Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatial patterns of white matter hyperintensities: a systematic review

Background White matter hyperintensities are an important marker of cerebral small vessel disease. This disease burden is commonly described as hyperintense areas in the cerebral white matter, as seen on T2-weighted fluid attenuated inversion recovery magnetic resonance imaging data. Studies have demonstrated associations with various cognitive impairments, neurological diseases, and neuropathologies, as well as clinical and risk factors, such as age, sex, and hypertension. Due to their heterogeneous appearance in location and size, studies have started to investigate spatial distributions and patterns, beyond summarizing this cerebrovascular disease burden in a single metric–its volume. Here, we review the evidence of association of white matter hyperintensity spatial patterns with its risk factors and clinical diagnoses. Design/methods We performed a systematic review in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) Statement. We used the standards for reporting vascular changes on neuroimaging criteria to construct a search string for literature search on PubMed. Studies written in English from the earliest records available until January 31st, 2023, were eligible for inclusion if they reported on spatial patterns of white matter hyperintensities of presumed vascular origin. Results A total of 380 studies were identified by the initial literature search, of which 41 studies satisfied the inclusion criteria. These studies included cohorts based on mild cognitive impairment (15/41), Alzheimer’s disease (14/41), Dementia (5/41), Parkinson’s disease (3/41), and subjective cognitive decline (2/41). Additionally, 6 of 41 studies investigated cognitively normal, older cohorts, two of which were population-based, or other clinical findings such as acute ischemic stroke or reduced cardiac output. Cohorts ranged from 32 to 882 patients/participants [median cohort size 191.5 and 51.6% female (range: 17.9–81.3%)]. The studies included in this review have identified spatial heterogeneity of WMHs with various impairments, diseases, and pathologies as well as with sex and (cerebro)vascular risk factors. Conclusion The results show that studying white matter hyperintensities on a more granular level might give a deeper understanding of the underlying neuropathology and their effects. This motivates further studies examining the spatial patterns of white matter hyperintensities.
Genetic analysis of VCP variants in a Turkish dementia cohort

Valosin-containing protein (VCP) mutations are causative for multisystem proteinopathy, a disease characterized by variable phenotypes including inclusion body myopathy, Paget's disease of bone, and frontotemporal dementia. More recent reports identified VCP variants as the cause of other neurodegenerative diseases, such as Parkinson's disease and vacuolar tauopathy. We screened a Turkish dementia cohort for VCP variants in order to assess their role as the cause of disease in this population. One hundred and forty six Turkish dementia patients were examined clinically and were analyzed for VCP coding variants using whole-exome sequencing. Familial samples were collected and analyzed in order to test for segregation of candidate variants. We identified a heterozygous missense VCP p.Ile216Met variant segregating with disease in a family where the proband was diagnosed with prodromal dementia with Lewy bodies. Our report potentially extends the spectrum of phenotypes attributed to VCP mutations to include prodromal dementia with Lewy bodies.
Large-Eddy Simulations on Indoor/Outdoor Air Quality Relationship in an Isolated Urban Building

The airflow, pollutant dispersion and penetration of outdoor pollutants indoor in an isolated urban building are investigated computationally. The computation involves solving the two-dimensional Navier — Stokes equations using large eddy simulations based on the Smagorinsky subgrid scale model. The simulations involve investigations of the phenomena of airflow and pollutant dispersion in both indoor and outdoor environments under different Reynolds numbers with distinct combinations of building height, floor height, and building width. Pollutants originate from outdoor, located at the datum level of the windward side of the building. The objective is to study how outdoor pollutants penetrate indoor and relate this pattern to different building geometric configurations. The gradual increase in Reynolds number significantly favors pollutant transportation into the indoor environment and thus eventually changes the indoor/outdoor (IO) air ratio. Moreover, the value of the IO air ratio is particularly found to be highly affected by building height due to the capability of climbing over and escaping from the roof of the building. Results also show that the IO air ratio is dependent on the position of the sampling, which has been ignored in many previous experimental works. The research work poses important questions of indoor air quality as well as field measurements of the IO parameter.
The local metric dimension of a graph

