Miracle-dz/UniFAR-FTUs huggingface dataset:
Lightning Disaster Risk Assessment Method in Colombia A Review of Educational Methodologies on Lightning Safety

This paper presents a compilation of some of the educational methodologies proposed and implemented to promote and spread the lightning safety message within populations with particular characteristics, reviewing previous documentation from researches whose results and experiences have contributed to reach people with helpful information that can save their lives. Likewise, 10 lightning incidents (9 occurred in Colombia and 1 in Tanzania) are referenced and described including the conditions in which they happened. Then, a discussion is made about the current situation of Colombia in relation to lightning management, comparing the effectiveness of protection systems versus the lack of lightning prevention knowledge among Colombian people. Finally, the structure of the National System of Disaster Risk Management (SNGRD in Spanish) is presented, which is the foundation for the design and execution of lightning safety programs in the country.
NOTES AND

This study focuses on the evaluation of 3-hourly, 0.25 8 3 0.25 8 , satellite-based precipitation products: the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42RT, the NOAA/Climate Prediction Center morphing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information using Artiﬁcial Neural Networks (PERSIANN). CMORPH is primarily microwave based, 3B42RT is primarily microwave based when microwave data are available and infrared based when microwave data are not available, and PERSIANN is primarily infrared based. The results show that 1) 3B42RT and CMORPH give similar rainfall ﬁelds (in terms of bias, spatial structure, elevation-dependent trend, and distribution function), which are different from PERSIANN rainfall ﬁelds; 2) PERSIANN does not show the elevation-dependent trend observed in rain gauge values, 3B42RT, and CMORPH; and 3) PERSIANN considerably underestimates rainfall in high-elevation areas.
KEMM: A Knowledge Enhanced Multitask Model for Travel Recommendation

In today’s fast-moving world with a wide spectrum of choices and options available regarding the places to travel, it’s tedious to ﬁnd the most optimal destination to visit keeping in mind the constraints of budget, choices, preferences, and weather. Most of the current systems either rely on the user’s location or their travel history making the selection suboptimal and not accustomed to the user’s preferences. The focus of this research is on recommendation systems that utilize a graph-based approach. The method involves creating an interaction graph based on past user-item interactions to overcome data sparsity and cold start issues. However, this study has identiﬁed a problem in existing graph based models related to early summarization. To address this problem, a new approach to the existing Knowledge based Neighborhood Interaction (KNI) model is proposed. A knowledge Enchanced Multitask Model for Travel Recommendation (KEMM) has been proposed to capture unique characteristics of each neighbor pair between users and items. Also corpus creation for a Knowledge Graph of Indian Places to visit has also been done. The model’s performance have been assessed using real-world datasets and evaluated against the current state-of-the-art models using standard metrics. The comparative analysis of this model on various datasets reveal that the model is performing better or simillar to other existing state-of-the-art models. It has been observed that there was a minor increase in the Precision@k metric and slight improvement in AUC.
DEEP LEARNING DETECTING FRAUD IN CREDIT CARD TRANSACTIONS

Fraudulent acts -in the financial sector-cause dramatic losses to companies and individuals. To tackle this conundrum, artificial intelligence trends forthcame to develop a fraud detection system. This paper comes to process fraudulent credit card transactions issue deploying ANN and CNN, two supervised deep learning algorithms that proved efficiency . Yet, two hurdles appear: Constant emersion of new fraudulent patterns and highly-imbalanced dataset. So, sampling techniques are required to balance data, the thing that affects the system performance. Thus, Autoencoder, as an unsupervised deep learning algorithm, was added to compare it to the aforementioned algorithms. Three models were trained on a dataset of 284,807 credit card transactions labeled as fraudulent and legitimate. Various techniques were conducted in the pre-processing phase as normalization, data balancing, and feature selection. In the during-applying model stage, tuning and analysis were conducted on the model parameters to improve the classification decision. Similarly, in the post-applying model stage, a boosting technique was applied. Not only were the models compared in terms of accuracy, precision, recall, and AUC score but also they were based on confusion matrix. Eventually, one model was chosen out of the experimented models based on the robustness of detecting new fraud patterns; especially, the latter demonstrates optimal rates, achieving an f1-score of 93% after classifying not fraud transactions.
HILL-CLIMBING POWERED GATED RECURRENT UNIT NETWORK TO PREDICT STOCK TRADING SIGNALS USING MEAN AVERAGE CONVERGENCE DIVERGENCE INDICATOR

