Miracle-dz/UniFAR-FTUs huggingface dataset:
Studio preliminare sulla valutazione indiretta delle fibre inorganiche respirabili aerodisperse in Valle di Susa (Piemonte-Alpi Occidentali)

The presence of asbestos in serpentinite rocks of the Western Alps has been known for a century. Further investigations have revealed the presence of nine fibrous minerals, besides the asbestos tremolite, actinolite and chrysotile, some of them in high amount. All these fibres are carried away over a long distance both by the wind and by human activities. Mineral fibres are therefore a constant component of environmental background; the potential effects on human health of this kind of exposition, generally at low dose, are currently investigated. The assessment of the breathable fibrous minerals fraction (bfmf) can be done on animals called "animal sentinel system» (SSA) as an alternative to humans. Animal studies are free from some of the factors that blur the evidence (such as occupational risk factors and lifestyle) and yield information about environmental exposure only. This study concerns the assessment of bfmf in lungs of cattle from the Susa Valley, an area of the Piedmont Region (NW Italy) underlain by rocks bearing asbestos tremolite, actinolite and chrysotile. The data are compared with that of lungs of cattle from the Asti province, an area free of serpentinite, and therefore chosen as control case. Samples have been suitably prepared and then examined by optical microscopy (OM) to detect ferruginous bodies (Fb) and by Scanning Electron Microscopy (SEM) with annexed Energy Dispersive Spectrometer (EDS) to identify and quantify inorganic fibres. OM data show that Fb are present in both animal groups, but are more frequent in the one from Asti. The presence of inorganic fibres (mainly silicates) has been detected by SEM-EDS throughout the samples from the Susa Valley, as against only a few from Asti. The set of data, though small, makes it clear that the Susa Valley samples mainly contain fibres from natural sources (tremolite and actinolite). Similar quantities of tremolite asbestos were met in NE Corsica (DUMORTIER et alii, 2002), an area with extensive outcrop of serpentinite bearing asbestos tremolite and chrysotile. Our results show that bfmf assessment in lung tissues of SSA can give information about the local environmental background (itself dependent on topographic, geological, climatic and anthropic characteristics). This method also highlights the geology dependent difference of mineralogical burden in geologically different areas. The two techniques provide useful information, both for health and environmental investigations. Research aimed at identifying inorganic fibres in lungs by micro-Raman spectroscopy is currently under way.
Digitale Strategien in der Lehre Strategies of Digitized Learning

Zusammenfassung Die Entwicklung digitaler Strategien in der Lehre beruht auf den technologischen Fortschritten der letzten Jahrzehnte, aber auch auf der Motivation, ein didaktisches Konzept verstärkt auf den Lernenden zu zentrieren. Aus verfügbaren Daten der deutschen Hochschulmedizin ergibt sich das Bild, dass in der Medizin ganz allgemein und speziell in der HNO-Heilkunde digitale Lehrkonzepte aktuell noch eine untergeordnete Rolle spielen. Durch Erhebung eigener Daten konnten wir zeigen, dass die Studierenden in der HNO-Heilkunde in der Mehrheit auf durch den Dozenten ausgegebene Materialien als einzige Lernquelle zurückgreifen. Die Anwendung fundierter digitaler Lehrstrategien bietet daher, insbesondere fachbezogen für die HNO-Heilkunde, besondere Chancen, u. a. um dem Überangebot von Informationen aus teils unklaren Quellen im Internet entgegenzutreten. Der mögliche Digitalisierungsgrad der Lehre reicht heute von digitalen Serviceangeboten über punktuelle Angebote klassischer Lehrkonzepte und Blended Learning bis hin zum volldigitalen Studium. Die Attraktivität der curricularen Integration digitaler Lehrstrategien beruht dabei weniger auf der Nutzung rein technischer Fortschritte, sondern vielmehr auf den Möglichkeiten der Anwendung innovativer Curricula und neuer didaktischer Konzepte. In Abhängigkeit vom beabsichtigten Lehrzweck werden insbesondere dem Flipped Classroom und der digitalisierten Realität großes Potenzial zugeschrieben, während mobiles Lernen sich in der Praxis bereits individuell etabliert hat. Die Erprobung und Evaluierung digitaler Lehrinnovationen für konkrete Szenarien gehört aktuell zu den wichtigen wissenschaftlichen Herausforderungen digitaler Lehrkonzepte. Der flächendeckenden Etablierung digitaler Lehre stehen heute weniger technische Voraussetzungen, sondern vielmehr fehlende Finanzierungsmöglichkeiten im Wege, da Förderungen derzeit überwiegend projektgebunden stattfinden, bei dauerhafter Umsetzung jedoch regelmäßige Kosten vorhanden sind. Zur Unterstützung dieser vielversprechenden Lehrformen könnte die Förderung der Einrichtung von Abteilungen für digitale Lehre mit Bereitstellung von entsprechenden Hard- und Softwarelösungen an den Universitäten wesentlich beitragen. Durch die Bildung von Kooperationen zur Nutzung solcher digitalen Plattformen ergäbe sich eine hohe Effizienz in der Verbreitung unter gleichzeitiger Ausnutzung von Sparpotenzialen.
A new dynamical mechanism for major climate shifts

