Miracle-dz/UniFAR-FTUs huggingface dataset:
Global forests are influenced by the legacies of past inter-annual temperature variability

Inter-annual climate variability (hereafter climate variability) is increasing in many forested regions due to climate change. This variability could have larger near-term impacts on forests than decadal shifts in mean climate, but how forests will respond remains poorly resolved, particularly at broad scales. Individual trees, and even forest communities, often have traits and ecological strategies—the legacies of exposure to past variable conditions—that confer tolerance to subsequent climate variability. However, whether local legacies also shape global forest responses is unknown. Our objective was to assess how past and current climate variability influences global forest productivity. We hypothesized that forests exposed to large climate variability in the past would better tolerate current climate variability than forests for which past climate was relatively stable. We used historical (1950–1969) and contemporary (2000–2019) temperature, precipitation, and vapor pressure deficit (VPD) and the remotely sensed enhanced vegetation index (EVI) to quantify how historical and contemporary climate variability relate to patterns of contemporary forest productivity. Consistent with our hypothesis, forests exposed to large temperature variability in the past were more tolerant of contemporary temperature variability than forests where past temperatures were less variable. Forests were 19-fold times less sensitive to contemporary temperature variability where historical inter-annual temperature variability was 0.66 °C (two standard deviations) greater than the global average historical temperature variability. We also found that larger increases in temperature variability between the two study periods often eroded the tolerance conferred by the legacy effects of historical temperature variability. However, the hypothesis was not supported in the case of precipitation and VPD variability, potentially due to physiological tradeoffs inherent in how trees cope with dry conditions. We conclude that the sensitivity of forest productivity to imminent increases in temperature variability may be partially predictable based on the legacies of past conditions.
Local Generalized Pauli's Theorem

In this work a generalized Pauli's theorem (proved by D. S. Shirokov for two sets $e^a, h^a$, $a=1,.,n$ of Clifford algebra elements $Cl(p,q)$, $p+q=n$) is extended to the case, when one or both sets of elements depends smoothly on points $x$ of the Euclidian space. We prove that in this case for any point $x_0$ of Euclidian space there exists $\epsilon$-neighborhood $O_\epsilon(x_0)$ and there exists smooth function $T : O_\epsilon(x_0)\to Cl(p,q)$ such that two sets of Clifford algebra elements are connected by a similarity transformation $h^a(x)=T(x)^{-1}e^a(x)T(x)$, $a=1,. ,n$ in $O_\epsilon(x_0)$.
Structural Reliability Analysis by Using Non-Probabilistic Multi-Cluster Ellipsoidal Model

Uncertainties are normally unavoidable in engineering practice, which should be taken into account in the structural design and optimization so as to reduce the relevant risks. Yet, the probabilistic models of the uncertainties are often unavailable in the problems due to the lack of samples, and the precision of the conventional non-probabilistic models are not satisfactory when the samples are of multi-cluster distribution. In view of this, an improved method by using a non-probabilistic multi-cluster ellipsoidal model (multi-CEM) for the critical structural reliability analysis is proposed in this paper, which describes the samples in a more accurate and compact way and helps to acquire more satisfactory reliability analysis results. Firstly, a Gaussian mixture model (GMM) is built for the multi-cluster samples with performing expectation maximization (EM) algorithm, based on which the multi-CEM can be constructed. In the structural reliability analysis, two cases, respectively, considering whether the components of the multi-CEM are intersected or not are researched in detail. The non-probabilistic reliability (NPR) indexes for each component of the multi-CEM are computed using the Hasofer–Lind–Rackwitz–Fiessler (HL-RF) algorithm, and then the multidimensional volume ratios of the safe domain to the whole uncertainty domain are computed based on these indexes, indicating the structural NPR. In the end, two numerical examples and a practical application are conducted and analyzed to testify the effectiveness of the method.
Effects of dephosphorization from solid 2CaO·SiO2-3CaO·P2O5 of steelmaking slag

