Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing Gender Roles in Dagaa Fishery Value Chain among Fishing Communities on Lake Victoria, A Case Study of Lake Victoria Beaches In Siaya County, Kenya

Fisheries in the East Africa region have suffered due to less emphasis given to some fishery specifically Dagaa (Rastrineobolaargentea), whose quantity is the highest of all the species in the Lake Victoria. Despite the importance of this resource in Kenya, there has been a concern of gender parity and inequality in terms of roles played by both gender in harvesting, processing, trading and marketing in the Dagaa fishery. This study analyzed gender roles in Dagaa Fishery Value Chain among fishing communities around Lake Victoria in Bondo Sub County, in Siaya County, Kenya. The study addressed the following objectives: Identified the various roles of men and women in Dagaa Fishery Value Chain, discussed factors influencing gender roles in Dagaa Fishery Value Chain, analyzed the barriers to women’s participation in certain Dagaa Fishery Value Chain and examined the strategies to overcome challenges in gender roles in Dagaa fishery value chain in Bondo Sub-County, Siaya County. The study adopted a cross-sectional research design. This study was guided by two models; gender analysis framework model that was developed by Sarah Longwe and supply chain model. Purposive sampling technique was used to select Bondo Sub-County and fishing community in Bondo Sub-County; random sampling technique was used to select five (5) fish landing sites/beaches where quantitative data were collected from 186 out of the targeted 188 primary respondents, from among the forty-four beaches of Lake Victoria in Bondo Sub-County. Quantitative data was analyzed using SPSS Version 25, and descriptive statistics such as frequencies and percentages were used in presenting analyzed data. The results were presented using tables and charts. The study findings revealed that majority of the boats and fishing gears were owned by men, motorized boats belonged to men while a higher percentage of females still had the paddled boats. While men dominated the fishing of Dagaa, women dominated processing and trading of Dagaa in the beaches. The study noted that men made higher returns than their female counterparts at all levels of Dagaa fishery value chain. The study concluded that there is a still wide disparity among gender roles in Dagaa fishery value chain. Most of the activities in the value chain are still dominated by men. This study recommends that women be encouraged to take part in Dagaa fishery value chains, empowerment of women to take part in transportation and distribution of Dagaa and application of various strategies such as joining SACCOs to access loans at low interest rates, formation of groups for ease of access to credit services and weakening patriarchy to mitigate factors affecting Gender roles in Dagaa fishery value chains.
A Comprehensive Knowledge Pedigree
on Environmental Transparency

Environmental transparency issue has drawn increasing concern, and the related research has shown explosive growth. A comprehensive knowledge pedigree of environmental transparency can help understand the spatial and temporal distribution of themes, research categories, cutting-edge research topics and development trends of environmental transparency research, providing research opportunities for the future. Based on the: Social Science Citation Index database in the Web of Science, this article retrieves 930 papers with the theme of “environment transparency” in all years, and analyzes the its knowledge system via the software of CiteSpace.
Mechanical Response of Gasketed Bell-and-Spigot Joint of Concrete Pipeline under Multifield Coupling

Concrete pipe may suffer joint failure under the coupling effect of internal fluid and overlying load, which may lead to pipe leakage. Based on Abaqus and Fluent finite element software, a three-dimensional refined model of drainage pipeline with gasketed bell-and-spigot joints and flow field model inside the pipeline was established. Fully considering the compression of the gasket during pipeline assembly and pipe-soil interaction, the fluid-structure coupling numerical simulation was carried out by using the MpCCI (Mesh-based parallel Code Coupling Interface) platform, and the mechanical response of the concrete pipe joint under the multifield loads coupling effects of burial condition, traffic load, and internal fluid was studied. The accuracy of the coupling model was verified through the full-scale tests that have been carried out. The influences of various factors on the circumferential stress and vertical deformation of the joint were mainly studied. The result reveals that the influence of different working conditions on the circumferential stress of the pipe joint is mainly concentrated on the crown and the invert of the joint, the areas vulnerable to tensile damage. The change of flow field leads to a slight difference in the vertical deformation of the joint, while variation in gasket hardness and cushion compactness has a certain influence on the vertical deformation of the joint. The change of buried depth has a negative correlation to the vertical deformation of the joint, and the change of load position has a significant nonlinear effect. The result provides a theoretical basis for further research on the mechanical mechanism of the pipeline joints during operation.
Thermo-kinetic explosions: Safety first or safety last?

