Miracle-dz/UniFAR-FTUs huggingface dataset:
Plankton Diatoms in the Eastern Caribbean Sea

Marine pelagic diatoms from offshore waters in the eastern part of the Caribbean Sea were examined. The material collected in the duration from Dec. 1955 to Feb. 1956 showed that the area rich in diatoms was confined only in neritic waters off Venezuela. Eighty-three diatoms in thirty genera, including 22 species of Chaetoceros, 12 of Rhizosolenia and 11 of Coscinodiscus, appeared under the microscope. Descriptions are also made about infraspecific forms of three species of Chaetoceros, i.e., Ch. lorenzianus form singularis f. nov., Ch. didymus form singularis f. nov., Ch. affinis form singularis subform extremis subf. nov. and subform ferox subf. nov., which seem to be new to the science. Pelagic diatoms in the Caribbean Sea are interesting subjects for the writer to study, because of biogeographical significance of the area as a tropic coastal sea neighboring the Atlantic. In addition to the location of the Sea, there are not so many papers concerning the plankton of the Caribbean waters, especially taxonomic works on diatoms. Last century, GREVILLE (1857) and CLEVE (1878) investigated diatoms from the West Indian Archipelago, and recently SUAREZ-CAABRO (1959) made reference to some neritic diatoms of the waters around Isla de Pinos, Cuba, which were identified by F. MULLER-MELCHERS. However, the pelagic diatom flora in offshore waters has not yet been sufficiently studied. Fortunately, a series of microplankton catches was obtained around the eastern part of the Caribbean Sea during a cruise of the 'Boso-maru,' Japanese research boat which belongs to the Chiba Prefectural Government, in connection with the survey work for tuna fishing in the Sea in 1955 and '56. The material was handed over to the writer at his disposal by courtesy of Mr. Masahiro NAGANO, technical expert of the Chiba Prefectural Government. In the present paper, the writer reports the results of his study on the material about distribution of diatom communities in the Sea, with reference to main ingredients of the pelagic flora. He also makes descriptions of some single cell forms of species of Fig. 1. Map to show stations and the settling volume of microplankton catches in the eastern Caribbean Sea. •›-less than 4 cc. •œ-more than 4 cc. * Received Oct. 21, 1960. * * Tokai Regional Fisheries Research Laboratory, Tsukishima, Tokyo.
L'uso di Internet nell'informazione sanitaria.

Internet is one of the most common means of searching for health information even by youth. Within the Patient's Library service of the Centro di Riferimento Oncologico, Aviano (PN) a survey was undertaken among high school students to describe the relationship that 585 teenagers have with Internet and health information available online. Students know and use Internet to find useful information and also health information; only a small percentage consider themselves satisfied with the information found in this matter; the majority of them would like to improve their ability. An important objective on which health institutions, schools and students should work together is getting the students to know how to gain access to a wide range of information sources and to assess the quality of health information.
Educational benefits of digital game-based learning: K-12 teachers' perspectives and attitudes

This study aims to examine K-12 teachers’ perspectives and attitudes toward the benefits of adopting and integrating digital game-based learning in education. The study involves 158 teachers of primary education and secondary education who filled in a 37-question questionnaire. Overall, teachers had significantly positive perspectives and attitudes. In contrast to their age and level of education in which they taught, teachers’ educational background, gender, and teaching experience were correlated with their responses. Based on the results, most teachers were familiar with digital games and their use in educational settings and had previous experience in adopting digital game-based learning in their classrooms. The lack of equipment, digital skills, and training emerged as the primary challenges that they face. Concerning its general benefits in education, digital game-based learning emerged as an effective educational approach that can be applied in various subjects and offer interactive and student-centered learning environments. Regarding the benefits it can yield for teachers, digital game-based learning emerged as a useful educational approach that can facilitate and enrich the teaching process as it improves teachers’ communication and digital skills and enables them to create motivational virtual learning environments that would consciously engage and encourage students to actively participate in educational activities and that would promote collaborative learning. In terms of the educational benefits that it can yield for students, digital game-based learning was evaluated as a valuable pedagogical approach that can enhance students’ cognitive and social-emotional development, enhance their digital competencies, improve their learning motivation, engagement, and achievements, and increase their joy, autonomy, critical thinking, creativity, and imagination. Finally, digital game-based learning emerged as an effective educational approach that can be used at all educational levels and in both face-to-face and online learning to meet the new educational requirements, provide benefits for teachers and students, and improve the overall quality of education.
Application of real-time polymerase chain reaction to quantitate induced expression of interleukin-1beta mRNA in ischemic brain tolerance.

