Miracle-dz/UniFAR-FTUs huggingface dataset:
Global Hourly 0.5-degree Land Surface Air Temperature Datasets

Global hourly 0.5-degree Surface Air Temperature (SAT) datasets were developed based on four reanalysis products [Modern-Era Retrospective Analysis for Research and Applications (MERRA for 1979-2009), 40-year ECMWF Re-Analysis (ERA-40 for 1958-2001), ECMWF Interim Re-Analysis (ERA-Interim for 1979-2009), and NCEP/NCAR reanalysis for 1948-2009)] and the Climate Research Unit Time Series version 3.10 (CRU TS3.10) for 1948-2009. The three-step adjustments included the spatial downscaling to 0.5-degree grid cells, the temporal interpolation from 6-hourly (in ERA-40 and NCEP/NCAR reanalysis) to hourly using the MERRA hourly SAT climatology for each day (and the linear interpolation from 3-hourly in ERA-Interim to hourly), and the bias correction in both monthly-mean maximum (Tmax) and minimum (Tmin) SAT using the CRU data. \n\nThe final products have exactly the same monthly Tmax and Tmin as the CRU data, and perform well in comparison with in-situ hourly measurements over six sites and with a regional daily SAT dataset over Europe. They agree with each other much better than the original reanalyses, and the spurious SAT jumps of reanalyses over some regions are also substantially eliminated. One of the uncertainties in the final products can be quantified by the differences in the true monthly mean (using 24-hourly values) and the monthly averaged diurnal cycle from different final products.
A New Method for Species Identification via Protein-Coding and Non-Coding DNA Barcodes by Combining Machine Learning with Bioinformatic Methods

Species identification via DNA barcodes is contributing greatly to current bioinventory efforts. The initial, and widely accepted, proposal was to use the protein-coding cytochrome c oxidase subunit I (COI) region as the standard barcode for animals, but recently non-coding internal transcribed spacer (ITS) genes have been proposed as candidate barcodes for both animals and plants. However, achieving a robust alignment for non-coding regions can be problematic. Here we propose two new methods (DV-RBF and FJ-RBF) to address this issue for species assignment by both coding and non-coding sequences that take advantage of the power of machine learning and bioinformatics. We demonstrate the value of the new methods with four empirical datasets, two representing typical protein-coding COI barcode datasets (neotropical bats and marine fish) and two representing non-coding ITS barcodes (rust fungi and brown algae). Using two random sub-sampling approaches, we demonstrate that the new methods significantly outperformed existing Neighbor-joining (NJ) and Maximum likelihood (ML) methods for both coding and non-coding barcodes when there was complete species coverage in the reference dataset. The new methods also out-performed NJ and ML methods for non-coding sequences in circumstances of potentially incomplete species coverage, although then the NJ and ML methods performed slightly better than the new methods for protein-coding barcodes. A 100% success rate of species identification was achieved with the two new methods for 4,122 bat queries and 5,134 fish queries using COI barcodes, with 95% confidence intervals (CI) of 99.75–100%. The new methods also obtained a 96.29% success rate (95%CI: 91.62–98.40%) for 484 rust fungi queries and a 98.50% success rate (95%CI: 96.60–99.37%) for 1094 brown algae queries, both using ITS barcodes.
Plasmacytoid DC from Aged Mice Down-Regulate CD8 T Cell Responses by Inhibiting cDC Maturation after Encephalitozoon cuniculi Infection