For an ordered set $W= \{w_1,w_2,\ldots ,w_k\}$ of $k$ distinct vertices in a nontrivial connected graph $G$, the metric code of a vertex $v$ of $G$ with respect to $W$ is the $k$-vector \[ \mathop {\rm code}(v)= ( d(v,w_1),d(v,w_2),\cdots ,d(v,w_k) ) \] where $d(v,w_i)$ is the distance between $v$ and $w_i$ for $1\le i\le k$. The set $W$ is a local metric set of $G$ if $\mathop {\rm code}(u)\ne \mathop {\rm code}(v)$ for every pair $u,v$ of adjacent vertices of $G$. The minimum positive integer $k$ for which $G$ has a local metric $k$-set is the local metric dimension $\mathop {\rm lmd}(G)$ of $G$. A local metric set of $G$ of cardinality $\mathop {\rm lmd}(G)$ is a local metric basis of $G$. We characterize all nontrivial connected graphs of order $n$ having local metric dimension $1$, $n-2$, or $n-1$ and establish sharp bounds for the local metric dimension of a graph in terms of well-known graphical parameters. Several realization results are presented along with other results on the number of local metric bases of a connected graph.
On New Weighted Ostrowski Type inequalities Involving Integral Means over End Intervals and Application

The aim of this paper is to establish new inequalities using weight function which generalizes the inequalities of Dragomir, Wang and Cerone. In this article we obtain bounds for the deviation of a function from a combination of weighted integral means over the end intervals covering the entire interval. A variety of earlier results are recaptured as particular instances of the current development. Applications for cumulative distribution function is also discussed.
Necessary and sufficient conditions for non-overshooting step responses for LTI systems

In this paper we consider a class of systems for which a necessary and sufficient condition is given for the determination of whether or not its impulse response starting from zero initial conditions is nonnegative. The class of plants considered is SISO, LTI, stable and strictly proper. We show that the system step response is nonovershooting by converting it to a root finding problem of a polynomial. The derived necessary and sufficient condition can then be used to develop other sufficiency conditions for more general plants where the poles need not satisfy the special form given above. Further we derive a necessary and sufficient condition guaranteeing a nonovershooting step response for another class of SISO, LTI stable and strictly proper systems. The poles of this class of systems are assumed real and of the form /spl lambda//sub i/ = i/spl lambda/, /spl lambda/ < 0, i = 1, 2,. , n. The conditions should be useful in practical control system design where a nonovershooting step response is desirable. In addition necessary and sufficient conditions are derived for a SISO plant with a complex conjugate pole pair. The latter result is then used to state conditions for a third order plant with no zeros.
Singularities and noise discrimination with wavelets

One can detect and characterize the singularities of a signal from the evolution of the wavelet transform coefficients across scales. The authors discriminate signal information from noise by using some prior knowledge of the properties of singularities. The wavelet transform of the signal is processed in order to remove the singularities created by the noise. The authors restore a sharp signal where part of the noise has been suppressed. Examples in one and two dimensions are shown. <<ETX>>
Relativistic X-band BWO with 3-GW output power

Results from a study of a relativistic X-band backward-wave oscillator (RBWO) with 3-GW output microwave power are presented. The RBWO was driven by the high-current electron accelerator SINUS-7. The dependence of radiated microwave pulse duration on microwave power was obtained. Pulse shortening occurring at the higher power levels is probably attributable to explosive electron emission from the slow wave structure (SWS). An increase in the cross section of the electrodynamic structure seems to be a way to increase the microwave pulse duration. Experimental results from a moderately oversized X-band RBWO using a resonance reflector are described. This tube can be operated with a low external magnetic field.
Two-photon phosphorescence lifetime microscopy (2PLM) for high resolution imaging of oxygen

We present a new method for imaging of oxygen in biological samples with micron-scale resolution and threedimensional capability. Our technique combines phosphorescence quenching with multiphoton laser scanning microscopy. It is termed two-photon phosphorescence lifetime microscopy (2PLM). 2PLM is made possible due to specially designed dendritic probes, in which phosphorescence of metalloporphyrins upon two-photon excitation is enhanced by intramolecular Förster-type energy transfer from two-photon antennae chromophores, located in the same probe molecule. Oxygen sensitivity of the probes is regulated by dendritic encapsulation of the core metalloporphyrin, while peripheral PEG groups on the dendrimer isolate the probes from contacts with biological macromolecules (e.g. proteins, nucleic acids etc) in the environment. Instrumentation and resolution of the method are discussed along with approaches to intracellular delivery of the probes. 2PLM was validated in pilot imaging experiments and used to obtain depth-resolved high-resolution oxygen maps in vivo in the brain.
Research Progress of Tumor Microenvironment Targeted Therapy for Clear Cell Renal Cell Carcinoma

Renal clear cell carcinoma (ccRCC) and the tumor microenvironment (TME) influence each other, leading to the tumor microenvironment that can guide the corresponding treatment. With the deepening of research, some treatment options have achieved good results, such as tyrosine kinase inhibitors, immune checkpoint inhibitors, and so on. As the link between TME and malignancy is constantly discovered, more targeted studies on different components of TME are increasing, and this targeted therapy is a new method for treating ccRCC, and also a current research hotspot. This review summarizes the characteristics of the ccRCC tumor microenvironment, the outcomes of different treatments, and some potential targets.
SU-8 photoresist as material of optical passive components integrated with analytical microsystems for real-time polymerase chain reaction

