Miracle-dz/UniFAR-FTUs huggingface dataset:
Atmospheric N Deposition Significantly Enhanced Soil N2O Emission From Eastern China Forests

Nitrous oxide (N2O) is an influential greenhouse gas (GHG) and an unregulated ozone‐depleting substance. The extent to which N2O emissions from natural forest soils have been enhanced by high atmospheric nitrogen (N) deposition in China during past decades is unclear; however, assessing land‐related N2O emissions for 2060 national “carbon neutrality” goal is urgent. In this study, we proposed a “gray box” conceptual model and deduced a linear relationship between soil N2O emissions and N deposition on a large scale. On this basis, we created a “process‐augmented data‐driven” approach using which we combined experimental N addition data from 38 Chinese forests with N deposition observation data to estimate regional soil N2O emissions. We found that the N2O emission budget of eastern China forest soils averaged 0.24 ± 0.07 TgN yr−1 from 1996 to 2015; of this, ∼36% (0.087 TgN yr−1) was directly induced by N deposition. Soil N2O emission rates (RN2O) fluctuated slightly after 2006, and the RN2Os of different ecoregions were significantly different (p < 0.001). Soil factors and N‐deposition‐related factors dominated the spatial variation of RN2O. Our findings provide country‐specific and ecoregion‐specific emission factors for national GHG inventories in China. Our approach bridges the gap between site‐level experiments and demand for regional N2O emissions, and is applicable for estimating N2O emissions in other countries/regions. Meanwhile, more N addition experiments are needed to comprehensively understand N cycling processes and extend the predictive capability of the approach.
Experimental HER2-Targeted Therapy Using ADAPT6-ABD-mcDM1 in Mice Bearing SKOV3 Ovarian Cancer Xenografts: Efficacy and Selection of Companion Imaging Counterpart

Overexpression of the human epidermal growth factor receptor 2 (HER2) in breast and gastric cancer is exploited for targeted therapy using monoclonal antibodies and antibody-drug conjugates. Small engineered scaffold proteins, such as the albumin binding domain (ABD) derived affinity proteins (ADAPTs), are a promising new format of targeting probes for development of drug conjugates with well-defined structure and tunable pharmacokinetics. Radiolabeled ADAPT6 has shown excellent tumor-targeting properties in clinical trials. Recently, we developed a drug conjugate based on the HER2-targeting ADAPT6 fused to an albumin binding domain (ABD) for increased bioavailability and conjugated to DM1 for cytotoxic action, designated as ADAPT6-ABD-mcDM1. In this study, we investigated the therapeutic efficacy of this conjugate in mice bearing HER2-expressing SKOV3 ovarian cancer xenografts. A secondary aim was to evaluate several formats of imaging probes for visualization of HER2 expression in tumors. Administration of ADAPT6-ABD-mcDM1 provided a significant delay of tumor growth and increased the median survival of the mice, in comparison with both a non-targeting homologous construct (ADAPTNeg-ABD-mcDM1) and the vehicle-treated groups, without inducing toxicity to liver or kidneys. Moreover, the evaluation of imaging probes showed that small scaffold proteins, such as 99mTc(CO)3-ADAPT6 or the affibody molecule 99mTc-ZHER2:41071, are well suited as diagnostic companions for potential stratification of patients for ADAPT6-ABD-mcDM1–based therapy.
Reinventing R&D in an Open Innovation

Today, the idea that random collisions and interactions offer solutions and business opportunities is no longer acceptable. Instead, partnerships and alignments, both downstream and upstream, are paramount for cross-fertilization and synergy. To survive, and thrive, in today's world of global innovation, alliances based on compatible differences must be sought. Innovation Partnerships and the Sharing-is-Winning model represent a paradigm shift toward accelerating co-development of sustainable innovation, with alignment of the entire value chain with consumer-centric innovations being one of its main pillars. It includes 3 levels of typical joint development: universities, research institutes, and centers; start-ups and individual inventors; a select number of key strategic suppliers. Reinventing R&D in an open innovation ecosystem and increasing success rates in an increasingly competitive marketplace require implementing significant steps—both perceived and tangible. Specific recommendations are provided for 10 major identified topics: leadership, strategy, the consumer, the value chain, internal experts and championship, metrics, IP, culture, academia, and passion. The Sharing-is-Winning model extends the scope of open innovation to sustainable and enhanced processes of co-innovation.
Giant and Controllable Photoplasticity and Photoelasticity in Compound Semiconductors.