A short duration of ischemia (i.e., ischemic preconditioning) was shown to result in significant tolerance to subsequent ischemic injury. Since previous reports suggest that interleukin-1beta (IL-1beta) may be involved in both ischemic damage and neuroprotection, the present work examined the expression of IL-1beta mRNA in cortical brain tissue after an established preconditioning (PC) stimulus known to produce significant brain tolerance to focal stroke after 1-7 days. Significant induction of IL-1beta mRNA was observed in the ipsilateral cortex at 6 hr (87+/-9 copies of the mRNA per microgram of brain tissue compared to 16+/-5 copies in sham-operated samples, P < 0.001, n = 4) and 8 hr (46+/-4 copies, P < 0.01, n = 4) after PC by means of real-time Taqman polymerase chain reaction (PCR). The peak expression of IL-1beta mRNA after PC was significantly (P < 0.01) lower than that after permanent occlusion of the middle cerebral artery (MCAO), i.e., 87+/-9 and 546+/-92 copies of RNA per microgram tissue at peak levels for PC and focal stroke, respectively. Immunohistochemistry studies revealed a parallel induction of IL-1beta in the ipsilateral cortex after PC. The maximal expression of IL-1beta was observed during the first week post-PC, showing marked parallelism with the duration of ischemic tolerance. These data suggest that the significant but low levels of IL-1beta induction after PC may contribute to ischemic brain tolerance.
Omics-Based Approaches for the Characterization of Pompe Disease Metabolic Phenotypes

Simple Summary Pompe disease is produced by an enzymatic deficiency that leads to aberrant accumulation of glycogen in in multiple tissues, mainly muscle, causing progressive heart, respiratory and motor failure. Dysregulations observed in these patients are derived from glycogen accumulation but also to different secondary abnormalities. The characterization of the metabolic profile associated with this disease is a valuable approach to gain a larger view of all the metabolic dysregulations caused by the disease, and its potential correlation with clinical progression and response to therapies. This article describes the metabolic alterations reported to be significantly altered in Pompe disease patients in recent years. From a clinical perspective, this information could contribute to guide in the diagnosis, evaluation of disease severity, treatment decision and monitoring of Pompe disease patients. Abstract Lysosomal storage disorders (LSDs) constitute a large group of rare, multisystemic, inherited disorders of metabolism, characterized by defects in lysosomal enzymes, accessory proteins, membrane transporters or trafficking proteins. Pompe disease (PD) is produced by mutations in the acid alpha-glucosidase (GAA) lysosomal enzyme. This enzymatic deficiency leads to the aberrant accumulation of glycogen in the lysosome. The onset of symptoms, including a variety of neurological and multiple-organ pathologies, can range from birth to adulthood, and disease severity can vary between individuals. Although very significant advances related to the development of new treatments, and also to the improvement of newborn screening programs and tools for a more accurate diagnosis and follow-up of patients, have occurred over recent years, there exists an unmet need for further understanding the molecular mechanisms underlying the progression of the disease. Also, the reason why currently available treatments lose effectiveness over time in some patients is not completely understood. In this scenario, characterization of the metabolic phenotype is a valuable approach to gain insights into the global impact of lysosomal dysfunction, and its potential correlation with clinical progression and response to therapies. These approaches represent a discovery tool for investigating disease-induced modifications in the complete metabolic profile, including large numbers of metabolites that are simultaneously analyzed, enabling the identification of novel potential biomarkers associated with these conditions. This review aims to highlight the most relevant findings of recently published omics-based studies with a particular focus on describing the clinical potential of the specific metabolic phenotypes associated to different subgroups of PD patients.
Utilisation des corrélations de bruit micro-sismique pour l'analyse des propriétés du champ d'onde et l'imagerie crustale

