Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Spectrum Pooling for Multi-Tenant C-RAN Under Privacy Constraints

This work studies the optimization of spectrum pooling for the downlink of a multi-tenant Cloud Radio Access Network (C-RAN) system in the presence of inter-tenant privacy constraints. The spectrum available for downlink transmission is partitioned into private and shared subbands, and the participating operators cooperate to serve the user equipments (UEs) on the shared subband. The network of each operator consists of a cloud processor (CP) that is connected to proprietary radio units (RUs) by means of finite-capacity fronthaul links. In order to enable inter-operator cooperation, the CPs of the participating operators are also connected by finite-capacity backhaul links. Inter-operator cooperation may hence result in loss of privacy. The problem of optimizing the bandwidth allocation, precoding, and fronthaul/backhaul compression strategies is tackled under constraints on backhaul and fronthaul capacity, as well as on per-RU transmit power and inter-onerator privacy.
GPU-Accelerated Massively Parallel Computation of Electromagnetic Scattering of a Time-Evolving Oceanic Surface Model I: Time-Evolving Oceanic Surface Generation

The development of a time-evolving oceanic surface model (TOSM) is important for the accuracy of determining electromagnetic scattering properties from the sea surface in oceanic remote sensing, target detection, and synthetic aperture radar imagery at arbitrary incident angles, especially small grazing angles. The double superimposition model (DSM) is a well-known approach for TOSM, which is composed of large-scale gravity waves and small-scale capillary ripples superimposed on them. However, due to the real-time dynamic complexity and dimensionality of the TOSM, the traditional DSM algorithm may be very time consuming and hardly meet the real-time requirements. In this paper, the feasibility of using graphics processing units (GPUs) with diverse compute unified device architecture optimization techniques to increase the speed of the generation of the TOSM is investigated. The entirely GPU-based TOSM implemented in this study includes the most effective use of temporary arrays, fast-math compiler options, shared memory, more L1 cache use than shared memory, and page-locked host memory. With respect to single-threaded C programs running on Intel(R) Core(TM) i7-2600K CPU, optimization on the GPU-based generated TOSM can achieve a speedup of $791 \times $ by using a single NVIDIA Tesla K80 GPU model. This new GPU-based TOSM implemented shows great potential for studying the scattering characteristics of electromagnetic backscattered echoes from dynamic sea surfacess.
Impact of lenalidomide exposure on blood cell collection for autotransplants in persons with POEMS syndrome

Introduction Lenalidomide is an effective therapy of POEMS syndrome. However, there is concern that exposure to lenalidomide may reduce the efficiency of blood cell collection in persons who may eventually receive an autotransplant. We studied the impact of lenalidomide therapy on subsequent blood cell mobilization and collection including frequency of blood CD34+ cells and CXCR4 expression before and after mobilization with cyclophosphamide and granulocyte-colony stimulating factor (G-CSF). Material and methods Forty-three subjects with POEMS were assigned to receive lenalidomide and dexamethasone for 2–4 28 d cycles (n = 19) or no therapy (n = 24). All subjects then received cyclophosphamide and G-CSF. Neither cohort had substantial numbers of blood CD34+ cells before mobilization. Results Mobilization increased blood CD34+ frequency in lenalidomide-treated subjects and controls similarly (0.25% (95% confidence interval (CI): 0.03–1.39% vs. 0.32%, 0.04–1.47%), p = 0.472). Increases in blood CD34+ numbers were also similar (10 × 106/l) (5–77 × 106/l) vs. 14 × 106/l (6–101 × 106/l), p = 0.312). Mean CXCR4 fluorescence intensity on bone marrow cells from controls decreased from 58 ±34 (mean ± SD) to 31 ±16 after mobilization (p = NS). In contrast, mean CXCR4 intensity on bone marrow cells in lenalidomide-treated subjects increased from 55 ±43 to 89 ±40 (p = 0.017, comparing the deviation between two groups). Median numbers of CD34+ cells collected in lenalidomide-treated subjects and controls were 2.3 × 106/kg (0.6–6.8 × 106/kg) and 2.8106/kg (1.0–8.9 × 106/kg; p = 0.521). Conclusions Brief lenalidomide treatment for POEMS did not reduce numbers of CD34+ blood cells collected but increased CXCR4 expression on bone marrow CD34+ cells.
Simultaneous Information and Energy Transmission: A Finite Block-Length Analysis