We show that the wide-band gap compound semiconductors ZnO, ZnS, and CdS feature large photoplastic and photoelastic effects that are mediated by point defects. We measure the mechanical properties of ceramics and single crystals using nanoindentation, and we find that elasticity and plasticity vary strongly with moderate illumination. For instance, the elastic stiffness of ZnO can increase by greater than 40% due to blue illumination of intensity 1.4 mW/cm^{2}. Above-band-gap illumination (e.g., uv light) has the strongest effect, and the relative effect of subband gap illumination varies between samples-a clear sign of defect-mediated processes. We show giant optomechanical effects can be tuned by materials processing, and that processing dependence can be understood within a framework of point defect equilibrium. The photoplastic effect can be understood by a long-established theory of charged dislocation motion. The photoelastic effect requires a new theoretical framework which we present using density functional theory to study the effect of point defect ionization on local lattice structure and elastic tensors. Our results update the longstanding but lesser-studied field of semiconductor optomechanics, and suggest interesting applications.
SOIL RESISTANCE AND MULTIVARIATE ANALYSIS AS AN AUXILIARY METHOD FOR SELECTING Calophyllum brasiliense PROGENIES

ABSTRACT Precision silviculture is being developed to manage and improve Calophyllum brasiliense, a tree species associated with wet and swampy soils. This study estimated genetic parameters for growth traits in response to soil resistance as an auxiliary tool for identifying and selecting progenies adapted to water-saturated soils. This was undertaken in a progeny test of C. brasiliense in which 1,200 seedlings grown from seeds collected from a natural population were planted in a randomized complete block design for single-tree plots. Genetic statistical analysis was conducted using the REML/BLUP method. Significant differences (p<0.01) in diameter at breast height were observed among the progenies. The coefficients of genetic variation and heritability at the individual and progeny levels were low for diameter at breast height and height, indicating low genetic control for these traits, while high positive and significant genetic and phenotypic correlations were detected between diameter at breast height and height. Theoretical genetic gains and multivariate statistical analysis indicated three groups of progenies with different degrees of tolerance and adaptability to flooded soils, which could be useful in future breeding programs for this species, although further analysis at advanced ages is still required. The mean heights of tolerant and sensitive progenies were 12 and 58%, respectively, lower than the theoretical values, indicating that constant soil flooding is harmful to this species.
Transcriptomic and physiological responses of contrasting maize genotypes to drought stress

Drought is a significant environmental stress factor that adversely affects maize productivity. However, many details regarding the molecular mechanisms of maize against drought are still unclear. In this study, leaf transcriptomics and physiological traits of two maize genotypes with differing drought resistance were analyzed. Transcriptome sequencing identified 8985 and 7305 differentially expressed genes (DEGs) in SD902 and SD609, respectively. Functional analysis suggested that numerous genes are highly involved in oxidative defense, protein modification, photosynthesis, phytohormone response, MAPK signaling, and transcription factors (TFs). Compared to SD902, SD609 had a higher expression of DEGs related to antioxidant enzymes, photosynthetic electron transport, heat shock proteins, and indole-3-acetic acid (IAA) signaling under drought conditions, which might contribute to its tolerance mechanisms to drought. Stress-induced TFs may play a crucial regulatory role in genotypic differences. Moreover, the physiological changes and gene expression abundance determined using quantitative reverse transcription polymerase chain reaction were consistent with the RNA sequencing data. The study results suggest that the higher drought tolerance of SD609 than SD902 can be attributed to stronger stress defense capabilities, IAA signal transduction, and more stable photosynthesis. Our findings provide new insights into the molecular mechanisms of maize against drought stress, and the candidate genes identified may be used in breeding drought-tolerant maize cultivars.
A Deep Reinforcement Learning-Based QoS Routing Protocol Exploiting Cross-Layer Design in Cognitive Radio Mobile Ad Hoc Networks

