Miracle-dz/UniFAR-FTUs huggingface dataset:
Unsupervised Natural Language Inference via Decoupled Multimodal Contrastive Learning

We propose to solve the natural language inference problem without any supervision from the inference labels via task-agnostic multimodal pretraining. Although recent studies of multimodal self-supervised learning also represent the linguistic and visual context, their encoders for different modalities are coupled. Thus they cannot incorporate visual information when encoding plain text alone. In this paper, we propose Multimodal Aligned Contrastive Decoupled learning (MACD) network. MACD forces the decoupled text encoder to represent the visual information via contrastive learning. Therefore, it embeds visual knowledge even for plain text inference. We conducted comprehensive experiments over plain text inference datasets (i.e. SNLI and STS-B). The unsupervised MACD even outperforms the fully-supervised BiLSTM and BiLSTM+ELMO on STS-B.
Background Risk and Small-Stakes Risk Aversion.

We show that under plausible levels of background risk, no theory of choice under risk---such as expected utility theory, prospect theory, or rank dependent utility---can simultaneously satisfy the following three economic postulates: (i) Decision makers are risk-averse over small gambles, (ii) they respect stochastic dominance, and (iii) they account for background risk.
Semantic Editing On Segmentation Map Via Multi-Expansion Loss

Semantic editing on segmentation map has been proposed as an intermediate interface for image generation, because it provides flexible and strong assistance in various image generation tasks. This paper aims to improve quality of edited segmentation map conditioned on semantic inputs. Even though recent studies apply global and local adversarial losses extensively to generate images for higher image quality, we find that they suffer from the misalignment of the boundary area in the mask area. To address this, we propose MExGAN for semantic editing on segmentation map, which uses a novel Multi-Expansion (MEx) loss implemented by adversarial losses on MEx areas. Each MEx area has the mask area of the generation as the majority and the boundary of original context as the minority. To boost convenience and stability of MEx loss, we further propose an Approximated MEx (A-MEx) loss. Besides, in contrast to previous model that builds training data for semantic editing on segmentation map with part of the whole image, which leads to model performance degradation, MExGAN applies the whole image to build the training data. Extensive experiments on semantic editing on segmentation map and natural image inpainting show competitive results on four datasets.
Training Data Generating Networks: Linking 3D Shapes and Few-Shot Classification

We propose a novel 3d shape representation for 3d shape reconstruction from a single image. Rather than predicting a shape directly, we train a network to generate a training set which will be feed into another learning algorithm to define the shape. Training data generating networks establish a link between few-shot learning and 3d shape analysis. We propose a novel meta-learning framework to jointly train the data generating network and other components. We improve upon recent work on standard benchmarks for 3d shape reconstruction, but our novel shape representation has many applications.
Cosmic-Ray Extremely Distributed Observatory

The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a newly formed, global collaboration dedicated to observing and studying cosmic rays (CR) and cosmic-ray ensembles (CRE): groups of at least two CR with a common primary interaction vertex or the same parent particle. The CREDO program embraces testing known CR and CRE scenarios, and preparing to observe unexpected physics, it is also suitable for multi-messenger and multi-mission applications. Perfectly matched to CREDO capabilities, CRE could be formed both within classical models (e.g., as products of photon–photon interactions), and exotic scenarios (e.g., as results of decay of Super-Heavy Dark Matter particles). Their fronts might be significantly extended in space and time, and they might include cosmic rays of energies spanning the whole cosmic-ray energy spectrum, with a footprint composed of at least two extensive air showers with correlated arrival directions and arrival times. As the CRE are predominantly expected to be spread over large areas and, due to the expected wide energy range of the contributing particles, such a CRE detection might only be feasible when using all available cosmic-ray infrastructure collectively, i.e., as a globally extended network of detectors. Thus, with this review article, the CREDO Collaboration invites the astroparticle physics community to actively join or to contribute to the research dedicated to CRE and, in particular, to pool together cosmic-ray data to support specific CRE detection strategies.
Attraction range of a sex pheromone trap for the damson‐hop aphid Phorodon humuli (Hemiptera: Aphididae)

