Miracle-dz/UniFAR-FTUs huggingface dataset:
Computational intelligence algorithms for optimisation of wireless sensor networks

Recent studies have tended towards incorporating Computation Intelligence, which is a large umbrella for all Machine Learning and Metaheuristic approaches into wireless sensor network (WSN) applications for enhanced and intuitive performance. Meta-heuristic optimisation techniques are used for solving several WSN issues such as energy minimisation, coverage, routing, scheduling and so on. This research designs and develops highly intelligent WSNs that can provide the core requirement of energy efficiency and reliability. To meet these requirements, two major decisions were carried out at the sink node or base station. The first decision involves the use of supervised and unsupervised machine learning algorithms to achieve an accurate decision at the sink node. This thesis presents a new hybrid approach for event (fire) detection system using k-means clustering on aggregated fire data to form two class labels (fire and non-fire). The resulting data outputs are trained and tested by the Feed Forward Neural Network, Naive Bayes, and Decision Trees classifier. This hybrid approach was found to significantly improve fire detection performance against the use of only the classifiers. The second decision employs a metaheuristic approach to optimise the solution of WSNs clustering problem. Two metaheuristic-based protocols namely the Dynamic Local Search Algorithm for Clustering Hierarchy (DLSACH) and Heuristics Algorithm for Clustering Hierarchy (HACH) are proposed to achieve an evenly balanced energy and minimise the net residual energy of each sensor nodes. This thesis proved that the two protocols outperforms state-of-the-art protocols such as LEACH, TCAC and SEECH in terms of network lifetime and maintains a favourable performance even under different energy heterogeneity settings.
Mapping global epidemiology of thyroid nodules among general population: A systematic review and meta-analysis

Introduction An emerging public health issue is brought on by the worldwide increase of thyroid nodules (TNs). The goal of the current study is to determine the global prevalence of TNs among the general population. Methods We screened articles published from January 2000 to May 2022. TN prevalence was calculated with the DerSimonian–Laird random effects model with arcsine transformation. Results A total of 20,358 entries were found in our research, and 102 of them met our inclusion criteria. A total of 9,276,178 individuals have been diagnosed as TNs; the overall prevalence was 24.83% (95% CI 21.44–28.55), regardless of the diagnostic techniques. TNs have become more prevalent during 2012–2022 (29.29%) compared with 2000–2011 (21.53%, p = 0.02). In addition, we discovered that women (36.51%) were more likely to have TNs than men (23.47%, p < 0.01). Interestingly, we found that obesity was correlated with the prevalence of TNs. Additionally, age-specific-stratified TN prevalence was found in our results. Discussion This meta-analysis shows that, regardless of country development and economic status, TNs are spreading more widely over the world. Our findings showed a strong correlation between rising TN prevalence and older age, female sex, and elevated weight. To stop the TN epidemic from spreading over the world, increased awareness, the understanding of the disease, and quick action are required.
Ship Emission Impacts on Air Quality and Human Health in the Pearl River Delta (PRD) Region, China, in 2015, With Projections to 2030

Ship emissions contribute to air pollution, increasing the adverse health impacts on people living in coastal cities. We estimated the impacts caused by ship emissions, both on air quality and human health, in 2015 and future (2030) within the Pearl River Delta (PRD) region of China. In addition, we assessed the potential health benefits of implementing an Emission Control Area (ECA) in the region by predicting avoided premature mortality with and without an ECA. In 2015, ship emissions increased PM2.5 concentrations and O3 mixing ratios by 1.4 μg/m3 and 1.9 ppb, respectively, within the PRD region. This resulted in 466 and 346 excess premature acute deaths from PM2.5 and O3, respectively. Premature mortality from chronic exposures was even more significant, with 2,085 and 852 premature deaths from ship‐related PM2.5 and O3, respectively. In 2030, we projected the future ship emissions with and without an ECA, using two possible land scenarios. With an ECA, we predicted 76% reductions in SO2 and 13% reductions in NOx from the shipping sector. Assuming constant land emissions from 2015 in 2030 (2030 Constant scenario), we found that an ECA could avoid 811 PM2.5‐related and 108 O3‐related deaths from chronic exposures. Using 2030 Projected scenario for land emissions, we found that an ECA would avoid 1,194 PM2.5‐related and 160 O3‐related premature deaths in 2030. In both scenarios, implementing an ECA resulted in 30% fewer PM2.5‐related premature deaths and 10% fewer O3‐related premature deaths, illustrating the importance of reducing ship emissions.
Subsurface Mesoscale Eddy Generation in the Ocean off Central Chile