We construct a network of observed climate indices in the period 1900–2000 and investigate their collective behavior. The results indicate that this network synchronized several times in this period. We find that in those cases where the synchronous state was followed by a steady increase in the coupling strength between the indices, the synchronous state was destroyed, after which a new climate state emerged. These shifts are associated with significant changes in global temperature trend and in ENSO variability. The latest such event is known as the great climate shift of the 1970s. We also find the evidence for such type of behavior in two climate simulations using a state‐of‐the‐art model. This is the first time that this mechanism, which appears consistent with the theory of synchronized chaos, is discovered in a physical system of the size and complexity of the climate system.
Computer-aided diagnostic system based on deep learning for classifying colposcopy images

Background Colposcopy is widely used to detect cervical cancer, but developing countries lack the experienced colposcopists necessary for accurate diagnosis. Artificial intelligence (AI) is being widely used in computer-aided diagnosis (CAD) systems. In this study, we developed and validated a CAD model based on deep learning to classify cervical lesions on colposcopy images. Methods Patient data, including clinical information, colposcopy images, and pathological results, were collected from Qilu Hospital. The study included 15,276 images from 7,530 patients. We performed two tasks in this study: normal cervix (NC) vs. low grade squamous intraepithelial lesion or worse (LSIL+) and high-grade squamous intraepithelial lesion (HSIL)− vs. HSIL+. The residual neural network (ResNet) probability was calculated for each patient to reflect the probability of lesions through a ResNet model. Next, a combination model was constructed by incorporating the ResNet probability and clinical features. We divided the dataset into a training set, validation set, and testing set at a ratio of 7:1:2. Finally, we randomly selected 300 patients from the testing set and compared the results with the diagnosis of a senior colposcopist and a junior colposcopist. Results The model that combines ResNet and clinical features performs better than ResNet alone. In the classification of NC and LSIL+, the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 0.953, 0.886, 0.932, 0.846, 0.838, and 0.936, respectively. In the classification of HSIL− and HSIL+, the AUC, accuracy, sensitivity, specificity, PPV, and NPV were 0.900, 0.807, 0.823, 0.800, 0.618, and 0.920, respectively. In the two classification tasks, the diagnostic performance of the model was determined to be comparable to that of the senior colposcopist and exhibited a stronger diagnostic performance than the junior colposcopist. Conclusions The CAD system for cervical lesion diagnosis based on deep learning performs well in the classification of cervical lesions and can provide an objective diagnostic basis for colposcopists.
Increased expression of the amyloid precursor β‐secretase in Alzheimer's disease

β‐Secretase cleavage represents the first step in the generation of Aβ polypeptides and initiates the amyloid cascade that leads to neurodegeneration in Alzheimer's disease. By comparative Western blot analysis, we show a 2.7‐fold increase in protein expression of the β‐secretase enzyme BACE in the brain cortex of Alzheimer's disease patients as compared to age‐matched controls. Similarly, we found the levels of the amyloid precursor protein C‐terminal fragment produced by β‐secretase to be increased by nearly twofold in Alzheimer's disease cortex.
Late Pleistocene glaciations at Lake Donggi Cona, eastern Kunlun Shan (NE Tibet): early maxima and a diminishing trend of glaciation during the last glacial cycle