The attraction range of olfactory response by winged female gynoparae (autumn migrants that give birth to oviparae, the sexual females) and male damson–hop aphids Phorodon humuli (Schrank) is investigated in field experiments over 2 years by analyzing the spatial patterns of catches in concentric circles of yellow‐painted traps (60 in total) around a central trap releasing the species' sex pheromone, (1RS,7S,7aS)‐nepetalactol. Males are more likely than females to be found in the central trap, with 65.6% of the 1824 males caught there compared with 11.2% of 1346 females. Both morphs are more numerous in traps axial with the mean wind direction and centred on the pheromone‐release trap than at other angles. Males are approximately five‐fold more numerous in traps downwind than at similar distances upwind of the pheromone, showing that its presence stimulates landing. For males, the estimated active space of the lure extends 6 m downwind. Catches of females are equally numerous up and downwind of the pheromone lure because females orienting on the axis of the pheromone source continue to respond to visual cues in their flight path if they overshoot the olfactory one. For females, the active space of a pheromone lure is less than 2 m downwind. It is unimportant for either morph whether the pheromone‐release trap is yellow or transparent. In these experiments, both morphs orient with, track and probably arrive in the pheromone source trap from at least 26 m, the distance to the nearest aphid‐infested hops.
Preparation of Three Fasciola gigantica antigens and determination of their efficacy as a vaccine for protection against fascioliasis in Rabbits

This study was included the preparation of vaccine against fascioliasis from three Fasciola gigantica antigens, somatic antigen, excretory-secretory antigen and partially purified cathepsin antigen. Their vaccine efficacy was tested in rabbits, by using 12 Lepus lepus arabica rabbit, aged 2 months, similar weight. The rabbits were subdivided to three groups each of four rabbits and was vaccinated with one antigen emulsified in freund adjuvant. In compare to control groups Which involved 4 rabbits vaccinated with PBS and other four left without vaccination, challenge infection was done by vaccination the animals with 90 metacercaria obtained from experimentally infected intermediate host. All animals were killed 12 weeks after challenge. Protein concentration of all prepared antigens and the molecular weight of P.P.CatA was also measured, which reached (1.5, 1.2 and 0.04) mg/ml in SA, ESA and P.P.CatA respectively, while P.P.CatA 26.7 KD. Protection estimated by followed number of aspects, the first aspect of this study, was the determination the hepatic damage which was evaluated using gross morphometric observations depending upon the severity and intensity of lesions. Significant differences (p<0.05) was noted between vaccinated and control groups. The second aspect was concerned with estimation of fluke number and reduction rate, the high rate (81.3%) recorded in animals vaccinated with P.P.CatA while (39.53%) of those vaccinated with SA. Significant differences (p<0.05) was documented in the length of fluke in animals vaccinated with P.P.CatA. No significant differences were noted in fluke burden (width, length, weight) and fecal egg counts, Significant differences (p<0.01) were noted in egg viability and reduction rate in the vaccinated animals in comparison with control group. ELISA was used for monitoring of IgG levels in all vaccinated and control animals, before and after infection. The IgG increased in the sera of animals vaccinated with SA, ESA and P.P.CatA within 1 week after the first injection. A boosting of the antibody responses was observed in all groups following both the second and third immunization. An increasing in the antibody titers in all vaccinated animals was observed within 2 weeks following challenge. IgG in all vaccinated groups remained high throughout the infection but decreased at approximately 6 weeks after infection, and then remained constant throughout the subsequent weeks. Antibodies to antigens in the sera of the control group increased within the first 2 to 4 weeks after infection but decreased at approximately 8 weeks and then remained constant throughout the subsequent weeks. Accordingly, the results of these aspects could be consider a P.P.CatA as a first best vaccine then secondly ESA.
Potassium requirements of pastures on North Island east coast hill country in New Zealand

