Miracle-dz/UniFAR-FTUs huggingface dataset:
Differential Seawater Adaptability in Three Different Sizes of Under-yearling Steelhead Trout

Abstract Seawater adaptability of steelhead trout increases along with the increase in the size of the fish, independent of parr-smolt transformation. Three 96 h seawater challenge tests were conducted to determine the size at which seawater adaptability of steelhead trout develops. Plasma Na+ and Cl− levels, moisture content, gill Na+/K+ ATPase activity, and mortality during the 96 h after direct transfer to seawater (32 ppt) were determined. Plasma Na+ and Cl− levels in 50 g fish continuously increased during the 96 h after the transfer to seawater (p<0.05), but the levels in 100 and 150 g fish leveled off after 24 h (p<0.05). Both 100 and 150 g size steelhead trout maintained muscle moisture content (%) better than 50 g size fish (p<0.05). Gill Na+/K+ ATPase activity in the 100 g size group increased in a time-dependent manner after transfer to seawater (p<0.05), whereas activity in the 50 and 150 g sizes did not increase (p>0.05), for which a possible explanation was discussed. A mere 2.6% mortality in both the 50 and 150 g size groups was observed. In conclusion, the current results indicate that 50 g size steelhead trout did not show development of a high level of hypoosmoregulatory capacity, whereas fish in the 100 and 150 g size groups showed a high level in our experimental conditions. Therefore, the steelhead trout larger than a 100 g size is recommended for transfer to seawater culture.
Numerical Simulations of Bird Strikes with the Use of Various Equations of State

Abstract The paper presents results of numerical analyses of the collision of various bird models (dummies) with a helicopter windshield. Three different numerical bird models were elaborated. According to the subject literature, applying an appropriate equation of state has an influence on impact parameters. The author used the LS_DYNA software package. This is a computational code designed to analyse fast-changing phenomena by means of the finite-element method. SPH method has been used for bird strike simulations. In the research, three different equations of state have been used: Grüneisen's, polynomial and tabulated.
High yield, shell-stabilized, narrow-sized C3F8 nanobubbles with different shell properties and precisely controllable response to acoustic excitations: experimental observations and numerical simulations

Understanding the pressure dependence of the nonlinear behavior of ultrasonically excited phospholipid (PL)-stabilized NBs is important for optimizing US exposure parameters for implementations of contrast enhanced ultrasound, critical to molecular imaging. The viscoelastic properties of the shell can be controlled by introduction of membrane additives, such as propylene glycol as a membrane softener or glycerol as a membrane stiffener. We report for the first time, the production of high yield NBs with narrow dispersity and different shell properties. Through precise control over size and shell structure, we show how these shell components interact with the phospholipid membrane, change its structure, affect their viscoelastic properties, and consequently change their acoustic response. A two-photon microscopy technique through a polarity-sensitive fluorescent dye, C-laurdan, was utilized to gain insights on the effect of membrane additives to the membrane structure. We report how the shell stiffness of NBs affects the pressure threshold (Pt) for the sudden amplification in the scattered acoustic signal from NBs. For narrow size NBs with 200 nm mean size, we find Pt to be between 123-245 kPa for the NBs with the most flexible membrane as assessed using C-Laurdan, 465-588 kPa for the NBs with intermediate stiffness and 588-710 kPa for the NBs with stiff membranes. Numerical simulations of the NB dynamics are in good agreement with the experimental observations confirming the dependence of acoustic response to shell properties, thereby substantiating further the development in engineering the shell of UCAs. The viscoelastic dependent threshold behavior can be utilized for significantly and selectively enhancing the diagnostic and therapeutic ultrasound applications of potent narrow size NBs.
X-Class: Text Classification with Extremely Weak Supervision

In this paper, we explore text classification with extremely weak supervision, i.e., only relying on the surface text of class names. This is a more challenging setting than the seed-driven weak supervision, which allows a few seed words per class. We opt to attack this problem from a representation learning perspective—ideal document representations should lead to nearly the same results between clustering and the desired classification. In particular, one can classify the same corpus differently (e.g., based on topics and locations), so document representations should be adaptive to the given class names. We propose a novel framework X-Class to realize the adaptive representations. Specifically, we first estimate class representations by incrementally adding the most similar word to each class until inconsistency arises. Following a tailored mixture of class attention mechanisms, we obtain the document representation via a weighted average of contextualized word representations. With the prior of each document assigned to its nearest class, we then cluster and align the documents to classes. Finally, we pick the most confident documents from each cluster to train a text classifier. Extensive experiments demonstrate that X-Class can rival and even outperform seed-driven weakly supervised methods on 7 benchmark datasets.
Rethinking embedding coupling in pre-trained language models

