patients with schizophrenia or schizophreniform psychosis using positron emission tomography and the D1-dopamine receptor radioligand [11C]SCH23390. Results We observed a statistically significant difference in the dorsolateral prefrontal cortex. Contrary to our expectations, patients had less D1-dopamine receptor availability with a moderate effect size. In a Bayesian analysis, we show that the data are over 50 times more likely to have occurred under the decrease as opposed to the increase hypothesis. This effect was not global, as our analysis showed that the null hypothesis was preferred over either hypothesis in the striatum. Conclusions This investigation represents the largest single sample of neuroleptic-naive patients examined for D1-dopamine receptor availability using PET and suggests a reduction of prefrontal D1-dopamine receptor density in the pathophysiology of schizophrenia. However, further work will be required to reach a consensus.
Inorganic Polysulfides and Related Reactive Sulfur–Selenium Species from the Perspective of Chemistry

Polysulfides (H2Sx) represent a class of reactive sulfur species (RSS) which includes molecules such as H2S2, H2S3, H2S4, and H2S5, and whose presence and impact in biological systems, when compared to other sulfur compounds, has only recently attracted the wider attention of researchers. Studies in this field have revealed a facet-rich chemistry and biological activity associated with such chemically simple, still unusual inorganic molecules. Despite their chemical simplicity, these inorganic species, as reductants and oxidants, metal binders, surfactant-like “cork screws” for membranes, components of perthiol signalling and reservoirs for inorganic hydrogen sulfide (H2S), are at the centre of complicated formation and transformation pathways which affect numerous cellular processes. Starting from their chemistry, the hidden presence and various roles of polysulfides in biology may become more apparent, despite their lack of clear analytical fingerprints and often murky biochemical footprints. Indeed, the biological chemistry of H2Sx follows many unexplored paths and today, the relationship between H2S and its oxidized H2Sx species needs to be clarified as a matter of “unmistaken identity”. Simultaneously, emerging species, such as HSSeSH and SenS8−n, also need to be considered in earnest.
Recognising the need for innovation in digitalising urgent or advance care planning in adults aged 70 years and over following emergency admission.

Approximately one in three hospital inpatients may be in their last year of life in Scotland;[1][1] however, no data exist for England, therefore this study aimed to establish the 1-year mortality of a cohort of patients aged 70 years and above admitted to a large London hospital trust, to explore
Functional Effects of let-7g Expression in Colon Cancer Metastasis

MicroRNA regulation is crucial for gene expression and cell functions. It has been linked to tumorigenesis, development and metastasis in colorectal cancer (CRC). Recently, the let-7 family has been identified as a tumor suppressor in different types of cancers. However, the function of the let-7 family in CRC metastasis has not been fully investigated. Here, we focused on analyzing the role of let-7g in CRC. The Cancer Genome Atlas (TCGA) genomic datasets of CRC and detailed data from a Taiwanese CRC cohort were applied to study the expression pattern of let-7g. In addition, in vitro as well as in vivo studies have been performed to uncover the effects of let-7g on CRC. We found that the expression of let-7g was significantly lower in CRC specimens. Our results further supported the inhibitory effects of let-7g on CRC cell migration, invasion and extracellular calcium influx through store-operated calcium channels. We report a critical role for let-7g in the pathogenesis of CRC and suggest let-7g as a potential therapeutic target for CRC treatment.
The Effect of Polydopamine on an Ag-Coated Polypropylene Nonwoven Fabric

A practical method for preparing multifunctional polypropylene (PP) nonwoven fabrics with excellent stability and durability was explored. First, the PP nonwoven fabric was sputtered by a magnetron sputtering system to form an Ag film on the surface of the fabric. Subsequently, the coated fabric was treated with dopamine. The fabrics were characterized by scanning electron microscopy (SEM), an energy dispersive spectrometer (EDS), electrical conductivity, electromagnetic interference shielding effectiveness (EMI SE), antibacterial activity, stability, and laundering durability. The results of the study revealed that the fabric was coated with Ag, and after the treatment with dopamine, the surfaces of Ag-coated fibers were coated with polydopamine (PDA). The fabrics still had a sheet resistance below ~15 Ω/sq and exhibited excellent EMI SE above ~25 dB, though few differences existed from the single Ag-coated sample. After the treatment with dopamine, the antibacterial activity of the fabric was enhanced. Meanwhile, the treated samples exhibited excellent resistance against sodium sulfide corrosion, which could enhance the stability of the Ag-coated fabric. Moreover, the laundering durability of the treated fabric was improved in the same process, whose lowest sheet resistance was ~18 Ω/sq and the EMI SE was ~8 dB more than single Ag-coated PP nonwoven fabrics. In conclusion, this method was considered to be effective in fabricating multifunctional, stable, and durable fabrics.