Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-term treatment with sevelamer increases serum fetuin-a concentration and improves endothelial dysfunction in chronic kidney disease stage 4 patients.

BACKGROUND AND OBJECTIVES Vascular calcification and endothelial dysfunction contribute to the development of cardiovascular disease in patients with chronic kidney disease (CKD). Sevelamer, a non-calcium-based phosphate binder, has been shown to attenuate cardiovascular calcification in CKD patients, although the exact mechanism has not been clarified. This study was designed to investigate the effect of short-term sevelamer treatment on both serum fetuin-A concentrations and endothelial dysfunction seen in CKD patients. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS Fifty nondiabetic stage 4 CKD patients whose phosphate levels were > or =5.5 mg/dl were enrolled in this 8-wk randomized prospective study. Thirty-six healthy volunteers served as matched controls. Patients were treated with either sevelamer (n = 25, 12 males) or calcium acetate (n = 25, 13 males). Fetuin-A, high-sensitivity C-reactive protein, Ca x PO4 product, flow-mediated dilation (FMD), insulin, and homeostasis model assessment (HOMA) were obtained at baseline and after the treatment period. RESULTS As expected, CKD patients had significantly lower levels of fetuin-A and FMD, and significantly higher levels of intact parathyroid hormone, Ca x PO4 product, and high-sensitivity C-reactive protein than controls (P < 0.001 for all). The use of sevelamer led to a significant increase in the fetuin-A concentration with improvement in FMD, whereas no significant difference was observed in the calcium acetate group. In a multiple regression analysis, FMD levels were independently related to fetuin-A both before (beta = 0.63, P < 0.001) and after (beta = 0.38, P = 0.004) treatment. CONCLUSIONS This small, randomized, prospective study shows that short-term sevelamer treatment significantly increases fetuin-A levels and improves FMD in nondiabetic stage 4 CKD patients.
Tyrosine Decarboxylase

Previous communications from this laboratory have established the function of pyridoxine derivatives' in the tyrosine decarboxylase system of Streptococcus faecalis, and a synthetic medium has been described for the production of cells active in this function (Bellamy and Gunsalus, 1943, 1944). Cells grown in media deficient in,pyridoxine derivatives have been shown to contain the tyrosine decarboxylating enzyme but not the coenzyme (Gunsalus and Bellamy, 1944a). Pyridoxal (Snell, 1944) will activate this enzyme in the living cells (Gunsalus and Bellamy, 1944b) but dried cell preparations from them are active only if adenosine triphosphate (ATP) is supplied in addition to pyridoxal (Gunsalus, Bellamy, and Umbreit, 1944). The growth of cells deficient in coenzyme appeared to offer a simpler method for the preparation of the decarboxylase apoenzyme than would the more conventional method of isolation and resolution of the enzyme. Therefore, the present work was undertaken. The main objective has been the production of the greatest possible yield of tyrosine decarboxylase apoenzyme with minimum coenzyme content per unit of medium. This differs from the previous study in which the primary purfiose was to find which vitamin or vitamins function in the tyrosine system and to produce as active a tyrosine decarboxylase as possible (Bellamy and Gunsalus, 1944). The method of apoenzyme production utilized the discovery of Snell and Guirard (1943) that an excess of alanine will support growth of Streptococcus faecalis, strain R, in the absence of pyridoxine derivatives. The lack of coenzyme in cells grown with alanine indicates that vitamin B6 analogues convertible into coenzyme are not synthesized from alanine during growth. This constitutes an exception to the working hypothesis used by Snell and Guirard (1943), who suggest that alanine might be used as an essential nucleus for the synthesis of pyridoxine. However, evidence of synthesis of pyridoxine derivatives by other lactic acid bacteria has been reported by Bohonos, Hutchings, and Peterson (1942). In the present paper, a medium for the production of a very active tyrosine decarboxylase apoenzyme in Streptococcusfaecalis, strain R, is reported, and some of the factors affecting its production are discussed. These cells respond quantitatively to pyridoxal, and dried cell preparations from them respond to pyridoxal in the presence of ATP.
Soft Partitioning Flow Tables for Virtual Networking in Multi-Tenant Software Defined Networks