In this paper, a non-asymptotic analysis of the fundamental limits of simultaneous information and energy transmission (SIET) is presented. The notion of the information-energy capacity region, i.e., the largest set of simultaneously achievable information and energy rates, is revisited in a context in which transmissions occur within a finite number of channel uses and strictly positive decoding error probability (DEP) and energy shortage probability (ESP) are tolerated. The focus is on the case of one transmitter, one information receiver and one energy harvester communicating through binary symmetric memoryless channels. In this case, some outer bounds on the information transmission rate and the energy transmission rate are presented. More specifically, given a finite block-length, a DEP, and an ESP, four scenarios arise depending on whether an average or maximal probability constraint is imposed on the DEP and the ESP. For each scenario, the limits on the information rate and energy rate beyond which a transmission is no longer possible are presented (impossibility results). These results reveal the competitive interaction between the information transmission and energy transmission tasks identifying a certain regime in which increasing the information rate necessarily implies decreasing the energy rate and vice versa.
Lightweight Visual Odometry for Autonomous Mobile Robots

Vision-based motion estimation is an effective means for mobile robot localization and is often used in conjunction with other sensors for navigation and path planning. This paper presents a low-overhead real-time ego-motion estimation (visual odometry) system based on either a stereo or RGB-D sensor. The algorithm’s accuracy outperforms typical frame-to-frame approaches by maintaining a limited local map, while requiring significantly less memory and computational power in contrast to using global maps common in full visual SLAM methods. The algorithm is evaluated on common publicly available datasets that span different use-cases and performance is compared to other comparable open-source systems in terms of accuracy, frame rate and memory requirements. This paper accompanies the release of the source code as a modular software package for the robotics community compatible with the Robot Operating System (ROS).
Eddy current losses in permanent magnets of a coaxial magnetic gear

In the present work, eddy current losses in permanent magnets of a coaxial magnetic gear construction are estimated. Transient finite element method model is implemented for eddy currents calculation in dynamic operational mode. Simulations in different rotational speeds are performed and results for the eddy currents demagnetization effect over the torque conversion are presented.
Recognizing Elevator Buttons and Labels for Blind Navigation

In this paper, we propose a method to detect elevator buttons and recognize their labels from images for blind navigation. First, a pixel-level mask of elevator buttons is segmented based on fully convolutional networks. Then a fast scene text detector is applied to recognize the text labels in the image as well as to extract their spatial vectors. Finally, all the detected buttons and their associated labels are paired by combining the button mask and spatial vectors of labels based on their location distribution. To evaluate the proposed method, we collect an elevator button dataset that contains 1,000 images with buttons captured from both inside and outside of elevators and annotate the locations and labels of all buttons. Preliminary results demonstrate the robustness and effectiveness of the proposed method for elevator button detection and associated label recognition.
Is one hyperparameter optimizer enough?

Hyperparameter tuning is the black art of automatically finding a good combination of control parameters for a data miner. While widely applied in empirical Software Engineering, there has not been much discussion on which hyperparameter tuner is best for software analytics.To address this gap in the literature, this paper applied a range of hyperparameter optimizers (grid search, random search, differential evolution, and Bayesian optimization) to a defect prediction problem. Surprisingly, no hyperparameter optimizer was observed to be “best” and, for one of the two evaluation measures studied here (F-measure), hyperparameter optimization, in 50% of cases, was no better than using default configurations. We conclude that hyperparameter optimization is more nuanced than previously believed. While such optimization can certainly lead to large improvements in the performance of classifiers used in software analytics, it remains to be seen which specific optimizers should be applied to a new dataset.
Vancomycin therapeutic drug monitoring and population pharmacokinetic models in special patient subpopulations

Vancomycin is a fundamental antibiotic in the management of severe Gram‐positive infections. Inappropriate vancomycin dosing is associated with therapeutic failure, bacterial resistance and toxicity. Therapeutic drug monitoring (TDM) is acknowledged as an important part of the vancomycin therapy management, at least in specific patient subpopulations, but implementation in clinical practice has been difficult because there are no consensus and agglutinator documents. The aims of the present work are to present an overview of the current knowledge on vancomycin TDM and population pharmacokinetic (PPK) models relevant to specific patient subpopulations. Based on three published international guidelines (American, Japanese and Chinese) on vancomycin TDM and a bibliographic review on available PPK models for vancomycin in distinct subpopulations, an analysis of evidence was carried out and the current knowledge on this topic was summarized. The results of this work can be useful to redirect research efforts to address the detected knowledge gaps. Currently, TDM of vancomycin presents a moderate level of evidence and practical recommendations with great robustness in neonates, pediatric and patients with renal impairment. However, it is important to investigate in other subpopulations known to present altered vancomycin pharmacokinetics (eg neurosurgical, oncological and cystic fibrosis patients), where evidence is still unsufficient.
Soil Moisture Monitoring System Based on Ziggbee Wireless Sensor Network