Age associated impairment of immune function results in inefficient vaccination, tumor surveillance and increased severity of infections. Several alterations in adaptive immunity have been observed and recent studies report age related declines in innate immune responses to opportunistic pathogens including Encephalitozoon cuniculi. We previously demonstrated that conventional dendritic cells (cDC) from 9-month-old animals exhibit sub-optimal response to E. cuniculi infection, suggesting that age associated immune senescence begins earlier than expected. We focused this study on how age affects plasmacytoid DC (pDC) function. More specifically how aged pDC affect cDC function as we observed that the latter are the predominant activators of CD8 T cells during this infection. Our present study demonstrates that pDC from middle-aged mice (12 months) suppress young (8 week old) cDC driven CD8 T cell priming against E. cuniculi infection. The suppressive effect of pDC from older mice decreased maturation of young cDC via cell contact. Aged mouse pDC exhibited higher expression of PD-L1 and blockade of their interaction with cDC via this molecule restored cDC maturation and T cell priming. Furthermore, the PD-L1 dependent suppression of cDC T cell priming was restricted to effector function of antigen-specific CD8 T cells not their expansion. To the best of our knowledge, the data presented here is the first report highlighting a cell contact dependent, PD-L1 regulated, age associated defect in a DC subpopulation that results in a sub-optimal immune response against E. cuniculi infection. These results have broad implications for design of immunotherapeutic approaches to enhance immunity for aging populations.
Diagnosing the causes of AMOC slowdown in a coupled model: a cautionary tale

Abstract. It is now established that the increase in atmospheric CO2 is likely to cause a weakening, or perhaps a collapse, of the Atlantic Meridional Overturning Circulation (AMOC). To investigate the mechanisms of this response in CMIP5 models, Levang and Schmitt (2020) have estimated the geostrophic streamfunction in these models offline and have decomposed the simulated changes into a contribution caused by the variations in temperature and salinity. They concluded that under a warming scenario, and for most models, the weakening of the AMOC is fundamentally driven by temperature anomalies, while freshwater forcing actually acts to stabilise it. However, given that both 3-D fields of ocean temperature and salinity are expected to respond to a forcing at the ocean surface, it is unclear to what extent the diagnostic is informative about the nature of the forcing. To clarify this question, we used the Earth system Model of Intermediate Complexity (EMIC), cGENIE, which is equipped with the C-GOLDSTEIN friction-geostrophic model. First, we reproduced the experiments simulating the Representative Concentration Pathway 8.5 (RCP8.5) warming scenario and observed that cGENIE behaves similarly to the majority of the CMIP5 models considered by Levang and Schmitt (2020), with the response dominated by the changes in the thermal structure of the ocean. Next, we considered hysteresis experiments associated with (1) water hosing and (2) CO2 increase and decrease. In all experiments, initial changes in the ocean streamfunction appear to be primarily caused by the changes in the temperature distribution, with variations in the 3-D distribution of salinity only partly compensating for the temperature contribution. These experiments also reveal limited sensitivity to changes in the ocean's salinity inventory. That the diagnostics behave similarly in CO2 and freshwater forcing scenarios suggests that the output of the diagnostic proposed in Levang and Schmitt (2020) is mainly determined by the internal structure of the ocean circulation rather than by the forcing applied to it. Our results illustrate the difficulty of inferring any information about the applied forcing from the thermal wind diagnostic and raise questions about the feasibility of designing a diagnostic or experiment that could identify which aspect of the forcing (thermal or haline) is driving the weakening of the AMOC.
Nutrient digestibility, characteristics of rumen fermentation, and microbial protein synthesis from Pesisir cattle diet containing non-fiber carbohydrate to rumen degradable protein ratio and sulfur supplement

