Miracle-dz/UniFAR-FTUs huggingface dataset:
A multi-arm phase Ib/II study designed for rapid, parallel evaluation of novel immunotherapy combinations in relapsed/refractory acute myeloid leukemia

Abstract We conducted a phase Ib/II multi-arm, parallel cohort study to simultaneously evaluate various immunotherapeutic agents and combinations in relapsed/refractory acute myeloid leukemia (AML). Overall, 50 patients were enrolled into one of 6 arms: (A) single agent PF-04518600 (OX40 agonist monoclonal antibody), (B) azacitidine + venetoclax + gemtuzumab ozogamicin (GO), (C) azacitidine + avelumab (anti-PD-L1 monoclonal antibody) + GO, (D) azacitidine + venetoclax + avelumab, (E) azacitidine + avelumab + PF-04518600, and (F) glasdegib + GO. Among all regimens evaluated, azacitidine + venetoclax + GO appeared most promising. In this arm, the CR/CRi rates among venetoclax-naïve and prior venetoclax-exposed patients were 50% and 22%, respectively, and the 1-year OS rate was 31%. This study shows the feasibility of a conducting a multi-arm trial to efficiently and simultaneously evaluate novel therapies in AML, a needed strategy in light of the plethora of emerging therapies. This trial was registered at www.clinicaltrials. gov as NCT03390296.
Prader-Willi Syndrome and PCSK1 mutation: a novel presentation of combined syndromic and monogenic obesity.

OBJECTIVE Prader-Willi syndrome (PWS) is a genomic imprinting disorder predominantly caused by the absence of paternally expressed imprinted genes at chromosome 15q11.2-q13. The PCSK1 gene is vital for the processing of hypothalamic POMC to ACTH and α-MSH, leading to food intake suppression and increased energy expenditure. The aim of this study was to investigate whether our PWS patient had a defect in genes involved in the hypothalamic melanocortin-4 receptor (MC4R) pathway. PATIENTS AND METHODS A 27-year-old Greek man with PWS presented to the Adult Endocrine Clinic with morbid obesity and hyperphagia. He also had obstructive sleep apnea, growth hormone deficiency, gonadal failure and metabolic disturbances. At 6 years of age, chromosomal testing confirmed PWS with a deletion in the q11q13 region of the long arm of paternal chromosome 15. RESULTS At the age of 27 years, further genetic testing was conducted, and next generation sequencing revealed a PCSK1_pN221D_HET mutation which was confirmed by Sanger sequencing. CONCLUSIONS Our findings suggest that different genetic abnormalities may be present in an individual with PWS and that patients with PWS may need to be investigated for PCSK1 mutations, as the finding may potentially offer a novel treatment perspective for them.
Design of multiple-input–multiple-output radar waveforms for Rician target detection

This study addresses the waveform design problem of multiple-input–multiple-output (MIMO) radar. The goal is to improve the detection performance for the Rician targets. The authors first establish a general signal model, which can describe the returns by both statistical and colocated MIMO radar systems. Then they derive the associated optimal Neyman–Pearson detector and find the difficulty of optimising the waveforms that maximise the probability of detection (for a fixed probability of false alarm). Alternatively, they employ the relative entropy associated with the detection problem as the design metric. In order to tackle the non-convex waveform optimisation problem, they propose a minorisation-maximisation-based design method. They prove that the proposed method can increase the relative entropy (of the devised waveforms) at each iteration and guarantees convergence. Finally, they include several numerical examples to demonstrate the effectiveness of the proposed method.
Effects of Differences in Exercise Programs With Regular Resistance Training on Resting Blood Pressure in Hypertensive Adults: A Systematic Review and Meta-Analysis