ABSTRACT The effects of potassium (K) (0–160 kg/ha/yr) on soil and pasture were measured in five small plot mowing sites on flat and easy slopes in Hawkes Bay hill country from 2004 to 2007. Initial soil QT K levels ranged from 1.6 to 3.8 at each site and increased to a range of 3.5–11.3 at the highest rate of K in the third year. At most sites, clover cover on some occasions increased up to the highest rate of K. Despite this increase, there was only one significant response in pasture production to K at one site in the third year. Possible reasons for the lack of a total DM production response to K application were more grass growth compensating for less clover growth at the nil and lower rates of K or insufficient transfer of nitrogen from the clover to grasses at higher rates of K.
Enslaved Laborer and Sharecropper Fishing Practices in 18th-19th Century Martinique: A Zooarchaeological and Ethnozoohistorical Study

Throughout the modern day Caribbean, artisanal fishing constitutes an important part of domestic subsistence and household economies. Many of the traditional fishing practices on the islands today were established during the Colonial Period, as enslaved Africans and their descendants developed social, economic, and subsistence strategies to persist under the plantation system. The historical record provides little insight into the day-to-day experiences of these enslaved laborers, including their subsistence regimes and practices. Fishing by slaves in the colonial French Antilles is portrayed in the historic literature as a practice reserved primarily for an “elite” group of fisherman held on wealthy plantations. Archaeology provides insight into the pieces of history left out of the written record and offers valuable information regarding the everyday lives of the enslaved peoples and communities underrepresented in this record. This article presents the results of the zooarchaeological analysis of faunal remains recovered from enslaved laborer and sharecropper occupations at Habitation Crève Cœur, an eighteenth–nineteenth century sugar plantation on the island of Martinique. The data reveal that fishing was an important economic activity for the slaves on this plantation and that the practice of fishing was likely more of a communal act than one for a privileged few. Furthermore, analysis indicates that fishing techniques that continue on the island today originated centuries ago, traditions developed by enslaved laborers living under the severe constraints of the oppressive plantation system.
Study the Effect of Hyperthyroidism on Heart Function by Using BNP as Indicator

The aim was made to specify the effect of hyperthyroidism on B-type natriuretic peptide (BNP) level. Twenty patients with hyperthyroidism, 20 patients with hyperthyroidism treated with (35) mg Carbimazole, 12 patients with hyperthyroidism associated with heart failure and 20 healthy participants were included in this study. Serum Triiodothyronine (T3), Thyroxin (T4) and Thyroid stimulating hormone (TSH) have been used for hyperthyroidism diagnosis test, also serum BNP level was measured. The results showed that the mean ± SE of serum BNP was significantly (P<0.05) increased in hyperthyroid group (420.76 ± 83.43) pg/mL and hyperthyroid with heart failure group (728.58±149.06) pg/mL when compared with the control group (23.18 ±10.10) pg/mL. While, no significant (P>0.05) differences between hyperthyroid treated with (35) mg carbimazole group (65.00 ± 16.21) pg/mL and control group (23.18 ±10.10) pg/mL. But, there was a significant (p<0.05) decrease in serum BNP level in hyperthyroid treated with (35) mg carbimazole group when compared with the hyperthyroid group and hyperthyroid with heart failure group. The present study demonstrated that the hyperthyroidism may lead to impaired heart function, and thus the high level of the BNP hormone
Valorization Strategy of Banana Passion Fruit Shell Wastes: An Innovative Source of Phytoprostanes and Phenolic Compounds and Their Potential Use in Pharmaceutical and Cosmetic Industries