In a multi-tenancy software defined network (SDN) environment, physical devices such as switches are shared among tenants. In addition to a centralized controller, each tenant has his own controller that manages resources allocated to the tenant. Hence, the centralized controller performs SDN resource virtualization among tenants and acts as proxy between physical resources and tenant controllers. In order to manage the flow tables of the SDN switches, two partitioning strategies are considered. Hard partitioning of flow tables allocates a fixed amount of flow entries to each tenant, but flow tables are wasted if the tenant does not actually use them. On the other hand, soft partitioning strategy shares available flow entries among tenants, resulting in higher utilization but a resource monopoly problem, i.e., flow entries dominated by some greedy tenants. To achieve high flow table utilization and avoid the resource monopoly problem, we propose a soft-partitioning resource manager (SPRM) to manage the flow table resources in a multi-tenancy SDN environment. In SPRM, the allowed number of flow entries for each tenant ranges from a lower bound which equals to the tenant’s quota to an upper bound which is dynamically adjusted according to the tenant’s past usage. If an incoming flow request of a tenant is beyond his lower bound but under his upper bound, it could be temporarily accepted when there are free entries available. These borrowed flow entries will later be replaced if needed. If a request of a tenant is beyond his upper bound, SPRM will select a least-recently used flow entry of the tenant and replace it with the new request. In addition, SPRM monitors flow table resources and submits modify flow entry messages directly to SDN switches without checks by the management plane as possible in order to reduce flow modification latency. As a result, SPRM could reach higher flow table utilization and lower both flow entry miss rate and Packet_in events. Experimental results show that 100% flow rejections, and 95% Packet_in events are reduced while flow modification latency is decreased by 30%, as compared to hard partitioning.
Self-learning and adaptation in a sensorimotor framework

We present a general framework to autonomously achieve the task of finding a sequence of actions that result in a desired state. Autonomy is acquired by learning sensorimotor patterns of a robot, while it is interacting with its environment. Gaussian processes (GP) with automatic relevance determination are used to learn the sensorimotor mapping. In this way, relevant sensory and motor components can be systematically found in high-dimensional sensory and motor spaces. We propose an incremental GP learning strategy, which discerns between situations, when an update or an adaptation must be implemented. The Rapidly exploring Random Tree (RRT*) algorithm is exploited to enable long-term planning and generating a sequence of states that lead to a given goal; while a gradient-based search finds the optimum action to steer to a neighbouring state in a single time step. Our experimental results prove the suitability of the proposed framework to learn a joint space controller with high data dimensions (10×15). It demonstrates short training phase (less than 12 seconds), real-time performance and rapid adaptations capabilities.
Secure sessions for Web services

We address the problem of securing sequences of SOAP messages exchanged between web services and their clients. The WS-Security standard defines basic mechanisms to secure SOAP traffic, one message at a time. For typical web services, however, using WS-Security independently for each message is rather inefficient; moreover, it is often important to secure the integrity of a whole session, as well as each message. To these ends, recent specifications provide further SOAP-level mechanisms. WS-SecureConversation defines security contexts, which can be used to secure sessions between two parties. WS-Trust specifies how security contexts are issued and obtained. We develop a semantics for the main mechanisms of WS-Trust and WS-SecureConversation, expressed as a library for TulaFale, a formal scripting language for security protocols. We model typical protocols relying on these mechanisms and automatically prove their main security properties. We also informally discuss some pitfalls and limitations of these specifications.
Journal of Reproduction and Development

