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As the scale of vision models continues to grow, the emergence of Visual Prompt Tuning (VPT) as a parameter-efficient transfer learning technique has gained attention due to its superior performance compared to traditional full-finetuning. However, the conditions favoring VPT (the ``when") and the underlying rationale (the ``why") remain unclear. In this paper, we conduct a comprehensive analysis across 19 distinct datasets and tasks. To understand the ``when" aspect, we identify the scenarios where VPT proves favorable by two dimensions: task objectives and data distributions. We find that VPT is preferrable when there is 1) a substantial disparity between the original and the downstream task objectives (e.g., transitioning from classification to counting), or 2) a similarity in data distributions between the two tasks (e.g., both involve natural images). In exploring the ``why" dimension, our results indicate VPT's success cannot be attributed solely to overfitting and optimization considerations. The unique way VPT preserves original features and adds parameters appears to be a pivotal factor. Our study provides insights into VPT's mechanisms, and offers guidance for its optimal utilization., Comment: 29 pages, 19 figures

We introduce the novel Diffusion Visual Programmer (DVP), a neuro-symbolic image translation framework. Our proposed DVP seamlessly embeds a condition-flexible diffusion model within the GPT architecture, orchestrating a coherent sequence of visual programs (i.e., computer vision models) for various pro-symbolic steps, which span RoI identification, style transfer, and position manipulation, facilitating transparent and controllable image translation processes. Extensive experiments demonstrate DVP's remarkable performance, surpassing concurrent arts. This success can be attributed to several key features of DVP: First, DVP achieves condition-flexible translation via instance normalization, enabling the model to eliminate sensitivity caused by the manual guidance and optimally focus on textual descriptions for high-quality content generation. Second, the framework enhances in-context reasoning by deciphering intricate high-dimensional concepts in feature spaces into more accessible low-dimensional symbols (e.g., [Prompt], [RoI object]), allowing for localized, context-free editing while maintaining overall coherence. Last but not least, DVP improves systemic controllability and explainability by offering explicit symbolic representations at each programming stage, empowering users to intuitively interpret and modify results. Our research marks a substantial step towards harmonizing artificial image translation processes with cognitive intelligence, promising broader applications., Comment: 25 pages, 20 figures

Cell segmentation is a fundamental task in analyzing biomedical images. Many computational methods have been developed for cell segmentation, but their performances are not well understood in various scenarios. We systematically evaluated the performance of 18 segmentation methods to perform cell nuclei and whole cell segmentation using light microscopy and fluorescence staining images. We found that general-purpose methods incorporating the attention mechanism exhibit the best overall performance. We identified various factors influencing segmentation performances, including training data and cell morphology, and evaluated the generalizability of methods across image modalities. We also provide guidelines for choosing the optimal segmentation methods in various real application scenarios. We developed Seggal, an online resource for downloading segmentation models already pre-trained with various tissue and cell types, which substantially reduces the time and effort for training cell segmentation models.

In this work, we introduce the Prototypical Transformer (ProtoFormer), a general and unified framework that approaches various motion tasks from a prototype perspective. ProtoFormer seamlessly integrates prototype learning with Transformer by thoughtfully considering motion dynamics, introducing two innovative designs. First, Cross-Attention Prototyping discovers prototypes based on signature motion patterns, providing transparency in understanding motion scenes. Second, Latent Synchronization guides feature representation learning via prototypes, effectively mitigating the problem of motion uncertainty. Empirical results demonstrate that our approach achieves competitive performance on popular motion tasks such as optical flow and scene depth. Furthermore, it exhibits generality across various downstream tasks, including object tracking and video stabilization., Comment: 21 pages, 10 figures

Visual-based perception is the key module for autonomous driving. Among those visual perception tasks, video object detection is a primary yet challenging one because of feature degradation caused by fast motion or multiple poses. Current models usually aggregate features from the neighboring frames to enhance the object representations for the task heads to generate more accurate predictions. Though getting better performance, these methods rely on the information from the future frames and suffer from high computational complexity. Meanwhile, the aggregation process is not reconfigurable during the inference time. These issues make most of the existing models infeasible for online applications. To solve these problems, we introduce a stepwise spatial global-local aggregation network. Our proposed models mainly contain three parts: 1). Multi-stage stepwise network gradually refines the predictions and object representations from the previous stage; 2). Spatial global-local aggregation fuses the local information from the neighboring frames and global semantics from the current frame to eliminate the feature degradation; 3). Dynamic aggregation strategy stops the aggregation process early based on the refinement results to remove redundancy and improve efficiency. Extensive experiments on the ImageNet VID benchmark validate the effectiveness and efficiency of our proposed models.

The advancement of computer vision has pushed visual analysis tasks from still images to the video domain. In recent years, video instance segmentation, which aims to track and segment multiple objects in video frames, has drawn much attention for its potential applications in various emerging areas such as autonomous driving, intelligent transportation, and smart retail. In this paper, we propose an effective framework for instance-level visual analysis on video frames, which can simultaneously conduct object detection, instance segmentation, and multi-object tracking. The core idea of our method is collaborative multi-task learning which is achieved by a novel structure, named associative connections among detection, segmentation, and tracking task heads in an end-to-end learnable CNN. These additional connections allow information propagation across multiple related tasks, so as to benefit these tasks simultaneously. We evaluate the proposed method extensively on KITTI MOTS and MOTS Challenge datasets and obtain quite encouraging results.

