Miracle-dz/UniFAR-FTUs huggingface dataset:
Extreme CO concentrations in the upper troposphere over northeast Asia in June 2003 from the in situ MOZAIC aircraft data

This paper analyses 320 MOZAIC (Measurements of Ozone aboard Airbus in‐service airCraft) flights between Europe and East Asia in the year 2003. Carbon monoxide (CO) measurements in the upper troposphere (UT) clearly show the influence of plumes from boreal forest fires burning around Lake Baikal between April and July. On many flights, CO concentrations were above 300 ppbv over several hundred kilometers, with values above 500 ppbv over 50 kilometers and peaks up to 800 ppbv. To our knowledge, such high UT CO concentrations have never been reported before. A case study reveals that biomass burning plumes were rapidly transported by a warm conveyor belt. On the regional and seasonal scale, MOZAIC monthly‐mean concentrations were above 150 ppbv on average, i.e. 30% above the northern hemisphere background as determined over Europe.
VERIFICATION OF SHARK CPUE REPORTED BY LOGBOOK OF JAPANESE LONGLINE FISHERY COMPARING WITH THE OBSERVER DATA

SUMMARY The shark CPUE from the Japanese logbook data was verified comparing with CPUE from Japanese observer data. And, the most appropriate range of reporting category for the logbook data was determined as abundance indices of blue and shortfin mako shark. Blue shark occupied 86 % of all sharks caught in more and equal 70 % of reporting categories in the logbook records. The CPUEs of blue shark were close to the values from Japanese observer data and within the range of the standard deviations of them. Shortfin mako shark occupied 40 % of all sharks caught in less than 40 % of reporting categories, and the CPUE of shortfin mako shark were almost within the range of the standard deviations. Therefore, these reporting categories (blue shark: more and equal 70 %, shortfin mako shark: less than 40 %) could be used as abundance indices for the species.
A comprehensive transcriptomic analysis of the bisphenol A affected kidney in mice

Introduction: Bisphenol A (BPA) is a substance belonging to the endocrine-disrupting chemicals, globally used in the production of polycarbonate plastics. It has been found that BPA enhances carcinogenesis, triggers obesity and exerts a pathogenic effect in several disorders, such as type 2 diabetes, asthma, or increased blood pressure. Recent studies have revealed, that BPA has a harmful impact on the kidneys function, therefore, the current research aimed to explore the specific molecular changes triggered in these organs after oral BPA exposure in mice. Materials and Methods: The experiment was carried out on 12 (3-month-old) female mice. Six mice served as controls. The other 6 mice were treated with BPA in the drinking water at a dose of 50 mg/kg b. w. for 3 months. Then animals were euthanized, the kidneys were collected, and extracted RNA was used to perform RNA-seq. Results: Applied multistep bioinformatics revealed 433 differentially expressed genes (DEGs) in the BPA-treated kidneys (232 upregulated and 201 downregulated). Additionally, 95 differentially expressed long-noncoding RNAs (DELs) were revealed in BPA samples. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) annotations indicated that BPA exposure resulted in profound changes in several essential processes, such as oxidative phosphorylation, mitochondrial and ribosome function, or chemical carcinogenesis. Conclusion: The obtained novel results suggest that BPA has a harmful impact on the fundamental processes of the kidney and significantly impairs its function by inducing mitochondrial dysfunction leading to oxidative stress and reactive oxygen species production.
Sidelobe Suppression of LFM Signal Using Variability Index (VI)-Wavelet Threshold Method

In the pulse compression radar using linear frequency modulation (LFM), the sidelobe suppression signal processing is very important to overcome an effect that may mask smaller targets or maybe mistaken as separate targets. This paper considers a novel framework of the sidelobe suppression for linear frequency modulation signal (LFM) at a receiver when existing internal receive noise. In pulse compression for LFM signal, there exist not only range mainlobe components but also range sidelobe components in the matched filter output. It is necessary to effectively suppress the sidelobe components at the receiver of radar. This paper presents variability index (VI)-threshold operation based on the wavelet transform to further reduce these range sidelobes, and then analyzes it compared to the conventional window method. The results show that the proposed method is very effective in suppression of sidelobes components for LFM signal. It also indicates that this method gives better a peak to sidelobe ratio (PSR) performance than other methods for the sidelobe suppression.
Effects of Siblings on Cognitive and Sociobehavioral Development: Ongoing Debates and New Theoretical Insights

