Miracle-dz/UniFAR-FTUs huggingface dataset:
GnRH Neuron Excitability and Action Potential Properties Change with Development But Are Not Affected by Prenatal Androgen Exposure

Abstract Gonadotropin-releasing hormone (GnRH) neurons produce the final output from the brain to control pituitary gonadotropin secretion and thus regulate reproduction. Disruptions to gonadotropin secretion contribute to infertility, including polycystic ovary syndrome (PCOS) and idiopathic hypogonadotropic hypogonadism. PCOS is the leading cause of infertility in women and symptoms resembling PCOS are observed in girls at or near the time of pubertal onset, suggesting that alterations to the system likely occurred by that developmental period. Prenatally androgenized (PNA) female mice recapitulate many of the neuroendocrine phenotypes observed in PCOS, including altered time of puberty, disrupted reproductive cycles, increased circulating levels of testosterone, and altered gonadotropin secretion patterns. We tested the hypotheses that the intrinsic properties of GnRH neurons change with puberty and with PNA treatment. Whole-cell current-clamp recordings were made from GnRH neurons in brain slices from control and PNA females before puberty at three weeks of age and in adulthood to measure GnRH neuron excitability and action potential (AP) properties. GnRH neurons from adult females were more excitable and required less current to initiate action potential firing compared with three-week-old females. Further, the afterhyperpolarization (AHP) potential of the first spike was larger and its peak was delayed in adulthood. These results indicate development, not PNA, is a primary driver of changes to GnRH neuron intrinsic properties and suggest there may be developmentally-induced changes to voltage-gated ion channels in GnRH neurons that alter how these cells respond to synaptic input.
The greatest air quality experiment ever: Policy suggestions from the COVID-19 lockdown in twelve European cities

COVID-19 (Coronavirus disease 2019) hit Europe in January 2020. By March, Europe was the active centre of the pandemic. As a result, widespread "lockdown" measures were enforced across the various European countries, even if to a different extent. Such actions caused a dramatic reduction, especially in road traffic. This event can be considered the most significant experiment ever conducted in Europe to assess the impact of a massive switch-off of atmospheric pollutant sources. In this study, we focus on in situ concentration data of the main atmospheric pollutants measured in twelve European cities, characterized by different climatology, emission sources, and strengths. We propose a methodology for the fair comparison of the impact of lockdown measures considering the non-stationarity of meteorological conditions and emissions, which are progressively declining due to the adoption of stricter air quality measures. The analysis of these unmatched circumstances allowed us to estimate the impact of a nearly zero-emission urban transport scenario on air quality in 12 European cities. The clearest result, common to all the cities, is that a dramatic traffic reduction effectively reduces NO2 concentrations. In contrast, each city’s PM and ozone concentrations can respond differently to the same type of emission reduction measure. From the policy point of view, these findings suggest that measures targeting urban traffic alone may not be the only effective option for improving air quality in cities.
Guided ultrasonic wave testing of an immersed plate with hidden defects

Abstract. This paper presents the results of an experimental study in which guided ultrasonic waves are used for the contactless nondestructive testing of a plate immersed in water. In the experiment, narrowband leaky Lamb waves are generated using a focused transducer and are detected with an array of five immersion sensors arranged in a semicircle. The ultrasonic signals are processed to extract a few damage-sensitive features from the time and frequency domains. These features are then fed to an artificial neural network to identify the presence of hidden defects, i.e., defects devised on the surface of the plate not facing the probing system. We find that the noncontact inspection system and the signal processing technique enable the classification of the plate health with a success rate >75%.
The Role of the Propensity Score in Estimating Dose-Response Functions