Different from other conventional large converter in Shougang, Shougang 100 t low flow bottom blow converter is easy increasing the phosphorus in the furnace before steel tapping, especially low carbon steel smelting. For this phenomenon, The effect of the presence of solid phosphorus-rich phase C2S-C3P on the phosphorus distribution ratio was investigated, test and calculation shows that solid phosphorus-rich phase in slag can improve the phosphorus distribution ratio. The reason is that the nature of the steel slag changed, it is mainly due to the reduction of the phosphorus-rich phase C2S-C3P in the slag, in addition, the change of iron water Si content in the converter has a certain impact on the phosphorus content at the converter end point, smelt the low phosphorus steel by double slag method, when the silicon content is below 0.40 % every 0.10 % reduction in Si content, the P content increase about 10 ppm. In addition, the oxygen supply is too high, it also easily leads the increasing of P at the end point , the main reason is FeO increasing and reduce C2S-C3P in furnace slag , This results in increased phosphorus in liquid slag, resulting in redistribution of P between slag and steel.
In Vivo Effect of Resveratrol-Cellulose Aerogel Drug Delivery System to Relieve Inflammation on Sports Osteoarthritis

Resveratrol (Res) is a plant extract with strong anti-inflammatory, antioxidant and anti-aging biological activities. However, Res is limited by its disadvantages, such as poor solubility, rapid metabolism and low bioavailability. In this study, the Resveratrol-loaded TEMPO-oxidized cellulose aerogel (RLTA) drug delivery system was prepared by the method of “dissolution-freeze-drying” and characterized by a series of analysis. Then the blood biochemical indexes and HE staining were measured and analyzed in animal experiments. The in vivo results showed that RLTA can decrease the levels of TNF-α and IL-6 inflammatory factors in the synovial fluid. Furthermore, the molecular mechanism was investigated through the analysis of silent information regulator 2 homolog 1 (Sirt1) protein expression, which suggested that RLTA could upregulate the expression of Sirt1 and mediate the P38 signaling pathway, thereby inhibiting the expression of COX-2 and MMP13 which can suppress the levels of IL-6 and TNF-α inflammatory factor. These results reveal that cellulose aerogel is a promising candidate for drug delivery and RLTA has great potential application for the treatment of sports osteoarthritis.
Comparison of Enzyme Activity in Order to Describe the Metabolic Profile of Dairy Cows during Early Lactation

Enzymatic diagnostics have practical applications in diseases of the liver, heart, pancreas, muscles, blood, and neoplastic diseases. This study aimed to compare enzyme activity to describe dairy cows’ metabolism during early lactation. Based on their general health symptoms, the cows were assigned to one of three groups: acidotic, healthy and ketotic. Samples of milk, blood and rumen fluid were collected at 12 ± 5 days postpartum. Ketotic cows were characterized by the highest malondialdehyde (MDA, 76.098 nM/mL), glutathione reductase (GluRed, 109.852 U/L), superoxide dismutase (SOD, 294.22 U/L) and gamma-glutamyltranspeptidase (GGTP, 71.175 U/L) activity. In comparing ketotic and acidotic cows, MDA, GluRed, SOD and GGTP activity were higher by a factor of almost: 1.85, 1.89, 0.79 and 2.50, respectively. Acidotic cows were characterized by the highest aspartate aminotransferase activity (AspAT, 125.914 U/L). In comparing acidotic and ketotic cows, AspAT activity was higher by a factor of almost 1.90. The use of enzymatic markers could limit the frequency of sampling for laboratory analyses and may result in a faster diagnosis of metabolic disorders. AspAT activity in blood serum seems to be a good indicator of acidosis; GGTP may participate in the pathogenesis of ketosis.
Antioxidant Potential of Santowhite as Synthetic and Ascorbic Acid as Natural Polymer Additives