Gas and vapour explosions have been involved in industrial accidents since the beginnings of industry. A century ago, at 11:55 am on Friday 24th September 1920, the petroleum barge Warwick exploded in London's docklands and seven men were killed. Understanding what happened when it blew up as it was being refurbished, and how to prevent similar explosions, involves chemistry plus fluid mechanics. I recount the 1920 accident as an example, together with the history of thermo-kinetic explosions prior to 1920 and up to the present day, and I review the history and the actual state of the science of ignition. The science of explosions has been aware of its societal implications from the beginning. Despite advances in health and safety over the past century, is there still work to do?
The Average Distance and the Diameter of Dense Random Regular Graphs

Let $\mathrm{AD}(G_{n,d})$ be the average distance of $G_{n,d}$, a random $n$-vertex $d$-regular graph. For $d=(\beta+o(1))n^{\alpha}$ with two arbitrary constants $\alpha\in(0,1)$ and $\beta>0$, we prove that $|\mathrm{AD}(G_{n,d})-\mu|<\epsilon$ holds with high probability for any constant $\epsilon>0$, where $\mu$ is equal to $\alpha^{-1}+\exp(-\beta^{1/\alpha})$ if $\alpha^{-1}\in\mathbb{N}$ and to $\lceil\alpha^{-1}\rceil$ otherwise. Consequently, we show that the diameter of the $G_{n,d}$ is equal to $\lfloor\alpha^{-1}\rfloor+1$ with high probability.
Gauge fixing for strongly correlated electrons coupled to quantum light

We discuss the problem of gauge fixing for strongly correlated electrons coupled to quantum light, described by projected low-energy models such as those obtained within tight-binding methods. Drawing from recent results in the field of quantum optics, we present a general approach to write down a quantum light-matter Hamiltonian in either dipole or Coulomb gauge which is explicitly connected by a unitary transformation, thus ensuring gauge equivalence even after projection. The projected dipole gauge Hamiltonian features a linear light-matter coupling and an instantaneous self-interaction for the electrons, similar to the structure in the full continuum theory. On the other hand, in the Coulomb gauge the photon field enters in a highly nonlinear way, through phase factors that dress the electronic degrees of freedom. We show that our approach generalizes the well-known Peierls approximation, to which it reduces when only local, on-site orbital contributions to light-matter coupling are taken into account. As an application we study a two-orbital model of interacting electrons coupled to a uniform cavity mode, recently studied in the context of excitonic superradiance and associated no-go theorems. Using both gauges we recover the absence of a superradiant phase in the ground state and show that excitations on top of it, described by polariton modes, contain instead nontrivial light-matter entanglement. Our results highlight the importance of treating the nonlinear light-matter interaction of the Coulomb gauge nonperturbatively, to obtain a well-defined ultrastrong coupling limit and to not spoil gauge equivalence.
Tasks, stability, architecture, and compute: Training more effective learned optimizers, and using them to train themselves

Much as replacing hand-designed features with learned functions has revolutionized how we solve perceptual tasks, we believe learned algorithms will transform how we train models. In this work we focus on general-purpose learned optimizers capable of training a wide variety of problems with no user-specified hyperparameters. We introduce a new, neural network parameterized, hierarchical optimizer with access to additional features such as validation loss to enable automatic regularization. Most learned optimizers have been trained on only a single task, or a small number of tasks. We train our optimizers on thousands of tasks, making use of orders of magnitude more compute, resulting in optimizers that generalize better to unseen tasks. The learned optimizers not only perform well, but learn behaviors that are distinct from existing first order optimizers. For instance, they generate update steps that have implicit regularization and adapt as the problem hyperparameters (e.g. batch size) or architecture (e.g. neural network width) change. Finally, these learned optimizers show evidence of being useful for out of distribution tasks such as training themselves from scratch.
Qlib: An AI-oriented Quantitative Investment Platform