Depuis 10 ans, l'imagerie de la croute par correlations de bruit a ete utilisee dans differentes regions. Ces etudes selectionnent les correlations sur la base du rapport signal sur bruit des signaux utilises. Selon la theorie, les correlations convergent vers les fonctions de Green en temps positif et negatif si la distribution des sources est homogene. Seule la verification de la parite des correlations permet d'evaluer la qualite de la convergence. Un ecart a la parite fournit des informations sur la synchronisation des horloges des stations et la distribution des sources de bruit. Ainsi, l'analyse des variations de temps de propagation des parties causale et acausale nous a permis d'identifier des erreurs d'horloge pour des stations du jeu de donnees SIMBAAD. Une analyse de polarisation et l'utilisation de la formation de voie sur les correlations ont permis de localiser des sources de bruit d'ondes P en ocean profond. Dans la region Egee-Anatolie, a 15s de periode la distribution des sources de bruit est homogene et elle devient heterogene a plus longues periodes. Nous utilisons la propriete de symetrie pour selectionner le temps de propagation des ondes de surface (Love et Rayleigh) les plus representatifs des fonctions de Green. L'inversion de ces temps de propagation permet de reconstruire les variations laterales des vitesses de groupe a toutes les frequences. Les courbes de dispersion locales obtenues sont inversees pour construire un modele en 3D de la vitesse des ondes S des la croute pour la region Egee-Anatolie. Les variations laterales de la vitesse et l'epaisseur de la croute sont coherentes avec la structure geologique connue, avec les resultats d'autres etudes geophysiques et avec la deformation recente.
Peningkatan Hasil Belajar Dengan Model Problem Based Learning di SMKN 9 Pinrang

Penelitian ini adalah penelitian tindakan kelas, yang bertujuan untuk meningkatkan hasil belajar siswa dengan penerapan model pembelajaran PBL ( Problem Based Learning) sebagai usaha untuk meningkatkan pembelajaran di SMKN 9 PINRANG pada mata pelajaran dasar desain grafis tahun pelajran 2020/2021. Penelitian ini dilaksanakan selama tiga siklus dengan proses penelitian : merencanakan tindakan, melaksanakan tindakan siklus I, siklus II dan siklus III, mengadakan pengamatan selama berlangsungnya pembelajaran pada tiga siklus, mengadakan evaluasi pada tiap akhir siklus, menganalisis data hasil evaluasi dan hasil pengamatan serta mengadakan refleksi berdasarkan hasil analisis dan tanggapan siswa. Hasil penelitian ini menunjukkan bahwa nilai meningkat hasil belajar siswa dimulai dari siklus I 80%, Siklus II 90% dan siklus III 100% berarti ada peningkatan pembelajaran. Dengan demikian, hasil penelitian ini dapat diperoleh gambaran bahwa Penerapan Model Pembelajaran Problem Based Learning sebagai usaha meningkatkan hasil belajar siswa kelas X.MM1 SMKN 9 Pinrang pada Mata pelajaran Dasar Desain Grafis dapat ditingkatkan dengan menggunakan penerapan model pembelajaran Problem Based Learning
ACR–ASNR–ASSR–SIR–SNIS PRACTICE PARAMETER FOR THE PERFORMANCE OF IMAGE-GUIDED EPIDURAL STEROID INJECTION

1 Epidural Steroid Injection The American College of Radiology, with more than 30,000 members, is the principal organization of radiologists, radiation oncologists, and clinical medical physicists in the United States. The College is a nonprofit professional society whose primary purposes are to advance the science of radiology, improve radiologic services to the patient, study the socioeconomic aspects of the practice of radiology, and encourage continuing education for radiologists, radiation oncologists, medical physicists, and persons practicing in allied professional fields.
A multi-objective consensus community detection algorithm based on Whale algorithm