Estimation of average treatment effects in observational, or non-experimental in pre-treatment variables. If the number of pre-treatment variables is large, and their distribution varies substantially with treatment status, standard adjustment methods such as covariance adjustment are often inadequate. Rosenbaum and Rubin (1983) propose an alternative method for adjusting for pre-treatment variables based on the propensity score conditional probability of receiving the treatment given pre-treatment variables. They demonstrate that adjusting solely for the propensity score removes all the bias associated with differences in pre-treatment variables between treatment and control groups. The Rosenbaum-Rubin proposals deal exclusively with the case where treatment takes on only two values. In this paper an extension of this methodology is proposed that allows for estimation of average causal effects with multi-valued treatments while maintaining the advantages of the propensity score approach.
Prebiotic oligofructose protects against high-fat diet-induced obesity by changing the gut microbiota, intestinal mucus production, glycosylation and secretion

ABSTRACT Obesity is a major risk factor for the development of type 2 diabetes and cardiovascular diseases, and gut microbiota plays a key role in influencing the host energy homeostasis. Moreover, obese mice have a different gut microbiota composition, associated with an alteration of the intestinal mucus layer, which represents the interface between the bacteria and the host. We previously demonstrated that prebiotic treatment with oligofructose (FOS) counteracted the effects of diet-induced obesity, together with changes in the gut microbiota composition, but it is not known if the intestinal mucus layer could be involved. In this study, we found that, in addition to preventing high-fat diet (HFD) induced obesity in mice, the treatment with FOS increased the expression of numerous genes involved in mucus production, glycosylation and secretion, the expression of both secreted and transmembrane mucins, and the differentiation and number of goblet cells. These results were associated with significant changes in the gut microbiota composition, with FOS significantly increasing the relative and absolute abundance of the bacterial genera Odoribacter, Akkermansia, two unknown Muribaculaceae and an unknown Ruminococcaceae. Interestingly, all these bacterial genera had a negative association with metabolic parameters and a positive association with markers of the mucus layer. Our study shows that FOS treatment is able to prevent HFD-induced metabolic disorders, at least in part, by acting on all the processes of the mucus production. These data suggest that targeting the mucus and the gut microbiota by using prebiotics could help to prevent or mitigate obesity and related disorders.
Spontaneous Mutational Patterns and Novel Mutations for Delamanid Resistance in Mycobacterium tuberculosis

Delamanid (DLM) and pretomanid (PTM) are recent additions to the anti-tuberculosis (TB) drug armamentarium, and they offer more effective options for drug-resistant TB treatment. In particular, DLM is included in Group C, which is recommended for use in longer multidrug-resistant (MDR)-TB regimens. ABSTRACT Delamanid (DLM) and pretomanid (PTM) are recent additions to the anti-tuberculosis (TB) drug armamentarium, and they offer more effective options for drug-resistant TB treatment. In particular, DLM is included in Group C, which is recommended for use in longer multidrug-resistant (MDR)-TB regimens. Previous studies have shown that resistance to DLM/PTM is caused by mutations in the ddn, fgd1, fbiA, fbiB, fbiC, and fbiD genes, which are related to the F420-dependent bioactivation pathway. Herein, we conduct in vitro selection of DLM-resistant strains using clinical Mycobacterium tuberculosis (MTB) isolates with various drug resistance profiles. The spontaneous resistance frequency of drug-susceptible (DS) MTB (1.14 × 10−6 to 1.04 × 10−4) to DLM was similar to that of H37Rv (8.88 × 10−6 to 9.96 × 10−6) but higher than those of multidrug-resistant MTB (2.03 × 10−7 to 3.18 × 10−6) and extensively drug-resistant (XDR) MTB (4.67 × 10−8 to 3.60 × 10−6). Of the 100 independently selected DLM-resistant MTB mutants, 65% harbored mutations in genes associated with either DLM prodrug activation (ddn, 39.73%; fgd1, 16.44%) or the F420 biosynthetic pathway (fbiA, 16.44%; fbiB, 5.48%; fbiC, 21.92%). Of the 45 mutations we identified, 38 were not previously reported. A structure analysis revealed that several point mutations affected the ligand binding or structural stability of enzymes related to DLM resistance, which would block the enzyme activity required for prodrug activation. Our results elucidate the in vitro spontaneous DLM-resistance patterns of different clinical strains, which could improve the understanding of the causes of DLM resistance in clinical strains and of the effects on drug resistance of different mutations in genes that are related to the DLM activation pathway.
Publications of the Astronomical Society of the Pacific 98:556-560, June 1986 IRAS OBSERVATIONS OF BINARIES WITH COMPACT OBJECTS