Transzonal projections (TZPs) that maintain bidirectional communication between oocytes and granulosa cells or cumulus cells are important structures for oocyte growth. However, whether TZPs develop between TZPfree oocytes and granulosa cells, and whether reestablished TZPs support oocyte growth, is unknown. We first examined changes in TZPs after denudation of bovine oocytes collected from early antral follicles (0.5–0.7 mm). Twenty-four hours after denudation, almost all the TZPs disappeared. We also examined the reestablishment of TZPs by coculturing TZP-free denuded oocytes (DOs) with mural granulosa cells (MGCs) collected from early antral follicles. In addition, to confirm if the reestablished TZPs were functional, the reconstructed complexes (DO+MGCs) were subjected to in vitro growth culture and found that the MGCs adhered to TZP-free DOs and TZPs were reestablished. During in vitro growth culture, DO+MGCs developed and formed antrum-like structures. After culture, the number of TZPs in DO+MGCs increased, and the oocytes grew fully and acquired meiotic competence. These results suggest that reestablished TZPs are able to support oocyte growth.
Scholarship@Western Scholarship@Western

Sequence Labelling is the task of mapping sequential data from one domain to another domain. As we can interpret language as a sequence of words, sequence labelling is very common in the ﬁeld of Natural Language Processing (NLP). In NLP, some fundamental sequence labelling tasks are Parts-of-Speech Tagging, Named Entity Recognition, Chunking, etc. Moreover, many NLP tasks can be modeled as sequence labelling or sequence to sequence labelling such as machine translation, information retrieval and question answering. An extensive amount of research has already been performed on sequence labelling. Most of the current high performing models are neural network models. These Deep Learning based models are outperforming traditional machine learning techniques by using abstract high dimensional feature representations of the input data. In this thesis, we propose a new neural sequence model which uses several additional types of linguistic information to improve the model performance. The convergence rate of the proposed model is signiﬁcantly less than similar models. Moreover, our model obtains state of the art results on the benchmark datasets of POS, NER, and chunking.
Design of MIMO array with low grating lobes in near-field imaging

MIMO (Multiple-Input Multiple-Output) radar is a new radar system, which can provide more observation channels than traditional array radar with the same number of the array elements. Based on far-field approximation, the usual MIMO array will lead to high azimuth grating lobes in near-field imaging. For designing near-field imaging MIMO array, this paper analyzed the reason of the grating lobes in near-field area and proposed a design method of MIMO array with low grating lobes in near-field imaging based on adding window to transmit array. Finally, the validity of the proposed method is verified by a simulation.
Character evolution of the benthic thecate dinoflagellate, gambierdiscus (Dinophyceae), with an introduction of the interactive key to species

The genus Gambierdiscus is one of the benthic marine dinoflagellates that are known to produce biotoxins, causing ciguatera food poisoning (CFP) in humans after consuming the contaminated marine fishes. These benthic marine dinoflagellates are commonly found in the warm tropical and subtropical waters. The phenomena associated with high cell abundance or “blooms” is referred to Benthic Harmful Algal Blooms (BHABs). Precise species identification is crucial as not all of the species in the genus are toxic. In this study, morphological characteristics of Gambierdiscus species widely used in species identification were analyzed, and the character states coded. Taxon sampling on the large subunit (LSU) rDNA of all Gambierdiscus species were carried out, and used for the phylogenetic reconstruction. The character states were mapped onto the Maximum Parsimony (MP) tree to investigate the character state evolution of Gambierdiscus species. Morphological information and the distribution of the 13 species were used to develop a comprehensive taxonomic database of Gambierdiscus, a web-based interactive identification key for species identification is presented.
Preferential Detachment During Human Brain Development: Age- and Sex-Specific Structural Connectivity in Diffusion Tensor Imaging (DTI) Data

