Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Scale Rotation-Invariant Haar-Like Feature Integrated CNN-Based Ship Detection Algorithm of Multiple-Target Environment in SAR Imagery

This paper proposes a multi-scale rotation-invariant haar-like (MSRI-HL) feature integrated convolutional neural network (MSRIHL-CNN)-based ship detection algorithm of the multiple-target environment in synthetic aperture radar (SAR) imagery. Usually, ship detection includes preprocessing, prescreening, discrimination, and classification. Among them, prescreening and discrimination are the most two important stages so that they catch great intention. Based on our previous work, we propose a truncated-clutter-statistics-based joint, constant false alarm rate (CFAR) detector (TCS-JCFAR) for ship target prescreening in the multiple-target environment. TCS-JCFAR greatly enhances the prescreening rate in the multiple-target environment while achieving a low observed FAR. In the discrimination stage, conventional CNN extracts the deep features (high-level features); however, it will lose the local texture and edge information (low-level features) which are of great significance for target discrimination. Hence, the MSRI-HL features are used to represent the multi-scale, rotation-invariant texture, and edge information that conventional CNN fails to capture. The extracted low-level MSRI-HL features and the high-level deep features are optimally fused to a multi-layered feature vector. Finally, the multi-layered feature vector is fed into a typical support vector machine (SVM) classifier for ship target discrimination. The proposed MSRIHL-CNN combines the low-level texture and edge features and the high-level deep features; moreover, they are optimally fused to fully represent the ship targets. Undoubtedly, MSRIHL-CNN has better discrimination performance. The superiority of the proposed TCS-JCFAR-based prescreener and MSRIHL-CNN-based discriminator is validated on the Chinese Gaofen-3 SAR imagery.
Multi-Switch Cooperative In-Network Aggregation for Distributed Deep Learning

Distributed deep learning (DDL) has recently been proposed to accelerate the training process of a deep learning model. The core idea is to have multiple workers collaboratively train a model in parallel. DDL, however, relies on synchronization among participating workers, which introduces significant communication overhead. To resolve this issue, recent research has demonstrated the effectiveness of in-network aggregation (INA), which reduces the bandwidth requirement of DDL training by allowing a programmable switch to combine the parameters of workers and only forward the aggregated parameter to the master. We, however, notice that existing approaches mainly focus on single-switch in-network aggregation and may overload a switch when the number of competing training jobs grows. In this work, we present Multi-Switch In-Network Aggregation (MS-INA), a system that efficiently offloads the aggregation load of DDL jobs across the switches of a network. To fully leverage the potential of all the available programmable switches for aggregation jobs, we assign each training job an aggregator switch that minimizes the end-to-end training latency. To this end, our MS-INA identifies the optimal switch that not only performs efficient aggregation but also introduces a short parameter forwarding latency. The trace-driven evaluation demonstrates that MS-INA effectively leverages the computational capability of all the switches and increases the number of successfully aggregated parameters by up to 5.3× as compared to conventional single-switch INA. The increasing aggregation capability contributes to bandwidth reduction by up to 64%.
The Distribution of Public Expenditure: The Case of Health Care