We report on the infrared emission of over 200 binary systems which contain compact objects (either white dwarfs, neutron stars, or possibly black holes). Our sample contains all the classic galactic X-ray binaries, many of the known cataclysmic variables, and a wide selection of other interesting objects. The infrared data were obtained by the Infrared Astronomy Satellite (IRAS) in four broad-band filters centered on 12,25, 60, and 100 microns. Of the 260 sources examined, only 32 were detected. X-ray-emitting Be-type stars (as well as all normal nonsupergiant Be-type stars) are found to have their flux proportional to frequency for 12.7 <log v< 14.7. However, GX304-1 has a highly reddened spectrum with unusual far infrared excesses. We find evidence for a static dust cloud with a radius of roughly one astronomical unit which has formed around the classical nova RR Pic since its 1925 eruption. We present the first far infrared light curve of a classical nova following eruption. This provides strong evidence for infrared emission from both dust grains formed during the eruption and dust grains existing from previous eruptions.
Near diffraction limited mid-IR spectromicroscopy using frequency upconversion

Mid-infrared microscopy and spectroscopy is interesting due to its medical, biological and chemical applications. Spectromicroscopy can be used for histopathology, sample analysis and diagnosis. The ability to do spectromicroscopy in the 2.5 to 4.5 μm wavelength range where many organic molecules have their fundamental vibrations, with the addition of sufficient spectroscopic resolution to resolve these bands, can e.g. potentially allow for diagnostics without the need for staining of the sample. On a longer timeframe, mid-IR spectromicroscopy has the potential for in-vivo diagnostics, combining morphological and spectral imaging. Recent developments in nonlinear frequency upconversion, have demonstrated the potential to perform both imaging and spectroscopy in the mid-IR range at unparalleled low levels of illumination, the low upconversion detector noise being orders of magnitude below competing technologies. With these applications in mind, we have incorporated microscopy optics into an image upconversion system, achieving near diffraction limited spatial resolution in the 3 μm range. Spectroscopic information is further acquired by appropriate control of the phase match condition of the upconversion process. Multispectral images for a region of interest can be obtained by XY-scanning this region of interest within the field of view of the mid-IR upconversion system. Thus, the whole region of interest can be imaged with all available converter wavelengths, and the spectral representation becomes equal for all points in the image. In addition, the range of converted/imaged wavelengths can be tuned continuously by changing the temperature of the crystal, or discretely by using a different poling channel in the PPLN crystal.
Geriatric Nutritional Risk Index as a Predictor of Prognosis in Metastatic Renal Cell Carcinoma Treated with Nivolumab

Abstract Background The Geriatric Nutritional Risk Index (GNRI) has been reported as a screening tool to assess the nutrition-related risk with mortality in older patients and those with the various diseases. However, the prognostic value of GNRI in metastatic renal cell carcinoma (mRCC) patients receiving nivolumab therapy remains unclear. Methods Fifty-six consecutive patients with mRCC receiving nivolumab between September 2013 and August 2020 at our institution were retrospectively analyzed. The survival outcomes and prognostic factors associated with overall survival (OS) were statistically analyzed. Results Thirteen and forty-three patients were classified with low (GNRI < 92) and high (GNRI ≥ 92) GNRI, respectively. Patients with low GNRI demonstrated significantly shorter OS (P = 0.0002) than those with high GNRI. In multivariate analysis, GNRI at the time of nivolumab (P = 0.008) was extracted as the predictor for OS in addition to Karnofsky performance status (KPS) (P = 0.016). Integration of the GNRI into the International Metastatic Renal Cell Cancer Database Consortium (IMDC) risk classification improved the c-index from 0.761 to 0.833 (combination of GNRI with IMDC risk classification) and to 0.778 (substitution of GNRI with KPS in IMDC risk classification). Conclusions GNRI was a significant prognostic biomarker in mRCC patients receiving nivolumab.
A Novel Approach for Color Image, Steganography Using NUBASI and Randomized, Secret Sharing Algorithm

