Miracle-dz/UniFAR-FTUs huggingface dataset:
Photonics Scanning Pentaprism System for the Integrated Inspection of Large-Aperture Telescopes

To improve their spatial resolution and detection capabilities, future ground-based optical telescopes will have a size of 30 m, and the aperture of space telescopes will be increased to 10 m. Such large optical systems necessitate the development of large integrated testing equipment. In this study, spectrum and system alignment measurements and wavefront quality checking were performed using the sub-aperture detection method and a fiber-connected Photonics Scanning Pentaprism (PSP). First, the system was aligned using an optical truss, ensuring that the optical axis was properly positioned. Second, using a sub-aperture light beam though the entrance pupil, light spots were formed on the focal plane and transmitted to the spectrometer via fibers to obtain the corresponding spectral components. Then, by taking measurements at different system positions, a full-aperture spectrum response could be reached. Lastly, by photon-integrated interference on the focal plane, intensity interference fringes could be projected at the entrance pupil of the system. And the wavefront quality of the system could be verified by observing the fringe deformation. The measurement accuracy of the optical axis of the system is better than 2 mrad. The spectral measurement accuracy was better than 5%, and the wavefront measurement accuracy surpassed 0.1 wavelengths (1 wavelength = 633 nm). This study effectively enhanced the detection and in situ calibration capabilities of large telescope systems, ensuring that the performance requirements can be met in the design of future telescopes.
Submonolayer and multilayer growth of titaniumoxide-phthalocyanine on Ag(111)

For exploiting the full potential of organic materials for future organic electronic devices it is of crucial importance to understand structural and electronic properties of metal-organic interfaces and adsorbate systems, in particular electronic interactions and growth mechanisms. Phthalocyanine molecules represent one class of materials which are very frequently discussed in this context. They feature an appealing tunability in terms of structural, electronic and magnetic properties, simply by exchanging the central (metal) atom or group of atoms. Here we present a comprehensive study of one of the model systems in this field, TiOPc on Ag(111). We discuss structure formation and growth from submonolayer to multilayer films, based on results obtained by electron diffraction, scanning tunneling microscopy, electron energy loss spectroscopy, x-ray standing waves, photoelectron spectroscopy and pair potential calculations. Similar to related metal-phthalocyanine adsorbate systems we find three distinct phases in the submonolayer regime, a disordered gas-like ‘g-phase’, a commensurate ‘c2-phase’ at low temperature, and a ‘p.o. l. -phase’ consisting of a series of point-on-line structures with continuously shrinking unit cells. For the latter a uniform TiO-up configuration (Ti–O group pointing towards vacuum) was found. Hence, the first-layer molecules form a strong dipole layer, the dipole moment of which is compensated by molecules adsorbing in the second layer at hollow-sites in TiO-down geometry (Ti-O group pointing towards the surface). The Coulomb interaction between the dipole moments in the first and second layer stabilizes this bilayer structure and causes a bilayer-by-bilayer growth mode of molecular films above a thickness of 2 ML. We report the structural properties (vertical adsorption heights, inter-layer distances, inplane orientations and positions) of the molecules in all phases in detail, and discuss the effect of inelastic dynamical charge transfer. Our results contribute to a comprehensive understanding of this interesting adsorbate system and, in comparison with earlier studies on CuPc, H2Pc and SnPc on Ag(111), we shine new light on the interesting interplay of molecule-molecule and molecule-substrate interactions.
Modeling Hierarchical Seasonality Through Low-Rank Tensor Decompositions in Time Series Analysis