A wide variety of additives are used to improve specific characteristics of the final polymeric product. Antioxidant additives (AAs) can prevent oxidative stress and thus the damage of polymeric materials. In this work, the antioxidant potential and thus the applicability of Santowhite (SW) as synthetic and ascorbic acid (Asc) as natural AAs were explored by using computational tools. Two density functional theory (DFT) methods, M05-2X and M06-2X, have been applied in combination with the 6-311++G(2d,2p) basis set in gas phase. Three antioxidant mechanisms have been considered: hydrogen atom transfer (HAT), single electron transfer-proton transfer (SET-PT), and sequential proton loss electron transfer (SPLET). Bond dissociation enthalpy (BDE), ionization potential (IP), proton dissociation enthalpy (PDE), proton affinity (PA), and electron transfer enthalpy (ETE) have been computed for each potential hydrogen donor site. The results indicate that the antioxidant potential of Asc is higher than SW. Furthermore, some of the C-H bonds, depending on their position in the structures, are potent radical scavengers, but O-H groups are more prone to donate H-atoms to free radicals. Nonetheless, both additives can be potentially applied to safeguard common polymers and prohibit oxidative stress-induced material deterioration.
Durable Remission in Hodgkin Lymphoma Treated With One Cycle of Bleomycin, Vinblastine, Dacarbazine and Two Doses of Nivolumab and Brentuximab Vedotin

A 49-year-old woman with systemic lupus erythematosus, lupus nephritis and chronic congestive heart failure presenting with “bulky” cervical lymphadenopathy was diagnosed with classic Hodgkin lymphoma (HL) stage IIIB (positron emission tomography-computed tomography (PET-CT) scan and bone marrow biopsy). She received one cycle of bleomycin, dacarbazine, and vinblastine to debulk the tumor. Given her advanced heart failure, doxorubicin was not administered. After the first cycle of chemotherapy, she was switched to nivolumab plus brentuximab vedotin (BV) and received two doses 4 weeks apart, finishing in July 2019. A restaging PET-CT in June 2019 showed a complete remission (CR). After the second course of treatment, she was unable to tolerate more treatments and hence was placed on a surveillance program. She remains in CR after a follow-up of 3 years. This case highlights the role of a tailored treatment approach to optimize clinical outcomes in uniquely complex clinical circumstances. BV in combination with nivolumab is a reasonable alternative regimen in HL ineligible for cytotoxic chemotherapy.
Rectified DenseNet169-based automated criminal recognition system for the prediction of crime prone areas using face recognition

Abstract. With the increase in the crime rate, it becomes difficult for police officials to catch criminals. Face recognition is a technique that helps police officials to catch suspects easily with the help of CCTV footage. The constant checking of surveillance video is a tiresome approach that involves substantial visual consideration and is not mentally captivating, making it increasingly inclined to errors. Therefore, the authors proposed an automated criminal recognition system in the present paper. The present paper comprised three phases; the initial phase investigated the performance of various existing face detection algorithms. The second phase proposed a rectified fine-tuned DenseNet169 model for face recognition. In the third phase, the authors proposed an automated criminal recognition system in which the identification of crime-prone areas is made, based on the data collected where most of the criminals are identified. The proposed rectified model outperformed 1.02% to DeepID, 1% to deep convolutional neural network (CNN), and 1.05% to self-learning CNN on the LFW dataset, 1.09% to VGGFace2, 1.13% to SphereFace, and 1.03% to lightweight CNN on the CPLFW dataset, and achieved 88.7% recognition accuracy on a self-created dataset by meticulously selecting the hyperparameters and customizing the layers of the model.
Cross-Layer Signaling for Enhanced Wireless QoE

The paper proposes a novel cross-layer signaling mechanism to provide unprecedented Quality of Experience (QoE) in next generation mobile networks. The number of network-connected cameras is rapidly increasing, especially on the widely and globally deploying cellular networks (i.e. LTE). In many cases, the video traffic can be considered as a real-time traffic, as the video traffic generating service may require continuous real-time human interaction or may be a part of the remote control system. Meanwhile, throughput and delay can vary rapidly due to changes in a radio network, thus affecting service QoE. The novel cross-layer signaling mechanism presented requires minimal modification to the networking stack at the client side for faster feedback of wireless link capacity variations. The proposed mechanism has been evaluated via simulation with video traffic. The results show outage rate decreased from 1.3 outages/sec to zero and reduction in self-inflicted delay, from 60 ms to 14 ms.
A lattice on decreasing trees : the metasylvester lattice