Quantitative investment aims to maximize the return and minimize the risk in a sequential trading period over a set of financial instruments. Recently, inspired by rapid development and great potential of AI technologies in generating remarkable innovation in quantitative investment, there has been increasing adoption of AI-driven workflow for quantitative research and practical investment. In the meantime of enriching the quantitative investment methodology, AI technologies have raised new challenges to the quantitative investment system. Particularly, the new learning paradigms for quantitative investment call for an infrastructure upgrade to accommodate the renovated workflow; moreover, the data-driven nature of AI technologies indeed indicates a requirement of the infrastructure with more powerful performance; additionally, there exist some unique challenges for applying AI technologies to solve different tasks in the financial scenarios. To address these challenges and bridge the gap between AI technologies and quantitative investment, we design and develop Qlib that aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment.
A Riemannian Barycentric Interpolation : Application to the Parametric Unsteady Navier-Stokes Reduced Order Model

A new application of subspaces interpolation for the construction of nonlinear Parametric Reduced Order Models (PROMs) is proposed. This approach is based upon the Riemannian geometry of the manifold formed by the quotient of the set of full-rank N -by-q matrices by the orthogonal group of dimension q. By using a set of untrained parametrized Proper Orthogonal Decomposition (POD) subspaces of dimension q, the subspace for a new untrained parameter is obtained as the generalized Karcher barycenter which solution is sought after by solving a simple fixed point problem. Contrary to existing PROM approaches, the proposed barycentric PROM is by construction easier to implement and more flexible with respect to change in parameter values. To assess the potential of the barycentric PROM, numerical experiments are conducted on the parametric flow past a circular cylinder and the flow in a lid driven cavity when the value of Reynolds number varies. It is demonstrated that the proposed barycentric PROM approach achieves competitive results with considerably reduced computational cost.
The great Kite in the sky: A LOFAR observation of the radio source in Abell 2626

Context. The radio source at the center of the galaxy cluster Abell 2626, also known as the Kite, stands out for its unique morphology composed of four symmetric arcs. Previous studies have probed the properties of this source at different frequencies and its interplay with the surrounding thermal plasma, but the puzzle of its origin is still unsolved. Aims. We use a new LOw-Frequency ARray (LOFAR) observation from the LOFAR Two-meter Sky Survey at 144 MHz to investigate the origin of the Kite. Methods. We present a detailed analysis of the new radio data, which we combined with archival radio and X-ray observations. We produced a new, resolved spectral index map of the source with a resolution of 7″ and we studied the spatial correlation of radio and X-ray emission to investigate the interplay between thermal and nonthermal plasma. Results. The new LOFAR data changed our view of the Kite because we discovered two steep-spectrum (α < −1.5) plumes of emission connected to the arcs. The spectral analysis shows, for the first time, a spatial trend of the spectrum along the arcs with evidence of curved synchrotron spectra and a spatial correlation with the X-ray surface brightness. On the basis of our results, we propose that the Kite was originally an X-shaped radio galaxy whose fossil radio plasma, after the end of the activity of the central active galactic nucleus, has been compressed as a consequence of motions of the thermal plasma encompassing the galaxy. The interplay between the compression and advection of the fossil plasma, with the restarting of the nuclear activity of the central galaxy, could have enhanced the radio emission of the fossil plasma producing the arcs of the Kite. We also present the first, low-frequency observation of a jellyfish galaxy in the same field, in which we detect extended, low-frequency emission without a counterpart at higher frequencies.
Can we trust online crowdworkers?: Comparing online and offline participants in a preference test of virtual agents