In contrast to the amount of attention paid recently to the distribution of income and wealth, very little work has been done in Britain on the distribution of public expenditure. The gap is particularly wide in the case of the distribution of expenditure conferring "benefits-in-kind", such as that on the public provision of education or health care. There are a number of North American studies, particularly on education (see, for example, Gillespie, 1965; Hansen and Weisbrod, 1969; Pechman, 1970; and Judy, 1970). However the only recent British work is the annual estimates of tax and social services produced by the Central Statistical Office (see Harris, 1977); and these do not pretend to be an elaborate study of the distribution of expenditure on benefits-in-kind, the distribution being simply assumed to be equal for individuals of the same age and sex. This omission is a serious one. Since expenditure on benefits-in-kind is an important part of the so-called "social wage", and since the latter has become a focus of political attention (being used, for example, as a partial justification for the holding down of "private" wages), it seems important to establish exactly how such expenditure is distributed between different groups in the population. This paper is an attempt to do so for one element of the social wage: the distribution of public expenditure on the National Health Service (NHS). The paper relates public expenditure on the Health Service to the incidence of illness by socioeconomic group, in order to see whether the position in society where an individual is placed affects the amount of medical treatment he receives when he is ill. It is divided into five parts. In Section I the distribution of morbidity (or ill health) among different social groups in the population is discussed. In Section II an attempt is made to estimate the costs of the health service facilities used by different social groups, and to relate this to the morbidity of the groups. The calculations are very tentative, and should not be regarded as in any way definitive. In Section III some possible explanations for the results are discussed. In Section IV some of the implications of the results are explored, and the conclusions are briefly summarized in Section V. The paper is a substantially revised version of evidence submitted to the Royal Commission on the Health Service (Le Grand, 1976). Access to more data has permitted the use of a method of calculation superior to that used in the Royal Commission evidence. Reassuringly, the change in the methods of calculation has not greatly changed the results. For reasons described below the basic source for the data used in the calculations is the health section of the General Household Survey undertaken by the Office of Population Censuses and Surveys (henceforth OPCS),
Prostate-Specific Membrane Antigen Is a Biomarker for Residual Disease following Neoadjuvant Intense Androgen Deprivation Therapy in Prostate Cancer

Purpose: Neoadjuvant intense androgen deprivation therapy (iADT) can exert a wide range of histological responses, which in turn are reflected in the final prostatectomy specimen. Accurate identification and measurement of residual tumor volumes are critical for tracking and stratifying patient outcomes. Materials and Methods: The goal of this current study was to evaluate the ability of antibodies against prostate-specific membrane antigen (PSMA) to specifically detect residual tumor in a cohort of 35 patients treated with iADT plus enzalutamide for 6 months prior to radical prostatectomy. Results: Residual carcinoma was detected in 31 patients, and PSMA reacted positively with tumor in all cases. PSMA staining was 96% sensitive for tumor, with approximately 82% of benign regions showing no reactivity. By contrast, PSMA positively reacted with 72% of benign regions in a control cohort of 37 untreated cases, resulting in 28% specificity for tumor. PSMA further identified highly dedifferentiated prostate carcinomas including tumors with evidence of neuroendocrine differentiation. Conclusions: We propose that anti-PSMA immunostaining be a standardized marker for identifying residual cancer in the setting of iADT.
Modification Identification in Recipe Comments 2 Introduction 2.1 Background 2.2 Design Process

1 Abstract Recipes are commonly modified for health, taste, ingredient availability reasons. A summary of modifications by other users of a recipe is useful in determining whether a proposed modification will be successful. We present a system for identifying modifications in comments posted on recipe websites. As a secondary goal, our system design process demonstrates how we can combine human understanding and machine learning techniques to rapidly construct a practical application with a minimal of annotated data. There is a proliferation of recipe websites and data available on the internet. While tools exists to assist in the discovery of the best recipes (e.g., recommendation systems based on user ratings and history ala Netflix), there is no quick way of determining whether a particular recipe will is suitable. Typically, users are forced to skim through large number of comments, easily exceeding hundreds on the most popular recipes, in order to determine whether they can make a particular substitution (e.g., to replace an ingredient not on hand with one that is available) successfully. This is essentially a sentiment classification task (" I think this recipe should be modified "). In this domain, we are helped by the domain specific jargon[1] but we are hurt by the subtleness of sentiments[2]. We will attempt to construct a system that collects the domain specific factors through unsupervised learning and use a small human annotated data set to learn about the semantics of various sentiments. Our main design methodology was to quickly build a commercially viable system (i.e. one that can be plugged into an existing website immediately). We do this through a combination of code reuse and smart pipeline development. We try to avoid custom code whenever possible, opting for well supported libraries instead. Our processing pipeline is designed to be fast and robust, but more importantly, the process to design the pipeline was designed to be intuitive. That is, we try to demonstrate a method for developing other such classification tools quickly. This was achieved through a combination of supervised machine learning with small datasets and human reasoning. In the end, we hope to have gained insights into the problem rather than just a set of coefficients. As a result, we prefer methods like decision trees and feature based classifiers over principal component analysis based classifiers.
Opportunistic Linked-Increases Congestion Control Algorithm for MPTCP

