Miracle-dz/UniFAR-FTUs huggingface dataset:
Analisi multitemporale (2006-2016) di una frana del bacino del Rio Cordon. Multi-temporal (2006-2016) analysis of a landslide of the Rio Cordon catchment.

In this paper was made a multi-temporal analysis of a landslide using remote sensing sensors. The landslide is placed in the Rio Cordon catchment for the period 2006-2016. The Cordon catchment is located in Selva di Cadore municipality (Belluno, BL) above the confluence with Fiorentina creek. The study area is located in the left hand side close to the hiking path CAI 466, with an elevation ranging between 2010 and 1800 meters above the level of the see. The event that had originated the landslide happened in 2001. The snow melted and caused a landslide that activated a mud flow along the downhill area. The mud flow stopped close to the Cordon steam area. In this thesis only the landslide area will be analyzed; the mud flow area will be not analyzed because, only for the first one mentioned, there are available multi-temporal data. This work examines sediments movements and identifies both erosional and depositional areas. This thesis is divided into four phases. In the first phase, high-resolution data of the last years were collected for the study area. Datasets from 2006, 2010, and 2011 were found and these data were made by LiDAR technique (ALS and TLS). The second phase consisted in analyzing the current condition of the study area and in producing a high-resolution database. The new database was created by using the Structure from Motion (SfM) photogrammetric technique. Using SfM technique, a geo-referred high density point cloud was produced. Each dataset was co-registered in the third phase to obtain the best overlapping for each pair of clouds. This process was made by using CloudCompare software. During the fourth phase, the co-registered point clouds were converted into DTM (Digital Terrain Model) and a DEM of Difference analysis (DoD) was done using Geomorphic Change Detection (GCD) which is a ArcGIS plugin based on Wheaton’s formula (2010). This technique allows to insert a threshold under which the DTM differences are not considered. The third and the fourth phase are strictly connected because they constitute a “try and error” process which is applied as long as a satisfying result is obtained. The results were also compared with historical photographs to check the consistency of the results. Overall, the application of this procedure was positive and the result obtained was interesting. One DoD in particular (2006-2011) showed a plausible representation of the study area evolution highlighting erosional and depositional areas which are also identified in the analysis of historical pictures. To sum up, future analyses of the study area are supposed to use different technologies and to monitor the future study area evolution with the proper devices basing on the data acquired.
SOHPIE: statistical approach via pseudo-value information and estimation for differential network analysis of microbiome data

Abstract Summary The SOHPIE R package implements a novel functionality for “multivariable” differential co-abundance network (DN, hereafter) analyses of microbiome data. It incorporates a regression approach that adjusts for additional covariates for DN analyses. This distinguishes from previous prominent approaches in DN analyses such as MDiNE and NetCoMi which do not feature a covariate adjustment of finding taxa that are differentially connected (DC, hereafter) between individuals with different clinical and phenotypic characteristics. Availability and implementation SOHPIE with a vignette is available on CRAN repository https://CRAN.R-project.org/package=SOHPIE and published under General Public License (GPL) version 3 license.
Terrestriality, bipedalism and the origin of language

Language is unique to humans, but in the context of the long time span of the human evolution it is a fairly recent innovation. All evidence suggests that human brain size and inferred cognitive and linguistic abilities reached their modern norms only within the last quarter of a million years. Foundations for human linguistic and cognitive evolution, however, lie much further back in evolutionary history. Arguments are presented suggesting that these unique human abilities are the legacy of our ancestors' terrestrial and bipedal adaptation. Both terrestriality and bipedalism are directly associated with the unique human propensy for vocal communication, including the range and quality of sound that all humans are capable of producing. Furthermore, terrestriality and bipedalism can also be directly associated with an increase in brain size and cognition. Increases in group size accompanying a committed terrestrial adaptation would have put a premium on social, or Machiavellian intelligence while bipedalism would have been associated with the increased neural circuity involved in enhanced speed and co-ordination of hand and arm movement. The constricted bipedal pelvis would have also necessited the birth of less mature offspring, exposing them to a rich environment while the brain was still rapidly growing and developping. A larger is not without its costs, however. Energetic arguments are also presented which suggest that a large brain can only evolve in concert with a change to high quality diet, resulting directly in life style changes for our early ancestors. All of these features were in place by the appearance for early Homo erectus about 1.8 million years ago and underpinned an apparentlystable hominine adaptation that lasted for well over 1.5 million years. Modern human cognitive and linguistic talents are rooted in this earlier Homo erectus adaptation and may have begun to develop in response to further need for increased group size. Both the cost and the b
Systemic Inflammatory Patterns in Ovarian Cancer Patients: Analysis of Cytokines, Chemokines, and Microparticles