This paper proposed a hill-climbing powered gated recurrent unit (HC-GRU) network to predict stock trading signals using the mean average convergence divergence (MACD) indicator. The proposed model was compared with the Buy/Hold Strategy, a benchmark strategy, and the traditional MACD indicator based trading strategy. All three models were evaluated in terms of the annualized rate of return, sharp ratio, and the number of profit/loss trades executed by the strategies. The experiments were conducted on twenty randomly selected stocks from the Bombay Stock Exchange, Nepal Stock Exchange, New York Stock Exchange, and the Shanghai Stock Exchange. From the experimental results, we observed that the HC-GRU outperformed the other two models in terms of all three measures. ARR obtained from HC-GRU strategy was 22.44% to 62.76% higher than the ARR obtained from the traditional MACD indicator based trading strategy and it was 14.69% to 71.72% higher than the Buy/Hold strategy. On the other side, 66.67% to 100% trades made by the HC-GRU strategy were profit trades but only 27.78% to 62.5% trades executed by the traditional MACD indicator based trading strategy were profit trades. From this observation, we concluded that the proposed HC-GRU approach is a superior strategy for automated stock trading whereas the traditional MACD indicator based strategy is not suitable for automated stock trading.
Systematic Review and Critique of the Contributions of Traditional Ecological Knowledge of Beluga Whales in the Marine Mammal Literature + Supplementary Appendix Table (See Article Tools)

Dans cette etude, nous avons passe en revue de maniere systematique la litterature existante sur les connaissances ecologiques traditionnelles (CET) des belugas ( Delphinapterus leucas ) et nous l’avons critiquee en tant qu’etude de cas dans le but de mieux comprendre la contribution des CET aux connaissances existantes sur les mammiferes marins au cours des quatre dernieres decennies. Differentes bases de donnees consultables en ligne ont ete examinees, puis des articles publies dans des revues scientifiques et des ecrits provenant de la litterature grise ont ete recueillis, apres quoi ceux-ci ont ete classes par emplacement geographique, discipline, ainsi que par leur utilisation des CET. Au total, 137 documents ont ete retenus pour les analyses finales, dont 67 % faisaient reference au nord du Canada, en particulier la sous-region de la baie d’Hudson. Les articles contenant des informations non publiees ou des anecdotes sur la representation des CET sur les belugas ont figure parmi les articles les plus abondants. Les documents contenant des CET sur les belugas ont augmente rapidement entre 1975 et 2004, mais leur nombre semble s’etre maintenu depuis. Les articles de biologie ont represente la majorite des documents (72%), suivis de ceux axes sur la gestion ou la cogestion. Cette revue de la litterature montre que bien que les connaissances des peuples autochtones aient contribue a une comprehension nettement meilleure des belugas, il y a un manque de rigueur dans la maniere de recueillir, de documenter et d’utiliser les CET dans la litterature sur le beluga, particulierement la litterature celle axee sur la gestion.
Marginalized Unscented Quaternion Estimator for Integrated INS/GPS