Background and Aim: To achieve optimal feed efficiency in ruminants, especially Pesisir cattle, it is necessary to maintain a harmonious equilibrium between energy and protein levels within the rumen. Sulfur supplementation can potentially escalate the energyâ€“protein balance in the rumen. The aim of this study was to explore the formulation of ruminant diets by synchronizing rumen degradable protein (RDP) and non-fiber carbohydrate (NFC) while adding sulfur minerals at different levels. Nutrient digestibility, NH3 concentration, volatile fatty acids (VFA) production, microbial protein synthesis (MPS), and methane gas production were assessed. Materials and Methods: We employed a randomized block design with a 2 Ã— 2 Ã— 3 factorial arrangement and examined diverse incubation periods of 6, 24, and 48 h. Treatment consisted of RDP (60% and 65%), NFC (35% and 40%), and sulfur (0%, 0.15%, and 0.3%) levels. In this study, the Tilley and Terry in vitro technique, which used Pesisir cattleâ€™s rumen fluid, was employed to assess the digestibility of dry matter, organic matter, acid detergent fiber, neutral detergent fiber, and RDP-Rumen undegradable protein. In addition, it measures various rumen fluid attributes, including pH, NH3, VFA, MPS, and methane gas production. Results: Treatment with a coordinated combination of 65% RDP and 40% NFC combined with 0.15% sulfur supplement yielded significantly improved digestibility and notably reduced methane gas production (p < 0.05). Conclusion: The enhancement in digestibility and reduction in methane gas emissions can be attributed to the interaction of RDP, NFC, and sulfur. Feed digestibility was increased in the 65% RDP treatment with 40% NFC and 0.15% sulfur, along with a decrease in methane gas production. Keywords: degradable and undegradable protein, digestibility, non-fiber carbohydrate, rumen fermentation, sulfur.
PLDAPS: A Hardware Architecture and Software Toolbox for Neurophysiology Requiring Complex Visual Stimuli and Online Behavioral Control

Neurophysiological studies in awake, behaving primates (both human and non-human) have focused with increasing scrutiny on the temporal relationship between neural signals and behaviors. Consequently, laboratories are often faced with the problem of developing experimental equipment that can support data recording with high temporal precision and also be flexible enough to accommodate a wide variety of experimental paradigms. To this end, we have developed a MATLAB toolbox that integrates several modern pieces of equipment, but still grants experimenters the flexibility of a high-level programming language. Our toolbox takes advantage of three popular and powerful technologies: the Plexon apparatus for neurophysiological recordings (Plexon, Inc., Dallas, TX, USA), a Datapixx peripheral (Vpixx Technologies, Saint-Bruno, QC, Canada) for control of analog, digital, and video input–output signals, and the Psychtoolbox MATLAB toolbox for stimulus generation (Brainard, 1997; Pelli, 1997; Kleiner et al., 2007). The PLDAPS (“Platypus”) system is designed to support the study of the visual systems of awake, behaving primates during multi-electrode neurophysiological recordings, but can be easily applied to other related domains. Despite its wide range of capabilities and support for cutting-edge video displays and neural recording systems, the PLDAPS system is simple enough for someone with basic MATLAB programming skills to design their own experiments.
Raman scattering through a metal-insulator transition

The exact solution for nonresonant A1g and B1g Raman scattering is presented for the simplest model that has a correlated metal-insulator transition, the Falicov-Kimball model, by employing dynamical mean-field theory. In the general case, the A1g response includes nonresonant, resonant, and mixed contributions, and the B1g response includes nonresonant and resonant contributions ~we prove the Shastry-Shraiman relation for the nonresonant B1g response! , while the B2g response is purely resonant. Three main features are seen in the nonresonant B1g channel: ~i! the rapid appearance of low-energy spectral weight at the expense of higherenergy weight; ~b! the frequency range for this low-energy spectral weight is much larger than the onset temperature, where the response first appears; and ~iii! the occurrence of an isosbestic point, which is a characteristic frequency where the Raman response is independent of temperature for low temperatures. Vertex corrections renormalize away all of these anomalous features in the nonresonant A1g channel. The calculated results compare favorably to the Raman response of a number of correlated systems on the insulating side of the quantum-critical point ~ranging from Kondo insulators to mixed-valence materials to underdoped hightemperature superconductors! We also show why the nonresonant B1g Raman response is ‘‘universal’’ on the insulating side of the metal-insulator transition.
Functional circuitry of visual adaptation in the retina