Supplemental Digital Content is Available in the Text. Abstract Igarashi, Y. Effects of differences in exercise programs with regular resistance training on resting blood pressure in hypertensive adults: A systematic review and meta-analysis. J Strength Cond Res 37(1): 253–263, 2023—This systematic review and meta-analysis aimed to evaluate changes in resting blood pressure (RBP) with differences in regular resistance training (RT) programs. Inclusion criteria were randomized controlled trials involving hypertensive adults and interventions involving only RT of both the upper and lower limbs for ≥7 weeks. The weighted mean difference (WMD) was defined as the mean difference between the exercise and control groups, weighted by the inverse of the squared standard error for each study, and all WMDs in RBP were pooled as overall effects. A simple meta-regression analysis was performed to evaluate the relationship between RT variables (percentage 1 repetition maximum [1RM], number of repetitions, number of sets, and weekly frequency) and changes in RBP. Seventeen studies (646 subjects) were analyzed. The pooled WMDs in the resting systolic blood pressure (RSBP) and resting diastolic blood pressure (RDBP) decreased significantly but contained significant heterogeneity {RSBP, −4.7 mm Hg (95% confidence interval [CI], −6.7 to −2.8; I2 = 46.6%); RDBP, −3.5 mm Hg (95% CI, −4.9 to −2.1; I2 = 39.1%)}. Meta-regression analysis revealed that an increase in % 1RM was significantly associated with a decrease in the RSBP (γ = −0.25x0 + 10.85, where γ represents the mean difference in RSBP, and x0 represents % 1RM [%]), and heterogeneity was alleviated (I2 = 0.0%). For reducing RSBP, regular RT with moderate or heavy loads may be more beneficial than regular RT with light loads.
Modelling the rowing stroke in racing shells

In this article we set up a mathematical model to represent the effects of the forces which operate during the rowing of racing shells. The analysis is conducted in terms of eights, but could apply equally well to fours, pairs and double or quad sculls, and even (with obvious verbal changes) to single sculls. McMahon as well as McMahon and Bonner have previously considered various numbers of rowers in racing shells, and reached conclusions suggesting that consideration of an eight is representative of all possible combinations of rowers.
SOME ASPECTS OF DEVELOPMENT AND PROGRAMMING A WHEELS MOBILE ROBOT USING THE ARDUINO DEVELOPMENT BOARD

The paper presents aspects regarding the development of a mobile robot (on wheels) fitted with ATmega328P-PV microcontroller and infrared and ultrasound sensors for detection. The robot programming elements and the test of its characteristics and performance are also highlighted. The robot is able to pursue an autonomously route determined in advance and avoid any obstacles which might arise in its path, returning then to the default route. Keywords—wheels mobile robot, microcontroller and sensors, robot programming elements
CLUSTER DE PEQUENAS E MÉDIAS EMPRESAS: A CONFIGURAÇÃO ORGANIZACIONAL DO PARQUE DE

The purpose of this paper is to analyze how a clust er organizes itself to adapt into a competitive, fast, dynamic and intensive knowledge environment, such as encountered now a days. The research here presented is explanat ive, of qualitative methods, using case study as its strategy. It was identified that the Software Park did not have all clusters advantage developed, due to the small number of int egrants. As a conclusion, the
An Approach to Design and Optimization of WLAN Patch Antennas for Wi-Fi Applications

Microstrip patch antennas have been widely used in a various useful applications, due to their low weight and low profile, conformability, easy and cheap realization. In this paper, an attempt has been made to investigate new microstrip antenna structure for wi-fi systems. The aim of this work is to obtain an efficient and economical patch antenna for indoor and outdoor uses. At present, dipole antenna is used indoor the portable devices such as laptops, mobiles, smart phones etc. and helix antenna is used as outdoor antenna for routers, modems, switches etc. HFSS and MATLAB are used for the simulation and design calculations of the microstrip antennas. The return loss, VSWR, Directivity, gain, radiation pattern are evaluated. Using HFSS simulation software proposed antenna is designed/simulated and optimized. The effectiveness of the proposed designs is confirmed through proper simulation results. Further, after designing and optimization in simulation software, the proposed antenna is analyze for performance.
Trajectory feasibility evaluation using path prescribed control of unmanned aerial vehicle in differential algebraic equations framework*