We introduce a new combinatorial structure: the metasylvester lattice on decreasing trees. It appears in the context of the $m$-Tamari lattices and other related $m$-generalizations. The metasylvester congruence has been recently introduced by Novelli and Thibon. We show that it defines a sublattice of the $m$-permutations where elements can be represented by decreasing labelled trees: the metasylvester lattice. We study the combinatorial properties of this new structure. In particular, we give different realizations of the lattice. The $m$-Tamari lattice is by definition a sublattice of our newly defined metasylvester lattice. It leads us to a new realization of the $m$-Tamari lattice, using certain chains of the classical Tamari lattice.
Drosophila as a Model for Human Viral Neuroinfections

The study of human neurological infection faces many technical and ethical challenges. While not as common as mammalian models, the use of Drosophila (fruit fly) in the investigation of virus–host dynamics is a powerful research tool. In this review, we focus on the benefits and caveats of using Drosophila as a model for neurological infections and neuroimmunity. Through the examination of in vitro, in vivo and transgenic systems, we highlight select examples to illustrate the use of flies for the study of exogenous and endogenous viruses associated with neurological disease. In each case, phenotypes in Drosophila are compared to those in human conditions. In addition, we discuss antiviral drug screening in flies and how investigating virus–host interactions may lead to novel antiviral drug targets. Together, we highlight standardized and reproducible readouts of fly behaviour, motor function and neurodegeneration that permit an accurate assessment of neurological outcomes for the study of viral infection in fly models. Adoption of Drosophila as a valuable model system for neurological infections has and will continue to guide the discovery of many novel virus–host interactions.
Representando Aspectos de Sistemas Operacionais na Abordagem de Gerenciamento Baseado em Modelos

O gerenciamento da configuração de mecanismos de segurança em ambientes computacionais está se tornando cada vez mais complexo, especialmente em redes de computadores de larga escala. Administradores de segurança encaram o desafio de projetar e manter políticas de segurança para um enorme número de mecanismos heterogêneos e diferentes sistemas operacionais para garantir a proteção desses ambientes. Para permitir o gerenciamento de configurações de segurança de sistemas operacionais e de rede em um único modelo, este trabalho apresenta uma extensão da abordagem de Gerenciamento Baseado em Modelos aplicado a redes de computadores que inclui gerenciamento de políticas de sistemas operacionais.
WFC3: UVIS and IR Flat Fields

Flat fielding is a standard calibration step for astronomical data, which allows us to correct for variations in the local response of a detector and improve the accuracy of photometric analysis. As for other Hubble Space Telescope (HST) instruments, ground based flat-fields are, and will be, the base to remove the pixel-to-pixel variations in the Wide Field Camera 3 (WFC3) data. Tests performed during the Servicing Mission Observatory Verification (SMOV4), that followed the installation of WFC3 on Hubble, indicate that ground based flat-fields do not completely remove local variation in the response of the detector, but that low-frequency structures are still present in both the UVIS and IR data. As part of the WFC3 standard calibration process we have used observations of the rich globular cluster Omega Centauri to compare the flux of the same stars at different positions on the WFC3 detectors and derive a correction to remove the remaining low-frequency structures. Here we will present the characteristics of the ground-based high frequency flat (better known as P-flat) and the low-frequency (or L-flat) flat fields, how these files are created and their impact on the processed astronomical data.
Development and Characterization of Unmodified and Modified Natural Rubber Composites Filled with Modified Clay