The UnScented QUaternion Estimator (USQUE) has been approved as a promising substitute for the extended Kalman filter when applied in the Standard Inertial Navigation Equations (SINE)-based inertial navigation system/global positioning system integration. However, the expensive computational burden makes it untenable in real time applications. In this paper, a computationally efficient filtering algorithm called Marginalised USQUE (MUSQUE) is derived by embedding the Marginalised Unscented Transformation (MUT) that is applicable to nonlinear systems with a linear substructure into the widely used USQUE. The contributions of the MUSQUE developed here are twofold. Firstly, the SINE are reconstructed to be only nonlinear in the attitude quaternion while linear in velocity and position, which makes the MUT potentially applicable in the USQUE. Secondly, the quaternion and generalised Rodrigues parameter-based sigma points are propagated simultaneously in the MUSQUE to deal with the dimensional mismatching hierarchy of the USQUE. Compared with the USQUE the number of sigma points can be decreased substantially, thereby making the applied MUSQUE computationally tenable. The experimental results show that the proposed MUSQUE has nearly identical performance with the USQUE but with much reduced computational burden.
Identi�cation of novel long noncoding RNA with distinct expression patterns in different subtypes of multiple myeloma

Evidence has accumulated regarding the association of some types of long noncoding RNA (lncRNAs) with severity and progression of multiple myeloma (MM). In this study, we explore the expression of novel lncRNA in different molecular subtypes of MM and examine their correlation with the prognosis of the patient. Whole transcriptome RNA sequencing of 643 newly diagnosed MM samples was performed. De novo and reference guided transcript assembly pipelines were used for RNA-seq data processing and discovery of novel lncRNAs in MM. We identi�ed 8,556 potentially novel lncRNA transcripts expressed in patients with MM. Of these, 1,264 novel transcripts showed signi�cant differential expression between the different molecular subtypes of MM. Through bioinformatic analysis, we identify their potential targets and roles in MM. Functional enrichment analysis of nearby coexpressed genes was used to predict involved pathways. The function was also inferred by comparing the k-mer content with known lncRNAs. Two of the novel lncRNAs had a signi�cant association with progression free survival and/or overall survival. In conclusion, we identi�ed many novel lncRNAs, describe their expression pattern among different genetic subtypes of MM and provide evidence of their potential role in the pathogenesis, progression, and prognosis of the disease.
A STUDY OF WATER QUALITY PARAMETERS TO BETTER MANAGE OUR PONDS OR LAKES

Successful pond or lake management requires an understanding of the role of nutrients and other water quality parameters, as well as regular monitoring of environmental conditions within the pond's or lake's ecosystem. Water quality is often overlooked in pond or lake management, and poor water quality can lead to common problems, such as excessive algal blooms, overgrowth of plants, noxious smells, or dead and dying fish. In order to prevent these problems, an understanding of basic water chemistry and other physical parameters is necessary. This paper describes the most important water quality factors that influence the health of ponds or lakes. Some factors that are particularly important in recreational fish ponds or lakes to ensure fish health and pond or lake productivity are also discussed.
Zoonotic Microparasites in Invasive Black Rats (Rattus rattus) from Small Islands in Central Italy

Simple Summary Invasive species negatively affect native populations through predation, competition, and the potential introduction of health threats, such as parasites. Black rats (Rattus rattus) are among the worst invaders of islands, and a significant source of parasites infecting humans and other animals. This study conducted a screening for zoonotic and veterinary-relevant microparasites in wild rats from small islands in central Italy, including the Pontine Islands and Pianosa, where the primary hosts of the selected parasites were either absent or scarce. The aim was to investigate the potential role of rats as their host. Rats were kill-trapped and molecular analyses were performed on different tissues to identify microparasite presence. Results confirm that invasive species such as rats may contribute to an elevated parasitological threat to local wildlife and human communities in specific ecosystems. Notably, we documented the first record of Babesia divergens, typically associated with cattle and wild ungulates, in wild rats. Additionally, we confirmed the presence of Leishmania infantum on an island without dogs, which have traditionally been considered the primary hosts. Our study helps to document parasite distribution and interactions between parasites and introduced invasive hosts, and represents useful knowledge to inform public health and wildlife management policy. Abstract Invasive species have a detrimental impact on native populations, particularly in island ecosystems, and they pose a potential zoonotic and wildlife threat. Black rats (Rattus rattus) are invasive species that disrupt native flora and fauna on islands and serve as potential competent reservoirs for various pathogens and parasites. Microparasites screening was conducted in rat populations from small islands in central Italy (the Pontine Islands and Pianosa) with the aim of assessing the role of rats in maintaining infections, particularly in cases where key reservoir hosts were scarce or absent. We focused on microparasites of zoonotic and veterinary relevance. A total of 53 rats was kill-trapped and target tissues were analysed with molecular techniques. We observed the absence or very low prevalence of Anaplasma spp. , while Babesia was found in rats from all locations, marking the first recorded instance of Babesia divergens in wild rats. Data from Pianosa strongly suggest the presence of an autochthonous Leishmania infantum cycle in the Tuscan archipelago islands. Neospora caninum was absent from all islands, even in areas where dogs, the main reservoirs, were present. Toxoplasma gondii was only recorded on the Pontine Islands, where genotyping is needed to shed light on infection dynamics. This study confirms that invasive species, such as rats, may be responsible for maintaining an increased parasitological threat to fauna and human communities in certain ecosystems.
EFFICIENT APPROACH OF CARDIAC CATHETERIZATION IMAGE ENHANCEMENT