ABSTRACT Mission simulation is a critical activity in the development and operation of Unmanned Aerial Vehicles (UAVs). It is important to ascertain the feasibility of a trajectory in a mission. In this work, an algorithm has been developed for feasibility study of a trajectory of a UAV using prescribed path optimal control through an inverse simulation method. This has been done under a Differential Algebraic Equations (DAE)/Inequalities (DAI) framework. The UAV model together with constraints is represented as a high index DAE system. The trajectory that UAV shall take is prescribed as one of the constraint equations. The solution for the DAE system is obtained using a variation of the alpha method that is capable of handling both equality and inequality constraints on system dynamics. The algorithm involves direct numerical integration of a DAI formulation in a time-stepping manner using a Sequential Quadratic Programming (SQP) solver that detects and satisfy active path constraints at each time step (mesh point). In this unique approach, the model and the constraints are always solved together. The method ensures stable solution at each time step, local minimum at each iteration of simulation and provides a regularised basis to the solver. A typical UAV trajectory has been simulated and demonstrated in this paper. This new approach can be used for path planning of UAVs before the actual control law is designed for flight control computer. Compared to other existing computationally intensive techniques, this approach is computationally simple, ensures continuous constraint satisfaction and provides a viable option for model predictive control of UAVs.
The Challenges of Being Agile in DoD

Abstract : In todays acquisition environment, it no longer is unusual for your program to award a product or service development contract in which the vendor intends to utilize Agile Methods for its software development efforts. In fact, the official push for Agile within the Department of Defense (DoD) came from Congress in Section 804 of the Fiscal Year 2010 National Defense Authorization Act: Implementation of New Acquisition Process for Information Technology Systems.
A 3-stage Spectral-spatial Method for Hyperspectral Image Classification

Hyperspectral images often have hundreds of spectral bands of different wavelengths captured by aircraft or satellites that record land coverage. Identifying detailed classes of pixels becomes feasible due to the enhancement in spectral and spatial resolution of hyperspectral images. In this work, we propose a novel framework that utilizes both spatial and spectral information for classifying pixels in hyperspectral images. The method consists of three stages. In the first stage, the pre-processing stage, the Nested Sliding Window algorithm is used to reconstruct the original data by enhancing the consistency of neighboring pixels and then Principal Component Analysis is used to reduce the dimension of data. In the second stage, Support Vector Machines are trained to estimate the pixel-wise probability map of each class using the spectral information from the images. Finally, a smoothed total variation model is applied to ensure spatial connectivity in the classification map by smoothing the class probability tensor. We demonstrate the superiority of our method against three state-of-the-art algorithms on six benchmark hyperspectral datasets with 10 to 50 training labels for each class. The results show that our method gives the overall best performance in accuracy even with a very small set of labeled pixels. Especially, the gain in accuracy with respect to other state-of-the-art algorithms increases when the number of labeled pixels decreases, and, therefore, our method is more advantageous to be applied to problems with a small training set. Hence, it is of great practical significance since expert annotations are often expensive and difficult to collect.
New Aspects of Optical Coherence and Their Potential for Quantum Technologies

Currently, optical technology impacts most of our lives, from light used in scientific measurement to the fiber optic cables that makeup the backbone of the internet. However, as our current optical infrastructure grows, we discover that these technologies are not limitless. However, our current optical technology functions on classical principles, and can be easily improved by incorporating our knowledge of quantum optics. In order to implement quantum technologies, our understanding of quantum coherence must improve. Through this knowledge we can maintain quantum states, and therefore their information, longer. In this dissertation, I will demonstrate that with sufficient knowledge of coherent properties, a simple algebra can be derived which can provide rules for graph reductions on a quantum network graph. Using this knowledge, I then provide a rudimentary algorithm which can find the optimal subgraph for communication on a quantum network. Next, I demonstrate that by measuring the photon statistics and second-order quantum coherence of a field, one can create a neural network capable of distinguishing the light sources on a pixel. Which is then applied to develop an imaging scheme capable of surpassing the Abbe-Rayleigh Criterion. Lastly, I present a multiphoton quantum version of the van Cittert-Zernike theorem. This provides formalism capable of determining the propagation of quantum coherence throughout a system. I then demonstrate the usefulness of the theorem by demonstrating sub-Poissonian statistics created by a linear system with an incident thermal beam, obtainable only by post-selection. Altogether, this provides incite into new applications of coherence to quantum technologies and the formalism to extending our knowledge even further.
Scalable Motif Counting for Large-scale Temporal Graphs