Human brain maturation is characterized by the prolonged development of structural and functional properties of large-scale networks that extends into adulthood. However, it is not clearly understood which features change and which remain stable over time. Here, we examined structural connectivity based on diffusion tensor imaging (DTI) in 121 participants between 4 and 40 years of age. DTI data were analyzed for small-world parameters, modularity, and the number of fiber tracts at the level of streamlines. First, our findings showed that the number of fiber tracts, small-world topology, and modular organization remained largely stable despite a substantial overall decrease in the number of streamlines with age. Second, this decrease mainly affected fiber tracts that had a large number of streamlines, were short, within modules and within hemispheres; such connections were affected significantly more often than would be expected given their number of occurrences in the network. Third, streamline loss occurred earlier in females than in males. In summary, our findings suggest that core properties of structural brain connectivity, such as the small-world and modular organization, remain stable during brain maturation by focusing streamline loss to specific types of fiber tracts.
Enhancing Named Entity Recognition in Twitter Messages Using Entity Linking

In this paper, we describe our approach for Named Entity Recognition in Twitter, a shared task for ACL 2015 Workshop on Noisy User-generated Text (Baldwin et al., 2015). Because of the noisy, short, and colloquial nature of Twitter, the performance of Named Entity Recognition (NER) degrades significantly. To address this problem, we propose a novel method to enhance the performance of the Twitter NER task by using Entity Linking which is a method for detecting entity mentions in text and resolving them to corresponding entries in knowledge bases such as Wikipedia. Our method is based on supervised machine-learning and uses the highquality knowledge obtained from several open knowledge bases. In comparison with the other systems proposed for this shared task, our method achieved the best performance.
Incomplete Information in Relational Databases

ABSTRACT This paper concerns the semantics of Codd's relational model of data. Formulated are precise conditions that should be satisfied in a semantically meaningful extension of the usual relational operators, such as projection, selection, union, and join, from operators on relations to operators on tables with “null values” of various kinds allowed. These conditions require that the system be safe in the sense that no incorrect conclusion is derivable by using a specified subset Ω of the relational operators; and that it be complete in the sense that all valid conclusions expressible by relational expressions using operators in Ω are in fact derivable in this system. Two such systems of practical interest are shown. The first, based on the usual Codd's null values, supports projection and selection. The second, based on many different (“marked”) null values or variables allowed to appear in a table, is shown to correctly support projection, positive selection (with no negation occurring in the selection condition), union, and renaming of attributes, which allows for processing arbitrary conjunctive queries. A very desirable property enjoyed by this system is that all relational operators on tables are performed in exactly the same way as in the case of the usual relations. A third system, mainly of theoretical interest, supporting projection, selection, union, join, and renaming, is also discussed. Under a so-called closed world assumption, it can also handle the operator of difference. It is based on a device called a conditional table and is crucial to the proof of the correctness of the second system. All systems considered allow for relational expressions containing arbitrarily many different relation symbols, and no form of the universal relation assumption is required. Categories and Subject Descriptors: H.2. 3 [Database Management]: Languages— query languages; H.2. 4 [Database Management]: Systems— query processing General Terms: Theory
Differentially Private Distributed Nonconvex Stochastic Optimization with Quantized Communications

This paper proposes a new distributed nonconvex stochastic optimization algorithm that can achieve privacy protection, communication efficiency and convergence simultaneously. Specifically, each node adds time-varying privacy noises to its local state to avoid information leakage, and then quantizes its noise-perturbed state before transmitting to improve communication efficiency. By employing the subsampling method controlled through the sample-size parameter, the proposed algorithm reduces the impact of privacy noises, and enhances the differential privacy level. When the global cost function satisfies the Polyak-Lojasiewicz condition, the mean and high-probability convergence rate and the oracle complexity of the proposed algorithm are given. Importantly, the proposed algorithm achieves both the mean convergence and a finite cumulative differential privacy budget over infinite iterations as the sample-size goes to infinity. A numerical example of the distributed training on the"MNIST"dataset is given to show the effectiveness of the algorithm.
Doppler-assisted quantum resonances through swappable excitation pathways in Potassium vapor