The Burhan Budai Shan in NE Tibet represents a key location for examining the variable influence of the mid‐latitude westerly and monsoonal circulations on late Quaternary glaciations in this sector of the Tibetan Plateau. Our study investigates the glacial history of mountains near Lake Donggi Cona (35°17′N, 98°33′E) using field mapping in combination with 10Be surface exposure dating and numerical reconstructions of former glacial equilibrium line altitudes (palaeo‐ELA). A set of 23 new exposure ages, collected from moraines in four glacial valleys, ranges from 45 to 190 ka, indicating ice expansion during the early and middle part of the last glacial cycle, and during the penultimate and possibly an earlier Mid‐Pleistocene glaciation. Ice advances reaching 12–15 km in length occurred at around 190–180 ka (≥MIS 6), between 140–100 ka (late MIS 6/MIS 5), and 90–65 ka (late MIS 5/early MIS 4), with a maximum ELA depression of 400–500 m below the estimated modern snowline. Exposure ages from the valley headwaters further indicate a small glaciation between c. 60–50 ka (late MIS 4/early MIS 3), which was essentially restricted to the cirque areas. Significantly, we find no evidence for any subsequent glaciation in the area during MIS 2 or the Holocene period. These results indicate a diminishing trend of glaciation in the region since at least MIS 4, and corroborate the case of a ‘missing LGM’ in the more interior parts of the northeastern Tibetan Plateau. The emerging pattern suggests that the most favourable conditions for glaciation during the Late Pleistocene correspond to periods of relatively moderate cooling combined with an intermediate or rising East Asian monsoon strength.
Acta Polytechnica

General energy demand is continuously increasing, thus the energy generating assets need to be optimised for higher efficiency. Wind turbines are no exception. Their maximum efficiency can be determined on a theoretical basis. The limit is approached by researches day by day, utilizing the latest developments in airfoil design, blade structure and new and improved ideas in conventional and unconventional wind turbine layouts. In this paper, we are reviewing the conventional and unconventional wind turbines and their place in smart cities. Then, an unconventional wind turbine design, the CO-DRWT (counter-rotating dual rotor wind turbine) is analysed with a CFD (computational fluid dynamics) code, varying the axial and radial distances between the two turbines. After the simulations, the power coefficients for the different turbine configurations is calculated. At the end of this paper, the simulations results are summarized and consequences are drawn for the CO-DRWT layouts.
An Efficient Image Segmentation Technique by Integrating FELICM with Negative Selection Algorithm

Segmentation is a efficient technique of dividing the image into different regions or segments. Most of the researchers took clustering as the best method of segmenting an image. In clustering we try to increase the similarity within a same class and decrease the similarity between the classes. Many clustering algorithms were developed like FCM, FLICM and FELICM which are considered as the best algorithms to cluster the data. In our paper, we combine FELICM (Fuzzy Edge and Local Information C-Mean) with the negative selection algorithm. Negative selection algorithm is an evolutionary method which is based on artificial immune systems. The proposed method result shows us high accuracy results and even solves the problem of over segmentation.
Building from scratch? An “inner connectivity” framework for soft urban tourism development

Purpose The purpose of this paper is to define a framework for urban tourism development, providing a rationale for tourism planners pursuing a competitive, sustainable and inclusive tourism destination model for urban settings. Design/methodology/approach A conceptual framework is proposed, discussed and exemplified in a specific geographical context. Findings The soft urban tourism development framework adopts a place-based approach to tourism destination building and suggests an integration method grounded in tourism urbanicity. Research limitations/implications The proposed tourism development model is based on theoretical premises. Empirical research should test the potential and pitfalls of this approach. Practical implications The proposed framework is a cognitive tool for strategy making in those cities that either need to radically re-envision city tourism or are attempting to build an urban tourism destination from scratch. Originality/value The paper contributes to the urban agenda in tourism studies. It proposes a framework emphasising the urban character of tourism and exploiting the multifunctionality of urban contexts for competitive niche tourism development.
Improved early development of porcine cloned embryos by treatment with quisinostat, a potent histone deacetylase inhibitor