This document describes the mechanism of OLIA, the "Opportunistic Linked Increases Algorithm". OLIA is a congestion control algorithm for MPTCP. The current congestion control algorithm of MPTCP, LIA [4], forces a tradeoff between optimal congestion balancing and responsiveness. OLIA's design departs from this tradeoff and provide these properties simultaneously. Hence, it solves the identified performance problems with LIA while retaining non- flappiness and responsiveness behavior of LIA, as shown by different studies [5, 6, 7, 8]. OLIA is now part of the UCLouvain's MPTCP implementation [9, 11].
The Micro-Endscraper: A New Tool Type of the Chalcolithic Period

Although certain aspects of the material culture of the Chalco lithic period have been known for more than fifty years, the flint assemblages of this time-span have been studied only sporadically. The large samples of flint artifacts recovered in the large-scale excavations of Teleilat Ghassul and the Beer Sheva sites have been only briefly described or totally ignored. The flint assemblages of T. Ghassul were published in Ghassul I-II by Neuville (1934) and Mahan (1940). Probably the richest sample, the assemblage from this site is described by Neuville without specifying the frequencies of the various artifact types. Whereas for the potsherds, "en raison de son importance" (Ghassul 1:55),their provenance was mentioned, the "less important" flint artifacts were treated as a unit, ignoring their distribution in time and space. For the Beer Sheva Chalcolithic sites, which must have yielded thousands of flint artifacts, only a preliminary description of a small sample from l:Iorvat Beter is available (Yeivin 1959). Since many of these implements were thrown away, these pieces are not available for further study. Of the flint assemblages of Bir Safadi and Bir Abu-Matar (Perrot 1968) nothing is yet published. The Besor sites near Tell el-Far'ah (S) yielded rich flint assemblages, but these were published a long time ago (BP II). To summarize, the flint assemblages of the Chalcolithic sites from the southern half of Israel and from T. Ghassul, i.e. the largest, richest and best preserved sites, are inadequately known; the information is either partial, outdated or missing entirely. During the past three decades, advanced methods for the analysis of flint artifacts have been applied to the local Stone Age flint assemblages. The result has been a much better understanding of the Palaeolithic cultural development and distribution. However, these methods have barely been applied to the study of Chalcolithic assemblages. The large quantities of pottery sherds found at these sites are still generally considered to be more "informative" than their flint artifacts. Recent studies of the known assemblages from the Tell el-Far'ah area by Roshwalb (1981) and new assemblages from northeastern Sinai by Gilead (Oren and Gilead 1981) have shown that the flint artifacts are significant components of the material culture and merit serious attention. The systematic collection of these artifacts, sifting of deposits for the recovery of the minute elements in the assemblage and an attribute analysis of the finds are essential for the proper understanding of the material culture. A further contribution towards a better understanding of the Chalco lithic flint assemblages is provided below in presenting a new tool type: the micro-endscraper.
TIVMM: An effective map algorithm for low-sampling-rate GPS trajectories in road networks

In the process of map matching, we often encounter such a scenario. When there are two parallel paths between two points and the diver actually chooses the path that is longer. This scenario can be handled very well by high-sampling-rate based map matching algorithm. However, due to their limited energy budgets of the handheld GPS devices, they are more capable to provide low-sampling-rate trajectories. And the existing low-sampling-rate map matching algorithm cannot be applied directly to the scenario discussed before. Hence this paper proposes a Time Interactive Voting Map Matching (TIVMM) algorithm to resolve the problem. TIVMM algorithm considers the spatial geometry and topological structures of the road network, the speed constraints of the paths, the actual traveling time and the strength of the mutual influence. Extensive evaluations are performed and the results show that the proposed algorithm can provide higher accuracy compared to the existing approaches.
2 Busemann spaces and their ideal compactifications

