Miracle-dz/UniFAR-FTUs huggingface dataset:
Detecting low respiratory rates using myriad, low-cost sensors

: The underlying problem for two of the three most common patterns of unexpected hospital deaths (PUHD) is hypoventilation 1 . Current methods of postoperative respiratory monitoring give delayed signals and have a high false positive rate leading nurses to ignore alarms. We hypothesize there exists a combination of low cost sensors which are capable of providing real time feedback and alarms regarding obstructive sleep apnea and ventilatory depression. Such a monitor would be useful during space travel when monitoring personnel are limited following an injury or if astronauts were to be sedated during extended travel. Methods: Twenty-six subjects were recruited to participate in a study of the effects of Propofol and Remifentanil. Throughout the day, these patients were exposed to varying levels of both drugs simultaneously via target controlled infusions. These patients were attached to breathing and oxygen monitors including chest bands, pulse oximeters, nasal pressure sensors, C0 2 capnography, breathing microphones, and thermistors. The patients were then observed for types of apnea or ventilatory depression. Results: The study is currently ongoing however preliminary analyses of the data indicate multiple low cost sensors are capable of detecting respiratory rate as well as obstructive events and apnea. Conclusion: Using only a combination of low cost sensors, we can provide real time respiratory event data to nurses and practitioners. The problem for two of the three most common patterns of unexpected hospital deaths (PUHD) is hypoventilation 1 .
Deep neural networks for predicting restricted mean survival times

AVAILABILITY AND IMPLEMENTATION Restricted mean survival time (RMST) is a useful summary measurement of the time-to-event data, and it has attracted great attention for its straightforward clinical interpretation. In this article, I propose a deep neural network model that directly relates the RMST to its baseline covariates for simultaneous prediction of RSMT at multiple times. Each subject's survival time is transformed into a series of jackknife pseudo observations and then used as quantitative response variables in a deep neural network model. By using the pseudo values, a complex survival analysis is reduced to a standard regression problem, which greatly simplifies the neural network construction. By jointly modelling RMST at multiple times, the neural network model gains prediction accuracy by information sharing across times. The proposed network model was evaluated by extensive simulation studies and was further illustrated on three real datasets. In real data analyses, I also used methods to open the blackbox by identifying subject-specific predictors and their importance in contributing to the risk prediction. SUPPLEMENTARY INFORMATION The source code is freely available at http://github.com/lilizhaoUM/DnnRMST.
Satellite‐detected fluorescence: Decoupling nonphotochemical quenching from iron stress signals in the South Atlantic and Southern Ocean

Satellite‐detected sunlight‐induced chlorophyll fluorescence could offer valuable information about the physiological status of phytoplankton on a global scale. Realization of this potential is confounded by the considerable uncertainty that exists in deconvolving the multiple ecophysiological processes that can influence the satellite signal. A dominant source of current uncertainty arises from the extent of reductions in chlorophyll fluorescence caused by the high light intensities phytoplankton are typically exposed to when satellite images are captured. In this study, results from over 200 nonphotochemical quenching (NPQ) experiments conducted on cruises spanning from subtropical gyre to Southern Ocean waters have confirmed that satellite fluorescence quantum yields have the potential to reveal broad regions of iron (Fe) stress. However, our results suggest significant variability in phytoplankton NPQ behavior between oceanic regimes. Dynamic NPQ must therefore be considered to achieve a reliable interpretation of satellite fluorescence in terms of Fe stress. Specifically, significantly lower NPQ was found in stratified subtropical gyre‐type waters than in well‐mixed Southern Ocean waters. Such variability is suggested to result from differences in incident irradiance fluctuation experienced by phytoplankton, with highly variable irradiance conditions likely driving phytoplankton to acclimate or adapt toward a higher dynamic NPQ capacity. Sea surface temperature empirically demonstrated the strongest correlation with NPQ parameters and is presented as a means of correcting the chlorophyll fluorescence signature for the region studied. With these corrections, a decadal composite of satellite austral summer observations is presented for the Southern Ocean, potentially reflecting spatial variability in the distribution and extent of Fe stress.
Arabidopsis Plant Natriuretic Peptide Is a Novel Interactor of Rubisco Activase

Plant natriuretic peptides (PNPs) are a group of systemically acting peptidic hormones affecting solute and solvent homeostasis and responses to biotrophic pathogens. Although an increasing body of evidence suggests PNPs modulate plant responses to biotic and abiotic stress, which could lead to their potential biotechnological application by conferring increased stress tolerance to plants, the exact mode of PNPs action is still elusive. In order to gain insight into PNP-dependent signalling, we set out to identify interactors of PNP present in the model plant Arabidopsis thaliana, termed AtPNP-A. Here, we report identification of rubisco activase (RCA), a central regulator of photosynthesis converting Rubisco catalytic sites from a closed to an open conformation, as an interactor of AtPNP-A through affinity isolation followed by mass spectrometric identification. Surface plasmon resonance (SPR) analyses reveals that the full-length recombinant AtPNP-A and the biologically active fragment of AtPNP-A bind specifically to RCA, whereas a biologically inactive scrambled peptide fails to bind. These results are considered in the light of known functions of PNPs, PNP-like proteins, and RCA in biotic and abiotic stress responses.
Replacing Molecular Genetic Testing With Immunohistochemistry Using Antibodies That Recognize the Protein Products of Gene Rearrangements: "Next-generation" Immunohistochemistry.