One fundamental problem in temporal graph anal-ysis is to count the occurrences of small connected subgraph patterns (i.e., motifs), which benefits a broad range of real-world applications, such as anomaly detection, structure prediction, and network representation learning. However, existing works focused on exacting temporal motif are not scalable to large-scale temporal graph data, due to their heavy computational costs or inherent inadequacy of parallelism. In this work, we propose a scalable parallel framework for exactly counting temporal motifs in large-scale temporal graphs. We first categorize the temporal motifs based on their distinct properties, and then design customized algorithms that offer efficient strategies to exactly count the motif instances of each category. Moreover, our compact data structures, namely triple and quadruple counters, enable our algorithms to directly identify the temporal motif instances of each category, according to edge information and relationship between edges, therefore significantly improving the counting efficiency. Based on the proposed counting algorithms, we design a hierarchical parallel framework that featuring both inter- and intra-node parallel strategies, and fully leverages the multi-threading capacity of modern CPU to concurrently count all temporal motifs. Extensive experiments on sixteen real-world temporal graph datasets demonstrate the superiority and capability of our proposed framework for temporal motif counting, achieving up to $538\times$ speedup compared to the state-of-the-art methods. The source code of our method is available at: https://github.com/steven-ccq/FAST-temporal-motif.
SAAC: Safe Reinforcement Learning as an Adversarial Game of Actor-Critics

Although Reinforcement Learning (RL) is effective for sequential decision-making problems under uncertainty, it still fails to thrive in real-world systems where risk or safety is a binding constraint. In this paper, we formulate the RL problem with safety constraints as a non-zero-sum game. While deployed with maximum entropy RL, this formulation leads to a safe adversarially guided soft actor-critic framework, called SAAC. In SAAC, the adversary aims to break the safety constraint while the RL agent aims to maximize the constrained value function given the adversary's policy. The safety constraint on the agent's value function manifests only as a repulsion term between the agent's and the adversary's policies. Unlike previous approaches, SAAC can address different safety criteria such as safe exploration, mean-variance risk sensitivity, and CVaR-like coherent risk sensitivity. We illustrate the design of the adversary for these constraints. Then, in each of these variations, we show the agent differentiates itself from the adversary's unsafe actions in addition to learning to solve the task. Finally, for challenging continuous control tasks, we demonstrate that SAAC achieves faster convergence, better efficiency, and fewer failures to satisfy the safety constraints than risk-averse distributional RL and risk-neutral soft actor-critic algorithms.
JanusAQP: Efficient Partition Tree Maintenance for Dynamic Approximate Query Processing

Approximate query processing over dynamic databases, i.e., under insertions/deletions, has applications ranging from high-frequency trading to internet-of-things analytics. We present JanusAQP, a new dynamic AQP system, which supports SUM, COUNT, AVG, MIN, and MAX queries under insertions and deletions to the dataset. JanusAQP extends static partition tree synopses, which are hierarchical aggregations of datasets, into the dynamic setting. This paper contributes new methods for: (1) efficient initialization of the data synopsis in the presence of incoming data, (2) maintenance of the data synopsis under insertions/deletions, and (3) re-optimization of the partitioning to reduce the approximation error. JanusAQP reduces the error of a state-of-the-art baseline by more than 60% using only 10% storage cost. JanusAQP can process more than 100K updates per second in a single node setting and keep the query latency at a millisecond level.
Mobility Analysis Workflow (MAW): An accessible, interoperable, and reproducible container system for processing raw mobile data