Novel composite based on rubber and modified bentonite clay (Clay) was investigated. The modified bentonite clay was developed by dispersing in ethanol solutions (Et-OH) using ultrasonic method. The effect of Et-OH on the dispersion of bentonite clay at various mixing temperatures in case of different type of rubber matrix, i.e., natural rubber (NR), epoxidized natural rubber (ENR25, ENR50) on dynamic mechanical rheology, Payne effect, XRD and mechanical properties of rubber composites were studied in detail. The bentonite clay dispersion in Et-OH at a mixing temperature of 80 °C improves the intercalation and exfoliation in rubber chains. Bentonite clay is highly intercalated in ENR 50-Clay composite, which can be confirmed from its superior mechanical properties. The results indicated that sonication of bentonite clay in Et-OH improves the interlayer spacing of bentonite clay by partial intercalation of rubber matrix.
Enzyme Nanosheet-Based Electrochemical Aspartate Biosensor for Fish Point-of-Care Applications

Bacterial infections in marine fishes are linked to mass mortality issues; hence, rapid detection of an infection can contribute to achieving a faster diagnosis using point-of-care testing. There has been substantial interest in identifying diagnostic biomarkers that can be detected in major organs to predict bacterial infections. Aspartate was identified as an important biomarker for bacterial infection diagnosis in olive flounder (Paralichthys olivaceus) fish. To determine aspartate levels, an amperometric biosensor was designed based on bi-enzymes, namely, glutamate oxidase (GluOx) and aspartate transaminase (AST), which were physisorbed on copolymer reduced graphene oxide (P-rGO), referred to as enzyme nanosheets (GluOx-ASTENs). The GluOx-ASTENs were drop casted onto a Prussian blue electrodeposited screen-printed carbon electrode (PB/SPCE). The proposed biosensor was optimized by operating variables including the enzyme loading amount, coreactant (α-ketoglutarate) concentration, and pH. Under optimal conditions, the biosensor displayed the maximum current responses within 10 s at the low applied potential of −0.10 V vs. the internal Ag/AgCl reference. The biosensor exhibited a linear response from 1.0 to 2.0 mM of aspartate concentrations with a sensitivity of 0.8 µA mM−1 cm−2 and a lower detection limit of approximately 500 µM. Moreover, the biosensor possessed high reproducibility, good selectivity, and efficient storage stability.
From Space and Time to a Deeper Reality as a Possible Way to Solve Global Problems

To deal with global problems we suggest to consider complex systems not in space and time, but in a possible deeper reality, i.e., the hierarchical network of prime integer relations. Encoded by arithmetic through the self-organization processes the hierarchical network appears as the mathematical structure of one harmonious and interconnected whole. Remarkably, the holistic nature of the hierarchical network allows to formulate a single universal objective of a complex system defined in terms of the integration principle. We propose that by the realization of the integration principle the Earth system could be transformed to become an integrated part of a larger system with more capacity and energy to sustain life. Significantly, based on integers and controlled by arithmetic only the hierarchical network has a unique potential to provide an irreducible common ground fully trusted by different parties and helping to reveal a higher collective purpose.
Precision neuroimaging biomarkers for bipolar disorder

Abstract Bipolar disorder (BD) is a severe mental illness associated with alterations in brain organization. Neuroimaging studies have generated a large body of knowledge regarding brain morphological and functional abnormalities in BD. Current advances in the field have focussed on the need for more precise neuroimaging biomarkers. Here we present a selective overview of precision neuroimaging biomarkers for BD, focussing on personalized metrics and novel neuroimaging methods aiming to provide mechanistic insights into the brain alterations associated with BD. The evidence presented covers (a) machine learning techniques applied to neuroimaging data to differentiate patients with BD from healthy individuals or other clinical groups; (b) the ‘brain-age-gap-estimation (brainAGE), which is an individualized measure of brain health; (c) diffusional kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI) and Positron Emission Tomography (PET) techniques that open new opportunities to measure microstructural changes in neurite/synaptic integrity and function.
Applications of Molecular Dynamics Simulation in Protein Study

Molecular Dynamics (MD) Simulations is increasingly used as a powerful tool to study protein structure-related questions. Starting from the early simulation study on the photoisomerization in rhodopsin in 1976, MD Simulations has been used to study protein function, protein stability, protein–protein interaction, enzymatic reactions and drug–protein interactions, and membrane proteins. In this review, we provide a brief review for the history of MD Simulations application and the current status of MD Simulations applications in protein studies.