In this paper, we present a new approach for concealing secret message in a digital image by adding three layer securities. In the first layer, the secret image is encrypted by using the famed AES algorithm. In the second layer, we establish a Non-Uniform Block Adaptive Segmentation on Image (NUBASI) algorithm for generating segments of the cover image. This algorithm accept a Key from sender and by using this key, split the cover image into small pieces each with different dimension. In the third layer, a new randomized secret sharing algorithm hide the secret data into the different segments. This algorithm defines 32 different patterns for selecting the segments order to implant the cipher data. This proposed method was implemented and tested for various size cover images and secret messages. The quality of the final stego-image and original image are compared and analyzed through their PSNR values.
Instability of N-body systems: can computers solve the problem?

The problem of the numerical study of instability of N-body gravitating systems by means of Lyapunov characteristic exponents is considered. The discontinuity of Lyapunov exponents is shown for computer-created systems both with softened and, what is more interesting, unsoftened (i.e. pure Newtonian) potentials. The Lyapunov technique thus cannot be considered as an appropriate method of study of N-body systems, and physical and astrophysical interpretations of results of previous computer studies appear to be unfounded.
Loss of NDR1/2 kinases impairs endomembrane trafficking and autophagy leading to neurodegeneration

NDR1/2 kinases are essential for efficient endocytosis and protein clearance by autophagy. Neuron-specific dual deletion of NDR1 and NDR2 causes cortical and hippocampal neurodegeneration, implicating these kinases in neuronal protein homeostasis and health. Autophagy is essential for neuronal development and its deregulation contributes to neurodegenerative diseases. NDR1 and NDR2 are highly conserved kinases, implicated in neuronal development, mitochondrial health and autophagy, but how they affect mammalian brain development in vivo is not known. Using single and double Ndr1/2 knockout mouse models, we show that only dual loss of Ndr1/2 in neurons causes neurodegeneration. This phenotype was present when NDR kinases were deleted both during embryonic development, as well as in adult mice. Proteomic and phosphoproteomic comparisons between Ndr1/2 knockout and control brains revealed novel kinase substrates and indicated that endocytosis is significantly affected in the absence of NDR1/2. We validated the endocytic protein Raph1/Lpd1, as a novel NDR1/2 substrate, and showed that both NDR1/2 and Raph1 are critical for endocytosis and membrane recycling. In NDR1/2 knockout brains, we observed prominent accumulation of transferrin receptor, p62 and ubiquitinated proteins, indicative of a major impairment of protein homeostasis. Furthermore, the levels of LC3-positive autophagosomes were reduced in knockout neurons, implying that reduced autophagy efficiency mediates p62 accumulation and neurotoxicity. Mechanistically, pronounced mislocalisation of the transmembrane autophagy protein ATG9A at the neuronal periphery, impaired axonal ATG9A trafficking and increased ATG9A surface levels further confirm defects in membrane trafficking, and could underlie the impairment in autophagy. We provide novel insight into the roles of NDR1/2 kinases in maintaining neuronal health.
Two galaxies with Wolf-rayet features in their spectra.

Spectral scans are presented of two galaxies, NGC 6764 and Mrk 309, which show the Wolf-Rayet emission band A4650 in the spectra of their nuclei. Their spectra are discussed and compared with the spectra of two previously known dwarf galaxies which show this same feature, as well as with the spectrum of the H n region NGC 604 in M33. The numbers of Wolf-Rayet stars in the nuclei of NGC 6764 and Mrk 309 similar to those in our Galaxy, or of supermassive Wolf-Rayet stars similar to the one which may be present in 30 Dor, are estimated. Subject headings: galaxies: individual — galaxies: nuclei — galaxies: stellar content — stars: Wolf-Rayet
Research on the critical parameters initialization of optical PMD compensator in high bit-rate systems