As the size of transformer-based models continues to grow, fine-tuning these large-scale pretrained vision models for new tasks has become increasingly parameter-intensive. Parameter-efficient learning has been developed to reduce the number of tunable parameters during fine-tuning. Although these methods show promising results, there is still a significant performance gap compared to full fine-tuning. To address this challenge, we propose an Effective and Efficient Visual Prompt Tuning (E^2VPT) approach for large-scale transformer-based model adaptation. Specifically, we introduce a set of learnable key-value prompts and visual prompts into self-attention and input layers, respectively, to improve the effectiveness of model fine-tuning. Moreover, we design a prompt pruning procedure to systematically prune low importance prompts while preserving model performance, which largely enhances the model's efficiency. Empirical results demonstrate that our approach outperforms several state-of-the-art baselines on two benchmarks, with considerably low parameter usage (e.g., 0.32% of model parameters on VTAB-1k). Our code is available at https://github.com/ChengHan111/E2VPT., Comment: 12 pages, 4 figures

The X/$\gamma$ ray polarimetry of the Crab pulsar/nebula is believed to hold crucial information on their emission models. In the past, several missions have shown evidence of polarized emission from the Crab. The significance of these measurements remains however limited. New measurements are therefore required. POLAR is a wide Field of View Compton-scattering polarimeter (sensitive in 50-500 keV) onboard the Chinese spacelab Tiangong-2 which took data from September 2016 to April 2017. Although not designed to perform polarization measurements of pulsars, we present here a novel method which can be applied to POLAR as well as that of other wide Field of View polarimeters. The novel polarimetric joint-fitting method for the Crab pulsar observations with POLAR, allows us to obtain constraining measurements of the pulsar component. The best fitted values and corresponding 1$\sigma$ deviations for the averaged phase interval: (PD=$14\substack{+15 \\ -10}$\%, PA=$108\substack{+33 \\ -54} ^{\circ}$), for Peak 1: (PD=$17\substack{+18 \\ -12}$\%, PA=$174\substack{+39 \\ -36} ^{\circ}$) and for Peak 2: (PD=$16\substack{+16 \\ -11}$\%, PA=$78\substack{+39 \\ -30} ^{\circ}$). Further more, the 3$\sigma$ upper limits on the polarization degree are for the averaged phase interval (55\%), Peak 1 (66\%) and Peak 2 (57\%). Finally, to illustrate the capabilities of this method in the future, we simulated two years observation to the Crab pulsar with POLAR-2. The results show that POLAR-2 is able to confirm the emission to be polarized with $5\sigma$ and $4\sigma$ confidence level if the Crab pulsar is polarized at $20\%$ and $10\%$ respectively., Comment: 14 pages, 18 figures, 2 tables; accepted for publication in MNRAS

The rational design and preparation of cost-effective, efficient and durable metal carbon nanomaterials for the oxygen evolution reaction (OER) is of great urgency. Herein, we report a high-performance OER electrocatalyst consisting of bimetallic FeNi₃ nanoparticles encapsulated in hierarchical carbon nanomaterial, denoted as FeNi3@NCNT. Through a stepwise strategy, hollow carbon nanorods with abundant carbon nanotubes can be successfully calcined from rod-like NiOF-1-Fe, which are hydrolyzed to the initial NiOF-1 by Fe(III) ions. The optimal FeNi₃@NCNT catalyst exhibits an excellent electrochemical performance with a low overpotential of 264 mV at 10 mA cm⁻², a Tafel slope of 58.5 mV dec⁻¹, and a robust stability over 10 hours compared to the control samples. This enhanced OER arises from the unique hollow nanorod modified with a nanotube structure, a large surface area, a rich nitrogen content, and the synergistic effect between Ni and Fe species. Indeed, it is catalyzed by in situ generated Fe coupling with NiOOH in carbon nanotubes, which is validated by the subsequent theoretical calculations. This work enables insights into the mechanism of Fe-doped Ni oxyhydroxides for efficient OER and adds to the increasing understanding of the design and synthesis of novel catalysts for efficient energy conversion and storage.

We devise deep nearest centroids (DNC), a conceptually elegant yet surprisingly effective network for large-scale visual recognition, by revisiting Nearest Centroids, one of the most classic and simple classifiers. Current deep models learn the classifier in a fully parametric manner, ignoring the latent data structure and lacking simplicity and explainability. DNC instead conducts nonparametric, case-based reasoning; it utilizes sub-centroids of training samples to describe class distributions and clearly explains the classification as the proximity of test data and the class sub-centroids in the feature space. Due to the distance-based nature, the network output dimensionality is flexible, and all the learnable parameters are only for data embedding. That means all the knowledge learnt for ImageNet classification can be completely transferred for pixel recognition learning, under the "pre-training and fine-tuning" paradigm. Apart from its nested simplicity and intuitive decision-making mechanism, DNC can even possess ad-hoc explainability when the sub-centroids are selected as actual training images that humans can view and inspect. Compared with parametric counterparts, DNC performs better on image classification (CIFAR-10, ImageNet) and greatly boots pixel recognition (ADE20K, Cityscapes), with improved transparency and fewer learnable parameters, using various network architectures (ResNet, Swin) and segmentation models (FCN, DeepLabV3, Swin). We feel this work brings fundamental insights into related fields., Comment: 23 pages, 8 figures

Over the last decade, multi-tasking learning approaches have achieved promising results in solving panoptic driving perception problems, providing both high-precision and high-efficiency performance. It has become a popular paradigm when designing networks for real-time practical autonomous driving system, where computation resources are limited. This paper proposed an effective and efficient multi-task learning network to simultaneously perform the task of traffic object detection, drivable road area segmentation and lane detection. Our model achieved the new state-of-the-art (SOTA) performance in terms of accuracy and speed on the challenging BDD100K dataset. Especially, the inference time is reduced by half compared to the previous SOTA model. Code will be released in the near future.

Background: The Netherlands strives for hepatitis C virus (HCV) elimination, in accordance with the World Health Organization targets. An accurate estimate when HCV elimination will be reached is elusive. We have embarked on a nationwide HCV elimination project (CELINE) that allowed us to harvest detailed data on the Dutch HCV epidemic. This study aims to provide a well‐supported timeline towards HCV elimination in The Netherlands. Methods: A previously published Markov model was used, adopting published data and unpublished CELINE project data. Two main scenarios were devised. In the Status Quo scenario, 2020 diagnosis and treatment levels remained constant in subsequent years. In the Gradual Decline scenario, an annual decrease of 10% in both diagnoses and treatments was implemented, starting in 2020. WHO incidence target was disregarded, due to low HCV incidence in The Netherlands (≤5 per 100,000). Results: Following the Status Quo and Gradual Decline scenarios, The Netherlands would meet WHO’s elimination targets by 2027 and 2032, respectively. From 2015 to 2030, liver‐related mortality would be reduced by 97% in the Status Quo and 93% in the Gradual Decline scenario. Compared to the Status Quo scenario, the Gradual Decline scenario would result in 12 excess cases of decompensated cirrhosis, 18 excess cases of hepatocellular carcinoma, and 20 excess cases of liverrelated death from 2020-2030. Conclusions: The Netherlands is on track to reach HCV elimination by 2030. However, it is vital that HCV elimination remains high on the agenda to ensure adequate numbers of patients are being diagnosed and treated.