Off the coast of central Chile, subsurface anticyclonic eddies are a salient feature of the oceanic circulation, transporting a signi ﬁ cant fraction of coastal water that is rich in nutrients and poor in dissolved oxygen offshore. In this study, the formation mechanism of these eddies is analyzed through a high ‐ resolution (~0.3 km) and low ‐ resolution (~3 km) oceanic model that realistically simulate the regional mean circulation, including the Peru ‐ Chile Undercurrent (PCUC). An analysis of the vorticity and eddy kinetic energy in both simulations indicated that the subsurface eddies can be triggered through a combination of processes that are associated with instabilities of the PCUC. In the high ‐ resolution simulation, we observed that the interaction between the PCUC and topographic slope generates anticyclonic vorticity and potential vorticity close to zero in the bottom boundary layer. The separation of the undercurrent from the slope favors the intensi ﬁ cation of anticyclonic vorticity. It reaches magnitudes that are larger than the planetary vorticity while kinetic energy is converted from the PCUC to the eddy ﬂ ow. These processes set the necessary conditions for the development of centrifugal instabilities, which can form submesoscale structures. The coalescence of submesoscale structures generates a subsurface anticyclonic mesoscale eddy. In the low ‐ resolution simulations (>3 km) centrifugal instabilities are not simulated, and the barotropic conversion of the mean kinetic energy into eddy kinetic energy appears as the main process of eddy formation. We showed that the vertical structure of these eddies is sensitive to the spatial resolution of the model.
Revisiting the R* theory: preemption enables multispecies coexistence on a single resource

Resource competition theory (R* theory) predicts that the species with the highest efficiency (lowest resource requirements) will exclude all other species when competing over a single resource. This prediction contrasts the vast diversity in natural systems where there are often few limiting resources. We conjecture that this prediction is derived from the unrealistic assumption that all species acquire the same amount of the resource, i.e. equal exploitation. Here, we introduce to this theory the concept of preemption exploitation and demonstrate that multispecies coexistence is possible when there is a tradeoff between resource use efficiency and preemption ability. Moreover, our model predicts a transition from efficiency dominated communities to preemption dominated communities with increasing resource availability. This new theory unifies many organism-specific mechanisms and tradeoffs into a single general tradeoff between preemption and efficiency that provides a mean of coexistence under resource competition.
Case report: Desmoid fibromatosis diagnosed in a 27-year-old male after being mistaken for a gastrointestinal stromal tumour

Despite being distinct lesions, gastrointestinal stromal tumours (GISTs) and desmoid fibromatosis may appear similar on imaging when they involve the stomach wall or bowel. As a result, they may be confused with one another when initially diagnosed. This report aims to present a case where a desmoid tumour was mistaken for a gastric GIST in a 27-year-old gentleman despite extensive investigation prior to exploratory laparotomy, and why differentiation through pathology, with a focus on the immunohistochemistry profile, is key for proper prognostication and appropriate management, including timely investigation for associated diseases such as Familial Adenomatous Polyposis in patients with desmoid tumours.
An introduction to p-adic period rings

This paper is the augmented notes of a course I gave jointly with Laurent Berger in Rennes in 2014. Its aim was to introduce the periods rings B crys and B dR and state several comparison theorems between{e}tale and crystalline or de Rham cohomologies for p-adic varieties.
Effects of phytocompound Precocene 1 on the expression and functionality of the P450 gene in λ-cyhalothrin-resistant Spodoptera litura (Fab.)

Spodoptera litura (Fabricius) is an agriculturally significant polyphagous insect pest that has evolved a high level of resistance to conventional insecticides. A dietary assay was used in this work to assess the resilience of field populations of S. litura to λ-cyhalothrin. Analysis of the function and expression of the cytochrome P450 gene was used to test the sensitivity of S. litura larvae to sub-lethal concentrations of the insecticidal plant chemical Precocene 1, both by itself and in combination with λ-cyhalothrin. The activity of esterase enzymes (α and β) was found to decrease 48 h post treatment with Precocene 1. The activity of GST enzyme and cytochrome P450 increased with Precocene 1 treatment post 48 h, however. Expression studies revealed the modulation by Precocene 1 of cytochrome P450 genes, CYP4M16, CYP4M15, CYP4S8V4, CYP4G31, and CYP4L10. While CYP4M16 expression was stimulated the most by the synergistic Precocene 1 + λ–cyhalothrin treatment, expression of CYP4G31 was the most down-regulated by Precocene 1 exposure. Hence, it is evident that λ–cyhalothrin-resistant pest populations are still sensitive to Precocene 1 at a sublethal concentration that is nevertheless capable of hindering their development. Precocene 1 can therefore be considered a potent candidate for the effective management of insecticide-resilient S. litura.
Light-Induced Interfacial Phenomena in Atomically Thin 2D van der Waals Material Hybrids and Heterojunctions