To improve the utilization rate of agricultural irrigation water, a soil moisture monitoring system based on ZigBee technology is designed to improve the complexity and high cost of the traditional wired network. The proposed system has the characteristics of low consumption, large capacity, high security and easy integration with combing the advantages of ZigBee ang WIFI. This system uses the Z-Stack protocol stack of TI company, takes the CC2520 chip as the core, and includes the STM32 MCU of TI company. This system can greatly improve the water use efficiency and keep the soil moisture in the optimum range of plant growth.
A randomized controlled trial to test efficacy and safety of thrombectomy in stroke with extended lesion and extended time window

Rationale The benefit of thrombectomy in patients with intracranial large vessel occlusion of the anterior circulation has been shown in selected patients in previous randomized controlled trials, but patients with extended ischemic lesions were excluded in the majority of these trials. TENSION aims to demonstrate efficacy and safety of thrombectomy in patients with extended lesions in an extended time window (up to 12 h from onset or from last seen well). Design TENSION is an investigator-initiated, randomized controlled, open label, blinded endpoint, European, two-arm, postmarket study to compare the safety and effectiveness of thrombectomy as compared to best medical care alone in stroke patients with extended stroke lesions defined by an Alberta Stroke Program Early Computed Tomography Scan score of 3–5 and in an extended time window. In an adaptive design study, up to 665 patients will be randomized. Outcomes Primary efficacy endpoint will be clinical outcome defined by the modified Rankin Scale at 90-day poststroke. The main safety endpoint will be death and dependency (modified Rankin Scale 4–6) at 90 days. Additional effect measures include adverse events, health-related quality of life, poststroke depression, and costs utility assessment. Discussion TENSION may make effective treatment available for patients with severe stroke in an extended time window, thereby improving functional outcome and quality of life of thousands of stroke patients and reducing the individual, societal, and economic burden of death and disability resulting from severe stroke. TENSION is registered at ClinicalTrials.gov (ClinicalTrials.gov Identifier NCT03094715).
Incidents related to the Hickman® catheter: identification of damages.

OBJECTIVE to identify damages resulting from incidents with the Hickman® catheter. METHOD descriptive, retrospective, qualitative approach. The source of data were the notifications of incidents that occurred between January 2012 and May 2015, as well as the information available on the medical records of patients involved in incidents with the Hickman® catheter. RESULTS the incidents related to the Hickman® catheter with the greatest impact on patient care were obstruction, fracture and traction. All incidents caused damage to patients, in a greater or lesser degree, in the dimensions of physical damage and subjective damage. FINAL CONSIDERATIONS damage or potential risk of damage was present in all incidents analyzed. The need to revise cleaning and obstruction protocols for the maintenance of the permeability of Hickman® catheters was demonstrated.
Noisy Non-Adaptive Group Testing: A (Near-)Definite Defectives Approach

The group testing problem consists of determining a small set of defective items from a larger set of items based on a number of possibly-noisy tests, and is relevant in applications such as medical testing, communication protocols, pattern matching, and more. We study the noisy version of this problem, where the outcome of each standard noiseless group test is subject to independent noise, corresponding to passing the noiseless result through a binary channel. We introduce a class of algorithms that we refer to as Near-Definite Defectives (NDD), and study bounds on the required number of tests for asymptotically vanishing error probability under Bernoulli random test designs. In addition, we study algorithm-independent converse results, giving lower bounds on the required number of tests under Bernoulli test designs. Under reverse Z-channel noise, the achievable rates and converse results match in a broad range of sparsity regimes, and under Z-channel noise, the two match in a narrower range of dense/low-noise regimes. We observe that although these two channels have the same Shannon capacity when viewed as a communication channel, they can behave quite differently when it comes to group testing. Finally, we extend our analysis of these noise models to a general binary noise model (including symmetric noise), and show improvements over known existing bounds in broad scaling regimes.
The Telomerase Complex Directly Controls Hematopoietic Stem Cell Differentiation and Senescence in an Induced Pluripotent Stem Cell Model of Telomeropathy

Telomeropathies are rare disorders associated with impaired telomere length control mechanisms that frequently result from genetic mutations in the telomerase complex. Dyskeratosis congenita is a congenital progressive telomeropathy in which mutation in the telomerase RNA component (TERC) impairs telomere maintenance leading to accelerated cellular senescence and clinical outcomes resembling premature aging. The most severe clinical feature is perturbed hematopoiesis and bone-marrow failure, but the underlying mechanisms are not fully understood. Here, we developed a model of telomerase function imbalance using shRNA to knockdown TERC expression in human induced pluripotent stem cells (iPSCs). We then promoted in vitro hematopoiesis in these cells to analyze the effects of TERC impairment. Reduced TERC expression impaired hematopoietic stem-cell (HSC) differentiation and increased the expression of cellular senescence markers and production of reactive oxygen species. Interestingly, telomere length was unaffected in shTERC knockdown iPSCs, leading to conclusion that the phenotype is controlled by non-telomeric functions of telomerase. We then assessed the effects of TERC-depletion in THP-1 myeloid cells and again observed reduced hematopoietic and myelopoietic differentiative potential. However, these cells exhibited impaired telomerase activity as verified by accelerated telomere shortening. shTERC-depleted iPSC-derived and THP-1-derived myeloid precursors had lower phagocytic capacity and increased ROS production, indicative of senescence. These findings were confirmed using a BIBR1532 TERT inhibitor, suggesting that these phenotypes are dependent on telomerase function but not directly linked to telomere length. These data provide a better understanding of the molecular processes driving the clinical signs of telomeropathies and identify novel roles of the telomerase complex other than regulating telomere length.
Sliding Windows over Context-Free Languages