In this paper, we propose a novel deep reinforcement learning-based quality-of-service (QoS) routing protocol, namely DRQR, exploiting cross-layer design to establish efficient QoS (EQS) routes in cognitive radio mobile ad hoc networks. An EQS route is a route with minimum end-to-end (E2E) queuing delay subject to QoS constraints such as link stability, residual energy, number of hops and avoiding licensed channels of primary users. Particularly, we propose an NP-complete optimization problem which has a feasible solution as an EQS route. To tackle this problem, we design a new deep reinforcement learning model which supports the DRQR protocol to establish EQS routes in real time by offline training instead of online training like most of literature studies. Moreover, the DRQR protocol guarantees to have high system performance. A mathematical analysis of the E2E queuing delay with random waypoint mobility model also provides to verify simulation results. Numerical results show that the DRQR protocol outperforms state-of-the-art routing protocols in terms of routing delay, queuing delay, control overhead, PDR and energy consumption.
Crustal Strain Rates in the Western United States and Their Relationship with Earthquake Rates

We present a suite of strain rate models for the western United States based on geologic and geodetic data. The geologic data consist of Quaternary fault-slip rates and the geodetic data consists of a new compilation of Global Positioning System (GPS) velocities derived from continuous, semicontinuous, and campaign measurements. We remove postseismic deformation from the GPS time series in order for our geodetic strain rate model to best capture the interseismic strain accumulation rate. We present models based on either geologic or geodetic data, but also create a hybrid model. Although there are some differences between the models, the large-scale features are the same, with the noticeable exception for the Pacific Northwest where interseismic strain is naturally more distributed than the long-term strain release. We also present a map of earthquake rate densities based on mainshocks, and the result has similar spatial features similar to the strain rate models (at least in the southwestern United States). We perform a general correlation analysis between strain rate and seismicity rate (south of Cascadia) and find a change in linearity between seismicity and strain rates from slow to faster deforming areas with seismicity rates relatively lower for the latter. The extent of that change depends a bit on assumptions made on the declustering and completeness of the catalog, but the finding of a change in slope is robust across the different strain rate models. Linearity for all areas is only expected when Gutenberg–Richter parameters and parameters involved in the conversion from strain to moment rate are uniform across the study area. We discuss these qualifications, but find no single satisfactory explanation for our observation. Moreover, when considering a rather short time and space, theoretical considerations of sampling from a power-law distribution actually predict there to be a power law instead of a linear relationship, generally consistent with our observation.
Raspberry Pi-based Intelligent Cyber Defense Systems for SMEs and Smart-homes: An Exploratory Study

Ongoing ransomware attacks have forced business to think about security of their resources. Recently, small- to-medium enterprises (SMEs) and Smart-homes have become easy targets for attackers since they don’t have cyber defense mechanism in place other than simple firewall systems which are quite vulnerable. Cyber defense systems are costly and often not within the budget of SMEs or families which inspired to think about low cost yet highly efficient cyber defense solutions. Regular individuals and families who use internet for day to day use often end-up becoming a possible resource for using them as Trojan or bitcoin nodes. This research explores the prospects of implementing a Raspberry Pi (Raspberry Pi)-based intelligent cyber- defense system (iCDS) for SME networks and Smart-homes to filter malicious contents from incoming traffic and detect malware using artificial intelligence. Primarily, the work presented in this paper tries to evaluate the hardware capability of network interfaces (both internal, and attached) of Raspberry Pi for handle high volumes of incoming traffic. For this, we measure the network performance of the Raspberry Pi using the speed test software and try to explore the possibility of a light weight machine learning (ML) based malware detection. The results show that the built in Ethernet interface outperforms the built in WiFi and external attached USB to Ethernet Adapter in terms of latency, download and upload throughput. Also, a new DNA based ML approach was successfully able to produce over 19.5% better accuracy rates of over classifier trained with hash-sequence. The experiment results further emphasise on the importance of generating complex malware signatures with variety to face existing threats which has taken a new form due to increase in malware based attacks, particularly for ransomware. The complexity of the generated malware is based on generic yet strong encryption principles which produced good results which is quite encouraging at this stage.
Microcavity exciton polaritons at room temperature

