Miracle-dz/UniFAR-FTUs huggingface dataset:
Bilinear Form-Based Non-Negative Matrix Set Factorization

Non-negative Matrix Factorization(NMF)is a popular technique for representations of non-negative multivariate data.While treating a set of matrices,NMF is confronted with two main problems(unsatisfactory accuracy of representation and bad generality). In this paper,Non-negative Matrix Set Factorization(NMSF)is conceived to overcome the two problems and to retain NMF's good properties.Under the frame of NMSF,Bilinear Form-Based Non-negative Matrix Set Factorization(BFBNMSF)is systematically studied,and a monotonic algorithm of BFBNMSF is put forward.Theoretical analysis and experimental results show that while processing a data matrix-set,BFBNMSF results in more accurate representation and holds better generality than NMF,therefore it tends to extract more essential features of data matrix sets than NMF.
Design of Shape Actively Controllable Planar Pneumatic Kirigami Actuator

Kirigami structure is featured as changing its shape by deforming its gaps through buckling and torsion. However, the existing Kigrigami structures lack the ability to control the shapes of their gaps actively, which hinders their shape deformation performances. This letter proposes a novel planar pneumatic Kirigami actuator (PKA) whose bidirectional bending deformation can be actively controlled, which gives PKA the ability to mimic various curved surfaces with different Gaussian curvatures. It is achieved by embedding four air chambers into four gap walls that are circumferentially and uniformly distributed on the PKA. Each gap angle can be actively adjusted by inflating its relative air chamber, and the changing of the gap angle causes the adjustment of PKA's local bending deformation. Thus, the bidirectional bending deformation of the PKA is programmable by controlling the air pressures in different chambers. To rapidly predict and control the PKA deformation, a geometry-physics-combined PKA active deformation model is designed. This model can get similar computational accuracy with finite element method (FEM), but 1800 times faster, which well supports real-time applications. Theoretical analysis and experimental results prove that we can make PKA have a good linear relationship between air pressure and PKA deformation by designing reasonable structural parameters. Application of PKA on sucker grippers is given to demonstrate its potential usage.
Magnetic reconnection processes induced by a CME expansion

On 10–11 December 2005 a slow CME occurred in the Western Hemisphere in between two coronal streamers. SOHO/MDI magnetograms show a multipolar magnetic configuration at the photosphere: a complex of active regions located at the CME source and two bipoles at the base of the lateral coronal streamers. White light observations reveal that the CME expansion affects both of them and induces the release of plasma within or close to the nearby streamers. These transient phenomena are possibly due to magnetic reconnections induced by the CME expansion and occurring inside the streamer current sheet or between the CME flanks and the streamer. These events have been observed by the SOHO/UVCS with the spectrometer slit centered at 1.8 R ⊙ over about a full day. In this work we focus on the interaction between the CME and the streamer: the UVCS spectral interval included UV lines from ions at different temperatures of maximum formation such as O VI, Si XIII and Al Xi. These data gave us the opportunity to infer the evolution of plasma temperature and density at the reconnection site and adjacent regions. These are relevant to characterize secondary reconnection processes occurring during a CME development.
Review of Possible Therapies in Treatment of Novichoks Poisoning and HAZMAT/CBRNE Approaches: State of the Art

Novichoks-organophosphorus compounds belong to the nerve agents group, constituting the fourth generation of chemical warfare agents. The tremendous toxicity of Novichoks is assumed to be several times greater than that of VX, whereas no published experimental research supports this. They were surreptitiously created during the Cold War by the Soviet Union. Novichok’s toxic action mechanism consists of the inhibition of acetylcholinesterase activity. The review includes data on treating poisoning caused by OPs which could be used as guidelines for the therapy in case of Novichok exposure and HAZMAT/CBRNE approaches. Novichoks pose a severe threat due to their toxicity; however, there is insufficient information about the identity of A-series nerve agents. Filling in the missing data gaps will accelerate progress in improving protection against Novichoks and developing optimal therapy for treating poisoning casualties. Furthermore, introducing solutions to protect medical personnel in contact with a hazardous substance increases the chances of saving casualties of HAZMAT/CBRNE incidents.
Regular Article: Direct Simulations of 2D Fluid-Particle Flows in Biperiodic Domains