Despite social scientists’ long-standing interest in the influences of siblings, previous research has not settled the debates on how relevant sibship size is to child development and whether growing up with more siblings could be beneficial. Using 30 years of longitudinal data and fixed-effects models, this study offers the most comprehensive evidence on how sibship size is tied to cognitive and sociobehavioral development. We also advance the literature by systematically comparing the consequences of gaining a sibling for children with varying ordinal positions. Contrary to prior studies using selective data from limited observation spans, we find that children experience net decreases in cognitive test scores as their family size grows. At the same time, our analysis shows that sibling additions are only important to first- and second-born children’s—not later-born children’s—cognitive development. Even for the first- and second-born, the marginal effect of adding a sibling lessens with each addition. Our results thus demonstrate the time-dependent nature of family resource-dilution processes. For sociobehavioral development, the evidence indicates that having an older sibling is beneficial, but gaining a younger sibling increases behavioral problems for some (e.g., first-born children). Because more children from large families have older siblings, children from larger families exhibit less problematic behavior, on average. By uncovering the complex relationship between siblings and noncognitive development, this study also generally contributes to the sociology of family and inequality.
Autobiographical memory in contact tracing: evidence from the COVID-19 pandemic

Introduction The recent COVID-19 pandemic has compelled various governments to trace all contacts of a confirmed case, as well as to identify the locations visited by infected individuals. This task, that requires the activation of our autobiographical memories, can make a difference in the spread of the contagion and was based primarily on telephone interviews with infected people. In this study, we examined whether participants were able to provide contact tracing information and whether their memories were influenced by salient events occurring during the initial phases of the pandemic. Methods Participants were asked to fill in an online standardized form in which they recounted every day of the 2 weeks before, reporting as much information as possible. The time period selected included, among other things, the day on which the Italian government issued the decree initiating the COVID-19 lockdown. The task was completed twice, the first time relying solely on their memory, and the second time using external aids (diaries, mobile phones etc.). Reports were then coded using a scheme that segmented accounts into informational details, divided into two broad categories, internal and external. Results Our findings showed that (i) the use of external aids was effective only when participants had to recall the day furthest away or if to-be-recalled events have low distinctiveness, and (ii) memories of internal details were recalled better than memories of external details. Participants were overall accurate and reported a large amount of information about people and places. However, because of the connection with key pandemic-related events, the effect was somewhat stronger on specific days (e.g., the day in which the lockdown was announced). Discussion The results of this work could provide a useful tool for improving the design of contact tracing procedures in the event of an unwanted future public health crisis caused by a highly infectious agent.
Isolation and characterization of intestinal bacteria associated with cellulose degradation in grasshoppers (Orthoptera)

Abstract Insect gut bacteria play an essential role in the nutritional metabolism, growth, and development of insects. Grasshoppers (Orthoptera) are cellulose-rich plant-feeding pests. Although the biological potential of grasshopper gut microorganisms to assist cellulose decomposition is well established, microbial resources for efficient degradation of cellulose biomass are still scarce and need to be developed. In this study, we used selective media to isolate cellulose-degrading bacteria from the intestines of Atractomorpha sinensis, Trilophidia annulata, Sphingonotus mongolicus, and Calliptamus abbreviatus. Phylogenetic analysis based on the maximum likelihood method using 16S rDNA sequencing sequences to identify bacteria revealed the isolation of 11 strains belonging to 3 genera, including Klebsiella, Aeromonas, and Bacillus. The degradability of the isolates to cellulose was then determined by the DNS colorimetric method, and the results showed that Bacillus had the highest degradation rate. The elucidation of microbial cellulose degradation capacity in grasshoppers not only contributes to the understanding of multiple plant–insect–microbe interactions, but also provides a valuable microbial resource for solving the biomass conversion of cellulose species problem.
Fasting durations of Steller sea lion pups vary among subpopulations—evidence from two plasma metabolites