Mobility analysis, or understanding and modeling of people's mobility patterns in terms of when, where, and how people move from one place to another, is fundamentally important as such information is the basis for large-scale investment decisions on the nation's multi-modal transportation infrastructure. Recent rise of using passively generated mobile data from mobile devices have raised questions on using such data for capturing the mobility patterns of a population because: 1) there is a great variety of different kinds of mobile data and their respective properties are unknown; and 2) data pre-processing and analysis methods are often not explicitly reported. The high stakes involved with mobility analysis and issues associated with the passively generated mobile data call for mobility analysis (including data, methods and results) to be accessible to all, interoperable across different computing systems, reproducible and reusable by others. In this study, a container system named Mobility Analysis Workflow (MAW) that integrates data, methods and results, is developed. Built upon the containerization technology, MAW allows its users to easily create, configure, modify, execute and share their methods and results in the form of Docker containers. Tools for operationalizing MAW are also developed and made publicly available on GitHub. One use case of MAW is the comparative analysis for the impacts of different pre-processing and mobility analysis methods on inferred mobility patterns. This study finds that different pre-processing and analysis methods do have impacts on the resulting mobility patterns. The creation of MAW and a better understanding of the relationship between data, methods and resulting mobility patterns as facilitated by MAW represent an important first step toward promoting reproducibility and reusability in mobility analysis with passively-generated data.
Real-time ultrasonic techniques suitable for implementing non-contact NDT systems employing piezoceramic composite transducers

Theory and experiments are presented for the generation and detection of shear waves, Rayleigh waves and Lamb waves using air-coupled piezoceramic ultrasonic transducers. An experimental air-coupled NDT system based on the Lamb wave technique has been constructed and using this it has been possible to produce real-time images of defects in thin plates of various materials including carbon fibre and aluminium
Heavy-Ball-Based Hard Thresholding Algorithms for Sparse Signal Recovery

The hard thresholding technique plays a vital role in the development of algorithms for sparse signal recovery. By merging this technique and heavy-ball acceleration method which is a multi-step extension of the traditional gradient descent method, we propose the so-called heavy-ball-based hard thresholding (HBHT) and heavy-ball-based hard thresholding pursuit (HBHTP) algorithms for signal recovery. It turns out that the HBHT and HBHTP can successfully recover a $k$-sparse signal if the restricted isometry constant of the measurement matrix satisfies $\delta_{3k}<0.618 $ and $\delta_{3k}<0.577,$ respectively. The guaranteed success of HBHT and HBHTP is also shown under the conditions $\delta_{2k}<0.356$ and $\delta_{2k}<0.377,$ respectively. Moreover, the finite convergence and stability of the two algorithms are also established in this paper. Simulations on random problem instances are performed to compare the performance of the proposed algorithms and several existing ones. Empirical results indicate that the HBHTP performs very comparably to a few existing algorithms and it takes less average time to achieve the signal recovery than these existing methods.
Search for the doubly heavy baryon Ξ + bc decaying to J/ψΞ +

A ﬁrst search for the Ξ + bc → J/ψΞ + c decay is performed by the LHCb experiment with a data sample of proton-proton collisions, corresponding to an integrated luminosity of 9 fb − 1 recorded at centre-of-mass energies of 7, 8, and 13 TeV. Two peaking structures are seen with a local (global) signiﬁcance of 4 . 3 (2 . 8) and 4 . 1 (2 . 4) standard deviations at masses of 6571 MeV/ c 2 and 6694 MeV/ c 2 , respectively. Upper limits are set on the Ξ + bc baryon production cross-section times the branching fraction relative to that of the B + c → J/ψD + s decay at centre-of-mass energies of 8 and 13 TeV, in the Ξ + bc and in the B + c rapidity and transverse-momentum ranges from 2.0 to 4.5 and 0 to 20 GeV/ c , respectively. Upper limits are presented as a function of the Ξ + bc mass and lifetime.
Risk-Averse Receding Horizon Motion Planning

This paper studies the problem of risk-averse receding horizon motion planning for agents with uncertain dynamics, in the presence of stochastic, dynamic obstacles. We propose a model predictive control (MPC) scheme that formulates the obstacle avoidance constraint using coherent risk measures. To handle disturbances, or process noise, in the state dynamics, the state constraints are tightened in a risk-aware manner to provide a disturbance feedback policy. We also propose a waypoint following algorithm that uses the proposed MPC scheme for discrete distributions and prove its risk-sensitive recursive feasibility while guaranteeing finite-time task completion. We further investigate some commonly used coherent risk metrics, namely, conditional value-at-risk (CVaR), entropic value-at-risk (EVaR), and g-entropic risk measures, and propose a tractable incorporation within MPC. We illustrate our framework via simulation studies.