We propose a method to simulate the motion of 2D rigid particles in a viscous, incompressible fluid. Within the arbitrary Lagrangian Eulerian framework, momentum equations for both the fluid and the particles are discretized, and a coupled variational formulation is established. By introducing an appropriate finite element approximation, a symmetric linear system is obtained. This system is solved by an inexact Uzawa algorithm. The main interest of such simulations lies in the average behaviour of a high number of particles. We therefore introduced a biperiodic formulation of the problem, which makes it possible to represent many-body mixtures at a reasonable computational cost. In order to model realistic situations, an extra term must be added to the pressure. This extra term is shown to be the lagrange multiplier associated with the vertical volume conservation constraint. We developed an appropriate unstructured mesh generator, so that the biperiodicity of the fields can be treated in a strong sense. The question of particle contact is addressed, and a simple technique to overcome numerical problems is proposed. The influence of periodic lengths is investigated through different simulations. The same case is simulated for different sizes of the window, and the behaviour of some space-averaged quantities is studied.
Our sun. II - Early mass loss of 0.1 solar mass and the case of the missing lithium

It is demonstrated that early main-sequence mass loss by the sun can solve the case of the missing solar Li. The mass loss is 0.10-0.11 solar if the ZAMS Li-7/H ratio is taken to be 1.0 {times} 10 to the -9th, the maximum value observed in Population I main-sequence stars. The mass loss is 0.12-0.13 solar if ZAMS Li-7/H is taken to be 2.6 {times} 10 to the -9th, the meteoritic value. The required amount of mass loss is nearly independent of the mass-loss time scale. A simple formula exists to estimate the amount of mass loss required by an observed Li depletion. Constant-mass models burn Li and Be at temperatures of 2.5 and 3.3 million K, respectively. Higher initial temperatures are required in mass-losing models. A prescription has been developed to estimate these temperatures as a function of initial stellar mass and initial mass-loss rate. 35 refs.
A Biallelic Truncating Variant in the TPR Domain of GEMIN5 Associated with Intellectual Disability and Cerebral Atrophy

GEMIN5 is a multifunctional RNA-binding protein required for the assembly of survival motor neurons. Several bi-allelic truncating and missense variants in this gene are reported to cause a neurodevelopmental disorder characterized by cerebellar atrophy, intellectual disability (ID), and motor dysfunction. Whole exome sequencing of a Pakistani consanguineous family with three brothers affected by ID, cerebral atrophy, mobility, and speech impairment revealed a novel homozygous 3bp-deletion NM_015465. 5:c. 3162_3164del that leads to the loss of NM_015465. 5 (NP_056280.2):p. (Asp1054_Ala1055delinsGlu) amino acid in one of the α-helixes of the tetratricopeptide repeats of GEMIN5. In silico 3D representations of the GEMIN5 dimerization domain show that this variant likely affects the orientation of the downstream sidechains out of the helix axis, which would affect the packing with neighboring helices. The phenotype of all affected siblings overlaps well with previously reported patients, suggesting that NM_015465. 5: c. 3162_3164del (NP_056280.2):p. (Asp1054_Ala1055delinsGlu) is a novel GEMIN5 pathogenic variant. Overall, our data expands the molecular and clinical phenotype of the recently described neurodevelopmental disorder with cerebellar atrophy and motor dysfunction (NEDCAM) syndrome.
Precise Event Sampling on AMD Versus Intel: Quantitative and Qualitative Comparison