We derive Onsager-Machlup functionals for countable product measures on weighted $\ell^p$ subspaces of the sequence space $\mathbb{R}^{\mathbb{N}}$. Each measure in the product is a shifted and scaled copy of a reference probability measure on $\mathbb{R}$ that admits a sufficiently regular Lebesgue density. We study the equicoercivity and $\Gamma$-convergence of sequences of Onsager-Machlup functionals associated to convergent sequences of measures within this class. We use these results to establish analogous results for probability measures on separable Banach or Hilbert spaces, including Gaussian, Cauchy, and Besov measures with summability parameter $1 \leq p \leq 2$. Together with Part I of this paper, this provides a basis for analysis of the convergence of maximum a posteriori estimators in Bayesian inverse problems and most likely paths in transition path theory., Comment: 32 pages

The Bayesian solution to a statistical inverse problem can be summarised by a mode of the posterior distribution, i.e. a MAP estimator. The MAP estimator essentially coincides with the (regularised) variational solution to the inverse problem, seen as minimisation of the Onsager-Machlup functional of the posterior measure. An open problem in the stability analysis of inverse problems is to establish a relationship between the convergence properties of solutions obtained by the variational approach and by the Bayesian approach. To address this problem, we propose a general convergence theory for modes that is based on the $\Gamma$-convergence of Onsager-Machlup functionals, and apply this theory to Bayesian inverse problems with Gaussian and edge-preserving Besov priors. Part II of this paper considers more general prior distributions., Comment: 30 pages

In the analysis of stochastic dynamical systems described by stochastic differential equations (SDEs), it is often of interest to analyse the sensitivity of the expected value of a functional of the solution of the SDE with respect to perturbations in the SDE parameters. In this paper, we consider path functionals that depend on the solution of the SDE up to a stopping time. We derive formulas for Fr\'{e}chet derivatives of the expected values of these functionals with respect to bounded perturbations of the drift, using the Cameron-Martin-Girsanov theorem for the change of measure. Using these derivatives, we construct an example to show that the map that sends the change of drift to the corresponding relative entropy is not in general convex. We then analyse the existence and uniqueness of solutions to stochastic optimal control problems defined on possibly random time intervals, as well as gradient-based numerical methods for solving such problems.

Uncertainty quantification plays an important role in problems that involve inferring a parameter of an initial value problem from observations of the solution. Conrad et al.\ (\textit{Stat.\ Comput.}, 2017) proposed randomisation of deterministic time integration methods as a strategy for quantifying uncertainty due to the unknown time discretisation error. We consider this strategy for systems that are described by deterministic, possibly time-dependent operator differential equations defined on a Banach space or a Gelfand triple. Our main results are strong error bounds on the random trajectories measured in Orlicz norms, proven under a weaker assumption on the local truncation error of the underlying deterministic time integration method. Our analysis establishes the theoretical validity of randomised time integration for differential equations in infinite-dimensional settings., Comment: 28 pages

BackgroundThe development of carotid-cavernous fistulas (CCFs) during surgical recanalization of chronic internal carotid artery occlusion (ICAO) may be secondary to severe ICA dissection rather than a focal tear of the cavernous ICA seen in typical traumatic CCFs. The purpose of this study is to investigate the causal relationship between the CCFs and severe ICA dissections and to characterize technical outcomes after treatment with stenting.MethodsFive patients underwent treatment with self-expanding stents due to intraprocedural CCF and ICA dissection following surgical removal of ICAO plaque. The stents were telescopically placed via true channel of the dissection. Safety of the procedure was evaluated with 30-day stroke and death rate. Procedural success was determined by the efficacy of CCF obliteration and ICAO recanalization with angiography.ResultsAll CCFs were associated with spiral and long segmental dissection from the cervical to cavernous ICA. After stenting, successful dissection reconstruction with TICI 3 was achieved in all patients, with complete (n = 4) or partial CCF (n = 1) obliteration. No patient had CCF syndrome, stroke, or death during follow-up of 6 to 37 months; but one patient had pulsatile tinnitus, which resolved 1 year later. Angiography at 6 to 24 months demonstrated CCF obliteration in all 5 patients and durable ICA patency in 4 patients.ConclusionsIntraprocedural CCFs with spiral and cervical-to-cavernous ICA dissection during ICAO surgery are dissection-related because of successful obliteration after stenting for dissection reconstruction. Self-expanding stenting through true channel of the dissection, serving as implanting stent-autograft, may be an optimal therapy for the atypical CCF complication from ICAO surgery.

Jisong Zhang, Cheng Han, Fan Yang, Shan Xu, Huihui Hu, Enguo Chen Department of Pulmonary and Critical Care Medicine, Sir Run Run Shaw Hospital of Zhejiang University, Hangzhou 310016, People’s Republic of ChinaCorrespondence: Enguo ChenDepartment of Pulmonary and Critical Care Medicine, Sir Run Run Shaw Hospital of Zhejiang University, No. 3 East Qingchun Road, Jianggan District, Hangzhou 310016, People’s Republic of ChinaTel +86 13588706779Email 3195024@zju.edu.cnObjective: A large number of isolation wards were built to screen suspected patients because of the outbreak of coronavirus disease 2019 (COVID-19). The particularity of the isolation wards would lead to more medical resource consumption and heavier hospital control tasks. Therefore, we adopted a vital signs telemetry system in the isolation wards to improve this situation.Materials and Technologies: Twenty sets of vital signs telemetry system were installed in the east district of the isolation area and the wards were used as the telemetry system wards (TSWs). The wards in the west district were used as the routine wards (RW). The daily telephone questionnaire was used to collect the frequency and time of ward rounds by medical staff and lasted for one week.Results: Within one-week survey, the average frequency of RW rounds was 3.00 ± 1.00 times per day, and the average time was 93.57 ± 66.25 min. The daily frequency of RW rounds was 0.428 ± 0.394 times per capita, and the time was 7.88 ± 2.36 min. There was a statistically significant difference in the time of ward rounds per capita, which presented that the daily time of TSW rounds per capita was shorter than that of RW rounds. No security events related to telemetry equipment were found throughout the study.Conclusion: The application of vital signs telemetry system as an alternative to traditional ward monitoring is considered feasible. The use of telemetry system can significantly reduc