In this paper, we consider Busemann non-positively curved spaces (shortly Busemann spaces). The term Busemann space was introduced by B. Bowditch in [2], the general geometric information on Busemann non-positively curved spaces can be found in [11]. The class of Busemann spaces contains all CAT (0)-spaces and strongly convex normed spaces. When X is a complete locally compact CAT (0)-space, its geometry depends badly on the geometric boundary at infinity ∂∞X and Tits metric Td on it. Busemann’s curvature non-positivity condition is weaker then Alexandrov’s one. This leads to definite specialties of the geometry at infinity in Busemann spaces. Firstly, there are two natural approaches for the definition of the geometric boundary at infinity. In the CAT (0)-case the two approaches gives the same result, but when X is Busemann space the results can be essentially different. We are to consider two different ideal boundaries — horofunction (or metric) one and geodesic one. Secondly, even the two boundaries coincide, there are no natural way to define a metric on ∂∞X with properties of Tits metric. We propose the following trick that allows using the properties of Tits metric without the definition of the metric itself. Note that there are two key values of Tits metric on ideal boundary of CAT (0)-space. The values are π and π/2. Conditions for ideal points ξ, η ∈ ∂∞X under which inequalities Td(ξ, η) ≥ π, (1.1) Td(ξ, η) ≤ π (1.2)
Effectiveness of high dose sublingual immunotherapy to induce a stepdown of seasonal asthma: a pilot study

Abstract Background: There is ample evidence to support the efficacy of sublingual immunotherapy (SLIT) on allergic rhinitis, while there is less solid data regarding asthma. We evaluated the effects of a high dose birch SLIT on birch-induced rhinitis and asthma in a controlled study. Methods: This double-blind, placebo-controlled, randomised, single centre trial on SLIT with birch pollen allergen extract (Stallergenes, Antony, France) included 24 patients presenting severe rhinitis and slight to moderate asthma, 14 actively and 10 placebo treated. SLIT was performed by a pre-coseasonal protocol, and was repeated for 2 years. The study plan included a selection visit, a visit at the start of the first and the second treatment cycle, a follow-up visit after 1–3 months from the start of each cycle, and a final visit at the end of each yearly cycle. Results: A significant decrease (p < 0.05) in rhinorrhoea and nasal obstruction occurred in actively treated patients. The median number of days with asthma at visit 3 was 10 (0–27) in the active (SLIT) group and 13 (0–29) in the placebo group. The median number of days with asthma at visit 6 was 2 (0–6) in the SLIT group and 7 (0–15) in the placebo group (p < 0.05 between groups). A stepdown of asthma occurred in 77% of actively treated vs. none of placebo treated patients (p = 0.05). No severe adverse events were observed. Conclusions: This pilot study suggests that SLIT with high dose birch extract may be able to step down seasonal pollen-induced asthma after prolonged treatment.
Lattice arrangement of myosin filaments correlates with fiber type in rat skeletal muscle

The thick (myosin-containing) filaments of vertebrate skeletal muscle are arranged in a hexagonal lattice, interleaved with an array of thin (actin-containing) filaments with which they interact to produce contraction. X-ray diffraction and electron microscopy have shown that there are two types of thick filament lattice. In the simple lattice, all filaments have the same orientation about their long axis, while in the super lattice, nearest neighbors have rotations differing by 60°. Tetrapods (amphibians, reptiles, birds, mammals) typically have only a super lattice, while the simple lattice is confined to fish. We have carried out X-ray diffraction and electron microscopy of the soleus (SOL) and extensor digitorum longus (EDL) muscles of the rat and found that while the EDL has a super-lattice, as expected, the SOL has a simple lattice. The EDL and SOL of the rat are unusual in being essentially pure fast and slow muscles respectively. The mixed fiber content of most tetrapod muscles and/or lattice disorder may explain why the simple lattice has not been apparent in these vertebrates before. This is supported by only weak simple lattice diffraction in the X-ray pattern of mouse SOL, which has a greater mix of fiber types than rat. We conclude that the simple lattice might be common in tetrapods. The correlation between fiber type and filament lattice arrangement suggests that the lattice arrangement may contribute to the functional properties of a muscle. Summary The three-dimensional arrangement of thick filaments in skeletal muscle is studied by X-ray diffraction and electron microscopy. A correlation is found between thick filament lattice type (simple or super lattice) and fiber type (fast/slow). This suggests that lattice organization contributes to muscle functional properties
Development and Stem Cells Research Article