ABSTRACT Geographic differences in population growth trends are well-documented in Steller sea lions (Eumetopias jubatus), a species of North Pacific pinniped listed under the U.S. Endangered Species Act in 1990 following a marked decline in population abundance that began during the 1970s. As population growth is intrinsically linked to pup production and survival, examining factors related to pup physiological condition provides useful information to management authorities regarding potential drivers of regional differences. During dam foraging trips, pups predictably transition among three fasting phases, distinguished by the changes in the predominant metabolic byproduct. We used standardized ranges of two plasma metabolites (blood urea nitrogen and β–hydroxybutyrate) to assign pups to fasting categories (n = 1528, 1990–2016, 12 subpopulations): Recently Fed–Phase I (digestion/assimilation–expected hepatic/muscle glycogen usage), Phase II (expected lipid utilization), transitioning between Phases II–III (expected lipid utilization with increased protein reliance), or Phase III (expected protein catabolism). As anticipated, the majority of pups were classified as Recently Fed–Phase I (overall mean proportion = 0.72) and few pups as Phase III (overall mean proportion = 0.04). By further comparing pups in Short (Recently Fed–Phase II) and Long (all other pups) duration fasts, we identified three subpopulations with significantly (P < 0.03) greater proportions of pups dependent upon endogenous sources of energy for extended periods, during a life stage of somatic growth and development: the 1) central (0.27 ± 0.09) and 2) western (0.36 ± 0.13) Aleutian Island (declining population trend) and 3) southern Southeast Alaska (0.32 ± 0.06; increasing population trend) subpopulations had greater Long fast proportions than the eastern Aleutian Islands (0.10 ± 0.05; stabilized population). Due to contrasting population growth trends among these highlighted subpopulations over the past 50+ years, both density-independent and density-dependent factors likely influence the dam foraging trip duration, contributing to longer fasting durations for pups at some rookeries.
Chimeric antigen receptor T cells to target CD79b in B-cell lymphomas

Background Chimeric antigen receptor (CAR) T cells targeting CD19 mediate potent and durable effects in B-cell malignancies. However, antigen loss or downregulation is a frequent cause of resistance. Here, we report development of a novel CAR T-cell therapy product to target CD79b, a pan B-cell antigen, widely expressed in most B-cell lymphomas. Methods We generated a novel anti-CD79b monoclonal antibody by hybridoma method. The specificity of the antibody was determined by testing against isogenic cell lines with human CD79b knock-in or knock-out. A single-chain variable fragment derived from the monoclonal antibody was used to make a panel of CD79b-targeting CAR molecules containing various hinge, transmembrane, and co-stimulatory domains. These were lentivirally transduced into primary T cells and tested for antitumor activity in in vitro and in vivo B-cell lymphoma models. Results We found that the novel anti-CD79b monoclonal antibody was highly specific and bound only to human CD79b and no other cell surface protein. In testing the various CD79b-targeting CAR molecules, superior antitumor efficacy in vitro and in vivo was found for a CAR consisting CD8α hinge and transmembrane domains, an OX40 co-stimulatory domain, and a CD3ζ signaling domain. This CD79b CAR specifically recognized human CD79b-expressing lymphoma cell lines but not CD79b knock-out cell lines. CD79b CAR T cells, generated from T cells from either healthy donors or patients with lymphoma, proliferated, produced cytokines, degranulated, and exhibited robust cytotoxic activity in vitro against CD19+ and CD19– lymphoma cell lines and patient-derived lymphoma tumors relapsing after prior CD19 CAR T-cell therapy. Furthermore, CD79b CAR T cells were highly efficient at eradicating pre-established lymphoma tumors in vivo in three aggressive lymphoma xenograft models, including two cell line-derived xenografts and one patient-derived xenograft. Notably, these CAR T cells did not demonstrate any significant tonic signaling activity or markers of exhaustion. Conclusion Our results indicated that this novel CD79b CAR T-cell therapy product has robust antitumor activity against B-cell lymphomas. These results supported initiation of a phase 1 clinical trial to evaluate this product in patients with relapsed or refractory B-cell lymphomas.
ePortfolio: l’uso di ambienti online per favorire l’orientamento in itinere nel percorso universitario