Despite over 50 years of research, many open questions remain about the origin and nature of GRBs. Polarization measurements of the prompt emission of these extreme phenomena have long been thought to be the key to answering a range of these questions. The POLAR detector was designed to produce the first set of detailed and reliable polarization measurements in an energy range of approximately 50-500 keV. During late 2016 and early 2017, POLAR detected a total of 55 GRBs. Analysis results of 5 of these GRBs have been reported in the past. The results were found to be consistent with a low or unpolarized flux. However, previous reports by other collaborations found high levels of polarization. We study the polarization for all the 14 GRBs observed by POLAR for which statistically robust inferences are possible. Additionally, time-resolved polarization studies are performed on GRBs with sufficient apparent flux. A publicly available polarization analysis tool, developed within the 3ML framework, was used to produce statistically robust results. The method allows to combine spectral and polarimetric data from POLAR with spectral data from the Fermi GBM and Swift-BAT to jointly model the spectral and polarimetric parameters. The time integrated analysis finds all results to be compatible with a low or zero polarization with the caveat that, when time-resolved analysis is possible within individual pulses, we observe moderate polarization with a rapidly changing polarization angle. Thus, time-integrated polarization results, while pointing to lower polarization are potentially an artifact of summing over the changing polarization signal and thus, washing out the true moderate polarization. Therefore, we caution against over interpretation of any time-integrated results and encourage one to wait for more detailed polarization measurements from forthcoming missions such as POLAR-2 and LEAP., Comment: 43 pages, 78 figures, Accepted for publication in A&A

We report here the design, performance, and in situ demonstration, on‐land and offshore, of an innovative high‐resolution low‐cost optical (laser) seismometer. The instrument was developed within the Laser Interferometry for Earth Strain project (French Agence Nationale de la Recherche [ANR] program), and first tested at the low‐noise underground laboratory Laboratoire Souterrain à Bas Bruit (LSBB, France). It is based on Fabry–Pérot optical interferometry between the extremity of a probing optical fiber and a reflecting mirror secured to the mobile mass of a passive 2 Hz geophone. The detection technique is based on the wavelength modulation of the laser diode (1310 nm), which allows the separation of the optical power into two signals in quadrature, thanks to an heterodyne technique. The relative displacement of the mobile mass is retrieved in real time by the phase unwrapping of these two signals. At LSBB, the fiber was 3 km long. It recorded many teleseismic earthquakes and a few regional ones, and resolves the low‐seismic noise of the Earth for periods up to 6 s, presenting an acceleration noise floor lower than 1 ng/Hz−−−√ in the 0.3–5 Hz range. A three‐component version of this fiber‐based interferometric 2 Hz geophone has been recently constructed, shielded in a hyperbaric container, and installed offshore for test in Brittany (France) in April 2018, with an improved control system. Its record of the marine ambient noise matches those of a collocated commercial broadband seismometer for periods up to 50 s. This opens promising perspectives for large‐scale ocean bottom instrumentation with up to 50‐kilometer‐long optical lines; an installation is planned for 2020, off Guadeloupe, with a 5‐kilometer‐long fiber cable. It may also prove useful for installations in other challenging and exposed environments, such as deep hot boreholes, active volcanoes, unstable landslides, for real‐time monitoring in regions with high natural hazard, but also for seismic monito

BackgroundAn in situ recanalization procedure of endovascular therapy (ET) or carotid endarterectomy (CEA) has been attempted in patients with symptomatic chronic internal carotid artery occlusions (ICAOs), though the recanalization rates of both are low.ObjectiveTo investigate the outcomes of Multimodality In situ Recanalization for ICAOs in a Hybrid Operating Room (MIRHOR) at the same session.MethodsSymptomatic chronic ICAOs were classified into type A or B (short occlusion with or without a tapered residual root [TRR]), and C or D (long occlusion with or without TRR), and managed in a hybrid operating room with ET, CEA, or both, as needed. Primary efficacy outcome was technical success of recanalization with Thrombolysis in Myocardial Infarction 3. Secondary efficacy outcome was any stroke or death within 30 days (primary safety outcome) plus an ipsilateral ischemic stroke after 30 days.ResultsTechnical success was finally achieved in 35 (83.3%) of 42 consecutively enrolled patients with ICAO, which was significantly higher than 35.7% (15/42, p<0.001) from the initial ET or CEA alone. Furthermore, the success rate was in descending order: 100% (18/18) for type A and B occlusions, 75% (6/8) for type C occlusions, and 69% (11/16) for type D occlusions (p=0.017). Two secondary efficacy outcome events (5.1%) without mortality, including one (2.4%) primary safety outcome, were observed during a mean follow-up of 10.5 months.ConclusionThe MIRHOR for symptomatic chronic ICAOs at the same session significantly improves technical success, with low periprocedural complications and favorable clinical outcomes. The ICAO classification appears valuable in predicting technical success.