At present, people with today's busy lifestyle have a general trend of consuming fruit like banana passion fruit (Passiflora tripartita var. mollisima) as juices or smoothies, being an increasing tendency that can generate a large amount of agro-industrial residues. Whereby, food industries have a significant investment to minimize these wastes generated or devise alternatives of residue use. So, food researches are aimed to exploit these fruit waste. In this sense, this study has allowed the detection for the first time, in banana passion fruit shell, phytoprostanes (PhytoPs), oxylipins with multiple biological activities in humans. Furthermore, this study, with methodology used (LC-MS) allowed us to detect higher amount of these compounds (2318.63 ± 71.51 µg/100 g DW) than other vegetable matrices previously studied (macroalgae, olives or almonds, among others). In addition, we were able to identify 14 phenolic compounds (including cinnamoyl acid derivatives, flavonoid-O-glycoside, flavonoid-C-glycosides), not previously described in this matrix. Hence, this work increased the knowledge about the bioactive compounds profile of banana passion fruit shells and thereby to achieve a product with added value that may be used as natural source of bioactive compounds as alternative of synthetic substances in several industries of pharmaceutic or cosmetic fields.
Habitat fragmentation and the prevalence of parasites (Diptera, Streblidae) on three Phyllostomid bat species

Ectoparasitism in bats seems to be influenced strongly by the type of roost preferred by the hosts, and group size; however, the effect of habitat loss and fragmentation on the prevalence of ectoparasites in bats has scarcely been studied. In northeastern Yucatan, Mexico, we estimated the prevalence of infestation by Streblidae flies in three phyllostomid bat species with different roost preferences (caves, trees, or both) in two types of landscape matrices (tropical semi‐deciduous forest and man‐made pastures) that differed in area of forest cover and the number of forest fragments. Habitat fragmentation and the presence of a contrasting matrix may limit the availability of roosts (trees) and the movement of bats across the landscape. Accordingly, we hypothesized higher prevalence of Streblidae infestation in the pasture matrix and in the group of bats that roost in trees. Bat abundance was higher in the pasture matrix; however, the prevalence of infestation was significantly higher in the continuous forest matrix and in bats that roosted in caves. The prevalence of some species of Streblidae was affected by habitat fragmentation in species that roost in caves, such as Desmodus rotundus, as well as those using foliage and caves, such as Artibeus jamaicensis. Our results provide evidence that some species of Streblidae may respond differently to habitat fragmentation than their hosts, generating changes to bat‐ectoparasite interactions in fragmented areas. Environmental variations involving roosts, not evaluated in this study, may influence our results, since these factors affect ectoparasite abundance and reproduction.
Modules with Non-Cyclic Socle and the Extension Property

In 2009, J. Wood proved that Frobenius bimodules have the extension property for symmetrized weight compositions. More generally, it was later shown that having a cyclic socle is sufficient for satisfying the property, while the necessity remained an open question. In this thesis, a partial converse is proved. For a significant class of finite module alphabets, the cyclic socle condition is shown necessary for satisfying the extension property. The idea is to use a new weight function to return to the original case of Hamming weight.
DNA barcoding and first records of two rare Adicella species (Trichoptera: Leptoceridae) in Croatia

Abstract Two species of the genus Adicella, A. cremisa Malicky, 1972 and A. balcanica Botosaneanu & Novak,1965, were recorded in the summer period of 2014 which represent the first records of these species in Croatia. The former was collected at two relatively distant sites, the Krapina and the Zrmanja rivers, while the later was collected at the Krupa River. Both species were identified by morphological characteristics as well as DNA barcoding method. We calculated the uncorrected pairwise distances within Adicella and used molecular phylogenetic approach to delimit species. A. cremisa from Croatia showed no significant difference in the mtCOI region and they are highly similar to A. cremisa from Italy. Additionally, the ecological preferences and distribution of Adicella species are presented. Our findings represent a significant contribution to the aquatic biodiversity of the Western Balkans.
On the exact computation of linear frequency principle dynamics and its generalization