The visual system continually adjusts its sensitivity, or ‘adapts’, to the conditions of the immediate environment. Adaptation increases responses when input signals are weak, to improve the signal‐to‐noise ratio, and decreases responses when input signals are strong, to prevent response saturation. Retinal ganglion cells adapt primarily to two properties of light input: the mean intensity and the variance of intensity over time (contrast). This review focuses on cellular mechanisms for contrast adaptation in mammalian retina. High contrast over the ganglion cell's receptive field centre reduces the gain of spiking responses. The mechanism for gain control arises partly in presynaptic bipolar cell inputs and partly in the process of spike generation. Following strong contrast stimulation, ganglion cells exhibit a prolonged after‐hyperpolarization, driven primarily by suppression of glutamate release from presynaptic bipolar cells. Ganglion cells also adapt to high contrast over their peripheral receptive field. Long‐range adaptive signals are carried by amacrine cells that inhibit the ganglion cell directly, causing hyperpolarization, and inhibit presynaptic bipolar terminals, reducing gain of their synaptic output. Thus, contrast adaptation in ganglion cells involves multiple synaptic and intrinsic mechanisms for gain control and hyperpolarization. Several forms of adaptation in ganglion cells originate in presynaptic bipolar cells.
A 175 mV multiply-accumulate unit using an adaptive supply voltage and body bias (ASB) architecture

The power dissipation of a digital circuit is minimized by simultaneous control of power supply voltage and body bias. The technique minimizes power dissipation for varying processing rates through dynamic adjustment of V/sub dd/ and V/sub tb/. A 16b MAC operates at 166 kHz and 14 nW at 175 mV V/sub dd/. A ring oscillator operates at 0.1 V.
A Grammar of Projections

A sequence of nodes in a syntax tree, each the head of the next, is usually called a projection path, or simply a projection. Projections in this sense are fairly basic phrase-structural entities, though hardly of central importance in most accounts. There are a few exceptions. For example, varieties of projection that I called c-projection and s-projection were significant in my earlier work on the grammar of function words, and the distinction was further developed by Grimshaw under the rubric extended projections. And in quite a different direction, Kayne proposed g-projections to account for constraints on long-distance dependencies. Pesetsky, inspired by Kayne’s g-projections, proposed using paths as the basis for an account of locality; and his paths, in turn, are reminiscent of the feature-passing paths that figure prominently in intuitive accounts of attribute-value grammars. If there is more to this train of precedent than just free association and coincidences of terminology, it suggests that an account of both constituent structure and long-distance dependencies might be based on a single notion of projection. I would like to propose such an approach in the present work. As a point of departure, let me make another set of free associations, not obviously related to the first. Traditionally, there have been two broad approaches to phrase structure: immediate-constituent analysis and dependency analysis. American structuralists mostly assumed immediate-constituent analysis in preference to dependency analysis, and that prejudice was inherited by Chomsky and transformational grammar. But as transformational grammar has evolved, it has assigned an ever more central role to dependency concepts. Whereas dominance is the primitive structural relation in immediate-constituent analysis, government is the fundamental structural relation in dependency grammar. At least since the point at which the Extended Standard Theory evolved into Government-Binding Theory (GB), government has come to play a central role in Chomsky’s work. (Some related notions had a prominent place in the theory much earlier, including headship and command—the latter being definable as the transitive closure of government.) I think it is not far from the mark to say that GB reconstructs dependency structures as defined terms, atop an immediate-constituency substrate. And with the more recent introduction of ‘bare phrase structure’ [? ], Chomsky’s phrase structures have all but abandoned the immediate-constituent substrate, and become nearly pure, if somewhat idiosyncratic, dependency stemmas. But let us return now to the relation between dependency structure and constituent structure, and the question of what it has to do with projections. There is something rather unsatisfying about the opportunistic mixture of constituent structure and dependency structure in GB. Constituent grammars (i.e.,
Increased Cerebrospinal Fluid Tau Protein in Multiple Sclerosis