Abstract Objective To compare the patterns of systemic inflammatory response in women with epithelial ovarian cancer (EOC) or no evidence of malignant disease, as well as to evaluate the profile of systemic inflammatory responses in type-1 and type-2 tumors. This is a non-invasive and indirect way to assess both tumor activity and the role of the inflammatory pattern during pro- and antitumor responses. Materials and Methods We performed a prospective evaluation of 56 patients: 30 women without evidence of malignant disease and 26 women with EOC. The plasma quantification of cytokines, chemokines, and microparticles (MPs) was performed using flow cytometry. Results Plasma levels of proinflammatory cytokines interleukin-12 (IL12), interleukin-6 (IL-6), tumor necrosis factor alpha (TNF-α) interleukin-1 beta (IL-1β), and interleukin-10 (IL-10), and C-X-C motif chemokine ligand 9 (CXCL-9) and C-X-C motif chemokine ligand 10 (CXCL-10) were significantly higher in patients with EOC than in those in the control group. Plasma levels of cytokine interleukin-17A (IL-17A) and MPs derived from endothelial cells were lower in patients with EOC than in the control group. The frequency of leukocytes and MPs derived from endothelial cells was higher in type-2 tumors than in those without malignancy. We observed an expressive number of inflammatory/regulatory cytokines and chemokines in the cases of EOC, as well as negative and positive correlations involving them, which leads to a higher complexity of these networks. Conclusion The present study showed that, through the development of networks consisting of cytokines, chemokines, and MPs, there is a greater systemic inflammatory response in patients with EOC and a more complex correlation of these biomarkers in type-2 tumors.
Inflection and derivation as traditional comparative concepts

Abstract This article revisits the distinction between inflectional and derivational patterns in general grammar and discusses the possibility that this well-known distinction is not rooted in the reality of languages, but in the Western tradition of describing languages, through dictionaries (for words, including derived lexemes) and through grammar books (where we often find tables of exemplary paradigms). This tradition has led to rather different terminological treatments of the two kinds of patterns, but from the perspective of a constructional view of morphology, there is no need to incorporate such differences into formal grammatical descriptions. For practical purposes, we need clear and simple definitions of entrenched terms of general linguistics, so the article proposes semantically based (retro-) definitions of inflection, derivation and lexeme that cover the bulk of the existing usage. Finally, I briefly explain why we need sharp definitions of comparative concepts, and why prototype-based and fuzzy definitions of traditional terms are not helpful.
E-learning experiences of students in Pakistan during COVID-19: Barriers and perceptions

The literature reveals that there has been significant research regarding online learning during the pandemic outbreak. This research project was conducted to investigate the experiences of university students by highlighting a few key barriers and perceptions to e-learning in Pakistan. A sample of 253 (age range: 17–31 years) students was recruited through a convenient sampling technique. According to participants the crucial online barriers included social interaction, family support, time, and motivation for studies. The majority of students were satisfied with the internet access and quality of online learning. In addition, the most intensively used web-platforms included Zoom, WhatsApp, Microsoft Teams, and Meet by Pakistani students. Furthermore, the findings revealed that students who sleep after midnight (M = 51.46, SD = 9.61) and wake-up around noon (M = 52, SD = 9.09) experience more online education barriers in comparison to students who sleep (M = 40.33, SD = 16.75) and rise early (M = 49.36, SD = 11.86). Hence, the findings of the current study might be helpful in addressing barriers and challenges faced by universities and the Higher Education Commission during such pandemic outbreaks.
Psychological stress detection with optimally selected EEG channel using machine learning techniques

Psychological stress buildup can lead to mental disorders, early mortality, stroke and sudden cardiac arrest and therefore, timely stress detection is important for reducing human suffering. This study aims to present a novel methodology of using reduced channel Electroencephalogram (EEG) signals for cost-effective, convenient, minimally intrusive framework for psychological stress detection. In this study, we investigate the feasibility of using 8-channel EEG configuration consisting of FT9, O1, FC6, Fp2, Oz, F4, T8 and C3 electrodes, selected based on Genetic Algorithm, for psychological stress detection. The dataset of the study comprises 28 healthy subjects (16 males and 12 females, age 23 ± 2 years) and the stressors used are real-life examination stressor and arithmetic stressor. The best results are obtained by classifying the data using machine learning based Support Vector Machines (SVM) classifier achieving highest accuracy 87.50%, sensitivity 81.25%, specificity 92.05% and with wavelet scattering features and SVM achieving highest accuracy 87.50%, sensitivity 82.81%, specificity 90.91%. These methodologies outperformed shallow Convolutional Neural Networks (CNN) based approach that achieved highest accuracy 84.18%, sensitivity 87.5%, specificity 81.76% with mean accuracy of 83.66% using 10-fold cross-validation. This shows the potential of a using only 8 EEG electrodes for reliable psychological stress detection. These results are encouraging for the development of automated stress detection systems for rapid detection in the home or outside the clinic.
DepIn-O: An Ontology on Dependency Injection Software Frameworks