Precise event sampling is a profiling feature in commodity processors that can sample hardware events and accurately locate the instructions that trigger the events. This feature has been used in a large number of tools to detect application performance issues. Although precise event sampling is readily supported in modern multicore architectures, vendor supports exhibit great differences that affect their accuracy, stability, overhead, and functionality. This work presents the most comprehensive study to date on benchmarking the event sampling features of Intel PEBS and AMD IBS and performs in-depth analysis on key differences through series of microbenchmarks. Our qualitative and quantitative analysis shows that PEBS allows finer-grained and more accurate sampling of hardware events, while IBS offers richer set of information at each sample though it suffers from lower accuracy and stability. Moreover, OS signal delivery, which is a common method used by the profiling software, introduces significant time overhead to the original overhead incurred by the hardware mechanisms in both PEBS and IBS. We also found that both PEBS and IBS have bias in sampling events across multiple different locations in a code. Lastly, we demonstrate how our findings on microbenchmarks under different thread counts hold for a full-fledged profiling tool that runs on the state-of-the-art Intel and AMD machines. Overall our detailed comparisons serve as a great reference and provide invaluable information for hardware designers and profiling tool developers.
Wearable optical sensor arrays for cardiovascular health monitoring and biomarker mapping

Photoplethysmography (PPG) is an optical technique to study light absorption variations by blood pulsation. We have developed a flexible thin-film photodiode array combined with flexible LED light sources, both integrated into a wearable form factor, to measure PPG signals at various wavelengths and at any location on the human body in reflection. The array contains 256 photodiodes over an area of approximately 4 cm2, which can be read out at high frequencies up to 5.4 kHz. The large number of photodiodes operated at high speeds enables spatiotemporal PPG information with a high signal quality. Furthermore, applying independent component analysis to the data array allows for signal quality mapping and enhancement of the PPG signals over the full array. These wearable sensor arrays allow for new types of cardiovascular health related analysis, such as local biomarker mapping and in-situ probing of blood pulsation at different depths underneath the skin.
Deep Learning Based Causal Inference for Large-Scale Combinatorial Experiments: Theory and Empirical Evidence

Large-scale online platforms launch hundreds of randomized experiments (a.k.a. A/B tests) every day to iterate their operations and marketing strategies, while the combinations of these treatments are typically not exhaustively tested. It triggers an important question of both academic and practical interests: Without observing the outcomes of all treatment combinations, how to estimate the causal effect of any treatment combination and identify the optimal treatment combination? We develop a novel framework combining deep learning and double machine learning to estimate the causal effect of any treatment combination for each user on the platform when observing only a small subset of treatment combinations. Our proposed framework (called debiased deep learning, DeDL) exploits Neyman orthogonality and combines interpretable and flexible structural layers in deep learning. We prove theoretically that this framework yields consistent and asymptotically normal estimators under mild assumptions, thus allowing for identifying the best treatment combination when only observing a few combinations. To empirically validate our method, we then collaborate with a large-scale video-sharing platform and implement our framework for three experiments involving three treatments where each combination of treatments is tested. When only observing a subset of treatment combinations, our DeDL approach significantly outperforms other benchmarks to accurately estimate and infer the average treatment effect (ATE) of any treatment combination and to identify the optimal treatment combination.
The role of forest extraction in the livelihood strategies of Indonesian smallholder cattle farmers

The understanding of the role of using forest resources in the livelihood strategies of smallholder farmers is limited. Rural household surveys often omit this aspect. From a survey of 600 Indonesian cattle farmers, we apply the sustainable livelihood framework to investigate the role extracting forest resources has in livelihood strategies and household income. We also quantify which farmers’ characteristics impact the decision to extract them. Forest extraction appears a core livelihood strategy of farmers who rely in some way on forests, which are on average poorer. Our findings suggest that forest extraction increases with increased income diversification. Farmers who specialize as feeders in the cattle supply chain engage significantly less in that. The promotion of sustainable forest resource usage schemes, such as agroforestry or silvopastoral systems that facilitate, and support cattle breeding would maintain the supply of youngstock for feeders and contribute to sustainable future use of forest resources.
A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT

In mobile edge computing (MEC), it is difficult to recognise an optimum solution that can perform in limited energy by selecting the best communication path and components. This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. We utilised a CNN to determine the best-transferring strategy and the most efficient partitioning of a specific task. The MKM method has more than one cluster head in each cluster to lead. It also reduces the number of reclustering cycles, which helps to overcome the energy consumption and delay during the reclustering process. The proposed model determines a training dataset by covering all the aspects of cost function calculation. This training dataset helps to train the model, which allows for efficient decision-making in optimum energy usage. In MEC, clusters have a dynamic nature and frequently change their location. Sometimes, this creates hurdles for the clusters to form a cluster head and, finally, abandons the cluster. The selected cluster heads must be recognised correctly and applied to maintain and supervise the clusters. The proposed pairing of the modified k-means method with a CNN fulfils this objective. The proposed method, existing weighted clustering algorithm (WCA), and agent-based secure enhanced performance approach (AB-SEP) are tested over the network dataset. The findings of our experiment demonstrate that the proposed hybrid model is promising in aspects of CD energy consumption, overhead, packet loss rate, packet delivery ratio, and throughput compared to existing approaches.
Phase 1 efficacy and pharmacodynamic results of exicorilant + enzalutamide in patients with metastatic castration-resistant prostate cancer.

145 Background: Metastatic castration-resistant prostate cancer (mCRPC) remains an incurable disease with significant morbidity. Androgen receptor (AR) signaling is a key driver of tumor growth in mCRPC, and AR-targeted therapies are the mainstay for patients (pts) with locally advanced or metastatic disease. Enzalutamide (ENZA) is commonly used, but resistance typically develops within 1–2 years. The glucocorticoid receptor (GR) can substitute for the AR, providing a tumor escape pathway (Arora et al. Cell 2013). In the 22Rv1 CRPC xenograft model, the selective GR modulator exicorilant (EXI) combined with ENZA reduced tumor growth, supporting the hypothesis that dual antagonism of GR + AR may block this escape pathway. Safety and pharmacokinetics from the first study of EXI + ENZA in pts with mCRPC (NCT03437941) were previously presented (Linch et al. ESMO 2022). Here, we report efficacy and pharmacodynamic (PD) results from the same study. Methods: Segment 1 (Seg 1) of this phase 1 study evaluated open-label, fasting, BID dosing of EXI (140 or 180 mg) + ENZA 160 mg QD. Segment 2 (Seg 2) tested QD dosing of EXI with food in a double-blind design: All pts received EXI 240 mg + ENZA and were randomized 3:1 to EXI titration (to 280 mg followed by 320 mg) or to remain on EXI 240 mg + placebo. Efficacy assessments included radiographic response and changes in prostate-specific antigen (PSA) levels. PSA was collected prior to study entry and PSA doubling times were calculated before and during treatment. PD analyses included baseline (BL) tumor GR expression and modulation of GR target genes in whole blood. As not all pts enrolled in Seg 1 were ENZA naïve, efficacy data are reported for Seg 2 only. Data cutoff date: July 7, 2022. Results: 39 pts were enrolled (Seg 1: 14, irrespective of prior ENZA exposure; Seg 2: 25, on a stable ENZA dose with rising PSA, defined as a 25% increase over nadir and absolute value >1 ng/mL). In Seg 2, there were no radiographic responses, 18 pts had a best overall response of stable disease per PCWG3, and 1 pt achieved a PSA response (≥50% PSA reduction from BL). BL tumor GR expression was detectable in all assessed tumors. PD analyses demonstrated EXI modulation of GR target genes, such as CDKN1C. Comparable PD effects were observed across EXI doses (240–320 mg QD). While BL 24-h urinary free cortisol (UFC) for most pts was within the normal range, improvements in PSA doubling times after treatment with EXI + ENZA were predominantly observed in pts with higher BL UFC ( P<0.05). Conclusions: This study did not include an ENZA-alone arm and was thus not designed to assess the contribution of EXI to the efficacy of the EXI + ENZA combination. In heavily pretreated pts with prior ENZA exposure, 1 PSA response and no radiographic responses were observed. PD analysis confirmed systemic GR modulation. Instances of PSA doubling time improvements were observed in pts with relatively higher UFC. Clinical trial information: NCT03437941 .
Multimodal microscopy imaging of cardiac collagen network: Are we looking at the same structures?