This pilot-study concerns the construction of an ePortfolio, carried out by students during the 2013/14 Course of “Didactic of the Educational Guidance”*. The aim is to facilitate the orientation of university students through the documenting of their lived learning experiences and the consequent reflectionabout them. In particular, a showcase portfolio has been realized using Mahara, an open source platform. The opinions of students, measured by input andoutput questionnaires related to the research hypothesis (Mahara usability, conception and design of the eP to promote the awareness of the educational process), show they positively experienced metacognition and individual and collegial reflection, as well as some critical issues related to the projection of the instrument in a future working field.
Plate subrotations

The kinematics of plates is defined by Euler pole and angular velocity. However, during their journey, plates may be affected by additional simultaneous rotations (i.e., subrotations) while they are rotating about their Euler poles. The kinematic description of this particular plate motion requires a different analytical approach: two angular velocities and two poles are necessary to completely describe plate displacements. If a subrotation occurs, none of the points on a plate moves along circles of the Euler pole but, instead, follows cycloid trajectories because of the combination of the two simultaneous rotations. Regardless of the forces that move the lithosphere, every time a plate experiences a subrotation, an additional force (or resisting) force could act on the plate, generating the two‐rotation motion. In the hot spot reference frame, we applied this model to the North America plate, investigating its past motion for a time interval Δt = 43 Ma up to the present and comparing results with those obtained by Gordon and Jurdy (1986). This application shows how the different positions of the North America plate over most of the Cenozoic can be reconstructed by two‐rotation plate kinematics.
Multi-Tap Resistive Sensing and FEM Modeling Enables Shape and Force Estimation in Soft Robots

We address the challenge of reliable and accurate proprioception in soft robots, specifically soft robots with tight packaging constraints and relying only on internally embedded sensors. While various sensing approaches with single sensors have commonly been tried using a constant curvature assumption, we look into sensing local deformations at multiple sensor locations. In our approach, we multi-tap an off-the-shelf resistive sensor by creating multiple electrical connections onto the resistive layer of the sensor, and we insert the sensor into a soft body. This modification allows us to measure changes in resistance at multiple segments throughout the length of the sensor, providing improved resolution of local deformations in the soft body. These measurements inform a model based on a finite element method (FEM) that estimates the shape of the soft body and the magnitude of an external force acting at a known arbitrary location. Our model-based approach estimates soft body deformation with approximately 3% average relative error while taking into account internal fluidic actuation. Our estimate of external force disturbance has an 11% relative error within a range of 0 to 5 N. For instance, the combined sensing and modeling approach can be integrated into soft manipulation platforms to enable features such as identifying the shape and material properties of an object being grasped. Such manipulators can benefit from the inherent softness and compliance while being fully proprioceptive, relying only on embedded sensing and not on external systems such as motion capture. Such proprioception is essential for the deployment of soft robots in real-world scenarios.
Nanosecond kinetics of phase separation in binary fluid studied by a combination of Laser-induced temperature jump and Forster Resonant Excitation Transfer probing

A novel technique for studying the demixing of binary fluids with nanosecond time resolution at nanometer spatial resolution is demonstrated. Nanosecond kinetics of phase separation initial stages in the water/2,6-lutidine mixture studied through the combination of a laser-induced temperature jump, and Forster Resonant Excitation Transfer techniques. A pair of chromophores: 8-hydroxy-1,3,6-pyrenetrisulfonate (HPTS) and Coumarin 480 form a FRET pair in the uniform phase of the mixture and separate into the components of the mixture in the nonuniform phase. The temperature jump that brings the mixture into a nonuniform phase is performed by the mid-infrared laser pulse. The exponential growth stage of phase separation is in the 5 to 20 nanoseconds range. The demonstrated technique can be applied to a broad range of chemical and biological systems.
FRUITS: Feature Extraction Using Iterated Sums for Time Series Classification