REFERENCES 1. Baranov E, McBride MJ, Bellizzi AM, et al. A novel SS18-SSX fusion-specific antibody for the diagnosis of synovial sarcoma. Am J Surg Pathol. 2020;44:922–933. 2. Zaborowski M, Vargas AC, Pulvers J, et al. When used together SS18-SSX fusion-specific and SSX C-terminus immunohistochemistry are highly specific and sensitive for the diagnosis of synovial sarcoma and can replace FISH or molecular testing in most cases.Histopathology. 2020; 77:588–600.
The effects of X-rays radiation on active and passive transport of erythrocytes membrane

X-rays play an important role in diagnosis. But it also rendered the biological effects that damage the bilayer lipid structure and cell membrane proteins that affect the structure and permeability of the membrane, which in turn, will affect the micro-nutrient transfer through active and passive transport processes. The purpose of this study was to determine the effect of X-rays on active and passive transport of the erythrocytes membrane under in vitro method. After obtaining approval from the Ethics Committee, erythrocyte samples were each divided into two groups, named irradiated and non-irradiated. Passive transport experiments used variation of glucose under the concentration of 20 mM, 30 mM, 40 mM, 50 mM, and 100 mM, while active transport experiments used variation of calcium under the concentration of 50 mM, 100 mM, 150 mM, and 200 mM. The results showed that there were significant differences (p < 0.05) in the transport rate between the irradiated group and the non-irradiated group. The transport rate of erythrocytes in irradiated group was lower than the non-irradiated group. The effects of X-rays radiation can disrupt cell membrane function by inhibiting the active and passive transport rate on erythrocyte membrane. Experimental article (J Int Dent Med Res 2018; 11(1): pp. 261-264)
ECC-based RFID/NFC Mutual Authentication Protocol

RFID (Radio Frequency IDentification) is a generic term for technologies that use radio signals to automatically identify objects in the IoT (Internet of Things). NFC (Near Field Communication) originating from RFID is a wireless peer-to-peer communication technology, which is widely applied to mobile phones for contactless payment. The open link between the RFID tag and reader is vulnerable to various attacks, such as eavesdropping, tampering and impersonating, etc. PKC (Public Key Cryptography) based authentication is able to solve the above problem. Compared with authentication methods based on symmetric key, PKC is more secure, flexible and suitable for large-scale RFID/NFC applications due to its flexible key management and high security. However, the traditional PKC technologies are not able to be directly applied to low-cost RFID tags because of the limited computing and storage capacity of tags. To alleviate this issue, we propose a low-cost RFID authentication protocol based on ECC (Elliptic Curve Cryptography) that has high security level and small size parameters. The protocol combines the cryptoGPS identification protocol and the precomputing based Diffie-Hellman key exchange method which is proposed in this paper. The security of the protocol is analyzed and proved under the random oracle model.
Effects of GrandFusion Diet on Cognitive Impairment in Transgenic Mouse Model of Alzheimer’s Disease

Alzheimer’s disease (AD) is the result of the deposition of amyloid β (Aβ) peptide into amyloid fibrils and tau into neurofibrillary tangles. At the present time, there are no possible treatments for the disease. We have recently shown that diets enriched in phytonutrients show protection or limit the extent of damage in a number of neurological disorders. GrandFusion (GF) diets have attenuated the outcomes in animal models of traumatic brain injury, cerebral ischemia, and chronic traumatic encephalopathy. In this study, we investigated the effect of GF diets in a mouse model of AD prior to the development of amyloid plaques to show how this treatment paradigm would alter the accumulation of Aβ peptide and related pathologic changes (i.e., inflammation, cathepsin B, and memory impairment). Administration of GF diets (2–4%) over a period of four months in APP/ΔPS1 double-transgenic mice resulted in attenuation in Aβ peptide levels, reduction of amyloid load, and inflammation, increased cathepsin B expression, and improved spatial orientation. Additionally, treatment with GF diets increased nerve growth factor (NGF) levels in the brain and tempered the memory impairment in the animal model. These data suggest that GF diets may alter the development and progression of the mechanisms associated with the disease process to effectively modify AD pathogenesis.
Conflict-of-Interest Reforms and Investment Bank Analysts’ Research Biases