Conducting user studies is a crucial component in many scientific fields. While some studies require participants to be physically present, other studies can be conducted both physically (e.g. in-lab) and online (e.g. via crowdsourcing). Inviting participants to the lab can be a time-consuming and logistically difficult endeavor, not to mention that sometimes research groups might not be able to run in-lab experiments, because of, for example, a pandemic. Crowdsourcing platforms such as Amazon Mechanical Turk (AMT) or Prolific can therefore be a suitable alternative to run certain experiments, such as evaluating virtual agents. Although previous studies investigated the use of crowdsourcing platforms for running experiments, there is still uncertainty as to whether the results are reliable for perceptual studies. Here we replicate a previous experiment where participants evaluated a gesture generation model for virtual agents. The experiment is conducted across three participant pools - in-lab, Prolific, and AMT - having similar demographics across the in-lab participants and the Prolific platform. Our results show no difference between the three participant pools in regards to their evaluations of the gesture generation models and their reliability scores. The results indicate that online platforms can successfully be used for perceptual evaluations of this kind.
Joint routing and pricing control of autonomous vehicles in mixed equilibrium simulation-based dynamic traffic assignment

Routing controllability of autonomous vehicles (AVs) has been shown to reduce the impact of selfish routing on network efficiency. However, the assumption that AVs would readily allow themselves to be controlled externally by a central agency is unrealistic. In this paper, we propose a joint routing and pricing control scheme that aims to incentivize AVs to seek centrally controlled system optimal (SO) routing by saving on tolls while user equilibrium (UE) seeking AVs and human-driven vehicles (HVs) are subject to a congestion charge. The problem is formulated as a bi-level optimization, in which dynamic tolls are optimized in the upper level, whereas the lower level is a mixed equilibrium simulation-based dynamic traffic assignment model considering mixed fleet of AVs and HVs. We develop a feedback-based controller to implement a second-based pricing scheme from which SO-seeking AVs are exempt; but UEseeking vehicles, including both AVs and HVs, are subject to a distance-based charge for entering a pricing zone. This control strategy encourages controllable AVs to adopt SO routing while discouraging UE-seeking users from entering the pricing zone. We demonstrate the performance of the proposed framework using the Nguyen network and a large-scale network model of Melbourne, Australia.
The affine Hecke category is a monoidal colimit

Let $G$ be a semisimple simply-connected algebraic group over an algebraically closed field of characteristic zero. We prove that the affine Hecke category associated to $G$ is equivalent to the colimit, evaluated in the $\infty$-category of stable monoidal $\infty$-categories, of the finite Hecke subcategories associated to standard parahoric subgroups of $G$. The same method yields analogous colimit presentations of the 0-Hecke monoid (where the colimit is taken in monoids in spaces) and of the Hecke algebra (where the colimit is taken in DG-algebras). We also construct a strong monoidal functor from any finite or affine type braid group to the corresponding Hecke category.
Cosine Similarity of Multimodal Content Vectors for TV Programmes

Multimodal information originates from a variety of sources: audiovisual files, textual descriptions, and metadata. We show how one can represent the content encoded by each individual source using vectors, how to combine the vectors via middle and late fusion techniques, and how to compute the semantic similarities between the contents. Our vectorial representations are built from spectral features and Bags of Audio Words, for audio, LSI topics and Doc2vec embeddings for subtitles, and the categorical features, for metadata. We implement our model on a dataset of BBC TV programmes and evaluate the fused representations to provide recommendations. The late fused similarity matrices significantly improve the precision and diversity of recommendations.
A Comparative Study on Structural and Semantic Properties of Sentence Embeddings