We introduce a pipeline for time series classification that extracts features based on the iterated-sums signature (ISS) and then applies a linear classifier. These features are intrinsically nonlinear, capture chronological information, and, under certain settings, are invariant to time-warping. We are competitive with state-of-the-art methods on the UCR archive, both in terms of accuracy and speed. We make our code available at \url{https://github.com/irkri/fruits}.
High-Order Tensor Recovery with A Tensor U1 Norm

Recently, numerous tensor SVD (t-SVD)-based tensor recovery methods have emerged, showing promise in processing visual data. However, these methods often suffer from performance degradation when confronted with high-order tensor data exhibiting non-smooth changes, commonly observed in real-world scenarios but ignored by the traditional t-SVD-based methods. Our objective in this study is to provide an effective tensor recovery technique for handling non-smooth changes in tensor data and efficiently explore the correlations of high-order tensor data across its various dimensions without introducing numerous variables and weights. To this end, we introduce a new tensor decomposition and a new tensor norm called the Tensor $U_1$ norm. We utilize these novel techniques in solving the problem of high-order tensor completion problem and provide theoretical guarantees for the exact recovery of the resulting tensor completion models. An optimization algorithm is proposed to solve the resulting tensor completion model iteratively by combining the proximal algorithm with the Alternating Direction Method of Multipliers. Theoretical analysis showed the convergence of the algorithm to the Karush-Kuhn-Tucker (KKT) point of the optimization problem. Numerical experiments demonstrated the effectiveness of the proposed method in high-order tensor completion, especially for tensor data with non-smooth changes.
A DRL solution to help reduce the cost in waiting time of securing a traffic light for cyclists

Cyclists prefer to use infrastructure that separates them from motorized traffic. Using a traffic light to segregate car and bike flows, with the addition of bike-specific green phases, is a lightweight and cheap solution that can be deployed dynamically to assess the opportunity of a heavier infrastructure such as a separate bike lane. To compensate for the increased waiting time induced by these new phases, we introduce in this paper a deep reinforcement learning solution that adapts the green phase cycle of a traffic light to the traffic. Vehicle counter data are used to compare the DRL approach with the actuated traffic light control algorithm over whole days. Results show that DRL achieves better minimization of vehicle waiting time at almost all hours. Our DRL approach is also robust to moderate changes in bike traffic. The code of this paper is available at https://github.com/LucasMagnana/A-DRL-solution-to-help-reduce-the-cost-in-waiting-time-of-securing-a-traffic-light-for-cyclists.
A Unified Framework for Fair Spectral Clustering With Effective Graph Learning

We consider the problem of spectral clustering under group fairness constraints, where samples from each sensitive group are approximately proportionally represented in each cluster. Traditional fair spectral clustering (FSC) methods consist of two consecutive stages, i.e., performing fair spectral embedding on a given graph and conducting $k$means to obtain discrete cluster labels. However, in practice, the graph is usually unknown, and we need to construct the underlying graph from potentially noisy data, the quality of which inevitably affects subsequent fair clustering performance. Furthermore, performing FSC through separate steps breaks the connections among these steps, leading to suboptimal results. To this end, we first theoretically analyze the effect of the constructed graph on FSC. Motivated by the analysis, we propose a novel graph construction method with a node-adaptive graph filter to learn graphs from noisy data. Then, all independent stages of conventional FSC are integrated into a single objective function, forming an end-to-end framework that inputs raw data and outputs discrete cluster labels. An algorithm is developed to jointly and alternately update the variables in each stage. Finally, we conduct extensive experiments on synthetic, benchmark, and real data, which show that our model is superior to state-of-the-art fair clustering methods.