Rapid development of analytical microsystems, also often called as labs-on-a-chip and used to perform various chemical and biochemical analysis with nano- and pico-volumes of the sample, has been observed for almost two decades. Successful application of analytical microsystems in medical and veterinary practices is relevant to many factors but one of them is low price of the disposable microsystem – often in the form of a chip. The chips are made of cheap materials, for example, polymers. One of such material is a negative photoresist SU-8. It is characterized by biocompatibility and possibility of easy fabrication of various three-dimensional fluidic microstructures. Moreover, SU-8 is transparent for visible light. It makes SU-8 attractive material for labs-on-a-chip dedicated for genetic material analysis by real-time polymerase chain reaction (PCR). In this paper, we present the results of investigations of the influence of PCR-like temperature profiling on the transmittance spectra. The autofluorescence effect of SU-8 illuminated with various lasers has also been investigated as one of the factors limiting sensitive fluorescence readout. The results obtained showed that SU-8 can be successfully applied as labs-on-a-chip material but, due to high SU-8 autofluorescence, red-line fluorochromes are preferred when high-sensitivity fluorescence detection is required.
Joint fractional transform correlator based on structured light coding

A new method for 3-D object recognition is proposed. The method combines structured light coding with the joint fractional transform correlator (JFrTC). When projecting sinusoidal grating fringes onto the surface of 3-D objects, the fringes are distorted due to the height of the objects. Then the distorted fringe patterns are regarded as the joint input image used for correlation recognition. Simultaneously, to achieve JFrTC, we can replace either (or both) Fourier transforms in the joint transform correlator (JTC) by a fractional Fourier transform. Four architectures of JFrTC with the distorted fringe pattern and four JFrTC with the intensity map are analyzed in detail. By comparing these different structures, a JFrTC with distorted fringe patterns, especially for the FrT-FT architecture, is suggested to improve the discernment performance, to more decrease the widths of the correlation peaks, and to flexibly change the intensity and position of correlation peaks. Both mathematical analysis and computer simulation results are presented in support of the proposed idea.
Computing Reachable Simulations

We study the problem of computing the reachable principals of simulation preorder and the reachable blocks of simulation equivalence. Following a theoretical investigation of the decidability and complexity aspects of this problem, which in particular highlights a stark contrast with the already settled case of bisimulation, we design algorithms to solve this problem by leveraging the idea of interleaving reachability and simulation computation while possibly avoiding the computation of all the reachable states or the whole simulation preorder. In particular, we put forward a symbolic algorithm processing state partitions and, in turn, relations between their blocks, which is suited for processing infinite state systems.
MCAL: Minimum Cost Human-Machine Active Labeling

Today, ground-truth generation uses data sets annotated by cloud-based annotation services. These services rely on human annotation, which can be prohibitively expensive. In this paper, we consider the problem of hybrid human-machine labeling, which trains a classifier to accurately auto-label part of the data set. However, training the classifier can be expensive too. We propose an iterative approach that minimizes total overall cost by, at each step, jointly determining which samples to label using humans and which to label using the trained classifier. We validate our approach on well known public data sets such as Fashion-MNIST, CIFAR-10, CIFAR-100, and ImageNet. In some cases, our approach has 6x lower overall cost relative to human labeling the entire data set, and is always cheaper than the cheapest competing strategy.
How Workflow Engines Should Talk to Resource Managers: A Proposal for a Common Workflow Scheduling Interface

Scientific workflow management systems (SWMSs) and resource managers together ensure that tasks are scheduled on provisioned resources so that all dependencies are obeyed, and some optimization goal, such as makespan minimization, is achieved. In practice, however, there is no clear separation of scheduling responsibilities between an SWMS and a resource manager because there exists no agreed-upon separation of concerns between their different components. This has two consequences. First, the lack of a standardized API to exchange scheduling information between SWMSs and resource managers hinders portability. It incurs costly adaptations when a component should be replaced by a different one (e.g., an SWMS with another SWMS on the same resource manager). Second, due to overlapping functionalities, current installations often actually have two schedulers, both making partial scheduling decisions under incomplete information, leading to suboptimal workflow scheduling. In this paper, we propose a simple REST interface between SWMSs and resource managers, which allows any SWMS to pass dynamic workflow information to a resource manager, enabling maximally informed scheduling decisions. We provide an implementation of this API as an example, using Nextflow as an SWMS and Kubernetes as a resource manager. Our experiments with nine real-world workflows show that this strategy reduces makespan by up to 25.1% and 10.8% on average compared to the standard Nextflow/Kubernetes configuration. Furthermore, a more widespread implementation of this API would enable leaner code bases, a simpler exchange of components of workflow systems, and a unified place to implement new scheduling algorithms.
Quantum key distribution with post-processing driven by physical unclonable functions