Community detection in dynamic network is an essential topic in recent years that faces challenging tasks. In this paper, we introduce the concept of consensus community and propose a consensus community detection algorithm based on whale algorithm. The purpose of consensus community is to find knowledge from the network of previous time step and brought the knowledge to the network of successive time. Experimental results on artificial and real-world networks show that our method is more accurate and robust than some other state-of-art algorithms.
Melons as Lemons : Asymmetric Information , Consumer Learning and Seller Reputation

A key problem in developing countries is the lack of high quality brands. I designed an experiment to understand this phenomenon in a setting that features typical market conditions in a developing country: the retail watermelon market in a major Chinese city. I begin by demonstrating empirically that there is substantial asymmetric information between sellers and buyers on sweetness, the key indicator of quality for watermelons, yet sellers do not sort and price watermelons by quality. I then randomly introduce one of two branding technologies into 40 out of 60 markets—one sticker label that is widely used and often counterfeited and one novel laser-cut label. I track sellers’ quality, pricing and sales over an entire season and collect household panel purchasing data to examine the demand side’s response. I find that laser branding induced sellers to provide higher quality and led to higher sales profits, establishing that reputational incentives are present and can be made to pay. However, after the intervention was withdrawn, all markets reverted back to baseline. To rationalize the experimental findings, I build an empirical model of consumer learning and seller reputation. The structural estimates suggest that consumers are hesitant to upgrade their perception about quality under the existing branding technology, which makes reputation building a low return investment. While the new technology enhances consumer learning, the resulting increase in profits is not su cient to cover the fixed cost of the technology for small individual sellers. Counterfactual analysis shows that information frictions and fragmented markets lead to significant under-provision of quality. Third-party interventions that subsidize initial reputation building for sellers could improve welfare. ⇤Department of Economics, Massachusetts Institute of Technology. E-mail: jieb@mit.edu. I am extremely grateful to my advisors Benjamin Olken, Abhijit Banerjee, Robert Townsend and Nikhil Agarwal for their continuous encouragement and guidance over the course of this project. I also thank David Atkin, Esther Duflo, Glenn Ellison, Robert Gibbons, German Sergio Gieczewski, Seema Jayachandran, Yan Ji, Siyuan Liu, Rocco Macchiavello, Yuhei Miyauchi, Xiaosheng Mu, Ariel Pakes, Parag Pathak, Frank Schilbach, Maheshwor Shrestha, Paulo Somaini, Tavneet Suri, Jean Tirole, Juuso Toikka, Juanjuan Zhang, Hongkai Zhang and participants of the development seminar, development lunch, and IO lunch at MIT, and the 2015 NEUDC conference for helpful discussions and feedback. Funding for this project was generously provided by the Weiss Family Fund, the Abdul Latif Jameel Poverty Action Lab, and the George and Obie Shultz Fund. All errors are my own.
Response of Acacia Species to Soil Disturbance by Roadworks in Southern New South Wales, Australia

Heavy machinery is regularly used throughout the world to maintain infrastructure corridors. The purpose of this study is to investigate the response of roadside populations of three Acacia shrub species to soil disturbance from roadworks. Results were highly variable. However, resprouting and seedling emergence led to a 6.2 percent population increase at four road reserves. Two years after grading, there was significant resprouting of A. decora and resprouts reached a mean height of 72 cm. One year after disturbance, 71 percent of A. decora resprouts flowered and 49 percent also set viable seed. In contrast, there was patchy seedling emergence of A. pycnantha and A. montana. These results show that grading of roadsides appears to favor plants with strong resprouting ability and that the scale of response depends on the plants life-history attributes and the prevailing disturbance regime. Further studies of individual plant responses to soil disturbance can only better our understanding of plant dynamics in road and other transportation corridors.
Endovascular Procedures for Intracranial Arterial Disease ( Atherosclerosis and Aneurysms ) Description

Intracranial arterial disease includes thromboembolic events, vascular stenoses, and aneurysms. Endovascular techniques have been investigated for treatment of intracranial arterial disease, as an alternative to intravenous TPA and supportive care for acute stenosis, and as an alternative to risk factor modification for chronic stenosis. For cerebral aneurysms, stent-assisted coiling has been evaluated as an alternative to endovascular coiling in patients whose anatomy is not amenable to simple coiling.
Physics Simulations in the Dash Hypermedia System