Accurately representing periodic behavior is a frequently encountered challenge in modeling time series. This is especially true for observations where multiple, nested seasonalities are present, which is often encountered in data that pertain to collective human activity. In this work, we propose a new method that models seasonality through the multilinear representations that characterize low-rank tensor decompositions. We show that the tensor formalism accurately describes multiple nested periodic patterns, and well-known tensor decompositions can be used to parametrize cyclical patterns, leading to superior generalization and parameter efficiency. Furthermore, we develop a Bayesian variant of our approach which facilitates extraction of these seasonal patterns in an interpretable fashion from large-scale datasets, providing insight into the underlying dynamics that create such emergent behavior. We lastly test our method in missing data imputation, where the results show that our method couples interpretability with accuracy in time series analysis.
Relationships between serum Klotho concentrations and cognitive performance among older chronic kidney disease patients with albuminuria in NHANES 2011-2014

Background The potential relationship between Klotho and cognitive function is limited and controversial. This study aimed to quantify the association of Klotho and cognitive impairment in chronic kidney disease (CKD) patients with albuminuria. Methods Serum Klotho was measured by enzyme-linked immunosorbent assay. Patients with urine albumin to creatinine ratio (UACR) > 30mg/g from the National Health and Nutrition Survey (NHANES) 2011-2014 were divided into 4 groups according to the quartile of Klotho. Cognitive function was examined using the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), Digit Symbol Substitution Test (DSST), and Animal Fluency Test. The relationship between Klotho and cognitive function was analyzed by multivariable regression and subgroup analysis. Results Among 368 CKD patients with albuminuria, we found that Klotho was negatively associated with creatinine, and positively associated with hemoglobin, and estimated glomerular filtration rate. No significant linear relationship was showed between Klotho (as a continuous variable) and cognitive function. When regarded Klotho as a category variable, patients in the quartile 3 group were at a better cognitive performance for CEARD-word learning subset and DSST, especially in the CKD patients with 30 mg/g < UACR <300 mg/g, but not in participants with UACR > 300 mg/g. Conclusions The increased Klotho was associated with an increased cognitive function in CKD patients with microalbuminuria. Further studies are needed to demonstrate whether Klotho may be a beneficial biomarker of cognitive health and neurodegeneration.
Computing the area-minimizing surface by the Allen-Cahn equation with the fixed boundary

The Allen-Cahn equation is a famous nonlinear reaction-diffusion equation used to study geometric motion and minimal hypersurfaces. This link has been scrutinized to construct minimal surfaces for many years. The shape of soap film is very interesting, and it can stimulate mathematical inspirations since it explains curvatures and equilibrium shapes in nature. There are many interesting ways to create area-minimizing surfaces with the boundaries, called frame boundaries. However, dealing with surface's ends (boundaries) numerically is not easy for constructing surfaces. This paper presents a mathematical formulation and numerical construction of area-minimizing surfaces, also known as minimal surfaces. We use differential geometry knowledge for numerical verification. The proposed numerical scheme involves fixed frame boundary conditions in the Laplacian operator. We treat the Laplacian with the constraint implicitly and explicitly solve the nonlinear free energy term. This approach ensures stable and efficient construction of area-minimizing surfaces with frame boundaries. In the numerical aspect, we suggest the construction of minimal surfaces by illustrating two classical examples, which are Scherk's minimal surface and catenoid. Both examples have the frame boundaries. Scherk's first surface is a doubly periodic, complete and properly embedded one with parallel ends. The catenoid is formed between two coaxial circular rings and is classified mathematically as the only properly embedded minimal surface with two ends and finite curvature. To be specific, we deal with two different frame boundaries, right angle frame and round frame boundaries, via two examples, Scherk's surface and catenoid.
Comparison between Morphological Aided Cytochemical Stains (Sudan Black B, PAS) and Flowcytometry in Diagnosis and Classification of Acute Leukemia’s .