Sentence embeddings encode natural language sentences as low-dimensional dense vectors. A great deal of effort has been put into using sentence embeddings to improve several important natural language processing tasks. Relation extraction is such an NLP task that aims at identifying structured relations defined in a knowledge base from unstructured text. A promising and more efficient approach would be to embed both the text and structured knowledge in low-dimensional spaces and discover semantic alignments or mappings between them. Although a number of techniques have been proposed in the literature for embedding both sentences and knowledge graphs, little is known about the structural and semantic properties of these embedding spaces in terms of relation extraction. In this paper, we investigate the aforementioned properties by evaluating the extent to which sentences carrying similar senses are embedded in close proximity sub-spaces, and if we can exploit that structure to align sentences to a knowledge graph. We propose a set of experiments using a widely-used large-scale data set for relation extraction and focusing on a set of key sentence embedding methods. We additionally provide the code for reproducing these experiments at this https URL. These embedding methods cover a wide variety of techniques ranging from simple word embedding combination to transformer-based BERT-style model. Our experimental results show that different embedding spaces have different degrees of strength for the structural and semantic properties. These results provide useful information for developing embedding-based relation extraction methods.
Gauge transformation of scalar induced tensor perturbation during matter domination

The scalar-induced secondary gravitational wave as the stochastic gravitational background is a useful tool to study the physics in the early universe. We study the scalar-induced tensor perturbations at second-order during matter domination in seven different gauges. We obtain the results in six other gauges from that in the Newtonian gauge using the gauge transformation law of the scalar-induced tensor perturbation. We find that the kernel functions ${I}_{\ensuremath{\chi}}$ in the synchronous and comoving orthogonal gauges are the same if the residual gauge modes in these two gauges are eliminated. By identifying the oscillating terms $\mathrm{sin}x$ and $\mathrm{cos}x$ in the scalar-induced tensor perturbations as the scalar-induced secondary gravitational waves, we find that its energy density is actually gauge independent. The energy density ${\ensuremath{\rho}}_{\mathrm{GW}}\ensuremath{\propto}{a}^{\ensuremath{-}4}$, or ${\mathrm{\ensuremath{\Omega}}}_{\mathrm{GW}}\ensuremath{\propto}{a}^{\ensuremath{-}1}$ in the matter-dominated era, and the scalar-induced secondary gravitational waves behave as radiation.
Phase I (3 hour infusion every 3 weeks) escalating dose study of intravenous ES-285 in patients with advanced malignant solid tumors

A4 Background: ES-285 is a synthetic small molecule originally found in the marine mollusc Spisula Polynyma. A phase I program including four clinical trials with different schedules of administration was launched. This study assessed a 3 hour (h) infusion every 3 weeks (w) schedule. The primary objectives were to evaluate the safety and tolerability of ES-285 and to define the dose limiting toxicities (DLTs) and maximum tolerated dose (MTD). Secondary objectives were preliminary pharmacokinetics and preliminary information on the anti-tumor activity of ES-285. Methods: The starting dose was 4 mg/m2. Cohorts of 3-6 patients (pts) and a minimum of additional 8 pts during the expanded cohort, were treated at doses (4, 8, 16, 32, 64, 128, 256, 200 and 160 mg/m2). PK sampling was performed in the first infusion. The last 6 patients included at 160 mg/m2 had brain tumor. Results: 61 pts have been registered. Median age was 52 years (range 25-73) and median performance status was 1 (range 0-2). There were DLTs at the two higher dose levels 2/2 and 3/19 pts at 256mg/m2 and 200 mg/m2 respectively . DLTs were asymptomatic grade 3-4 reversible transaminases elevation (RTE) and grade 3 self-limited (24 hours) confusional syndrome. Other toxicities observed included phlebitis and pyrexia as well as headache appearing early post- infusion. The RD has been reached at 160 mg/m2 with 21 pts included. One non confirmed partial response (PR) after 2 cycles was obtained in a metastatic melanoma at 128 mg/m2 and a SD for 16 cycles was obtained in a patient with glioblastoma at 160 mg/m2 . ES-285 is a long half-life, approximately 50 hours and wide distribution drug (Vss in excess of 3000 L). ES-285 pharmacokinetics appears dose linear in this schedule. Conclusion: ES-285 administered as a 3 h infusion every 3 w has a toxicity profile that makes this schedule feasible. The MTD is 200 mg/m2 and theRD is 160 mg/m2 .