We re-evaluate the standard practice of sharing weights between input and output embeddings in state-of-the-art pre-trained language models. We show that decoupled embeddings provide increased modeling flexibility, allowing us to significantly improve the efficiency of parameter allocation in the input embedding of multilingual models. By reallocating the input embedding parameters in the Transformer layers, we achieve dramatically better performance on standard natural language understanding tasks with the same number of parameters during fine-tuning. We also show that allocating additional capacity to the output embedding provides benefits to the model that persist through the fine-tuning stage even though the output embedding is discarded after pre-training. Our analysis shows that larger output embeddings prevent the model's last layers from overspecializing to the pre-training task and encourage Transformer representations to be more general and more transferable to other tasks and languages. Harnessing these findings, we are able to train models that achieve strong performance on the XTREME benchmark without increasing the number of parameters at the fine-tuning stage.
Spitzer Reveals Evidence of Molecular Absorption in the Atmosphere of the Hot Neptune LTT 9779b

Non-rocky sub-Jovian exoplanets in high-irradiation environments are rare. LTT 9779b, also known as Transiting Exoplanet Survey Satellite (TESS) object of interest (TOI) 193.01, is one of the few such planets discovered to date, and the first example of an ultrahot Neptune. The planet’s bulk density indicates that it has a substantial atmosphere, so to investigate its atmospheric composition and shed further light on its origin, we obtained Spitzer InfraRed Array Camera secondary eclipse observations of LTT 9779b at 3.6 and 4.5 μm. We combined the Spitzer observations with a measurement of the secondary eclipse in the TESS bandpass. The resulting secondary eclipse spectrum strongly prefers a model that includes CO absorption over a blackbody spectrum, incidentally making LTT 9779b the first TESS exoplanet (and the first ultrahot Neptune) with evidence of a spectral feature in its atmosphere. We did not find evidence of a thermal inversion, at odds with expectations based on the atmospheres of similarly irradiated hot Jupiters. We also report a nominal dayside brightness temperature of 2305 ± 141 K (based on the 3.6 μm secondary eclipse measurement), and we constrained the planet’s orbital eccentricity to e < 0.01 at the 99.7% confidence level. Together with our analysis of LTT 9779b’s thermal phase curves reported in a companion paper, our results set the stage for similar investigations of a larger sample of exoplanets discovered in the hot-Neptune desert, investigations that are key to uncovering the origin of this population.
Role of the magnetic field in the fragmentation process: the case of G14.225-0.506

Context. Magnetic fields are predicted to play a significant role in the formation of filamentary structures and their fragmentation to form stars and star clusters. Aims. We aim to investigate the role of the magnetic field in the process of core fragmentation toward the two hub–filament systems in the infrared dark cloud G14.225-0.506, which present different levels of fragmentation. Methods. We performed observations of the thermal dust polarization at 350 μm using the Caltech Submillimeter Observatory (CSO) with an angular resolution of 10″ toward the two hubs (Hub-N and Hub-S) in the infrared dark cloud G14.225-0.506. We additionally applied the polarization–intensity-gradient method to estimate the significance of the magnetic field over the gravitational force. Results. The sky-projected magnetic field in Hub-N shows a rather uniform structure along the east–west orientation, which is roughly perpendicular to the major axis of the hub–filament system. The intensity gradient in Hub-N displays a single local minimum coinciding with the dust core MM1a detected with interferometric observations. Such a prevailing magnetic field orientation is slightly perturbed when approaching the dust core. Unlike the northern Hub, Hub-S shows two local minima, reflecting the bimodal distribution of the magnetic field. In Hub-N, both east and west of the hub–filament system, the intensity gradient and the magnetic field are parallel whereas they tend to be perpendicular when penetrating the dense filaments and hub. Analysis of the |δ|- and ΣB-maps indicates that, in general, the magnetic field cannot prevent gravitational collapse, both east and west, suggesting that the magnetic field is initially dragged by the infalling motion and aligned with it, or is channeling material toward the central ridge from both sides. Values of ΣB ≳ 1 are found toward a north–south ridge encompassing the dust emission peak, indicating that in this region magnetic field dominates over gravity force, or that with the current angular resolution we cannot resolve a hypothetically more complex structure. We estimated the magnetic field strength, the mass-to-flux ratio, and the Alfvén Mach number, and found differences between the two hubs. Conclusions. The different levels of fragmentation observed in these two hubs could arise from differences in the properties of the magnetic field rather than from differences in the intensity of the gravitational field because the density in the two hubs is similar. However, environmental effects could also play a role.
ANLIzing the Adversarial Natural Language Inference Dataset