This study examines the consequences of the series of reforms targeting investment banking–related conflicts of interest. The authors compare and contrast optimism biases in analysts’ stock recommendations and earnings forecasts across different types of analyst firms in the postreform period of 2004 to 2007 versus the prereform period of 1998 to 2001. The authors document a significant reduction in the relative optimism of sanctioned investment bank analysts’ stock recommendations but not in their earnings forecasts. Moreover, the authors find little change in the profitability of their stock recommendations but detect a drop in the accuracy of earnings forecasts made by investment bank analysts. In sum, the reforms achieve the objective of mitigating the apparent optimism in investment bank stock recommendations, but they do not provide benefit to investors in terms of more profitable recommendations or more accurate earnings forecasts.
Simulation of the impregnation in the porous media by the Self- organized Gradient Percolation method

Many processes can correspond to reactive impregnation in porous solids. These processes are usually numerically computed by classical methods like finite element method, finite volume method, etc. The disadvantage of these methods remains in the computational time. The convergence and accuracy require a small step-time and a small mesh size, which is expensive in computational time and can induce a spurious oscillation. In order to avoid this problem, we propose a Self-organized Gradient Percolation algorithm. This method permits to reduce the CPU time drastically.
Nonlinear signal processing for ultrasonic imaging of material complexity

Ultrasonic imaging of material complexity is investigated theoretically and experimentally using the concept of symmetry analysis based signal processing in symbiosis with nonlinear elastic wave spectroscopy. These concepts were tested experimentally on several complex media with an advanced electronic system. This system exploits TR invariance, reciprocity, and coded excitation for an accurate extraction of the nonlinear signature of the medium under ultrasonic monitoring. Tested both in the context of the medical imaging of a tooth and in those of nondestructive testing of aeronautic composites, the basis of a new tomographic imaging of material complexity is presented with the help of algebraic concepts describing the TR operators.
Review Of Quantitative Mechanistic Models Of Radiation-Induced Non-Targeted Effects (NTE).

Quantitative mechanistic modeling of the biological effects of ionizing radiation has a long rich history. Initially, it was dominated by target theory, which quantifies damage caused by traversal of cellular targets like DNA by ionizing tracks. The discovery that mutagenesis, death and/or altered behavior sometimes occur in cells that were not themselves traversed by any radiation tracks but merely interacted with traversed cells was initially seen as surprising. As more evidence of such 'non-targeted' or 'bystander' effects accumulated, the importance of their contribution to radiation-induced damage became more recognized. Understanding and modeling these processes is important for quantifying and predicting radiation-induced health risks. Here we review the variety of mechanistic mathematical models of nontargeted effects that emerged over the past 2-3 decades. This review is not intended to be exhaustive, but focuses on the main assumptions and approaches shared or distinct between models, and on identifying areas for future research.
Fast and Slow Paths to Quiescence: Ages and Sizes of 400 Quiescent Galaxies from the LEGA-C Survey

We analyze the stellar age indicators (Dn4000 and EW(Hδ)) and sizes of 467 quiescent galaxies with M* ≥ 1010 M⊙ at z ∼ 0.7 drawn from DR2 of the LEGA-C survey. Interpreting index variations in terms of equivalent single stellar population age, we find that the median stellar population is younger for larger galaxies at fixed stellar mass. The effect is significant, yet small; the ages of the larger and smaller subsets differ by only <500 Myr, much less than the age variation among individual galaxies (∼1.5 Gyr). At the same time, post-starburst galaxies—those that experienced recent and rapid quenching events—are much smaller than expected based on the global correlation between age and size of normal quiescent galaxies. These coexisting trends unify seemingly contradictory results in the literature; the complex correlations between size and age indicators revealed by our large sample of galaxies with high-quality spectra suggest that there are multiple evolutionary pathways to quiescence. Regardless of the specific physical mechanisms responsible for the cessation of star formation in massive galaxies, the large scatter in Dn4000 and EW(Hδ) immediately implies that galaxies follow a large variety of evolutionary pathways. On the one hand, we see evidence for a process that slowly shuts off star formation and transforms star-forming galaxies to quiescent galaxies without necessarily changing their structures. On the other hand, there is likely a mechanism that rapidly quenches galaxies, an event that coincides with dramatic structural changes, producing post-starburst galaxies that can be smaller than their progenitors.
Ultrahigh-efficiency wavelength conversion in nanophotonic periodically poled lithium niobate waveguides