The POLAR detector is a space based Gamma-Ray Burst (GRB) polarimeter sensitive in the 15-500 keV energy range. Apart from its main scientific goal as a Gamma-Ray Burst polarimeter it is also able to detect photons from pulsars in orbit. By using the six-months in-orbit observation data, significant pulsation from the PSR B0531+21 (Crab pulsar) was obtained. In this work, we present the precise timing analysis of the Crab pulsar, together with a phase-resolved spectroscopic study using a joint-fitting method adapted for wide field of view instruments like POLAR. By using single power law fitting over the pulsed phase, we obtained spectral indices ranging from 1.718 to 2.315, and confirmed the spectral evolution in a reverse S shape which is homogenous with results from other missions over broadband. We will also show, based on the POLAR in-orbit performance and Geant4 Monte-Carlo simulation, the inferred capabilities of POLAR-2, the proposed follow-up mission of POLAR on board the China Space Station (CSS), for pulsars studies., Comment: 15 pages, 9 figures, 2 tables, accepted for publication in Journal of High Energy Astrophysics

Gamma-ray bursts are the strongest explosions in the Universe since the Big Bang, believed to be produced either in forming black holes at the end of massive star evolution or merging of compact objects. Spectral and timing properties of gamma-ray bursts suggest that the observed bright gamma-rays are produced in the most relativistic jets in the Universe; however, the physical properties, especially the structure and magnetic topologies in the jets are still not well known, despite several decades of studies. It is widely believed that precise measurements of the polarization properties of gamma-ray bursts should provide crucial information on the highly relativistic jets. As a result there have been many reports of gamma-ray burst polarization measurements with diverse results, see, however many such measurements suffered from substantial uncertainties, mostly systematic. After the first successful measurements by the GAP and COSI instruments, here we report a statistically meaningful sample of precise polarization measurements, obtained with the dedicated gamma-ray burst polarimeter, POLAR onboard China's Tiangong-2 spacelab. Our results suggest that the gamma-ray emission is at most polarized at a level lower than some popular models have predicted; although our results also show intrapulse evolution of the polarization angle. This indicates that the low polarization degrees could be due to an evolving polarization angle during a gamma-ray burst., Comment: 34 pages, 15 figures (16 pages and 3 figures without supplementary information). Accepted for publication in Nature Astronomy, http://dx.doi.org/10.1038/s41550-018-0664-0

In certain applications involving the solution of a Bayesian inverse problem, it may not be possible or desirable to evaluate the full posterior, e.g. due to the high computational cost of doing so. This problem motivates the use of approximate posteriors that arise from approximating the data misfit or forward model. We review some error bounds for random and deterministic approximate posteriors that arise when the approximate data misfits and approximate forward models are random., Comment: 8 pages

Transition path theory (TPT) for diffusion processes is a framework for analysing the transitions of multiscale ergodic diffusion processes between disjoint metastable subsets of state space. Most methods for applying TPT involve the construction of a Markov state model on a discretisation of state space that approximates the underlying diffusion process. However, the assumption of Markovianity is difficult to verify in practice, and there are to date no known error bounds or convergence results for these methods. We propose a Monte Carlo method for approximating the forward committor, probability current, and streamlines from TPT for diffusion processes. Our method uses only sample trajectory data and partitions of state space based on Voronoi tessellations. It does not require the construction of a Markovian approximating process. We rigorously prove error bounds for the approximate TPT objects and use these bounds to show convergence to their exact counterparts in the limit of arbitrarily fine discretisation. We illustrate some features of our method by application to a process that solves the Smoluchowski equation on a triple-well potential., Comment: 25 pages, 4 figures; minor change in wording, title modification

In this work, fine powders of K0.5Na0.5NbO3 (KNN) are produced by a single step of solution combustion synthesis (SCS) using glycine as the reductant fuel and potassium & sodium nitrates as the oxidizers, which are mixed with niobium oxide. Single phase of KNN products can be successfully prepared in a one-step SCS by adjusting the glycine-nitrate ratio. It is concluded that the stoichiometric or slightly fuel-excess condition is good for the single step production of KNN. The one-step SCS of KNN also shows good scaling-up productivity, which can be ignited by both electric heating and microwave heating. This work may provide a feasible large-scale production of various functional oxides by a one-step SCS process.

In this study we argue that mentoring, as a “social learning process”, can assist employees to merge into the organization more rapidly. The purpose of this study is to explore the relationship between supervisory mentoring functions and newcomers’ innovation performance. To explore this relationship, the moderating effects of task autonomy and supervisor capability were tested. Data were collected from two sources, newcomers and supervisors employed in four and five star hotels in Taiwan. The findings reveal that supervisory mentoring functions have a significant positive impact on newcomer’s innovation. Furthermore, the study also finds that task autonomy and supervisor capability strengthen the relationship between supervisory mentoring functions and newcomer’s innovation performance. Our findings suggest that mentoring is a powerful strategy that can be used to encourage innovation and that innovation performance is enhanced when organizations develop mentoring processes and structures which facilitate the development of creativity, interaction, and communication between employees.

We introduce a family of implicit probabilistic integrators for initial value problems (IVPs), taking as a starting point the multistep Adams-Moulton method. The implicit construction allows for dynamic feedback from the forthcoming time-step, in contrast to previous probabilistic integrators, all of which are based on explicit methods. We begin with a concise survey of the rapidly-expanding field of probabilistic ODE solvers. We then introduce our method, which builds on and adapts the work of Conrad et al. (2016) and Teymur et al. (2016), and provide a rigorous proof of its well-definedness and convergence. We discuss the problem of the calibration of such integrators and suggest one approach. We give an illustrative example highlighting the effect of the use of probabilistic integrators - including our new method - in the setting of parameter inference within an inverse problem.

A series of surface-doped LiMn2O4 samples modified by a Li2CuO2-Li2NiO2 solid solution were synthesized using a simple and facile sol-gel method to achieve the enhanced cycling performance, especially at elevated temperatures. The corresponding phase structure and morphology were investigated by X-ray diffraction (XRD) and scanning electron microscopy (SEM), respectively. The modified layer on the surface of LiMn2O4 particles, featuring a LiNi delta Mn2-delta O4-like phase, together with a Li2CuO2-Li2NiO2 solid solution, as confirmed by XRD and transmission electron microscopy (TEM), plays a key role in alleviating the dissolution of manganese, thus enhancing the cycling performance and rate capability relative to bare LiMn2O4. The 0.5 wt.%-modified LiMn2O4 sample delivers a discharge capacity of 113 mAh g(-1), and a capacity retention of 93.2% following 300 cycles at 1C and 25 degrees C, which is higher than the values of 96 mAh g(-1) and 81.2% for bare LiMn2O4. In addition, at 55 degrees C, a capacity retention of 81.2% at 1C is obtained for the 0.5 wt.%-modified LiMn2O4 sample after 200 cycles, compared to 70.0% for bare LiMn2O4. Modifying the surface of the latter by a LiNi delta Mn2-delta O4-like phase mixed with a Li2CuO2Li2NiO2 solid solution, is an effective strategy for improving electrochemical properties.