Recent works show an intriguing phenomenon of Frequency Principle (F-Principle) that deep neural networks (DNNs) fit the target function from low to high frequency during the training, which provides insight into the training and generalization behavior of DNNs in complex tasks. In this paper, through analysis of an infinite-width two-layer NN in the neural tangent kernel (NTK) regime, we derive the exact differential equation, namely Linear Frequency-Principle (LFP) model, governing the evolution of NN output function in the frequency domain during the training. Our exact computation applies for general activation functions with no assumption on size and distribution of training data. This LFP model unravels that higher frequencies evolve polynomially or exponentially slower than lower frequencies depending on the smoothness/regularity of the activation function. We further bridge the gap between training dynamics and generalization by proving that LFP model implicitly minimizes a Frequency-Principle norm (FP-norm) of the learned function, by which higher frequencies are more severely penalized depending on the inverse of their evolution rate. Finally, we derive an \textit{a priori} generalization error bound controlled by the FP-norm of the target function, which provides a theoretical justification for the empirical results that DNNs often generalize well for low frequency functions.
Estimation of Discrete Choice Models: A Machine Learning Approach

In this paper we propose a new method of estimation for discrete choice demand models when individual level data are available. The method employs a two-step procedure. Step 1 predicts the choice probabilities as functions of the observed individual level characteristics. Step 2 estimates the structural parameters of the model using the estimated choice probabilities at a particular point of interest and the moment restrictions. In essence, the method uses nonparametric approximation (followed by) moment estimation. Hence the name---NAME. We use simulations to compare the performance of NAME with the standard methodology. We find that our method improves precision as well as convergence time. We supplement the analysis by providing the large sample properties of the proposed estimator.
An Approximation Algorithm for Optimal Subarchitecture Extraction

We consider the problem of finding the set of architectural parameters for a chosen deep neural network which is optimal under three metrics: parameter size, inference speed, and error rate. In this paper we state the problem formally, and present an approximation algorithm that, for a large subset of instances behaves like an FPTAS with an approximation error of $\rho \leq |{1- \epsilon}|$, and that runs in $O(|{\Xi}| + |{W^*_T}|(1 + |{\Theta}||{B}||{\Xi}|/({\epsilon\, s^{3/2})}))$ steps, where $\epsilon$ and $s$ are input parameters; $|{B}|$ is the batch size; $|{W^*_T}|$ denotes the cardinality of the largest weight set assignment; and $|{\Xi}|$ and $|{\Theta}|$ are the cardinalities of the candidate architecture and hyperparameter spaces, respectively.
Restless reachability in temporal graphs

We study a family of temporal reachability problems under waiting-time restrictions. In particular, given a temporal graph and a set of source vertices, we find the set of vertices that are reachable from a source via a time-respecting path, and such that the difference in timestamps between consecutive edges is at most a resting time. This kind of problems have several interesting applications in understanding the spread of a disease in a network, tracing contacts in epidemic outbreaks, and finding signaling pathways in the brain network. We present an algebraic algorithm based on constrained multilinear sieving for solving the restless reachability problems we propose. With an open-source implementation we demonstrate that the algorithm can scale to large temporal graphs with tens of millions of edges, despite the problem being NP-hard. The implementation is efficiently engineered and highly optimized. For instance, we can solve the restless reachability problem by restricting the path length to $9$ in a real-world graph dataset with over 36 million directed edges in less than one hour on a 4-core Haswell desktop.
Towards truly local gradients with CLAPP: Contrastive, Local And Predictive Plasticity

Back-propagation (BP) is costly to implement in hardware and implausible as a learning rule implemented in the brain. However, BP is surprisingly successful in explaining neuronal activity patterns found along the cortical processing stream. We propose a locally implementable, unsupervised learning algorithm, CLAPP, which minimizes a simple, layer-specific loss function, and thus does not need to back-propagate error signals. The weight updates only depend on state variables of the pre- and post-synaptic neurons and a layer-wide third factor. Networks trained with CLAPP build deep hierarchical representations of images and speech.