Periodically poled lithium niobate (PPLN) waveguide is a powerful platform for efficient wavelength conversion. Conventional PPLN converters however typically require long device lengths and high pump powers due to the limited nonlinear interaction strength. Here we use a nanostructured PPLN waveguides to demonstrate an ultrahigh normalized efficiency of 2600%/W-cm$^2$ for second-harmonic generation of 1.5-$\mu$m radiation, more than 20 times higher than that in state-of-the-art diffused waveguides. This is achieved by a combination of sub-wavelength optical confinement and high-fidelity periodic poling at a first-order poling period of 4 $\mu$m. Our highly integrated PPLN waveguides are promising for future chip-scale integration of classical and quantum photonic systems.
NAD+ flux is maintained in aged mice

NAD+ is an essential coenzyme found in all living cells. NAD+ concentrations decline during aging, but whether this reflects impaired production or accelerated consumption remains unclear. Here we employed isotope tracing and mass spectrometry to probe NAD+ metabolism across tissues in aged mice. In 25-month-old mice, we observe modest tissue NAD+ depletion (median decrease ~ 30%) without significant changes in circulating NAD+ precursors. Isotope tracing showed unimpaired synthesis of circulating nicotinamide from tryptophan, and maintained flux of circulating nicotinamide into tissue NAD+ pools. Although absolute NAD+ biosynthetic flux was maintained in most tissues of aged mice, fractional tissue NAD+ labeling from infused labeled nicotinamide was modestly accelerated, consistent with increased activity of NAD+ consuming enzymes. Long-term calorie restriction partially mitigated age-associated NAD+ decline despite decreasing NAD+ synthesis, suggesting that calorie restriction reduces NAD+ consumption. Thus, age-related decline in NAD+ is relatively subtle and driven by increased NAD+ consumer activity rather than impaired production.
The essential role of costimulatory molecules in systemic lupus erythematosus

Systemic lupus erythematosus (SLE) is a chronic inflammatory disease with immune system disorder mediated through complex autoimmune pathways that involve immune cells, nonimmune cells, cytokines, chemokines, as well as costimulatory molecules. Costimulatory signals play a critical role in initiating, maintaining and regulating immune reactions, and these include ligands and receptors and their interactions involving multiple types of signal information. Dysfunction of costimulatory factors results in complicated abnormal immune responses, with biological effects and eventually, clinical autoimmune diseases. Here we outline what is known about various roles that costimulatory families including the B7 family and tumor necrosis factor super family play in SLE. The aim of this review is to understand the possible association of costimulation with autoimmune diseases, especially SLE, and to explore possible therapeutic target(s) of costimulatory molecules and pathways that might be used to develop therapeutic approaches for patients with these conditions.
Upotreba ugrađenog sustava za identifikaciju biometrijskom metodom prepoznavanja lica

Computer systems today are a necessity in constant concept of improving the world. The challenge of the Covid virus has steered us into a new normal age where all potentially infected people should be quarantined immediately from the rest of the population. The hectic course of life unfortunately leads to the emergence of an increasing number of quarantine offenders. This paper presents the architecture and proposal of an embedded system that could be taught to recognize persons in quarantine. By placing such a system in the frequency zones, violators would be identified very quickly. Despite the fact that in our work we reach a fairly large error threshold, justified suspicion will more easily enable the police to more easily supervise persons under quarantine.
Dynamic-DeepHit: A Deep Learning Approach for Dynamic Survival Analysis With Competing Risks Based on Longitudinal Data

Currently available risk prediction methods are limited in their ability to deal with complex, heterogeneous, and longitudinal data such as that available in primary care records, or in their ability to deal with multiple competing risks. This paper develops a novel deep learning approach that is able to successfully address current limitations of standard statistical approaches such as landmarking and joint modeling. Our approach, which we call Dynamic-DeepHit, flexibly incorporates the available longitudinal data comprising various repeated measurements (rather than only the last available measurements) in order to issue dynamically updated survival predictions for one or multiple competing risk(s). Dynamic-DeepHit learns the time-to-event distributions without the need to make any assumptions about the underlying stochastic models for the longitudinal and the time-to-event processes. Thus, unlike existing works in statistics, our method is able to learn data-driven associations between the longitudinal data and the various associated risks without underlying model specifications. We demonstrate the power of our approach by applying it to a real-world longitudinal dataset from the U.K. Cystic Fibrosis Registry, which includes a heterogeneous cohort of 5883 adult patients with annual follow-ups between 2009 to 2015. The results show that Dynamic-DeepHit provides a drastic improvement in discriminating individual risks of different forms of failures due to cystic fibrosis. Furthermore, our analysis utilizes post-processing statistics that provide clinical insight by measuring the influence of each covariate on risk predictions and the temporal importance of longitudinal measurements, thereby enabling us to identify covariates that are influential for different competing risks.