The diagnosis of AL undergoes a stepwise approach. First the distinction of an acute leukemia from other hematological diseases . Second is differentiating AML and ALL . The third is the classification of AML and ALL into categories that define treatment and prognosis. The Aim is to assess the importance of morphologic and cytochemical diagnosis in comparison with flowcytometric diagnosis in acute leukemia. A total of 79 bone marrow specimens were diagnosed as acute leukemia based on morphology, cytochemistry and by flowcytometry. The results based on morphology are 58.21% diagnosed as AML, 37.9 % diagnosed as ALL and 3.79% as AUL. In AML, SBB was positive in 78.2 % of cases ,sub classified from M1 to M4, while 21.7% had negative SBB subclassified as M5a, M5b and M6. PAS were negative in all AML cases. In ALL, PAS was positive in 60% of cases and SBB was negative in all cases. AUL cases had negative results in both stains. Flowcytometric results are: AML; M0 (2.53%), M1(2.53%), M2 (24.05%), M3 (5.06%), M3v (5.06%), M4 (8.86%), M5a (7.59%), M5b (1.27%), M6 (2.53%) and M7 (1.27%). ALL ; LB precursor (26.58%), LB common (6.33%), LT type (3.8%) and L3 in (2.53%). SBB is still an important and cheap method in diagnosis and classification of AML, while PAS can diagnose 60% of ALL. FCA not only helps in confirming morphologic diagnosis in AL but also helps in assigning specific lineage.
Text Messages Exchanged Between Individuals With Opioid Use Disorder and Their mHealth e-Coaches: Content Analysis Study

Background Opioid use disorder (OUD) has affected 2.2 million people in the United States. About 7.2 million people reported using illicit drugs in 2019, which contributed to over 70,000 overdose deaths. SMS text messaging interventions have been shown to be effective in OUD recovery. However, the interpersonal communication between individuals in OUD treatment and a support team on digital platforms has not been well examined. Objective This study aims to understand the communication between participants undergoing OUD recovery and their e-coaches by examining the SMS text messages exchanged from the lens of social support and the issues related to OUD treatment. Methods A content analysis of messages exchanged between individuals recovering from OUD and members of a support team was conducted. Participants were enrolled in a mobile health intervention titled “uMAT-R,” a primary feature of which is the ability for patients to instantly connect with a recovery support staff or an “e-coach” via in-app messaging. Our team analyzed dyadic text-based messages of over 12 months. In total, 70 participants’ messages and 1196 unique messages were analyzed using a social support framework and OUD recovery topics. Results Out of 70 participants, 44 (63%) were between the ages of 31 and 50 years, 47 (67%) were female, 41 (59%) were Caucasian, and 42 (60%) reported living in unstable housing conditions. An average of 17 (SD 16.05) messages were exchanged between each participant and their e-coach. Out of 1196 messages, 64% (n=766) messages were sent by e-coaches and 36% (n=430) by participants. Messages of emotional support occurred the most, with 196 occurrences (n=9, 0.8%) and e-coaches (n=187, 15.6%). Messages of material support had 110 occurrences (participants: n=8, 0.7%; e-coaches: n=102, 8.5%). With OUD recovery topics, opioid use risk factors appeared in most (n=72) occurrences (patient: n=66, 5.5%; e-coach: n=6, 0.5%), followed by a message of avoidance of drug use 3.9% (n=47), which occurred mainly from participants. Depression was correlated with messages of social support (r=0.27; P=.02). Conclusions Individuals with OUD who had mobile health needs tended to engage in instant messaging with the recovery support staff. Participants who are engaged in messaging often engage in conversations around risk factors and avoidance of drug use. Instant messaging services can be instrumental in providing the social and educational support needs of individuals recovering from OUD.
Frequency-sparse optimal quantum control

A new class of cost functionals for optimal control of quantum systems which produces controls which are sparse in frequency and smooth in time is proposed. This is achieved by penalizing a suitable time-frequency representation of the control field, rather than the control field itself, and by employing norms which are of $L^1$ or measure form with respect to frequency but smooth with respect to time. We prove existence of optimal controls for the resulting nonsmooth optimization problem, derive necessary optimality conditions, and rigorously establish the frequency-sparsity of the optimizers. More precisely, we show that the time-frequency representation of the control field, which a priori admits a continuum of frequencies, is supported on only finitely many frequencies. These results cover important systems of physical interest, including (infinite-dimensional) Schrodinger dynamics on multiple potential energy surfaces as arising in laser control of chemical reactions. Numerical simulations confirm that the optimal controls, unlike those obtained with the usual $L^2$ costs, concentrate on just a few frequencies, even in the infinite-dimensional case of laser-controlled chemical reactions.
Extending Finite-state Models of Reduplication to Tone in Thai