Abstract. The quest for realizing novel fundamental physical effects and practical applications in ambient conditions has led to tremendous interest in microcavity exciton polaritons working in the strong coupling regime at room temperature. In the past few decades, a wide range of novel semiconductor systems supporting robust exciton polaritons have emerged, which has led to the realization of various fascinating phenomena and practical applications. This paper aims to review recent theoretical and experimental developments of exciton polaritons operating at room temperature, and includes a comprehensive theoretical background, descriptions of intriguing phenomena observed in various physical systems, as well as accounts of optoelectronic applications. Specifically, an in-depth review of physical systems achieving room temperature exciton polaritons will be presented, including the early development of ZnO and GaN microcavities and other emerging systems such as organics, halide perovskite semiconductors, carbon nanotubes, and transition metal dichalcogenides. Finally, a perspective of outlooking future developments will be elaborated.
Foliage applied boron along with boron-tolerant bacteria (Bacillus sp. MN54) ensures better nodulation, growth, grain yield and grains-B biofortification of chickpea

Abstract Boron (B) deficiency is the leading constraints in chickpea production in calcareous soils; albeit the range between B deficiency and toxicity is very narrow. Boron-tolerant bacteria (BTB) can optimize plant functions under B-deficient conditions by improving its uptake and can also tolerate B toxicity. This two-year pot study was conducted to optimize the best level of B as foliar application along with BTB (Bacillus sp. MN54) inoculation to improve nodulation, yield and grain-B concentration of chickpea. Two sets of pots, one with BTB inoculation and other without BTB were prepared. Foliar treatments of B were applied to plants at concentrations of 0.000, 0.023, 0.046, 0.069, and 0.092 M while plants sprayed with distilled water were taken as control. Boron application improved root and growth-related traits, nodulation, yield-related traits and grains-B concentration compared with no B and water spray controls. Among levels tested, foliar application of 0.046 M B solution was better in improving root system, nodulation, yield-related traits; while higher B levels resulted more grains-B concentration. Seed inoculation with BTB further augmented chickpea productivity compared to non-inoculation controls. Foliar application of B (0.046 M) coupled with BTB enhanced number of grains per plant (40%), nodules population (60%) and grain yield (43%) compared with control. Lower levels of B (≤0.069 M) seemed good to improve yield-related traits while its higher levels improved grains-B concentration. In crux, foliar application of 0.046 M B solution along with seed inoculation with BTB (Bacillus sp. MN54) seemed a pragmatic option to improve nodulation, yield and grains-B concentration of chickpea.
Bus bunching simulation based on the lattice Boltzmann model of traffic flow

Bus bunching is a typical phenomenon observed in daily public transit operations and that significantly reduces the reliability and attractiveness of transit service. Although various control strategies, such as vehicle holding, speed guidance, and signal priority, have been proposed to eliminate or alleviate bus bunching, the impact of road traffic flow on bus bunching has not been well studied. To bridge this gap, this work proposes a new mesoscopic simulation model by incorporating the lattice Boltzmann model to simulate bus bunching considering the impacts of road traffic flow. Simulation results show that by utilizing the new simulation model, different phase diagrams can be observed. Under different conditions of traffic flow-density evolution, i.e., no oscillation, single oscillation, global oscillation, and irregular oscillation, the resulting bus trajectories are significantly different. In addition, an investigation of a real-world bus line in Beijing with global positioning system (GPS)-based vehicle location data shows that some results of the model are qualitatively consistent with the actual characteristics of the bus route. It shows that the proposed new simulation model has great potential for enhancing our understanding of the impacts of road traffic flow on bus bunching.
Lattice QCD with Classical and Quantum Electrodynamics