The objective of this project was to develop a new physics simulation platform that is integrated in the Dash hyper-media system and addresses limitations of existing physics simulation platforms. The new platform has seven simulation types and three interaction modes to target different use cases. Overall, this project represents a promising start for an easy-to-use physics simulation platform that can be integrated in students’ typical workflow and offers different interaction modes that allow for both physically correct animation and animation based on student inputted values.
Fast Approximate Inference for Arbitrarily Large Semiparametric Regression Models via Message Passing

ABSTRACT We show how the notion of message passing can be used to streamline the algebra and computer coding for fast approximate inference in large Bayesian semiparametric regression models. In particular, this approach is amenable to handling arbitrarily large models of particular types once a set of primitive operations is established. The approach is founded upon a message passing formulation of mean field variational Bayes that utilizes factor graph representations of statistical models. The underlying principles apply to general Bayesian hierarchical models although we focus on semiparametric regression. The notion of factor graph fragments is introduced and is shown to facilitate compartmentalization of the required algebra and coding. The resultant algorithms have ready-to-implement closed form expressions and allow a broad class of arbitrarily large semiparametric regression models to be handled. Ongoing software projects such as Infer.NET and Stan support variational-type inference for particular model classes. This article is not concerned with software packages per se and focuses on the underlying tenets of scalable variational inference algorithms. Supplementary materials for this article are available online.
Improvement of Remote sensing image target detection algorithm based on YOLO V5

YOLO V5 algorithm is the current target detection algorithm, but the accuracy of target boundary regression is relatively low, and it cannot be used in scenarios with high requirement of prediction frame intersection ratio. Therefore, this paper proposes an improved YOLO V5 algorithm with high accuracy of target frame and fast convergence of model. The algorithm can avoid the loss of shallow semantic information, deepen the pyramid depth and increase the detection layer by using cross-hierarchy method and multiple feature fusion. By reducing network computation and parameter number, network lightweight processing is realized, and real-time performance loss caused by model complexity is avoided.
A Fast Image Matching Method Based on Improved SURF

In order to solve the problems of low matching accuracy, slow speed and high system overhead in image matching methods, a rotation binary descriptor construction method based on Speed Up Robust Features (SURF) feature point detection is designed by using different Fast Library for Approximate Nearest Neighbors (FLANN) parameters and the filtering mechanism to screen out wrong matches according to the types of feature descriptors constructed in different feature extraction algorithms. This method ensures scale and rotation invariant while simplifying the representation of feature descriptors and speeding up the calculation speed in the initial stage of matching by combining the binary characteristics of descriptors. Finally, the Hamming distance is used as the filtering mechanism to improve the success rate of the final matching. The experimental results show that the accuracy of image matching is improved by 1.5% and the matching time is improved by 0.116s, while the robustness of the image to noise and rotation is ensured.
Landslide susceptibility modeling and mapping at Dien Bien province, Vietnam using Bagging based MLP neural network

In this article, the main aim is to build landslide susceptibility map at the Dien Bien province (Vietnam) using a hybrid machine learning model including BG-MLP which is a hybridization of Bagging and Multilayer Perceptron (MLP) neural networks. For this purpose, 665 past landslide events together with 665 non-landslide locations and 10 landslide influencing parameters including geology, normalized difference vegetation index (NDVI), distance to roads, distance to rivers, topographic wetness index (TWI), slope, curvature, aspect, distance to faults and elevation were collected and used for generation of datasets for model’s development and validation. To validate the predictive capability of the model, area under the ROC curve and other popular statistical indices were used. Results presented that BG-MLP (AUC = 0.81) has a good performance in modeling and mapping landslide susceptibility at the study area, especially its performance is better than single MLP model (AUC = 0.78). Thus, it can be concluded that BG-MLP is powerful tool that can be employed for assessment of susceptibility of landslides in other landslide prone regions of the world. Map of landslide susceptibility created from this study would be useful for decision making and land use planning in reducing the harmful impacts of landslides.