Languages exhibiting both tonal and reduplication processes pose a challenge for finite-state technologies. In this sense, Markowska et al. (2021) propose a combination of 2-way FSTs and multi-tape FSTs in order to simultaneously deal with total reduplication on the segmental level and independent tonal processes on the au-tosegmental level. Here, we evaluate this model for reduplication processes in Thai, which shows total reduplication both for tones and segments, and we suggest that the expressivity of 2-way FSTs is needed at both levels.
Culture and Social Norms: Development and Application of a Model for Culturally Contextualized Communication Measurement (MC 3 M)

Studies of social norms are common in the communication literature and are increasingly focused on cultural dynamics: studying co-cultural groups within national boundaries or comparing countries. Based on the review of the status quo in cross-cultural measurement development and our years of experience in conducting this research among a co-cultural group, this paper describes a Model for Culturally Contextualized Communication Measurement (MC 3 M) for intercultural and/or cross-cultural communication research. As an exemplar, we report on a program of research applying the model to develop a culturally derived measurement of social norms and the factors impacting the norm-behavior relationship for members of a unique population group (i.e., ethnically Tibetan pastoralists in Western China). The results provide preliminary evidence for the construct validity and reliability of the culturally derived measurements. The implications, bene ﬁ ts, and shortcomings of the MC 3 M model are discussed. Recommendations for advancing both conceptual and measurement re ﬁ nement in intercultural and cross-cultural communication research are provided.
Using fast visual inpainting transformers for anomaly detection

The detection and segmentation of irregularities in images is an anomaly detection problem in computer vision. An approach that is used commonly uses autoencoders trained on good images to fully reconstruct anomalous images. These reconstructions can then be used to perform detection and segmentation by mathematically comparing the original input and the reconstruction. Other solutions introduce patch inpainting as a solution for anomaly detection. One approach uses an attention-based transformer model that achieves promising results. Transformers are generally slower models and thus faster versions have been proposed. We therefore combine the inpainting solution with two types of transformers and see that a linear attention approach performs slightly better than full attention when doing detection and segmentation on the MVTec AD dataset.
The Use of a Barley-Based Well to Define Cationic Betaglucan to Study Mammalian Cell Toxicity Associated with Interactions with Biological Structures

Among potential macromolecule-based pharmaceuticals, polycations seem particularly interesting due to their proven antimicrobial properties and use as vectors in gene therapy. This makes an understanding of the mechanisms of these molecules’ interaction with living structures important, so the goal of this paper was to propose and carry out experiments that will allow us to characterize these phenomena. Of particular importance is the question of toxicity of such structures to mammalian cells and, in the work presented here, two lines, normal fibroblasts 3T3-L1 and A549 lung cancer, were used to determine this. In this work, three well-defined cationic derivatives of barley-derived betaglucans obtained in a reaction with glycidyltrimethylammonium chloride (BBGGTMAC) with different degrees of cationization (50, 70, and 100% per one glucose unit) and electrostatic charge were studied. The studies address interactions of these polymers with proteins (bovine serum proteins and BSA), nucleic acids (DNA), glycosaminoglycans (heparin), and biological membranes. The results described in this study make it possible to indicate that toxicity is most strongly influenced by interactions with biological membranes and is closely related to the electrostatic charge of the macromolecule. The presentation of this observation was the goal of this publication. This paper also shows, using fluorescently labeled variants of polymers, the penetration and impact on cell structure (only for the polymer with the highest substitution binding to cell membranes is observed) by using confocal and SEM (for the polymer with the highest degree of substitution, and the appearance of additional structures on the surface of the cell membrane is observed). The labeled polymers are also tools used together with dynamic light scattering and calorimetric titration to study their interaction with other biopolymers. As for the interactions with biological membranes, lipid Langmuir monolayers as model membrane systems were used.
Motion Planning Diffusion: Learning and Planning of Robot Motions with Diffusion Models