We perform an in-depth error analysis of Adversarial NLI (ANLI), a recently introduced large-scale human-and-model-in-the-loop natural language inference dataset collected over multiple rounds. We propose a fine-grained annotation scheme of the different aspects of inference that are responsible for the gold classification labels, and use it to hand-code all three of the ANLI development sets. We use these annotations to answer a variety of interesting questions: which inference types are most common, which models have the highest performance on each reasoning type, and which types are the most challenging for state of-the-art models? We hope that our annotations will enable more fine-grained evaluation of models trained on ANLI, provide us with a deeper understanding of where models fail and succeed, and help us determine how to train better models in future.
Federated Learning in Multi-RIS-Aided Systems

The fundamental communication paradigms in the next-generation mobile networks are shifting from connected things to connected intelligence. The potential result is that current communication-centric wireless systems are greatly stressed when supporting computation-centric intelligent services with distributed big data. This is one reason that makes federated learning come into being, it allows collaborative training over many edge devices while avoiding the transmission of raw data. To tackle the problem of model aggregation in federated learning systems, this article resorts to multiple reconfigurable intelligent surfaces (RISs) to achieve efficient and reliable learning-oriented wireless connectivity. The seamless integration of communication and computation is actualized by over-the-air computation (AirComp), which can be deemed as one of the uplink nonorthogonal multiple access (NOMA) techniques without individual information decoding. Since all local parameters are uploaded via noisy concurrent transmissions, the unfavorable propagation error inevitably deteriorates the accuracy of the aggregated global model. The goals of this work are to 1) alleviate the signal distortion of AirComp over shared wireless channels and 2) speed up the convergence rate of federated learning. More specifically, both the mean-square error (MSE) and the device set in the model uploading process are optimized by jointly designing transceivers, tuning reflection coefficients, and selecting clients. Compared to baselines, extensive simulation results show that 1) the proposed algorithms can aggregate model more accurately and accelerate convergence and 2) the training loss and inference accuracy of federated learning can be improved significantly with the aid of multiple RISs.
Improving the Exploration of Deep Reinforcement Learning in Continuous Domains using Planning for Policy Search

Local policy search is performed by most Deep Reinforcement Learning (D-RL) methods, which increases the risk of getting trapped in a local minimum. Furthermore, the availability of a simulation model is not fully exploited in D-RL even in simulation-based training, which potentially decreases efficiency. To better exploit simulation models in policy search, we propose to integrate a kinodynamic planner in the exploration strategy and to learn a control policy in an offline fashion from the generated environment interactions. We call the resulting model-based reinforcement learning method PPS (Planning for Policy Search). We compare PPS with state-of-the-art D-RL methods in typical RL settings including underactuated systems. The comparison shows that PPS, guided by the kinodynamic planner, collects data from a wider region of the state space. This generates training data that helps PPS discover better policies.
Serum Metabolomics for Biomarker Screening of Esophageal Squamous Cell Carcinoma and Esophageal Squamous Dysplasia Using Gas Chromatography-Mass Spectrometry

Background: Esophageal squamous cell carcinoma (ESCC) is one of the most common malignancies with poor diagnosis. Esophageal squamous dysplasia (ESD) is considered as an immediate precancerous lesion of ESCC. Lack of biomarkers for discriminating ESCC and ESD from healthy subjects limits the early diagnosis and treatment of ESCC. Therefore, a serum metabolomic strategy was conducted to identify and validate potential metabolic markers for the screening of ESCC and ESD subjects. Methods: A total of 74 patients with ESCC, 72 patients with ESD, and 75 normal control (NC) subjects were enrolled in this study. Gas chromatography-mass spectrometry was used to acquire serum metabolic profiles. Pathway analysis was conducted to uncover the fluctuated metabolic pathways during ESCC. Multivariate analyses were used to screen and validate the biomarkers. Results: ESCC, ESD, and NC subjects revealed progressively altered metabolic profiles, in which amino acids globally increased, while fatty acids decreased in ESCCs compared with the control groups. Pathway analysis demonstrated the activated biosynthesis of amino acids and inhibited desaturation of saturated fatty acids. The panel constructed with propanoic acid, linoleic acid, glycerol-3-phosphate, and l-glutamine showed the area under the curve (AUC), sensitivity, and specificity of 0.817, 0.75, and 0.74, respectively, in the discrimination of ESCC/ESD patients from NC subjects. The panel constructed by propanoic acid, l-leucine, and hydroxyproline revealed the AUC, sensitivity, and specificity of 0.819, 0.76, and 0.72, respectively, in the discrimination of ESD from NC subjects. The combination of hypoxanthine, 2-ketoisocaproic acid, l-glutamate, and l-aspartate showed the AUC, sensitivity, and specificity of 0.818, 0.83, and 0.74, respectively, in the discrimination of ESCC patients from ESD subjects. Conclusions: Our study revealed the systematic landscape for metabolic alterations in sera of ESD and ESCC patients. The defined metabolite markers showed reasonable performance in the discrimination of ESCC and ESD patients, and may provide helpful reference for clinicians and biologists.
Electrochemotherapy and Simultaneous Photodynamic Bone Stabilization of Upper Limbs in Metastatic Renal Cancer Disease: Case Report and Literature Review