Quantum key distribution protocols allow two honest distant parties to establish a common truly random secret key in the presence of powerful adversaries, provided that the two users share a short secret key beforehand. This pre-shared secret key is used mainly for authentication purposes in the post-processing of classical data that have been obtained during the quantum communication stage, and it prevents a man-in-the-middle attack. The necessity of a pre-shared key is usually considered to be the main drawback of quantum key distribution protocols, and it becomes even stronger for large networks involving more than two users. Here, we discuss the conditions under which physical unclonable functions can be integrated in currently available quantum key distribution systems in order to facilitate the generation and the distribution of the necessary pre-shared key with the smallest possible cost in the security of the systems. Moreover, the integration of physical unclonable functions in quantum key distribution networks allows for real-time authentication of the devices that are connected to the network.
'Aariz: A Benchmark Dataset for Automatic Cephalometric Landmark Detection and CVM Stage Classification

The accurate identification and precise localization of cephalometric landmarks enable the classification and quantification of anatomical abnormalities. The traditional way of marking cephalometric landmarks on lateral cephalograms is a monotonous and time-consuming job. Endeavours to develop automated landmark detection systems have persistently been made, however, they are inadequate for orthodontic applications due to unavailability of a reliable dataset. We proposed a new state-of-the-art dataset to facilitate the development of robust AI solutions for quantitative morphometric analysis. The dataset includes 1000 lateral cephalometric radiographs (LCRs) obtained from 7 different radiographic imaging devices with varying resolutions, making it the most diverse and comprehensive cephalometric dataset to date. The clinical experts of our team meticulously annotated each radiograph with 29 cephalometric landmarks, including the most significant soft tissue landmarks ever marked in any publicly available dataset. Additionally, our experts also labelled the cervical vertebral maturation (CVM) stage of the patient in a radiograph, making this dataset the first standard resource for CVM classification. We believe that this dataset will be instrumental in the development of reliable automated landmark detection frameworks for use in orthodontics and beyond.
Carbon nanotubes on Jurkat cells: effects on cell viability and plasma membrane potential

Carbon nanotubes (CNT) are one of the most novel attractive materials in nanotechnology for their potential multiple applications, including in the biomedical fields. The biocompatibility and toxicity of these novel nanomaterials are still largely unknown and a systematic study on biological interference is essential. We present a toxicological assessment of different types of CNT on the human tumor lymphocytic Jurkat cells. The carbon nanomaterials examined differ in preparation, size, contaminants and morphology: (1) CNT composed of MWCNT+SWCNT, with no metal contaminants; (2) MWCNT and (3) SWCNT, both with metal contaminants; (4) carbon black as control. The results indicate that CNT exert a dose- and time-dependent cytotoxic effect on Jurkat cells, inducing apoptotic cell death, accelerating the transition to secondary necrosis and increasing the extent of apoptosis induced by damaging agents; interestingly, CNT induce a plasma membrane hyperpolarization. These alterations are produced by all types of CNT, but contaminants and/or the size modulate the extent of such effects. Thus CNT deeply affect cell behavior, suggesting that they might play a role in inflammation, and recommending greater attention in terms of evaluation of exposure risks.
A guide to regression discontinuity designs in medical applications

We present a practical guide for the analysis of regression discontinuity (RD) designs in biomedical contexts. We begin by introducing key concepts, assumptions, and estimands within both the continuity‐based framework and the local randomization framework. We then discuss modern estimation and inference methods within both frameworks, including approaches for bandwidth or local neighborhood selection, optimal treatment effect point estimation, and robust bias‐corrected inference methods for uncertainty quantification. We also overview empirical falsification tests that can be used to support key assumptions. Our discussion focuses on two particular features that are relevant in biomedical research: (i) fuzzy RD designs, which often arise when therapeutic treatments are based on clinical guidelines, but patients with scores near the cutoff are treated contrary to the assignment rule; and (ii) RD designs with discrete scores, which are ubiquitous in biomedical applications. We illustrate our discussion with three empirical applications: the effect CD4 guidelines for anti‐retroviral therapy on retention of HIV patients in South Africa, the effect of genetic guidelines for chemotherapy on breast cancer recurrence in the United States, and the effects of age‐based patient cost‐sharing on healthcare utilization in Taiwan. Complete replication materials employing publicly available data and statistical software in Python, R and Stata are provided, offering researchers all necessary tools to conduct an RD analysis.