Dependency Injection (DI) is a state-of-practice design pattern utilized for implementing inversion of control, with various DI frameworks widely adopted in many object-oriented programming languages. However, to the best of our knowledge, a formal definition of the associated terminologies within these frameworks has yet to be established. This lack of standardization can make it challenging to achieve semantic interoperability goals, such as code migration between different frameworks or identification of architectural issues regardless of the specific framework in use. To tackle this challenge, we propose DepIn-O, a domain reference ontology designed to capture and express the semantic concepts associated with DI within software development.
ScholarWorks@UARK ScholarWorks@UARK

Immune checkpoint drugs have completely changed the way people treat metastatic melanoma and non-small-cell lung cancer. While the impacts of these immunological checkpoints and their suppression on T cell function are well characterized, their consequences on the tumor microenvironment are not. In a CT26 mouse colorectal cancer model, we employed diffuse reflectance spectroscopy to track in vivo tumor microenvironmental alterations in response to immune checkpoint inhibitors. On three separate days, animals bearing CT26 tumor xenografts were given anti-PD-L1, anti-CTLA-4, a combination of both inhibitors, and isotype control. Within the first 6 days, monotherapy with either anti-PD-L1 or anti-CTLA-4 resulted in a significant increase in tumor vascular oxygenation. The combination of increased oxygenated hemoglobin and decreased deoxygenated hemoglobin caused reoxygenation in anti-CTLA-4-treated tumors, indicating a probable alteration in tumor oxygen consumption following treatment. Reoxygenation was predominantly owing to a rise in oxygenated hemoglobin within a minor change in deoxygenated hemoglobin in anti-PD-L1-treated tumors, indicating a potential increase in tumor perfusion. Except for tumors treated with both inhibitors in combination, none of the other tumor groups demonstrated any reduction in tumor volume. Following therapy, there were no significant changes in tumor oxygenation in the combination treatment group. These results show that diffuse reflectance spectroscopy may detect changes in the tumor microenvironment after immunotherapy and that such non-invasive approaches can be used to predict early tumor response to immune checkpoint inhibitors.
Assessing the efficiency of shape-based functions and descriptors in multi-scale matching of linear objects

Abstract The study of objects similarity in terms of shape has various applications such as determining the similarity degree in object matching. To this end, different functions and descriptors have been used. However, efficiency of each method used in various studies for solving linear object matching in datasets with either different or similar scales or sources has not been studied yet. This article studies the efficiency of the most important functions (i.e. turning, signature, and tangent) along with shape descriptors (i.e. shape context, LORD, and shape signature) in vector datasets with different scales and sources. For this purpose, three datasets of roads network with different sources and scales were employed. Results showed the greater efficiency of the turning function compared to the other methods. In addition to being able to identify corresponding objects in multi-scale datasets, it can improve matching and is capable of discovering shape difference in non-corresponding objects.
The Need for Speed A Fast Guessing Entropy Calculation for Deep Learning-Based SCA

: The adoption of deep neural networks for proﬁling side-channel attacks opened new perspectives for leakage detection. Recent publications showed that cryptographic implementations featuring different countermeasures could be broken without feature selection or trace preprocessing. This success comes with a high price: an extensive hyperparameter search to ﬁnd optimal deep learning models. As deep learning models usually suffer from overﬁtting due to their high ﬁtting capacity, it is crucial to avoid over-training regimes, which require a correct number of epochs. For that, early stopping is employed as an efﬁcient regularization method that requires a consistent validation metric. Although guessing entropy is a highly informative metric for proﬁling side-channel attacks, it is time-consuming, especially if computed for all epochs during training, and the number of validation traces is signiﬁcantly large. This paper shows that guessing entropy can be efﬁciently computed during training by reducing the number of validation traces without affecting the efﬁciency of early stopping decisions. Our solution signiﬁcantly speeds up the process, impacting the performance of the hyperparameter search and overall proﬁling attack. Our fast guessing entropy calculation is up to 16 × faster, resulting in more hyperparameter tuning experiments and allowing security evaluators to ﬁnd more efﬁcient deep learning models.
Giant hogweed at its northern distribution limit in North America: Experiments for a better understanding of its dispersal dynamics along rivers