Axonal damage is now being recognized as a common finding in multiple sclerosis (MS) lesions and a cause of irreversible neurological damage. Attempts to identify markers of early axonal damage are of great significance. This prompted us to examine the microtubule-associated protein tau in the cerebrospinal fluid (CSF) of patients with MS vs. controls. Tau was measured by double antibody sandwich ELISA. Increased CSF tau levels were found in MS as compared to controls (medians 249.6 and 135 pg/ml respectively, p < 0.001). Half of the MS patients presented with levels above the upper limit of the controls. A significant increase vs. controls was found in both relapsing-remitting and progressive subtypes. These data may indicate axonal impairment in a subpopulation of MS patients and may provide a tool for the estimation of axonal damage during life.
An Anomaly Detection Approach Based on Bidirectional Temporal Convolutional Network and Multi-Head Attention Mechanism

Anomaly detection aims at detecting the data instances that deviate from the majority of data, and it is widely used in various fields for its ability to ensure the quality of the overall data. However, traditional anomaly detection methods face the problems such as low efficiency due to high data complexity and lack of data labels. At the same time, most methods only learn the forward features of time-series data, while lacking attention to the reverse features. For these disadvantages, this paper designs an anomaly detection approach called BiTCN-MHA based on the bidirectional temporal convolutional network (BiTCN) and multi-head attention (MHA) mechanism, which learns the features of anomalous data by capturing the forward and reverse temporal features in the time-series data, as well as solves the problems of feature information overload and neuron “death” by using MHA mechanism and ELU activation function, respectively, thereby quickly and accurately detecting anomalous data. Extensive experiments on six public datasets show that compared with eight state-of-the-arts, the proposed BiTCN-MHA method can improve the precision, recall, AUC and F1-Score by about 6.10%, 10.16%, 4.06% and 8.50%, respectively, especially having better detection performance on small time-series data.
The Right Inferior Frontal Gyrus and Poststroke Aphasia: A Follow-Up Investigation

Background and Purpose— Recently, a combined repetitive transcranial magnetic stimulation (rTMS) and activation positron emission tomography (PET) study showed essential language function of the right inferior frontal gyrus (IFG) in some right-handed acute poststroke aphasics. We reexamined these patients in the chronic phase to test whether the right IFG remained essential for language performance. Methods— We reexamined 9 male right-handed patients, age 41 to 75 years, with aphasia 8 weeks after left hemispheric stroke. rTMS was performed over the maximum activation within the left and right IFG as defined by 15[O]water PET to interfere with language function. A positive rTMS effect was defined as increased reaction time latency or error rate in the semantic task relative to no stimulation. Results— PET activations of the IFG were observed on the left (2 patients) and bilaterally (7). During rTMS interference over the left IFG, all patients had positive TMS effects, indicating that the left IFG remained essential. Stimulation over the right IFG yielded positive rTMS effects in 2 patients with persisting right IFG activation. Two patients with positive rTMS effects over the right side in the initial study did not show these effects at follow-up. Language performance improved in all patients. Conclusions— Successful regeneration from poststroke aphasia seems to depend more on the integration of available language-related brain regions than on recruiting new brain regions during the rehabilitation process. Restoration of the left hemisphere network seems to be more effective, although in some cases, right hemisphere areas are integrated successfully.
Traffic features extraction and clustering analysis for abnormal behavior detection

With the increasing of the network bandwidth, users generate massive traffic data, how to extract the effective traffic features and achieve the goal of abnormal behavior detection is a hot and difficult problem in the area of network security monitoring. In this paper, several traffic features are proposed to capture the traffic characteristics, and then we employ the DBSCAN methods to realize abnormal traffic mining based on those features. We extract four traffic features to capture the traffic characteristics, including the ratio between number of source and destination IP addresses, ration between number of source port and destination port, ration between number of TCP packet and the total number of packets and that of number of small packets between the total number of package in a specific time window. Based on the feature extracted, we employ the DBSCAN method to cluster the network traffic in different clusters. Traffic packet in different clusters has different statistical characteristics, and the isolated points are employed to perform abnormal traffic detection. The implementation results based on traffic collect from our Lab show that proposed statistics features can capture traffic characteristics, and clustering method can classify the abnormal traffic packets into a special cluster.