Yang Liu, Li Sun, Zhi-Cheng Xiong, Xin Sun, Shu-Ling Zhang, Jie-Tao Ma, Cheng-Bo Han Department of Oncology, Shengjing Hospital of China Medical University, Shenyang, People’s Republic of China Purpose: The purpose of this meta-analysis was to explore the influences of pretreatment de novo and posttreatment-acquired epidermal growth factor receptor (EGFR) T790M mutations in patients with advanced non-small cell lung cancer (NSCLC) who had received tyrosine kinase inhibitors (TKIs).Methods: We searched PubMed, Embase, and the China National Knowledge Infrastructure database for eligible literature. Data were extracted to assess the hazard ratios (HRs) for progression-free survival (PFS), overall survival (OS), and post-progression survival (PPS) and the relative ratios (RRs) for objective response rate (ORR).Results: This meta-analysis included 22 studies comprising 1,462 patients with NSCLC who harbored activating EGFR mutations and were treated with EGFR-TKIs. Compared to pretreatment T790M mutation-negative NSCLC, pretreatment T790M mutation-positive NSCLC was associated with decreased PFS (HR 2.23, P<0.001) and OS (HR 1.55, P=0.003). A trend toward significance of worsening ORR (RR 0.86, P=0.051) was evident. The acquired T790M mutation was correlated with improved PFS (HR 0.75, P=0.006) and PPS (HR 0.57, P<0.001), compared to patients without the T790M mutation who progressed after EGFR-TKI treatment. There were no significant differences in OS or ORR between patients with acquired T790M mutation-positive and T790M mutation-negative NSCLC. However, in the tumor tissue rebiopsy subgroup, patients with acquired T790M mutation had improved OS (HR 0.60, P<0.001) compared to T790M mutation-negative patients. In the plasma ctDNA subgroup, acquired T790M mutation decreased the OS (HR 1.87, P<0.001).Conclusion: Pretreatment T790M mutation was associated with worse PFS and OS in patients with advanced NSCLC treated with EGFR-TKIs, wh

This dissertation emphasizes the use of end-effector sensor information for the performance enhancement of indirect drive systems for motion control. Indirect drive systems, unlike direct drive systems, use gear transmission mechanisms in the chain of links and actuator for the purpose of speed reduction and torque amplification. As a result, they are widely used in applications that require high torque capacity such as robotic applications. The gear transmission mechanisms, however, introduce compliance and nonlinear properties such as friction and hysteresis to the system. Moreover, when robots are driven at high speeds to increase productivity and quality, oscillations on the end-effector often occur caused by the transmission mechanism. Thus, the use of gear mechanisms brings great challenges to the design of servo control systems for robot manipulators that requires high precision at high speed.To enhance the performance of servo control systems for robot manipulators, this dissertation first presents a tuning method that automatically finds the servo gains of fixed structure controllers for a specified trajectory. The current practice is to tune the controller gains manually, which is a time-consuming task even for experienced control engineers. An automated gain tuning process saves not only time but also the labor cost. The tuning method presented in this dissertation finds the optimal controller gains using real-time nonlinear programming. The controller gains are tuned and the effectiveness of the tuning method is demonstrated by experiments. The dissertation then presents an adaptive disturbance cancellation scheme to reduce the oscillations caused by the transmission error from speed reducers. To enhance performance of the adaptive scheme while maintaining a good transient response, two modifications are introduced to the basic compensation structure. Experimental results confirm the effectiveness of the proposed schemes and the improvement in load side

Title: Enhancing Swedish Large MNEs’ Strategies in Chinese Market -By Analyzing the Perspectives of Consumers in Sweden and China Authors: Cheng Han and Xiaojing Gu Supervisor: Svante Andersson Level: Master Dissertation in International Marketing, 15 credits Keywords: Consumer behavior, Multinational enterprise, Marketing strategy, Swedish and Chinese market Background: With the trend of globalization, multinational enterprises noticed the potential market in China. Base on previous research, researchers indicated consumer behaviors have a sort of relationship and influence on MNEs’ strategies. Purpose: Investigate the distinctions between Swedish and Chinese consumer behaviors, due to the distinction, explore the way to enhance MNEs’ strategies in Chinese market. Research Questions: Q1: What are the differences between Chinese consumers and Swedish consumers evaluating same enterprises? Q2: How Swedish large MNEs develop their strategies for adapting the distinctions of Chinese consumers? Theoretical Framework: The theoretical framework includes theories regarding what factors of consumer behaviors are considered as influencing on enterprises’ strategies and the theories of general enterprise strategies. Methodology: This dissertation is a quantitative study accompany with case study. Empirical Framework: The empirical framework presents case descriptions and statistics. Analysis: The five hypotheses are analyzed and critical examined. Conclusion: Since consumers from different countries have different consumer behaviors, enterprises need to alter their strategies by adapting the distinctions of consumers.

In this paper, a novel method is proposed to produce MnO/carbon composites, in which the MnO nanoparticles were embedded into a porous carbon matrix, by a single-step nitrate-cellulose combustion synthesis. The composition, structure and morphology of the composites were characterized by X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, thermogravimetric analysis, and scanning/transmission electron microscopy. The composites were used as lithium ion battery anodes to evaluate their electrochemical properties. The MnO/carbon composite with a proper carbon content showed enhanced cycling performance and capacity retention, which delivered a reversible capacity of 561 mAh g(-1) after 90 cycles at 0.2 A g(-1). The easy production and good electrochemical properties enables the composite to be a possible candidate as an anode alternative for high-performance lithium ion battery.