Atomically thin 2D van der Waals (2D-vDW) materials have attracted significant attention for optoelectronic applications in photodetectors, photovoltaics, and quantum information science. Their atomically thin thickness, however, renders them poor absorbers. Hybrid structures of 2D-vDW materials assembled with other semiconducting materials, such as quantum dots, nanowires, polymers, other 2D-vDW materials, or 3D bulk materials, have provided an elegant way to increase light harvesting and carrier generation via interfacial charge and energy transfer interactions. Here we present recent examples focused on the characterization of interfacial charge transfer and energy transfer in 2D-vDW hybrids and heterostructures and methods to modulate and control these processes through band gap engineering, morphology engineering, and external factors. Finally, we discuss potential future directions of research, including scalability from micron-sized flake-based devices to wafer size for commercial deployment, issue.
Do Energy-Oriented Changes Hinder Maintainability?

Energy efficiency is a crucial quality requirement for mobile applications. However, improving energy efficiency is far from trivial as developers lack the knowledge and tools to aid in this activity. In this paper we study the impact of changes to improve energy efficiency on the maintainability of Android applications. Using a dataset containing 539 energy efficiency-oriented commits, we measure maintainability – as computed by the Software Improvement Group's web-based source code analysis service Better Code Hub (BCH) – before and after energy efficiency-related code changes. Results show that in general improving energy efficiency comes with a significant decrease in maintainability. This is particularly evident in code changes to accommodate the Power Save Mode and Wakelock Addition energy patterns. In addition, we perform manual analysis to assess how real examples of energy-oriented changes affect maintainability. Our results help mobile app developers to 1) avoid common maintainability issues when improving the energy efficiency of their apps; and 2) adopt development processes to build maintainable and energy-efficient code. We also support researchers by identifying challenges in mobile app development that still need to be addressed.
Data Context Adaptation for Accurate Recommendation with Additional Information

Given a sparse rating matrix and an auxiliary matrix of users or items, how can we accurately predict missing ratings considering different data contexts of entities? Many previous studies proved that utilizing the additional information with rating data is helpful to improve the performance. However, existing methods are limited in that 1) they ignore the fact that data contexts of rating and auxiliary matrices are different, 2) they have restricted capability of expressing independence information of users or items, and 3) they assume the relation between a user and an item is linear.We propose DACONA, a neural network based method for recommendation with a rating matrix and an auxiliary matrix. DACONA is designed with the following three main ideas. First, we propose a data context adaptation layer to extract pertinent features for different data contexts. Second, DACONA represents each entity with latent interaction vector and latent independence vector. Unlike previous methods, both of the two vectors are not limited in size. Lastly, while previous matrix factorization based methods predict missing values through the inner-product of latent vectors, DACONA learns a non-linear function of them via a neural network. We show that DACONA is a generalized algorithm including the standard matrix factorization and the collective matrix factorization as special cases. Through comprehensive experiments on real-world datasets, we show that DACONA provides the state-of-the-art accuracy.
Readable matrix code

The method comprising a method for on the basis of the input image and a readable matrix coding specification can encode a message read matrix generates a code image, calculates the readable feature area to follow the pattern feature specifications; Determining the level of free cells and derived cell according to the code word specification; Calculating a decoded input value for the free cell to the exterior of the free cells compared to each area of ​​the input image message, follow the respective degree of similarity and the reference code word specification; And the free cell by decoding based on the input value and readable matrix code image generation method comprises the step of calculating a decoded input value for the induced cells in response to the code word specification.
Introductory Chapter: Applications of Stress Endocrinology in Wildlife Conservation and Livestock Science

Animals have contributed towards the progress of mankind in many ways such as through biomedicine, scientific research, domestication and farming, zoo animals and aquaculture [1–5]. The key concept of animal welfare underpins the quality of life of an animal while living under human management [6]. Animal welfare is a complex subject which takes into account the environmental and management factors that influence the physiological, behavioural and emotional (well-being or affective) state of animals [7, 8]. Animals such as elephants, dolphins, birds and dogs can display complex cognitive ability guided by processes such as perception, learning, memory and decisionmaking [9, 10]. Emotion in animals involves complex physiological, behavioural, immune, cognitive and morphological responses that enable them to generate behaviours to cope against stressors [11]. There are specific physiological markers of pain and stress that enable researchers to evaluate the welfare of animals from a quantitative viewpoint and relate the data to understand how the animal perceives its environment [12, 13].
1: Challenges in the 21st century in pig and poultry nutrition and the future of animal nutrition