Recently, the modification of the epigenetic status of somatic cell nuclear transfer (SCNT) embryos by treatment with histone deacetylase inhibitors (HDACis) has made it possible to alter epigenetic traits and improve the developmental competence of these embryos. In the current study, we examined the effects of an HDACi, quisinostat (JNJ), on the in vitro development of porcine cloned embryos and their epigenetic nuclear reprogramming status. SCNT embryos were cultured under various conditions, and we found that treatment with 100 nM JNJ for 24 h post activation could improve blastocyst formation rates compared to the control (P < 0.05). Therefore, this was chosen as the optimal condition and used for further investigations. To explore the effects of JNJ on the nuclear reprogramming of early stage embryos and how it improved cloning efficiency, immunofluorescence staining and quantitative real-time PCR were performed. From the pseudo-pronuclear to 2-cell stages, the levels of acetylation of histone 3 at lysine 9 (AcH3K9) and acetylation of histone 4 at lysine 12 (AcH4K12) increased, and global DNA methylation levels revealed by anti-5-methylcytosine (5-mC) antibody staining were decreased in the JNJ-treated group compared to the control (P < 0.05). However, JNJ treatment failed to alter AcH3K9, AcH4K12, or 5-mC levels at the 4-cell embryo stage. Moreover, JNJ treatment significantly upregulated the expression of the development-related genes OCT4, SOX2, and NANOG, and reduced the expression of genes related to DNA methylation (DNMT1, DNMT3a, and DNMT3b) and histone acetylation (HDAC1, HDAC2, and HDAC3). Together, these results suggest that treatment of SCNT embryos with JNJ could promote their developmental competence by altering epigenetic nuclear reprogramming events.
Seismic-Reflection Imaging of a Pull-Apart Sag within Tan-Lu Strike-Slip Fault Zone: Cenozoic Structure and Evolution of the Weibei Sag, Southeastern Bohai Bay Basin, China

The Weibei sag is a Cenozoic sag located within the Tan-Lu strike-slip fault zone southeast of the Bohai Bay Basin, China. The sag is controlled by two branches of the Tan-Lu right-lateral strike-slip fault zone (strike N30°E) and the Gucheng-Weihekou normal fault (strike E-W). This sag was thought to be a promising exploration area after several oil fields were found there. However, the most highly productive oil and gas wells are located on traps far from the source rocks, a situation thought to be related to the tectonic evolution of this sag. Thus, a regional study of the Weibei sag, involving three-dimensional seismic data sets and drilling cores, has been undertaken to document the sag’s evolution. Five groups of secondary faults are distinguished within the Weibei sag: WNW-, E-W-, and ENE-striking normal faults and NNW- and NNE-striking strike-slip faults. Except for the preexisting WNW-striking faults, the other four groups of faults developed under Cenozoic tectonic movement. The combined analysis, including seismic profiles, drilling cores, and structure-contour and isopach maps, reveals that the Weibei sag is a simple right-lateral pull-apart basin, associated with right-stepping of the main displacement zones of the Tan-Lu fault zone, that experienced three stages of tectonic evolution: a right-lateral pull-apart stage (66–41.2 Ma), an uplift and erosion stage (41.2–23 Ma), and a depression stage (23 Ma–present). Based on the vertical and antithetic shear restorations, the minimum amounts of right-lateral strike-slip displacement along the Tan-Lu fault zone are 5.3 and 9.5 km, respectively. Our results suggest that it is important to take tectonic evolution, such as the dip direction and activity of secondary faults, into consideration to target a potential petroleum reservoir.
Doing More with Less: The Inequitable Funding of Community Colleges. AACC Policy Brief 2010-03PBL.