In this study, MnO nanocrystals incorporated in a N-containing carbon matrix were fabricated by the facile thermal decomposition of manganese nitrate-glycine gels. MnO/C composites with different carbon contents were prepared by controlling the initial ratio of manganese to glycine. The composition, phase structure and morphology of the composites were characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, scanning and transmission electron microscopy, and thermogravimetric analysis. The results indicated that MnO nanocrystals were uniformly embedded in the N-doped carbon matrix. The carbon matrix could effectively enhance the electrical conductivity of MnO and alleviate the strain arising from the discharge/charge cycling. The composite materials exhibited high discharge/charge capacities, superior cycling performance, and excellent rate capability. A high reversible capacity of 556 mA h g(-1) was obtained after 110 cycles of discharging and charging at a current rate of 0.5 A g(-1). Even at a high current rate of 3 A g(-1), the sample still delivered a capacity of around 286 mA h g(-1). The easy production and superior electrochemical properties enables the composites to be a promising candidate as an anode alternative for high-performance lithium-ion batteries.

In this study, MnO nanocrystals incorporated in a N-containing carbon matrix were fabricated by the facile thermal decomposition of manganese nitrate-glycine gels. MnO/C composites with different carbon contents were prepared by controlling the initial ratio of manganese to glycine. The composition, phase structure and morphology of the composites were characterized by X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, scanning and transmission electron microscopy, and thermogravimetric analysis. The results indicated that MnO nanocrystals were uniformly embedded in the N-doped carbon matrix. The carbon matrix could effectively enhance the electrical conductivity of MnO and alleviate the strain arising from the discharge/charge cycling. The composite materials exhibited high discharge/charge capacities, superior cycling performance, and excellent rate capability. A high reversible capacity of 556 mA h g(-1) was obtained after 110 cycles of discharging and charging at a current rate of 0.5 A g(-1). Even at a high current rate of 3 A g(-1), the sample still delivered a capacity of around 286 mA h g(-1). The easy production and superior electrochemical properties enables the composites to be a promising candidate as an anode alternative for high-performance lithium-ion batteries.

In this paper, a novel method is proposed to produce MnO/carbon composites, in which the MnO nanoparticles were embedded into a porous carbon matrix, by a single-step nitrate-cellulose combustion synthesis. The composition, structure and morphology of the composites were characterized by X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy, thermogravimetric analysis, and scanning/transmission electron microscopy. The composites were used as lithium ion battery anodes to evaluate their electrochemical properties. The MnO/carbon composite with a proper carbon content showed enhanced cycling performance and capacity retention, which delivered a reversible capacity of 561 mAh g(-1) after 90 cycles at 0.2 A g(-1). The easy production and good electrochemical properties enables the composite to be a possible candidate as an anode alternative for high-performance lithium ion battery.

High-voltage LiNi0.5Mn1.5O4 cathode materials were synthesized using urea-based solution combustion synthesis combined with a calcination treatment. The morphology and particle size distribution of the products were considerably dependent on the amount of urea fuel. The electrochemical characterization illustrated that the sample that was produced with a fuel ratio of phi = 0.5 had a homogenous particle size distribution of approximately 8 mu m, and showed the best cycling and rate performance. LiNi0.5Mn1.5O4 with two different structures of disordered Fd (3) over barm and ordered P4(3)32 were obtained by controlling the calcination process. The samples, which were calcined at 800 degrees C with fast cooling, presented a disordered structure of Fd (3) over barm, and the samples, which were calcined at 800 degrees C with slow cooling and reannealing at 600 degrees C, demonstrated an ordered structure of P4(3)32. The sample with a disordered structure exhibited a better electrochemical performance than the sample with an ordered structure. The disordered sample produced at phi = 0.5 presented a discharge capacity of 130.73 mA h g(-1) and a capacity retention of 98.43% after 100 cycles at 1 C. Even at a higher current rate of 3 C, the sample still showed a high discharge capacity of 117.79 mA h g(-1) and a capacity retention efficiency of 97.63% after 300 cycles.

High-voltage LiNi0.5Mn1.5O4 cathode materials were synthesized using urea-based solution combustion synthesis combined with a calcination treatment. The morphology and particle size distribution of the products were considerably dependent on the amount of urea fuel. The electrochemical characterization illustrated that the sample that was produced with a fuel ratio of phi = 0.5 had a homogenous particle size distribution of approximately 8 mu m, and showed the best cycling and rate performance. LiNi0.5Mn1.5O4 with two different structures of disordered Fd (3) over barm and ordered P4(3)32 were obtained by controlling the calcination process. The samples, which were calcined at 800 degrees C with fast cooling, presented a disordered structure of Fd (3) over barm, and the samples, which were calcined at 800 degrees C with slow cooling and reannealing at 600 degrees C, demonstrated an ordered structure of P4(3)32. The sample with a disordered structure exhibited a better electrochemical performance than the sample with an ordered structure. The disordered sample produced at phi = 0.5 presented a discharge capacity of 130.73 mA h g(-1) and a capacity retention of 98.43% after 100 cycles at 1 C. Even at a higher current rate of 3 C, the sample still showed a high discharge capacity of 117.79 mA h g(-1) and a capacity retention efficiency of 97.63% after 300 cycles.

Drugs that inhibit insulin-like growth factor 1 (IGFI) receptor IGFIR were encouraging in early trials, but predictive biomarkers were lacking and the drugs provided insufficient benefit in unselected patients. In this study, we used genetic screening and downstream validation to identify the WNT pathway element DVL3 as a mediator of resistance to IGFIR inhibition. Sensitivity to IGFIR inhibition was enhanced specifically in vitro and in vivo by genetic or pharmacologic blockade of DVL3. In breast and prostate cancer cells, sensitization tracked with enhanced MEK-ERK activation and relied upon MEK activity and DVL3 expression. Mechanistic investigations showed that DVL3 is present in an adaptor complex that links IGFIR to RAS, which includes Shc, growth factor receptor-bound-2 (Grb2), son-of-sevenless (SOS), and the tumor suppressor DAB2. Dual DVL and DAB2 blockade synergized in activating ERKs and sensitizing cells to IGFIR inhibition, suggesting a nonredundant role for DVL3 in the Shc-Grb2-SOS complex. Clinically, tumors that responded to IGFIR inhibition contained relatively lower levels of DVL3 protein than resistant tumors, and DVL3 levels in tumors correlated inversely with progression-free survival in patients treated with IGFIR antibodies. Because IGFIR does not contain activating mutations analogous to EGFR variants associated with response to EGFR inhibitors, we suggest that IGF signaling achieves an equivalent integration at the postreceptor level through adaptor protein complexes, influencing cellular dependence on the IGF axis and identifying a patient population with potential to benefit from IGFIR inhibition.