Learning priors on trajectory distributions can help accelerate robot motion planning optimization. Given previously successful plans, learning trajectory generative models as priors for a new planning problem is highly desirable. Prior works propose several ways on utilizing this prior to bootstrapping the motion planning problem. Either sampling the prior for initializations or using the prior distribution in a maximum-a-posterior formulation for trajectory optimization. In this work, we propose learning diffusion models as priors. We then can sample directly from the posterior trajectory distribution conditioned on task goals, by leveraging the inverse denoising process of diffusion models. Furthermore, diffusion has been recently shown to effectively encode data multi-modality in high-dimensional settings, which is particularly well-suited for large trajectory dataset. To demonstrate our method efficacy, we compare our proposed method - Motion Planning Diffusion - against several baselines in simulated planar robot and 7-dof robot arm manipulator environments. To assess the generalization capabilities of our method, we test it in environments with previously unseen obstacles. Our experiments show that diffusion models are strong priors to encode high-dimensional trajectory distributions of robot motions. https://sites.google. com/view/mp-diffusion
A diverse high-performance platform for Advanced Driver Assistance System (ADAS

Advanced driver assistance systems (ADAS) are becoming increasingly popular. ADAS applications such as lane departure warning (LDW), forward collision warning (FCW), automatic cruise control (ACC), auto emergency braking (AEB) and surround view (SV) that were present only in luxury vehicles in the past have trickled down to entry-and mid-level vehicles. Many of these applications are also mandated by safety authorities such as European New Car Assessment Program (Euro NCAP) and National Highway Traffic Safety Administration (NHTSA). In order to make these applications affordable in entry-and mid-level vehicles, it is important to have a cost-effective, yet high-performance and low-power solution. Texas Instruments (TI’s) TDA3x is an ideal platform to address these needs. In this paper we will illustrate the mapping of multiple algorithms such as SV, LDW, object detection (OD), structure from motion (SFM) and camera-monitor systems (CMS) to the TDA3x device, thereby demonstrating its computing capabilities. We also share the performance for these embedded vision applications, showing that TDA3x is an excellent high-performance device for ADAS applications.
Constraining the Active-to-Heavy-Neutrino transitional magnetic moments associated with the Z (cid:48) interactions at FASER ν .

We investigate the eﬀects of the transitional magnetic dipole moment of the active-to-heavy-neutrino associated with a new neutral gauge boson Z (cid:48) on neutrino-nucleon scattering at the For-wArd Search ExpeRiment-ν (FASER ν ). We consider the neutral-current neutrino-nucleon scattering ( νA → NA ) as the production mechanism of the heavy neutrino N at FASER ν and estimate the sensitivity reach on the magnetic moment coupling µ ν α for a range of heavy neutrino mass (1 GeV < M N < 70GeV). In this study, we consider three benchmark models, in which the heavy neutrino is coupled to L e , L µ or L τ doublet, respectively.
Directly measuring the concurrence of two-atom state via detecting coherent lights

Concurrence is an important parameter for quantifying quantum entanglement, but usually the state tomography must be determined before quantification. In this paper we propose a scheme, based on cavity-assisted atom–light interaction, to measure the concurrence of two-atom pure states and the Collins–Gisin state directly, without tomography. The concurrence of atomic states is encoded in the output coherent optical beams after interacting with cavities and the atoms therein, so the results of detection applied to the output coherent optical beams provide the concurrence data of the atomic states. This scheme provides an alternative method for directly measuring atomic entanglement by detecting coherent light, rather than measuring the atomic systems, which thus greatly simplifies the realization complexity of the direct measurement of atomic entanglement. In addition, as the cavity-assisted atom–light interaction used here is robust and scalable in realistic applications, the current scheme may be realized in the near future.