ACKNOWLEDGMENTS The leadership and support of AACC President and CEO George Boggs and Senior Vice President for Government Relations and Research David Baime were invaluable to the completion of this manuscript. The views expressed in this publication are those of the author and do not necessarily represent those of Lumina Foundation for Education, its officers, or employees. Lumina Foundation for Education works to ensure that 60% of Americans are college-educated by 2025. Without the aforementioned people, this product would not have been possible. While their input was informative, I take responsibility for the final product; any errors are my own.
Soil organic carbon stock estimation in range lands of Kumrat Dir Kohistan KPK Pakistan

The present study was carried out in two grass land of Kumrat Dir Kohistan, North Hindukush regions of KPK Pakistan. Locally these two grass land are known as Roshi Dab and Bothore Dab. The area of these two Dabs is about 400 hectare. The elevation of these two Dabs ranges from 7665 feet to 7954 feet while the geographic location of the study site was N 35° 33.249’ and E 72° 12.258’. Stratified random sampling method was used for data collection. 18 soil samples were taken with the depth of 0-15 cm and 16-30 cm. The average soil pH was 5.3. The mean soil bulk density was 1.107 -g/cm3. In present study it was found that the undisturbed range land stored maximum amount of soil carbon (32.69 tons hac-1) as compare to range land near to the agriculture land (29.77 tons hac-1) Similarly the rangeland near to forest land stored 35.62 t ha-1 carbon, also stored more carbon as compare to range land near to agriculture land 29.77 t ha-1. The results of the present study confirmed that conversion of range land into agriculture land reduced the soil carbon in the study area. Key words: Carbon stocks, climate change, soil bulk density, range lands, forestry.
Compression du chiasma optique et tomographie en cohérence optique

La tomographie en coherence optique (OCT) permet de quantifier la perte axonale des voies visuelles anterieures dans de nombreuses pathologies, y compris dans les compressions chiasmatiques (1, 2). Il a ete recemment suggere que la mesure de l'epaisseur de la couche des fibres optiques (souvent appelee retinal nerve fiber layer [RNFL]) dans la region peripapillaire est un facteur pronostique de recuperation visuelle chez les patients ayant une tumeur comprimant les voies visuelles anterieures (3, 4).
A Scalable and Generalizable Pathloss Map Prediction

Large-scale channel prediction, i.e., estimation of the pathloss from geographical/morphological/building maps, is an essential component of wireless network planning. Ray tracing (RT)-based methods have been widely used for many years, but they require significant computational effort that may become prohibitive with the increased network densification and/or use of higher frequencies in B5G/6G systems. In this paper, we propose a data-driven, model-free pathloss map prediction (PMP) method, called PMNet. PMNet uses a supervised learning approach: it is trained on a limited amount of RT (or channel measurement) data and map data. Once trained, PMNet can predict pathloss over location with high accuracy (an RMSE level of $10^{-2}$) in a few milliseconds. We further extend PMNet by employing transfer learning (TL). TL allows PMNet to learn a new network scenario quickly (x5.6 faster training) and efficiently (using x4.5 less data) by transferring knowledge from a pre-trained model, while retaining accuracy. Our results demonstrate that PMNet is a scalable and generalizable ML-based PMP method, showing its potential to be used in several network optimization applications.
A Multilevel Guidance-Exploration Network and Behavior-Scene Matching Method for Human Behavior Anomaly Detection

Human behavior anomaly detection aims to identify unusual human actions, playing a crucial role in intelligent surveillance and other areas. The current mainstream methods still adopt reconstruction or future frame prediction techniques. However, reconstructing or predicting low-level pixel features easily enables the network to achieve overly strong generalization ability, allowing anomalies to be reconstructed or predicted as effectively as normal data. Different from their methods, inspired by the Student-Teacher Network, we propose a novel framework called the Multilevel Guidance-Exploration Network(MGENet), which detects anomalies through the difference in high-level representation between the Guidance and Exploration network. Specifically, we first utilize the pre-trained Normalizing Flow that takes skeletal keypoints as input to guide an RGB encoder, which takes unmasked RGB frames as input, to explore motion latent features. Then, the RGB encoder guides the mask encoder, which takes masked RGB frames as input, to explore the latent appearance feature. Additionally, we design a Behavior-Scene Matching Module(BSMM) to detect scene-related behavioral anomalies. Extensive experiments demonstrate that our proposed method achieves state-of-the-art performance on ShanghaiTech and UBnormal datasets, with AUC of 86.9 % and 73.5 %, respectively. The code will be available on https://github.com/molu-ggg/GENet.