Drugs that inhibit insulin-like growth factor 1 (IGFI) receptor IGFIR were encouraging in early trials, but predictive biomarkers were lacking and the drugs provided insufficient benefit in unselected patients. In this study, we used genetic screening and downstream validation to identify the WNT pathway element DVL3 as a mediator of resistance to IGFIR inhibition. Sensitivity to IGFIR inhibition was enhanced specifically in vitro and in vivo by genetic or pharmacologic blockade of DVL3. In breast and prostate cancer cells, sensitization tracked with enhanced MEK-ERK activation and relied upon MEK activity and DVL3 expression. Mechanistic investigations showed that DVL3 is present in an adaptor complex that links IGFIR to RAS, which includes Shc, growth factor receptor-bound-2 (Grb2), son-of-sevenless (SOS), and the tumor suppressor DAB2. Dual DVL and DAB2 blockade synergized in activating ERKs and sensitizing cells to IGFIR inhibition, suggesting a nonredundant role for DVL3 in the Shc-Grb2-SOS complex. Clinically, tumors that responded to IGFIR inhibition contained relatively lower levels of DVL3 protein than resistant tumors, and DVL3 levels in tumors correlated inversely with progression-free survival in patients treated with IGFIR antibodies. Because IGFIR does not contain activating mutations analogous to EGFR variants associated with response to EGFR inhibitors, we suggest that IGF signaling achieves an equivalent integration at the postreceptor level through adaptor protein complexes, influencing cellular dependence on the IGF axis and identifying a patient population with potential to benefit from IGFIR inhibition.

ARKIVOC: vol. 2007, no. 12, (issn) 1551-7012, (dlps) 5550190.0008.c02, This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 License. Please contact mpub-help@umich.edu to use this work in a way not covered by the license.

The purpose of this investigation was to study fundamentally the difference in structure of aluminum phosphates synthesized in various mediums.

A boehmite deposit has been discovered whose ore grade of 77.09 wt% Al2O3 is the highest ever recorded in China. Calcining at 650 degrees C for 0.5-1 hr increased the mineral's specific surface area to 207.71 m3/g by transforming it into gamma-Al2O3, giving it the capacity to reduce fluorine in groundwater from 6.0 to 0.75 mg/l at pH 6.5 and from 5.8 to 0.40 mg/l at pH 5.43., A boehmite deposit has been discovered whose ore grade of 77.09 wt% Al2O3 is the highest ever recorded in China. Calcining at 650 degrees C for 0.5-1 hr increased the mineral's specific surface area to 207.71 m3/g by transforming it into gamma-Al2O3, giving it the capacity to reduce fluorine in groundwater from 6.0 to 0.75 mg/l at pH 6.5 and from 5.8 to 0.40 mg/l at pH 5.43.

The laser heated pedestal growth technique has been successfully employed to grow pure and doped sapphire crystal fibres for characterisation as suitable sensor materials. Source materials used were polycrystalline and crystalline sapphire rods while fibres with typical diameters in the range 80 - 170 mm were grown. Pure sapphire fibres, both a- and c-axis, were found to grow easily with no complications such as melt instability. C-axis fibre growth was readily initiated while a-axis fibres required an appropriate a-axis oriented seed crystal. Dip-coating has been used to prepare suitably coated sapphire source rods for growth into doped fibres. Doped fibres grown included Cr3+:, Er3+:, Er3+:Yb3+: and Yb3+:Er3+:Al2O3. Er3+:Yb3+:Al2O3 fibres have been prepared with approximately equal concentration of both dopants while a 10:1 Yb3+ to Er3+ concentration ratio was used for preparing Yb3+:Er3+:Al2O3 fibres. Ruby fibres were also found to grow easily although brownish-green deposits have been observed on some of these fibres. Large transmission losses have been found in fibres with these deposits. Acid cleaning was not effective in removing these deposits, suggesting that they have diffused beneath the surface of the fibres. This was attributed to the condensation of chromium oxide on the fibre surface during growth. Growth of rare earth-doped fibres was initially problematic due to the constant breaking-off of the crystallising fibres from the melt. This was thought to be due to the flexibility of the small diameter source fibres used as well as the high concentration levels of doping. Replacing these small fibres with larger source rods thus permitted RE-doped fibres with relatively good optical quality to be grown. Fibres were grown with typical growth rates of 0.5 - 1 mm/min.

The laser heated pedestal growth technique has been successfully employed to grow pure and doped sapphire crystal fibres for characterisation as suitable sensor materials. Source materials used were polycrystalline and crystalline sapphire rods while fibres with typical diameters in the range 80 - 170 mm were grown. Pure sapphire fibres, both a- and c-axis, were found to grow easily with no complications such as melt instability. C-axis fibre growth was readily initiated while a-axis fibres required an appropriate a-axis oriented seed crystal. Dip-coating has been used to prepare suitably coated sapphire source rods for growth into doped fibres. Doped fibres grown included Cr3+:, Er3+:, Er3+:Yb3+: and Yb3+:Er3+:Al2O3. Er3+:Yb3+:Al2O3 fibres have been prepared with approximately equal concentration of both dopants while a 10:1 Yb3+ to Er3+ concentration ratio was used for preparing Yb3+:Er3+:Al2O3 fibres. Ruby fibres were also found to grow easily although brownish-green deposits have been observed on some of these fibres. Large transmission losses have been found in fibres with these deposits. Acid cleaning was not effective in removing these deposits, suggesting that they have diffused beneath the surface of the fibres. This was attributed to the condensation of chromium oxide on the fibre surface during growth. Growth of rare earth-doped fibres was initially problematic due to the constant breaking-off of the crystallising fibres from the melt. This was thought to be due to the flexibility of the small diameter source fibres used as well as the high concentration levels of doping. Replacing these small fibres with larger source rods thus permitted RE-doped fibres with relatively good optical quality to be grown. Fibres were grown with typical growth rates of 0.5 - 1 mm/min.