We are doubtlessly familiar with some edition of Jackson's tome on electrodynamics, and Schwinger's calculation of the anomalous magnetic moment of the electron in QED. From the perspective of strong interactions, however, electromagnetic effects usually amount to negligible contributions. Despite this fact, electromagnetic probes have always been a fundamental source for our knowledge of QCD experimentally. Elastic scattering of electrons off nucleons provides us a window to their distributions of charge and magnetism. To account for the spectrum of QCD at the percent level, moreover, we need isospin breaking introduced from both quark masses and electric charges. This overview concerns some of the prospects and progress of studying electromagnetic effects in QCD. Our focus is divided between classical and quantum effects. In classical electromagnetic fields, the dynamical response of QCD to external conditions can be investigated. The vacuum and hadrons alike should be viewed as media which respond to external fields: both magnetize and polarize in magnetic fields, for example. At the quantum level, electromagnetism and QCD renormalize each other. In the era of high precision lattice computations, both strong and electromagnetic contributions must be accounted for to make predictions at the percent level.
Material extrusion additive manufacturing of dense pastes consisting of macroscopic particles

Additive manufacturing of dense pastes, those with greater than 50 vol% particles, via material extrusion direct ink write is a promising method to produce customized structures for high-performance materials, such as energetic materials and pharmaceuticals, as well as to enable the use of waste or other locally available particles. However, the high volume fraction and the large sizes of the particles for these applications lead to significant challenges in developing inks and processing methods to prepare quality parts. In this prospective, we analyze challenges in managing particle characteristics, stabilizing the suspensions, mixing the particles and binder, and 3D printing the pastes. Graphical abstract
The Celestial Reference Frame

The conceptual basis of reference frames defined by extragalactic objects is straightforwaxd: that the universe as a whole does not rotate so very distant objects cannot have an overall rotational motion. Experimentally, the global rotation of the universe is less than 10(exp -12) arcsecond/yr as inferred from the 3K microwave background radiation. At the distance of 10(exp 8) parsecs, even if an object were moving transversely at the speed of light, its angular velocity would be less than 0.6 x 10(exp -3) arcsecond/yr, while an object moving at a physically more reasonable speed comparable to the Sun would show a motion of 10(exp -6) arcsecond/yr, entirely undetectable by current technology. Since neither systematic universal motion nor random motion at such great distance is measurable, it is reasonable to construct a static celestial reference frame on the basis that such objects axe fixed in the sky.
Fingolimod Promotes Antibacterial Effect of Doripenem against Carbapenem-Resistant Escherichia coli

The aim of this study was to determine whether fingolimod could synergize the antibacterial activity of doripenem against carbapenem-resistant Escherichia coli (CREC) and its potential as an antibiotic adjuvant for doripenem. The E. coli used in this study had the blaKPC gene and became resistant to many classes of antibiotics, particularly carbapenems. The minimum inhibitory concentrations (MICs) of fingolimod and doripenem were determined. To investigate the synergistic action between fingolimod and doripenem, synergy checkerboard, growth curve, and time-kill analyses were performed. A motility test was also performed using a semi-solid medium to determine whether fingolimod could inhibit the motility of E. coli, one of its virulence mechanisms. The expression levels of carbapenemase-, motility-, and efflux pump-related genes suppressed by fingolimod were analyzed by quantitative polymerase chain reaction (qPCR). Our study demonstrated that the combination of fingolimod and doripenem inhibited carbapenemase, biological activity and other CREC virulence factors. This study findings suggest the potential of fingolimod as an adjuvant to prevent antibiotic resistance in CREC.