Introduction Metastatic bone disease represents a systemic pathology that heavily affects the quality of life of oncologic patients causing pain and functional disability. Methodology. We present the case of a patient with a history of renal cell cancer presenting pathologic fractures of both humeri and proximal right radius. Results After a careful multidisciplinary approach, an adjuvant anticancer therapy and a photodynamic bone stabilization procedure were performed with a minimally invasive technique aiming to minimize pain and local disease progression, while restoring functional autonomy and improving the patient's quality of life. Electrochemotherapy was delivered on the lytic bone lesions with extraskeletal involvement of the proximal left humerus and the proximal right radius, and then polymeric bone stabilization was performed on both humeri. At two months of follow-up, the patient presented satisfactory functional scores (MSTS score: 12/30 bilaterally; DASH scores: 46.7/100 for the right side and 48.3/100 for the left one), and pain was well controlled with opioid analgesics. Radiographs showed good results in terms of ossification of lytic bone lesions and durability of polymeric stabilization. At four months of follow-up, the patient reported a stable clinical scenario. Six months after surgery, due to extremely poor prognosis after the progression of primary disease, the patient was referred to palliative care and died shortly thereafter. Conclusion Over the last decade, the management of metastatic bone disease has changed. Low-toxicity and minimally invasive procedures such as electrochemotherapy and polymeric bone stabilization might be performed concomitantly in selected patients, as an alternative to radiation therapy and to more demanding surgical procedures such as plating and adjuvant cementing.
Cadmium Level in Soil, Coarse Fodder, Organs and Tissue of Cattle in West Siberia

Book of the 18 International Conference on Heavy Metals in the Environment, 12 to 15 September 2016, Ghent, Belgium This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. – 417 – 18th International Conference on avy Metals in the Environment 12 to 15 September 2016, Ghent, Belgium ICHMET 2016 Proceedings of the 18 International Confer nce on Heavy Metals in the Environment, 12 to 15 September 2016, Ghent, Belgium
Constrained Abstractive Summarization: Preserving Factual Consistency with Constrained Generation

Summaries generated by abstractive summarization are supposed to only contain statements entailed by the source documents. However, state-of-the-art abstractive methods are still prone to hallucinate content inconsistent with the source documents. In this paper, we propose constrained abstractive summarization (CAS), a general setup that preserves the factual consistency of abstractive summarization by specifying tokens as constraints that must be present in the summary. We explore the feasibility of using lexically constrained decoding, a technique applicable to any abstractive method with beam search decoding, to fulfill CAS and conduct experiments in two scenarios: (1) Standard summarization without human involvement, where keyphrase extraction is used to extract constraints from source documents; (2) Interactive summarization with human feedback, which is simulated by taking missing tokens in the reference summaries as constraints. Automatic and human evaluations on two benchmark datasets demonstrate that CAS improves the quality of abstractive summaries, especially on factual consistency. In particular, we observe up to 11.2 ROUGE-2 gains when several ground-truth tokens are used as constraints in the interactive summarization scenario.
“Same procedure as last year?” – Repeatedly tracked swifts show individual consistency in migration pattern in successive years

Individual migration pattern during non-breeding season is still a black box in many migratory birds. However, knowledge on both individual level and population level in migration and overwintering is fundamental to understand the life cycle of these birds and the constraints affecting them. We showed in a highly aerial migrant, the common swift Apus apus, that repeatedly tracked birds breeding at one site in Germany used the same individual-specific migration routes and wintering areas in subsequent years. In contrast, different individuals from the same breeding colony showed diverse movement patterns during non-breeding season suggesting that several suitable areas for overwintering coexist. We found lower variation in timing of autumn and spring migration within than between individuals. Our findings provide first indication of individual consistency but between-individual variation in migration pattern in a small non-passerine bird revealed by geolocators. This supports that swifts have diverse but individual-specific ‘step-by-step’ migration patterns revealing high flexibility through individual strategies. This article is protected by copyright. All rights reserved.