We study the space complexity of sliding window streaming algorithms that check membership of the window content in a fixed context-free language. For regular languages, this complexity is either constant, logarithmic or linear [4]. We prove that every context-free language whose sliding window space complexity is log2(n)− ω(1) must be regular and has constant space complexity. Moreover, for every c ∈ N, c ≥ 1 we construct a (nondeterministic) context-free language whose sliding window space complexity is O(n1/c) \ o(n1/c). Finally, we give an example of a deterministic one-counter language whose sliding window space complexity is Θ((logn)2). 2012 ACM Subject Classification Theory of computation → Streaming models
SHLD2/FAM35A co‐operates with REV7 to coordinate DNA double‐strand break repair pathway choice

DNA double‐strand breaks (DSBs) can be repaired by two major pathways: non‐homologous end‐joining (NHEJ) and homologous recombination (HR). DNA repair pathway choice is governed by the opposing activities of 53BP1, in complex with its effectors RIF1 and REV7, and BRCA1. However, it remains unknown how the 53BP1/RIF1/REV7 complex stimulates NHEJ and restricts HR to the S/G2 phases of the cell cycle. Using a mass spectrometry (MS)‐based approach, we identify 11 high‐confidence REV7 interactors and elucidate the role of SHLD2 (previously annotated as FAM35A and RINN2) as an effector of REV7 in the NHEJ pathway. FAM35A depletion impairs NHEJ‐mediated DNA repair and compromises antibody diversification by class switch recombination (CSR) in B cells. FAM35A accumulates at DSBs in a 53BP1‐, RIF1‐, and REV7‐dependent manner and antagonizes HR by limiting DNA end resection. In fact, FAM35A is part of a larger complex composed of REV7 and SHLD1 (previously annotated as C20orf196 and RINN3), which promotes NHEJ and limits HR. Together, these results establish SHLD2 as a novel effector of REV7 in controlling the decision‐making process during DSB repair.
Nonproliferative and Proliferative Lesions of the Rat and Mouse Endocrine System

The INHAND (International Harmonization of Nomenclature and Diagnostic Criteria for Lesions in Rats and Mice) Project (www.toxpath.org/inhand.asp) is a joint initiative among the Societies of Toxicological Pathology from Europe (ESTP), Great Britain (BSTP), Japan (JSTP) and North America (STP) to develop an internationally accepted nomenclature for proliferative and nonproliferative lesions in laboratory animals. The purpose of this publication is to provide a standardized nomenclature for classifying microscopic lesions observed in the endocrine organs (pituitary gland, pineal gland, thyroid gland, parathyroid glands, adrenal glands and pancreatic islets) of laboratory rats and mice, with color photomicrographs illustrating examples of the lesions. The standardized nomenclature presented in this document is also available electronically on the internet (http://www.goreni.org/). Sources of material included histopathology databases from government, academia, and industrial laboratories throughout the world. Content includes spontaneous and aging lesions as well as lesions induced by exposure to test materials. A widely accepted and utilized international harmonization of nomenclature for endocrine lesions in laboratory animals will decrease confusion among regulatory and scientific research organizations in different countries and provide a common language to increase and enrich international exchanges of information among toxicologists and pathologists.
High-confidence error estimates for learned value functions

Estimating the value function for a fixed policy is a fundamental problem in reinforcement learning. Policy evaluation algorithms---to estimate value functions---continue to be developed, to improve convergence rates, improve stability and handle variability, particularly for off-policy learning. To understand the properties of these algorithms, the experimenter needs high-confidence estimates of the accuracy of the learned value functions. For environments with small, finite state-spaces, like chains, the true value function can be easily computed, to compute accuracy. For large, or continuous state-spaces, however, this is no longer feasible. In this paper, we address the largely open problem of how to obtain these high-confidence estimates, for general state-spaces. We provide a high-confidence bound on an empirical estimate of the value error to the true value error. We use this bound to design an offline sampling algorithm, which stores the required quantities to repeatedly compute value error estimates for any learned value function. We provide experiments investigating the number of samples required by this offline algorithm in simple benchmark reinforcement learning domains, and highlight that there are still many open questions to be solved for this important problem.