Cardiac catheterization is the process of inserting a tube called a catheter into the heart through an artery such as the femoral artery or aortic artery to reach the left ventricle of the heart or coronary arteries for diagnostic purposes such as ventricular injection left or coronary arteries that can facilitate X-ray vision or the introduction of therapeutic equipment. Image enhancement will be represented as one of the main areas of interest of most of researchers. For human interpretation the subjective quality of images is so important. Thus different image enhancement techniques have been used to provide a better diagnosis. The aim of this paper is how to enhance the visualization of the cardiac image to be more suitable to the doctor in order to make a correct decision for the patient. This implemented system can be divided into many steps including preprocessing, enhancement and decision making. The focus of this research is on how to improve the features of the image so as to be clear to the doctor. Two types of filters (Gaussian and Average) were applied and then the results were compared for both types. The Gaussian filter showed better results in improving the image parameters.
Influence of hydromechanical heterogeneities of fault zones on earthquake ruptures

SUMMARY Fluid pressurization, a possible mechanism of fault weakening, exerts a critical control on earthquake rupture in the upper crust. One cause for this control is the presence of high fluid pressures inside the fault zone. However, the precise mechanisms relating high fluid pressures and fault rupture remain unclear. Here, we use 2-D hydromechanical models to show that effective stress changes induced by a transient pulse of fluid pressure along a fault zone with spatially variable material properties—conditions that are representative of natural faults—can be sufficient to produce large slip in the fault core, and fracturing in the surrounding damage volume. Rupture properties outside the limited source region are examined for ranges of values of the degree of material contrast across the fault. Our results indicate that the slip dimension is highly influenced by the contrasts of permeability and rigidity across the fault zone components, from the fault core through the various subzones of the fractured damage zone and to the less fractured host rock. Moreover, high fluid pressures may also develop locally off the narrow fault core, preferentially into the more permeable and less rigid parts of the damage zone, where the deformation is plastic, highlighting a possible mechanism for off-fault rupture. Finally, on faults with hydromechanical heterogeneities at the scale of the internal structure, the fluid pressure and rupture are highly asymmetric with propagation in a preferred direction, that is the more permeable and compliant material of the fault zones.
Alteration in Community Dynamics of Chaetoceros curvisetus and Bacterioplankton Communities in Response to Surfactin Exposure