Visualization of collagen fibers in cardiac tissues is essential for clinical diagnosis and pathological analysis of cardiac fibrosis. Selecting a proper imaging method is still challenging for researchers and clinicians who want to determine specific information about the collagen network in cardiac tissues. We examined fibrillar collagen network from mouse ventricular myocardium by commonly available light microscopy techniques using our home-built multimodal microscope. Myocardial slices were unstained or stained with either Picrosirius red or collagen type I antibody/dye conjugation, then imaged by polarized light, confocal fluorescence, second harmonic generation (SHG), two-photon excited fluorescence (TPEF), and stimulated emission depletion (STED) microscopy techniques. This study is intended to serve as a reference for basic research and clinical evaluation of fibrillar collage network in cardiac tissues.
Highlighted Advances in Therapies for Difficult-To-Treat Brain Tumours Such as Glioblastoma

Glioblastoma multiforme (GBM) remains a challenging disease, as it is the most common and deadly brain tumour in adults and has no curative solution and an overall short survival time. This incurability and short survival time means that, despite its rarity (average incidence of 3.2 per 100,000 persons), there has been an increased effort to try to treat this disease. Standard of care in newly diagnosed glioblastoma is maximal tumour resection followed by initial concomitant radiotherapy and temozolomide (TMZ) and then further chemotherapy with TMZ. Imaging techniques are key not only to diagnose the extent of the affected tissue but also for surgery planning and even for intraoperative use. Eligible patients may combine TMZ with tumour treating fields (TTF) therapy, which delivers low-intensity and intermediate-frequency electric fields to arrest tumour growth. Nonetheless, the blood–brain barrier (BBB) and systemic side effects are obstacles to successful chemotherapy in GBM; thus, more targeted, custom therapies such as immunotherapy and nanotechnological drug delivery systems have been undergoing research with varying degrees of success. This review proposes an overview of the pathophysiology, possible treatments, and the most (not all) representative examples of the latest advancements.
Existence, stability and formation of baroclinic tripoles in quasi-geostrophic flows

Hetons are baroclinic vortices able to transport tracers or species, which have been observed at sea. This paper studies the offset collision of two identical hetons, often resulting in the formation of a baroclinic tripole, in a continuously stratified quasi-geostrophic model. This process is of interest since it (temporarily or definitely) stops the transport of tracers contained in the hetons. First, the structure, stationarity and nonlinear stability of baroclinic tripoles composed of an upper core and two lower (symmetric) satellites are studied analytically for point vortices and numerically for finite-area vortices. The condition for stationarity of the point vortices is obtained and it is proven that the baroclinic point tripoles are neutral. Finite-volume stationary tripoles exist with marginal states having very elongated (figure-of-eight shaped) upper cores. In the case of vertically distant upper and lower cores, the latter can nearly join near the centre of the plane. These steady states are compared with their two-layer counterparts. Then, the nonlinear evolution of the steady states shows when they are often neutral (showing an oscillatory evolution); when they are unstable, they can either split into two hetons (by breaking of the upper core) or form a single heton (by merger of the lower satellites). These evolutions reflect the linearly unstable modes which can grow on the vorticity poles. Very tall tripoles can break up vertically due to the vertical shear mutually induced by the poles. Finally, the formation of such baroclinic tripoles from the offset collision of two identical hetons is investigated numerically. This formation occurs for hetons offset by less than the internal separation between their poles. The velocity shear during the interaction can lead to substantial filamentation by the upper core, thus forming small upper satellites, vertically aligned with the lower ones. Finally, in the case of close and flat poles, this shear (or the baroclinic instability of the tripole) can be strong enough that the formed baroclinic tripole is short-lived and that hetons eventually emerge from the collision and drift away.