To meet the challenges in the 21st century in pig and poultry nutrition, it is necessary to involve into the innovation activities besides classical animal nutrition knowledge, newer areas of natural and technical sciences (e.g. molecular biology, molecular nutrition, molecular genetics, nutrigenomics, information technology, etc.). The importance of these disciplines will continue to grow in the near future, in the following 5-10 years. Animal nutrition will need to increasingly focus on the production of safe and nutritious foods in a traceable manner produced within systems that care for the environment and animal welfare using ingredients not suitable for human consumption. The use of precision animal nutrition in practice greatly contributes to the changes required for the successful production of animal derived foods in the 21st century, as well as for the success of innovation activities. In order for the animal agricultural sector to be able to provide proper quantities of safe animal origin food materials to the food industry, there is a rapidly increasing need for better cooperation between medical and agricultural sciences on the basis of professional logic, as well as cooperation in R&DI programs and education. It is highly probable that new areas of science will revolutionise animal nutrition sciences such as bioinformatics, molecular biology, molecular nutrition, as well as quantum biology. These areas of science will greatly contribute to the development of animal nutrition science and, as a result, to a more efficient animal nutrition, as well as to a better quality and safe food base material production of animal origin.
Contrasting Spring and Summer Large-Scale Environments Associated with Mesoscale Convective Systems over the U.S. Great Plains

Mesoscale convective systems (MCSs) are frequently observed over the U.S. Great Plains during boreal spring and summer. Here, four types of synoptically favorable environments for spring MCSs and two types each of synoptically favorable and unfavorable environments for summer MCSs are identified using self-organizing maps (SOMs) with inputs from observational data. During spring, frontal systems providing a lifting mechanism and an enhanced Great Plains low-level jet (GPLLJ) providing anomalous moisture are important features identified by SOM analysis for creating favorable dynamical and thermodynamic environments for MCS development. During summer, the composite MCS environment shows small positive convective available potential energy (CAPE) and convective inhibition (CIN) anomalies, which are in stark contrast with the large positive CAPE and negative CIN anomalies in spring. This contrast suggests that summer convection may occur even with weak large-scale dynamical and thermodynamic perturbations so MCSs may be inherently less predictable in summer. The two synoptically favorable environments identified in summer have frontal characteristics and an enhanced GPLLJ, but both shift north compared to spring. The two synoptically unfavorable environments feature enhanced upper-level ridges, but differ in the strength of the GPLLJ. In both seasons, MCS precipitation amount, area, and rate are much larger in the frontal-related MCSs than in nonfrontal MCSs. A large-scale index constructed using pattern correlation between large-scale environments and the synoptically favorable SOM types is found to be skillful for estimating MCS number, precipitation rate, and area in spring, but its explanatory power decreases significantly in summer. The low predictability of summer MCSs deserves further investigation in the future.
A Software Modeling Perspective of UMLS Semantic Network

The UMLS is a standard medical vocabulary developed by aggregating standard terminologies and sources from diverse healthcare domains, which encapsulates a broad spectrum of medical knowledge. The two primary knowledge sources of the UMLS are semantic network (SN) and metathesaurus (META). In the present state, the impact of the semantic knowledge captured by UMLS-SN on healthcare application is minimal or has no impact, as UMLS confines the UMLS-SN knowledge. Further, healthcare application design and development is achieved primarily by using sound software modeling principles and established object-oriented (OO) frameworks and languages. The goal of this chapter is to translate UMLS-SN knowledge into an OO modeling framework to utilize SN’s knowledge in designing healthcare application. The result is the design and development of UMLS-SN, a custom metamodel by leveraging UML profile and metamodel. This specialized metamodel allows developers to design healthcare applications that are coherent with object-oriented modeling and software engineering approaches.
NUEVAS DISTINCIONES CONCEPTUALES EN GRAMÁTICA GENERATIVA Y ALGUNAS OBSERVACIONES SOBRE SINTAXIS Y DISCURSO

The crucial changes that generative linguistics has suffered along the last years involve the increasing of underlying leading ideas about the object of linguistics as well as modifications in the form and organization of the grammar. This paper concerns both questions just mentioned. In the first part an informal and philosophical-like presentation of the set of new distinctions made by this linguistics is given. The distinction core vs periphery, derivational vs representational and sentence vs discourse grammar are discussed and briefly illustrated. The notions of parametric variation and modularity are also explained. In the second part the interplay between sentence and discourse grammar is specifically illustrated and analyzed. It is shown, first, that certain rules of discourse have to apply at the level of "logical form" and after other deletion rules apparently similar but belonging to sentence grammar. Secondly, a correlation between structural properties and the discourse phenomenon of topic-comment is shown.