INTRODUCTION A crucial step in the development of the germline is the transition from an undifferentiated germ cell that divides by mitosis to a differentiating germ cell that is ready to begin meiosis. In animals, this transition often takes place via an intermediate cell type that still divides by mitosis but has begun to express factors required for meiosis. For example, in C. elegans a group of ~220 mitotic germ cells are maintained throughout life at the distal end of each gonad ('mitotic zone', Fig. The progeny of these cells differentiate in a distal-to-proximal gradient along the length of the gonad. The mitotic zone contains two cell types (Fig. 1A): distal-most cells, including the germline stem cells, which remain undifferentiated throughout the life of the animal; and proximal cells, which begin to express meiotic genes and are likely to include transit-amplifying cells and cells in meiotic S phase (Cinquin et al., 2010; Hubbard, 2007). Upon exit from the mitotic zone, cells initiate the chromosome dynamics required for meiotic pairing and synapsis ('transition zone', Fig. 1A). In preparation for this transition, proximal cells in the mitotic zone activate the expression of both regulators of meiotic entry (e.g. the RNA-binding protein GLD-1) and chromosomal proteins required for synapsis (e.g. HIM-3) (Hansen et al., 2004). The mechanisms that coordinate meiotic entry with the synthesis of meiotic chromosomal proteins are not known and are the focus of this study. Meiotic entry is regulated by a complex network of RNA-binding proteins (Byrd and Kimble, 2009). Central to the network are FBF-1 and FBF-2, two highly similar Puf-domain RNA-binding proteins known collectively as FBF (Crittenden et al., 2002). FBF prevents
An Almost-Linear-Time Algorithm for Approximate Max Flow in Undirected Graphs, and its Multicommodity Generalizations

In this paper, we introduce a new framework for approximately solving flow problems in capacitated, undirected graphs and apply it to provide asymptotically faster algorithms for the maximum s-t flow and maximum concurrent multicommodity flow problems. For graphs with n vertices and m edges, it allows us to find an e-approximate maximum s-t flow in time O(m1+o(1)e-2), improving on the previous best bound of O(mn1/3poly(e-1)). Applying the same framework in the multicommodity setting solves a maximum concurrent multicommodity flow problem with k commodities in O(m1+o(1)e-2k2) time, improving on the existing bound of O(m4/3poly(k>,e-1)). Our algorithms utilize several new technical tools that we believe may be of independent interest: • We give a non-Euclidean generalization of gradient descent and provide bounds on its performance. Using this, we show how to reduce approximate maximum flow and maximum concurrent flow to oblivious routing. • We define and provide an efficient construction of a new type of flow sparsifier. Previous sparsifier constructions approximately preserved the size of cuts and, by duality, the value of the maximum flows as well. However, they did not provide any direct way to route flows in the sparsifier G' back in the original graph G, leading to a longstanding gap between the efficacy of sparsification on flow and cut problems. We ameliorate this by constructing a sparsifier G' that can be embedded (very efficiently) into G with low congestion, allowing one to transfer flows from G' back to G. • We give the first almost-linear-time construction of an O(mo(1))-competitive oblivious routing scheme. No previous such algorithm ran in time better than Ω(mn). By reducing the running time to almost-linear, our work provides a powerful new primitive for constructing very fast graph algorithms. The interested reader is referred to the full version of the paper [8] for a more complete treatment of these results.