We report the observation of two additional sub-natural line width quantum interference in the $D_2$ manifold of $^{39}K$ vapor, in addition to the usual single Electromagnetically induced transparency peak. The other two features appear exclusively because $^{39}K$ ground hyperfine splitting is smaller than the Doppler broadened absorption profile. This allows probe and control beams to swap their transition pathways. The control beam detuning captures the nature of the coherence, therefore an unusual phenomenon of conversion from perfect transparency to enhanced absorption is observed and explained by utilizing adiabatic elimination of the excited state in the Master equation. Controlling such dark and bright resonances leads to new applications in quantum technologies viz. frequency offset laser stabilization and long-lived quantum memory.
Semi-Supervised Image Captioning Considering Wasserstein Graph Matching

Image captioning can automatically generate captions for the given images, and the key challenge is to learn a mapping function from visual features to natural language features. Existing approaches are mostly supervised ones, i.e., each image has a corresponding sentence in the training set. However, considering that describing images always requires a huge of manpower, we usually have limited amount of described images (i.e., image-text pairs) and a large number of undescribed images in real-world applications. Thereby, a dilemma is the"Semi-Supervised Image Captioning". To solve this problem, we propose a novel Semi-Supervised Image Captioning method considering Wasserstein Graph Matching (SSIC-WGM), which turns to adopt the raw image inputs to supervise the generated sentences. Different from traditional single modal semi-supervised methods, the difficulty of semi-supervised cross-modal learning lies in constructing intermediately comparable information among heterogeneous modalities. In this paper, SSIC-WGM adopts the successful scene graphs as intermediate information, and constrains the generated sentences from two aspects: 1) inter-modal consistency. SSIC-WGM constructs the scene graphs of the raw image and generated sentence respectively, then employs the wasserstein distance to better measure the similarity between region embeddings of different graphs. 2) intra-modal consistency. SSIC-WGM takes the data augmentation techniques for the raw images, then constrains the consistency among augmented images and generated sentences. Consequently, SSIC-WGM combines the cross-modal pseudo supervision and structure invariant measure for efficiently using the undescribed images, and learns more reasonable mapping function.
Toward CXL-Native Memory Tiering via Device-Side Profiling

The Compute Express Link (CXL) interconnect has provided the ability to integrate diverse memory types into servers via byte-addressable SerDes links. Harnessing the full potential of such heterogeneous memory systems requires efficient memory tiering. However, existing research in this domain has been constrained by low-resolution and high-overhead memory access profiling techniques. To address this critical challenge, we propose to enhance existing memory tiering systems with a novel NeoMem solution. NeoMem offloads memory profiling functions to device-side controllers, integrating a dedicated hardware unit called NeoProf. NeoProf readily tracks memory access and provides the operating system with crucial page hotness statistics and other useful system state information. On the OS kernel side, we introduce a revamped memory-tiering strategy, enabling accurate and timely hot page promotion based on NeoProf statistics. We implement NeoMem on a real CXL-enabled FPGA platform and Linux kernel v6.3. Comprehensive evaluations demonstrate that NeoMem achieves 32% to 67% geomean speedup over several existing memory tiering solutions.
Addressing Data Annotation Challenges in Multiple Sensors: A Solution for Scania Collected Datasets

Data annotation in autonomous vehicles is a critical step in the development of Deep Neural Network (DNN) based models or the performance evaluation of the perception system. This often takes the form of adding 3D bounding boxes on time-sequential and registered series of point-sets captured from active sensors like Light Detection and Ranging (LiDAR) and Radio Detection and Ranging (RADAR). When annotating multiple active sensors, there is a need to motion compensate and translate the points to a consistent coordinate frame and timestamp respectively. However, highly dynamic objects pose a unique challenge, as they can appear at different timestamps in each sensor's data. Without knowing the speed of the objects, their position appears to be different in different sensor outputs. Thus, even after motion compensation, highly dynamic objects are not matched from multiple sensors in the same frame, and human annotators struggle to add unique bounding boxes that capture all objects. This article focuses on addressing this challenge, primarily within the context of Scania collected datasets. The proposed solution takes a track of an annotated object as input and uses the Moving Horizon Estimation (MHE) to robustly estimate its speed. The estimated speed profile is utilized to correct the position of the annotated box and add boxes to object clusters missed by the original annotation.