We studied the reproduction and dispersal of giant hogweed (Heracleum mantegazzianum) at its northern distribution limit in North America (Québec, 2014–2016) to better understand the invasion dynamics of the species along rivers. Seeds were collected from a riparian population to conduct germination, floatation, and dispersal experiments. Data were analysed in comparison with a real invasion case that was initiated about 10 years ago along a river system. In Québec, giant hogweed individuals produce on average 14,000 to 16,000 seeds with a germination rate of 75–85%. Seeds with endosperm that fall in water likely sink within 5 hr. Along a small brook, most disperse over short distances (<40 m) in summer, although some can travel 100–300 m. These data suggest that late‐summer or early‐fall water dispersal of seeds would not explain the magnitude and rapidity of the invasion patterns observed along streams. We suggest that late‐fall and, especially, spring floods are the most efficient dispersal vectors for giant hogweed seeds and are likely responsible for the establishment of populations kilometres downstream from introduction points along river systems. The spread of giant hogweed would consequently be less influenced in the near future by a rise in temperature than by a change in the magnitude or timing of flood events.
Functional analysis of RET in MEN2

The RET proto-oncogene encodes a receptor tyrosine kinase whose dysfunction plays a crucial role in the development of several neural crest-related disorders. Distinct activating RET mutations cause Multiple Endocrine Neoplasia type 2A (MEN2A), type 2B (MEN2B) and Familial Medullary Thyroid Carcinoma (FMTC), respectively. Despite clear genotype-phenotype correlations, the molecular mechanisms connecting the mutated receptors with the distinct clinical subtypes are far from understood. Site-directed mutagenesis, luciferase reporter assays, western analysis in combination with structural modelling studies were performed in order to find RET mutant specific signalling. We show that ERK1/2 and STAT3 are differentially activated by specific MEN2-RET oncoproteins and that the activation level of both pathways strongly correlated with the degree of RET Tyr1062 and Tyr981 phosphorylation, respectively. Moreover, phosphorylation levels of RET Tyr1062 and Tyr918 were up-regulated by co-expression of a constitutive active SRC (v-SRC), suggesting in trans phosphorylation/activation of RET by v-SRC. Receptor activation was stronger for those intracellular point mutations situated in the proximity of or within the WMxxEx motif, also known as the P+1 loop of RET. Furthermore, we modelled the tyrosine kinase domain of RET with MEN2B mutations, RETA883F and RETM918T. Our modelling results confirmed that MEN2B-type mutations could alter the conformation of the RET kinase domain. In particular, the RETM918T mutation display an increased P+1 and P+3 binding pocket, changing the overall shape of the substrate binding site, possibly altering its substrate specificity. Mutation RETA883F was able to induce both, conformational changes in the activation loop resulting in a more open ATP and substrate binding conformation as well as an alteration in the conformation of the catalytic loop thereby shifting the equilibrium from the inactive to the active state of the kinase domain of RET.
Analyzing Wet-Neuromorphic Computing Using Bacterial Gene Regulatory Neural Networks

—The vision of biocomputing is to develop computing paradigms using biological systems, ranging from micron-level components to collections of cells, such as organoids. This paradigm shift exploits hidden natural computing properties, developing miniaturized wet computing devices deployable in harsh environments, and exploring designing novel energy-efficient systems. Parallelly, we witness the emergence of AI hardware including neuromorphic processors aiming to improve computational capacity. This study brings together the concept of bio-computing and neuromorphic systems by focusing on the Bacterial gene regulatory networks and their transformation into Gene Regulatory Neural Networks (GRNNs) that can be used for biocomputing. We explore the intrinsic properties of gene regulations, map this to a gene-perceptron function, and propose an application-specific sub-GRNN search algorithm that maps the network structure to match a problem. Focusing on the model organism Escherichia coli (E. coli), the base-GRNN is initially extracted and validated for accuracy. Subsequently, a comprehensive feasibility analysis of the derived GRNN confirms its computational prowess in classification and regression tasks. Furthermore, we discuss the possibility of performing a well-known digit classification task as a use case. Our analysis and simulation experiments show promising results in offloading computation to GRNN in bacterial cells, advancing wet-neuromorphic computing using natural cells.
Heavy Metals and Phosphorus Forms Mobilization during Re-Suspension of Bottom Sediments of the Prut River

Bottom sediments of the river are repositories for various elements, acting both as sinks and sources of supplying of elements to overlying water horizon. Re-suspension of the bottom sediments of the Prut River was performed in field conditions by „aquarium” method. The results suggest that during the resuspension, bottom sediments can become a relevant source of heavy metals and phosphorus forms which are mobilized in the water horizon overlying the bottom sediments.