The use of surfactin is a promising method to mitigate algal blooms. However, little is known about surfactin toxicity to algae and bacterioplankton. Here, we treated Chaetoceros curvisetus, the dominant species of algal blooms in the East China Sea, with 0, 0.5, 1, 2, 3, and 4 mg/L of surfactin for 96 h to investigate temporal variability. Our results showed that low concentrations of surfactin (<2 mg/L) changed the cell morphology of C. curvisetus, and higher concentrations (>3 mg/L) had lethal effects. Meanwhile, we examined the community dynamics of the free-living (FL, 0.22–5 μm) and particle-attached (PA, >5 μm) bacterioplankton of C. curvisetus in response to different surfactin concentrations and cultivation periods. Both PA and FL bacterioplankton were mainly composed of Proteobacteria, Actinobacteria, and Bacteroidetes, while FL bacterioplankton were more diverse than PA bacterioplankton. The variations of FL and PA bacterioplankton were significantly constrained by the surfactin concentration. Surfactin changed the lifestyle of some bacterioplankton from FL to PA, which mainly belonged to abundant bacterioplankton. Furthermore, we identified some surfactin-sensitive species/taxa. Our study will help enhance the ability to predict marine microbial responses under the effect of surfactin, providing a research foundation for this new harmful algal bloom mitigation method.
Morphology and Chemical Messenger Regulation of Echinoderm Muscles

Simple Summary Various physiological activities of organisms, including movement, feeding, reproduction, breathing, excretion, etc., all require the participation of their neuromuscular systems. Echinoderms, a phylum closely related to chordates, possess a well-differentiated but simpler muscular system, which provides a great opportunity to trace the evolutionary origins of the vertebrate muscular system. Here, we review the morphology of different musculatures and the effects of different neurotransmitters and neuropeptides involved in muscle regulation in echinoderms. In addition, we highlight the potential molecular mechanisms underpinning the action of these chemical messengers on echinoderm muscles. Abstract The muscular systems of echinoderms play important roles in various physiological and behavioral processes, including feeding, reproduction, movement, respiration, and excretion. Like vertebrates, echinoderm muscle systems can be subdivided into two major divisions, somatic and visceral musculature. The former usually has a myoepithelial organization, while the latter contains muscle bundles formed by the aggregation of myocytes. Neurons and their processes are also detected between these myoepithelial cells and myocytes, which are capable of releasing a variety of neurotransmitters and neuropeptides to regulate muscle activity. Although many studies have reported the pharmacological effects of these chemical messengers on various muscles of echinoderms, there has been limited research on their receptors and their signaling pathways. The muscle physiology of echinoderms is similar to that of chordates, both of which have the deuterostome mode of development. Studies of muscle regulation in echinoderms can provide new insights into the evolution of myoregulatory systems in deuterostomes.
History of Maturation of Prokaryotic Molybdoenzymes—A Personal View

In prokaryotes, the role of Mo/W enzymes in physiology and bioenergetics is widely recognized. It is worth noting that the most diverse family of Mo/W enzymes is exclusive to prokaryotes, with the probable existence of several of them from the earliest forms of life on Earth. The structural organization of these enzymes, which often include additional redox centers, is as diverse as ever, as is their cellular localization. The most notable observation is the involvement of dedicated chaperones assisting with the assembly and acquisition of the metal centers, including Mo/W-bisPGD, one of the largest organic cofactors in nature. This review seeks to provide a new understanding and a unified model of Mo/W enzyme maturation.
Social Trading, Communication, and Networks

Social trading is an emerging market in the sharing economy, allowing investors (followers) to duplicate the trades of other investors (leaders) in real time. We analyze the formation and dissolution of links in a large social trading network. Such networks are characterized by the rapid dissolution of links, increasing the importance of studying network dissolution. We investigate how social communication, along with financial performance and demographics, affects dynamic network evolution. We show that different types of social communication, such as posts and comments, have different implications for link formation and dissolution. Moreover, we find financial performance to be highly important for link formation and dissolution, whereas demographic characteristics are only relevant for link formation. In social trading, the extreme flexibility of followers in dissolving links and thereby, terminating their relationship instantaneously brings about large income uncertainty for leaders. Thus, a thorough understanding of network evolution and its determinants is crucial for leaders. Our results can provide guidance on when and how to communicate with followers. As vocal leaders on social media may exert a significant influence on financial markets—as demonstrated by recent the GameStop frenzy—a better understanding of the evolution of investment networks is also important for regulators.