Based on the proposed polarization mode dispersion (PMD) compensation simulation model and statistical analysis method (Monte-Carlo), the critical parameters initialization of two typical optical domain PMD compensators, which include optical PMD method with fixed compensation differential group delay (DGD) and that with variable compensation DGD, are detailedly investigated by numerical method. In the simulation, the line PMD values are chosen as 3ps, 4ps and 5ps and run samples are set to 1000 in order to achieve statistical evaluation for PMD compensated systems, respectively. The simulation results show that for the PMD value pre-known systems, the value of the fixed DGD compensator should be set to 1.5~1.6 times of line PMD value in order to reach the optimum performance, but for the second kind of PMD compensator, the DGD range of lower limit should be 1.5~1.6 times of line PMD provided that of upper limit is set to 3 times of line PMD, if no effective ways are chosen to resolve the problem of local minimum in optimum process. Another conclusion can be drawn from the simulation is that, although the second PMD compensator holds higher PMD compensation performance, it will spend more feedback loops to look up the optimum DGD value in the real PMD compensation realization, and this will bring more requirements on adjustable DGD device, not only wider adjustable range, but rapid adjusting speed for real time PMD equalization.
Physics of amorphous silicon based alloy field‐effect transistors

In this paper we develop a new theory to describe the characteristics of amorphous silicon based alloy field‐effect transistors. We show that the transition from below to above threshold operation occurs when the Fermi level in the accumulation region moves from the deep to tail localized states in the energy gap. The current‐voltage and capacitance‐voltage characteristics are related to the basic material parameters such as the distribution of localized states in the energy gap, band mobility, device geometry, channel doping, and series resistances. Our analysis shows that an on current in excess of 2×10−7 A/μm gate width can be obtained with a 10‐μm gate length. We also demonstrate that even in the above threshold regime the field‐effect mobility is dependent on the gate voltage. Our theory can be used to optimize the design of amorphous silicon based alloy field‐effect transistors.
Measurement of Investment activity in China based on Natural language processing technology

The purpose of this study is to propose a new index to measure and reflect China's investment activity in time, and to analyze the changes of China's investment activity in the past five years. This study first uses the NEZHA model for semantic representation, and expand the indicator system based on semantic similarity. Then we calculate China's investment activity index by using the network search data. This study shows that China's investment activity began to decline in 2019, rebounded for a period of time after the outbreak of COVID-19 in 2020, and then continued to maintain a downward trend. Private investment activity has declined significantly, while government investment activity has increased. Among the provinces in Chinese Mainland, the investment activity of economically developed provinces has decreased significantly, while the investment activity of some economically less developed provinces in the north and south is higher. After the outbreak of COVID-19, the investment period became shorter. Our research will provide timely investment information for the government, decision makers and managers, as well as provide other researchers who also pay attention to investment with a perspective other than investment in fixed asset.
Efficient Reinforcement Learning Through Trajectory Generation

A key barrier to using reinforcement learning (RL) in many real-world applications is the requirement of a large number of system interactions to learn a good control policy. Off-policy and Offline RL methods have been proposed to reduce the number of interactions with the physical environment by learning control policies from historical data. However, their performances suffer from the lack of exploration and the distributional shifts in trajectories once controllers are updated. Moreover, most RL methods require that all states are directly observed, which is difficult to be attained in many settings. To overcome these challenges, we propose a trajectory generation algorithm, which adaptively generates new trajectories as if the system is being operated and explored under the updated control policies. Motivated by the fundamental lemma for linear systems, assuming sufficient excitation, we generate trajectories from linear combinations of historical trajectories. For linear feedback control, we prove that the algorithm generates trajectories with the exact distribution as if they are sampled from the real system using the updated control policy. In particular, the algorithm extends to systems where the states are not directly observed. Experiments show that the proposed method significantly reduces the number of sampled data needed for RL algorithms.